Screeningsinstrumenten
Uitgangsvraag
Wat is het meest betrouwbare en valide instrument om cognitieve achteruitgang te screenen bij mensen met een migratieachtergrond?
Aanbeveling
Overweeg de RUDAS in combinatie met de IQCODE te gebruiken om te screenen op cognitieve stoornissen bij patiënten met een migratieachtergrond.
Wees terughoudend met gebruik van de kloktekentest.
Indien er onduidelijkheid is over de resultaten van de anamnese in combinatie met cognitieve screeningstest RUDAS, overweeg dan de CCD als tweede stap screener in te zetten mits afgenomen door een getrainde testafnemer en onder supervisie van een neuropsycholoog.
Overwegingen
Voor- en nadelen van de interventie en de kwaliteit van het bewijs
Het doel van deze uitgangsvraag was om te achterhalen wat de diagnostische accuratesse is van verschillende cognitieve screeningsinstrumenten bij mensen met een migratieachtergrond en anderstaligen en/of laaggeschoolden. In totaal zijn zes studies gevonden die verschillende cognitieve screeningsinstrumenten waaronder de CCD, MMSE, RUDAS, IQCODE en vier soorten visuo-constructieve testen hebben vergeleken. In de geïncludeerde studies is er sprake van een hoog risico op bias, brede betrouwbaarheidsintervallen en kleine onderzoekspopulatie. De bewijskracht voor de cruciale uitkomstmaten sensitiviteit en negatief voorspellende waarden werd beoordeeld als (zeer) laag. De algehele bewijskracht voor de verschillende gerapporteerde cognitieve screeningsinstrumenten komt daarmee op zeer laag. Op basis van de huidige literatuur kan er geen conclusie worden getrokken over de accuratesse van cognitieve screeningsinstrumenten bij mensen met een migratieachtergrond en anderstaligen en/of laaggeschoolden.
De kwaliteit van bewijs voor de diagnostische testeigenschappen van de RUDAS, MMSE, IQCODE en CCD is laag tot zeer laag. Er was afwaardering in verband met risico op selectiebias. Daarnaast was er sprake van onnauwkeurigheid door kleine onderzoekspopulaties en grote betrouwbaarheidsintervallen. Een onderzoek vergeleek de testeigenschappen van RUDAS en MMSE, daartussen leek geen relevant verschil, al werd op de RUDAS minder invloed van opleiding gevonden dan op de MMSE (Goudsmit, 2018). Gevonden verschillen in de diagnostische accuratesse van de RUDAS in de onderzoeken van Goudsmit (2021) en Nielsen (2016) kunnen worden verklaard door een verschil in onderzoekspopulatie: in de populatie van Goudsmit was het aandeel laaggeletterden (nog) hoger. Het toevoegen van de IQCODE aan de RUDAS leek de diagnostische accuratesse significant te verbeteren (Nielsen, 2016; Goudsmit, 2021).
Een voordeel van de RUDAS is dat deze test minder gevoelig is voor het effect van opleiding waardoor hij met name in de groep patienten met een migratie achtergrond en een lage opleiding beter lijkt aan te sluiten dan de MMSE (Goudsmit, 2018; Storey, 2004). In twee onderzoeken spreken clinici daarom hun voorkeur uit voor de RUDAS boven de MMSE (Mateos-Alvarez, 2017; Pang, 2009). Desondanks zijn de sensitiviteit en specificiteit van de RUDAS vergelijkbaar met die van de MMSE (Goudsmit, 2018). Bij een onderzoek over de diagnostische accuratesse van de MMSE onder Marokkaanse en Turkse immigranten (Zwart, 2015) kon bij veel deelnemers de MMSE echter niet volledig worden afgenomen en werden de totaalscores geëxtrapoleerd, wat tot onjuiste interpretatie kan leiden.
Voor de RUDAS leidt een afkappunt van <22 tot een acceptabele combinatie van sensitiviteit (0.74) en specificiteit (0.74). Bij de MMSE leidt het standaard afkappunt van <24 tot een zeer lage sensitiviteit van 0.14 en een hoog aandeel fout-positieve testuitslagen. De MMSE heeft als nadeel dat er onduidelijkheid bestaat over de te kiezen afkapwaarde bij laaggeletterden of de keuze voor extrapoleren.
Een voordeel van de IQCODE is dat dit screeningsinstrument meetbare kenmerken heeft en tevens kan dienen als leidraad voor een heteroanamnese. Je hoeft niet enkel af te gaan op wat er in het gesprek verteld wordt maar ook op meetbare kenmerken. Het is bekend dat zelfrapportage (klachten) niet overeenstemt met objectieve cognitieve stoornissen.
Nadeel bij alle bovengenoemde instrumenten is dat er voor de afname een tolk nodig is.
Een mogelijk voordeel van de CCD is dat het gestandaardiseerd screeningsinstrument is, met beschikbare digitale geluidsinstructies in verschillende talen die aan een patiënt kunnen worden afgespeeld met minimale interventie van een tolk.
Het cluster meent op basis van de beschikbare literatuur en expert opinion dat de RUDAS adequaat aansluit bij de belevingswereld van de laaggeletterde patiënt of niet-westerse migrant en is minder gevoelig voor het niveau van scholing. Door de RUDAS te combineren met de IQCODE wordt de accuratesse vergroot. Indien er onduidelijkheid heerst over de resultaten, dan kan de CCD dienen als tweede stap screener.
De aanname bestaat dat het onderzoek van visuospatiële vaardigheden zoals de kloktekentest niet taalafhankelijk is en daarom geschikt is voor gebruik bij mensen met laaggeletterdheid of een migratieachtergrond. De kloktekentest wordt echter ongeschikt bevonden bij laaggeletterden met een migratieachtergrond (Maestri, 2022). In het algemeen leunen neuropsychologische testen zwaar op het opleidingsniveau (Nielsen, 2013). Daarom adviseert het cluster terughoudend te zijn met het gebruik van de kloktekentaak als cognitieve screener bij patiënten die laaggeletterd zijn.
Waarden en voorkeuren van patiënten (en evt. hun verzorgers)
Patiënten en mantelzorgers hechten waarschijnlijk waarde aan een accurate test. Onder migranten is er mogelijk door de negatieve connotatie van de ziekte dementie of door een gebrek aan kennis over de (eerste) symptomen van dementie de neiging om geheugenproblemen niet te onderkennen en/of in de familiesfeer op te vangen in plaats van aan te kaarten bij een hulpverlener. De drempel om een geheugenpoli te bezoeken voor ouderen met een migratieachtergrond is hoog. Dit kan bijdragen aan onderdiagnostiek (de diagnose wordt niet gesteld). Daarom is het van belang een cognitief screeningsinstrument te kiezen dat rekening houdt met variatie in opleidingsniveaus. Het kan moeilijk en confronterend zijn voor mensen oefeningen uit te voeren die vaardigheden onderzoeken die zij nooit geleerd hebben, zoals schrijven in de MMSE.
Kosten (middelenbeslag).
Het uitvoeren van de RUDAS is niet duur, maar kost wel tijd (gemiddeld 25 minuten in de eerstelijn, Vissenberg 2019 H&W) en moet tijdens een consult plaatsvinden. Er wordt aanbevolen dat de hulpverlener zich voor afname van de test verdiept in het instrument en/of een training volgt (digitale instructie Trimbos, 2023: Meetinstrumenten voor de ouderenpsychiatrie - Trimbos-instituut). Het uitvoeren van de MMSE duurt 10-20 minuten. De IQCODE kan in 10-15 minuten worden afgenomen bij de mantelzorger terwijl deze bijvoorbeeld wacht in de wachtkamer. Tijdens het consult wordt voor de meeste instrumenten de aanwezigheid van een formele tolk aanbevolen, wat extra kosten oplevert. De CCD is afneembaar met digitale geluidsinstructies in het Turks, Marokkaans-Berbers, Marokkaans-Arabisch, Sranan Tongo, Hindoestaans en Nederlands. Afnameduur is ongeveer 30 minuten.
Aanvaardbaarheid, haalbaarheid en implementatie.
Alle instrumenten zijn beschikbaar in het Nederlands en andere talen. De Nederlandse versie is gratis. Voor RUDAS en MMSE is een handleiding beschikbaar. De MMSE is ingeburgerd in de tweede lijnspraktijk, hoewel de MOCA inmiddels vaker gebruikt wordt dan de MMSE. De RUDAS is voor veel professionals een nieuw instrument. Onderzoek in de eerste lijn leert dat huisartsen en POH de RUDAS een prettig instrument vinden (Vissenberg, 2019). Om zich dit eigen te maken, zullen zij zich moeten verdiepen of een online trainingsvideo moeten kijken. Het feit dat voor afname van alle instrumenten wordt aangeraden een formele tolk in te schakelen bemoeilijkt implementatie. Een voordeel van de RUDAS is dat deze specifiek ontwikkeld werd voor mensen met verschillende achtergronden en volgens de onderzoekers beter aansluit bij diverse belevingswerelden. Dit aspect kan implementatie vergemakkelijken. Afname van de IQCODE is eenvoudig en een handleiding is beschikbaar (www.meetinstrumentenzorg.nl). De CCD wordt op verschillende geheugenpoliklinieken al ingezet. Deze kan worden afgenomen door getrainde zorgverleners . Interpretatie dient door een expert plaats te vinden (bijvoorbeeld door een neuropsycholoog).
Afhankelijk van het aantal migranten en laaggeletterden in het adherentiegebied van een hulpverlener of instelling zal er meer of minder ervaring opgedaan kunnen worden met het gebruik van een relatief nieuw instrument zoals de RUDAS wat de implementatiegraad ook weer zal beïnvloeden.
Er zijn inmiddels ook steeds meer mogelijkheden voor uitgebreider neuropsychologisch onderzoek bij deze doelgroep, waardoor adequate screening de laatste jaren nog belangrijker is geworden. Zo zijn er meerdere nieuwe neuropsychologische testen ontwikkeld in het kader van de TULIPA studie (Franzen, 2023).
Rationale van de aanbeveling: weging van argumenten voor en tegen de interventies
De testeigenschappen van de RUDAS lijken voor laaggeletterde patiënten (in ieder geval) even goed als die van de MMSE. De RUDAS lijkt volgens de onderzoekers beter aan te sluiten bij de belevingswereld van de laaggeletterde patiënt met een migratie achtergrond en is minder gevoelig voor het niveau van scholing. Hierdoor is de RUDAS mogelijk een alternatief in plaats van de MMSE als onderdeel van de dementiediagnostiek bij mensen met laaggeletterdheid, en hoogstwaarschijnlijk dus ook bij mensen met een migratieachtergrond die beperkt Nederlands spreken. Toevoegen van de IQCODE aan de RUDAS lijkt de accuratesse te vergroten. Onderstaande aanbevelingen gelden voor patiënten met een migratieachtergrond en anderstaligen en/of met een laag opleidingsniveau, bij screening op cognitieve achteruitgang.
Onderbouwing
Achtergrond
The number of elderly people in the Netherlands increased in recent years. This increase also results in a higher number of elderly people with a migration background. The prevalence of dementia among migrants is higher than among Dutch people without a migration background. To provide them with the necessary care, recognizing cognitive disorders is extremely important.
Migration background may create barriers in healthcare in various ways (e.g., education, language, culture). A significant proportion of (generally) first generation patients with a migration background are not fully proficient in Dutch. Illiteracy, a low-level of education and cultural aspects further complicate the process of conducting adequate screening to diagnose cognitive disorders.
Partly due to the migration background, certain screening instruments may not always be applicable. For example, translated versions (e.g., MMSE, MOCA) cannot be administered to all people. Currently various screening instruments are used in clinical practice, and it is unclear which instrument is the most beneficial.
Another question is the desirability of a professional interpreter during the appointment including cognitive screening and/or (auto) anamnesis. However, there is a lot of variation in clinical practice regarding the use of interpreters. In some disciplines the use of interpreters is reimbursed, but this is not standard. It is expected that a professional interpreter is essential for good information provision.
To summarize, the cluster considers it desirable to standardize the method for screening cognitive disorders in the memory clinic. First, the cluster evaluates the various screening instruments (sub-question 1) and then the cluster evaluates the use of an interpreter (sub-question 2). Please note that the evaluation of screening instruments for cognitive disorders in this module is based on diagnostic accuracy values as provided in the utilized literature.
Conclusies
1. RUDAS
1.1 Sensitivity, specificity and AUC
|
Very low GRADE |
The evidence is very uncertain about whether RUDAS is accurate in screening for cognitive disorders in people with a migration background in the hospital setting.
Source: Goudsmit, 2018; Goudsmit, 2021; Nielsen, 2016; Nielsen, 2018. |
1.2 Negative and positive predictive value
|
Very low GRADE |
The evidence is very uncertain regarding the NPV of RUDAS to screen for cognitive disorders in people with a migration background in the hospital setting.
Source: Goudsmit, 2021; Nielsen, 2016. |
|
Low GRADE |
The confidence in the reported PPV of RUDAS to screen for cognitive disorders in people with a migration background in the hospital setting is low.
Source: Goudsmit, 2021; Nielsen, 2016. |
2. MMSE
2.1 Sensitivity, specificity and AUC
|
Low GRADE |
The confidence in the reported sensitivity and specificity of MMSE to screen for cognitive disorders in people with a migration background in the hospital setting is low.
Source: Goudsmit, 2018. |
|
Very low GRADE |
The evidence is very uncertain regarding the AUC of MMSE to screen for cognitive disorders in people with a migration background in the hospital setting.
Source: Goudsmit, 2018. |
2.2 Negative and positive predictive value
|
no GRADE |
No evidence was found regarding NPV and PPV of the MMSE to screen for cognitive disorders in people with a migration background in the hospital setting.
Source: - |
3. IQCODE
3.1 Sensitivity, specificity and AUC
|
Very low GRADE |
The evidence is very uncertain about whether IQCODE is accurate in screening for cognitive disorders in people with a migration background in the hospital setting.
Source: Goudsmit, 2021; Nielsen, 2016. |
3.2 Negative and positive predictive value
|
Very low GRADE |
The evidence is very uncertain regarding the NPV of IQCODE to screen for cognitive disorders in people with a migration background in the hospital setting.
Source: Goudsmit, 2021; Nielsen, 2016. |
|
Very low GRADE |
The evidence is very uncertain regarding the PPV of IQCODE to screen for cognitive disorders in people with a migration background in the hospital setting.
Source: Goudsmit, 2021; Nielsen, 2016. |
4. CCD
4.1 Sensitivity, specificity and AUC
|
Very low GRADE |
The evidence is very uncertain about whether CCD is accurate in screening for cognitive disorders in people with a migration background in the hospital setting.
Source: Goudsmit, 2017. |
|
no GRADE |
No evidence was found regarding AUC of the CCD to screen for cognitive disorders in people with a migration background in the hospital setting.
Source: - |
4.2 Negative and positive predictive value
|
no GRADE |
No evidence was found regarding NPV and PPV of the CCD to screen for cognitive disorders in people with a migration background in the hospital setting.
Source: - |
5. Greek cross
5.1 Sensitivity, specificity and AUC
|
Very low GRADE |
The evidence is very uncertain about whether Greek cross test is accurate in screening for cognitive disorders in people with a migration background in the hospital setting.
Source: Staios, 2023. |
5.2 Negative and positive predictive value
|
no GRADE |
No evidence was found regarding NPV and PPV of the Greek cross test to screen for cognitive disorders in people with a migration background in the hospital setting.
Source: - |
6. Four-pointed star
6.1 Sensitivity, specificity and AUC
|
Very low GRADE |
The evidence is very uncertain about whether Four-pointed star test is accurate in screening for cognitive disorders in people with a migration background in the hospital setting.
Source: Staios, 2023. |
6.2 Negative and positive predictive value
|
no GRADE |
No evidence was found regarding NPV and PPV of the Four-pointed star test to screen for cognitive disorders in people with a migration background in the hospital setting.
Source: - |
7. Intersecting pentagons
7.1 Sensitivity, specificity and AUC
|
Very low GRADE |
The evidence is very uncertain about whether Intersecting pentagons test is accurate in screening for cognitive disorders in people with a migration background in the hospital setting.
Source: Staios, 2023. |
7.2 Negative and positive predictive value
|
no GRADE |
No evidence was found regarding NPV and PPV of the Intersecting pentagons test to screen for cognitive disorders in people with a migration background in the hospital setting.
Source: - |
8. Necker cube
8.1 Sensitivity, specificity and AUC
|
Very low GRADE |
The evidence is very uncertain about whether Necker cube test is accurate in screening for cognitive disorders in people with a migration background in the hospital setting.
Source: Staios, 2023. |
8.2 Negative and positive predictive value
|
no GRADE |
No evidence was found regarding NPV and PPV of the Necker cube test to screen for cognitive disorders in people with a migration background in the hospital setting.
Source: - |
9. RUDAS in combination with IQCODE
9.1 Sensitivity, specificity and AUC
|
Very low GRADE |
The evidence is very uncertain regarding the sensitivity and AUC of the RUDAS in combination with IQCODE to screen for cognitive disorders in people with a migration background in the hospital setting.
Source: Goudsmit, 2021; Nielsen, 2016. |
|
Low GRADE |
The confidence in the reported specificity of RUDAS in combination with IQCODE to screen for cognitive disorders in people with a migration background in the hospital setting is low.
Source: Goudsmit, 2021; Nielsen, 2016. |
9.2 Negative and positive predictive value
|
Low GRADE |
The confidence in the reported NPV of RUDAS in combination with IQCODE to screen for cognitive disorders in people with a migration background in the hospital setting is low.
Source: Goudsmit, 2021; Nielsen, 2016. |
|
Low GRADE |
The confidence in the reported PPV of RUDAS in combination with IQCODE to screen for cognitive disorders in people with a migration background in the hospital setting is low.
Source: Goudsmit, 2021; Nielsen, 2016. |
Samenvatting literatuur
Diagnostic accuracy
Description of studies
Goudsmit (2017) performed a study to examine the diagnostic accuracy of the Cross-cultural Dementia (CCD) screening test. A total of 54 participants aged ≥55 years being of Turkish, Moroccan, Surinamese or native Dutch descent with a diagnosis of probable dementia were included. The diagnosis of dementia was made according to the Dutch consensus guidelines by a geriatrician or neurologist. Additionally, 54 age-, education-, gender- and ethnicity-matched healthy controls were included. After the routine diagnostic procedures, the CCD was administered by an experienced neuropsychologist or a trained examiner. The CCD consists of three subtests: 1) Objects test (memory), 2) Sun-Moon test (mental speed and executive functioning), and 3) Dots test (mental speed and executive functioning). The discriminative capacity of the CCD was evaluated with receiver operating characteristics (ROC) curves. Cut-off scores were determined based on the Youden’s index: (sensitivity – specificity) – 1. Relevant outcomes were sensitivity and specificity. Characteristics are reported in the evidence tables.
Goudsmit (2018) performed a cross-sectional study to examine the diagnostic accuracy of the Rowland Universal Dementia Assessment Scale (RUDAS) and the Mini Mental State Examination (MMSE). A total of 144 ‘’non-Western’’ patients aged ≥55 years referred to three geriatric outpatient clinics for somatic and/or cognitive evaluation were included. Geriatricians or neurologists provided a research diagnosis, which served as the reference in this study, subdividing patients into 42 with intact cognition, 44 with mild cognitive impairment (MCI), and 58 with dementia. MCI was diagnosed according to the core clinical criteria provided by the National Institute on Aging-Alzheimer’s Association (NIA-AA) workgroup. Dementia was diagnosed according to DSM-IV-TR criteria. Patients completed the cognitive tests in the following order: 1) MMSE, 2) RUDAS, 3) other cognitive tests. All cognitive tests were administered by trained specialized nurses assisted by a professional interpreter. Patients who reported that they could not read and write were considered illiterate. Education level was scored with the International Standard Classification of Education 2011 of UNESCO and in number of years. Diagnostic test accuracy was assessed with ROC curve analyses for group status (intact cognition/MCI/dementia). Cut-off scores were determined based on the Youden’s index. Relevant outcomes were sensitivity, specificity and AUC. Characteristics are reported in the evidence tables.
Goudsmit (2021) performed a cross-sectional study to compare the diagnostic accuracy of the Informant Questionnaire for Cognitive Decline in the Elderly (IQCODE) with that of the RUDAS. A total of 109 ‘’non-Western’’ immigrant geriatric outpatients aged ≥55 years and 20 community controls were included. Geriatricians provided a research diagnosis, subdividing patients into 27 with intact cognition, 33 with MCI, and 49 with dementia. MCI diagnosis was made according to criteria outlined by the NIA-AA workgroup, and dementia diagnosis was according to DSM-IV-TR criteria. The cognitive tests were administered by trained specialized nurses assisted by a professional interpreter. Patients who reported that they could not read and write were considered illiterate. Education level was scored with the International Standard Classification of Education 2011 of UNESCO and in number of years. Diagnostic accuracy was assessed with ROC curve analyses for group status for both IQCODE, RUDAS and combined scores. To determine cut-off points, Youden index was calculated. Relevant outcomes were sensitivity, specificity, AUC, NPV and PPV. Characteristics are reported in the evidence tables.
Nielsen (2016) conducted a case-control study to investigate whether combining the IQCODE and Arabic RUDAS could improve diagnostic accuracy when screening for dementia in an illiterate Arabic-speaking population. Participants were enrolled from the communities, social organizations for the elderly, community-based primary care clinics and hospital-based geriatric and neurological clinics. Participants were included if 1) they were aged ≥ 65 years, 2) they had normal cognition (controls) or mild-to-moderate dementia (cases), 3) they had a knowledgeable informant who could give an independent assessment of the participant’s health and cognitive status. A total of 225 participants were included, of whom 90 had dementia (48 mild dementia, and 42 moderate dementia) and 135 had normal cognition. Dementia and MCI were diagnosed according to the DSM-IV and NIA-AA criteria. Diagnostic accuracy was evaluated using ROC curve analyses. Areas under the curve (AUC) were used to compare the diagnostic accuracy of the RUDAS, IQCODE and combined measures in differentiating between people with dementia and cognitively intact controls. Optimal cut-off values were <23/30 for the RUDAS and >2.34/5 for IQCODE based on previous validation studies in the same population. Relevant outcomes were sensitivity, specificity, AUC, NPV and PPV. Characteristics are reported in the evidence tables.
Nielsen (2018) performed a prospective international cross-sectional multicenter study to investigate the diagnostic accuracy of the RUDAS in a multicultural population. Participants with a “non-Western” immigrant background as well as from native-born populations were enrolled from multidisciplinary European memory clinics. People with a diagnosis of dementia were consecutively included. Dementia was diagnosed according to the DSM-IV—TR diagnostic criteria, and diagnostic research criteria for dementia. Cognitively intact volunteers aged between 50-90 years were recruited from the community. A total of 441 participants were included, of whom 80 had dementia and 361 had intact cognition. Diagnostic accuracy was evaluated using ROC curve analyses. In order to calculate the diagnostic accuracy measures of the RUDAS reflecting various clinical contexts, different cut-off scores were applied. Optimal cut-off values were calculated using Youden’s index. Subanalysis based on immigrant status was performed and reported. Relevant outcome was AUC. Characteristics are further summarized in the evidence tables.
Staios (2023) performed a case-control study to compare the diagnostic accuracy of visuoconstructional tests in a sample of older Greek Australian immigrants. Healthy participants were recruited via several Greek social clubs (controls) and participants with Alzheimer’s Disease (AD) via specialist outpatient clinics (cases) throughout the Melbourne metropolitan area. Participants were included if 1) they were aged 70-85 years, 2) they were literate, immigrants from Greece, and 3) had to have Greek as their dominant language. In total, 110 participants were included of whom 90 were healthy and 20 had a diagnosis of AD. Dementia diagnosis was based on the diagnostic criteria as described by the DSM-5 and diagnostic research criteria for AD. Participants completed four visuoconstructional drawing tests in the following order: 1) Greek cross, 2) four-pointed star, 3) intersecting pentagons, and 4) the Necker cube. Tests were administered by two registered bilingual Greek-English speaking clinical neuropsychologists. ROC curve analyses were used to examine the sensitivity and specificity of each test, using the AD group as the reference standard. Diagnostic accuracy was estimated by the AUC. Cut-off values were based on recommended scores reported in the literature. Relevant outcomes were sensitivity, specificity and AUC. Characteristics are summarized in the evidence tables.
Torkpoor (2022) performed a study to compare the diagnostic accuracy of the Swedish version of the RUDAS (RUDAS-S) with the Swedish version of the MMSE (MMSE-SR). A total of 123 native and nonnative Swedish outpatients from four memory clinics in Southern Sweden were included. 28% of participants were nonnative Swedes. Physicians provided a clinical diagnosis based on the International Classification of Diseases (ICD-10) diagnostic system, subdividing patients into 63 patients with dementia, 13 with subjective cognitive impairment, 35 with MCI and 16 with other conditions. ROC curve analyses were used to compare the diagnostic accuracy of the RUDAS-S and MMSE-SR. An AUC of 0.9-1.0 was considered excellent, 0.8-0.9 good, 0.7-0.8 fair, 0.6-0.7 poor, and 0.5-0.6 failed. A subanalysis without native Swedish patients was performed and reported. Relevant outcome was AUC. Characteristics are further summarized in the evidence tables.
Results
Diagnostic accuracy is assessed below for the following cognitive tests:
1. RUDAS (Goudsmit, 2018; Goudsmit, 2021; Nielsen, 2016; Nielsen, 2018; Torkpoor, 2022)
2. MMSE (Goudsmit, 2018; Torkpoor, 2022)
3. IQCODE (Goudsmit, 2021; Nielsen, 2016)
4. CCD (Goudsmit, 2017)
5. Greek cross (Staios, 2023)
6. Four-pointed star (Staios, 2023)
7. Intersecting pentagons (Staios, 2023)
8. Necker cube (Staios, 2023)
9. RUDAS in combination with IQCODE (Goudsmit, 2021; Nielsen, 2016)
Due to heterogeneity in the patient population and different versions of the instruments studies, and the variety in cut-off values, results could not be pooled.
Regarding the cut-off values, it is important to realize that the choice for a cut-off point depends on the setting and the purpose of the test. In this module, optimal cut-off values based on literature and calculations performed by the authors are reported.
1. RUDAS
1.1 Sensitivity, specificity and AUC
Goudsmit (2018) assessed the diagnostic accuracy of the RUDAS for discriminating intact cognition from MCI and dementia in 144 ‘’non-Western’’ elderly patients (42 with intact cognition, 44 with MCI, and 58 with dementia). The authors reported an AUC of 0.81 (95%CI 0.74 to 0.88), which was considered clinically relevant. Sensitivity and specificity values are presented in Table 1. Using <22 (based on their own calculations using Youden’s index) and <23 (based on Storey, 2004) as (advised) cut-off scores, sensitivity and specificity were both not clinically relevant.
Goudsmit (2021) assessed the diagnostic accuracy of the RUDAS for discriminating intact cognition from MCI and dementia in 109 ‘’non-Western’’ older immigrants (27 with intact cognition, 33 with MCI, and 49 with dementia). An AUC of 0.82 (95%CI 0.74 to 0.90) was reported, which was considered clinically relevant. Sensitivity and specificity are presented in Table 1. Sensitivity with cut-off point <23 (based on Storey, 2004) was considered clinically relevant, whereas specificity was not.
Nielsen (2016) assessed the diagnostic accuracy of the RUDAS-A for discriminating normal cognition from dementia in 225 illiterate Arabic-speaking participants (135 with normal cognition, 48 with mild dementia, and 42 with moderate dementia). The authors reported an AUC of 0.92, which was considered clinically relevant. Sensitivity and specificity are presented in Table 1. Using <23 as cut-off score (based on Chaaya, 2016), sensitivity and specificity were both considered clinically relevant.
Nielsen (2018) assessed the diagnostic accuracy of the RUDAS for discriminating intact cognition from dementia in 164 “non-Western” immigrants (48 with dementia and 116 with intact cognition). The authors reported an AUC of 0.95 (95%CI 0.92 to 0.99), which was considered clinically relevant. No sensitivity and specificity were reported separately for the immigrant participants.
Torkpoor (2022) assessed the accuracy of the RUDAS-S for detecting dementia in 34 nonnative Swedish participants (20 with dementia and 14 without dementia). The authors reported an AUC of 0.86 (95%CI 0.72 to 0.99), which was considered clinically relevant. No sensitivity and specificity were reported separately for the nonnative participants.
1.2 Negative and positive predictive value
Goudsmit (2021) reported NPV and PPV values, which are displayed in Table 1. PPV values with cut-off point <22 (based on their own calculations using Youden’s index) and <23 (based on Storey, 2004) were considered clinically relevant.
Nielsen (2016) reported NPV and PPV values, which are shown in Table 1. NPV value with cut-off point <23 (based on Chaaya, 2016) was considered clinically relevant.
Goudsmit (2018) and Torkpoor (2022) did not report on the outcome measures NPV and PPV.
Table 1: Diagnostic accuracy of the RUDAS.
|
Study |
N |
Sensitivity (95% CI) |
Specificity (95% CI) |
PPV (95%CI) |
NPV (95%CI) |
Cut-off point |
|
Goudsmit, 2018 |
144 |
0.74 |
0.74 |
- |
- |
<22a |
|
0.75 |
0.62 |
- |
- |
<23b |
||
|
Goudsmit, 2021 |
109 |
0.78 (0.68-0.87) |
0.70 (0.50-0.86) |
0.89 (0.81-0.93) |
0.53 (0.41-0.65) |
<22a |
|
0.80 (0.69-0.88) |
0.59 (0.39-0.78) |
0.85 (0.78-0.90) |
0.50 (0.37-0.63) |
<23b |
||
|
Nielsen, 2016 |
225 |
0.82 (0.72-0.89) |
0.84 (0.77-0.90) |
0.78 (0.68-0.93) |
0.88 (0.80-0.93) |
<23c |
Values displayed in bold were considered clinically relevant. Abbreviations: CI = confidence interval; NPV = negative predictive value; PPV = positive predictive value.
a Best cut-off score in this study based on Youden’s index.
b Regular cut-off score for RUDAS (Storey, 2004).
c Optimal cut-off score based on validation study in the same population (Chaaya, 2016).
2. MMSE
2.1 Sensitivity, specificity and AUC
Goudsmit (2018) assessed the diagnostic accuracy of the MMSE for discriminating intact cognition from MCI and dementia in 144 ‘’non-Western’’ elderly patients (42 with intact cognition, 44 with MCI, and 58 with dementia). The authors reported an AUC of 0.77 (95%CI 0.69 to 0.85), which was considered not clinically relevant. Sensitivity and specificity are presented in Table 2. Sensitivity with cut-off score <24 (based on Folstein, 1975) and specificity with cut-off score <14 (based on their own calculations using Youden’s index) were considered clinically relevant.
Torkpoor (2022) assessed the accuracy of the MMSE-SR for detecting dementia in 34 nonnative Swedish participants (20 with dementia and 14 without dementia). The authors reported an AUC of 0.84 (95%CI 0.71 to 0.97), which was considered clinically relevant. No sensitivity and specificity were reported.
2.2 Negative and positive predictive value
Goudsmit (2018) and Torkpoor (2022) did not report on the outcome measures NPV and PPV.
Table 2: Diagnostic accuracy of the MMSE.
|
Study |
N |
Sensitivity (95% CI) |
Specificity (95% CI) |
Cut-off point |
|
Goudsmit, 2018 |
144 |
0.60 |
0.90 |
<14a |
|
0.94 |
0.17 |
<24b |
Values displayed in bold were considered clinically relevant. Abbreviations: CI = confidence interval.
a Best cut-off score in this study based on Youden’s index.
b Regular cut-off score for MMSE (Folstein, 1975).
3. IQCODE
3.1 Sensitivity, specificity and AUC
Goudsmit (2021) assessed the diagnostic accuracy of the IQCODE for discriminating intact cognition from MCI and dementia in 109 ‘’non-Western’’ geriatric immigrants (27 with intact cognition, 33 with MCI, and 49 with dementia). The authors reported an AUC of 0.86 (95%CI 0.77 to 0.94), which was considered clinically relevant. Sensitivity and specificity are presented in Table 3. Specificity with cut-off point >3.8 (based on their own calculations using Youden’s index) was considered clinically relevant, whereas sensitivity was not.
Nielsen (2016) assessed the diagnostic accuracy of the IQCODE for discriminating normal cognition from dementia in 225 illiterate Arabic-speaking participants (135 with normal cognition, 48 with mild dementia, and 42 with moderate dementia). An AUC of 0.97 was reported, which was considered clinically relevant. Sensitivity and specificity are presented in Table 3. Using >3.34 (based on Phung, 2015) as cut-off score, sensitivity and specificity were both clinically relevant.
3.2 Negative and positive predictive value
Goudsmit (2021) reported NPV and PPV values, which are displayed in Table 3. PPV value with cut-off point >3.8 (based on their own calculations using Youden’s index) was considered clinically relevant, whereas NPV value was not.
Nielsen (2016) reported NPV and PPV values, which are shown in Table 3. Using >3.34 (based on Phung, 2015) cut-off score, PPV and NPV values were both considered clinically relevant.
Table 3: Diagnostic accuracy of the IQCODE.
|
Study |
N |
Sensitivity (95% CI) |
Specificity (95% CI) |
PPV (95%CI) |
NPV (95%CI) |
Cut-off point |
|
Goudsmit, 2021 |
109 |
0.77 (0.66-0.85) |
0.81 (0.62-0.94) |
0.93 (0.85-0.97) |
0.54 (0.43-0.64) |
>3.8a |
|
Nielsen, 2016 |
225 |
0.92 (0.84-0.96) |
0.96 (0.90-0.98) |
0.93 (0.85-0.97) |
0.95 (0.89-0.98) |
>3.34b |
Values displayed in bold were considered clinically relevant. Abbreviations: CI = confidence interval; NPV = negative predictive value; PPV = positive predictive value.
a Best cut-off score in this study based on Youden’s index.
b Optimal cut-off score based on validation study in the same population (Phung, 2015).
4. CCD
4.1 Sensitivity, specificity and AUC
Goudsmit (2017) assessed the diagnostic accuracy of the CCD for discriminating between patients with dementia and cognitively healthy controls in 108 participants aged ≥55 years being of Turkish, Moroccan, Surinamese, or Dutch descent (54 with probable dementia and 54 with normal cognition). No AUC was reported. Sensitivity and specificity for all subtests of the CCD are presented in Table 4. All reported sensitivity and specificity values were considered clinically relevant, except the sensitivity for part A of the dots test with cut-off value >115 (based on their own calculations using Youden’s index). In addition, the authors reported a sensitivity of 85% and specificity of 89% for the combination of subtests, which were considered clinically relevant.
Table 4: Diagnostic accuracy of the CCD
|
Study |
N |
Subtest |
Part |
Sensitivity |
Specificity |
Cut-off point |
|
Goudsmit, 2017 |
108 |
Objects test |
A: Immediate recognition score |
0.85 |
0.89 |
<118a |
|
B: Delayed recognition score |
0.92 |
0.91 |
<109a |
|||
|
Sun-Moon test |
A: Corrected time score (s) |
0.81 |
0.85 |
>39a |
||
|
B: Corrected time score (s) |
0.85 |
0.89 |
>71a |
|||
|
Dots test |
A: Time (s) |
0.67 |
0.98 |
>115a |
||
|
B: Time (s) |
0.85 |
0.83 |
>216a |
Values displayed in bold were considered clinically relevant. NA = not applicable.
a Best cut-off score in this study based on Youden’s index.
4.2 Negative and positive predictive value
Goudsmit (2017) did not report on the outcome measures NPV and PPV.
5. Greek cross
5.1 Sensitivity, specificity and AUC
Staios (2023) assessed the diagnostic accuracy of the Greek cross visuoconstructional test for discriminating normal cognition from dementia in 110 older Greek Australian immigrants (90 with normal cognition and 20 with dementia). The authors reported an AUC of 0.80 (95%CI 0.69 to 0.91), which was considered clinically relevant. Sensitivity and specificity are presented in Table 5. Specificity with a cut-off point of 1 (based on Strub & Black, 1988) was considered clinically relevant, whereas sensitivity was not.
Table 5: Diagnostic accuracy of the Greek cross visuoconstructional test.
|
Study |
N |
Sensitivity (95% CI) |
Specificity (95% CI) |
Cut-off point |
|
Staios, 2023 |
110 |
0.40 |
0.96 |
1a |
Values displayed in bold were considered clinically relevant. Abbreviations: CI = confidence interval.
a Established cut-off score based on literature (Strub & Black, 1988).
5.2 Negative and positive predictive value
Staios (2023) did not report on the outcome measures NPV and PPV.
6. Four-pointed star
6.1 Sensitivity, specificity and AUC
Staios (2023) assessed the diagnostic accuracy of the Four-pointed star visuoconstructional test for discriminating normal cognition from dementia in 110 older Greek Australian immigrants (90 with normal cognition and 20 with dementia). The authors reported an AUC of 0.68 (95%CI 0.57 to 0.80), which was considered not clinically relevant. Sensitivity and specificity are presented in Table 6, which were both considered not clinically relevant with cut-off point 1 (based on Strub & Black, 1988).
Table 6: Diagnostic accuracy of the Four-pointed star visuoconstructional test.
|
Study |
N |
Sensitivity (95% CI) |
Specificity (95% CI) |
Cut-off point |
|
Staios, 2023 |
110 |
0.55 |
0.73 |
1a |
Values displayed in bold were considered clinically relevant. Abbreviations: CI = confidence interval.
a Established cut-off score based on literature (Strub & Black, 1988).
6.2 Negative and positive predictive value
Staios (2023) did not report on the outcome measures NPV and PPV.
7. Intersecting pentagons
7.1 Sensitivity, specificity and AUC
Staios (2023) assessed the diagnostic accuracy of the Intersecting pentagons visuoconstructional test for discriminating normal cognition from dementia in 110 older Greek Australian immigrants (90 with normal cognition and 20 with dementia). The authors reported an AUC of 0.72 (95%CI 0.61 to 0.83), which was considered not clinically relevant. Sensitivity and specificity are presented in Table 7. Sensitivity with a cut-off point of 4 (based on Bourke, 1995) was considered clinically relevant, whereas specificity was not.
Table 7: Diagnostic accuracy of the Intersecting pentagons visuoconstructional test.
|
Study |
N |
Sensitivity (95% CI) |
Specificity (95% CI) |
Cut-off point |
|
Staios, 2023 |
110 |
0.95 |
0.31 |
4a |
Values displayed in bold were considered clinically relevant. Abbreviations: CI = confidence interval.
a Established cut-off score based on literature (Bourke, 1995).
7.2 Negative and positive predictive value
Staios (2023) did not report on the outcome measures NPV and PPV.
8. Necker cube
8.1 Sensitivity, specificity and AUC
Staios (2023) assessed the diagnostic accuracy of the Necker cube visuoconstructional test for discriminating normal cognition from dementia in 110 older Greek Australian immigrants (90 with normal cognition and 20 with dementia). The authors reported an AUC of 0.55 (95%CI 0.48 to 0.67), which was considered not clinically relevant. Sensitivity and specificity are presented in Table 8, which were both considered not clinically relevant at cut-off point 2 (based on Shimada, 2006).
Table 8: Diagnostic accuracy of the Necker cube visuoconstructional test.
|
Study |
N |
Sensitivity (95% CI) |
Specificity (95% CI) |
Cut-off point |
|
Staios, 2023 |
110 |
0.75 |
0.36 |
2a |
Values displayed in bold were considered clinically relevant. Abbreviations: CI = confidence interval.
a Established cut-off score based on literature (Shimada, 2006).
8.2 Negative and positive predictive value
Staios (2023) did not report on the outcome measures NPV and PPV.
9. RUDAS in combination with IQCODE
9.1 Sensitivity, specificity and AUC
Goudsmit (2021) assessed the diagnostic accuracy of the RUDAS and IQCODE combined for discriminating intact cognition from MCI and dementia in 109 ‘’non-Western’’ geriatric immigrants (27 with intact cognition, 33 with MCI, and 49 with dementia). An AUC of 0.91 (95%CI 0.85 to 0.97) was reported, which was considered clinically relevant. No sensitivity and specificity were reported.
Nielsen (2016) assessed the diagnostic accuracy of the RUDAS-A and IQCODE combined for discriminating normal cognition from dementia in 225 illiterate Arabic-speaking participants (135 with normal cognition, 48 with mild dementia, and 42 with moderate dementia). The authors reported an AUC of 0.86, which was considered clinically relevant. Sensitivity and specificity are presented in Table 9. Specificity was considered clinically relevant, whereas sensitivity was not.
9.2 Negative and positive predictive value
Nielsen (2016) reported NPV and PPV values, which are shown in Table 9. Using <23 (based on Chaaya, 2016) and >3.34 (based on Phung, 2015) as cut-off scores, PPV and NPV values were both considered clinically relevant.
Goudsmit (2021) did not report on the outcome measures NPV and PPV.
Table 9: Diagnostic accuracy of the RUDAS in combination with IQCODE.
|
Study |
N |
Sensitivity (95% CI) |
Specificity (95% CI) |
PPV (95%CI) |
NPV (95%CI) |
Cut-off point |
|
Nielsen, 2016 |
225 |
0.76 (0.65-0.84) |
0.97 (0.92-0.99) |
0.94 (0.86-0.98) |
0.86 (0.79-0.91) |
<23 for RUDASa >3.34 for IQCODEb |
Values displayed in bold were considered clinically relevant. Abbreviations: CI = confidence interval; NPV = negative predictive value; PPV = positive predictive value.
a Optimal cut-off score based on validation study in the same population (Chaaya, 2016).
b Optimal cut-off score based on validation study in the same population (Phung, 2015).
Level of evidence of the literature
1. RUDAS
1.1 Sensitivity, specificity and AUC
The level of evidence regarding the outcome measure sensitivity was downgraded by three levels to very low because of study limitations including issues with patient selection and index test and the case-control design of one study (risk of bias: -2), and because different conclusions can be drawn from the upper and lower limits of the confidence interval (imprecision: -1).
The level of evidence regarding the outcome measure specificity was downgraded by three levels to very low because of study limitations including issues with patient selection and index test and the case-control design of one study (risk of bias: -2), and because different conclusions can be drawn from the upper and lower limits of the confidence interval (imprecision: -1).
The level of evidence regarding the outcome measure AUC was downgraded by three levels to very low because of study limitations including issues with patient selection, index test, and reference test and the case-control design of one study (risk of bias: -2), and because of the low number of included patients (imprecision: -1).
1.2 Negative and positive predictive value
The level of evidence regarding the outcome measure NPV was downgraded by three levels to very low because of study limitations including issues with patient selection and index test and case-control design of one study (risk of bias: -2), and conflicting results (inconsistency: -1).
The level of evidence regarding the outcome measure PPV was downgraded by two levels to low because of study limitations including issues with patient selection and index test and case-control design of one study (risk of bias: -2).
2. MMSE
2.1 Sensitivity, specificity and AUC
The level of evidence regarding the outcome measure sensitivity was downgraded by two levels to low because of the low number of included patients and no reporting of confidence intervals (imprecision: -2).
The level of evidence regarding the outcome measure specificity was downgraded by two levels to low because of the low number of included patients and no reporting of confidence intervals (imprecision: -2).
The level of evidence regarding the outcome measure AUC was downgraded by three levels to very low because of study limitations including issues with the index test and reference standard (risk of bias: -1), and the low number of included patients and no reporting of confidence intervals (imprecision: -2).
2.2 Negative and positive predictive value
The level of evidence regarding the outcome measures NPV and PPV was not assessed since none of the included studies reported on these outcomes.
3. IQCODE
3.1 Sensitivity, specificity and AUC
The level of evidence regarding the outcome measure sensitivity was downgraded by three levels to very low because of study limitations including issues with patient selection and index test and case-control design of one study (risk of bias: -2), and the low number of included patients (imprecision: -1).
The level of evidence regarding the outcome measure specificity was downgraded by three levels to very low because of study limitations including issues with patient selection and index test and case-control design of one study (risk of bias: -2), and the low number of included patients (imprecision: -1).
The level of evidence regarding the outcome measure AUC was downgraded by three levels to very low because of study limitations including issues with patient selection and index test and case-control design of one study (risk of bias: -2), and the low number of included patients (imprecision: -1).
3.2 Negative and positive predictive value
The level of evidence regarding the outcome measure NPV was downgraded by three levels to very low because of study limitations including issues with patient selection and index test and case-control design of one study (risk of bias: -2), and the low number of included patients (imprecision: -1).
The level of evidence regarding the outcome measure PPV was downgraded by three levels to very low because of study limitations including issues with patient selection and index test and case-control design of one study (risk of bias: -2), and the low number of included patients (imprecision: -1).
4. CCD
4.1 Sensitivity, specificity and AUC
The level of evidence regarding the outcome measure sensitivity was downgraded by three levels to very low because of study limitations including the case-control design and issues with the index test (risk of bias: -1), and because no confidence intervals were reported (imprecision: -1).
The level of evidence regarding the outcome measure specificity was downgraded by three levels to very low because of study limitations including the case-control design and issues with the index test (risk of bias: -1), and because no confidence intervals were reported (imprecision: -1).
The level of evidence regarding the outcome measure AUC was not assessed since none of the included studies reported on this outcome.
4.2 Negative and positive predictive value
The level of evidence regarding the outcome measures NPV and PPV was not assessed since none of the included studies reported on these outcomes.
5. Greek cross
5.1 Sensitivity, specificity and AUC
The level of evidence regarding the outcome measure sensitivity was downgraded by three levels to very low because of study limitations including issues with patient selection, index test and reference and the case-control design (risk of bias: -2), and the low number of included patients (imprecision: -1).
The level of evidence regarding the outcome measure specificity was downgraded by three levels to very low because of study limitations including issues with patient selection, index test and reference and the case-control design (risk of bias: -2), and the low number of included patients (imprecision: -1).
The level of evidence regarding the outcome measure AUC downgraded by three levels to very low because of study limitations including issues with patient selection, index test and reference and the case-control design (risk of bias: -2), and the low number of included patients (imprecision: -1).
5.2 Negative and positive predictive value
The level of evidence regarding the outcome measures NPV and PPV was not assessed since none of the included studies reported on these outcomes.
6. Four-pointed star
6.1 Sensitivity, specificity and AUC
The level of evidence regarding the outcome measure sensitivity was downgraded by three levels to very low because of study limitations including issues with patient selection, index test and reference and the case-control design (risk of bias: -2), and the low number of included patients (imprecision: -1).
The level of evidence regarding the outcome measure specificity was downgraded by three levels to very low because of study limitations including issues with patient selection, index test and reference and the case-control design (risk of bias: -2), and the low number of included patients (imprecision: -1).
The level of evidence regarding the outcome measure AUC was downgraded by three levels to very low because of study limitations including issues with patient selection, index test and reference and the case-control design (risk of bias: -2), and the low number of included patients (imprecision: -1).
6.2 Negative and positive predictive value
The level of evidence regarding the outcome measures NPV and PPV was not assessed since none of the included studies reported on these outcomes.
7. Intersecting pentagons
7.1 Sensitivity, specificity and AUC
The level of evidence regarding the outcome measure sensitivity was downgraded by three levels to very low because of study limitations including issues with patient selection, index test and reference and the case-control design (risk of bias: -2), and the low number of included patients (imprecision: -1).
The level of evidence regarding the outcome measure specificity was downgraded by three levels to very low because of study limitations including issues with patient selection, index test and reference and the case-control design (risk of bias: -2), and the low number of included patients (imprecision: -1).
The level of evidence regarding the outcome measure AUC was downgraded by three levels to very low because of study limitations including issues with patient selection, index test and reference and the case-control design (risk of bias: -2), and the low number of included patients (imprecision: -1).
7.2 Negative and positive predictive value
The level of evidence regarding the outcome measures NPV and PPV was not assessed since none of the included studies reported on these outcomes.
8. Necker cube
8.1 Sensitivity, specificity and AUC
The level of evidence regarding the outcome measure sensitivity was downgraded by three levels to very low because of study limitations including issues with patient selection, index test and reference and the case-control design (risk of bias: -2), and the low number of included patients (imprecision: -1).
The level of evidence regarding the outcome measure specificity was downgraded by three levels to very low because of study limitations including issues with patient selection, index test and reference and the case-control design (risk of bias: -2), and the low number of included patients (imprecision: -1).
The level of evidence regarding the outcome measure AUC was downgraded by three levels to very low because of study limitations including issues with patient selection, index test and reference and the case-control design (risk of bias: -2), and the low number of included patients (imprecision: -1).
8.2 Negative and positive predictive value
The level of evidence regarding the outcome measures NPV and PPV was not assessed since none of the included studies reported on these outcomes.
9. RUDAS in combination with IQCODE
9.1 Sensitivity, specificity and AUC
The level of evidence regarding the outcome measure sensitivity was downgraded by three levels to very low because of study limitations including issues with patient selection and index test and case-control design of one study (risk of bias: -2), because different conclusions can be drawn from the upper and lower limits of the confidence interval (imprecision: -1).
The level of evidence regarding the outcome measure specificity was downgraded by two levels to low because of study limitations including issues with patient selection and index test and case-control design of one study (risk of bias: -2).
The level of evidence regarding the outcome measure AUC was downgraded by three levels to very low because of study limitations including issues with patient selection and index test and case-control design of one study (risk of bias: -2), because no reporting of confidence intervals (imprecision: -1).
9.2 Negative and positive predictive value
The level of evidence regarding the outcome measure NPV was downgraded by two levels to low because of study limitations including issues with patient selection and index test and case-control design of one study (risk of bias: -2).
The level of evidence regarding the outcome measure PPV was downgraded by two levels to low because of study limitations including issues with patient selection and index test and case-control design of one study (risk of bias: -2).
Zoeken en selecteren
A systematic review of the literature was performed to answer the following question:
PICO1: What is the diagnostic accuracy of screening instruments to determine cognitive disorders in people with a migration background and non-native speakers and/or with a low-level education?
P: People with a migration background and non-native speakers and/or with a low-level of education
I: Screening instruments for cognitive disorders (e.g., MMSE, clock, MOCA, RUDAS) in European practice
C: Other screening tools
R: Clinical diagnosis cognitive disorder
O: Diagnostic test accuracy (sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV), area under the curve (AUC)), time to complete the instrument, patient satisfaction
T/S: At entrance in a hospital, hospital setting
Relevant outcome measures
The guideline development group considered (high) sensitivity and (high) NPV as critical outcome measures for decision making and (high) specificity, (high) PPV, and AUC as important outcome measures for decision making.
A priori, the working group defined that the outcome measure patient satisfaction had to be assessed by using a validated questionnaire. The working group did not define the other outcome measures listed above but used the definitions used in the studies.
Per outcome, the working group defined the following differences as a minimally clinically (patient) important difference:
- Diagnostic accuracy (sensitivity, NPV, specificity, PPV, and AUC) ≥ 0.8.
- Time to complete the instrument ≤ 30 minutes.
- Patient satisfaction: 0.8 ≤ RR ≥ 1.25 for dichotomous outcomes, and 0.5 SD for continuous outcomes.
Regarding the instruments, various cut-off scores are reported in the literature and used in different settings in clinical practice. In this module, all cut-off scores are reported that are used in the studies.
Search and select (Methods)
Regarding PICO 1 Diagnostic accuracy, the databases Medline (via OVID) and Embase (via Embase.com) were searched. The initial search was performed with relevant search terms from 2000 until 29 March 2022. The systematic literature search resulted in 180 unique hits. The search was updated with relevant search terms from March 2022 until 3 July 2023. The update resulted in 465 unique hits. The detailed search strategy is depicted under the tab Methods. Studies were selected based on the following criteria:
- Systematic review (searched in at least two databases, and detailed search strategy, risk of bias assessment and results of individual studies available), randomized controlled trial or observational study comparing screening instruments for cognitive disorders resulting in diagnostic accuracy measures;
- Patients aged ≥ 18 years;
- Full-text English language publication;
- Studies including ≥ 20 patients (ten in each study arm); and
- Studies according to PICRO, timing, and setting.
Initially, 27 studies were selected based on title and abstract screening. After reading the full text, 21 studies were excluded (see the table with reasons for exclusion under the tab Methods), and six studies were included.
Results
Regarding PICO 1 Diagnostic accuracy, six studies were included in the analysis of the literature. Important study characteristics and results are summarized in the evidence tables. The assessment of the risk of bias is summarized in the risk of bias tables.
Referenties
- Berenschot. (2022). Tolken in de zorg een overzicht van huidige inzet, financiering en knelpunten. Retrieved from https://open.overheid.nl/repository/ronl-9995daa4a75cf7c65a601562332f6db5a6c03d43/1/pdf/tolken-in-de-zorg-een-overzicht-van-huidige-inzet-financiering-en-knelpunten.pdf
- Bourke, J., Castleden, C.M., Stephen, R. and Dennis, M. (1995), A comparison of clock and pentagon drawing in Alzheimer's disease. Int. J. Geriat. Psychiatry, 10: 703-705. https://doi.org/10.1002/gps.930100811
- Chaaya M, Phung TK, El Asmar K, Atweh S, Ghusn H, Khoury RM, Prince M, Nielsen TR, Waldemar G. Validation of the Arabic Rowland Universal Dementia Assessment Scale (A-RUDAS) in elderly with mild and moderate dementia. Aging Ment Health. 2016 Aug;20(8):880-7. doi: 10.1080/13607863.2015.1043620. Epub 2015 May 18. PMID: 25984584.
- Fernández AL, Evans J (editors). (2022). Understanding Cross-Cultural Neuropsychology (1st ed.). Taylor and Francis. Retrieved from https://www.perlego.com/book/3240663/understanding-crosscultural-neuropsychology-science-testing-and-challenges-pdf (Original work published 2022)
- Folstein MF, Folstein SE, McHugh PR. "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975 Nov;12(3):189-98. doi: 10.1016/0022-3956(75)90026-6. PMID: 1202204.
- Franzen S; European Consortium on Cross-Cultural Neuropsychology (ECCroN); Watermeyer TJ, Pomati S, Papma JM, Nielsen TR, Narme P, Mukadam N, Lozano-Ruiz Á, Ibanez-Casas I, Goudsmit M, Fasfous A, Daugherty JC, Canevelli M, Calia C, van den Berg E, Bekkhus-Wetterberg P. Cross-cultural neuropsychological assessment in Europe: Position statement of the European Consortium on Cross-Cultural Neuropsychology (ECCroN). Clin Neuropsychol. 2022 Apr;36(3):546-557. doi: 10.1080/13854046.2021.1981456. Epub 2021 Oct 6. PMID: 34612169.
- Franzen S, van den Berg E, Bossenbroek W, Kranenburg J, Scheffers EA, van Hout M, van de Wiel L, Goudsmit M, van Bruchem-Visser RL, van Hemmen J, Jiskoot LC, Papma JM. Neuropsychological assessment in the multicultural memory clinic: Development and feasibility of the TULIPA battery. Clin Neuropsychol. 2023 Jan;37(1):60-80. doi: 10.1080/13854046.2022.2043447. Epub 2022 Feb 27. PMID: 35225154.
- Goudsmit M, Uysal-Bozkir Ö, Parlevliet JL, van Campen JP, de Rooij SE, Schmand B. The Cross-Cultural Dementia Screening (CCD): A new neuropsychological screening instrument for dementia in elderly immigrants. J Clin Exp Neuropsychol. 2017 Mar;39(2):163-172. doi: 10.1080/13803395.2016.1209464. Epub 2016 Aug 8. PMID: 27501011.
- Goudsmit M, van Campen J, Schilt T, Hinnen C, Franzen S, Schmand B. One Size Does Not Fit All: Comparative Diagnostic Accuracy of the Rowland Universal Dementia Assessment Scale and the Mini Mental State Examination in a Memory Clinic Population with Very Low Education. Dement Geriatr Cogn Dis Extra. 2018 Aug 29;8(2):290-305. doi: 10.1159/000490174. PMID: 30323830; PMCID: PMC6180264.
- Goudsmit M, van Campen J, Franzen S, van den Berg E, Schilt T, Schmand B. Dementia detection with a combination of informant-based and performance-based measures in low-educated and illiterate elderly migrants. Clin Neuropsychol. 2021 Apr;35(3):660-678. doi: 10.1080/13854046.2020.1711967. Epub 2020 Jan 17. PMID: 31951511.
- Karliner LS, Jacobs EA, Chen AH, Mutha S. Do professional interpreters improve clinical care for patients with limited English proficiency? A systematic review of the literature. Health Serv Res. 2007 Apr;42(2):727-54. doi: 10.1111/j.1475-6773.2006.00629.x. PMID: 17362215; PMCID: PMC1955368.
- Kuipers, E. (2022, 4 december). Motie en rapport over tolken in de zorg [Kamerbrief]. Geraadpleegd van https://www.rijksoverheid.nl/documenten/kamerstukken/2022/12/16/kamerbrief-over-verzoek-om-reactie-op-motie-van-de-leden-paulusma-en-bikker-35925-xvi-50-en-het-rapport-tolken-in-de-zorg-een-overzicht-van-huidige-inzet-financiering-en-knelpunten
- Kuipers, E. (2023, 27 november). Tolken in de zorg [Kamerbrief]. Geraadpleegd van https://www.rijksoverheid.nl/documenten/kamerstukken/2023/11/27/kamerbrief-over-tolken-in-de-zorg
- Maestri G, Nicotra A, Pomati S, Canevelli M, Pantoni L, Cova I. Cultural influence on clock drawing test: A systematic review. J Int Neuropsychol Soc. 2023 Aug;29(7):704-714. doi: 10.1017/S1355617722000662. Epub 2022 Nov 25. PMID: 36426579.
- Nielsen TR, Jørgensen K. Visuoconstructional abilities in cognitively healthy illiterate Turkish immigrants: a quantitative and qualitative investigation. Clin Neuropsychol. 2013;27(4):681-92. doi: 10.1080/13854046.2013.767379. Epub 2013 Feb 4. PMID: 23379740.
- Nielsen TR, Phung TK, Chaaya M, Mackinnon A, Waldemar G. Combining the Rowland Universal Dementia Assessment Scale and the Informant Questionnaire on Cognitive Decline in the Elderly to Improve Detection of Dementia in an Arabic-Speaking Population. Dement Geriatr Cogn Disord. 2016;41(1-2):46-54. doi: 10.1159/000441649. Epub 2015 Nov 28. PMID: 26613533.
- Nielsen TR, Segers K, Vanderaspoilden V, Bekkhus-Wetterberg P, Bjørkløf GH, Beinhoff U, Minthon L, Pissiota A, Tsolaki M, Gkioka M, Waldemar G. Validation of the Rowland Universal Dementia Assessment Scale (RUDAS) in a multicultural sample across five Western European countries: diagnostic accuracy and normative data. Int Psychogeriatr. 2019 Feb;31(2):287-296. doi: 10.1017/S1041610218000832. Epub 2018 Jul 18. PMID: 30017010.
- Phung TK, Chaaya M, Asmar K, Atweh S, Ghusn H, Khoury RM, Prince M, Waldemar G. Performance of the 16-Item Informant Questionnaire on Cognitive Decline for the Elderly (IQCODE) in an Arabic-Speaking Older Population. Dement Geriatr Cogn Disord. 2015;40(5-6):276-89. doi: 10.1159/000437092. Epub 2015 Aug 25. PMID: 26338716; PMCID: PMC5756546.
- Shimada, Y., Meguro, K., Kasai, M., Shimada, M., Ishii, H., Yamaguchi, S. and Yamadori, A. (2006), Necker cube copying ability in normal elderly and Alzheimer's disease. A community-based study: The Tajiri project. Psychogeriatrics, 6: 4-9. https://doi.org/10.1111/j.1479-8301.2006.00121.x
- Staios M, Nielsen TR, Kosmidis MH, Papadopoulos A, Kokkinias A, Velakoulis D, Tsiaras Y, March E, Stolwyk RJ. Validity of Visuoconstructional Assessment Methods within Healthy Elderly Greek Australians: Quantitative and Error Analysis. Arch Clin Neuropsychol. 2023 May 22;38(4):598-607. doi: 10.1093/arclin/acac091. PMID: 36446753.
- Storey JE, Rowland JT, Basic D, Conforti DA, Dickson HG. The Rowland Universal Dementia Assessment Scale (RUDAS): a multicultural cognitive assessment scale. Int Psychogeriatr. 2004 Mar;16(1):13-31. doi: 10.1017/s1041610204000043.
- Strub RL. & Black FW. (1988). The mental status in neurology (2nd edition). Philadelphia, PA: F.A. Davis Company.
- Torkpoor R, Frolich K, Nielsen TR, Londos E. Diagnostic Accuracy of the Swedish Version of the Rowland Universal Dementia Assessment Scale (RUDAS-S) for Multicultural Cognitive Screening in Swedish Memory Clinics. J Alzheimers Dis. 2022;89(3):865-876. doi: 10.3233/JAD-220233. PMID: 35964182; PMCID: PMC9535584.
- Trimbos, 2023. Meetinstrumenten voor de ouderenpsychiatrie: Rowland Universal Dementia Assessment Scale (RUDAS). Toegang op 20-12023. Link: https://www.trimbos.nl/kennis/ouderenpsychiatrie-nkop/meetinstrumenten-ouderenpsychiatrie/. Animatievideo: https://vimeo.com/670134017/c0f81cb0b4
- Vissenberg R, Uysal-Bozkir O, Goudsmit M, Buurman-van Es B, van Campen J. Dementie bij oudere migranten. Huisarts en wetenschap. 2019 May 14;6:42-45. doi: 10.1007/s12445-019-0115-x
- Zwart LA, Goudsmit M, van Campen JP, Rijkers CJ, Wind AW. Het gebruik van de MMSE als screeningsinstrument voor dementie bij oudere Turkse en Marokkaanse migranten [Using the MMSE as a cognitive screener among Turkish and Moroccan migrants]. Tijdschr Gerontol Geriatr. 2015 Feb;46(1):28-36. Dutch. doi: 10.1007/s12439-014-0105-1. PMID: 25475409.
Evidence tabellen
|
Study reference |
Study characteristics |
Patient characteristics
|
Index test (test of interest) |
Reference test
|
Follow-up |
Outcome measures and effect size |
Comments |
|
Goudsmit, 2017 |
Type of study[1]: Case-control study
Setting and country: Dutch memory clinics
Funding and conflicts of interest: The study was supported by the Innovatiefonds Zorgverzekeraars, and partially by the innovation fund of Stichting Transmuraal. |
Inclusion criteria: - Patients aged ≥55 years with a diagnosis of probable dementia and healthy controls of different ethnicities.
Exclusion criteria: - Current or previous conditions that affect cognitive functioning.
N= 108 Intact cognition: 54 Dementia: 54
Mean age: NR Sex (%F): NR |
Describe index test: CCD Cut-off point(s): <118 <109 >39 >71 >115 >216
Comparator test[2]: None
Cut-off point(s): Not applicable |
Describe reference test[3]: Clinical diagnosis
Cut-off point(s): Dementia: according to Dutch consensus guidelines
|
Time between the index test and reference test: Reference test was performed before CCD
For how many participants were no complete outcome data available? None
Reasons for incomplete outcome data described? Not applicable |
CCD Objects test – part A Cut-off: <118 Sensitivity: 0.85 Specificity: 0.89
Objects test – part B Cut-off: <109 Sensitivity: 0.92 Specificity: 0.91
Sun-Moon test – part A Cut-off: >39 Sensitivity: 0.81 Specificity: 0.85
Sun-Moon test – part B Cut-off: >71 Sensitivity: 0.85 Specificity: 0.89
Dots test – part A Cut-off: >115 Sensitivity: 0.67 Specificity: 0.98
Dots test – part B Cut-off: >216 Sensitivity: 0.85 Specificity: 0.83 |
None |
|
Goudsmit, 2018 |
Type of study[4]: Cross-sectional study
Setting and country: Geriatric outpatient clinics in Amsterdam and Rotterdam
Funding and conflicts of interest: The Rotterdam branch of this study was funded by Stichting Coolsingel and by ZonMw Memorabel project. The authors have no conflicts of interest |
Inclusion criteria: - ‘’Non-western’’ descent based on self-defined ethnicity - Age ≥55 years
Exclusion criteria: - Serious vision or hearing disabilities or other conditions that could interfere with cognitive testing - Failure to complete MMSE and RUDAS.
N=144 Intact cognition: 42 MCI: 44 Dementia: 58
Median age (Q1-Q3): Intact cognition: 75 (68-78) MCI: 75 (68-81) Dementia: 76 (71-79)
Sex: % F Intact cognition: 60% MCI: 73% Dementia: 48% |
Describe index test: RUDAS Cut-off point(s): <16-25
Comparator test[5]: MMSE
Cut-off point(s): <12-25 |
Describe reference test[6]: Clinical diagnosis
Cut-off point(s): MCI: according to core clinical criteria provided by NIA-AA workgroup
Dementia: according to DSM-IV-TR criteria
|
Time between the index test and reference test: Same day. Clinical diagnosis was based on all available clinical information on that day, except MSSE and RUDAS scores.
For how many participants were no complete outcome data available? None
Reasons for incomplete outcome data described? Not applicable |
Outcome measures RUDAS Cut-off: <22 Sensitivity: 0.74 Specificity: 0.74
Cut-off: <23 Sensitivity: 0.75 Specificity: 0.62
AUC = 0.81 (0.74-0.88)
MMSE Cut-off: <14 Sensitivity: 0.60 Specificity: 0.90
Cut-off: <24 Sensitivity: 0.94 Specificity: 0.17
AUC = 0.77 (0.69-0.85)
|
None |
|
Goudsmit, 2021 |
Type of study: Cross-sectional study
Setting and country: Geriatric outpatient clinics in the Netherlands
Funding and conflicts of interest: Study was funded by the Netherlands Organization for Health Research and Development-project. No potential conflicts of interest were reported. |
Inclusion criteria: - ‘’Non-western’’ immigrants - Age ≥55 years
Exclusion criteria: - Serious vision or hearing disabilities or other conditions that could interfere with cognitive testing -Absence of an informant who could complete the IQCODE.
N= 109 Intact cognition: 27 MCI: 33 Dementia: 49
Median age (Q1-Q3): Intact cognition: 76 (70-78) MCI: 77 (71-82) Dementia: 78 (74-81)
Sex: % F Intact cognition: 70% MCI: 76% Dementia: 49% |
Describe index test: IQCODE
Cut-off point(s): >3.3-3.8
Comparator test: RUDAS
Cut-off point(s): <20-25 |
Describe reference test: Clinical diagnosis
Cut-off point(s): MCI: according to core clinical criteria provided by NIA-AA workgroup
Dementia: according to DSM-IV-TR criteria
|
Time between the index test and reference test: Same day. Clinical diagnosis was based on all available clinical information on that day, except MSSE, IQCODE and RUDAS scores.
For how many participants were no complete outcome data available? None
Reasons for incomplete outcome data described? Not applicable |
Outcome measures IQCODE Cut-off: >3.8 Sensitivity: 0.77 (0.66-0.85) Specificity: 0.0.81 (0.62-0.94) PPV: 0.93 (0.85-0.97) NPV: 0.54 (0.43-0.64)
AUC = 0.86 (0.77-0.94)
RUDAS Cut-off: <22 Sensitivity: 0.78 (0.68-0.87) Specificity: 0.70 (0.50-0.86) PPV: 0.89 (0.81-0.93) NPV: 0.53 (0.41-0.65)
Cut-off: <23 Sensitivity: 0.80 (0.69-0.88) Specificity: 0.59 (0.39-0.78) PPV: 0.85 (0.78-0.90) NPV: 0.50 (0.37-0.63)
AUC = 0.82 (0.74-0.90)
|
None |
|
Nielsen, 2016 |
Type of study: Case-control study
Setting and country: Denmark
Funding and conflicts of interest: Fieldwork was funded by the Fogarty International Center, American National Institute of Health and National Institute of Aging. Potential conflicts of interest are not reported. |
Inclusion criteria: - Age ≥65 years - Having normal cognition (controls) or mild-to-moderate dementia (cases) - Having an informant who could give an independent assessment of the participant’s health and cognitive status.
Exclusion criteria: - Severe somatic or psychiatric illness - MCI
N= 225 Normal cognition: 135 Dementia: 90
Mean age (SD): Normal cognition: 77.0 (7.5) Dementia: 81.9 (7.5)
Sex: % F Normal cognition: 61.5% Dementia: 67.8% |
Describe index test: IQCODE
Cut-off point(s): >3.34/5
Comparator test: RUDAS
Cut-off point(s): <23/30 |
Describe reference test: Clinical diagnosis
Cut-off point(s): Dementia: according to DSM-IV criteria
|
Time between the index test and reference test: Not reported.
For how many participants were no complete outcome data available? Unclear
Reasons for incomplete outcome data described? Not applicable |
Outcome measures IQCODE Cut-off: >3.34 Sensitivity: 0.92 (0.84-0.96) Specificity: 0.96 (0.90-0.98) PPV: 0.93 (0.85-0.97) NPV: 0.95 (0.89-0.98)
AUC = 0.97
RUDAS Cut-off: <23 Sensitivity: 0.82 (0.72-0.89) Specificity: 0.84 (0.77-0.90) PPV: 0.78 (0.68-0.93) NPV: 0.88 (0.80-0.93)
AUC = 0.92 |
None |
|
Staios, 2023 |
Type of study: Case-control study
Setting and country: Greece
Funding and conflicts of interest: This research was supported by Fronditha Care, Marathon Foods, the Australasian Hellenic Educational Progressive Association, Anna Timou, the Australian Hellenic Golf Federation, the Hellenic Women’s Cultural Association, Kirsty Chiaplias, and the Thessaloniki Association. The authors report no conflicts of interest. |
Inclusion criteria: - Age 70-85 years - Literate, immigrants from Greece - Greek as dominant language - Having normal cognition (controls) or diagnosis of AD (cases)
Exclusion criteria: - MMSE < 22/30 - Self-reported functional or memory decline - History of neurological or psychiatric conditions known to impact cognition - Score >6/15 on geriatric depression scale or ≥8/20 on the geriatric anxiety inventory - Uncorrected visual and/or auditory deficits - History or current consumption of >10 standard alcoholic drinks per week and/or >4 standard drinks on one day - History or current substance use
N= 110 Normal cognition: 90 Dementia: 20
Mean age ± SD: Normal cognition: 77.1 (4.5) Dementia: 78.0 (3.5)
Sex: %F Normal cognition: 56.7% Dementia: 55.0% |
Describe index test: Greek cross
Cut-off point(s): 1/2
Comparator test: Four-pointed star Intersecting pentagons Necker cube
Cut-off point(s): 1/2 1-6 1-6 |
Describe reference test: Clinical diagnosis
Cut-off point(s): Dementia: diagnostic criteria according to DSM-5 and diagnostic research criteria for AD. |
Time between the index test and reference test: Not reported.
For how many participants were no complete outcome data available? None
Reasons for incomplete outcome data described? Not applicable |
Outcome measures Greek cross Cut-off: 1 Sensitivity: 0.40 Specificity: 0.96
AUC = 0.80 (0.69-0.91)
Four-pointed star Cut-off: 1 Sensitivity: 0.10 Specificity: 0.98
AUC = 0.68 (0.57-0.80)
Intersecting pentagons Cut-off: 4 Sensitivity: 0.95 Specificity: 0.31
AUC = 0.71 (0.61-0.83)
Necker cube Cut-off: 2 Sensitivity: 0.75 Specificity: 0.36
AUC = 0.55 (0.48-0.67)
|
None |
|
Torkpoor, 2022 |
Type of study: Cross-sectional study
Setting and country: 4 memory clinics in Southern Sweden
Funding and conflicts of interest: The study was supported by the Swedish federal government and by the Kockska foundation and Vinnova. |
Inclusion criteria: - Patients referred to the memory clinics to assess their cognitive impairment.
Exclusion criteria: No exclusion criteria.
N= 36 Mean (SD) age: 70.5 (12.9) years Sex (%F): 63.9% |
Describe index test: RUDAS-S
Cut-off point(s): <25
Comparator test: MMSE-SR
Cut-off point(s): <23 |
Describe reference test: Clinical diagnosis
Cut-off point(s): According to the international classification of diseases (ICD-10) |
Time between the index test and reference test: Same day.
For how many participants were no complete outcome data available? Unclear
Reasons for incomplete outcome data described? Not applicable |
RUDAS-S AUC = 0.86 (0.72-0.99)
MMSE-SR AUC = 0.84 (0.71-0.97) |
None |
|
Nielsen, 2018 |
Type of study: Prospective cross-sectional study
Setting and country: Multicenter study in memory clinics in Germany, Belgium, Denmark, Sweden, Norway and Greece.
Funding and conflicts of interest: Supported by the European Union funded Interreg IV A program. The authors report no conflicts of interest. |
Inclusion criteria: - Participants with a “non-Western” immigrant background and native-born participants with intact cognition and with a diagnosis of dementia.
Exclusion criteria (for individuals with intact cognition): - Individuals reporting significant memory problems, psychiatric or neurological disorders, or substance abuse, or scoring above the proposed cut-off of ≥10/15 on the 15-item GDS. - Individuals had to be free of physical disabilities that could interfere with cognitive testing.
N= 280 Normal cognition: 200 Dementia: 80
Mean age ± SD: Normal cognition: 69.4 (9.7) Dementia: 75.0 (8.8)
Sex: %F Normal cognition: 61% Dementia: 48% |
Describe index test: RUDAS
Cut-off point(s): <22-26
Comparator test: None
Cut-off point(s): Not applicable |
Describe reference test: Clinical diagnosis
Cut-off point(s): According to the DSM-IV-TR criteria and diagnostic research criteria for dementia |
Time between the index test and reference test: Same day
For how many participants were no complete outcome data available? Diagnostic accuracy of the RUDAS was assessed in 280 (80 with dementia, 200 with intact cognition) of 441 individuals.
Reasons for incomplete outcome data described? - History of significant memory problems (n=4) - Stroke (n=4) - Traumatic brain injury (n=1) - Parkinson’s disease (n=1) - GDS score above cut-off (n=10) For the other participants, no reasons are reported. |
RUDAS AUC = 0.95 (0.92-0.99) |
None |
[1] In geval van een case-control design moeten de patiëntkarakteristieken per groep (cases en controls) worden uitgewerkt. NB; case control studies zullen de accuratesse overschatten (Lijmer et al., 1999)
[2] Comparator test is vergelijkbaar met de C uit de PICO van een interventievraag. Er kunnen ook meerdere tests worden vergeleken. Voeg die toe als comparator test 2 etc. Let op: de comparator test kan nooit de referentiestandaard zijn.
[3] De referentiestandaard is de test waarmee definitief wordt aangetoond of iemand al dan niet ziek is. Idealiter is de referentiestandaard de Gouden standaard (100% sensitief en 100% specifiek). Let op! dit is niet de “comparison test/index 2”.
4 Beschrijf de statistische parameters voor de vergelijking van de indextest(en) met de referentietest, en voor de vergelijking tussen de indextesten onderling (als er twee of meer indextesten worden vergeleken).
[5] Comparator test is vergelijkbaar met de C uit de PICO van een interventievraag. Er kunnen ook meerdere tests worden vergeleken. Voeg die toe als comparator test 2 etc. Let op: de comparator test kan nooit de referentiestandaard zijn.
[6] De referentiestandaard is de test waarmee definitief wordt aangetoond of iemand al dan niet ziek is. Idealiter is de referentiestandaard de Gouden standaard (100% sensitief en 100% specifiek). Let op! dit is niet de “comparison test/index 2”.
4 Beschrijf de statistische parameters voor de vergelijking van de indextest(en) met de referentietest, en voor de vergelijking tussen de indextesten onderling (als er twee of meer indextesten worden vergeleken).
Risk of bias tables
|
Study reference |
Patient selection |
Index test |
Reference standard |
Flow and timing |
Comments with respect to applicability |
|
Goudsmit, 2017 |
Was a consecutive or random sample of patients enrolled? Unclear
Was a case-control design avoided? No
Did the study avoid inappropriate exclusions? Yes |
Were the index test results interpreted without knowledge of the results of the reference standard? No
If a threshold was used, was it pre-specified? Yes |
Is the reference standard likely to correctly classify the target condition? Yes
Were the reference standard results interpreted without knowledge of the results of the index test? Yes
|
Was there an appropriate interval between index test(s) and reference standard? No
Did all patients receive a reference standard? Yes
Did patients receive the same reference standard? Yes
Were all patients included in the analysis? Yes, missing values were replaced by the lowest normal values of the patient group |
Are there concerns that the included patients do not match the review question? No
Are there concerns that the index test, its conduct, or interpretation differ from the review question? No
Are there concerns that the target condition as defined by the reference standard does not match the review question? No |
|
CONCLUSION: Could the selection of patients have introduced bias?
RISK: HIGH |
CONCLUSION: Could the conduct or interpretation of the index test have introduced bias?
RISK: HIGH
|
CONCLUSION: Could the reference standard, its conduct, or its interpretation have introduced bias?
RISK: LOW |
CONCLUSION Could the patient flow have introduced bias?
RISK: UNCLEAR |
||
|
Goudsmit, 2018 |
Was a consecutive or random sample of patients enrolled? Yes
Was a case-control design avoided? Yes
Did the study avoid inappropriate exclusions? Yes
|
Were the index test results interpreted without knowledge of the results of the reference standard? Yes
If a threshold was used, was it pre-specified? Yes
|
Is the reference standard likely to correctly classify the target condition? Yes
Were the reference standard results interpreted without knowledge of the results of the index test? Yes
|
Was there an appropriate interval between index test(s) and reference standard? Yes
Did all patients receive a reference standard? Yes
Did patients receive the same reference standard? Yes
Were all patients included in the analysis? No
|
Are there concerns that the included patients do not match the review question? No
Are there concerns that the index test, its conduct, or interpretation differ from the review question? No
Are there concerns that the target condition as defined by the reference standard does not match the review question? No
|
|
CONCLUSION: Could the selection of patients have introduced bias?
RISK: LOW |
CONCLUSION: Could the conduct or interpretation of the index test have introduced bias?
RISK: LOW |
CONCLUSION: Could the reference standard, its conduct, or its interpretation have introduced bias?
RISK: LOW |
CONCLUSION Could the patient flow have introduced bias?
RISK: LOW |
|
|
|
Goudsmit, 2021 |
Was a consecutive or random sample of patients enrolled? Yes
Was a case-control design avoided? Yes
Did the study avoid inappropriate exclusions? Yes
|
Were the index test results interpreted without knowledge of the results of the reference standard? Yes
If a threshold was used, was it pre-specified? Yes
|
Is the reference standard likely to correctly classify the target condition? Yes
Were the reference standard results interpreted without knowledge of the results of the index test? Yes
|
Was there an appropriate interval between index test(s) and reference standard? Yes
Did all patients receive a reference standard? Yes
Did patients receive the same reference standard? Yes
Were all patients included in the analysis? Yes |
Are there concerns that the included patients do not match the review question? No
Are there concerns that the index test, its conduct, or interpretation differ from the review question? Yes
Are there concerns that the target condition as defined by the reference standard does not match the review question? No
|
|
|
CONCLUSION: Could the selection of patients have introduced bias?
RISK: LOW |
CONCLUSION: Could the conduct or interpretation of the index test have introduced bias?
RISK: LOW
|
CONCLUSION: Could the reference standard, its conduct, or its interpretation have introduced bias?
RISK: LOW |
CONCLUSION Could the patient flow have introduced bias?
RISK: LOW |
|
|
Nielsen, 2016 |
Was a consecutive or random sample of patients enrolled? Unclear
Was a case-control design avoided? No
Did the study avoid inappropriate exclusions? Yes
|
Were the index test results interpreted without knowledge of the results of the reference standard? No
If a threshold was used, was it pre-specified? Yes
|
Is the reference standard likely to correctly classify the target condition? Yes
Were the reference standard results interpreted without knowledge of the results of the index test? Yes
|
Was there an appropriate interval between index test(s) and reference standard? Unclear
Did all patients receive a reference standard? Unclear
Did patients receive the same reference standard? Unclear
Were all patients included in the analysis? Unclear
|
Are there concerns that the included patients do not match the review question? No
Are there concerns that the index test, its conduct, or interpretation differ from the review question? No
Are there concerns that the target condition as defined by the reference standard does not match the review question? Yes
|
|
|
CONCLUSION: Could the selection of patients have introduced bias?
RISK: HIGH |
CONCLUSION: Could the conduct or interpretation of the index test have introduced bias?
RISK: HIGH
|
CONCLUSION: Could the reference standard, its conduct, or its interpretation have introduced bias?
RISK: LOW |
CONCLUSION Could the patient flow have introduced bias?
RISK: UNCLEAR |
|
|
Staios, 2023 |
Was a consecutive or random sample of patients enrolled? No
Was a case-control design avoided? No
Did the study avoid inappropriate exclusions? Yes
|
Were the index test results interpreted without knowledge of the results of the reference standard? No
If a threshold was used, was it pre-specified? Yes
|
Is the reference standard likely to correctly classify the target condition? Yes
Were the reference standard results interpreted without knowledge of the results of the index test? No
|
Was there an appropriate interval between index test(s) and reference standard? Unclear
Did all patients receive a reference standard? Unclear
Did patients receive the same reference standard? Unclear
Were all patients included in the analysis? Yes
|
Are there concerns that the included patients do not match the review question? Yes
Are there concerns that the index test, its conduct, or interpretation differ from the review question? No
Are there concerns that the target condition as defined by the reference standard does not match the review question? Yes
|
|
|
CONCLUSION: Could the selection of patients have introduced bias?
RISK: HIGH |
CONCLUSION: Could the conduct or interpretation of the index test have introduced bias?
RISK: HIGH
|
CONCLUSION: Could the reference standard, its conduct, or its interpretation have introduced bias?
RISK: HIGH |
CONCLUSION Could the patient flow have introduced bias?
RISK: UNCLEAR |
|
|
Torkpoor, 2022 |
Was a consecutive or random sample of patients enrolled? Yes
Was a case-control design avoided? Yes
Did the study avoid inappropriate exclusions? Yes |
Were the index test results interpreted without knowledge of the results of the reference standard? Yes
If a threshold was used, was it pre-specified? No |
Is the reference standard likely to correctly classify the target condition? Yes
Were the reference standard results interpreted without knowledge of the results of the index test? No
|
Was there an appropriate interval between index test(s) and reference standard? No
Did all patients receive a reference standard? Yes
Did patients receive the same reference standard? Yes
Were all patients included in the analysis? Yes |
Are there concerns that the included patients do not match the review question? No
Are there concerns that the index test, its conduct, or interpretation differ from the review question? No
Are there concerns that the target condition as defined by the reference standard does not match the review question? Yes |
|
|
CONCLUSION: Could the selection of patients have introduced bias?
RISK: LOW |
CONCLUSION: Could the conduct or interpretation of the index test have introduced bias?
RISK: UNCLEAR |
CONCLUSION: Could the reference standard, its conduct, or its interpretation have introduced bias?
RISK: HIGH |
CONCLUSION Could the patient flow have introduced bias?
RISK: UNCLEAR |
|
|
Nielsen, 2018 |
Was a consecutive or random sample of patients enrolled? Yes
Was a case-control design avoided? Yes
Did the study avoid inappropriate exclusions? Yes |
Were the index test results interpreted without knowledge of the results of the reference standard? No
If a threshold was used, was it pre-specified? Yes |
Is the reference standard likely to correctly classify the target condition? Yes
Were the reference standard results interpreted without knowledge of the results of the index test? No |
Was there an appropriate interval between index test(s) and reference standard? Yes
Did all patients receive a reference standard? Yes
Did patients receive the same reference standard? Yes
Were all patients included in the analysis? No |
Are there concerns that the included patients do not match the review question? No
Are there concerns that the index test, its conduct, or interpretation differ from the review question? No
Are there concerns that the target condition as defined by the reference standard does not match the review question? No |
|
|
CONCLUSION: Could the selection of patients have introduced bias?
RISK: LOW |
CONCLUSION: Could the conduct or interpretation of the index test have introduced bias?
RISK: HIGH |
CONCLUSION: Could the reference standard, its conduct, or its interpretation have introduced bias?
RISK: HIGH |
CONCLUSION Could the patient flow have introduced bias?
RISK: LOW |
|
Table of excluded studies - PICO 1 Diagnostic accuracy
|
Reference |
Reason for exclusion |
|
Naqvi RM, Haider S, Tomlinson G, Alibhai S. Cognitive assessments in multicultural populations using the Rowland Universal Dementia Assessment Scale: a systematic review and meta-analysis. CMAJ. 2015 Mar 17;187(5):E169-75. doi: 10.1503/cmaj.140802. Epub 2015 Feb 17. PMID: 25691786; PMCID: PMC4361127. |
Wrong population (majority of participants in the included studies had no migration background) |
|
O'Driscoll C, Shaikh M. Cross-Cultural Applicability of the Montreal Cognitive Assessment (MoCA): A Systematic Review. J Alzheimers Dis. 2017;58(3):789-801. doi: 10.3233/JAD-161042. PMID: 28482634. |
Wrong population (no migration background) |
|
Franzen S, van den Berg E, Goudsmit M, Jurgens CK, van de Wiel L, Kalkisim Y, Uysal-Bozkir Ö, Ayhan Y, Nielsen TR, Papma JM. A Systematic Review of Neuropsychological Tests for the Assessment of Dementia in Non-Western, Low-Educated or Illiterate Populations. J Int Neuropsychol Soc. 2020 Mar;26(3):331-351. doi: 10.1017/S1355617719000894. Epub 2019 Sep 12. PMID: 31511111. |
Wrong population (no migration background), results are narratively described |
|
Franzen S, van den Berg E, Kalkisim Y, van de Wiel L, Harkes M, van Bruchem-Visser RL, de Jong FJ, Jiskoot LC, Papma JM. Assessment of Visual Association Memory in Low-Educated, Non-Western Immigrants with the Modified Visual Association Test. Dement Geriatr Cogn Disord. 2019;47(4-6):345-354. doi: 10.1159/000501151. Epub 2019 Jul 18. PMID: 31319408; PMCID: PMC6878732. |
Wrong outcomes (no diagnostic accuracy values reported) |
|
Franzen, S., Van den Berg, E., Ayhan, Y., Satoer, D., Türkoğlu, Ö, Genç Akpulat, G., . . . Papma, J. (2023). The Naming Assessment in Multicultural Europe (NAME): Development and Validation in a Multicultural Memory Clinic. Journal of the International Neuropsychological Society, 29(1), 92-104. doi:10.1017/S135561772100148X |
No subanalysis without native Turkish patients |
|
Maillet D, Narme P, Amieva H, Matharan F, Bailon O, Le Clésiau H, Belin C. The TMA-93: A New Memory Test for Alzheimer's Disease in Illiterate and Less Educated People. Am J Alzheimers Dis Other Demen. 2017 Dec;32(8):461-467. doi: 10.1177/1533317517722630. Epub 2017 Jul 27. PMID: 28750554. |
Wrong population (native speakers and immigrants in population) |
|
Nielsen TR, Andersen BB, Gottrup H, Lützhøft JH, Høgh P, Waldemar G. Validation of the Rowland Universal Dementia Assessment Scale for multicultural screening in Danish memory clinics. Dement Geriatr Cogn Disord. 2013;36(5-6):354-62. doi: 10.1159/000354375. Epub 2013 Sep 10. PMID: 24022429. |
Wrong population (75% was native Danish speaker) |
|
Schoenmakers B, Robben T. Barriers in screening for dementia in elderly migrants in primary care and the use of the Rowland Universal Dementia Assessment Scale. A mixed cross-sectional and qualitative study. Eur J Gen Pract. 2021 Dec;27(1):45-50. doi: 10.1080/13814788.2021.1913116. PMID: 33928835; PMCID: PMC8816395. |
Wrong population (no migration background) |
|
Nielsen TR, Vogel A, Waldemar G. Comparison of performance on three neuropsychological tests in healthy Turkish immigrants and Danish elderly. Int Psychogeriatr. 2012 Sep;24(9):1515-21. doi: 10.1017/S1041610212000440. Epub 2012 Apr 16. PMID: 22717281. |
Wrong outcomes (no diagnostic accuracy values reported) |
|
Franzen S, van den Berg E, Bossenbroek W, Kranenburg J, Scheffers EA, van Hout M, van de Wiel L, Goudsmit M, van Bruchem-Visser RL, van Hemmen J, Jiskoot LC, Papma JM. Neuropsychological assessment in the multicultural memory clinic: Development and feasibility of the TULIPA battery. Clin Neuropsychol. 2023 Jan;37(1):60-80. doi: 10.1080/13854046.2022.2043447. Epub 2022 Feb 27. PMID: 35225154. |
Wrong outcomes (no diagnostic accuracy values reported) |
|
Zwart LA, Goudsmit M, van Campen JP, Rijkers CJ, Wind AW. Het gebruik van de MMSE als screeningsinstrument voor dementie bij oudere Turkse en Marokkaanse migranten [Using the MMSE as a cognitive screener among Turkish and Moroccan migrants]. Tijdschr Gerontol Geriatr. 2015 Feb;46(1):28-36. Dutch. doi: 10.1007/s12439-014-0105-1. PMID: 25475409. |
No English full-text publication available |
|
Harrison JK, Fearon P, Noel-Storr AH, McShane R, Stott DJ, Quinn TJ. Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) for the diagnosis of dementia within a secondary care setting. Cochrane Database Syst Rev. 2015 Mar 10;(3):CD010772. doi: 10.1002/14651858.CD010772.pub2. Update in: Cochrane Database Syst Rev. 2021 Jul 19;7:CD010772. PMID: 25754745. |
Wrong population (individuals without migration background)
|
|
Giaquinto F, Battista P, Angelelli P. Touchscreen Cognitive Tools for Mild Cognitive Impairment and Dementia Used in Primary Care Across Diverse Cultural and Literacy Populations: A Systematic Review. J Alzheimers Dis. 2022;90(4):1359-1380. doi: 10.3233/JAD-220547. PMID: 36245376. |
Wrong population (no migration background) |
|
Pellicer-Espinosa I, Díaz-Orueta U. Cognitive Screening Instruments for Older Adults with Low Educational and Literacy Levels: A Systematic Review. J Appl Gerontol. 2022 Apr;41(4):1222-1231. doi: 10.1177/07334648211056230. Epub 2021 Dec 2. PMID: 34856843; PMCID: PMC8966106. |
Wrong outcomes (no diagnostic accuracy values reported) |
|
Maestri G, Nicotra A, Pomati S, Canevelli M, Pantoni L, Cova I. Cultural influence on clock drawing test: A systematic review. J Int Neuropsychol Soc. 2023 Aug;29(7):704-714. doi: 10.1017/S1355617722000662. Epub 2022 Nov 25. PMID: 36426579. |
Wrong population (no migration background) |
|
Maher C, Calia C. The effect of illiteracy on performance in screening tools for dementia: A meta-analysis. J Clin Exp Neuropsychol. 2021 Dec;43(10):945-966. doi: 10.1080/13803395.2022.2040433. Epub 2022 Feb 24. PMID: 35200100. |
Wrong outcomes (no diagnostic accuracy values reported) |
|
Torkpoor R, Frolich K, Nielsen TR, Londos E. Diagnostic Accuracy of the Swedish Version of the Rowland Universal Dementia Assessment Scale (RUDAS-S) for Multicultural Cognitive Screening in Swedish Memory Clinics. J Alzheimers Dis. 2022;89(3):865-876. doi: 10.3233/JAD-220233. PMID: 35964182; PMCID: PMC9535584. |
Reported sensitivity and specificity only for total population (nonnative and native participants together) |
|
Celik S, Onur O, Yener G, Kessler J, Özbek Y, Meyer P, Frölich L, Teichmann B. Cross-cultural comparison of MMSE and RUDAS in German and Turkish patients with Alzheimer's disease. Neuropsychology. 2022 Mar;36(3):195-205. doi: 10.1037/neu0000764. Epub 2021 Sep 2. PMID: 34472899. |
Wrong outcomes (no diagnostic accuracy values reported) |
|
Alkeridy WA, Al Khalifah RA, Mohammedin AS, Khallaf R, Muayqil T, Bucks RS. The Arabic Translation and Cross-Cultural Adaptation of the Bristol Activity of Daily Living Scale. J Alzheimers Dis. 2022;86(3):1123-1130. doi: 10.3233/JAD-215489. PMID: 35147542. |
Wrong outcomes (no diagnostic accuracy values reported) |
|
Gianattasio KZ, Ciarleglio A, Power MC. Development of Algorithmic Dementia Ascertainment for Racial/Ethnic Disparities Research in the US Health and Retirement Study. Epidemiology. 2020 Jan;31(1):126-133. doi: 10.1097/EDE.0000000000001101. PMID: 31567393; PMCID: PMC6888863. |
Wrong aim (to develop and distribute an algorithm that performs comparably across racial/ethnic groups for use in dementia) |
|
Delgado-Álvarez A, Nielsen TR, Delgado-Alonso C, Valles-Salgado M, López-Carbonero JI, García-Ramos R, Gil-Moreno MJ, Díez-Cirarda M, Matías-Guiu J, Matias-Guiu JA. Validation of the European Cross-Cultural Neuropsychological Test Battery (CNTB) for the assessment of mild cognitive impairment due to Alzheimer's disease and Parkinson's disease. Front Aging Neurosci. 2023 May 5;15:1134111. doi: 10.3389/fnagi.2023.1134111. PMID: 37213535; PMCID: PMC10196233. |
Wrong intervention (cognitive test battery) |
Table of excluded studies - PICO 2 Professional interpreter
|
Reference |
Reason for exclusion |
|
Heath M, Hvass AMF, Wejse CM. Interpreter services and effect on healthcare - a systematic review of the impact of different types of interpreters on patient outcome. J Migr Health. 2023 Jan 24;7:100162. doi: 10.1016/j.jmh.2023.100162. PMID: 36816444; PMCID: PMC9932446. |
Wrong P (geen cogn. stoornis) |
|
Stinson JM, Armendariz V, Hegazy MIR, Strutt AM, McCauley SR, York MK. Developing a Culturally Competent Neuropsychological Battery for Diagnosis of Dementia in Arabic-Speaking Patients in the United States. Arch Clin Neuropsychol. 2023 Apr 26;38(3):433-445. doi: 10.1093/arclin/acad017. PMID: 36988467. |
Wrong I/C |
|
Chejor P, Laging B, Whitehead L, Porock D. Experiences of older immigrants living with dementia and their carers: a systematic review and meta-synthesis. BMJ Open. 2022 May 24;12(5):e059783. doi: 10.1136/bmjopen-2021-059783. PMID: 35613772; PMCID: PMC9125757. |
Wrong I/C |
|
Brijnath B, Croy S, Sabates J, Thodis A, Ellis S, de Crespigny F, Moxey A, Day R, Dobson A, Elliott C, Etherington C, Geronimo MA, Hlis D, Lampit A, Low LF, Straiton N, Temple J. Including ethnic minorities in dementia research: Recommendations from a scoping review. Alzheimers Dement (N Y). 2022 Apr 29;8(1):e12222. doi: 10.1002/trc2.12222. PMID: 35505899; PMCID: PMC9053375. |
Wrong I/C/aim |
|
Chan CC, Fage BA, Burton JK, Smailagic N, Gill SS, Herrmann N, Nikolaou V, Quinn TJ, Noel-Storr AH, Seitz DP. Mini-Cog for the detection of dementia within a secondary care setting. Cochrane Database Syst Rev. 2021 Jul 14;7(7):CD011414. doi: 10.1002/14651858.CD011414.pub3. PMID: 34260060; PMCID: PMC8278979. |
Wrong P (geen cogn. stoornis) |
|
Tillmann J, Just J, Schnakenberg R, Weckbecker K, Weltermann B, Münster E. Challenges in diagnosing dementia in patients with a migrant background - a cross-sectional study among German general practitioners. BMC Fam Pract. 2019 Feb 25;20(1):34. doi: 10.1186/s12875-019-0920-0. PMID: 30803438; PMCID: PMC6388491. |
Wrong I/C |
|
Sagbakken M, Spilker RS, Nielsen TR. Dementia and immigrant groups: a qualitative study of challenges related to identifying, assessing, and diagnosing dementia. BMC Health Serv Res. 2018 Nov 29;18(1):910. doi: 10.1186/s12913-018-3720-7. PMID: 30497459; PMCID: PMC6267848. |
Wrong I/C |
|
Brandl EJ, Schreiter S, Schouler-Ocak M. Are Trained Medical Interpreters Worth the Cost? A Review of the Current Literature on Cost and Cost-Effectiveness. J Immigr Minor Health. 2020 Feb;22(1):175-181. doi: 10.1007/s10903-019-00915-4. PMID: 31256314. |
Wrong P (geen cogn. stoornis) |
|
Karliner LS, Jacobs EA, Chen AH, Mutha S. Do professional interpreters improve clinical care for patients with limited English proficiency? A systematic review of the literature. Health Serv Res. 2007 Apr;42(2):727-54. doi: 10.1111/j.1475-6773.2006.00629.x. PMID: 17362215; PMCID: PMC1955368. |
Wrong P (geen cogn. stoornis) |
|
Flores G. The impact of medical interpreter services on the quality of health care: a systematic review. Med Care Res Rev. 2005 Jun;62(3):255-99. doi: 10.1177/1077558705275416. PMID: 15894705. |
Wrong P (geen cogn. stoornis) |
|
Ono N, Kiuchi T, Ishikawa H. Development and pilot testing of a novel education method for training medical interpreters. Patient Educ Couns. 2013 Dec;93(3):604-11. doi: 10.1016/j.pec.2013.09.003. Epub 2013 Sep 12. PMID: 24075728. |
Wrong P/I/C |
|
Ng JH, Tirodkar MA, French JB, Spalt HE, Ward LM, Haffer SC, Hewitt N, Rey D, Scholle SH. Health Quality Measures Addressing Disparities in Culturally and Linguistically Appropriate Services: What are Current Gaps? J Health Care Poor Underserved. 2017;28(3):1012-1029. doi: 10.1353/hpu.2017.0093. PMID: 28804074. |
Wrong P/I/C |
|
Chan CC, Fage BA, Burton JK, Smailagic N, Gill SS, Herrmann N, Nikolaou V, Quinn TJ, Noel-Storr AH, Seitz DP. Mini-Cog for the diagnosis of Alzheimer's disease dementia and other dementias within a secondary care setting. Cochrane Database Syst Rev. 2019 Sep 14;9(9):CD011414. doi: 10.1002/14651858.CD011414.pub2. Update in: Cochrane Database Syst Rev. 2021 Jul 14;7:CD011414. PMID: 31521064; PMCID: PMC6744952. |
Wrong I/C |
|
Sleptsova M, Hofer G, Morina N, Langewitz W. The role of the health care interpreter in a clinical setting--a narrative review. J Community Health Nurs. 2014;31(3):167-84. doi: 10.1080/07370016.2014.926682. PMID: 25051322. |
Wrong P (geen cogn. stoornis) |
|
Hadziabdic E, Albin B, Hjelm K. Arabic-speaking migrants' attitudes, opinions, preferences and past experiences concerning the use of interpreters in healthcare: a postal cross-sectional survey. BMC Res Notes. 2014 Feb 3;7:71. doi: 10.1186/1756-0500-7-71. PMID: 24484628; PMCID: PMC3915075. |
Wrong P (geen cogn. stoornis) |
|
Brijnath B, Gonzalez E, Hlavac J, Enticott J, Woodward-Kron R, LoGiudice D, Low LF, Antoniades J, White J, Hwang K, Lin X, Gilbert AS. The impact of training on communication quality during interpreter-mediated cognitive assessments: Study protocol for a randomized controlled trial. Alzheimers Dement (N Y). 2022 Aug 30;8(1):e12349. doi: 10.1002/trc2.12349. PMID: 36089932; PMCID: PMC9428280. |
Wrong design |
|
Standiford CJ, Nolan E, Harris M, Bernstein SJ. Improving the provision of language services at an academic medical center: ensuring high-quality health communication for limited-English-proficient patients. Acad Med. 2009 Dec;84(12):1693-7. doi: 10.1097/ACM.0b013e3181bf4659. PMID: 19940574. |
Wrong P/I/C |
|
Hilder J, Gray B, Dowell A, Macdonald L, Tester R, Stubbe M. 'It depends on the consultation': revisiting use of family members as interpreters for general practice consultations - when and why? Aust J Prim Health. 2017 Jul;23(3):257-262. doi: 10.1071/PY16053. PMID: 27832830. |
Wrong P (geen cogn. stoornis) |
|
Iyer GK, Paplikar A, Alladi S, Dutt A, Sharma M, Mekala S, Kaul S, Saroja AO, Divyaraj G, Ellajosyula R, Ghosh A, Hooda R, Justus S, Kandukuri R, Khan AB, Mathew R, Mathuranath PS, Menon R, Nandi R, Narayanan J, Nehra A, Padma MV, Pauranik A, Ramakrishnan S, Sabnis P, Sarath L, Shah U, Tripathi M, Sylaja PN, Varma RP, Verma M, Varghese F; ICMR Neurocognitive Tool Box Consortium. Standardising Dementia Diagnosis Across Linguistic and Educational Diversity: Study Design of the Indian Council of Medical Research-Neurocognitive Tool Box (ICMR-NCTB). J Int Neuropsychol Soc. 2020 Feb;26(2):172-186. doi: 10.1017/S1355617719001127. Epub 2019 Dec 12. PMID: 31826780. |
Wrong design |
|
Gitlin LN, Marx K, Stanley IH, Hodgson N. Translating Evidence-Based Dementia Caregiving Interventions into Practice: State-of-the-Science and Next Steps. Gerontologist. 2015 Apr;55(2):210-26. doi: 10.1093/geront/gnu123. Epub 2015 Feb 17. PMID: 26035597; PMCID: PMC4542834. |
Wrong design |
Verantwoording
Autorisatiedatum en geldigheid
Laatst beoordeeld : 15-10-2024
Laatst geautoriseerd : 15-10-2024
Geplande herbeoordeling : 15-10-2029
Algemene gegevens
De ontwikkeling van deze richtlijnmodule werd ondersteund door het Kennisinstituut van de Federatie Medisch Specialisten (www.demedischspecialist.nl/kennisinstituut) en werd gefinancierd uit de Kwaliteitsgelden Medisch Specialisten (SKMS). De financier heeft geen enkele invloed gehad op de inhoud van de richtlijnmodule.
Samenstelling werkgroep
Voor het ontwikkelen van de richtlijnmodules is in 2021 een multidisciplinaire cluster ingesteld. Dit cluster bestaat uit vertegenwoordigers van alle relevante organisaties die betrekking hebben op de zorg voor patiënten met dementie en delier.
Het cluster Cognitieve stoornissen en Dementie bestaat uit drie richtlijnen, zie hier voor de actuele clusterindeling. De stuurgroep bewaakt het proces van modulair onderhoud binnen het cluster. De expertisegroepsleden worden indien nodig gevraagd om hun expertise in te zetten voor een specifieke richtlijnmodule. Het cluster Cognitieve stoornissen en Dementie bestaat uit de volgende personen.
Clusterstuurgroep
- Dhr. Prof. Dr. M.G.M. (Marcel) Olde Rikkert (voorzitter), klinisch geriater, Radboudumc, Nijmegen; NVKG
- Dhr. Prof. Dr. A.R. (Tony) Absalom, anesthesioloog, Universitair Medisch Centrum Groningen, Groningen; NVA
- Dhr. Dr. J.H.J.M. (Jeroen) de Bresser, radioloog, Leids Universitair Medisch Centrum, Leiden; NVvR
- Mevr. J.L.M. (Josephine) Lambregts, patiëntvertegenwoordiger; Alzheimer Nederland
- Mevr. Dr. I.K. (Indrag) Lampe, psychiater, OLVG, Amsterdam; NVvP
- Mevr. Prof. Dr. B.C. (Barbara) van Munster, internist, Universitair Medisch Centrum Groningen, Groningen; NIV
- Dhr. Prof. Dr. E. (Edo) Richard, neuroloog, Radboudumc, Nijmegen; NVN
- Mevr. Prof. Dr. Ir. C. (Charlotte) Teunissen, klinisch chemicus, AmsterdamUMC, Amsterdam; NVKC
- Dhr. Dr. R.A.W. (Ronald) Verhagen, orthopedisch chirurg, Tergooi MC, Hilversum; NOV
Clusterexpertisegroep
- Dhr. Dr. A.P.A. (Auke) Appelman, radioloog, Universitair Medisch Centrum Groningen, Groningen; NVvR
- Dhr. Prof. Dr. B.N.M. (Bart) van Berckel, nucleair geneeskundige, AmsterdamUMC, Amsterdam; NVNG
- Mevr. Dr. R.L. (Rozemarijn) van Bruchem- Visser, internist ouderengeneeskunde, Erasmus Medisch Centrum, Rotterdam; NIV
- Dhr. B.P.H. (Bas) ter Brugge, specialist ouderengeneeskunde, Vilente, Doorwerth; Verenso
- Dhr. J.P.C.M. (Jos) van Campen, klinisch geriater, OLVG, Amsterdam; NVKG
- Dhr. Dr. J.A.H.R. (Jurgen) Claassen, klinisch geriater, Radboudumc, Nijmegen; NVKG
- Dhr. Dr. P.L.J. (Paul) Dautzenberg, klinisch geriater, Jeroen Bosch Ziekenhuis, ‘s-Hertogenbosch; NVKG
- Mevr. Dr. A.M. (Agnies) van Eeghen, Arts voor Verstandelijk Gehandicapten, AmsterdamUMC, Amsterdam; NVAVG
- Mevr. Dr. M.E.A. (Marlise) van Eersel, internist, Universitair Medisch Centrum Groningen, Groningen; NIV
- Mevr. Dr. S. (Sanne) Franzen, neuropsycholoog, Erasmus Medisch Centrum, Rotterdam; NIP
- Mevr. C.M. (Christa) de Geus, neurogeneticus, AmsterdamUMC, Amsterdam; NVKG
- Mevr. M. (Marjolein) Groeneveld, MSc, verpleegkundig Consulent Geriatrie, klinisch epidemioloog, Catharina Ziekenhuis, Eindhoven; V&VN
- Dhr. Dr. R.B. (Rients) Huitema, klinisch neuropsycholoog, Universitair Medisch Centrum Groningen, Groningen; NIP
- Dhr. Drs. A. (Ali) Lahdidioui, internist, HagaZiekenhuis, Den Haag; NIV
- Dhr. Dr. J. (Jules) Lavalaye, nucleair geneeskundige, St.Antonius Ziekenhuis, Nieuwegein/Utrecht; NVNG
- Mevr. Drs. L. (Lieke) Mitrov, ziekenhuisapotheker, Maasstad Ziekenhuis, Rotterdam; NVZA – tijdelijk vervangen door Shirley Sparla.
- Mevr. Dr. M. (Marieke) Perry, huisarts/onderzoeker, Radboudumc, Nijmegen; NHG
- Dhr. Dr. G. (Gerwin) Roks, neuroloog, Elisabeth-TweeSteden Ziekenhuis, Tilburg; NVN
- Mevr. Dr. T.R. (Rikje) Ruiter, internist, Maasstad Ziekenhuis, Rotterdam; NIV
- Mevr. A.J.B.P. (Astrid) Schoonbrood, ergotherapeut, Ergotherapiepraktijk Zuid-Limburg; Ergotherapie Nederland
- Mevr. Dr. N. (Niki) Schoonenboom, neuroloog, Spaarne Gasthuis, Haarlem/Hoofdorp, NVN
- Dhr. Dr. H. (Harro) Seelaar, neuroloog, Erasmus Medisch Centrum, Rotterdam; NVN
- Dhr. Dr. K.S. (Koen) Simons, intensivist-internist, Jeroen Bosch Ziekenhuis, ‘s-Hertogenbosch; NVIC
- Mevr. Drs. M.M.E. (Marlies) Sleegers-Kerkenaar, klinisch geriater, Sint Jans Gasthuis, Weert; NVKG
- Mevr. Drs. S.C.A. (Shirley) Sparla, ziekenhuisapotheker, St. Antonius Ziekenhuis; NVZA – tijdelijke vervanging van Lieke Mitrov.
- Mevr. Dr. P.E. (Petra) Spies, klinisch geriater, Gelre ziekenhuizen, Apeldoorn/Zutphen; NVKG
- Mevr. Dr. Ir. J. (Jenny) T. van der Steen, universitair hoofddocent, LUMC, Leiden en senior onderzoeker, Radboudumc, Nijmegen; persoonlijke titel
- Drs. VCJ (Vera) van Stek-Smits, neuropsycholoog-gezondheidszorgpsycholoog, Basalt Revalidatie HMC Westeinde, Den Haag, NIP
- Mevr. Prof. Dr. M. (Meike) Vernooij, radioloog, Erasmus Medisch Centrum, Rotterdam; NVvR
- Dhr. Dr. E.G.B. (Jort) Vijverberg, neuroloog, AmsterdamUMC, Amsterdam, NVN
- Mevr. Dr. M.A. (Marjolein) Wijngaarden, internist, Leids Universitair Medisch Centrum, Leiden, Leiden; NIV
Met ondersteuning van:
- Mevr. Dr. C.T.J. (Charlotte) Michels, adviseur, Kennisinstituut van de Federatie Medisch Specialisten
- Mevr. Dr. L.C. (Lotte) Houtepen, adviseur, Kennisinstituut van de Federatie Medisch Specialisten
- Mevr. Drs. L.C. (Laura) van Wijngaarden, junior adviseur, Kennisinstituut van de Federatie Medisch Specialisten
Belangenverklaringen
De Code ter voorkoming van oneigenlijke beïnvloeding door belangenverstrengeling is gevolgd. Alle clusterstuurgroepleden en actief betrokken expertisegroepsleden (fungerend als schrijver en/of meelezer bij tenminste één van de geprioriteerde richtlijnmodules) hebben schriftelijk verklaard of zij in de laatste drie jaar directe financiële belangen (betrekking bij een commercieel bedrijf, persoonlijke financiële belangen, onderzoeksfinanciering) of indirecte belangen (persoonlijke relaties, reputatiemanagement) hebben gehad. Gedurende de ontwikkeling of herziening van een richtlijnmodule worden wijzigingen in belangen aan de projectleider doorgegeven. De belangenverklaring wordt opnieuw bevestigd tijdens de commentaarfase. Een overzicht van de belangen van de clusterleden en betrokken expertisegroepsleden en het oordeel over het omgaan met eventuele belangen vindt u in onderstaande tabel. De ondertekende belangenverklaringen zijn op te vragen bij het secretariaat van het Kennisinstituut van de Federatie Medisch Specialisten.
Clusterstuurgroep: Gemelde (neven)functies en belangen stuurgroep
|
Clusterlid |
Functie |
Nevenfuncties |
Gemelde belangen |
Ondernomen actie |
|
Olde Rikkert* |
Hoogleraar Geriatrie, Radboudumc, Nijmegen |
Hoofdredacteur Nederlands Tijdschrift voor Geneeskunde |
Geen; uitsluitend ZonMw gefinancierd onderzoek dat overheidsbelang centraal stelt. Sinds 2017 geen farma-onderzoek meer. |
Geen restrictie |
|
Absalom |
Hoogleraar Anesthesiologie, UMCG, Groningen |
Consultancy werkzaamheden (betaald, alle betalingen aan UMCG) 6. Consultancy werk voor Becton Dickinson (Eysins, Switzerland) en Terumo (Tokyo, Japan) – technische advies over spuitpompen. Niet gerelateerd aan dementie/ MCI/ delier. |
Extern gefinancierd onderzoeken, maar financier heeft geen belangen bij de richtlijn. * Rigel Pharmaceuticals (San Francisco, USA) (PAST) * The Medicines Company (Parsippany, NJ, USA) (PAST) |
Geen restricties, omdat adviseurswerk niet gerelateerd is aan de afbakening van het cluster |
|
De Bresser |
- Neuroradioloog 1.0fte, LUMC, Leiden |
Geen |
Mijn onderzoek wordt mede gesponsord door Alzheimer Nederland. Deze financier heeft geen belang bij bepaalde uitkomsten van de richtlijn. |
Geen restrictie |
|
Lambregts |
Medewerker belangenbehartiging bij Alzheimer Nederland |
Geen |
Geen |
Geen restrictie |
|
Lampe |
Psychiater, OLVG Ziekenhuis, Amsterdam |
Geen |
Geen |
Geen restrictie |
|
Richard |
Neuroloog (1.0fte) Radboudumc, Nijmegen |
- Neuroloog-onderzoeker AmsterdamUMC, locatie AMC, gastvrijheidsaanstelling. |
Geen, uitsluitend onderzoek financiering van non-profit instellingen (e.g. ZonMw, Europese Commissie). |
Geen restrictie |
|
Teunissen |
Hoofd Neurochemisch laboratorium, Afdeling Klinische Chemie, AmsterdamUMC, locatie VUmc, Amsterdam |
*Adviseur voor educatief blad: Mednet Neurologie (betaald). * Alle betalingen zijn aan het AmsterdamUMC. |
Onderzoeksubsidies zijn ontvangen van European Commission (Marie Curie International Training Network, JPND), Health Holland, ZonMW, Alzheimer Drug Discovery Foundation, The Selfridges Group Foundation, Alzheimer Netherlands, Alzheimer Association, Innovative Medicines Initiatives 3TR, EPND, JPND, National MS Society, ABOARD, TAP-dementia. |
Geen restrictie |
|
Van Munster |
* Hoogleraar Interne Geneeskunde, Ouderengeneeskunde/Geriatrie, UMCG, Groningen. *Plaatsvervangend opleider Geriatrie, UMCG, Groningen. |
* 2020 – heden Voorzitter Alzheimer Centrum Groningen (alle functies zijn onbetaald) |
*2022 ZONMw: Young Onset Dementia- INCLUDED: Advance care planning. 2022 ZEGG/ZONMw: "The impact of a comprehensive geriatric assessment including advance care planning in acutely hospitalized frail patients with cognitive disorders: the GOA” study" |
Geen restrictie |
|
Verhagen |
Orthopedisch chirurg/opleider in Tergooi MC |
Geen |
Geen |
Geen restrictie |
Clusterexpertisegroep: Gemelde (neven)functies en belangen expertisegroep
Richtlijn Dementie: Module ‘Screening cognitieve stoornissen - Mensen met een migratieachtergrond’
|
Clusterlid
|
Functie |
Nevenfuncties |
Gemelde belangen |
Ondernomen actie |
|
Franzen |
"Neuropsycholoog afdeling Neurologie Erasmus MC (betaald) "Onderzoeker afdeling Neurologie/Alzheimercentrum Erasmus MC (betaald) "Psycholoog in opleiding tot GZ-psycholoog afdeling Psychiatrie Erasmus MC (betaald)" |
Gastdocent universiteit van Padua, Italië (2022) |
Eenmalige consultingfee ontvangen (2022) van Biogen m.b.t. deelname aan roundtable series over Health Equity.
Aanstelling werd gefinancierd door Health Holland/ ZonMw/ Alzheimer Nederland. De TULIPA studie: ZonMw/ Health Holland De ABOARD studie: ZonMw, Nederlands Dementie Preventie Initiatief. Mede-auteur van een cognitieve test, de VAT (uitgegever: Hogrefe). |
Geen restrictie |
|
Lahdidioui |
Internist ouderengeneeskunde, HagaZiekenhuis, Den Haag. |
*Docent, SOOL Leiden (Specialisme Ouderengeneeskunde Opleiding Leiden), LUMC (betaald). *Voorzitter Associatie Marokkaanse Artsen Nederland (AMAN) (onbetaald). |
Geen |
Geen restrictie |
|
Perry |
* Huisarts, Huisartsenpraktijk Velp, 0.5 fte |
* Auteur hoofdstuk Vergeetachtigheid in Álledaagse klachten 2020 (onkostenvergoeding) * Diverse malen gastspreker bij verschillende Alzheimer Cafés (vrijwillig) |
Projectleider DementieNet (financiering door Giekes-Strijbis fonds, Alzheimer Nederland en ZonMw) |
Geen restrictie |
|
Van Campen |
Geriater, OLVG Amsterdam, nul-aan stelling (geen financiele vergoeding) |
Geen |
Ontvangt royalties van Bohn Stafleu Lochem voor co-auteurschap van een cognitieve test batterij voor oudere migranten met cognitieve klachten (de CCD, cross cultural dementia screening). |
Geen restrictie |
Inbreng patiëntenperspectief
Er werd aandacht besteed aan het patiëntenperspectief door deelname van relevante patiëntenorganisaties aan de need-for-update en/of prioritering. De verkregen input is meegenomen bij het opstellen van de uitgangsvragen, de keuze voor de uitkomstmaten en bij het opstellen van de overwegingen. De conceptrichtlijnmodule is tevens ter commentaar voorgelegd aan alle relevante patiëntenorganisaties in de stuur- en expertisegroep (zie ‘Samenstelling cluster’ onder ‘Verantwoording’) en aan alle patiëntenorganisaties die niet deelnemen aan de stuur- en expertisegroep, maar wel hebben deelgenomen aan de need-for-update (zie ‘Need-for-update’ onder ‘Verantwoording’). De eventueel aangeleverde commentaren zijn bekeken en verwerkt.
Kwalitatieve raming van mogelijke financiële gevolgen in het kader van de Wkkgz
Bij de richtlijnmodule is conform de Wkkgz een kwalitatieve raming uitgevoerd of de aanbevelingen mogelijk leiden tot substantiële financiële gevolgen. Bij het uitvoeren van deze beoordeling is de richtlijnmodule op verschillende domeinen getoetst (zie het stroomschema).
Uit de kwalitatieve raming blijkt dat er waarschijnlijk geen substantiële financiële gevolgen zijn, zie onderstaande tabel.
Module |
Uitkomst raming |
Toelichting |
|
Module ‘Screening cognitieve stoornissen - Mensen met een migratieachtergrond’ |
Geen substantiële financiële gevolgen |
Hoewel uit de toetsing volgt dat de aanbeveling(en) breed toepasbaar zijn (>40.000 patiënten), volgt uit de toetsing dat het overgrote deel van de zorgverleners al aan de norm voldoet, het geen nieuwe manier van zorgverlening betreft, het geen toename in het aantal voltijdsequivalenten of wijziging in het opleidingsniveau van zorgverleners betreft. Er worden daarom geen financiële gevolgen verwacht. |
Werkwijze
AGREE
Deze richtlijnmodule is opgesteld conform de eisen vermeld in het rapport Medisch Specialistische Richtlijnen 3.0 van de adviescommissie Richtlijnen van de Raad Kwaliteit. Dit rapport is gebaseerd op het AGREE II instrument (Appraisal of Guidelines for Research & Evaluation II; Brouwers, 2010).
Need-for-update, prioritering en uitgangsvragen
Tijdens de need-for-update fase en prioriteringsfase (februari, 2023) inventariseerde het cluster de geldigheid van de richtlijnmodules binnen het cluster. Naast de partijen die deelnemen aan de stuur- en expertisegroep zijn hier ook andere stakeholders voor benaderd. Per richtlijnmodule is aangegeven of deze geldig is, herzien moet worden, kan vervallen of moet worden samengevoegd. Ook was er de mogelijkheid om nieuwe onderwerpen aan te dragen die aansluiten bij één (of meerdere) richtlijn(en) behorend tot het cluster. De richtlijnmodules waarbij door één of meerdere partijen werd aangegeven herzien te worden, werden doorgezet naar de prioriteringsronde. Ook suggesties voor nieuwe richtlijnmodules werden doorgezet naar de prioriteringsronde. Afgevaardigden vanuit de partijen in de stuur- en expertisegroep werden gevraagd om te prioriteren (zie ‘Samenstelling cluster’ onder ‘Verantwoording’). Hiervoor werd de RE-weighted Priority-Setting (REPS) – tool gebruikt. De uitkomsten (ranklijst) werd gebruikt als uitgangspunt voor de discussie. Voor de geprioriteerde richtlijnmodules zijn door de het cluster concept-uitgangsvragen herzien of opgesteld en definitief vastgesteld.
Uitkomstmaten
Na het opstellen van de zoekvraag behorende bij de uitgangsvraag inventariseerde het cluster welke uitkomstmaten voor de patiënt relevant zijn, waarbij zowel naar gewenste als ongewenste effecten werd gekeken. Hierbij werd een maximum van acht uitkomstmaten gehanteerd. Het cluster waardeerde deze uitkomstmaten volgens hun relatieve belang bij de besluitvorming rondom aanbevelingen, als cruciaal (kritiek voor de besluitvorming), belangrijk (maar niet cruciaal) en onbelangrijk. Tevens definieerde het cluster tenminste voor de cruciale uitkomstmaten welke verschillen zij klinisch (patiënt) relevant vonden.
Methode literatuursamenvatting
Een uitgebreide beschrijving van de strategie voor zoeken en selecteren van literatuur is te vinden onder ‘Zoeken en selecteren’. Indien mogelijk werd de data uit verschillende studies gepoold in een random-effects model. Review Manager 5.4 werd indien mogelijk gebruikt voor de statistische analyses. De beoordeling van de kracht van het wetenschappelijke bewijs wordt hieronder toegelicht.
Beoordelen van de kracht van het wetenschappelijke bewijs
De kracht van het wetenschappelijke bewijs werd bepaald volgens de GRADE-methode. GRADE staat voor ‘Grading Recommendations Assessment, Development and Evaluation’ (zie http://www.gradeworkinggroup.org/). De basisprincipes van de GRADE-methodiek zijn: het benoemen en prioriteren van de klinisch (patiënt) relevante uitkomstmaten, een systematische review per uitkomstmaat, en een beoordeling van de bewijskracht per uitkomstmaat op basis van de acht GRADE-domeinen (domeinen voor downgraden: risk of bias, inconsistentie, indirectheid, imprecisie, en publicatiebias; domeinen voor upgraden: dosis-effect relatie, groot effect, en residuele plausibele confounding). GRADE onderscheidt vier gradaties voor de kwaliteit van het wetenschappelijk bewijs: hoog, redelijk, laag en zeer laag. Deze gradaties verwijzen naar de mate van zekerheid die er bestaat over de literatuurconclusie, in het bijzonder de mate van zekerheid dat de literatuurconclusie de aanbeveling adequaat ondersteunt (Schünemann, 2013; Hultcrantz, 2017).
Tabel 6. Gradaties voor de kwaliteit van wetenschappelijk bewijs
|
GRADE |
Definitie |
|
Hoog |
|
|
Redelijk |
|
|
Laag |
|
|
Zeer laag |
|
Bij het beoordelen (graderen) van de kracht van het wetenschappelijk bewijs in een richtlijnmodule volgens de GRADE-methodiek spelen grenzen voor klinische besluitvorming een belangrijke rol (Hultcrantz, 2017). Dit zijn de grenzen die bij overschrijding aanleiding zouden geven tot een aanpassing van de aanbeveling. Om de grenzen voor klinische besluitvorming te bepalen moeten alle relevante uitkomstmaten en overwegingen worden meegewogen. De grenzen voor klinische besluitvorming zijn daarmee niet één op één vergelijkbaar met het minimaal klinisch relevant verschil (Minimal Clinically Important Difference, MCID). Met name in situaties waarin een interventie geen belangrijke nadelen heeft en de kosten relatief laag zijn, kan de grens voor klinische besluitvorming met betrekking tot de effectiviteit van de interventie bij een lagere waarde (dichter bij het nuleffect) liggen dan de MCID (Hultcrantz, 2017).
Overwegingen (van bewijs naar aanbeveling)
Om te komen tot een aanbeveling zijn naast (de kwaliteit van) het wetenschappelijke bewijs ook andere aspecten belangrijk en worden meegewogen, zoals aanvullende argumenten uit bijvoorbeeld de biomechanica of fysiologie, waarden en voorkeuren van patiënten, kosten (middelenbeslag), aanvaardbaarheid, haalbaarheid en implementatie. Deze aspecten zijn systematisch vermeld en beoordeeld (gewogen) onder het kopje ‘Overwegingen’ en kunnen (mede) gebaseerd zijn op expert opinion. Hierbij is gebruik gemaakt van een gestructureerd format gebaseerd op het evidence-to-decision framework van de internationale GRADE Working Group (Alonso-Coello, 2016a; Alonso-Coello 2016b). Dit evidence-to-decision framework is een integraal onderdeel van de GRADE methodiek.
Formuleren van aanbevelingen
De aanbevelingen geven antwoord op de uitgangsvraag en zijn gebaseerd op het beschikbare wetenschappelijke bewijs en de belangrijkste overwegingen, en een weging van de gunstige en ongunstige effecten van de relevante interventies. De kracht van het wetenschappelijk bewijs en het gewicht dat door het cluster wordt toegekend aan de overwegingen, bepalen samen de sterkte van de aanbeveling. Conform de GRADE-methodiek sluit een lage bewijskracht van conclusies in de systematische literatuuranalyse een sterke aanbeveling niet a priori uit, en zijn bij een hoge bewijskracht ook zwakke aanbevelingen mogelijk (Agoritsas, 2017; Neumann, 2016). De sterkte van de aanbeveling wordt altijd bepaald door weging van alle relevante argumenten tezamen. Het cluster heeft bij elke aanbeveling opgenomen hoe zij tot de richting en sterkte van de aanbeveling zijn gekomen.
In de GRADE-methodiek wordt onderscheid gemaakt tussen sterke en zwakke (of conditionele) aanbevelingen. De sterkte van een aanbeveling verwijst naar de mate van zekerheid dat de voordelen van de interventie opwegen tegen de nadelen (of vice versa), gezien over het hele spectrum van patiënten waarvoor de aanbeveling is bedoeld. De sterkte van een aanbeveling heeft duidelijke implicaties voor patiënten, behandelaars en beleidsmakers (zie onderstaande tabel). Een aanbeveling is geen dictaat, zelfs een sterke aanbeveling gebaseerd op bewijs van hoge kwaliteit (GRADE gradering HOOG) zal niet altijd van toepassing zijn, onder alle mogelijke omstandigheden en voor elke individuele patiënt.
Tabel 7. Sterkte van de aanbevelingen
|
Implicaties van sterke en zwakke aanbevelingen voor verschillende richtlijngebruikers |
||
|
|
Sterke aanbeveling |
Zwakke (conditionele) aanbeveling |
|
Voor patiënten |
De meeste patiënten zouden de aanbevolen interventie of aanpak kiezen en slechts een klein aantal niet. |
Een aanzienlijk deel van de patiënten zouden de aanbevolen interventie of aanpak kiezen, maar veel patiënten ook niet. |
|
Voor behandelaars |
De meeste patiënten zouden de aanbevolen interventie of aanpak moeten ontvangen. |
Er zijn meerdere geschikte interventies of aanpakken. De patiënt moet worden ondersteund bij de keuze voor de interventie of aanpak die het beste aansluit bij zijn of haar waarden en voorkeuren. |
|
Voor beleidsmakers |
De aanbevolen interventie of aanpak kan worden gezien als standaardbeleid. |
Beleidsbepaling vereist uitvoerige discussie met betrokkenheid van veel stakeholders. Er is een grotere kans op lokale beleidsverschillen. |
Organisatie van zorg
Bij de ontwikkeling van de richtlijnmodule is expliciet aandacht geweest voor de organisatie van zorg: alle aspecten die randvoorwaardelijk zijn voor het verlenen van zorg (zoals coördinatie, communicatie, (financiële) middelen, mankracht en infrastructuur). Randvoorwaarden die relevant zijn voor het beantwoorden van deze specifieke uitgangsvraag zijn genoemd bij de overwegingen. Meer algemene, overkoepelende, of bijkomende aspecten van de organisatie van zorg worden behandeld in de richtlijnmodule Organisatie van zorg.
Commentaar- en autorisatiefase
De conceptrichtlijnmodule werd voorgelegd aan alle partijen die benaderd zijn voor de need-for-update fase. De commentaren werden verzameld en besproken met het cluster. Naar aanleiding van de commentaren werd de conceptrichtlijnmodule aangepast en definitief vastgesteld door het cluster. De definitieve richtlijnmodule werd ter autorisatie of goedkeuring voorgelegd aan de partijen die beschreven staan bij ‘Initiatief en autorisatie’ onder ‘Verantwoording’.
Literatuur
Agoritsas T, Merglen A, Heen AF, Kristiansen A, Neumann I, Brito JP, Brignardello-Petersen R, Alexander PE, Rind DM, Vandvik PO, Guyatt GH. UpToDate adherence to GRADE criteria for strong recommendations: an analytical survey. BMJ Open. 2017 Nov 16;7(11):e018593. doi: 10.1136/bmjopen-2017-018593. PubMed PMID: 29150475; PubMed Central PMCID: PMC5701989.
Alonso-Coello P, Schünemann HJ, Moberg J, Brignardello-Petersen R, Akl EA, Davoli M, Treweek S, Mustafa RA, Rada G, Rosenbaum S, Morelli A, Guyatt GH, Oxman AD; GRADE Working Group. GRADE Evidence to Decision (EtD) frameworks: a systematic and transparent approach to making well informed healthcare choices. 1: Introduction. BMJ. 2016 Jun 28;353:i2016. doi: 10.1136/bmj.i2016. PubMed PMID: 27353417.
Alonso-Coello P, Oxman AD, Moberg J, Brignardello-Petersen R, Akl EA, Davoli M, Treweek S, Mustafa RA, Vandvik PO, Meerpohl J, Guyatt GH, Schünemann HJ; GRADE Working Group. GRADE Evidence to Decision (EtD) frameworks: a systematic and transparent approach to making well informed healthcare choices. 2: Clinical practice guidelines. BMJ. 2016 Jun 30;353:i2089. doi: 10.1136/bmj.i2089. PubMed PMID: 27365494.
Brouwers MC, Kho ME, Browman GP, Burgers JS, Cluzeau F, Feder G, Fervers B, Graham ID, Grimshaw J, Hanna SE, Littlejohns P, Makarski J, Zitzelsberger L; AGREE Next Steps Consortium. AGREE II: advancing guideline development, reporting and evaluation in health care. CMAJ. 2010 Dec 14;182(18):E839-42. doi: 10.1503/cmaj.090449. Epub 2010 Jul 5. Review. PubMed PMID: 20603348; PubMed Central PMCID: PMC3001530.
Hultcrantz M, Rind D, Akl EA, Treweek S, Mustafa RA, Iorio A, Alper BS, Meerpohl JJ, Murad MH, Ansari MT, Katikireddi SV, Östlund P, Tranæus S, Christensen R, Gartlehner G, Brozek J, Izcovich A, Schünemann H, Guyatt G. The GRADE Working Group clarifies the construct of certainty of evidence. J Clin Epidemiol. 2017 Jul;87:4-13. doi: 10.1016/j.jclinepi.2017.05.006. Epub 2017 May 18. PubMed PMID: 28529184; PubMed Central PMCID: PMC6542664.
Medisch Specialistische Richtlijnen 2.0 (2012). Adviescommissie Richtlijnen van de Raad Kwalitieit. http://richtlijnendatabase.nl/over_deze_site/over_richtlijnontwikkeling.html
Neumann I, Santesso N, Akl EA, Rind DM, Vandvik PO, Alonso-Coello P, Agoritsas T, Mustafa RA, Alexander PE, Schünemann H, Guyatt GH. A guide for health professionals to interpret and use recommendations in guidelines developed with the GRADE approach. J Clin Epidemiol. 2016 Apr;72:45-55. doi: 10.1016/j.jclinepi.2015.11.017. Epub 2016 Jan 6. Review. PubMed PMID: 26772609.
Schünemann H, Brożek J, Guyatt G, et al. GRADE handbook for grading quality of evidence and strength of recommendations. Updated October 2013. The GRADE Working Group, 2013. Available from http://gdt.guidelinedevelopment.org/central_prod/_design/client/handbook/handbook.html.
Zoekverantwoording
Zoekacties zijn opvraagbaar. Neem hiervoor contact op met de Richtlijnendatabase.