Identificatie van kwetsbaarheid bij ouderen

Publicatiedatum: 25-06-2026

Beoordeeld op geldigheid: 25-06-2026

Uitgangsvraag

Welke screeningsinstrumenten zijn het meest geschikt om ouderen met een verhoogd risico op negatieve uitkomsten waaronder functionele achteruitgang, morbiditeit en mortaliteit op te sporen, en bij wie dus een geriatrisch assessment (GA) of een comprehensive geriatric assessment (CGA) een meerwaarde heeft?

Aanbeveling

Aanbeveling-1

Implementeer screeningsinstrumenten om het risico op negatieve uitkomsten waaronder functionele achteruitgang en mortaliteit in te schatten bij oudere patiënten zowel poliklinisch als in risicovolle settingen zoals de SEH en bij opname.

Maak een risico inschatting van negatieve uitkomsten waaronder functionele achteruitgang, morbiditeit en mortaliteit bij oudere patiënten op de polikliniek:

als er een plan is voor een behandeling met hoog risico op complicaties;
als er een plan is voor een behandeling met een hoog risico op functionele en/of cognitieve achteruitgang;
als er een plan is voor een behandeling met een potentieel beperkte opbrengst; of
als er twijfel is over de belastbaarheid van de patiënt.

Inventariseer of een patiënt in aanmerking zou kunnen komen voor een GA of CGA middels screenende vragen/instrumenten waarbij onder andere de volgende domeinen van belang zijn: somatisch, psychisch, sociaal, en functioneel.

Aanbeveling-2 subgroep SEH

Gebruik op de SEH een gevalideerd instrument, bij voorkeur de APOP, ISAR-HP of VMS, om het risico op functionele achteruitgang en mortaliteit in te schatten.

Aanbeveling-3 subgroep klinische setting

Gebruik in de kliniek de VMS-vragen of een ander gevalideerd screeningsinstrument om het risico op functionele achteruitgang in te schatten.

Aanbeveling-4 subgroep poliklinische setting

Gebruik op de polikliniek een instrument dat passend is voor de patiëntengroep, bijvoorbeeld de G8 voor patiënten met een oncologische diagnose, om het risico op functionele achteruitgang in te schatten.

Overwegingen

Balans tussen gewenste en ongewenste effecten

Er is niet gezocht naar studies die het directe effect van de toepassing van de APOP-screener, ISAR-HP-screener, VMS-screener, G8 en de Clinical Frailty Scale (CFS) op relevante uitkomstmaten (functionele achteruitgang, morbiditeit en mortaliteit) onderzochten, omdat het bij het cluster bekend was dat deze studies niet zijn uitgevoerd in een Europese setting. Daardoor is er geen informatie bekend over het directe effect van het gebruik van deze instrumenten op relevante uitkomstmaten.

Er is wel literatuuronderzoek verricht naar het discriminerend vermogen en kalibratievermogen van de screeningsinstrumenten om een samengestelde uitkomstmaat van functionele achteruitgang en mortaliteit te voorspellen in oudere patiënten die zich presenteren in een Europees ziekenhuis. Er zijn drie studies gevonden en uitgewerkt die de prestaties van de APOP-screener, ISAR-HP-screener en de VMS-screener onderzochten in oudere patiënten die zich presenteerden op een SEH in Nederland (De Gelder, 2018; Schuijt, 2020; Van Dam, 2021).

De APOP‑2018‑screener, de APOP‑2016‑screener (voor het gecombineerde eindpunt functionele achteruitgang of mortaliteit) en de ISAR‑HP‑screener laten bruikbare discriminatie zien voor het identificeren van patiënten met een verhoogd risico op functionele achteruitgang en mortaliteit op de SEH. De mate van zekerheid van dit bewijs is matig (GRADE: moderate).

Voor de APOP‑2016‑screener voor mortaliteit als afzonderlijke uitkomstmaat is de discriminatie mogelijk bruikbaar, maar de zekerheid van het bewijs is laag (GRADE: low).

Voor de VMS‑screener zijn de bevindingen minder consistent. De discriminatie varieert van beperkt tot mogelijk bruikbaar, en de zekerheid van het bewijs is laag (GRADE: low). Daardoor kan geen eenduidige conclusie worden getrokken over de bruikbaarheid van dit instrument voor het voorspellen van functionele achteruitgang en mortaliteit op de SEH.

Voor geen van de instrumenten waren de beschikbare gegevens voldoende om conclusies te trekken over de kalibratie. Zie tabel 1 voor een overzicht van de conclusies. Voor de andere instrumenten of prestaties in andere populaties werd geen literatuur gevonden die voldeed aan de inclusiecriteria.

Tabel 1. Conclusies voor prestaties van screeners t.a.v. het voorspellen van een samengestelde uitkomstmaat van functionele achteruitgang en mortaliteit in oudere patiënten die zich presenteren op een SEH in Nederland

	APOP 2018-screener voor functionele achteruitgang of mortaliteit	APOP 2016-screener. Voor functionele achteruitgang of mortaliteit	APOP 2016-screener voor mortaliteit	ISAR-HP-screener	VMS-screener
Discriminatie	Mogelijk bruikbaar (matige bewijskracht)	Mogelijk bruikbaar (matige bewijskracht)	Mogelijk bruikbaar (lage bewijskracht)	Mogelijk bruikbaar (matige bewijskracht)	Resultaten variëren van beperkt tot mogelijk bruikbaar (lage bewijskracht)
Kalibratie	Geen conclusie	Geen conclusie	Geen conclusie	Geen conclusie	Geen conclusie

Bij gebrek aan bewijs voor de klinische- en poliklinische setting baseert het cluster zich op praktische overwegingen die spelen bij het gebruik van dergelijk instrumenten in de praktijk, zoals tijdsduur en instrumenten waar in Nederland veel ervaring mee is. De effecten van eventuele implementatie van screeningstesten op bijvoorbeeld de effectiviteit van een GA of CGA zijn op dit ogenblik nog onvoldoende onderzocht maar zullen moeten worden meegenomen worden in toekomstig onderzoek.

SEH

De APOP-screening (acuut presenterende oudere patiënt) is speciaal ontwikkeld in de Nederlandse setting met als doel om de uitkomsten te verbeteren van acuut zieke ouderen door de zorg op de SEH te optimaliseren en de juiste vervolgzorg in te schakelen (de Gelder, 2016; De Gelder, 2018; van Dam 2021). Genoemde studies beschrijven ook een prognostische waarde van het inzetten van dit screeningsinstrument. Het APOP-programma geeft zorgverleners meer inzicht in de individuele situatie en kwetsbaarheid van de oudere patiënt. Daarmee kunnen zij rekening houden in de zorg aan de oudere patiënt en zo zorg op maat leveren. Nadeel van de APOP kan zijn dat er een redelijk hoge specificiteit is waardoor een deel van de patiënten met potentiële kwetsbaarheid gemist wordt. De ISAR is één van de meest onderzochte, en een veel gebruikt screeningsinstrument (Van Dam, 2021). Daarnaast is de ISAR ook voor de Nederlandse situatie gevalideerd om ouderen met een verhoogd risico op functieverlies op te sporen (Hoogerduijn, 2010), en daarom kan de ISAR ook gebruikt worden als screeningsinstrument. De ISAR- HP (Van Dam, 2021) en de VMS (Schuijt, 2020; van Dam, 2021) hebben eveneens een prognostische waarde; het heeft een onderscheidend vermogen om patiënten met een slechte dan wel een goede uitkomst op het gebied van functionaliteit en mortaliteit te identificeren. Hoewel in één studie het onderscheidend vermogen van de VMS als screeningsinstrument op de SEH klein was. Het doel van de screeningsinstrumenten is om het risico op negatieve uitkomsten zoals functieverlies en mortaliteit te verlagen en daarmee de prognose te verbeteren middels het inzetten van gerichte interventies.

Andere screeningsinstrumenten die in Nederland lokaal gebruikt worden op de SEH zijn bijvoorbeeld de IKOS (Inschatting Kwetsbare Oudere op de SEH) en de 5-GEM-vragen.

De 5-GEM-vragen worden veelal gebruikt door de GEM-teams (Geriatric Emergency Medicine), die in steeds meer ziekenhuizen worden geïmplementeerd. Het GEM-team is een gespecialiseerd multidisciplinair team op de SEH dat de zorg voor kwetsbare ouderen (70+) optimaliseert. In de praktijk blijkt dat dit leidt tot de juiste zorg op de juiste plek, minder onnodige opnames en een kortere ligduur. De teams worden door de IGJ gezien als een waardevolle preventieve maatregel in de acute zorg voor kwetsbare ouderen. Momenteel loopt er validatieonderzoek naar de GEM-screeningsvragen (zie kennisvraag).

Klinisch

De VMS-vragen met betrekking tot identificatie van kwetsbaarheid bij ouderen worden momenteel breed toegepast op de klinische afdelingen in Nederlandse ziekenhuizen (Oud, 2019). Dit heeft geleid tot een verhoogde alertheid bij artsen en verpleegkundigen op vallen, ondervoeding, delier en fysieke beperkingen. De VMS-vragen zijn initieel ontwikkeld om het risico op individuele geriatrische/ouderengeneeskundige problemen op te sporen en niet om deze in te zetten als instrument om ouderen te selecteren die baat kunnen hebben bij een CGA. Er is echter wel behoefte aan een screeningsinstrument om ouderen te selecteren die baat kunnen hebben bij een GA of CGA.

De VMS-vragen worden in veel Nederlandse ziekenhuizen bij opname gebruikt om het risico op vallen, delier, ondervoeding en fysieke beperkingen in kaart te brengen en gerichte interventies te initiëren als er sprake is van een (risico) op één of meer geriatrische problemen bij een individuele patiënt. Zo wordt bij een verhoogd valrisico de fysiotherapeut in consult gevraagd. De onlangs herziene richtlijn Ondervoeding en sarcopenie bij ouderen met een kwetsbare gezondheid geeft aan dat er meer bewijs is voor gebruik van de Mini Nutritional Assessment – Short Form (MNA SF) dan voor de Short Nutritional Assessment Questionnaire (SNAQ) of Malnutrition Universal Screening Tool (MUST) om te screenen op ondervoeding.

Poliklinisch

Het cluster kan zich erin vinden dat voor verschillende diagnosegroepen waar veel oudere patiënten zijn en een intensieve behandeling nodig is, een screeningsinstrument gebruikt wordt om kwetsbaarheid te signaleren. Welk type instrument gebruikt wordt, is verschillend per patiëntengroep. Zie hiervoor module Geriatrisch assessment (GA).

Een grote patiëntenpopulatie betreft de patiënten met een oncologische diagnose. In deze populatie worden in Nederland de VMS-vragen en de G8 veel gebruikt (Oud, 2019). De resultaten uit de studie van Souwer (2019) laten zien dat de VMS-vragen in een populatie ouderen met colorectaal carcinoom postoperatieve complicaties, heropnamen binnen 30 dagen en opname op een revalidatieafdeling voorspellen. De G8 is een vragenlijst bestaande uit 8 vragen, ontwikkeld speciaal voor de oudere patiënt met kanker. Afname duurt circa 2 minuten. De G8 voorspelt chemotoxiciteit alsmede survival. Binnen een groep oncologische patiënten die in opzet curatieve (chemo) radiatie kregen, met een gemiddelde leeftijd van 72 jaar, bleek de overleving na 2,5 jaar 87% binnen de groep met een hoge G8 score en 55% binnen de groep met een lage G8 score (Middelburg, 2021). De G8 heeft een sensitiviteit van circa 80% en een specificiteit van circa 60%. De G8 is een bruikbaar instrument gebleken voor de oncologische populatie. Het cluster kan zich erin vinden om ook voor andere patiëntgroepen in de poliklinische setting gebruik te maken van de multi-domeincriteria van de G8 voor inschatting van het risico op functionele achteruitgang. Aanvullend onderzoek zal moeten uitwijzen of de G8 inderdaad ook voor andere patiëntgroepen gebruikt kan worden voor identificatie van het risico op negatieve uitkomsten waaronder functionele achteruitgang, morbiditeit en mortaliteit. Cognitieve problemen worden niet geïdentificeerd met de G8 terwijl cognitie wel een belangrijke voorspeller is voor negatieve uitkomsten waaronder functionele achteruitgang, morbiditeit en mortaliteit. Een aanvullende analyse van de cognitie is daarom gewenst.

Andere poliklinisch patiëntengroepen zijn bijvoorbeeld patiënten die in aanmerking komen voor een Transcatheter Aortic Valve Implantation (TAVI). In deze populatie wordt in Nederland vaak de G8 vragenlijst gebruikt.

De Clinical Frailty Scale (CFS) kan onder andere worden toegepast bij patiënten met nierfalen. De CFS is een 9-punts screeningstool die verschillende domeinen beoordeeld, waaronder functioneren (ADL en IADL). Een scoping review van Church (2020) laat zien dat de CFS in verschillende settingen wordt gebruikt (zowel klinisch, poliklinisch als op de SEH). De resultaten van de CFS zijn predictief voor: mortaliteit (87% van de studies), comorbiditeit (73% van de studies), complicaties (alles studies), opnameduur (75% van de studies), vallen (71% van de studies), cognitie (94% van de studies), dagelijks functioneren (91% van de studies) en andere kwetsbaarheidsscores (94% van de studies). In de literatuur worden verschillende afkapwaarden gebruikt; een afkapwaarde van ≥5 werd veruit het meeste gerapporteerd (68% van de studies). Daarmee lijkt de CFS in theorie een instrument dat in staat is om negatieve uitkomsten waaronder functionele achteruitgang, morbiditeit of mortaliteit te onderscheiden. Het kan worden gebruikt voor de screening van patiënten met nierfalen (Demirhan, 2025). In de praktijk wordt de CFS niet zeer frequent gebruikt voor screening in de verschillende settingen.

Het cluster is van mening dat er in alle bovenstaande patiëntenpopulaties een screeningsinstrument zou moeten worden ingezet om patiënten met risico(‘s) te identificeren. Door te screenen kan een efficiëntieslag worden gemaakt. Hierdoor kan een selectie worden gemaakt van ouderen die vitaal zijn waar de reguliere behandeling gevolgd kan worden, van ouderen die baat kunnen hebben bij gerichte interventies en van ouderen die baat kunnen hebben bij een GA of CGA.

Kwaliteit van bewijs

De overall kwaliteit van bewijs kon niet worden vastgesteld, omdat er geen studies zijn gevonden die het effect van het gebruik van screeningsinstrumenten, om functionele achteruitgang of mortaliteit te voorspellen, op patiëntrelevante uitkomstmaten onderzochten. Dit betekent dat we zeer onzeker zijn over het geschatte effect van het gebruik van deze screeningsinstrumenten op de patiëntrelevante uitkomstmaten.

Waarden en voorkeuren van patiënten (en eventueel hun naasten/verzorgers)

Ouderen die in de kliniek, polikliniek of op de SEH worden opgenomen, hebben er baat bij wanneer zij gescreend worden op negatieve uitkomsten. Op deze manier kan het risico op functieverlies worden beperkt. De verwachte voordelen van een dergelijke screening worden als groot ingeschat. Daarbij worden er geen ongewenste effecten voorzien; het cluster gaat ervan uit dat de screening en de op grond daarvan ingezette gerichte interventies geen nadelige gevolgen met zich meebrengen.

Kostenaspecten

De verschillende screeningsinstrumenten hebben naar verwachting geen grote impact op kosten, omdat screeningsinstrumenten eenvoudig ingebed kunnen worden, of al ingebed zijn, in de gebruikte settingen.

Gelijkheid ((health) equity/equitable)

De inzet van verschillende screeningsinstrumenten heeft naar verwachting geen grote impact op gezondheidsgelijkheid.

Aanvaardbaarheid

Ethische aanvaardbaarheid

De inzet van de verschillende screeningsinstrumenten lijkt aanvaardbaar voor de betrokkenen. Het cluster voorziet geen ethische bezwaren.

Duurzaamheid

Bij de screening op negatieve uitkomsten spelen duurzaamheidsaspecten geen rol.

Haalbaarheid

Het gevolg van de aanbeveling is niet dat dit tot een toename van het jaarlijkse aantal screenings zal leiden. De aanbevelingen hebben betrekking op de keuze voor specifieke screeningsinstrumenten, en beschrijven niet de frequentie van screening. Het beslag op middelen en menskracht lijkt gezien de verwachte gezondheidswinst aanvaardbaar.

De prognostiek lijkt haalbaar. De prognostiek is over het algemeen al standaardzorg in de praktijk. Er is geen verschil in haalbaarheid gebleken tussen de verschillende instrumenten.

Rationale van aanbeveling-1:

Het is in alle ziekenhuissettingen van belang ouderen met een kwetsbare gezondheid te identificeren om negatieve uitkomsten zoals functieverlies en mortaliteit te kunnen voorkomen.

Rationale van aanbeveling-2 subgroep SEH: weging van argumenten voor en tegen de instrumenten

Uit de literatuur blijkt dat de Acute Presenting Older Patient (APOP), Identification of Seniors At Risk – Hospitalized Patients (ISAR-HP), Veiligheidsmanagementsysteem (VMS), en de Geriatric 8 (G8) als screeningsinstrument kunnen worden gebruikt om het risico op functionele achteruitgang en mortaliteit te inventariseren bij patiënten ≥65 jaar op de SEH.

Rationale van aanbeveling-3 subgroep klinische setting: weging van argumenten voor en tegen de instrumenten

De VMS is een screeningslijst waarmee in de Nederlandse ziekenhuizen veel ervaring is opgedaan bij klinische patiënten. Het wordt gebruikt om het risico op vallen, delier, ondervoeding en fysieke beperkingen in kaart te brengen en gerichte interventies te initiëren als hiervan sprake is.

Rationale van aanbeveling-4 subgroep poliklinische setting: weging van argumenten voor en tegen de instrumenten

De G8 is een screeningsinstrument, dat poliklinisch bij patiënten met een oncologische diagnose kan worden afgenomen in slechts 2 minuten en bruikbaar is gebleken voor het maken van een inschatting van het risico op functionele achteruitgang.

Onderbouwing

In various healthcare settings - such as the emergency department, inpatient care, and outpatient clinics - it is important to identify older patients who are at increased risk of adverse outcomes, including functional decline, morbidity, and mortality. Several screening tools are available for this purpose. These tools must have a high predictive value to accurately detect frail patients, allowing for a Geriatric Assessment (GA) or Comprehensive Geriatric Assessment (CGA) or) to be performed when appropriate.

Additionally, when a high risk of adverse outcomes is identified through these screening instruments, targeted interventions can be implemented to help prevent these outcomes as much as possible. The degree of frailty can also be taken into account when making treatment decisions.

At present, it remains unclear which screening instrument offers the best predictive value of adverse outcomes in older patients in various healthcare settings.

Summary of Findings

APOP 2018-screener (for functional decline or mortality)

Patients: Elderly patients (>65 years) in a European hospital setting (i.e. emergency department, outpatient, inpatient)

Index instrument: APOP 2018-screener for functional decline or mortality

Comparator instrument: Not applicable

Timing: Timepoint using the instrument: patients receiving hospital care

Timepoint of prediction: at least 3 months follow-up

Setting: Receiving hospital care (emergency department, inpatient, outpatient)

Outcome (performance measures)

Study results and measurements

Certainty of the Evidence

(Quality of evidence)

Conclusions

Discrimination:
AUC

De Gelder (2018)

0.71

(95% CI 0.69 to 0.73)

Based on data from 2629 participants in one study

Moderate

Due to high risk of bias¹

The APOP-screener for functional decline or mortality likely results in possibly helpful discrimination when predicting a composite outcome of functional decline in elderly patients presenting at an emergency department in the Netherlands.

(de Gelder, 2018)

Calibration:
Intercept or slope of the calibration plot; O:E ratio

De Gelder (2018)

Observed probabilities were in line with expected probabilities

Based on data from 2629 participants in one study

No grade

(No evidence was found)

The calibrative performance of the APOP 2018-screener for functional decline or mortality predicting a composite outcome of functional decline in elderly patients presenting at an emergency department in the Netherlands could not be graded as no quantitative outcome measures were reported.

(de Gelder, 2018)

_^1._{Risk of bias: high (-1 level). Due to a selective study population.}

APOP 2016-screener (for functional decline or mortality)

Patients: Elderly patients (>65 years) in a European hospital setting (i.e. emergency department, outpatient, inpatient)

Index instrument: APOP 2016-screener for functional decline or mortality

Comparator instrument: Not applicable

Timing: Timepoint using the instrument: patients receiving hospital care

Timepoint of prediction: at least 3 months follow-up

Setting: Receiving hospital care (emergency department, inpatient, outpatient)

Outcome (performance measures)

Study results and measurements

Certainty of the Evidence

(Quality of evidence)

Conclusions

Discrimination:
AUC

Van Dam (2021)

0.72
(95% CI 0.69 to 0.76)

Based on data from 889 participants in two studies

Moderate

Due to high risk of bias¹

The APOP 2016-screener for functional decline or mortality likely results in possibly helpful discrimination when predicting a composite outcome of functional decline in elderly patients presenting at an emergency department in the Netherlands.

(van Dam, 2021)

Calibration:
Intercept or slope of the calibration plot; O:E ratio

Van Dam (2021)

Reasonable calibration based on visual inspection of the calibration plot

Based on data from 889 participants in two studies

No GRADE

(No evidence was found)

The calibrative performance of the APOP 2016-screener for functional decline or mortality predicting a composite outcome of functional decline in elderly patients presenting at an emergency department in the Netherlands could not be graded as no quantitative outcome measures were reported.

(van Dam, 2021)

_^1._{Risk of bias: high (-1 level). Due to a selective study population.}

APOP 2016-screener (for mortality)

Patients: Elderly patients (>65 years) in a European hospital setting (i.e. emergency department, outpatient, inpatient)

Index instrument: APOP 2016-screener for mortality

Comparator instrument: Not applicable

Timing: Timepoint using the instrument: patients receiving hospital care

Timepoint of prediction: at least 3 months follow-up

Setting: Receiving hospital care (emergency department, inpatient, outpatient)

Outcome (performance measures)

Study results and measurements

Certainty of the Evidence

(Quality of evidence)

Conclusions

Discrimination:
AUC

0.62
(95% CI 0.58 to 0.62)

Based on data from 889 participants in one study

Low

Due to high risk of bias, due to serious imprecision¹

The APOP 2016-screener for mortality may result in possibly helpful discrimination when predicting a composite outcome of functional decline in elderly patients presenting at an emergency department in the Netherlands.

(van Dam, 2021)

Calibration:
Intercept or slope of the calibration plot; O:E ratio

Van Dam (2021)

Poor calibration based on visual inspection of the calibration plot

Based on data from 889 participants in two studies

No GRADE

(No evidence was found)

The calibrative performance of the APOP 2016-screener for mortality predicting a composite outcome of functional decline in elderly patients presenting at an emergency department in the Netherlands could not be graded as no quantitative outcome measures were reported.

(van Dam, 2021)

_{^1. Risk of bias: high (-1 level). Due to a selective study population. Imprecision: serious (-1 level). Confidence interval crosses the border of clinical relevance for poor discrimination.}

ISAR-HP-screener

Patients: Elderly patients (>65 years) in a European hospital setting (i.e. emergency department, outpatient, inpatient)

Index instrument: ISAR-HP-screener

Comparator instrument: Not applicable

Timing: Timepoint using the instrument: patients receiving hospital care

Timepoint of prediction: at least 3 months follow-up

Setting: Receiving hospital care (emergency department, inpatient, outpatient)

Outcome (performance measures)

Study results and measurements

Certainty of the Evidence

(Quality of evidence)

Conclusions

Discrimination:
AUC

0.72
(95% CI 0.68 to 0.76)

Based on data from 889 participants in one study

Moderate

Due to high risk of bias¹

The ISAR-HP-screener likely results in possibly helpful discrimination when predicting a composite outcome of functional decline in elderly patients presenting at an emergency department in the Netherlands.

(van Dam, 2021)

Calibration:
Intercept or slope of the calibration plot; O:E ratio

Van Dam (2021)

Poor calibration based on visual inspection of the calibration plot

Based on data from 889 participants in two studies

No GRADE

(No evidence was found)

The calibrative performance of the ISAR-HP-screener predicting a composite outcome of functional decline in elderly patients presenting at an emergency department in the Netherlands could not be graded as no quantitative outcome measures were reported.

(van Dam, 2021)

_^1._{Risk of bias: high (-1 level). Due to a selective study population.}

Patients: Elderly patients (>65 years) in a European hospital setting (i.e. emergency department, outpatient, inpatient)

Index instrument: VMS-screener

Comparator instrument: Not applicable

Timing: Timepoint using the instrument: patients receiving hospital care

Timepoint of prediction: at least 3 months follow-up

Setting: Receiving hospital care (emergency department, inpatient, outpatient)

Outcome (performance measures)

Study results and measurements

Certainty of the Evidence

(Quality of evidence)

Conclusions

Discrimination:
AUC

Van Dam (2021)

0.70
(95% CI 0.66 to 0.73)

Schuijt (2020)

0.54

(95% CI 0.46 to 0.62)

Based on data from 1138 participants in two studies

Low GRADE

Due to high risk of bias, due to inconsistency¹

The VMS-screener may result in poor or possibly helpful discrimination when predicting a composite outcome of functional decline in elderly patients presenting at an emergency department in the Netherlands.

(Schuijt, 2018; van Dam, 2021)

Calibration:
Intercept or slope of the calibration plot; O:E ratio

Van Dam (2021)

Reasonable calibration based on visual inspection of the calibration plot

Based on data from 889 participants in two studies

No GRADE

(No evidence was found)

The calibrative performance of the VMS-screener for functional decline predicting a composite outcome of functional decline in elderly patients presenting at an emergency department in the Netherlands could not be graded as no quantitative outcome measures were reported.

(van Dam, 2021)

_{^1. Risk of bias: high (-1 level). Due to a selective study population. Inconsistency (-1 level). Due to inconsistent study results.}

For G8 no studies were selected.

CFS

For Clinical Frailty Scale no studies were selected.

Description of studies

A total of three studies were included in the analysis of the literature. Important study characteristics and results are summarized in table 4. The assessment of the risk of bias is summarized in the risk of bias tables (under the tab ‘Evidence tabellen’).

Van Dam (2021) and Schuijt (2020) performed an external validation study focusing on the VMS in patients in Dutch emergency departments. In the study of Van Dam (2021), all patients aged ≥70 years attending the emergency department in the presence of the researchers were screened for eligibility. Exclusion criteria were high-urgency status (code red according to the Manchester Triage System), a language barrier, and the inability to give informed consent. Schuijt (2020) included patients aged 70 years or older at the emergency department of Gelre Hospital Apeldoorn presenting for the following specialties: internal medicine, geriatric medicine, general surgery (including trauma), orthopedic surgery, gastroenterology, pulmonary medicine, and urology. Inclusion hours were between 10AM and 7PM during weekdays. Exclusion criteria were logistical impossibility to include patient, language barrier (patient not proficient in Dutch or English), severe cognitive impairment with no proxy present, and no permission to approach the patient by their attending nurse or physician.

Van Dam (2021) and De Gelder (2018) performed an external validation study focusing on the APOP1 (functional decline) and APOP2 (mortality) in patients in Dutch emergency departments. De Gelder (2018) included patients aged 70 years and over who were visiting the emergency departments of four Dutch hospitals. Exclusion criteria were red triage category, an unstable medical condition, no permission of nurse or physician to approach the patient, a language barrier, and impossibility to obtain informed consent.

Van Dam (2021) performed an external validation study focusing on the ISAR-HP (ISAR for hospitalized patients) screener in patients in Dutch emergency departments.

Note that Van Dam (2021) also compared the three above mentioned scales in the same population.

For G8 and Clinical Frailty Scale no studies were selected.

Table 4. Characteristics of included studies

Study	Participants	Instrument	Follow-up	Outcome measures	Comments	Risk of bias (per outcome measure)*
Van Dam (2021)	N at baseline 889 Age (mean, IQR) 78 (73-83) years Sex (n, %): Male: 467 (48%) Katz Index of Independence in Activities of Daily Living score (median, IQR): 0 (0-1) Living situation (n, %): - home without home care: 463 (52%) - home with home care: 367 (41%) - other: 59 (7%) Charlson Comobidity Index (median, IQR): 5 (4-6) Event rate after 3 months (n, %): Composite outcome: 267 (31%) (missing n=36) Mortality: 76 (9%) (missing n=36) Functional decline: 123 (15%) (missing n=36) Institutionalization: 112 (13%) (missing n=36)	Index instrument: VMS Outcome: composite outcome of functional decline, mortality and institutionalization Index instrument: APOP 2016 (for functional decline or mortality) Outcome: composite outcome of functional decline, mortality and institutionalization Index instrument: APOP 2016 (for mortality) Outcome: composite outcome of functional decline, mortality and institutionalization Index instrument: ISAR-HP Outcome: composite outcome of functionel decline, mortality and institutionalization In general: “Functional decline was defined as an increase of 1 or more points in Katz Index of Independence in Activiteits of Daily Living Score compared with baseline.” “Instituionalization: The patient was considered institutionalized if he or she lived at home during baseline but had to stay elsewhere during follow-up (eg. In a nursing home, rehabilitation center or contemporary health institute)” “Mortality was extracted from the electronic health record.”	3 months after presentation on the emergency department	Discrimination: AUC-ROC Calibration: Calibration plots	Hospital (country): Amsterdam UMC, location VUmc and Amstelland Hospital (Netherlands) Validation study (external validation) “In total, 1,601 patients were screened for eligibility, and 712 were excluded. Most patients (n.404) were excluded because no informed consent was given, often due to the absence of a caregiver who could provide consent when the patient was too ill or confused. The exact number of patients with informed consent by proxy was not noted. Furthermore, 134 patients were unapproachable, according to the medical staff at the ED (eg, patients who had just received bad news or patients in extreme pain). An additional 96 were excluded due to their limited length of stay at the ED (these were patients who were admitted to the hospital or transferred to different hospitals before the researcher could approach them). No reason of exclusion was reported for 11 patients.” “During this study, the APOP consortium released an optimized version. At that time, we had already assessed patients using the first version; therefore, we decided to continue with this version. The optimized version consists of nearly the same variables and shows comparable predictive properties.”	High
Schuijt (2020)	N at baseline 249 Age (median, IQR) 80 (75-86) years Sex (n, %): Male: 153 (61%) Katz Index of Independence in Activities of Daily Living score (median, IQR): 1 (0-2) Living situation (n, %): - living in an institutional care facility: 35 (14%) Diagnosed with dementia (n, %) 19 (8%) Number of different medication (median, IQR): 5.5 (3-8) Event rate after 3 months (n, %): Composite outcome: 84 (39%) (missing: 32) Mortality: 30 (12%) Functional decline: 54 (29%) (missing: 62)	Index instrument: VMS Outcome: composite outcome of functional decline and mortality In general: “functional decline, defined as a one-or-more point loss of KATZ-ADL” “90-day mortality was determined by consulting the municipal civil registry.”	90 days after presentation on the emergency department	Discrimination: AUC-ROC Calibration: Not reported	Hospital (country): Gelre Hospital Apeldoorn (Netherlands) Validation study (external validation) “During the study period, 1203 eligible patients presented to the ED, 379 of whom presented within inclusion hours. A total of 112 patients were excluded. Due to a software error in data registration, 18 subjects had to be excluded because their VMS data was incomplete.”	High
De Gelder (2018)	N at baseline 2629 LUMC: 751 Alrijne: 881 HMC Bronovo: 498 Erasmus MC: 499 Age (mean, IQR) 79 (74-84) years Sex (n, %): Male: 1236 (47%) Katz Index of Independence in Activities of Daily Living score (median, IQR): 0 (0-1) Living situation (n, %): - Independent with others: 1421 (54,1%) - Independent alone: 991 (37.7%) - Residentional care or nursing home: 216 (8.2%) Impaired cognition (n,%): 492 (20.5%) Event rate after 3 months (n, %): Composite outcome: 805 (30.6%) (missing 139, 5.3%) Mortality: 259 (9.9%)	Index instrument: APOP 2018 (for functional decline or mortality) Outcome: composite outcome of functional decline and mortality In general: “Functional decline was defined as at least one point increase in Katz ADL score or new institutionalization (e.g. nursing home admission).” “Data on mortality were obtained from the municipal records.”	90 days after visiting the emergency department	Discrimination: AUC-ROC Calibration: Calibration plots	Hospital (country): LUMC, Leiden; Alrijne Hospital, Leiderdorp; Haaglanden Medical Center, The Hague; Erasmus MC, Rotterdam (Netherlands) Development and validation study (intenal-external validation design: Steyerberg, 2016) “A total of 3544 individual patients aged 70 years and older visited the emergency departments (EDs) of the four hospitals combined during the inclusion of the study period. Of those, 3147 were eligible for inclusion in the APOP study. In total 2629 patients were included (84% of the eligible patients)”	High

_{*For further details, see risk of bias table in the appendix}

Results

Discrimination (area under the ROC-curve)

Van Dam (2021), Schuijt (2020) and De Gelder (2018) evaluated the discriminative performance of several screeners by calculating the area under the curve. Results are summarized in Table 5. For the APOP-screeners and ISAR-HP screener, a possible helpful discrimination was observed. For the VMS-screener, results were inconsistent as Van Dam (2021) reported possible helpful discrimination and Schuijt (2020) reported poor discrimination.

Table 5. calculated area under the curve (AUC) predicting composite outcome (functional decline)

Outcome: composite outcome	APOP 2018 (for functional decline or mortality) AUC (95% CI)	APOP 2016 (functional decline or mortality) AUC (95% CI)	APOP 2016 (mortality) AUC (95% CI)	ISAR-HP AUC (95% CI)	VMS AUC (95% CI)
Van Dam (2021)	NA	0.72 (0.69 to 0.76)	0.62 (0.58 to 0.66)	0.72 (0.68 to 0.76)	0.70 (0.66 to 0.73)
Schuijt (2020)	NA	NA	NA	NA	0.54 (0.46 to 0.62)
De Gelder (2018)	0.71 (0.69 to 0.73)	NA	NA	NA	NA

_{AUC: area under the curve}

_{NA: not applicable}

Calibration (intercept, slope or O:E ratio)

Van Dam (2021) and De Gelder (2018) showed calibration plots to evaluate the calibrative performance of the evaluated screeners. Their conclusions about calibrative performance by visual inspection are summarized in Table 6. Slopes and intercepts were not reported.

Table 6. Evaluation by visual inspection of calibration plots by researchers

Calibrative performance	APOP 2018 (for functional decline or mortality)	APOP 2016 (functional decline or mortality)	APOP 2016 (mortality)	ISAR-HP	VMS
Van Dam (2021)	NA	Reasonable	Poor	Poor	Reasonable
Schuijt (2020)	NA	NA	NA	NA	Not reported
De Gelder (2018)	Observed probabilities were in line with expected probabilities	NA	NA	NA	NA

_{NA: not applicable}

O:E ratios for the overall calibrative performance were not reported and could not be calculated as the expected probability scores were not provided. O:E ratios for specific cut-off values were not taken into account in this summary of literature.

For more information on literature analysis on clinical questions regarding prognosis see ‘richtlijnmethodologie’.

As the guideline panel was not aware of any studies evaluating the use of screening instruments in clinical decision making and its impact on clinical outcome measures, the guideline panel decided to focus on studies evaluating the predictive ability of screening instruments on functional decline, morbidity and mortality. Clinical outcome measures were therefore not included in the PICOTS, despite being regarded as critical outcome measures for decision making (see relevant outcome measures).

A systematic review of the literature was performed to answer the following question:

What is the predictive value of screening instruments to predict a composite outcome of functional decline and mortality in elderly patients in a hospital setting?

Table 2. PICOTS

Patients	Elderly patients (>65 years) in a European hospital setting (i.e. emergency department, outpatient, inpatient)
Index instrument	VMS, APOP, ISAR, G8, CFS used for predicting a composite outcome including functional decline and mortality)
Comparator instrument	See Index instrument
Outcomes	Discrimination measures: C-statistic or area under the ROC curve Calibration measures: intercept and/or slope of the calibration curve or O:E ratio
Timing	Timepoint using the instrument: patients receiving hospital care Timepoint of prediction: at least 3 months follow-up
Setting	Receiving hospital care (emergency department, inpatient, outpatient)
Other selection criteria	Study design: systematic reviews, cohort studies (prediction model development studies, prediction model validation studies) Validation: external validation

_{*VMS: Safety Management System;}
_{*APOP: Acutely Presenting Older Patients screener;}
_{*ISAR: Identification of Senior at Risk;}

_{*G8: G8 geriatric screening tool;}
_{*CFS: Clinical Frailty Score.}

Relevant outcome measures

The guideline panel considered clinical outcomes (not included in PICOTS) as critical outcome measures for decision making; and discrimination and calibration as important outcome measures for decision making.

The guideline panel considered definitions and thresholds for clinical relevance as defined in table 3.

Table 3. Definitions and thresholds

Outcome	Definition	Threshold
Important outcome measures
Discrimination	C-statistic or AUC: used definition in the used studies	C-statistic or AUC: <0.6: poor discrimination; ³0.6 and ≤0.75: possibly helpful discrimination; >0,75: useful discrimination.
Calibration	Calibration intercept Calibration slope O:E ratio	Niet vastgesteld

Search and select (Methods)

A systematic literature search was performed by a medical information specialist using the following bibliographic databases: Embase.com and Ovid/Medline. Both databases were searched from 2018 to the 11^th of March 2025 for systematic reviews, RCTs and observational studies. Systematic searches were completed using a combination of controlled vocabulary/subject headings (e.g., Emtree-terms, MeSH) wherever they were available and natural language keywords. The overall search strategy was derived from three primary search concepts: (1) Elderly patients; (2) Screening instruments; (3) Prognosis. Duplicates were removed using EndNote software. After deduplication a total of 6047 records were imported for title/abstract screening. Initially, 104 studies were selected based on title and abstract screening using ASreview. After reading the full text, 101 studies were excluded (see the exclusion table under the tab ‘Evidence tabellen’), and three studies were included.

1 - Church S, Rogers E, Rockwood K, Theou O. A scoping review of the Clinical Frailty Scale. BMC Geriatr. 2020 Oct 7;20(1):393. doi: 10.1186/s12877-020-01801-7. PMID: 33028215; PMCID: PMC7540438.
2 - Demirhan I, Jongejan M, van Oevelen M, Kiriwenno K, Mooijaart SP, Verhaar MC, Bos WJW, Joosten H, Cnossen TT, van Buren M, Abrahams AC; DIALOGICA study group. Clinical Frailty Scale, Surprise Question and One-year Mortality in Older Patients With Advanced CKD. Kidney360. 2025 Aug 21. doi: 10.34067/KID.0000000936. Epub ahead of print. PMID: 40839396.
3 - de Gelder J, Lucke JA, de Groot B, Fogteloo AJ, Anten S, Mesri K, Steyerberg EW, Heringhaus C, Blauw GJ, Mooijaart SP. Predicting adverse health outcomes in older emergency department patients: the APOP study. Neth J Med. 2016 Oct;74(8):342-352. PMID: 27762216.
4 - de Gelder J, Lucke JA, Blomaard LC, Booijen AM, Fogteloo AJ, Anten S, Steyerberg EW, Alsma J, Klein Nagelvoort Schuit SCE, Brink A, de Groot B, Blauw GJ, Mooijaart SP. Optimization of the APOP screener to predict functional decline or mortality in older emergency department patients: Cross-validation in four prospective cohorts. Exp Gerontol. 2018 Sep;110:253-259. doi: 10.1016/j.exger.2018.06.015. Epub 2018 Jun 20. PMID: 29935293.
5 - Hoogerduijn JG, Schuurmans MJ, Korevaar JC, Buurman BM, de Rooij SE. Identification of older hospitalised patients at risk for functional decline, a study to compare the predictive values of three screening instruments. J Clin Nurs. 2010 May;19(9-10):1219-25. doi: 10.1111/j.1365-2702.2009.03035.x. Epub 2010 Mar 16. PMID: 20345834.
6 - Middelburg JG, Middelburg RA, van Zwienen M, Mast ME, Bhawanie A, Jobsen JJ, Rozema T, Maas H, Geijsen ED, van der Leest AH, van den Bongard DHJG, van Loon J, Budiharto T, Aarts MJ, Terhaard CHJ, Struikmans H; LPRO (Dutch National Organization for Radiotherapy in the Elderly). Impaired Geriatric 8 Score is Associated with Worse Survival after Radiotherapy in Older Patients with Cancer. Clin Oncol (R Coll Radiol). 2021 Apr;33(4):e203-e210. doi: 10.1016/j.clon.2020.09.002. Epub 2020 Sep 22. PMID: 32972801.
7 - Oud FMM, de Rooij SEJA, Arends AJ, Emmelot-Vonk MH, Melis RJF, Mooijaart SP, Willems HC, van Munster BC. Meetinstrumenten bij kwetsbare ouderen: een pleidooi voor meer standaardisatie [Assessment instruments in frail older patients; a call for more standardisation]. Ned Tijdschr Geneeskd. 2019 Nov 12;163:D3267. Dutch. PMID: 31769625.
8 - Schuijt HJ, Oud FMM, Bruns EJR, van Duijvendijk P, Van der Zaag-Loonen HJ, Spies PE, van Munster BC. Does the Dutch Safety Management Program predict adverse outcomes for older patients in the emergency department? Neth J Med. 2020 Sep;78(5):244-250. PMID: 33093249.
9 - Souwer ETD, Hultink D, Bastiaannet E, Hamaker ME, Schiphorst A, Pronk A, van der Bol JM, Steup WH, Dekker JWT, Portielje JEA, van den Bos F. The Prognostic Value of a Geriatric Risk Score for Older Patients with Colorectal Cancer. Ann Surg Oncol. 2019 Jan;26(1):71-78. doi: 10.1245/s10434-018-6867-x. Epub 2018 Oct 25. PMID: 30362061; PMCID: PMC6338720.
10 - van Dam CS, Trappenburg MC, Ter Wee MM, Hoogendijk EO, de Vet HC, Smulders YM, Nanayakkara PW, Muller M, Peters MJ. The Accuracy of Four Frequently Used Frailty Instruments for the Prediction of Adverse Health Outcomes Among Older Adults at Two Dutch Emergency Departments: Findings of the AmsterGEM Study. Ann Emerg Med. 2021 Oct;78(4):538-548. doi: 10.1016/j.annemergmed.2021.04.027. Epub 2021 Jul 23. PMID: 34304915.
11 - van Loon IN, Goto NA, Boereboom FTJ, Bots ML, Verhaar MC, Hamaker ME. Frailty Screening Tools for Elderly Patients Incident to Dialysis. Clin J Am Soc Nephrol. 2017 Sep 7;12(9):1480-1488. doi: 10.2215/CJN.11801116. Epub 2017 Jul 17. PMID: 28716855; PMCID: PMC5586582.

Risk of bias tables

Study reference

(first author, year of publication)

Participant selection

1) Were appropriate data sources used?

2) Was an appropriate study design used
3) Did the in- and exclusions of study participants result in a representative dataset?

Definitely yes

Probably yes

Probably no

Definitely no

No information

Concern regarding quality of selection of participants and data sources / Risk of bias introduced by the selection of participants and data sources

Concern that the (data of the) included participants do not match the review question or the assessor’s intended use of the prediction model

Risk of bias:

Low

High

Unclear

Predictors

1) Were predictors defined and assessed in a similar way for all participants?

2) Was any pre-processing of predictors similar for all participants?

3) Were predictor assessments made without knowledge of outcome data?

4) Were the predictors included in the model available at the time the model was intended to be used?

Definitely yes

Probably yes

Probably no

Definitely no

No information

Concern regarding the quality of the predictors or their assessment / Risk of bias introduced by the predictors or their assessment

Concern that the definition, pre-processing, assessment, or timing of assessment of the predictors in the model do not match the review question or the assessor’s intended use

Risk of bias:

Low

High

Unclear

Outcome

1) Were outcomes defined and assessed appropriately?

2) Were outcomes defined and assessed in a similar way for all participants?

3) Were outcome assessments made without use or knowledge of predictor data?

4) Was the time interval between predictor assessment and outcome assessment appropriate?

Definitely yes

Probably yes

Probably no

Definitely no

No information

Concern regarding quality of the outcome or its determination / Risk of bias introduced by the outcome or its determination

Concern that the outcome, its definition, assessment, or timing of assessment do not match the review question or the assessor’s intended use

Risk of bias:

Low

High

Unclear

Analysis – Development

1) Was there evidence that the sample size was reasonable?

2) Were continuous and categorical predictors handled appropriately?

3) Were participants with missing or censored data handled appropriately in the analysis?

4) If methods to address class imbalance were used, was the model or the model predictions recalibrated? (relevant for AI-models)

5) Were methods used to address potential model overfitting?

Definitely yes

Probably yes

Probably no

Definitely no

No information

Concern regarding quality of the analysis

Risk of bias:

Low

High

Unclear

Analysis - Validation

1) Was model evaluation based on only apparent performance avoided?
2) Was there evidence that the sample size was reasonable?
3) Were participants with missing or censored data handled appropriately in the analysis?
4) If methods to address class imbalance were used, was the evaluation done in a dataset without imbalance correction? (relevant for AI-models)
5) If data splitting was done to create training and test datasets, was there evidence that data leakage was avoided? (only relevant for internal validation)
6) If resampling methods were used to evaluate model performance, were all model development steps replicated in the resampling process? (only relevant for internal validation)
7) Was the predictive performance of the model evaluated appropriately, e.g., calibration, discrimination, and net benefit?

Definitely yes

Probably yes

Probably no

Definitely no

No information

Risk of bias introduced by the analysis

Risk of bias:

Low

High

Unclear

Overall judgment

High: at least one domain of high concern.

Low: all domeins of low concern

Unclear: at least one domein of unclear concern and no domains of high concern.

Risk of bias:

Low

High

Unclear

Van Dam, 2021

Conclusion:
definitely no

Reason:
- prospective cohort study emergency departments of two hospitals in the Netherlands
- all eligible patients were screened
- high urgency cases were excluded
- unapproachable patients were excluded
- patients with limited length of stay were excluded
- patients with language barrier were excluded

Conclusion:
probably no

Reason:
- data collected by chart review and interviews by trained student researchers
- detailed instructions were given to the student researchers and random quality checks were carried out
- screening instruments were used at baseline

Conclusion:
probably no

Reason:
- students researchers were not blinded for baseline data, but were not involved in care of the patients
- data on institutionalization and mortality were extracted from electronic health record and crossed-referenced with the general practitioner or caregiver
- data on functional status after 3 months was obtained by telephone after 3 months and cross-referenced with the electronic health record
- outcomes were clearly defined

Conclusion:

Reason:

Conclusion:

Apparent performance: NA
Internally validated: NA
Externally validated: probably yes

Reason:
- external validation
- 889 patients included with 267 events
- no sample size calculation performed
- handling missing data was not described, but number of missing data was low (n=36)
- discrimination was evaluated by area under the curve and calibration with calibration plots

Quality (development):

RoB (evaluation):
High

Applicability (development):

Applicability (evaluation):
Low

Quality (development):

RoB (evaluation):
High concern

Rational:
Part of relevant patients were excluded

Applicability (development):

Applicability (evaluation):
Low concern

Rational:
Type of patients within scope of PICO

Quality (development):

RoB (evaluation):
Low concern

Rational:
Although data is collected by chart review, we assume that data registration of relevant characteristics is done in similar ways within the department

Applicability (development):

Applicability (evaluation):
Low concern

Rational:
Type of predictors within scope of PICO

Quality (development):

RoB (evaluation):
Low concern

Rational:
Although student researchers were aware of baseline data, outcome measures were clearly defined and very objective.

Applicability (development):

Applicability (evaluation):
Low concern

Rational:
Type of outcome within scope of PICO

Quality (development):

Rational:

RoB (evaluation):
Low concern

Rational:
Although sample size is not calculated, a large sample size is used for appropriate performance measures.

Schuijt, 2020

Conclusion:
definitely no

Reason:
- prospective cohort study emergency departments hospitals in the Netherlands
- eligible patients between 10 AM and 7 PM were screened
- patients with unstable medical conditions were excluded
- patients with severe cognitive impairment were excluded
- patients with language barrier were excluded

Conclusion:
probably yes

Reason:
- data collected within 30 minutes of presentation at the department
- data collector received training to use VMS-screener

Conclusion:
probably no

Reason:
- mortality was determined by consulting the municipal civil registry
- 90 days after presentation, participants were contacted by telephone for other outcomes
- outcomes were clearly defined
- information on blinding not given

Conclusion:

Reason:

Conclusion:

Apparent performance: NA
Internally validated: NA
Externally validated: probably no

Reason:
- external validation
- 249 patients included with 84 events
- no sample size calculation performed, but 200 patients was stated as convenient
- patients with missing data were excluded from the analyses and number of missing data was relatively high (n=32; 13%)
- discrimination was evaluated by area under the curve

Quality (development):

RoB (evaluation):
High

Applicability (development):

Applicability (evaluation):
Low

Quality (development):

RoB (evaluation):
High concern

Rational:
Part of relevant patients were excluded

Applicability (development):

Applicability (evaluation):
Low concern

Rational:
Type of patients within scope of PICO

Quality (development):

RoB (evaluation):
Low concern

Rational:
Assesment performed by trained assessor witin 30 minutes of presentation at ED department.

Applicability (development):

Applicability (evaluation):
Low concern

Rational:
Type of predictors within scope of PICO

Quality (development):

RoB (evaluation):
Low concern

Rational:
Although unclear whether assessor was blinded for baseline data, outcome measures were clearly defined and very objective.

Applicability (development):

Applicability (evaluation):
Low concern

Rational:
Type of outcome within scope of PICO

Quality (development):

Rational:

RoB (evaluation):
High concern

Rational:
Relatively small sample size with <100 events and high percentage of missing data.

De Gelder, 2018

Conclusion:

Definitely no

Reason:
- prospective cohort study emergency departments hospitals in the Netherlands
- eligible patients, but not always 24 hours/day
- patients with red triage category or unstable medical condition were excluded
- patients with language barrier were excluded

Conclusion:

Probably yes

Reason:

- data collected at baseline

Conclusion:
probably no

Reason:
- mortality was obtained from the municipal civil registry
- 90 days after presentation, participants were contacted by telephone for other outcomes
- outcomes were clearly defined
- information on blinding not given

Conclusion:

Reason:

Conclusion:

Apparent performance: NA
Internally validated: NA
Externally validated: probably yes

Reason:
- internal-external validation design
- 2629 patients included with 805 events
- no sample size calculation performed, but it was aimed to include 500 patients
- no information was given regarding handling missing data, but number of missing data was relatively high (n=139; 5.3%)
- discrimination was evaluated by area under the curve and calibration with calibration plots

Quality (development):

RoB (evaluation):

High concern

Applicability (development):

Applicability (evaluation):
Low concern

Quality (development):

RoB (evaluation):
High concern

Rational:
Part of relevant patients were excluded

Applicability (development):

Applicability (evaluation):
Low concern

Rational:
Type of patients within scope of PICO

Quality (development):

RoB (evaluation):
Low concern

Rational:
- Although not much information was given regarding collection, predictors were well described and collected at baseline

Applicability (development):

Applicability (evaluation):
Low concern

Rational:
Type of predictors within scope of PICO

Quality (development):

RoB (evaluation):
Low concern

Rational:
Although unclear whether assessor was blinded for baseline data, outcome measures were clearly defined and very objective.

Applicability (development):

Applicability (evaluation):
Low concern

Rational:
Type of outcome within scope of PICO

Quality (development):

Rational:

RoB (evaluation):
Low concern

Rational:
Development and evaluation study with internal-external validation design.

Table of excluded studies

Reference	Reason for exclusion
Snijders BMG, Emmelot-Vonk MH, Souwer ETD, Kaasjager HAH, van den Bos F. Prognostic value of screening instrument based on the Dutch national VMS guidelines for older patients in the emergency department. Eur Geriatr Med. 2021;12(1):143–150. doi:10.1007/s41999-020-00385-0. PMID:32870476.	Wrong I (no relevant outcome for model of interest)
Oud FMM, Meulman MD, Merten H, Wagner C, van Munster BC. Value of the Safety Management System (VMS) frailty instrument as a frailty screener in care for older hospital patients: a systematic review. Eur Geriatr Med. 2024;15(3):609–620. doi:10.1007/s41999-024-00957-4. PMID:38668846.	More than 50% of included studies excluded for the current review: relevant studies individual included
Oud FMM, Wolzak NK, Spies PE, van der Zaag-Loonen HJ, van Munster BC. The predictive value of the ‘VMS frail older patients’ for adverse outcomes in geriatric inpatients. Arch Gerontol Geriatr. 2021;97:104514. doi:10.1016/j.archger.2021.104514. PMID:34571343.	Wrong O (no discrimination or calibration measures reported)
Warnier RMJ, van Rossum E, van Kuijk SMJ, Magdelijns FJ, Schols JMGA, Kempen GIJM. Frailty screening in hospitalised older adults: How does the brief Dutch National Safety Management Program perform compared to a more extensive approach? J Clin Nurs. 2020;29(7–8):1064–1073. doi:10.1111/jocn.15148. PMID:31856316.	Wrong prediction (no functional decline)
Winters AM, Hartog LC, Roijen HIF, Brohet RM, Kamper AM. Relationship between clinical outcomes and Dutch frailty score among elderly patients who underwent surgery for hip fracture. Clin Interv Aging. 2018;13:2481–2486. doi:10.2147/CIA.S181497. PMID:30584288.	Wrong O (no discrimination or calibration measures reported)
Calf AH, Lubbers S, van den Berg A, van den Berg E, Jansen CJ, van Munster BC, de Rooij SE, ter Maaten JC. Clinical impression for identification of vulnerable older patients in the Emergency Department. Eur J Emerg Med. 2020;27(2):137–141. doi:10.1097/MEJ.0000000000000632. PMID:32101960.	Wrong O (no discrimination or calibration measures reported)
van Dam CS, Trappenburg MC, ter Wee MM, et al. Prognostic accuracy of clinical judgment versus a validated frailty screening instrument among hospitalized older adults in two Dutch emergency departments. Ann Emerg Med. 2022;79(3):345–354. doi:10.1016/j.annemergmed.2022.04.039. PMID:35717270.	Same patient population as Van Dam 2021
Leahy A, Corey G, Purtill H, O'Neill A, Devlin C, Barry L, Cummins N, Gabr A, Mohamed A, Shanahan E, Shchetkovsky D, Ryan D, O'Loughlin M, O'Connor M, Galvin R. Screening instruments to predict adverse outcomes for undifferentiated older adults attending the Emergency Department: Results of SOAED prospective cohort study. Age Ageing. 2023 Jul 1;52(7):afad116. doi: 10.1093/ageing/afad116. PMID: 37463282; PMCID: PMC10353758.	Wrong O (no discrimination or calibration measures reported)
McCusker J, Warburton RN, Lambert SD, Belzile E, de Raad M. The Revised Identification of Seniors At Risk screening tool predicts readmission in older hospitalized patients: a cohort study. BMC Geriatr. 2022 Nov 22;22(1):888. doi: 10.1186/s12877-022-03458-w. PMID: 36418981; PMCID: PMC9682664.	Wrong prediction (no functional decline)
Loddo, Simona, et al. "Emergency department: risk stratification in the elderly." Journal of Gerontology and Geriatrics 69.3 (2021): 84-90.	Wrong I (no relevant outcome for model of interest)
Lim SH, Malhotra R, Østbye T, Ang SY, Ng XP, Agus N, Sunari RNB, Aloweni F. Sensitivity and specificity of three screening tools for frailty in hospitalized older adults. Int J Nurs Stud. 2023 Mar;139:104435. doi: 10.1016/j.ijnurstu.2022.104435. Epub 2023 Jan 5. PMID: 36640700.	Wrong prediction (no composite outcome with functional decline)
Gretarsdottir E, Jonsdottir AB, Sigurthorsdottir I, Gudmundsdottir EE, Hjaltadottir I, Jakobsdottir IB, Tomasson G, Jonsson PV, Thorsteinsdottir T. Patients in need of comprehensive geriatric assessment: The utility of the InterRAI emergency department screener. Int Emerg Nurs. 2021 Jan;54:100943. doi: 10.1016/j.ienj.2020.100943. Epub 2020 Dec 25. PMID: 33370678.	Wrong prediction (no functional decline)
Rizka A, Harimurti K, Pitoyo CW, Koesnoe S. Comparison between the Identification of Seniors at Risk and Triage Risk Screening Tool in predicting mortality of older adults visiting the emergency department: Results from Indonesia. Geriatr Gerontol Int. 2020 Jan;20(1):47-51. doi: 10.1111/ggi.13817. Epub 2019 Nov 21. PMID: 31755195.	Wrong prediction (no functional decline)
Hsu CW, Lee CW, Hsu SC, Huang WC, Hsu YP, Chi MJ. Improvement of the Identification of Seniors at Risk scale for predicting adverse health outcomes of elderly patients in the emergency department. Int Emerg Nurs. 2023 May;68:101274. doi: 10.1016/j.ienj.2023.101274. Epub 2023 Mar 15. PMID: 36931014.	Wrong prediction (no functional decline)
Martín-Sánchez FJ, Llopis García G, González-Colaço Harmand M, Fernandez Pérez C, González Del Castillo J, Llorens P, Herrero P, Jacob J, Gil V, Domínguez-Rodriguez A, Rossello X, Miró O; en representación de los investigadores del Registro OAK; Resto de investigadores del registro OAK. Identification of Senior At Risk scale predicts 30-day mortality among older patients with acute heart failure. Med Intensiva (Engl Ed). 2020 Jan-Feb;44(1):9-17. English, Spanish. doi: 10.1016/j.medin.2018.07.009. Epub 2018 Aug 27. PMID: 30166245.	Wrong prediction (no functional decline)
Wang MC, Liao WC, Lee KC, Lu SH, Lin YP. Validation of Screening Tools for Predicting the Risk of Functional Decline in Hospitalized Elderly Patients. Int J Environ Res Public Health. 2022 May 30;19(11):6685. doi: 10.3390/ijerph19116685. PMID: 35682269; PMCID: PMC9180656.	Wrong prediction (no composite outcome with functional decline)
Lopez Cuenca S, Oteiza L, Lazaro Martín N, Ibarz M, Irazabal M, Artigas A, Lorente JA. ISAR Score (Identification of Seniors At Risk) predice la mortalidad en mayores de 75 años ingresados en Cuidados Intensivos [ISAR Score (Identification of Seniors At Risk) predicts mortality in patients older than 75 years admitted in Intensive Care]. Rev Esp Geriatr Gerontol. 2021 Jan-Feb;56(1):5-10. Spanish. doi: 10.1016/j.regg.2020.09.009. Epub 2020 Dec 11. PMID: 33309421.	Spanish
SEZİK, Savaş. "A 30-DAY RISK ASSESSMENT OF GERIATRIC PATIENTS IN THE EMERGENCY DEPARTMENT: A COMPARISON OF ISAR AND TRST SCORES." Turkish Journal of Geriatrics/Türk Geriatri Dergisi 26.1 (2023).	Wrong prediction (no functional decline)
Bahadirli, Suphi, et al. "Evaluation and comparison of screening tools used to predict the adverse outcomes of elderly patients in the emergency department." Acta Med Mediter 37 (2021): 1133-39.	Wrong prediction (no functional decline)
Chavarro-Carvajal DA, Sánchez DC, Vargas-Beltran MP, Venegas-Sanabria LC, Muñoz OM. Clinical value of Hospital Admission Risk Profile (HARP) and the Identification of Seniors at Risk (ISAR) scales to predict hospital-associated functional decline in an acute geriatric unit in Colombia. Colomb Med (Cali). 2023 Mar 30;54(1):e2005304. doi: 10.25100/cm.v54i1.5304. PMID: 37440979; PMCID: PMC10335384.	Wrong prediction (no composite outcome with functional decline)
Luttikhuis HM, Blomaard LC, van der Kaaij MAE, Gombert-Handoko KB, de Groot B, Mooijaart SP. Geriatric characteristics and the risk of drug-related hospital admissions in older Emergency Department patients. Eur Geriatr Med. 2022 Apr;13(2):329-337. doi: 10.1007/s41999-021-00580-7. Epub 2021 Nov 10. PMID: 34755308.	Wrong prediction (no functional decline)
van der Velde MGAM, van der Aa MJ, van Daal MHC, Kremers MNT, Keijsers CJPW, van Kuijk SMJ, Haak HR. Performance of the APOP-screener for predicting in-hospital mortality in older COVID-19 patients: a retrospective study. BMC Geriatr. 2022 Jul 15;22(1):584. doi: 10.1186/s12877-022-03274-2. PMID: 35840904; PMCID: PMC9284964.	Wrong prediction (no functional decline)
Shrier W, Dewar C, Parrella P, Hunt D, Hodgson LE. Agreement and predictive value of the Rockwood Clinical Frailty Scale at emergency department triage. Emerg Med J. 2021 Dec;38(12):868-873. doi: 10.1136/emermed-2019-208633. Epub 2020 Nov 10. PMID: 33172880.	Wrong prediction (no functional decline)
Chong E, Ho E, Baldevarona-Llego J, Chan M, Wu L, Tay L, Ding YY, Lim WS. Frailty in Hospitalized Older Adults: Comparing Different Frailty Measures in Predicting Short- and Long-term Patient Outcomes. J Am Med Dir Assoc. 2018 May;19(5):450-457.e3. doi: 10.1016/j.jamda.2017.10.006. Epub 2017 Nov 15. PMID: 29153536.	Wrong prediction (no functional decline)
Kaeppeli T, Rueegg M, Dreher-Hummel T, Brabrand M, Kabell-Nissen S, Carpenter CR, Bingisser R, Nickel CH. Validation of the Clinical Frailty Scale for Prediction of Thirty-Day Mortality in the Emergency Department. Ann Emerg Med. 2020 Sep;76(3):291-300. doi: 10.1016/j.annemergmed.2020.03.028. Epub 2020 Apr 24. PMID: 32336486.	Wrong prediction (no functional decline)
YÜCEL, Mustafa, et al. "COMPARISON OF CLINICAL FRAILTY SCALE AND EDMONTON FRAIL SCALE IN OLDER ADULTS PRESENTING TO THE EMERGENCY DEPARTMENT." Turkish Journal of Geriatrics/Türk Geriatri Dergisi 27.1 (2024).	Wrong prediction (no functional decline)
Fernando SM, Guo KH, Lukasik M, Rochwerg B, Cook DJ, Kyeremanteng K, Perry JJ. Frailty and associated prognosis among older emergency department patients with suspected infection: A prospective, observational cohort study. CJEM. 2020 Sep;22(5):687-691. doi: 10.1017/cem.2020.377. PMID: 32493517.	Wrong O (no discrimination or calibration measures reported)
Darvall JN, Bellomo R, Paul E, Bailey M, Young PJ, Reid A, Rockwood K, Pilcher D. Routine Frailty Screening in Critical Illness: A Population-Based Cohort Study in Australia and New Zealand. Chest. 2021 Oct;160(4):1292-1303. doi: 10.1016/j.chest.2021.05.049. Epub 2021 Jun 4. PMID: 34089741.	Wrong prediction (no functional decline)
Hajibandeh S, Hajibandeh S, Brown C, Harper ER, Saji AP, Hughes I, Mitra K, Rashwany H, Clayton A, Patel N, Abdelrahman T, Foliaki A, Kumar N. Sarcopenia versus clinical frailty scale in predicting the risk of postoperative mortality after emergency laparotomy: a retrospective cohort study. Langenbecks Arch Surg. 2024 Feb 14;409(1):59. doi: 10.1007/s00423-024-03252-9. PMID: 38351404.	Wrong prediction (no functional decline)
Sun CY, Huang CC, Tsai YS, Chang YT, Ou CH, Su WC, Fan SY, Wang ST, Yang DC, Huang CC, Chang CM. Clinical Frailty Scale in Predicting Postoperative Outcomes in Older Patients Undergoing Curative Surgery for Urologic Malignancies: A Prospective Observational Cohort Study. Urology. 2020 Oct;144:38-45. doi: 10.1016/j.urology.2020.06.069. Epub 2020 Jul 23. PMID: 32711011.	Wrong prediction (no composite outcome with functional decline)
Clark S, Shaw C, Padayachee A, Howard S, Hay K, Frakking TT. Frailty and hospital outcomes within a low socioeconomic population. QJM. 2019 Dec 1;112(12):907-913. doi: 10.1093/qjmed/hcz203. PMID: 31386153.	Wrong O (no discrimination or calibration outcomes)
Vrettos I, Voukelatou P, Panayiotou S, Kyvetos A, Tsigkri A, Makrilakis K, Sfikakis PP, Niakas D. Factors Associated With Mortality in Elderly Hospitalized Patients at Admission. Cureus. 2022 Feb 28;14(2):e22709. doi: 10.7759/cureus.22709. PMID: 35386138; PMCID: PMC8967403.	Wrong prediction (no functional decline)
Utino Taniguchi L, Ibrahim Q, Azevedo LCP, Stelfox HT, Bagshaw SM. Comparison of two frailty identification tools for critically ill patients: A post-hoc analysis of a multicenter prospective cohort study. J Crit Care. 2020 Oct;59:143-148. doi: 10.1016/j.jcrc.2020.06.007. Epub 2020 Jul 1. PMID: 32679466.	Wrong prediction (no functional decline)
Bielza R, Balaguer C, Zambrana F, Arias E, Thuissard IJ, Lung A, Oñoro C, Pérez P, Andreu-Vázquez C, Neira M, Anguita N, Sáez C, de la Puente EMF. Accuracy, feasibility and predictive ability of different frailty instruments in an acute geriatric setting. Eur Geriatr Med. 2022 Aug;13(4):827-835. doi: 10.1007/s41999-022-00645-1. Epub 2022 Apr 23. PMID: 35460515; PMCID: PMC9034644.	Wrong prediction (no compositie outcome with both functional decline and mortality)
Stuck AK, Mangold JM, Wittwer R, Limacher A, Bischoff-Ferrari HA. Ability of 3 Frailty Measures to Predict Short-Term Outcomes in Older Patients Admitted for Post-Acute Inpatient Rehabilitation. J Am Med Dir Assoc. 2022 May;23(5):880-884. doi: 10.1016/j.jamda.2021.09.029. Epub 2021 Oct 20. PMID: 34687605.	Wrong prediction (no composite outcome with functional decline)
Langlais E, Nesseler N, Le Pabic E, Frasca D, Launey Y, Seguin P. Does the clinical frailty score improve the accuracy of the SOFA score in predicting hospital mortality in elderly critically ill patients? A prospective observational study. J Crit Care. 2018 Aug;46:67-72. doi: 10.1016/j.jcrc.2018.04.012. Epub 2018 Apr 22. PMID: 29705407.	Wrong prediction (no functional decline)
Subramaniam A, Ueno R, Tiruvoipati R, Srikanth V, Bailey M, Pilcher D. Comparison of the predictive ability of clinical frailty scale and hospital frailty risk score to determine long-term survival in critically ill patients: a multicentre retrospective cohort study. Crit Care. 2022 May 3;26(1):121. doi: 10.1186/s13054-022-03987-1. PMID: 35505435; PMCID: PMC9063154.	Wrong prediction (no functional decline)
Wretborn J, Munir-Ehrlington S, Hörlin E, Wilhelms DB. Addition of the clinical frailty scale to triage tools and early warning scores improves mortality prognostication at 30 days: A prospective observational multicenter study. J Am Coll Emerg Physicians Open. 2024 Sep 9;5(5):e13244. doi: 10.1002/emp2.13244. PMID: 39253302; PMCID: PMC11381915.	Wrong prediction (no functional decline)
Zhang D, Tang W, Dou LY, Luo J, Sun Y. Four different frailty models predict health outcomes in older patients with stable chronic obstructive pulmonary disease. BMC Geriatr. 2022 Jan 16;22(1):57. doi: 10.1186/s12877-022-02750-z. PMID: 35034605; PMCID: PMC8761265.	Wrong prediction (no functional decline)
Thillainadesan J, Mudge AM, Aitken SJ, Hilmer SN, Cullen JS, Yumol MF, Close JCT, Norris CM, Kerdic R, Naganathan V. The Prognostic Performance of Frailty for Delirium and Functional Decline in Vascular Surgery Patients. J Am Geriatr Soc. 2021 Mar;69(3):688-695. doi: 10.1111/jgs.16907. Epub 2020 Nov 5. PMID: 33151550.	Wrong prediction (no composite outcome with functional decline)
Aliberti MJR, Szlejf C, Avelino-Silva VI, Suemoto CK, Apolinario D, Dias MB, Garcez FB, Trindade CB, Amaral JRDG, de Melo LR, de Aguiar RC, Coelho PHL, Hojaij NHSL, Saraiva MD, da Silva NOT, Jacob-Filho W, Avelino-Silva TJ; COVID HCFMUSP Study Group. COVID-19 is not over and age is not enough: Using frailty for prognostication in hospitalized patients. J Am Geriatr Soc. 2021 May;69(5):1116-1127. doi: 10.1111/jgs.17146. Epub 2021 Apr 5. PMID: 33818759; PMCID: PMC8251205.	Wrong prediction (no functional decline)
Mak, Jonathan KL, et al. "Using an electronic frailty index to predict adverse outcomes in geriatric COVID-19 patients: data from the Stockholm GeroCovid study." Medrxiv (2021): 2021-12.	Wrong prediction (no functional decline)
Ikram A, Norrish AR, Marson BA, Craxford S, Gladman JRF, Ollivere BJ. Can the Clinical Frailty Scale on admission predict 30-day survival, postoperative complications, and institutionalization in patients with fragility hip fracture? : a cohort study of 1,255 patients. Bone Joint J. 2022 Aug;104-B(8):980-986. doi: 10.1302/0301-620X.104B8.BJJ-2020-1835.R2. PMID: 35909371; PMCID: PMC9948448.	Wrong prediction (no functional decline)
Reichart D, Rosato S, Nammas W, Onorati F, Dalén M, Castro L, Gherli R, Gatti G, Franzese I, Faggian G, De Feo M, Khodabandeh S, Santarpino G, Rubino AS, Maselli D, Nardella S, Salsano A, Nicolini F, Zanobini M, Saccocci M, Bounader K, Kinnunen EM, Tauriainen T, Airaksinen J, Seccareccia F, Mariscalco G, Ruggieri VG, Perrotti A, Biancari F. Clinical frailty scale and outcome after coronary artery bypass grafting. Eur J Cardiothorac Surg. 2018 Dec 1;54(6):1102-1109. doi: 10.1093/ejcts/ezy222. PMID: 29897529.	Wrong I (no model of interest evaluated)
Lee JH, Park YS, Kim MJ, Shin HJ, Roh YH, Kim JH, Chung HS, Park I, Chung SP. Clinical Frailty Scale as a predictor of short-term mortality: A systematic review and meta-analysis of studies on diagnostic test accuracy. Acad Emerg Med. 2022 Nov;29(11):1347-1356. doi: 10.1111/acem.14493. Epub 2022 Apr 25. PMID: 35349205.	Wrong prediction (no functional decline)
Kenig J, Szabat K, Mituś J, Mituś-Kenig M, Krzeszowiak J. Usefulness of eight screening tools for predicting frailty and postoperative short- and long-term outcomes among older patients with cancer who qualify for abdominal surgery. Eur J Surg Oncol. 2020 Nov;46(11):2091-2098. doi: 10.1016/j.ejso.2020.07.040. Epub 2020 Aug 7. PMID: 32800399.	Wrong prediction (no functional decline)
Rivasi G, Ceolin L, Turrin G, Tortù V, D'Andria MF, Capacci M, Testa GD, Montali S, Tonarelli F, Brunetti E, Bo M, Romero-Ortuno R, Mossello E, Ungar A. Comparison of different frailty instruments for prediction of functional decline in older hypertensive outpatients (HYPER-FRAIL pilot study 2). Eur J Intern Med. 2024 Nov;129:35-40. doi: 10.1016/j.ejim.2024.05.013. Epub 2024 May 18. PMID: 38763848.	Wrong prediction (no composite outcome with functional decline)
Rueegg M, Nissen SK, Brabrand M, Kaeppeli T, Dreher T, Carpenter CR, Bingisser R, Nickel CH. The clinical frailty scale predicts 1-year mortality in emergency department patients aged 65 years and older. Acad Emerg Med. 2022 May;29(5):572-580. doi: 10.1111/acem.14460. Epub 2022 Apr 23. PMID: 35138670; PMCID: PMC9320818.	Wrong I (no model of interest evaluated)
De Geer L, Fredrikson M, Tibblin AO. Frailty predicts 30-day mortality in intensive care patients: A prospective prediction study. Eur J Anaesthesiol. 2020 Nov;37(11):1058-1065. doi: 10.1097/EJA.0000000000001156. PMID: 31977631.	Wrong prediction (no functional decline)
Van Nguyen T, Tran HM, Ngo TKT. Comparative clinical frailty scale and hospital frailty risk score in identifying frailty and predicting mid-term outcomes in older patients with acute coronary syndrome: a multicenter cohort study in Vietnam. BMC Geriatr. 2025 Feb 24;25(1):125. doi: 10.1186/s12877-025-05690-6. PMID: 39994542; PMCID: PMC11849291.	Wrong prediction (no functional decline)
Fagard K, Geyskens L, Van den Bogaert B, Willems S, Flamaing J, Wolthuis A, Deschodt M. Frailty screening in older patients undergoing elective colorectal surgery: Comparative study of seven screening instruments. J Am Geriatr Soc. 2025 Apr;73(4):1060-1072. doi: 10.1111/jgs.19317. Epub 2024 Dec 29. PMID: 39737615; PMCID: PMC11970229.	Wrong prediction (no composite outcome with functional decline)
McIsaac DI, Taljaard M, Bryson GL, Beaulé PE, Gagné S, Hamilton G, Hladkowicz E, Huang A, Joanisse JA, Lavallée LT, MacDonald D, Moloo H, Thavorn K, van Walraven C, Yang H, Forster AJ. Frailty as a Predictor of Death or New Disability After Surgery: A Prospective Cohort Study. Ann Surg. 2020 Feb;271(2):283-289. doi: 10.1097/SLA.0000000000002967. PMID: 30048320.	Wrong prediction (no functional decline)
Anand A, Cudmore S, Robertson S, Stephen J, Haga K, Weir CJ, Murray SA, Boyd K, Gunn J, Iqbal J, MacLullich A, Shenkin SD, Fox KAA, Mills N, Denvir MA. Frailty assessment and risk prediction by GRACE score in older patients with acute myocardial infarction. BMC Geriatr. 2020 Mar 13;20(1):102. doi: 10.1186/s12877-020-1500-9. PMID: 32164580; PMCID: PMC7069195.	Wrong prediction (no functional decline)
McIsaac DI, Harris EP, Hladkowicz E, Moloo H, Lalu MM, Bryson GL, Huang A, Joanisse J, Hamilton GM, Forster AJ, van Walraven C. Prospective Comparison of Preoperative Predictive Performance Between 3 Leading Frailty Instruments. Anesth Analg. 2020 Jul;131(1):263-272. doi: 10.1213/ANE.0000000000004475. PMID: 31569165.	Wrong I (no model of interest evaluated)
Mak JKL, Hägg S, Eriksdotter M, Annetorp M, Kuja-Halkola R, Kananen L, Boström AM, Kivipelto M, Metzner C, Bäck Jerlardtz V, Engström M, Johnson P, Lundberg LG, Åkesson E, Sühl Öberg C, Olsson M, Cederholm T, Jylhävä J, Religa D. Development of an Electronic Frailty Index for Hospitalized Older Adults in Sweden. J Gerontol A Biol Sci Med Sci. 2022 Nov 21;77(11):2311-2319. doi: 10.1093/gerona/glac069. PMID: 35303746; PMCID: PMC9678204.	Wrong prediction (no functional decline)
Checa-Lopez M, Rodriguez-Laso A, Carnicero JA, Solano-Jaurrieta JJ, Saavedra Obermans O, Sinclair A, Landi F, Scuteri A, Álvarez-Bustos A, Sepúlveda-Loyola W, Rodriguez-Manas L. Differential utility of various frailty diagnostic tools in non-geriatric hospital departments of several countries: A longitudinal study. Eur J Clin Invest. 2023 Jul;53(7):e13979. doi: 10.1111/eci.13979. Epub 2023 Mar 10. PMID: 36855840.	Wrong O (no discrimination or calibration measures reported)
Fan, I-Wei, et al. "Comparing the predictive performance of in-hospital mortality of different frailty scales for elderly patients in the emergency department." Signa Vitae 20.9 (2024).	Wrong prediction (no functional decline)
Arteaga AS, Aguilar LT, González JT, Boza AS, Muñoz-Cruzado VD, Ciuró FP, Ruíz JP. Impact of frailty in surgical emergencies. A comparison of four frailty scales. Eur J Trauma Emerg Surg. 2021 Oct;47(5):1613-1619. doi: 10.1007/s00068-020-01314-3. Epub 2020 Feb 8. PMID: 32036392.	wrong prediction (no functional decline)
Shang N, Liu H, Wang N, Guo S, Ma L. Comparison of three frailty screening instruments for prediction of adverse outcomes among older adults in the emergency department. Geriatr Gerontol Int. 2022 Oct;22(10):851-856. doi: 10.1111/ggi.14469. Epub 2022 Aug 30. PMID: 36054799; PMCID: PMC9804829.	Wrong I (no model of interest evaluated)
Hao L, Zhou Y, Zou J, Hao L, Deng P. Predictive Value of PRISMA-7, qSOFA, ESI, and CFS for 28-Day Mortality in Elderly Patients in the Emergency Department. J Inflamm Res. 2023 Jul 13;16:2947-2954. doi: 10.2147/JIR.S419538. PMID: 37465342; PMCID: PMC10351523.	wrong prediction (no functional decline)
Aliberti MJR, Covinsky KE, Apolinario D, Lee SJ, Fortes-Filho SQ, Melo JA, Viana SSC, Suemoto CK, Jacob-Filho W. A 10-min Targeted Geriatric Assessment Predicts Mortality in Fast-Paced Acute Care Settings: A Prospective Cohort Study. J Nutr Health Aging. 2019;23(3):286-290. doi: 10.1007/s12603-018-1152-z. PMID: 30820518.	Wrong prediction (no functional decline)
Argillander TE, van der Hulst HC, van der Zaag-Loonen HJ, van Duijvendijk P, Dekker JWT, van der Bol JM, Bastiaannet E, Verkuyl J, Neijenhuis P, Hamaker M, Schiphorst AH, Aukema TS, Burghgraef TA, Sonneveld DJA, Schuijtemaker JS, van der Meij W, van den Bos F, Portielje JEA, Souwer ETD, van Munster BC. Predictive value of selected geriatric parameters for postoperative outcomes in older patients with rectal cancer - A multicenter cohort study. J Geriatr Oncol. 2022 Jul;13(6):796-802. doi: 10.1016/j.jgo.2022.05.004. Epub 2022 May 20. PMID: 35599096.	Wrong I (no model of interest evaluated)
Zaib J, Madni A, Saad Azhar M. Predictive Value of Comprehensive Geriatric Assessment Scores for Mortality in Patients With Hip Fracture: A Retrospective Cohort Study. Cureus. 2023 Sep 11;15(9):e45070. doi: 10.7759/cureus.45070. PMID: 37842357; PMCID: PMC10568117.	wrong prediction (no functional decline)
Thorne G, Hodgson L. Performance of the Nottingham Hip Fracture Score and Clinical Frailty Scale as predictors of short and long-term outcomes: a dual-centre 3-year observational study of hip fracture patients. J Bone Miner Metab. 2021 May;39(3):494-500. doi: 10.1007/s00774-020-01187-x. Epub 2021 Jan 2. PMID: 33387062.	wrong prediction (no functional decline)
Turcotte LA, Heckman G, Rockwood K, Vetrano DL, Hébert P, McIsaac DI, Rhynold E, Mitchell L, Mowbray FI, Larsen RT, Hirdes JP. External validation of the hospital frailty risk score among hospitalised home care clients in Canada: a retrospective cohort study. Age Ageing. 2023 Feb 1;52(2):afac334. doi: 10.1093/ageing/afac334. PMID: 36735847; PMCID: PMC9897298.	wrong prediction (no functional decline)
Lewis ET, Dent E, Alkhouri H, Kellett J, Williamson M, Asha S, Holdgate A, Mackenzie J, Winoto L, Fajardo-Pulido D, Ticehurst M, Hillman K, McCarthy S, Elcombe E, Rogers K, Cardona M. Which frailty scale for patients admitted via Emergency Department? A cohort study. Arch Gerontol Geriatr. 2019 Jan-Feb;80:104-114. doi: 10.1016/j.archger.2018.11.002. Epub 2018 Nov 8. PMID: 30448693.	wrong prediction (no functional decline)
Langsted A, Benatar J, Kerr A, Bloomfield K, Devlin G, Sasse A, Smythe D, To A, White H, Wilkins G, Stewart R. Comparison of frailty instruments for predicting mortality and prolon ged hospitalization in acute coronary syndrome patients. PLoS One. 2025 Feb 7;20(2):e0318656. doi: 10.1371/journal.pone.0318656. PMID: 39919129; PMCID: PMC11805369.	wrong prediction (no functional decline)
Langsted A, Benatar J, Kerr A, Bloomfield K, Devlin G, Sasse A, Smythe D, To A, White H, Wilkins G, Stewart R. Comparison of frailty instruments for predicting mortality and prolon ged hospitalization in acute coronary syndrome patients. PLoS One. 2025 Feb 7;20(2):e0318656. doi: 10.1371/journal.pone.0318656. PMID: 39919129; PMCID: PMC11805369.	Wrong prediction (no functional decline)
Parini S, Azzolina D, Massera F, Garlisi C, Papalia E, Baietto G, Bora G, Mastromarino MG, Barini M, Ruffini E, Carriero A, Rena O. Comparison of frailty indexes as predictors of clinical outcomes after major thoracic surgery. J Thorac Dis. 2024 May 31;16(5):3192-3203. doi: 10.21037/jtd-23-963. Epub 2024 May 29. PMID: 38883684; PMCID: PMC11170436.	Wrong I (Prognostic outcome measures for CFS (AUC) not reported)
Di Prazza A, Canino B, Barbagallo M, Veronese N. The importance of prognosis in geriatric patients attending the emergency department: a comparison between two common short geriatric assessment tools. Aging Clin Exp Res. 2023 Dec;35(12):3041-3046. doi: 10.1007/s40520-023-02603-8. Epub 2023 Nov 6. PMID: 37932645; PMCID: PMC10721668.	wrong prediction (no functional decline)
Mancino F, Wall B, Bucher TA, Prosser GH, Yates PJ, Jones CW. The Clinical Frailty Scale is a Strong Predictor of 1-Year Mortality in Surgically Managed Hip Periprosthetic Fracture: An Analysis From a High-Volume Institution. J Arthroplasty. 2024 May;39(5):1157-1164. doi: 10.1016/j.arth.2023.11.010. Epub 2023 Nov 10. PMID: 37952739.	wrong prediction (no functional decline)
Cardona M, Lewis ET, Kristensen MR, Skjøt-Arkil H, Ekmann AA, Nygaard HH, Jensen JJ, Jensen RO, Pedersen JL, Turner RM, Garden F, Alkhouri H, Asha S, Mackenzie J, Perkins M, Suri S, Holdgate A, Winoto L, Chang DCW, Gallego-Luxan B, McCarthy S, Petersen JA, Jensen BN, Backer Mogensen C, Hillman K, Brabrand M. Predictive validity of the CriSTAL tool for short-term mortality in older people presenting at Emergency Departments: a prospective study. Eur Geriatr Med. 2018;9(6):891-901. doi: 10.1007/s41999-018-0123-6. Epub 2018 Oct 31. PMID: 30574216; PMCID: PMC6267649.	wrong I (no model of interest evaluated)
Narula S, Lawless A, D'Alessandro P, Jones CW, Yates P, Seymour H. Clinical Frailty Scale is a good predictor of mortality after proximal femur fracture: A cohort study of 30-day and one-year mortality. Bone Jt Open. 2020 Aug 1;1(8):443-449. doi: 10.1302/2633-1462.18.BJO-2020-0089.R1. PMID: 33215137; PMCID: PMC7667224.	wrong prediction (no functional decline)
Cords CI, van Baar ME, Nieuwenhuis MK, Pijpe A, van der Vlies CH; FRAIL group; Dutch Burn Repository group. Reliability and validity of a frailty assessment tool in specialized burn care, a retrospective multicentre cohort study. Burns. 2023 Nov;49(7):1621-1631. doi: 10.1016/j.burns.2023.05.001. Epub 2023 May 5. PMID: 37211474.	Wrong O (no discrimination or calibration reported)
Patrizio E, Zambon A, Mazzola P, Massariello F, Galeazzi M, Cavalieri d'Oro L, Bonfanti P, Bellelli G. Assessing the mortality risk in older patients hospitalized with a diagnosis of sepsis: the role of frailty and acute organ dysfunction. Aging Clin Exp Res. 2022 Oct;34(10):2335-2343. doi: 10.1007/s40520-022-02182-0. Epub 2022 Jul 7. PMID: 35799097.	wrong prediction (no functional decline)
Hwang D, Lee E, Park S, Yoo BC, Park S, Choi KJ, Oh S, Kim MJ, Kim H, Jeon JS, Noh H, Han DC, Kwon SH. Validation of risk prediction tools in elderly patients who initiate dialysis. Int Urol Nephrol. 2019 Jul;51(7):1231-1238. doi: 10.1007/s11255-019-02160-y. Epub 2019 May 27. PMID: 31134506.	Wrong prediction (no functional decline)
Na YS, Kim JH, Baek MS, Kim WY, Baek AR, Lee BY, Seong GM, Lee SI. In-hospital mortality prediction using frailty scale and severity score in elderly patients with severe COVID-19. Acute Crit Care. 2022 Aug;37(3):303-311. doi: 10.4266/acc.2022.00017. Epub 2022 Jul 5. PMID: 35791648; PMCID: PMC9475168.	wrong prediction (no functional decline)
Van Hauwermeiren C, Claessens M, Berland M, Dumoulin B, Lieten S, Surquin M, Benoit F. Comparison of different prognostic scores in estimating short- and long-term mortality in COVID-19 patients above 60 years old in a university hospital in Belgium. Eur Geriatr Med. 2023 Oct;14(5):1125-1133. doi: 10.1007/s41999-023-00836-4. Epub 2023 Aug 3. PMID: 37535234.	wrong prediction (no functional decline)
Ruiz de Gopegui Miguelena P, Martínez Lamazares MT, Claraco Vega LM, Gurpegui Puente M, González Almárcegui I, Gutiérrez Ibañes P, Carrillo López A, Castiella García CM, Miguelena Hycka J. Evaluating frailty may complement APACHE II in estimating mortality in elderly patients admitted to the ICU after digestive surgery. Med Intensiva (Engl Ed). 2022 May;46(5):239-247. doi: 10.1016/j.medine.2022.02.019. Epub 2022 Mar 2. PMID: 35248506.	wrong prediction (no functional decline)
Kawamura K, Osawa A, Tanimoto M, Kagaya H, Matsuura T, Arai H. Clinical frailty scale is useful in predicting return-to-home in patients admitted due to coronavirus disease. BMC Geriatr. 2023 Jul 13;23(1):433. doi: 10.1186/s12877-023-04133-4. PMID: 37442988; PMCID: PMC10347876.	Wrong prediction (no functional decline)
Ji S, Jung HW, Kim J, Kwon Y, Seo Y, Choi S, Oh HJ, Baek JY, Jang IY, Lee E. Comparative Study of the Accuracy of At-Point Clinical Frailty Scale and Morse Fall Scale in Identifying High-Risk Fall Patients among Hospitalized Adults. Ann Geriatr Med Res. 2023 Jun;27(2):99-105. doi: 10.4235/agmr.23.0057. Epub 2023 Jun 9. PMID: 37305899; PMCID: PMC10326405.	wrong prediction (no functional decline)
Tejiram S, Cartwright J, Taylor SL, Hatcher VH, Galet C, Skeete DA, Romanowski KS. A Prospective Comparison of Frailty Scores and Fall Prediction in Acutely Injured Older Adults. J Surg Res. 2021 Jan;257:326-332. doi: 10.1016/j.jss.2020.08.007. Epub 2020 Sep 2. PMID: 32889331; PMCID: PMC7736528.	Wrong O (no discrimination or calibration measures reported)
Aakre EK, Aakre KM, Flaatten H, Hufthammer KO, Ranhoff AH, Jammer I. High-Sensitivity Cardiac Troponin T and Frailty Predict Short-Term Mortality in Patients ≥75 Years Undergoing Emergency Abdominal Surgery: A Prospective Observational Study. Anesth Analg. 2024 Aug 1;139(2):313-322. doi: 10.1213/ANE.0000000000006845. Epub 2024 Jul 15. PMID: 39008976.	Wrong prediction (no functional decline)
Carter B, Keevil VL, Anand A, Osuafor CN, Goudie RJB, Preller J, Lowry M, Clunie S, Shenkin SD, McCarthy K, Hewitt J, Quinn TJ. The Prognostic and Discriminatory Utility of the Clinical Frailty Scale and Modified Frailty Index Compared to Age. Geriatrics (Basel). 2022 Aug 24;7(5):87. doi: 10.3390/geriatrics7050087. PMID: 36136796; PMCID: PMC9498791.	Wrong prediction (no functional decline)
Vlachogiannis NI, Baker KF, Georgiopoulos G, Lazaridis C, Schim van der Loeff I, Hanrath AT, Sopova K, Tual-Chalot S, Gatsiou A, Spyridopoulos I, Stamatelopoulos K, Duncan CJA, Stellos K. Clinical frailty, and not features of acute infection, is associated with late mortality in COVID-19: a retrospective cohort study. J Cachexia Sarcopenia Muscle. 2022 Jun;13(3):1502-1513. doi: 10.1002/jcsm.12966. Epub 2022 Mar 7. PMID: 35257497; PMCID: PMC9088314.	Wrong P (no restrictions)
Lima DFT, Cristelo D, Reis P, Abelha F, Mourão J. Outcome prediction with Physiological and Operative Severity Score for the enumeration of Mortality and Morbidity score system in elderly patients submitted to elective surgery. Saudi J Anaesth. 2019 Jan-Mar;13(1):46-51. doi: 10.4103/sja.SJA_206_18. PMID: 30692888; PMCID: PMC6329253.	Wrong I (no model of interest evaluated)
Somech J, Joshi A, Mancini R, Chetrit J, Michel C, Sheppard R, Nguyen V, Walker M, Giannetti N, Sharma A, Maghakian D, Laforest E, Afilalo J. Comparison of Questionnaire and Performance-Based Physical Frailty Scales to Predict Survival and Health-Related Quality of Life in Patients With Heart Failure. J Am Heart Assoc. 2023 Mar 21;12(6):e026951. doi: 10.1161/JAHA.122.026951. Epub 2023 Mar 9. PMID: 36892053; PMCID: PMC10111541.	Wrong I (no model of interest evaluated)
Garcia-Perez E, Aguirre-Larracoechea U, Portugal-Porras V, Azpiazu-Landa N, Telletxea-Benguria S. Frailty assessment has come to stay: Retrospective analysis pilot study of two frailty scales in oncological older patients undergoing colorectal surgery. Rev Esp Anestesiol Reanim (Engl Ed). 2023 Jan;70(1):1-9. doi: 10.1016/j.redare.2021.05.023. Epub 2023 Jan 20. PMID: 36682609.	Wrong I (no model of interest evaluated)
Grosshauser FJ, Schoene D, Kiesswetter E, Sieber CC, Volkert D. Frailty in Nursing Homes-A Prospective Study Comparing the FRAIL-NH and the Clinical Frailty Scale. J Am Med Dir Assoc. 2022 Oct;23(10):1717.e1-1717.e8. doi: 10.1016/j.jamda.2022.07.028. Epub 2022 Sep 5. PMID: 36065096.	Wrong O (no discrimination or calibration measures reported)
Węgiel M, Kleczyński P, Dziewierz A, Rzeszutko Ł, Surdacki A, Bartuś S, Rakowski T. Frailty as a Predictor of In-Hospital Outcome in Patients with Myocardial Infarction. J Cardiovasc Dev Dis. 2022 May 5;9(5):145. doi: 10.3390/jcdd9050145. PMID: 35621856; PMCID: PMC9145424.	Wrong prediction (no functional decline)
Puri A, Lloyd AM, Bello AK, Tonelli M, Campbell SM, Tennankore K, Davison SN, Thompson S. Frailty Assessment Tools in Chronic Kidney Disease: A Systematic Review and Meta-analysis. Kidney Med. 2025 Jan 4;7(3):100960. doi: 10.1016/j.xkme.2024.100960. PMID: 39980935; PMCID: PMC11841092.	Wrong prediction (no functional decline)
Wu HHL, Van Mierlo R, McLauchlan G, Challen K, Mitra S, Dhaygude AP, Nixon AC. Prognostic performance of clinical assessment tools following hip fracture in patients with chronic kidney disease. Int Urol Nephrol. 2021 Nov;53(11):2359-2367. doi: 10.1007/s11255-021-02798-7. Epub 2021 Mar 8. PMID: 33686533; PMCID: PMC7939449.	Wrong prediction (no functional decline)
Sze S, Pellicori P, Zhang J, Weston J, Clark AL. Which frailty tool best predicts morbidity and mortality in ambulatory patients with heart failure? A prospective study. Eur Heart J Qual Care Clin Outcomes. 2023 Nov 2;9(7):731-739. doi: 10.1093/ehjqcco/qcac073. PMID: 36385564.	Wrong prediction (no functional decline)
Ishii R, Ogawa T, Ohkoshi A, Nakanome A, Takahashi M, Katori Y. Use of the Geriatric-8 screening tool to predict prognosis and complications in older adults with head and neck cancer: A prospective, observational study. J Geriatr Oncol. 2021 Sep;12(7):1039-1043. doi: 10.1016/j.jgo.2021.03.008. Epub 2021 Mar 21. PMID: 33757718.	Wrong prediction (no functional decline)
Elamin A, Tsoutsanis P, Sinan L, Tari SPH, Elamin W, Kurihara H. Emergency General Surgery: Predicting Morbidity and Mortality in the Geriatric Population. Surg J (N Y). 2022 Sep 26;8(3):e270-e278. doi: 10.1055/s-0042-1756461. Erratum in: Surg J (N Y). 2022 Nov 19;8(4):e341. doi: 10.1055/s-0042-1758693. PMID: 36172534; PMCID: PMC9512589.	Wrong predection (no functional decline)
Soh CH, Guan L, Reijnierse EM, Lim WK, Maier AB. Comparison of the modified Frailty-Index based on laboratory tests and the Clinical Frailty Scale in predicting mortality among geriatric rehabilitation inpatients: RESORT. Arch Gerontol Geriatr. 2022 May-Jun;100:104667. doi: 10.1016/j.archger.2022.104667. Epub 2022 Feb 24. PMID: 35240386.	Wrong prediction (no functional decline)
Fernández Alonso C, Del Arco Galán C, Torres Garate R, Madrigal Valdés JF, Romero Pareja R, Bibiano Guillén C, Rodríguez Miranda B, Ruiz Grinspan MS, Gutiérrez Gabriel S, Del Rey Ubago A, Fuentes Ferrer ME, Martín-Sánchez FJ; Registro Frail-ED-Madrid. Performance of 3 frailty scales for predicting adverse outcomes at 30 days in older patients discharged from emergency departments. Emergencias. 2023 Jun;35(3):196-204. English, Spanish. doi: 10.55633/s3me/E062.2023. PMID: 37350602.	Wrong prediction (no composite outcome with functional decline)
Blomaard LC, Lucke JA, de Gelder J, Anten S, Alsma J, Schuit SCE, Gussekloo J, de Groot B, Mooijaart SP. The APOP screener and clinical outcomes in older hospitalised internal medicine patients. Neth J Med. 2020 Feb;78(1):25-33. PMID: 32043475.	Wrong O (no discrimination or calibration measures reported)
Chong E, Chia JQ, Law F, Chew J, Chan M, Lim WS. Validating a Standardised Approach in Administration of the Clinical Frailty Scale in Hospitalised Older Adults. Ann Acad Med Singap. 2019 Apr;48(4):115-124. PMID: 31131383.	Same population and analyses regarding results CFS as Chong (2018)
Nygaard H, Henriksen M, Suetta C, Ekmann A. Comparison of two frailty screening tools for acutely admitted elderly patients. Dan Med J. 2022 Jul 6;69(8):A11210866. PMID: 35959830.	Wrong prediction (no functional decline)

Beoordelingsdatum en geldigheid

Publicatiedatum : 25-06-2026

Beoordeeld op geldigheid : 25-06-2026

Initiatief en autorisatie

Initiatief:

Cluster Algemene geriatrie/ouderengeneeskunde

Geautoriseerd door:

Nederlandse Internisten Vereniging
Nederlandse Vereniging voor Klinische Geriatrie
Verpleegkundigen en Verzorgenden Nederland

Samenstelling werkgroep

Voor het ontwikkelen van de richtlijnmodules is in 2024 een multidisciplinair cluster ingesteld. Het cluster Algemene geriatrie/ouderengeneeskunde bestaat uit meerdere richtlijnen (zie hier de actuele clusterindeling). De stuurgroep bewaakt het proces van modulair onderhoud binnen het cluster. De expertisegroepsleden brengen hun expertise in, indien nodig. De volgende personen uit het cluster zijn betrokken geweest bij de herziening van deze module:

Clusterstuurgroepleden

Drs. A.J. (Arend) Arends (voorzitter), klinisch geriater, werkzaam in het Van Weel-Bethesda-ziekenhuis te Dirksland, NVKG
Prof. Dr. S.P. (Simon) Mooijaart (vicevoorzitter), internist, werkzaam in het Leids Universitair Medisch Centrum te Leiden, NIV
Drs. R.L. (Rozemarijn) van Bruchem-Visser, internist ouderengeneeskunde, werkzaam in het Erasmus MC te Rotterdam, NIV
Drs. N.S. (Niamh) Landa-Hoogerbrugge, verpleegkundig specialist, werkzaam in het Maasstad Ziekenhuis te Rotterdam, V&VN
Drs. E.M. (Eefje) Meulenberg, klinisch geriater, werkzaam in het Elisabeth-TweeSteden Ziekenhuis te Tilburg, NVKG
G.J.M. (Truus) Noij, vrijwilliger, Senioren Brabant-Zeeland
Dr. T.R. (Rikje) Ruiter, internist ouderengeneeskunde, werkzaam in het Maasstad Ziekenhuis te Rotterdam, NIV
Drs. F.J. (Erik) Slim, revalidatiearts, werkzaam in het Ziekenhuis Rivierenland te Tiel, VRA
Dr. W.M.W.H. (Walther) Sipers, klinisch geriater, werkzaam in het Zuyderland Medisch Centrum te Heerlen/Sittard-Geleen, NVKG

Betrokken clusterexpertisegroepleden

Dr. A.C. (Alferso) Abrahams, internist-nefroloog, werkzaam in het UMC Utrecht te Utrecht, NIV
Drs. I.C. (Iris) Jobse, klinisch geriater, werkzaam in het Bravis Ziekenhuis te Bergen op Zoom, NVKG
Drs. M.A.E. (Marleen) van der Kaaij, internist ouderengeneeskunde, werkzaam in het St. Ziekenhuis Amstelland, NIV
Drs. H.P.P.R. (Heike) de Wever, specialist ouderengeneeskunde, werkzaam bij TanteLouise te Bergen op Zoom, Verenso

Met ondersteuning van

E. (Esther) van der Bijl, literatuurspecialist, Kennisinstituut van de Federatie Medisch Specialisten
Dr. R. (Renee) Bolijn, adviseur, Kennisinstituut van de Federatie Medisch Specialisten
Drs. M. (Mischa) Lenaers, junior adviseur, Kennisinstituut van de Federatie Medisch Specialisten

Belangenverklaringen

Een overzicht van de belangen van de clusterleden 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 via secretariaat@kennisinstituut.nl.

Gemelde (neven)functies en belangen stuurgroep

Naam	Hoofdfunctie	Nevenwerkzaamheden	Gemelde belangen	Ondernomen actie
Arends	klinisch geriater in SpijkenisseMC en VanWeel-Bethesdaziekenhuis; gedetacheerd	voorzitter Stichting Mentorschap Rotterdam per 1-1-2024	Geen	Geen restricties
Van Bruchem-Visser	internist ouderengeneeskunde/ethicus 1.0 fte Erasmus MC Rotterdam	koplopertraject cognitieve stoornissen, inventarisatie diagnostische instrumenten Lid sectie ouderengeneeskunde NIV, vacatiegelden	Presentaties over ethiek op congressen, opbrengsten gaan naar de stichting	Geen restricties
Landa-Hoogerbrugge	Verpleegkundig specialist bij Rivas Zorggroep (ouderengeneeskunde) Bij start project verpleegkundig specialist geriatrie/chirurgie in het Maasstad ziekenhuis.	Geen	Geen	Geen restricties
Meulenberg	Klinisch geriater ETZ	Bestuurslid Coöperatie Medisch Specialisten Midden Brabant (stafbestuur ETZ, onderdeel van hoofdfunctie)	Geen	Geen restricties
Mooijaart	Hoogleraar interne geneeskunde i.h.b. ouderengeneeskunde, Leids Universitair Medisch Centrum	Werkgroep Spoedzorg, Nederlandse Internisten Vereniging (lid) Cluster Geriatrie/Ouderengeneeskunde, FMS (vice-voorzitter)	Acuut Presenterende Oudere Patiënt studie (APOP; hoofdonderzoeker) COVID-19 Outcomes in Older Peeople (COOP; hoofdonderzoeker; ZonMw) COVID-19 Ouderen Landelijke Database (COVID-OLD; hoofdonderzoeker) Chemotherapie Op Maat in Ouderen (COMO; hoofdaanvrager; ZEGG) Cognition in Older People with End Stage Renal Disease (COPE; lid stuurgroep) Pathway for Older People with ESRD studie (POLDER; lid stuurgroep) DIAlysis or not: Outcomes in Older people With Geriatric Assessment study (DIALOGICA; lid stuurgroep; ZEGG) Triage in Elderly people Needing Treatment study (TENT; lid stuurgroep)	Geen restricties
Noij	geen werkgever bekend	Vrijwilliger bij Senioren Brabant-Zeeland	Geen	Geen restricties
Ruiter	Internist ouderengeneeskunde, klinisch farmacoloog, Maasstad ziekenhuis 0.8 fte. Mijn aanstelling bij het college ter beoordeling van Geneesmiddelen, ik ben daar collegelid, 0.16 fte	Postdoctoraal onderzoeker, afdeling epidemiologie, EMC, Rotterdam, 0.1 fte. NIV: Lid commissie richtlijnen - vacatie gelden. Secretaris Forum Visitatorum - vacatie gelden. Overig: Lid Raad van Toezicht Stichting Landelijk Wonen Klein Houtdijk - vacatiegelden. Redactie lid Tijdschrift voor gerontologie en geriatrie. - onbezoldigd.	Geen	Geen restricties
Sipers	scen-arts, klinisch geriater, opleider binnen Zuyderland Medisch Centrum te Heerlen-Sittard-Geleen.	Richtlijn Ondervoeding en sarcopenie Cluster algemene geriatrie Namens NVKG afgevaardigd om de participeren in de werkgroep als voorzitter om deze richtlijn te ontwikkelen	Die heb ik niet. Na mijn promotie onderzoek is mijn interesse voor ondervoeding en sarcopenie alleen maar groter geworden en hoop ik een bijdrage te kunnen leveren aan zinnige zorg.	Geen restricties
Slim	Revalidatiearts ziekenhuis rivierenland Tiel (loondienst). Revalidatiearts Jow Voetkliniek (vaste aanstelling) ZBC gericht op zkh verplaatste zorg in de eerstelijn. 2025 Revalidatiearts Deventer zkh (tijdelijke waarneming). 2025 Revalidatiearts CIR tijdelijk contract.	Docent UMCU, onbetaald. Raad van Advies OIM-OSB van SEMH, onkostenvergoeding. Scientific Review Committee Leprosy Research Initiative. Lepastichting, onbetaald. Firma IPSEN. Onderwijsproject. Skills lab anatomie, onkostenvergoeding.	ZonMW: deelname aan gesubsidieerd onderzoek naar gevolgen en revalidatie van post-IC patienten die Covid hebben gehad. ZonMW: deelname aan Shoe-OFF studie	Geen restricties

Gemelde (neven)functies en belangen expertisegroep

Naam	Hoofdfunctie	Nevenwerkzaamheden	Gemelde belangen	Ondernomen actie
Abrahams	Internist-nefroloog UMC Utrecht	Geen	1. DIALOGICA: Conservatieve behandeling vs dialyse bij oudere patienten met nierfalen, projectleider 2. Domestico: Effecten van thuisdialyse vs centrumdialyse, projectleider	Geen restricties
Jobse	Bravis Ziekenhuis, klinisch geriater	Geen	Geen	Geen restricties
Van der Kaaij	Internist Ouderengeneeskunde Ziekenhuis Amstelland, Amstelveen	Voorzitter Gezamenlijke Wetenschapscommissie Ouderengeneeskunde van NIV Ouderengeneeskunde en NVKG Lid Kerngroep Ouderengeneeskunde van NIV	Geen	Geen restricties
De Wever	Specialist ouderengeneeskunde, werkgever stichting tanteLouise, Bergen op Zoom.	Neem deel aan platform Prothese van het VWS.	Geen	Geen restricties

Inbreng patiëntenperspectief

Er werd aandacht besteed aan het patiëntenperspectief door deelname van relevante patiëntenorganisaties aan de need-for-update en/of prioritering. Vanuit de stuurgroep nam tevens een lid deel namens Senioren Brabant Zeeland. De verkregen input is meegenomen bij het afbakenen en uitwerken van de modules. De conceptrichtlijnmodules zijn daarnaast 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 voerden de clusterleden conform de Wet kwaliteit, klachten en geschillen zorg (Wkkgz) een kwalitatieve raming uit om te beoordelen 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 bij Werkwijze).

Module	Uitkomst raming	Toelichting
Identificatie van kwetsbaarheid bij ouderen	Geen financiële gevolgen	Uitkomst 3: Hoewel uit de toetsing volgt dat de aanbeveling breed toepasbaar is (>40.000 patiënten), volgt uit de toetsing dat het geen nieuwe manier van zorgverlening of andere organisatie van zorgverlening betreft, het geen toename in het aantal in te zetten voltijdsequivalenten van zorgverleners betreft en het geen wijziging in het opleidingsniveau van zorgpersoneel betreft. Er worden daarom geen financiële gevolgen verwacht.

Werkwijze

Voor meer details over de gebruikte richtlijnmethodologie verwijzen wij u naar de Werkwijze. Relevante informatie voor de ontwikkeling/herziening van deze richtlijnmodule is hieronder weergegeven.

Zoekverantwoording

Zoekstrategie - 11 maart 2025

Embase.com

*No.*	*Query*	*Results*
#1	('aged hospital patient'/exp OR 'institutionalized elderly'/exp OR 'frail elderly'/exp OR 'very elderly'/exp OR eldest:de,ab,ti OR ((oldest NEXT/1 (old* OR elder)):de,ab,ti) OR senium:de,ab,ti OR ((very NEXT/1 (old OR elder)):de,ab,ti) OR septagenarian:de,ab,ti OR octagenarian:de,ab,ti OR octogenarian:de,ab,ti OR nonagenarian:de,ab,ti OR centarian:de,ab,ti OR centenarian:de,ab,ti OR supercentenarian:de,ab,ti OR (((75 OR 80 OR 85 OR 90 OR 95 OR 100) NEAR/2 (year* OR age)):ti,ab,kw) OR (((old OR eldest OR elder* OR aged) NEXT/3 (people OR patient* OR individual* OR adult)):ti,ab,kw) OR senil:ti,ab,kw OR frail:ti,ab,kw) NOT (('adolescent'/exp OR 'child'/exp OR adolescent:ti,ab,kw OR child:ti,ab,kw OR schoolchild:ti,ab,kw OR infant:ti,ab,kw OR girl:ti,ab,kw OR boy:ti,ab,kw OR teen:ti,ab,kw OR teens:ti,ab,kw OR teenager:ti,ab,kw OR youth:ti,ab,kw OR pediatr:ti,ab,kw OR paediatr:ti,ab,kw OR puber:ti,ab,kw) NOT ('adult'/exp OR 'aged'/exp OR 'middle aged'/exp OR adult*:ti,ab,kw OR man:ti,ab,kw OR men:ti,ab,kw OR woman:ti,ab,kw OR women:ti,ab,kw))	1329174
#2	'morse fall scale'/exp OR 'triage risk screening tool'/exp OR 'goodness of fit index'/exp OR 'edmonton frail scale'/exp OR 'clinical frailty scale'/exp OR 'frailty index'/exp OR 'frailty score'/exp OR 'frailty assessment'/exp OR 'frailty index score'/exp OR 'frailty screening index'/exp OR 'frailty risk score'/exp OR 'frail scale'/exp OR 'tilburg frailty indicator'/exp OR (((bright OR compri OR 'fi?cga' OR harp OR isar OR 'isar?hp' OR mfs OR mpi OR sherpa OR trst OR runciman OR rowland OR vip OR vms OR g8 OR barber OR fried OR moca OR mmse OR '6?cit' OR efs OR erasmus OR cfs OR edmonton OR tilburg OR 4at OR apop OR fti OR tfi) NEAR/3 (instrument* OR tool* OR scale* OR score* OR scoring OR assessment* OR indicator* OR questionnaire* OR screen* OR frail)):ti,ab,kw) OR (('geriatric assessment'/exp OR 'scoring system'/exp OR 'clinical assessment tool'/exp OR 'screening test'/exp) AND frail:ti,ab,kw) OR ((frail* NEAR/3 (instrument* OR tool* OR scale* OR score* OR scoring OR assessment* OR indicator)):ti,ab,kw) OR (((screening NEAR/3 (instrument* OR tool* OR assessment* OR test)):ti,ab,kw) AND frail:ti,ab,kw) OR ('goodness of fit index':ti,ab,kw AND frail:ti,ab,kw) OR 'frail index':ti,ab,kw OR 'silver code':ti,ab,kw OR 'apop stud':ti,ab,kw	57338
#3	'prognosis'/exp OR 'prognostic assessment'/exp OR 'prediction'/exp OR predict:ti,ab,kw OR prognos:ti,ab,kw	4392271
#4	#1 AND #2 AND #3	12377
#5	#4 AND [2018-2025]/py NOT ('conference abstract'/it OR 'editorial'/it OR 'letter'/it OR 'note'/it) NOT (('animal'/exp OR 'animal experiment'/exp OR 'animal model'/exp OR 'nonhuman'/exp) NOT 'human'/exp)	5630
#6	'meta analysis'/exp OR 'systematic review'/exp OR 'scoping review'/exp OR 'rapid review'/exp OR 'umbrella review'/exp OR 'cochrane database of systematic reviews'/jt OR 'network meta-analysis'/exp OR 'networkmeta analy':ti,ab,kw OR 'networkmetaanaly':ti,ab,kw OR metaanaly:ti,ab,kw OR 'meta analy':ti,ab,kw OR metanaly:ti,ab,kw OR prisma:ti,ab,kw OR prospero:ti,ab,kw OR metaanali:ti,ab,kw OR 'meta anali':ti,ab,kw OR metanali:ti,ab,kw OR (((systemati* OR scoping OR umbrella OR 'structured literature') NEAR/3 (review* OR overview)):ti,ab,kw) OR (((structured OR systemic) NEAR/3 (review* OR overview* OR synth) NEAR/3 literature):ti,ab,kw) OR ((systemic NEAR/1 review):ti,ab,kw) OR (((systemati OR literature OR database* OR 'data base') NEAR/10 search):ti,ab,kw) OR (((structured OR comprehensive* OR systemic) NEAR/3 search):ti,ab,kw) OR (((literature NEAR/3 (review* OR overview)):ti,ab,kw) AND (search:ti,ab,kw OR database:ti,ab,kw OR 'data base':ti,ab,kw)) OR (('data extraction':ti,ab,kw OR 'data source':ti,ab,kw) AND ('study selection':ti,ab,kw OR 'studies selection':ti,ab,kw)) OR ('search strateg':ti,ab,kw AND 'selection criteria':ti,ab,kw) OR ('data source':ti,ab,kw AND 'data synth':ti,ab,kw) OR medline:ti,ab,kw OR pubmed:ti,ab,kw OR 'pub med':ti,ab,kw OR embase:ti,ab,kw OR cochrane:ti,ab,kw OR (((critical* OR rapid) NEAR/2 (review OR overview* OR synth)):ti) OR ((((critical OR rapid) NEAR/3 (review OR overview* OR synth)):ab) AND (search:ab OR database:ab OR 'data base':ab)) OR metasynth:ti,ab,kw OR 'meta synth':ti,ab,kw OR 'review* of review*':ti,ab,kw	1088056
#7	'clinical trial'/exp OR 'randomization'/exp OR 'single blind procedure'/exp OR 'double blind procedure'/exp OR 'crossover procedure'/exp OR 'placebo'/exp OR 'prospective study'/exp OR rct:ab,ti OR random:ab,ti OR 'single blind':ab,ti OR 'randomised controlled trial':ab,ti OR 'randomized controlled trial'/exp OR placebo:ab,ti	4225278
#8	'major clinical study'/de OR 'clinical study'/de OR 'family study'/de OR 'longitudinal study'/de OR 'retrospective study'/de OR 'prospective study'/de OR 'cohort analysis'/de OR 'case control study'/de OR 'comparative study'/exp OR 'control group'/de OR 'controlled study'/de OR 'controlled clinical trial'/de OR 'crossover procedure'/de OR 'double blind procedure'/de OR 'phase 2 clinical trial'/de OR 'phase 3 clinical trial'/de OR 'phase 4 clinical trial'/de OR 'pretest posttest design'/de OR 'pretest posttest control group design'/de OR 'quasi experimental study'/de OR 'single blind procedure'/de OR 'triple blind procedure'/de OR ((cohort NEAR/1 (study OR studies)):ab,ti) OR (('case control' NEAR/1 (study OR studies)):ab,ti) OR (('follow up' NEAR/1 (study OR studies)):ab,ti) OR (observational NEAR/1 (study OR studies)) OR ((epidemiologic NEAR/1 (study OR studies)):ab,ti) OR (('cross sectional' NEAR/1 (study OR studies)):ab,ti) OR (((control OR controlled) NEAR/6 trial):ti,ab,kw) OR (((control OR controlled) NEAR/6 (study OR studies)):ti,ab,kw) OR (((control OR controlled) NEAR/1 active):ti,ab,kw) OR 'open label':ti,ab,kw OR (((double OR two OR three OR multi OR trial) NEAR/1 (arm OR arms)):ti,ab,kw) OR ((allocat NEAR/10 (arm OR arms)):ti,ab,kw) OR placebo:ti,ab,kw OR 'sham-control':ti,ab,kw OR (((single OR double OR triple OR assessor) NEAR/1 (blind* OR masked)):ti,ab,kw) OR nonrandom:ti,ab,kw OR 'non-random':ti,ab,kw OR 'quasi-experiment':ti,ab,kw OR crossover:ti,ab,kw OR 'cross over':ti,ab,kw OR 'parallel group':ti,ab,kw OR 'factorial trial':ti,ab,kw OR ((phase NEAR/5 (study OR trial)):ti,ab,kw) OR ((case* NEAR/6 (matched OR control)):ti,ab,kw) OR ((match NEAR/6 (pair OR pairs OR cohort* OR control* OR group* OR healthy OR age OR sex OR gender OR patient* OR subject* OR participant)):ti,ab,kw) OR ((propensity NEAR/6 (scor OR match)):ti,ab,kw) OR versus:ti OR vs:ti OR compar:ti OR ((compar* NEAR/1 study):ti,ab,kw) OR (('observational study'/de OR 'cross-sectional study'/de OR 'multicenter study'/de OR 'correlational study'/de OR 'follow up'/de OR cohort:ti,ab,kw OR 'follow up':ti,ab,kw OR followup:ti,ab,kw OR longitudinal:ti,ab,kw OR prospective:ti,ab,kw OR retrospective:ti,ab,kw OR observational:ti,ab,kw OR 'cross sectional':ti,ab,kw OR cross?ectional:ti,ab,kw OR multicent:ti,ab,kw OR 'multi-cent':ti,ab,kw OR consecutive:ti,ab,kw) AND (group:ti,ab,kw OR groups:ti,ab,kw OR subgroup:ti,ab,kw OR versus:ti,ab,kw OR vs:ti,ab,kw OR compar:ti,ab,kw OR 'odds ratio':ab OR 'relative odds':ab OR 'risk ratio':ab OR 'relative risk*':ab OR 'rate ratio':ab OR aor:ab OR arr:ab OR rrr:ab OR ((('or' OR 'rr') NEAR/6 ci):ab)))	17876821
#9	#5 AND #6 - SR	356
#10	#5 AND #7 NOT #9 - RCT	1573
#11	#5 AND #8 NOT (#9 OR #10) - Observationeel	3199
#12	#9 OR #10 OR #11 - Totaal	5128

Ovid/Medline

#	Searches	Results
1	exp "Aged, 80 and over"/ or exp Centenarians/ or exp Nonagenarians/ or exp Octogenarians/ or exp Frail Elderly/ or exp Frailty/ or exp Frail Elderly/ or eldest.ti,ab,kf. or (oldest adj1 (old* or elder)).ti,ab,kf. or senium.ti,ab,kf. or (very adj1 (old or elder)).ti,ab,kf. or septagenarian.ti,ab,kf. or octagenarian.ti,ab,kf. or octogenarian.ti,ab,kf. or nonagenarian.ti,ab,kf. or centarian.ti,ab,kf. or centenarian.ti,ab,kf. or supercentenarian.ti,ab,kf. or (("75" or "80" or "85" or "90" or "95" or "100") adj2 (year* or age)).ti,ab,kf. or ((old or eldest or elder* or aged) adj3 (people or patient* or individual* or adult)).ti,ab,kf. or senil.ti,ab,kf. or frail*.ti,ab,kf.	1835942
2	((exp Geriatric Assessment/ or Mass Screening/ or exp Risk Assessment/) and (exp Frailty/ or frail.ti,ab,kf.)) or ((bright or compri or fi?cga or harp or isar or isar?hp or mfs or mpi or sherpa or trst or runciman or rowland or vip or vms or g8 or barber or fried or moca or mmse or 6?cit or efs or erasmus or cfs or edmonton or tilburg or 4at or apop or fti or tfi) adj3 (instrument or tool* or scale* or score* or scoring or assessment* or indicator* or questionnaire* or screen* or frail)).ti,ab,kf. or (frail adj3 (instrument* or tool* or scale* or score* or scoring or assessment* or indicator)).ti,ab,kf. or ((screening adj3 (instrument* or tool* or assessment* or test)) and frail).ti,ab,kf. or (goodness of fit index and frail).ti,ab,kf. or frail index.ti,ab,kf. or silver code.ti,ab,kf. or apop stud.ti,ab,kf.	34246
3	exp "Predictive Value of Tests"/ or Prognosis/ or predict.ti,ab,kf. or prognos.ti,ab,kf.	3271590
4	1 and 2 and 3	8535
5	limit 4 to yr="2018 -Current"	5996
6	5 not (comment/ or editorial/ or letter/) not ((exp animals/ or exp models, animal/) not humans/)	5895
7	meta-analysis/ or meta-analysis as topic/ or (metaanaly* or meta-analy* or metanaly).ti,ab,kf. or systematic review/ or cochrane.jw. or (prisma or prospero).ti,ab,kf. or ((systemati or scoping or umbrella or "structured literature") adj3 (review* or overview)).ti,ab,kf. or (systemic adj1 review).ti,ab,kf. or ((systemati or literature or database* or data-base) adj10 search).ti,ab,kf. or ((structured or comprehensive* or systemic) adj3 search).ti,ab,kf. or ((literature adj3 review) and (search or database* or data-base)).ti,ab,kf. or (("data extraction" or "data source") and "study selection").ti,ab,kf. or ("search strategy" and "selection criteria").ti,ab,kf. or ("data source" and "data synthesis").ti,ab,kf. or (medline or pubmed or embase or cochrane).ab. or ((critical or rapid) adj2 (review or overview* or synthes)).ti. or (((critical or rapid) adj3 (review or overview* or synthes)) and (search or database* or data-base)).ab. or (metasynthes or meta-synthes*).ti,ab,kf.	815123
8	exp clinical trial/ or randomized controlled trial/ or exp clinical trials as topic/ or randomized controlled trials as topic/ or Random Allocation/ or Double-Blind Method/ or Single-Blind Method/ or (clinical trial, phase i or clinical trial, phase ii or clinical trial, phase iii or clinical trial, phase iv or controlled clinical trial or randomized controlled trial or multicenter study or clinical trial).pt. or random.ti,ab. or (clinic adj trial).tw. or ((singl or doubl* or treb* or tripl) adj (blind$3 or mask$3)).tw. or Placebos/ or placebo.tw.	2854965
9	Epidemiologic studies/ or case control studies/ or exp cohort studies/ or Controlled Before-After Studies/ or Case control.tw. or cohort.tw. or Cohort analy$.tw. or (Follow up adj (study or studies)).tw. or (observational adj (study or studies)).tw. or Longitudinal.tw. or Retrospective.tw. or prospective.tw. or consecutive*.tw. or Cross sectional.tw. or Cross-sectional studies/ or historically controlled study/ or interrupted time series analysis/ [Onder exp cohort studies vallen ook longitudinale, prospectieve en retrospectieve studies]	4981898
10	Case-control Studies/ or clinical trial, phase ii/ or clinical trial, phase iii/ or clinical trial, phase iv/ or comparative study/ or control groups/ or controlled before-after studies/ or controlled clinical trial/ or double-blind method/ or historically controlled study/ or matched-pair analysis/ or single-blind method/ or (((control or controlled) adj6 (study or studies or trial)) or (compar* adj (study or studies)) or ((control or controlled) adj1 active) or "open label" or ((double or two or three or multi or trial) adj (arm or arms)) or (allocat adj10 (arm or arms)) or placebo* or "sham-control" or ((single or double or triple or assessor) adj1 (blind or masked)) or nonrandom* or "non-random" or "quasi-experiment" or "parallel group" or "factorial trial" or "pretest posttest" or (phase adj5 (study or trial)) or (case adj6 (matched or control)) or (match adj6 (pair or pairs or cohort* or control* or group* or healthy or age or sex or gender or patient* or subject* or participant)) or (propensity adj6 (scor or match))).ti,ab,kf. or (confounding adj6 adjust).ti,ab. or (versus or vs or compar).ti. or ((exp cohort studies/ or epidemiologic studies/ or multicenter study/ or observational study/ or seroepidemiologic studies/ or (cohort or 'follow up' or followup or longitudinal* or prospective* or retrospective* or observational* or multicent* or 'multi-cent' or consecutive).ti,ab,kf.) and ((group or groups or subgroup* or versus or vs or compar).ti,ab,kf. or ('odds ratio' or 'relative odds' or 'risk ratio' or 'relative risk' or aor or arr or rrr).ab. or (("OR" or "RR") adj6 CI).ab.))	5927084
11	6 and 7 - SR	364
12	(6 and 8) not 11 - RCT	794
13	(6 and (9 or 10)) not (11 or 12) - Observationeel	3723
14	11 or 12 or 13 - Totaal	4881

Richtlijnendatabase

Comprehensive geriatric assessment (CGA)

Comprehensive geriatric assessment (CGA)

Identificatie van kwetsbaarheid bij ouderen

Uitgangsvraag

Aanbeveling

Overwegingen

Onderbouwing

Beoordelingsdatum en geldigheid

Initiatief en autorisatie

Samenstelling werkgroep

Belangenverklaringen

Inbreng patiëntenperspectief

Werkwijze

Zoekverantwoording

Comprehensive geriatric assessment (CGA)

Comprehensive geriatric assessment (CGA)

Uitgangsvraag

Aanbeveling

Overwegingen

Onderbouwing

Achtergrond

Conclusies / Summary of Findings

Samenvatting literatuur

Zoeken en selecteren

Referenties

Evidence tabellen

Verantwoording

Beoordelingsdatum en geldigheid

Initiatief en autorisatie

Samenstelling werkgroep

Belangenverklaringen

Inbreng patiëntenperspectief

Werkwijze

Zoekverantwoording

Bijlagen

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