Biochemische diagnostiek

Beoordeeld: 08-07-2022

Uitgangsvraag

Wat is de (toegevoegde) waarde van verschillende biochemische bepalingen in de liquor cerebrospinalis voor het stellen van de diagnose bacteriële meningitis?

De uitgangsvraag heeft betrekking op de volgende liquorbepalingen:

lactaat
procalcitonine

Aanbeveling

Bepaal bij verdenking op een community acquired bacteriële meningitis het celgetal, totaal eiwit en glucosegehalte in de liquor cerebrospinalis. Voeg vooralsnog niet routinematig de bepaling van procalcitonine en lactaat toe.

Overwegingen

Voor- en nadelen van de interventie en de kwaliteit van het bewijs

Er is een literatuuronderzoek verricht naar biochemische liquordiagnostiek additioneel aan conventioneel onderzoek van het celgetal, totaal eiwit en glucoseconcentratie in liquor. Om de juiste patiënten zo snel mogelijk antibiotica te kunnen geven ter behandeling van bacteriële meningitis is het van belang om onderscheid te kunnen maken tussen bacteriële en aseptische meningitis bij patiënten met een verdenking op ‘community acquired bacterial meningitis’. In deze module zijn twee nieuwe testen onderzocht: lactaat en procalcitonine, beiden gemeten in de liquor cerebrospinalis.

De diagnostische accuratesse verschilt per studie en is bovendien afhankelijk van de onderzoekspopulatie en de prevalentie van bacteriële meningitis. Op basis van de geselecteerde literatuur blijkt dat de diagnostische accuratesse van procalcitonine vergelijkbaar en die van lactaat wellicht zelfs iets beter is dan die van celgetal, totaal eiwit en glucoseconcentratie als deze een op een vergeleken worden. De bewijskracht van de geïncludeerde studies is echter laag. Ook is de specificiteit van lactaat nog onvoldoende bekend voor patiënten die zich presenteren met convulsies of cerebrale ischemie. Dat wil zeggen dat meer onderzoek nodig is voordat er met zekerheid kan worden gezegd dat deze nieuwe testen beter presteren dan de conventionele testen.

De waarde van de conventionele liquorbepalingen celgetal, eiwit en glucose staat echter niet ter discussie. In de praktijk worden de biochemische bepalingen in liquor niet individueel, maar in samenhang beoordeeld. Het is niet duidelijk hoe de testkarakteristieken van lactaat of procalcitonine zich verhouden tot de interpretatie van de combinatie van celgetal, glucose (ratio) en eiwit omdat dit nog niet is onderzocht. De eventuele toegevoegde waarde van procalcitonine of lactaat in liquor als extra bepaling naast de standaard chemie is ook onvoldoende onderzocht. Om een uitspraak te kunnen doen of de toevoeging van lactaat en/of procalcitonine daadwerkelijk bijdraagt aan een snellere en betere diagnose van bacteriële en/of aseptische meningitis is het essentieel dat de toegevoegde waarde van deze twee markers naast de conventionele testen wordt onderzocht.

Naast de lactaat- en procalcitonine-test zijn er nog andere nieuwe testen (bijvoorbeeld cytokines) in liquor beschreven in de literatuur. Deze bepalingen worden echter nog alleen in studieverband gedaan. Vanwege de beperkte toepassingsmogelijkheden in huidige praktijk zijn deze testen niet meegenomen in de literatuursamenvatting. Meer onderzoek naar de toepasbaarheid hiervan in de patiëntenzorg is nodig voordat deze testen daadwerkelijk geïntroduceerd kunnen worden in de diagnostiek.

Waarden en voorkeuren van patiënten (en eventueel hun verzorgers)

Bacteriële meningitis is een ernstig ziektebeeld met een hoge mortaliteit en morbiditeit.

Het is daarom belangrijk om bij verdenking op een bacteriële meningitis deze diagnose snel met behulp van liquordiagnostiek (via een lumbaalpunctie) vast te stellen of uit te sluiten. Wanneer de diagnose op basis van de uitslagen van biochemisch onderzoek van de liquor niet voldoende onwaarschijnlijk gemaakt kan worden, volgt empirische behandeling met antibiotica in afwachting van verdere uitslagen van microbiologische diagnostiek. Deze strategie leidt bewust tot overbehandeling van patiënten. Sommige patiënten zullen achteraf gezien onterecht (langer) opgenomen zijn en met antibiotica en corticosteroïden behandeld. Het is echter aannemelijk dat deze strategie voor de groep patiënten met verdenking op een bacteriële meningitis leidt tot de beste uitkomst. De werkgroep is van mening dat er onvoldoende bewijs is dat het routinematig bepalen van lactaat of procalcitonine in liquor zal leiden tot minder overbehandeling, en dat ook niet leidt tot een slechtere uitkomst bij patiënten bij wie de diagnose bacteriële meningitis onterecht werd verworpen.

Kosten (middelenbeslag)

Aangezien de aanbeveling niet leidt tot een aanpassing van het huidige beleid zullen de kosten gelijk blijven.

Aanvaardbaarheid, haalbaarheid en implementatie

Aangezien de aanbeveling niet leidt tot een aanpassing van het huidige beleid verwacht de werkgroep geen problemen wat betreft de aanvaardbaarheid, haalbaarheid en/of implementatie wat betreft de aanbeveling.

Rationale van de aanbeveling: weging van argumenten voor en tegen de interventie

Alhoewel het bepalen van procalcitonine en/of lactaat in liquor een bacteriële meningitis meer of minder waarschijnlijk kan maken, is de meerwaarde van deze bepalingen ten opzichte van de combinatie van celgetal, totaal eiwit en glucose(ratio) niet aangetoond. Of procalcitonine en/of lactaat bepalingen in liquor als aanvulling op celgetal, eiwit en glucose (ratio) een toegevoegde waarde kan hebben is onvoldoende onderzocht.

Onderbouwing

Achtergrond

De testkarakteristieken van biochemische bepalingen voor het stellen van de diagnose bacteriële meningitis verschillen per gekozen afkapwaarde, per leeftijdsgroep, per verwekker en als gevolg van co-morbiditeit. Het is onduidelijk of er nieuw verschenen onderzoeken zijn die kunnen bijdragen aan een betere inschatting van de kans op bacteriële meningitis aan de hand van uitslagen van biochemisch onderzoek van de liquor. Bij nieuwe testen verdient het de voorkeur om de toegevoegde waarde boven op de gebruikelijke liquordiagnostiek te bepalen.

Conclusies

Lactate versus conventional markers

GRADE

Sensitivity, specificity, PPV, NPV (neonates)

None of the studies reported the diagnostic accuracy, specifically in neonates. Therefore, it was not possible to draw a conclusion regarding this outcome measure.

Low

GRADE

Sensitivity (patients >1 month old)

The sensitivity of the lactate test is superior (relative difference of > 10%) compared to the glucose test, glucose ratio, protein concentration and the total number of leukocytes.

Sources: (Buch, 2018; Giulieri, 2015; Huy, 2010)

Low

GRADE

Specificity (patients >1 month old)

The specificity of the lactate test is superior (relative difference of > 10%) compared to the protein concentration, and total number of leukocytes. However, the specificity is similar compared to the glucose test, and glucose ratio.

Sources: (Buch, 2018; Giulieri, 2015; Huy, 2010; Sanaei Dashti, 2017)

Low

GRADE

PPV (patients >1 month old)

The PPV of the lactate test is superior (relative difference of > 10%) compared to the glucose test, protein concentration, and total number of leukocytes. However, the PPV is similar compared to the glucose ratio.

Sources: (Buch, 2018; Giulieri, 2015; Huy, 2010; Sanaei Dashti, 2017)

Low

GRADE

NPV (patients >1 month old)

The NPV of the lactate test is superior (relative difference of > 10%) compared to all conventional markers (glucose, glucose ratio, protein concentration, and total number of leukocytes).

Sources: (Buch, 2018; Giulieri, 2015; Huy, 2010; Sanaei Dashti, 2017)

Lactate in addition to conventional markers

GRADE

Sensitivity, specificity, PPV, NPV (neonates and patients >1 month old)

None of the studies reported the diagnostic accuracy of lactate as an additional marker to conventional CSF markers. Therefore, it was not possible to draw a conclusion regarding these outcome measures.

Procalcitonin versus conventional markers

Low

GRADE

Sensitivity (neonates)

The sensitivity of the procalcitonin test is similar (relative difference of < 10%) compared to the protein concentration. However, the sensitivity is similar compared to the glucose test, glucose ratio, and total number of leukocytes.

Sources: (Reshi, 2017)

Low

GRADE

Specificity (neonates)

The specificity of the procalcitonin test is similar (relative difference of < 10%) compared to all conventional markers (glucose test, glucose ratio, protein concentration, and total number of leukocytes).

Sources: (Reshi, 2017)

Low

GRADE

PPV (neonates)

The PPV of the procalcitonin test is similar (relative difference of <10%) compared to all conventional markers (glucose test, glucose ratio, protein concentration, and total number of leukocytes).

Sources: (Reshi, 2017)

Low

GRADE

NPV (neonates)

The NPV of the procalcitonin test is superior (relative difference of > 10%) compared to the protein concentration. However, the NPV of the procalcitonin test is similar (relative difference of < 10%) compared to the glucose test, glucose ratio, and total number of leukocytes).

Sources: (Reshi, 2017)

GRADE

Sensitivity, specificity, PPV, NPV (patients >1 month old)

None of the studies compared the procalcitonin test with the conventional marker glucose, the glucose ratio, and the protein concentration. Therefore, it was not possible to draw a conclusion regarding these conventional markers.

Sources: (Sanaei, Dashti, 2017)

Very low GRADE

Sensitivity (patients > 1 month old)

The sensitivity of the procalcitonin test is similar (relative difference of < 10%) compared to the total number of leukocytes in patients >1 month old.

Sources: (Sanaei, Dashti, 2017)

Very low GRADE

Specificity (patients > 1 month old)

The sensitivity of the procalcitonin test is inferior (relative difference of >10%) compared to the total number of leukocytes in patients > 1 month old.

Sources: (Sanaei, Dashti, 2017)

Very low GRADE

PPV (patients > 1 month old)

The PPV of the procalcitonin test is inferior (relative difference of > 10%) compared to the total number of leukocytes in patients > 1 month old.

Sources: (Sanaei, Dashti, 2017)

Very low GRADE

NPV (patients > 1 month old)

The NPV of the procalcitonin test is similar (relative difference of < 10%) compared to the total number of leukocytes in patients > 1 month old.

Sources: (Sanaei, Dashti, 2017)

Procalcitonin in addition to conventional markers

GRADE

Sensitivity, specificity, PPV, NPV (neonates and patients > 1 month old)

None of the studies reported the diagnostic accuracy. Therefore, it was not possible to draw a conclusion regarding these outcome measures.

Samenvatting literatuur

Description of studies (CSF lactate)

Systematic reviews

The systematic review of Huy (2010) evaluated the value of cerebrospinal fluid (CSF) lactate concentration as a marker to differentiate between bacterial meningitis and aseptic meningitis. Searches in PubMed, Scopus, the MEDION database, and the Cochrane Library were conducted to identify relevant articles published before March 2009. Only articles written in English that evaluated the CSF lactate concentration for differential diagnosis distinguishing bacterial meningitis (BM) from aseptic meningitis were included. Studies with < 16 patients were excluded to limit selection bias. In addition, animal studies, case reports, replies, reviews, studies in which data could not be extracted, and studies that used lactate as a criterion for aseptic meningitis diagnosis were excluded. In total, 25 studies were identified that met the eligibility criteria: 18 studies with a cross-sectional study design and seven studies with a case-control study design. A meta-analysis was performed of these 25 studies. The studies included 783 patients with bacterial meningitis and 909 patients with aseptic meningitis. Excluded from the bacterial meningitis group were (1) patients with tuberculous or fungal meningitis, (2) BM patients who received antibiotics before lumbar puncture, (3) post-surgery or traumatic patients, and (4) patients with other central nervous system conditions that could contribute to elevation of CSF lactate (such as recent stroke, seizures, brain hypoxia, and brain trauma). The studies included children, adults or a combination of children and adults but did not report a subgroup analysis. The systematic review assessed the accuracy of CSF lactate as a differential marker for diagnosed bacterial meningitis and diagnosed aseptic meningitis. The systematic review also compared the diagnostic accuracy of the CSF lactate marker to four conventional markers (CSF glucose, CSF/plasma glucose ratio, CSF protein and CSF leukocyte count). Bacterial meningitis was defined as CSF pleocytosis and one of the following criteria: positive CSF Gram-stained smear for a bacterial pathogen, positive CSF or blood culture for a bacterial pathogen, positive CSF latex agglutination assay or PCR assay for a bacterial pathogen. The diagnostic accuracy of the CSF lactate marker was compared with the conventional markers: glucose (CSF), glucose ratio (CSF/plasma), protein concentration (CSF), leukocytes (CSF total number). The diagnostic accuracy of CSF lactate in addition to the conventional markers was not reported.

Additional observational studies

The study of Buch (2018) assessed the diagnostic value of CSF lactate to discriminate between bacterial meningitis and aseptic meningitis. All patients aged 15 years or older were prospectively included if they had a microbiologically proven CNS infection or a clinical presentation strongly suggestive of a CNS infection and CSF leukocytes > 10 x 10⁶ cells/L. In total, 176 patients were included in the study of which 51 had bacterial meningitis (mean age 64 years old) and 125 aseptic meningitis (mean age 41 years old). The diagnostic accuracy of the CSF lactate marker was compared with the conventional markers: total number of leukocytes, glucose ratio and protein. The diagnostic accuracy of CSF lactate in addition to the conventional markers was not reported.

The study of Sanaei Dashti (2017) evaluated the diagnostic accuracy of lactate, procalcitonin and other known biomarkers to differentiate bacterial meningitis from viral meningitis. Any child aged 28 days to 14 years who was diagnosed with suspected meningitis who underwent a lumber puncture was included. In total, 50 patients were diagnosed with meningitis with an average age of 42.75 months, ranging between 21 days and 144 months. From these 50 patients, 12 were diagnosed with bacterial meningitis and 38 with viral meningitis. The clinical diagnosis was used as a reference standard for bacterial meningitis and aseptic meningitis. Patients were divided into two groups with a definite or presumed diagnosis. A definite bacterial meningitis diagnosis was based on a positive Gram staining, culture or PCR, a presumed diagnosis was based on the presence of clinical picture of meningitis with at least two of the following: protein ≥ 80, glucose ≤ 40, WBC ≥ 300, and/ or polymorph nuclear cell predominancy. The diagnostic accuracy of the CSF lactate marker and CSF procalcitonin marker was compared with the CSF number of leukocytes. The diagnostic accuracy of CSF lactate in addition to the conventional markers was not reported.

The study of Giulieri (2015) evaluated the diagnostic performance of lactate and other CSF parameters in a prospective cohort of adult patients (> 16 years old) with acute meningitis. All patients with microbiologically documented acute meningitis that fulfilled the following criteria were included: clinical symptoms, CSF pleocytosis, microbiological documentation of the etiology of bacterial meningitis (positive Gram stain, culture, or PCR in the CSF and/or positive blood culture). In total, 45 patients were included in the study of which 18 had bacterial meningitis (mean age 53 years old) and 27 viral meningitis (mean age 35 years old). The diagnostic accuracy of the CSF lactate markers was compared with the conventional markers: glucose ratio, proteins, and number of leukocytes. The diagnostic accuracy of CSF lactate in addition to the conventional markers was not reported.

Description of studies (CSF procalcitonin)

Observational studies

The study of Reshi (2017) studied the performance of CSF procalcitonin as a marker for bacterial meningitis in neonates. Neonates (< 28 days old) admitted for sepsis who qualified for lumbar puncture were included. In total, 168 neonates were included with a mean age of 8 days, ranging between 4 days and 13 days. From these 168 patients, 75 were diagnosed with bacterial meningitis and 93 were not diagnosed with meningitis. Bacterial meningitis was diagnosed in neonates with sepsis with either positive CSF and/or blood culture or positive Gram staining. The diagnostic accuracy of the CSF procalcitonin marker was compared with the conventional markers: glucose (CSF), glucose ratio (CSF/plasma), protein concentration (CSF), leukocytes (CSF total number). The diagnostic accuracy of CSF procalcitonin in addition to the conventional markers was not reported.

Results

Lactate

Comparison: lactate versus conventional markers

The diagnostic accuracy of studies reporting lactate versus conventional markers (glucose, glucose ratio, protein concentration and total number of leukocytes) is presented in Table 1. The included studies only reported the diagnostic accuracy for patients >1 month old.

Lactate versus glucose (CSF)-test characteristics in included studies

Sensitivity

The sensitivity was reported in the systematic review of Huy (2010). The sensitivity of the lactate test ranges between 71.4% and 100%, while the sensitivity of the glucose test ranges between 50.0% and 84.6% (Table 1.1). This indicates that the lactate test has a superior sensitivity compared to the glucose test in the included studies. Because the relative difference between the lower and upper limit of these ranges is > 10%, this difference is considered clinically relevant.

Specificity

The specificity was reported in the systematic review of Huy (2010). The specificity of the lactate test ranges between 78.6% and 97.7%, while the specificity of the glucose test ranges between 71.4% and 100% (Table 1.1). This indicates that the lactate test has a slightly superior specificity compared to the glucose test in the included studies. Because the relative difference between the lower limit of these ranges is < 10%, this difference is considered not clinically relevant.

PPV

The PPV was reported in the systematic review of Huy (2010). The PPV of the lactate test ranged from 81.3% to 93.8%, while the PPV of the glucose test ranges between 73.3% and 100% (Table 1.1). This indicates that the lactate test has a superior PPV compared to the glucose test in the included studies. Because the relative difference between the lower limit of these ranges is > 10%, this difference is considered clinically relevant.

NPV

The NPV was reported in the systematic review of Huy (2010). The NPV of the lactate test ranged from 91.7% to 100%, while the NPV of the glucose test ranges between 81.7% and 89.4% (Table 1.1). This indicates that the lactate test has a superior NPV compared to the glucose test in the included studies. Because the relative differences between the lower and upper limits of these ranges are > 10%, this difference is considered clinically relevant.

Lactate versus glucose ratio (CSF/plasma)-test characteristics in included studies

Sensitivity

The sensitivity of the lactate test was reported in the systematic review of Huy (2010) and the studies of Buch (2018) and Giulieri (2015). The sensitivity of the lactate test ranges between 88.9% and 100%, while the sensitivity of the glucose ratio ranges between 58.8% and 91.3% (Table 1.1). This indicates that the lactate test has a superior sensitivity compared to the glucose ratio in the included studies. Because the relative difference between the lower limit of these ranges is > 10%, this difference is considered clinically relevant.

Specificity

The specificity of the lactate test was reported in the systematic review of Huy (2010) and the studies of Buch (2018) and Giulieri (2015). The specificity of the lactate test ranges between 89.3% and 100%, while the sensitivity of the glucose ratio ranges between 87.0% and 100% (Table 1.1). This indicates that the lactate test has a superior sensitivity compared to the glucose ratio. Because the relative difference between the lower limit of these ranges is < 10%, this difference is considered not clinically relevant. This indicates that the lactate test has a similar specificity compared to the glucose ratio.

PPV

The PPV of the lactate test was reported in the systematic review of Huy (2010) and the studies of Buch (2018) and Giulieri (2015). The PPV of the lactate test ranges between 64.0% and 100%, while the PPV of the glucose ratio ranges between 61.5% and 100% (Table 1.1). This indicates that the lactate test has a superior PPV compared to the glucose ratio in the included studies. Because the relative difference between the lower limit of these ranges is < 10%, this difference is considered not clinically relevant.

NPV

The NPV of the lactate test was reported in the systematic review of Huy (2010) and the studies of Buch (2018) and Giulieri (2015). The NPV of the lactate test ranges between 96.6% and 100%, while the NPV of the glucose ratio ranges between 78.8% and 97.5% (Table 1.1). This indicates that the lactate test has a superior NPV compared to the glucose ratio in the included studies. Because the relative difference between the lower limit of these ranges is > 10%, this difference is considered clinically relevant.

Lactate versus protein concentration (CSF)-test characteristics in included studies

Sensitivity

The sensitivity of the lactate test was reported in the systematic review of Huy (2010) and the studies of Buch (2018) and Giulieri (2015). The sensitivity of the lactate test ranges between 87.5% and 100%, while the sensitivity of the protein concentration ranges between 72.7% and 100% (Table 1.1). Because the relative difference between the lower limit of these ranges is > 10%, this difference is considered clinically relevant.

Specificity

The specificity of the lactate test was reported in the systematic review of Huy (2010) and the studies of Buch (2018) and Giulieri (2015). The specificity of the lactate test ranges between 79.7% to 100%, while the specificity of the protein concentration ranges between 23.0% to 100% (Table 1.1). This indicates that the lactate test has a superior specificity compared to the protein concentration in the included studies. Because the relative difference between the lower limit of these ranges is > 10%, this difference is considered clinically relevant.

PPV

The PPV of the lactate test was reported in the systematic review of Huy (2010) and the studies of Buch (2018) and Giulieri (2015). The PPV of the lactate test ranges between 64.0% to 100%, while the PPV of the protein concentration ranges between 35.0% to 100% (Table 1.1). This indicates that the lactate test has a superior PPV compared to the protein concentration in the included studies. Because the relative difference between the lower limit of these ranges is > 10%, this difference is considered clinically relevant.

NPV

The NPV of the lactate test was reported in the systematic review of Huy (2010) and the studies of Buch (2018) and Giulieri (2015). The NPV of the lactate test ranges between 94.7% and 100%, while the NPV of the protein concentration ranges between 80.0% and 100% (Table 1.1). This indicates that the lactate test has a superior NPV compared to the protein concentration in the included studies. Because the relative difference between the lower limit of these ranges is > 10%, this difference is considered clinically relevant.

Lactate versus total number of leukocytes (CSF)-test characteristics in included studies

Sensitivity

The sensitivity of the lactate test was reported in the systematic review of Huy (2010) and the studies of Buch (2018), Giulieri (2015), and Sanaei Dashti (2017). The sensitivity of the lactate test ranges between 87.5% and 100%, while the sensitivity of the total number of leukocytes ranges between 62.5% and 98.0% (Table 1.1). This indicates that the lactate test has a superior sensitivity compared to the total number of leukocytes in the included studies. Because the relative difference between the lower limit of these ranges is >10%, this difference is considered clinically relevant.

Specificity

The specificity of the lactate test was reported in the systematic review of Huy (2010) and the studies of Buch (2018), Giulieri (2015), and Sanaei Dashti (2017). The specificity of the lactate test ranges between 78.6% and 100%, while the specificity of the total number of leukocytes ranges between 11.0% and 100% (Table 1.1). This indicates that the lactate test has a superior specificity compared to the total number of leukocytes in the included studies. Because the relative difference between the lower limit of these ranges is > 10%, this difference is considered clinically relevant.

PPV

The PPV of the lactate test was reported in the systematic review of Huy (2010) and the studies of Buch (2018), Giulieri (2015), and Sanaei Dashti (2017). The PPV of the lactate test ranges between 72.0% and 100%, while the PPV of the total number of leukocytes ranges between 31.0% and 100% (Table 1.1). This indicates that the lactate test has a superior PPV compared to the total number of leukocytes in the included studies. Because the relative difference between the lower limit of these ranges is > 10%, this difference is considered clinically relevant.

NPV

The NPV of the lactate test was reported in the systematic review of Huy (2010) and the studies of Buch (2018), Giulieri (2015), and Sanaei Dashti (2017). The NPV of the lactate test ranges between 91.7% and 100%, while the NPV of the total number of leukocytes ranges between 76.5% and 96.3% (Table 1.1). This indicates that the lactate test has a superior NPV compared to the total number of leukocytes in the included studies. Because the relative difference between the lower limit of these ranges is > 10%, this difference is considered clinically relevant.

Addition of the lactate test to the conventional markers

None of the studies reported the diagnostic accuracy of the lactate marker in addition to the conventional markers compared to the conventional markers alone.

Table 1 The diagnostic accuracy of the studies that included a comparison with one of the conventional markers

Study			Conventional Marker	Conventional marker assay					Lactate assay results
	Population	Prevalence BM (%)		Cut-off	Sensitivity (%)	Specificity (%)	PPV (%)	NPV (%)	Cut-off	Sensitivity (%)	Specificity (%)	PPV (%)	NPV (%)
Shaltout (Huy, 2010)	Children (n=23)	60.9	Glucose (CSF)	NR	62.5	97.6	90.9	87.2	3.0 mmol/L	87.5	97.6	93.3	95.3
Donald (Huy, 2010)	Children (n=66)	65.2		NR	68.8	97.1	94.3	81.7	2.85 mmol/L	93.8	95.8	93.8	95.8
Ponka (Huy, 2010)	Child/adult (n=38)	28.9		NR	50.0	100	100	84.4	3.0 mmol/L	90.9	96.3	90.9	96.3
Briem (Huy, 2010)	Child/adult (n=147)	30.6		NR	56.6	100	100	89.4	3.5 mmol/L	100	97.7	92.2	100
Lanningan (Huy, 2010)	Adult (n=28)	50.0		NR	84.6	71.4	73.3	83.3	3.89 mmol/L	92.9	78.6	81.3	91.7
Total	Child/adult (n=385)	27 - 65			50 – 85	71 - 100	73 - 100	82 – 89		88 – 100	79 – 98	81 – 94	92 - 100
Genton (Huy, 2010)	Adult (n=47)	40.4	Glucose ratio (CSF/plasma)	NR	91.3	100	100	93.1	4.2 mmol/L	96.0	100	100	96.6
Nelson (Huy, 2010)	Children (n=39)	28.2		NR	58.8	100	100	78.8	2.4 mmol/L	100	89.3	85.7	100
Briem (Huy, 2010)	Child/adult (n=147)	30.6		NR	75.5	99.5	97.0	93.6	3.5 mmol/L	100	97.7	92.2	100
Berg (Huy, 2010)	Child/adult (n=139)	12.9		NR	88.9	88.6	61.5	97.5	3.0 mmol/L	88.9	92.6	64.0	98.2
Buch (2018)	Adult (n=176)	29.0		0.4	89.0	87.0	74.0	95.0	3.5 mmol/L	96.0	85.0	72.0	98.0
Giulieri (2015)	Adult (n=45)	40.0		0.35	92.0	100	100	96.0	3.5 mmol/L	100	100	100	100
Total	Child/adult (n=593)	13 - 40			59 - 92	87 - 100	74 – 100	79 – 98		89 – 100	85 – 100	64 – 100	97 - 100
Genton (Huy, 2010)	Adult (n=47)	40.4	Protein concentration (CSF)	NR	85.7	100	100	89.3	4.2 mmol/L	96.0	100	100	96.6
Shaltout (Huy, 2010)	Children (n=23)	60.9		NR	81.3	100	100	93.3	3.0 mmol/L	87.5	97.6	93.3	95.3
Donald (Huy, 2010)	Children (n=66)	65.2		NR	81.3	98.6	97.5	86.1	2.85 mmol/L	93.8	95.8	93.8	95.8
Vanprapar (Huy, 2010)	Children (n=40)	55.0		NR	72.7	100	100	80.0	3.89 mmol/L	92.3	100	100	94.7
Ponka (Huy, 2010)	Child/adult (n=38)	28.9		NR	90.9	59.3	47.6	94.1	3.0 mmol/L	90.9	96.3	90.9	96.3
Briem (Huy, 2010)	Child/adult (n=147)	30.6		NR	82.0	96.3	85.4	95.3	3.5 mmol/L	100	97.7	92.2	100
Berg (Huy, 2010)	Child/adult (n=139)	12.9		NR	73.3	86.3	44.0	95.7	3.0 mmol/L	88.9	92.6	64.0	98.2
Buch (2018)	Adult (n=176)	29.0		450 mg/L	100	23.0	35.0	100	3.5 mmol/L	96.0	85.0	72.0	98.0
Giulieri (2015)	Adult (n=45)	40.0		1934 mg/L	88.0	100	100	93.0	3.5 mmol/L	100	100	100	100
Total	Child/adult (n=804)	13 - 65			73 – 100	23 – 100	35 – 100	80 – 100		88 – 100	85 – 100	64 – 100	95 - 100
Genton (Huy, 2010)	Adult (n=47)	40.4	Leukocytes (CSF total number)	NR	66.7	100	100	76.5	4.2 mmol/L	96.0	100	100	96.6
Shaltout (Huy, 2010)	Children (n=23)	60.9		NR	62.5	95.1	83.3	86.7	3.0 mmol/L	87.5	97.6	93.3	95.3
Nelson (Huy, 2010)	Children (n=39)	28.2		NR	94.4	96.3	94.4	96.3	2.4 mmol/L	100	89.3	85.7	100
Ponka (Huy, 2010)	Child/adult (n=38)	28.9		NR	63.6	92.6	77.8	86.2	3.0 mmol/L	90.9	96.3	90.9	96.3
Lanningan (Huy, 2010)	Adult (n=28)	50.0		NR	85.7	85.7	85.7	85.7	3.89 mmol/L	92.9	78.6	81.3	91.7
Buch (2018)	Adult (n=176)	29.0		15 x10⁶/L	98.0	11.0	31.0	93	3.5 mmol/L	96.0	85.0	72.0	98.0
Giulieri (2015)	Adult (n=45)	40.0		388 cells/µl	81.0	92.0	75.0	96.0	3.5 mmol/L	100	100	100	100
Sanaei Dashti (2017)	Children (n=50)	24.0		390 cells/µl	81.0	59.2	37.0	91.3	30.2 mg/dL	96.2	78.4	78.3	97.1
Total	Child/adult (n=529)	24 – 61			63 – 98	11 – 100	31 – 100	77 – 96		88 – 100	78 – 100	72 – 100	92 - 100

BM = community-acquired bacterial meningitis, NR = not reported

Procalcitonin

Comparison: procalcitonin versus conventional markers.

The diagnostic accuracy of procalcitonin versus conventional markers (glucose, glucose ratio, protein concentration and total number of leukocytes) is reported in two studies (Reshi, 2017; Sanaei Dashti, 2017). Reshi (2017) reported glucose, glucose ratio, protein concentration and total number of leukocytes in neonates. Sanaei Dashti (2012) reported total number of leukocytes in children.

The diagnostic accuracy in patients > 1 month old was not reported separately.

Glucose (CSF)

Sensitivity

The sensitivity of the procalcitonin test was 92.0%, and the sensitivity of the glucose test was 96.8% in neonates (Reshi, 2017; Table 1.2). This indicates that the procalcitonin test has an inferior sensitivity compared to the glucose test in neonates in the included studies. Because the relative difference between the tests is < 10%, this difference is considered not clinically relevant.

Specificity

The specificity of the procalcitonin test was 87.1%, and the specificity of glucose 85.3% in neonates (Reshi, 2017; Table 1.2). This indicates that the procalcitonin test has a superior specificity compared to the glucose test in neonates in the included studies. Because the relative difference between the tests is < 10%, this difference is considered not clinically relevant.

PPV

The PPV of the procalcitonin test was 85.2%, and the PPV of glucose 89.1% in neonates (Reshi, 2017; Table 1.2). This indicates that the procalcitonin test has an inferior PPV compared to the glucose test in neonates in the included studies. Because the relative difference between the tests is < 10%, this difference is considered not clinically relevant.

NPV

The NPV of the procalcitonin test was 93.1%, and the NPV of glucose 95.5% in neonates (Reshi, 2017; Table 1.2). This indicates that the procalcitonin test has an inferior NPV compared to the glucose test in neonates in the included studies. Because the relative difference between the tests is < 10%, this difference is considered not clinically relevant.

Glucose ratio (CSF/plasma)

Sensitivity

The sensitivity of the procalcitonin test was 92.0%, and the sensitivity of the glucose ratio was 90.3% in neonates (Reshi, 2017; Table 1.2). This indicates that the procalcitonin test has a superior sensitivity compared to the glucose ratio in neonates in the included studies. Because the relative difference between the tests is < 10%, this difference is considered not clinically relevant.

Specificity

The specificity of the procalcitonin test was 87.1%, and the specificity of the glucose ratio was 92.0% in neonates (Reshi, 2017; Table 1.2). This indicates that the procalcitonin test has an inferior specificity compared to the glucose ratio in neonates in the included studies. Because the relative difference between the tests is < 10%, this difference is considered not clinically relevant.

PPV

The PPV of the procalcitonin test was 85.2%, and the PPV of the glucose ratio was 93.3% in neonates (Reshi, 2017; Table 1.2). This indicates that the procalcitonin test has an inferior PPV compared to the glucose ratio in neonates in the included studies. Because the relative difference between the tests is < 10%, this difference is considered not clinically relevant.

NPV

The NPV of the procalcitonin test was 93.1%, and the NPV of the glucose ratio was 88.5% (Reshi, 2017; Table 1.2) in neonates. This indicates that the procalcitonin test has a superior NPV compared to the glucose ratio in neonates in the included studies. Because the relative difference between the tests is < 10%, this difference is considered not clinically relevant.

Protein concentration (CSF)

Sensitivity

The sensitivity of the procalcitonin test was 92.0%, and the sensitivity of the protein concentration was 72.0% in neonates (Reshi, 2017; Table 1.2). This indicates that the procalcitonin test has a superior sensitivity compared to the protein concentration in neonates in the included studies. Because the relative difference between the tests is > 10%, this difference is considered clinically relevant.

Specificity

The specificity of the procalcitonin test was 87.1%, and the specificity of the protein concentration was 87.0% in neonates (Reshi, 2017; Table 1.2). This indicates that the procalcitonin test has a similar specificity compared to the protein concentration in neonates in the included studies.

PPV

The PPV of the procalcitonin test was 85.2%, and the PPV of the protein concentration was 87.0% in neonates (Reshi, 2017; Table 1.2). This indicates that the procalcitonin test has an inferior PPV compared to the protein concentration in the included studies. Because the relative difference between the tests is < 10%, this difference is considered not clinically relevant.

NPV

The NPV of the procalcitonin test was 93.1%, and the NPV of the protein concentration was 79.4% in neonates (Reshi, 2017; Table 1.2). This indicates that the procalcitonin test has a superior NPV compared to the protein concentration in neonates in the included studies. Because the relative difference between the tests is > 10%, this difference is considered clinically relevant.

Total number of leukocytes (CSF)

Sensitivity

The sensitivity of the procalcitonin test was 92.0%, and the sensitivity of the total number of leukocytes was 98.7% in neonates (Reshi, 2017; Table 1.2). This indicates that the procalcitonin test has an inferior sensitivity compared to the total number of leukocytes in neonates in the included studies. Because the relative difference between the tests is < 10%, this difference is considered not clinically relevant.

The sensitivity of the procalcitonin test was 75.0%, and the sensitivity of the total number of leukocytes was 81.0% in children (Sanaei Dashti, 2017; Table 1.2). This indicates that the procalcitonin test has an inferior sensitivity compared to the total number of leukocytes in children in the included studies. Because the relative difference between the tests is < 10%, this difference is considered not clinically relevant.

Specificity

The specificity of the procalcitonin test was 87.1%, and the specificity of the total number of leukocytes was 87.1% in neonates (Reshi, 2017; Table 1.2). This indicates that the procalcitonin test has a similar specificity compared to the total number of leukocytes in neonates in the included studies.

The specificity of the procalcitonin test was 47.4%, and the specificity of the total number of leukocytes was 59.2% in children (Sanaei Dashti, 2017; Table 1.2). This indicates that the procalcitonin test has an inferior specificity compared to the total number of leukocytes in children in the included studies. Because the relative difference between the tests is > 10%, this difference is considered clinically relevant.

PPV

The PPV of the procalcitonin test was 85.2%, and the PPV of the total number of leukocytes was 86.0% in neonates (Reshi, 2017; Table 1.2). This indicates that the procalcitonin test has a similar PPV compared to the total number of leukocytes in neonates in the included studies.

The PPV of the procalcitonin test was 31.0%, and the PPV of the total number of leukocytes was 37.0% in children (Sanaei Dashti, 2017; Table 1.2). This indicates that the procalcitonin test has an inferior PPV compared to the total number of leukocytes in children in the included studies. Because the relative difference between the tests is > 10%, this difference is considered clinically relevant.

NPV

The NPV of the procalcitonin test was 93.1%, and the NPV of the total number of leukocytes was 98.8% in neonates (Reshi, 2017; Table 1.2). This indicates that the procalcitonin test has an inferior NPV compared to the total number of leukocytes in neonates in the included studies. Because the relative difference between the tests is < 10%, this difference is considered not clinically relevant.

The NPV of the procalcitonin test in children was 85.7%, and the NPV of the total number of leukocytes was 91.3% (Sanaei Dashti, 2017; Table 1.2). This indicates that the procalcitonin test has an inferior NPV compared to the total number of leukocytes in children in the included studies. Because the relative difference between the tests is < 10%, this difference is considered not clinically relevant.

Addition of procalcitonin to the conventional markers

None of the studies reported the diagnostic accuracy of the procalcitonin marker in addition to the conventional markers compared to the conventional markers alone.

Table 2 The diagnostic accuracy of the studies that included a comparison with one of the conventional markers

Study			Conventional Marker	Conventional marker assay					Procalcitonin assay results
	Population	Prevalence BM (%)		Cut-off	Sensitivity (%)	Specificity (%)	PPV (%)	NPV (%)	Cut-off	Sensitivity (%)	Specificity (%)	PPV (%)	NPV (%)
Reshi (2017)	Neonates (n=168)	44.6	Glucose (CSF)	45 mg/dL	96.8	85.3	89.1	95.5	33.0 ng/dL	92.0	87.1	85.2	93.1
Reshi (2017)	Neonates (n=168)	44.6	Glucose ratio (CSF/plasma)	0.4	90.3	92.0	93.3	88.5	33.0 ng/dL	92.0	87.1	85.2	93.1
Reshi (2017)	Neonates (n=168)	44.6	Protein concentration (CSF)	102 mg/dL	72.0	87.0	82.0	79.4	33.0 ng/dL	92.0	87.1	85.2	93.1
Reshi (2017)	Neonates (n=168)	44.6	Total number of leukocytes (CSF)	5 cells/µl	98.7	87.1	86.0	98.8	33.0 ng/dL	92.0	87.1	85.2	93.1
Sanaei Dashti (2017)	Children (n=50)	24.0		390 cells/µl	81.0	59.2	37.0	91.3	41.2 ng/dL	75.0	47.4	31.0	85.7
Total	Neonates + children (n=218)	24 – 45			81 – 99	59 – 87	37 – 86	91 – 99		75 – 92	47 – 87	31 – 85	86 - 93

BM = community acquired bacterial meningitis

Level of evidence of the literature

Lactate versus conventional markers

Diagnostic accuracy (sensitivity, specificity, PPV and NPV)

Because diagnostic accuracy studies were included, the level of evidence regarding the diagnostic accuracy started ‘high’. The level of evidence was downgraded by two levels because of the heterogeneity in diagnostic threshold levels (risk of bias, 1 level), and because of a low number of included patients (imprecision, 1 level). The level of evidence was therefore graded ‘low’.

Lactate in addition to conventional markers

Diagnostic accuracy (sensitivity, specificity, PPV and NPV)

Because none of the studies compared the diagnostic accuracy of the lactate test in addition to conventional markers with the diagnostic accuracy of conventional markers alone, the level of evidence could not be assessed.

Procalcitonin versus conventional markers (neonates)

Diagnostic accuracy (sensitivity, specificity, PPV and NPV)

Because diagnostic accuracy studies were included, the level of evidence regarding diagnostic accuracy started ‘high’. The level of evidence was downgraded by two levels because of a low number of included patients (imprecision, 1 level) and because of problems related to applicability as only children were included (bias due to indirectness, 1 level). The level of evidence was therefore graded ‘low’.

Procalcitonin versus conventional markers (patients >1 month old)

Diagnostic accuracy (sensitivity, specificity, PPV and NPV)

Because diagnostic accuracy studies were included, the level of evidence regarding the diagnostic accuracy started ‘high’. The level of evidence was downgraded by three levels because of study limitations (risk of bias, 1 level), a low number of included patients (imprecision, 1 level) and because of problems related to applicability as only children were included (bias due to indirectness, 1 level). The level of evidence was therefore graded ‘very low’.

Procalcitonin in addition to conventional markers

Diagnostic accuracy (sensitivity, specificity, PPV and NPV)

Because none of the studies compared the diagnostic accuracy of the procalcitonin test in addition to conventional markers with the diagnostic accuracy of conventional markers alone, the level of evidence could not be assessed.

Zoeken en selecteren

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

What is the diagnostic accuracy of lactate and procalcitonin in cerebrospinal fluid (CSF) to distinguish bacterial meningitis from aseptic meningitis in patients with suspected community acquired bacterial meningitis?

P: patients (neonates and patients > 1 month old) with a suspicion of community acquired bacterial meningitis;

I: lactate and procalcitonin in CSF, preferably added to the comparison tests;

C: CSF number of leukocytes, CSF glucose, CSF/plasma: glucose ratio, CSF protein;

R: positive CSF culture, PCR, Gram stain or antigen test OR a combination of CSF pleiocytosis with a positive blood culture;

O: diagnostic accuracy for bacterial meningitis (sensitivity, specificity, positive predictive value, negative predictive value).

Relevant outcome measures

The guideline development group considered the sensitivity and negative predictive value as critical outcome measures for decision making; and specificity and positive predictive value as important outcome measures for decision making.

The working group defined a relative difference of 10% as a minimal clinically (patient) important difference regarding the sensitivity, specificity, positive predictive value, and negative predictive value. An absolute difference of < 1% is defined as a similar effect.

Search and select (Methods)

The databases Medline (via OVID) and Embase (via Embase.com) were searched with relevant search terms from January 1^st, 2010, until March 3^rd, 2020. The detailed search strategy is depicted under the tab Methods. The systematic literature search resulted in 782 hits. Studies were selected based on the following criteria: randomized controlled trials, comparative observational studies, or systematic reviews on the diagnostic accuracy of biochemical tests in CSF (lactate and procalcitonin) in patients with suspected community acquired bacterial meningitis. In total, 24 studies were initially selected based on title and abstract screening. After reading the full text, 19 studies were excluded (see the table with reasons for exclusion under the tab Methods), and 5 studies were included.

Results

In total, 5 studies were included in the analysis of the literature. Important study characteristics and results are summarized in the evidence tables. The assessment of the risk of bias is summarized in the risk of bias tables.

Referenties

Buch, K., Bodilsen, J., Knudsen, A., Larsen, L., Helweg-Larsen, J., Storgaard, M., Brandt, C., Wiese, L., Østergaard, C., Nielsen, H., Lebech, A. M., & Danish Study Group for Infections in the Brain (2018). Cerebrospinal fluid lactate as a marker to differentiate between community-acquired acute bacterial meningitis and aseptic meningitis/encephalitis in adults: a Danish prospective observational cohort study. Infectious diseases (London, England), 50(7), 514–521. https://doi.org/10.1080/23744235.2018.1441539.
Giulieri, S., Chapuis-Taillard, C., Jaton, K., Cometta, A., Chuard, C., Hugli, O., Du Pasquier, R., Bille, J., Meylan, P., Manuel, O., & Marchetti, O. (2015). CSF lactate for accurate diagnosis of community-acquired bacterial meningitis. European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology, 34(10), 2049–2055. https://doi.org/10.1007/s10096-015-2450-6.
Huy, N. T., Thao, N. T., Diep, D. T., Kikuchi, M., Zamora, J., & Hirayama, K. (2010). Cerebrospinal fluid lactate concentration to distinguish bacterial from aseptic meningitis: a systemic review and meta-analysis. Critical care (London, England), 14(6), R240. https://doi.org/10.1186/cc9395.
Reshi, Z., Nazir, M., Wani, W., Malik, M., Iqbal, J., & Wajid, S. (2017). Cerebrospinal fluid procalcitonin as a biomarker of bacterial meningitis in neonates. Journal of perinatology : official journal of the California Perinatal Association, 37(8), 927–931. https://doi.org/10.1038/jp.2017.73.
Sanaei Dashti, A., Alizadeh, S., Karimi, A., Khalifeh, M., & Shoja, S. A. (2017). Diagnostic value of lactate, procalcitonin, ferritin, serum-C-reactive protein, and other biomarkers in bacterial and viral meningitis: A cross-sectional study. Medicine, 96(35), e7637. https://doi.org/10.1097/MD.0000000000007637.
Santotoribio, J. D., Cuadros-Muñoz, J. F., & García-Casares, N. (2018). Comparison of C
Reactive Protein and Procalcitonin Levels in Cerebrospinal Fluid and Serum to Differentiate Bacterial from Viral Meningitis. Annals of clinical and laboratory science, 48(4), 506–510.
Shokrollahi, M. R., Shabanzadeh, K., Noorbakhsh, S., Tabatabaei, A., Movahedi, Z., & Shamshiri, A. R. (2018). Diagnostic Value of CRP, Procalcitonin, and Ferritin Levels in Cerebrospinal Fluid of Children with Meningitis. Central nervous system agents in medicinal chemistry, 18(1), 58–62. https://doi.org/10.2174/1871524916666160302103223.
Wei, T. T., Hu, Z. D., Qin, B. D., Ma, N., Tang, Q. Q., Wang, L. L., Zhou, L., & Zhong, R. Q. (2016). Diagnostic Accuracy of Procalcitonin in Bacterial Meningitis Versus Nonbacterial Meningitis: A Systematic Review and Meta-Analysis. Medicine, 95(11), e3079. https://doi.org/10.1097/MD.0000000000003079.
Zhang, L., Ma, L., Zhou, X., Meng, J., Wen, J., Huang, R., Gao, T., Xu, L., & Zhu, L. (2019). Diagnostic Value of Procalcitonin for Bacterial Meningitis in Children: A Comparison Analysis Between Serum and Cerebrospinal Fluid Procalcitonin Levels. Clinical pediatrics, 58(2), 159–165. https://doi.org/10.1177/0009922818809477.

Evidence tabellen

Evidence table for systematic review of RCTs and observational studies (intervention studies)

Study reference

Study characteristics

Patient characteristics

Index test (test of interest)

Reference test

Follow-up

Outcome measures and effect size

Comments

Huy, 2010

SR and meta-analysis.

Literature searches up to March 2009.

A: Abro, 2008

B: Kleine, 2003

C: Schwarz, 2000

D: Uduman, 2000

E: Cameron, 1993

F: Genton, 1990

G: Shaltout, 1989

H: Donald, 1986

I: Nelson, 1986

J: Low, 1986

K: Ruuskanen, 1985

L: Lester, 1985

M: Vanprapar, 1983

N: Mandal, 1983

O: Ponka, 1983

P: Briem, 1983

Q: Berg, 1982

R: Ecross, 1981

S: Knight, 1981

T: Curtis, 1981

U: Lanningan, 1980

V: Gastrin, 1979

W: Lauwers, 1978

X: Controni, 1977

Y: Bland, 1974

Study design:

A: case-control

B: cross-sectional

C: cross-sectional

D: cross-sectional

E: case-control

F: cross-sectional

G: cross-sectional

H: case-control

I: cross-sectional

J: case-control

K: cross-sectional

L: cross-sectional

M: cross-sectional

N: cross-sectional

O: cross-sectional

P: case-control

Q: cross-sectional

R: cross-sectional

S: case-control

T: cross-sectional

U: cross-sectional

V: cross-sectional

W: cross-sectional

X: cross-sectional

Y: case-control

Setting and Country:

A: United Arab Emirates

B: Germany

C: Germany

D: United Arab Emirates

E: UK

F: Switzerland

G: Kuwait

H: S. Africa

I: Sweden

J: Singapore

K: Finland

L: Denmark

M: Thailand

N: UK

O: Finland

P: Sweden

Q: Sweden

R: Australia

S: US

T: UK

U: Canada

V: Sweden

W: Belgium

X: US

Y: US

Source of funding and conflicts of interest:

The authors declare that they have no competing interests.

Inclusion criteria SR: Only articles written in English that evaluated the CSF lactate/lactic acid concentration for differential diagnosis distinguishing

BM from AM were included.

Exclusion criteria SR: Studies with fewer than 16 participants were excluded in

order to limit selection bias. Furthermore,

the following studies were also excluded: (1) animal studies, case reports, replies and reviews; (2) studies in which data could not be extracted; and (3) studies that

used lactate as a criterion for diagnosis of AM.

25 studies included

Important patient characteristics at baseline:

A: 86 BM, 48 AM

B: 73 BM, 128 AM

C: 16 BM, 14 AM

D: 23 BM, 42 AM

E: 11 BM, 9 AM

F: 19 BM, 28 AM

G: 14 BM, 9 AM

H: 43 BM, 23 AM

I: 11 BM, 28 AM

J: 22 BM, 54 AM

K: 32 BM, 30 AM

L: 15 BM, 15 AM

M: 22 BM, 18 AM

N: 20 BM, 59 AM

O: 11 BM, 27 AM

P: 45 BM, 102 AM

Q: 18 BM, 121 AM

R: 66 BM, 31 AM

S: 68 BM, 20 AM

T: 13 BM, 12 AM

U: 14 BM, 14 AM

V: 38 BM, 17 AM

W: 35 BM, 20 AM

X: 55 BM, 15 AM

Y: 13 BM, 25 AM

Age

A: adult

B: adult

C: adult

D: children

E: children

F: adult

G: children

H: children

I: children

J: children

K: children

L: child/adult

M: children

N: children

O: child/adult

P: child/adult

Q: child/adult

R: child/adult

S: children

T: child/adult

U: adult

V: child/adult

W: NR

X: children

Y: children

Other important characteristics?

Not reported.

Describe index test:

CSF Lactate assay

A: Enzymatic

B: Enzymatic

C: Not reported

D: Enzymatic

E: Enzymatic

F: Automatic

analyzer

G: Automatic

analyzer

H: Enzymatic

I: Enzymatic

J: Enzymatic

K: Enzymatic

L: Enzymatic

M: Enzymatic

N: Enzymatic

O: Enzymatic

P: Enzymatic

Q: Enzymatic

R: Enzymatic

S: Enzymatic

T: Enzymatic

U: Enzymatic

V: gas-liquid chromatography

W: gas-liquid chromatography

X: Enzymatic & gas-liquid chromatography

Y: Enzymatic

Cut-off points (mmol/L)

A: 3.8

B: 2.61

C: 2.1

D: Not reported

E: 4.1

F: 4.2

G: 3

H: 2.85

I: 2.4

J: 2.78

K: 3

L: 4.3

M: 3.89

N: 3.9

O: 3

P: 3.5

Q: 3

R: 3.9

S: 3.3

T: 2.8

U: 3.89

V: 3.5

W: 3.89

X: 2.78

Y: 4.44

Describe comparator test:

Clinical diagnosis of BM:

Conventional markers were used as a comparator test.

A: Not applicable

B: Not applicable

C: Not applicable

D: Not applicable

E: Not applicable

F: Glucose quotient (CSF/plasma) + Protein concentration (CSF) + Leukocytes (CSF total number) + Granulocytes (CSF %)

G: Glucose (CSF) + Protein concentration (CSF) + Leukocytes (CSF total number)

H: Glucose (CSF) + Protein concentration (CSF)

I: Glucose quotient (CSF/plasma) + Leukocytes (CSF total number)

J: Not applicable

K: Not applicable

L: Not applicable

M: Protein concentration (CSF)

N: Not applicable

O: Glucose (CSF) + Protein concentration (CSF) + Leukocytes (CSF total number) + Granulocytes (CSF %)

P: Glucose (CSF) + Glucose quotient (CSF/plasma) + Protein concentration (CSF)

Q: Glucose quotient (CSF/plasma) + Protein concentration (CSF)

R: Not applicable

S: Not applicable

T: Not applicable

U: Glucose (CSF) + Leukocytes (CSF total number)

V: Not applicable

W: Not applicable

X: Not applicable

Y: Not applicable

Cut-off points:

Not described

Describe reference test and cut-off points:

Clinical diagnosis was used as reference standard for

BM and AM to avoid misclassification of BM patients as AM.

For sub-group analysis, diagnosed BM was defined

as a patient with CSF pleocytosis (CSF leukocyte count > 4 cells/µl) and one of the following criteria: (1) positive CSF Gram-stained smear for a bacterial pathogen, (2) positive CSF culture for a bacterial pathogen, (3) positive

CSF latex agglutination assay or polymerase chain reaction assay for a bacterial pathogen, or (4) positive

blood culture.

Diagnosed viral AM was defined as the

diagnosis of a patient with pleocytosis in the CSF of

= 4 leukocytes/µl combined with the absence of any of the four criteria for BM and with either of the following criteria: a positive polymerase chain reaction assay or a positive culture for viral pathogen or specific antiviral antibodies in CSF and serum.

Prevalence BM

A: 85/86 = 99%

B: 73/73 = 100%

C: 15/16 = 94%

D: 22/23 = 96%

E: 11/11 = 100%

F: 18 /19 = 95%

G: 13/14 = 93%

H: 40/43 = 93%

I: 11/11 = 100%

J: 19/22 = 86%

K: 30/32 = 94%

L: 15/15 = 100%

M: 20/22 = 91%

N: 20/20 = 100%

O: 10/11 = 91%

P: 45/45 = 100%

Q: 16/18 = 89%

R: 64/66 = 97%

S: 68/68 = 100%

T: 13/13 = 100%

U: 13/14 = 93%

V: 37/38 = 97%

W: 33/35 = 94%

X: 53/55 = 96%

Y: 12/13 = 92%

For how many participants were no complete outcome data available?

Not reported

Reasons for incomplete outcome data described.

Not reported.

Endpoint of follow-up

Not reported

Outcome measure-1

Sensitivity

The sensitivity of included studies ranged from 0.86 to

1.00 (mean, 0.96; 95% confidence interval (CI), 0.95 to 0.98).

Pooled effect 0.97 (95% CI 0.95 to 0.98).

Heterogeneity (I²): 25.9%

Specificity

The specificity varied widely from 0.43 to 1.00 (mean, 0.94; 95% CI, 0.93 to 0.96).

Pooled effect 0.94 (95% CI 0.93 to 0.96).

Heterogeneity (I²): 73.6

LR+

The pooled effect of LR+ was calculated at 14.53 (95% CI, 8.07 to 26.19) using a random effects model.

Heterogeneity (I²): 79.5%

LR-

The pooled effect of LR- was calculated at 0.07 (95% CI, 0.05 to 0.09) using a random effects model.

Heterogeneity (I²): 0.0%

Sub meta-analysis of lactate as a differential marker for diagnosed BM from AM

The result showed a SROC curve with the Q value and

AUC at 0.9426 and 0.9828, respectively, indicating

excellent accuracy, and was consistent with the 25

included studies (data not shown).

Sub meta-analysis of lactate as a differential marker for

diagnosed BM from diagnosed viral AM

The result revealed a SROC curve with the Q value and AUC at 0.9563 and 0.9891, respectively, suggesting excellent accuracy, and was consistent with above results (data not shown).

Head-to-head comparison of CSF lactate level versus

conventional markers

In addition,

the AUC values were found to be lower for the four conventional markers (0.881, 0.952, 0.862, and 0.948 for CSF glucose, CSF/plasma glucose quotient, CSF protein, and CSF total number of leukocytes, respectively), suggesting a lower accuracy compared to the CSF lactate test (0.9840).

Study quality (ROB): method used and results per individual study

Place of the index test in the clinical pathway: add-on

Key messages:

The diagnostic accuracy of cerebrospinal fluid (CSF)

lactate assay for differential diagnosis between bacterial

meningitis and aseptic meningitis were excellent with Q value of 0.9451 and area under the curve of 0.9840.

CSF lactate was a better marker for distinguishing

bacterial meningitis from aseptic meningitis compared

to other conventional markers including CSF glucose, CSF/plasma glucose quotient, CSF protein, and CSF total number of leukocytes

Overwegingen

The measurement of CSF lactate concentration is a

simple, rapid, inexpensive assay, takes just 15 minutes,

and can be performed at the bedside.

Since the CSF lactate con

Centration is not specific for BM; the results of this assay should be interpreted in parallel with clinical findings

and the results of conventional assays including

CSF concentrations of protein, cells, glucose, and a

microbiological examination of CSF.

Another disadvantage of CSF lactate is that it is not useful in the choice of antibiotic selection, which must be based on the results of microscopic examination

of a smear or culture for bacteria, as well as the

other clinical data.

Table of quality assessment for systematic reviews of diagnostic studies

Based on AMSTAR checklist (Shea, 2007; BMC Methodol 7: 10; doi:10.1186/1471-2288-7-10) and PRISMA checklist (Moher, 2009; PLoS Med 6: e1000097; doi:10.1371/journal.pmed1000097)

Study

First author, year

Appropriate and clearly focused question?¹

Yes/no/unclear

Comprehensive and systematic literature search?²

Yes/no/unclear

Description of included and excluded studies?³

Yes/no/unclear

Description of relevant characteristics of included studies?⁴

Yes/no/unclear

Assessment of scientific quality of included studies?⁵

Yes/no/unclear

Enough similarities between studies to make combining them reasonable?⁶

Yes/no/unclear

Potential risk of publication bias taken into account?⁷

Yes/no/unclear

Potential conflicts of interest reported?⁸

Yes/no/unclear

Huy, 2010

Yes

The references of the excluded papers were not included.

Yes

Yes, the study takes heterogeneity into account when pooling the data.

Yes, funnel plot and Egger test were available to assess publication bias.

No, not reported for the systematic review, nor for the individual studies.

Research question (PICO) and inclusion criteria should be appropriate (in relation to the research question to be answered in the clinical guideline) and predefined.
Search period and strategy should be described; at least Medline searched.
Potentially relevant studies that are excluded at final selection (after reading the full text) should be referenced with reasons.
Characteristics of individual studies relevant to the research question (PICO) should be reported.
Quality of individual studies should be assessed using a quality scoring tool or checklist (preferably QUADAS-2; COSMIN checklist for measuring instruments) and taken into account in the evidence synthesis.
Clinical and statistical heterogeneity should be assessed; clinical: enough similarities in patient characteristics, diagnostic tests (strategy) to allow pooling? For pooled data: at least 5 studies available for pooling; assessment of statistical heterogeneity and, more importantly (see Note), assessment of the reasons for heterogeneity (if present)? Note: sensitivity and specificity depend on the situation in which the test is being used and the thresholds that have been set, and sensitivity and specificity are correlated; therefore, the use of heterogeneity statistics (p-values; I²) is problematic, and rather than testing whether heterogeneity is present, heterogeneity should be assessed by eye-balling (degree of overlap of confidence intervals in Forest plot), and the reasons for heterogeneity should be examined.
There is no clear evidence for publication bias in diagnostic studies, and an ongoing discussion on which statistical method should be used. Tests to identify publication bias are likely to give false-positive results, among available tests, Deeks’ test is most valid. Irrespective of the use of statistical methods, you may score “Yes” if the authors discuss the potential risk of publication bias.
Sources of support (including commercial co-authorship) should be reported in both the systematic review and the included studies. Note: To get a “yes,” source of funding or support must be indicated for the systematic review AND for each of the included studies.

Evidence table for diagnostic test accuracy studies

Study reference

Study characteristics

Patient characteristics

Index test

(Test of interest)

Reference test

Follow-up

Outcome measures and effect size

Comments

Buch, 2018

Type of study: observational study

Setting and country: prospective,

Funding and conflicts of interest: No potential conflict of interest was reported by the authors.

Inclusion criteria: All patients aged 15 years or older were prospectively

included in the DASGIB cohort if they had a microbiologically

proven CNS infection or a clinical presentation

strongly suggestive of a CNS infection and CSF leukocytes of >10 x 10⁶ cells/L.

Exclusion criteria: We excluded patients with hospital-acquired CNS infections, as defined by the Center for Disease Control and Prevention, or an

implanted neurosurgical device.

N= 176

Prevalence: 51/176 = 29.0%

Mean age ± SD:

ABM: 64 (52-74)

AME: 41 (29-61)

Sex: % F

ABM: 25 (49%)

AME: 64 (50.8%))

Other important characteristics: NA

Describe index test:

CSF lactate.

Cut-off point(s): not specified.

Comparator test:

CSF glucose ratio

CSF protein

CSF neutrophils

Cut-off point(s): not specified.

Describe reference test and cut-off points:

Microbiologically

proven CNS infection or a clinical presentation

strongly suggestive of a CNS infection and CSF leukocytes of >10 x 10⁶ cells/L.

Time between the index test and reference test: not reported.

For how many participants were no complete outcome data available?

Not reported.

Reasons for incomplete outcome data described.

Outcome measures and effect size (include 95%CI and p-value if available):

Lactate

Sensitivity: 96

Specificity: 85

PPV: 72

NPV: 98

Leukocytes

Sensitivity: 98

Specificity: 11

PPV: 31

NPV: 93

Protein

Sensitivity: 100

Specificity: 23

PPV: 35

NPV: 100

Glucose ratio

Sensitivity: 89

Specificity: 87

PPV: 74

NPV: 95

Specifically, community acquired BM.

Sanaei Dashti, 2017

Type of study: cross-sectional study

Setting and country: prospective, Iran

Funding and conflicts of interest: The financial support of this project was supported by the “Vice- Presidency for Science and Technology” affiliated to “Presidency of the I. R. Iran”.

Authors have no conflicts of interest to declare.

Inclusion criteria: Any child aged 28 days to 14 years who was diagnosed with

suspected meningitis, defined as follows, underwent lumbar puncture

Exclusion criteria: Immunocompromised patients, those

/mm3) without CSF pleocytosis (CSF WBC

= 10cell as well as CSF

shunt infections were excluded.

N= 50

Prevalence:

12/50 = 24%

Mean age ± SD: The average age was 42.75 months with the minimum of

21 days and maximum of 144 months.

Sex: 30 M / 20 F

Other important characteristics: NA

Describe index test and cut-off point:

CSF procalcitonin (41.2 ng/dL)

CSF lactate (30.2 mg/dL)

Comparator test and cut-off point:
CSF WBC (390 cell/mm3)

Describe reference test and cut-off points:

Definite bacterial meningitis: samples with positive Gram

staining, culture, or PCR (for S pneumoniae, N meningitidis, H influenzae, L monocytogenes, and Group B streptococcus). Presumed bacterial meningitis: The presence of clinical picture of meningitis with at least 2 of the following: protein ≥80, glucose ≤ 40, WBC ≥300 and or polymorph nuclear cell predominancy were considered as bacterial

meningitis.

Definite viral/aseptic meningitis: samples with positive PCR of Enterovirus, Human Herpesvirus, Varicella zoster virus, and Epstein-Barr virus.

Presumed viral/aseptic meningitis: Presence of clinical symptoms of meningitis with any CSF lacking the bacterial

characteristics (previously mentioned in the group 1b

meningitis).

Time between the index test and reference test: not reported.

For how many participants were no complete outcome data available? NA

Reasons for incomplete outcome data described. NA

Outcome measures and effect size (include 95%CI and p-value if available):

Sensitivity

PCT = 75%

Lactate = 96.2%

WBC = 80.96%

Specificity

PCT = 47.4%

Lactate = 78.4%

WBC = 59.17

PPV

PCT = 31.03%

Lactate = 78.3%

WBC = 37%

NPV

PCT = 85.71%

Lactate = 97.1%

WBC = 91.3%

Giulieri, 2015

Type of study: observational cohort study

Setting and country: prospective, Switzerland

Funding and conflicts of interest: The study was partially supported by unrestricted research

grants from the Quality Control Program of the Lausanne

University Hospital (Project # 127) and the Foundation for the

Advancement in Medical Microbiology and Infectious Diseases

(FAMMID), Lausanne, Switzerland. The authors declare no competing financial interest

in relation to the manuscript.

Inclusion criteria: For the present study, only patients with microbiologically

documented acute meningitis fulfilling all the following

criteria were included: (1) clinical presentation with at least one of the following symptoms/signs: fever, headache, neck

stiffness, impaired level of consciousness, (2) CSF pleocytosis

(i.e., >4 white blood cells/mm³), and (3) microbiological documentation

of the etiology (for bacterial meningitis: positive Gram stain, culture, or PCR in the CSF and/or positive blood culture; for viral meningitis: positive CSF PCR or positive blood serology).

Exclusion criteria: Patients were excluded if they were <16 years old, if no LP was performed, if they had a nosocomial meningitis

according to CDC criteria, or had a neurosurgical

shunt.

N= 45

Prevalence: 18/45 = 40%

Mean age ± SD:

BM: 53 (17-86)

VM: 35 (17-77)

Sex: % F

BM: 9 (50%)

VM: 12 (44%)

Other important characteristics: NA

Describe index test:

CSF lactate

Cut-off point(s): not specified

Comparator test:

CSF leukocytes

CSF proteins

CSF glucose ratio

Cut-off point(s): not specified.

Describe reference test and cut-off points:

The following

microbiological tests were systematically performed on the CSF in all patients presenting with acute meningitis during the study period: (1) Gram stain, (2) bacterial culture, (3) a multiplex real-time bacterial PCR targeting the four most frequent

pathogens of community-acquired bacterial meningitis

(Streptococcus pneumoniae, Neisseria meningitidis,

Haemophilus influenzae and Listeria monocytogenes), (4) real-

time viral PCR for enterovirus and herpes-simplex virus 1 and 2.

Time between the index test and reference test: not reported.

For how many participants were no complete outcome data available?

Not reported.

Reasons for incomplete outcome data described.

Outcome measures and effect size (include 95%CI and p-value if available):

Lactate (>3.5 mmol/l)

Sensitivity: 100

Specificity: 100

PPV: 100

NPV: 100

Leukocytes (>388 cells/mm³)

Sensitivity: 81

Specificity: 92

PPV: 75

NPV: 96

Proteins (>1934 mg/l)

Sensitivity: 88

Specificity: 100

PPV: 100

NPV: 93

Glucose ratio (<0.35)

Sensitivity: 92

Specificity: 100

PPV: 100

NPV: 96

Reshi, 2017

Type of study: observational study

Setting and country: prospective, India

Funding and conflicts of interest: The authors declare no conflict of interest.

Inclusion criteria: infants <28 days old,

admitted for sepsis who qualified for lumbar puncture. The study was

conducted in the neonatal intensive care unit of Department of

Neonatology and Pediatrics at SKIMS, Srinagar, over a period of 2 years

(January 2014 to December 2015).

Exclusion criteria: neonates who had received antibiotics prior to hospital admission, recent brain surgery, the presence of another focus of infection, in addition to meningitis, viral meningitis.

N= 168

Prevalence: 75/168 = 44.6%

Median age ± range:

Meningitis: 8 days (5-13)

No meningitis: 8 days (4-13)

Sex (M/F):

Meningitis: 1.08

No meningitis: 1.02

Other important characteristics: NA

Describe index test:

PCT concentration in CSF was measured by lumitest kit (Brahms Diagnostic,

Berlin, Germany).

Cut-off point(s): not specified.

Comparator test: total leukocyte count in CSF, CSF protein, CSF sugar, CSF serum glucose ratio.

Cut-off point(s): not specified.

Describe reference test:

Bacterial culture and CSF PCR for herpes simplex virus.

Cut-off point(s): The diagnosis of bacterial meningitis was made in neonates with sepsis with either positive CSF and/or blood culture or positive Gram staining.

Time between the index test and reference test: not reported.

For how many participants were no complete outcome data available?

None.

Reasons for incomplete outcome data described. NA

Outcome measures and effect size (include 95%CI and p-value if available):

PCT:

Sensitivity: 0.92

Specificity: 0.871

PPV: 0.852

NPV: 0.931

Total leukocyte count:

Sensitivity: 0.987

Specificity: 0.871

PPV: 0.86

NPV: 0.988

Protein:

Sensitivity: 0.72

Specificity: 0.87

PPV: 0.82

NPV: 0.794

Sugar:

Sensitivity: 0.968

Specificity: 0.853

PPV: 0.891

NPV: 0.955

CSF:serum ratio:

Sensitivity: 0.903

Specificity: 0.920

PPV: 0.933

NPV: 0.885

Study in neonates.

Risk of bias assessment diagnostic accuracy studies (QUADAS II, 2011)

Study reference

Patient selection

Index test

Reference standard

Flow and timing

Comments with respect to applicability

Buch, 2018

Was a consecutive or random sample of patients enrolled?

Yes

Was a case-control design avoided?

Did the study avoid inappropriate exclusions?

Yes

Were the index test results interpreted without knowledge of the results of the reference standard?

If a threshold was used, was it pre-specified?

Is the reference standard likely to correctly classify the target condition?

Yes

Were the reference standard results interpreted without knowledge of the results of the index test?

Was there an appropriate interval between index test(s) and reference standard?

Yes

Did all patients receive a reference standard?

Yes

Did patients receive the same reference standard?

Were all patients included in the analysis?

Yes

Are there concerns that the included patients do not match the review question?

Are there concerns that the index test, its conduct, or interpretation differ from the review question?

Are there concerns that the target condition as defined by the reference standard does not match the review question?

CONCLUSION:

Could the selection of patients have introduced bias?

RISK: LOW

CONCLUSION:

Could the conduct or interpretation of the index test have introduced bias?

RISK: LOW

CONCLUSION:

Could the reference standard, its conduct, or its interpretation have introduced bias?

RISK: LOW

CONCLUSION

Could the patient flow have introduced bias?

RISK: LOW

OVERALL RISK: LOW

Sanaei Dashti, 2017

Was a consecutive or random sample of patients enrolled?

Yes

Was a case-control design avoided?

Did the study avoid inappropriate exclusions?

Yes

Were the index test results interpreted without knowledge of the results of the reference standard?

If a threshold was used, was it pre-specified?

Is the reference standard likely to correctly classify the target condition?

Yes

Were the reference standard results interpreted without knowledge of the results of the index test?

Was there an appropriate interval between index test(s) and reference standard?

Yes

Did all patients receive a reference standard?

Yes

Did patients receive the same reference standard?

Were all patients included in the analysis?

Yes

Are there concerns that the included patients do not match the review question?

Unclear, unknown whether only patients with acquired BM were included.

Are there concerns that the index test, its conduct, or interpretation differ from the review question?

Are there concerns that the target condition as defined by the reference standard does not match the review question?

CONCLUSION:

Could the selection of patients have introduced bias?

RISK: LOW

CONCLUSION:

Could the conduct or interpretation of the index test have introduced bias?

RISK: LOW

CONCLUSION:

Could the reference standard, its conduct, or its interpretation have introduced bias?

RISK: LOW

CONCLUSION

Could the patient flow have introduced bias?

RISK: LOW

OVERALL RISK: UNCLEAR

Giulieri, 2015

Was a consecutive or random sample of patients enrolled?

Yes

Was a case-control design avoided?

Did the study avoid inappropriate exclusions?

Yes

Were the index test results interpreted without knowledge of the results of the reference standard?

If a threshold was used, was it pre-specified?

Is the reference standard likely to correctly classify the target condition?

Yes

Were the reference standard results interpreted without knowledge of the results of the index test?

Was there an appropriate interval between index test(s) and reference standard?

Yes

Did all patients receive a reference standard?

Yes

Did patients receive the same reference standard?

Were all patients included in the analysis?

Yes

Are there concerns that the included patients do not match the review question?

Are there concerns that the index test, its conduct, or interpretation differ from the review question?

Are there concerns that the target condition as defined by the reference standard does not match the review question?

CONCLUSION:

Could the selection of patients have introduced bias?

RISK: LOW

CONCLUSION:

Could the conduct or interpretation of the index test have introduced bias?

RISK: LOW

CONCLUSION:

Could the reference standard, its conduct, or its interpretation have introduced bias?

RISK: LOW

CONCLUSION

Could the patient flow have introduced bias?

RISK: LOW

OVERALL RISK: LOW

Reshi, 2017

Was a consecutive or random sample of patients enrolled?

Yes

Was a case-control design avoided?

Did the study avoid inappropriate exclusions?

Yes

Were the index test results interpreted without knowledge of the results of the reference standard?

If a threshold was used, was it pre-specified?

Is the reference standard likely to correctly classify the target condition?

Yes

Were the reference standard results interpreted without knowledge of the results of the index test?

Was there an appropriate interval between index test(s) and reference standard?

Yes

Did all patients receive a reference standard?

Yes

Did patients receive the same reference standard?

Were all patients included in the analysis?

Yes

Are there concerns that the included patients do not match the review question?

Are there concerns that the index test, its conduct, or interpretation differ from the review question?

Are there concerns that the target condition as defined by the reference standard does not match the review question?

CONCLUSION:

Could the selection of patients have introduced bias?

RISK: LOW

CONCLUSION:

Could the conduct or interpretation of the index test have introduced bias?

RISK: LOW

CONCLUSION:

Could the reference standard, its conduct, or its interpretation have introduced bias?

RISK: LOW

CONCLUSION

Could the patient flow have introduced bias?

RISK: LOW

OVERALL RISK: LOW

Judgments on risk of bias are dependent on the research question: some items are more likely to introduce bias than others, and may be given more weight in the final conclusion on the overall risk of bias per domain:

Patient selection:

Consecutive or random sample has a low risk to introduce bias.
A case control design is very likely to overestimate accuracy and thus introduce bias.
Inappropriate exclusion is likely to introduce bias.

Index test:

This item is similar to “blinding” in intervention studies. The potential for bias is related to the subjectivity of index test interpretation and the order of testing.
Selecting the test threshold to optimise sensitivity and/or specificity may lead to overoptimistic estimates of test performance and introduce bias.

Reference standard:

When the reference standard is not 100% sensitive and 100% specific, disagreements between the index test and reference standard may be incorrect, which increases the risk of bias.
This item is similar to “blinding” in intervention studies. The potential for bias is related to the subjectivity of index test interpretation and the order of testing.

Flow and timing:

If there is a delay or if treatment is started between index test and reference standard, misclassification may occur due to recovery or deterioration of the condition, which increases the risk of bias.
If the results of the index test influence the decision on whether to perform the reference standard or which reference standard is used, estimated diagnostic accuracy may be biased.
All patients who were recruited into the study should be included in the analysis, if not, the risk of bias is increased.

Judgement on applicability:

Patient selection: there may be concerns regarding applicability if patients included in the study differ from those targeted by the review question, in terms of severity of the target condition, demographic features, presence of differential diagnosis or co-morbidity, setting of the study and previous testing protocols.

Index test: if index tests methods differ from those specified in the review question there may be concerns regarding applicability.

Reference standard: the reference standard may be free of bias but the target condition that it defines may differ from the target condition specified in the review question.

Table of excluded studies

Author and year	Reason for exclusion
Jabir, 2019	Voldoet niet aan PICRO: alleen vergelijking lactaat versus referentiestandaard.
Majwala, 2013	Voldoet niet aan PICRO: alleen vergelijking lactaat versus referentiestandaard.
Mekitarian Filho, 2014	Voldoet niet aan PICRO: alleen vergelijking lactaat versus referentiestandaard.
Nazir, 2018	Voldoet niet aan PICRO: alleen vergelijking lactaat versus referentiestandaard.
Pires, 2017	Voldoet niet aan PICRO: alleen vergelijking lactaat versus referentiestandaard.
Wei, 2016	Voldoet niet aan PICRO: alleen vergelijking procalcitonin versus referentiestandaard.
Santotoribio, 2018	Voldoet niet aan PICRO: alleen vergelijking procalcitonin versus referentiestandaard.
Zhang, 2019	Voldoet niet aan PICRO: alleen vergelijking procalcitonin versus referentiestandaard.
Shokrollahi, 2018	Voldoet niet aan PICRO: alleen vergelijking procalcitonin versus referentiestandaard.
Konstantinidis, 2015	Studie is opgenomen in Wei, 2016
Makoo, 2010	Studie is opgenomen in Wei, 2016
Shen, 2015	Studie is opgenomen in Wei, 2016
Sakushima, 2011	SR van Huy, 2010 is vollediger.
Velissaris, 2018	SR van Wei, 2016 is vollediger.
Alons, 2016	De sensitiviteit wordt niet specifiek voor community-aquired BM weergegeven, alleen samen met postneurosurgery group.
Carcamo Yanez, 2017	De diagnostic accuracy van meningitis samples wordt niet beschreven; een assay wordt gevalideerd met bepaalde samples zonder de diagnostic accuracy te bepalen.
Li, 2017	Empirical antibiotoca administration was not an exclusion criteria (De patiënten hadden gemiddeld al 11 dagen antibiotica ontvangen voordat CSF werd afgenomen) + De sensitiviteit wordt niet specifiek voor community-aquired BM weergegeven, alleen samen met postneurosurgery group.
Zhang, 2017	De diagnostic accuracy wordt niet bepaald in deze studie.
Chen, 2012	Voldoet niet aan PICRO: geen vergelijking van lactaat als toevoeging tot de conventionele markers versus de conventionele markers alleen.

Verantwoording

Autorisatiedatum en geldigheid

Laatst beoordeeld : 08-07-2022

Laatst geautoriseerd : 08-07-2022

Geplande herbeoordeling :

Initiatief en autorisatie

Initiatief:

Nederlandse Vereniging voor Neurologie

Geautoriseerd door:

Nederlandse Internisten Vereniging
Nederlandse Vereniging voor Keel-Neus-Oorheelkunde en Heelkunde van het Hoofd-Halsgebied
Nederlandse Vereniging voor Kindergeneeskunde
Nederlandse Vereniging voor Medische Microbiologie
Nederlandse Vereniging voor Neurochirurgie
Nederlandse Vereniging voor Neurologie
Nederlandse Vereniging voor Intensive Care
Patiëntenfederatie Nederland

Algemene gegevens

Kennisgenomen: Nederlandse Huisartsen Genootschap

De ontwikkeling/herziening van deze richtlijnmodule werd ondersteund door het

Kennisinstituut van de Federatie Medisch Specialisten (www.demedischspecialist.nl/kennisinstituut) en werd gefinancierd uit de Stichting Kwaliteitsgelden Medisch Specialisten (SKMS).

De financier heeft geen enkele invloed gehad op de inhoud van de richtlijnmodule.

Samenstelling werkgroep

Voor het ontwikkelen van de richtlijnmodule is in 2019 een multidisciplinaire werkgroep ingesteld, bestaande uit vertegenwoordigers van alle relevante specialismen (zie hiervoor de Samenstelling van de werkgroep) die betrokken zijn bij de zorg voor patiënten met (verdenking op) bacteriële meningitis.

Werkgroep

Prof. dr. D. van de Beek, neuroloog, Amsterdam Universitair Medische Centra, Amsterdam, NVN
Dr. M.C. Brouwer, neuroloog, Amsterdam Universitair Medische Centra, Meibergdreef, NVN
Dr. S.G.B. Heckenberg, neuroloog, Spaarne Gasthuis, Haarlem, NVN
Dr. A. van Samkar, neuroloog in opleiding, Canisius Wilhelmina Ziekenhuis, Nijmegen, NVN
Dr. E.F. Hensen, KNO-arts, Leiden Universitair Medisch Centrum, Leiden, NVKNO
Dr. D.F. Postma, internist-infectioloog, Universitair Medisch Centrum Groningen, Groningen, NIV, NVII
Dr. M.W. Bijlsma, kinderarts, Amsterdam Universitair Medische Centra, Meibergdreef, NVK
Dr. R.A.G. Huis in ’t Veld, arts-microbioloog, Universitair Medisch Centrum Groningen, Groningen, NVMM
Dr. A.J.H. Cremers, arts-microbioloog i.o., Radboud Universitair Medisch Centrum, Nijmegen, NVMM
Dr. R.D.S. Nandoe Tewarie, neurochirurg, Haaglanden Medisch Centrum, Den Haag, NVvN
Dr. M.A. Kuiper, neuroloog-intensivist, Medisch Centrum Leeuwarden, Leeuwarden, NVIC
Dr. M. Kool, huisarts, Gezondheidscentrum de Volgerlanden, Hendrik-Ido-Ambacht, NHG
W.H. Witkamp, patiëntvertegenwoordiger, Meningitisstichting

Met ondersteuning van

Dr. M.A. Pols, senior adviseur, Kennisinstituut van de Federatie Medisch Specialisten
Dr. A. Balemans, adviseur, Kennisinstituut van de Federatie Medisch Specialisten (tot oktober 2020)
Drs. B.L. Gal-de Geest, junior adviseur, Kennisinstituut van de Federatie Medisch Specialisten (vanaf oktober 2020)

Belangenverklaringen

De Code ter voorkoming van oneigenlijke beïnvloeding door belangenverstrengeling is gevolgd. Alle werkgroepleden hebben schriftelijk verklaard of zij in de laatste drie jaar directe financiële belangen (betrekking bij een commercieel bedrijf, persoonlijke financiële belangen, onderzoeksfinanciering) of indirecte belangen (persoonlijke relaties, reputatiemanagement) hebben gehad. Gedurende de ontwikkeling of herziening van een module worden wijzigingen in belangen aan de voorzitter doorgegeven. De belangenverklaring wordt opnieuw bevestigd tijdens de commentaarfase.

Een overzicht van de belangen van werkgroepleden 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.

Werkgroeplid	Functie	Nevenfuncties	Gemelde belangen	Ondernomen actie
Van de Beek	Neuroloog, Amsterdam UMC, locatie AMC	Lid wetenschappelijke adviesraad Nederlands Instituut voor Neurowetenschappen (onbetaald) Lid commissie Wetenschappelijk Onderzoek Neurologie (onbetaald)	Wetenschappelijke adviesraad van de Nederlandse Meningitis Stichting en sarcoïdose belangenvereniging Nederland	Geen actie
Bijlsma	Kinderarts (Amsterdam UMC) Postdoctoraal onderzoeker (Amsterdam UMC)	Werkgroepdocent EpidM cursus regressietechnieken (betaling aan Amsterdam UMC) - NVK congrescommissie (onbetaald) - NVK richtlijnen en indicatoren commissie (onbetaald) - Adviseur Nederlandse Meningitis Stichting (onbetaald)	Onderzoeksfinanciering NOGBS studie door: Amsterdam UMC, Stichting Steun Emma, C.J. Vaillantfonds, Remmert Adriaan Laan Fonds, The European & Developing Countries Clinical Trials Partnership (EDCTP), London School of Hygiene and Tropical Medicine. Geen van deze financiers heeft belang bij de richtlijn adviezen.	Geen actie
Huis in ’t Veld	Arts-microbioloog, HagaZiekenhuis Den Haag.	Geen	Geen	Geen actie
Brouwer	Neuroloog, Amsterdam UMC, locatie AMC, Amsterdam 1,0 fte	Geen	Regelmatig (1x per 1 tot 2 jaar) gevraagd als expert bij de patiëntenorganisaties van meningitis en encefalitis patiënten (Nederlandse meningitis stichting). Spreker bij de NVN bij het jaarlijks assistentenonderwijs over neuroinfecties en inflammatie. Spreker voor de NVN bij de jaarlijkse nascholing (biemond cursus). Voorzitter van de richtlijncommissie van de European Society of Clinical Microbiology and Infectious Diseases (ESCMID) study Group of Infections the Brain (ESGIB). Deelname aan de richtlijn of de inhoud van de richtlijn heeft geen invloed op reputatie/positie	Geen actie
Nandoe Tewarie	Neurochirurg Haaglanden MC	Geen	Geen	Geen actie
Heckenberg	Neuroloog, Spaarne Gasthuis Haarlem	Geen	Geen	Geen actie
Kuiper	Neuroloog-Intensivist Werkgever: Medisch Centrum Leeuwarden	Medisch Adviseur Nederlandse Transplantatiestichting; betaald, 2 dagen per maand Voorzitter Wetenschappelijke Raad van de Nederlandse Reanimatieraad; vacatiegeld van 1500 euro per jaar	Geen	Geen actie
Van Samkar	AIOS Neurologie CWZ Nijmegen	Geen	Geen	Geen actie
Cremers	AIOS Medische microbiologie, RadboudUMC, 1FTE	Bestuurslid NVAMM, onbetaald. Lid Commissie Wetenschap en Innovatie NVMM, (Nationale Kennisagenda), betaald. Lid Werkgroep Sepsis, RadboudUMC Center for Infectious Diseases, onbetaald. Lid ESCMID Study Groups "Bloodstream Infections, Endocarditis and Sepsis" en "Genomic and Molecular Diagnostics", onbetaald.	Als AIOS actief in innovatie van microbiologische diagnostiek voor invasieve bacteriële infecties.	Geen actie
Hensen	KNO-arts, Leids Universitair Medisch Centrum	Sectie-redacteur, Nederlands Tijdschrift voor Geneeskunde (onbetaald) Redacteur, Nederlands Tijdschrift voor Keel-Neus Oorheelkunde (onbetaald)	Geen	Geen actie
Kool	huisarts - stichting Zonboog 0,72fte wetenschappelijk docent, Erasmus MC afdeling huisartsgeneeskunde 0,2fte	Geen	Geen	Geen actie
Witkamp	Communicatieadviseur bij Poonawalla Sciencepark B.V. (fulltime, betaaldefunctie)	Voorzitter Nederlandse Meningitis Stichting: meewerkend voorzitter-onbetaald Governing council lid van Confederation of Meningitis Organizations (CoMO): council-lid meedenken en werken aan ontwikkeling van CoMO - onbetaald Skileraar-betaald	Deelname aan de werkgroep is goed voor de reputatie van de Nederlandse Meningitis Stichting. Voor mij persoonlijk niet van toepassing.	Geen actie
Postma	Internist-infectioloog, Universitair Medisch Centrum Groningen	Lid ESCMID Fungal Infection Study Group en ESCMID Study Group for Infections in Compromised Hosts (onbetaald). docent voor verschillende cursus infectieziekten (betaald).	Geen	Geen actie

Inbreng patiëntenperspectief

Er werd aandacht besteed aan het patiëntenperspectief door afvaardiging van de Meningitisstichting in de werkgroep. De verkregen input is meegenomen bij het opstellen van de uitgangsvragen, de keuze voor de uitkomstmaten en bij het opstellen van de overwegingen. De richtlijnmodules zijn tevens voor commentaar voorgelegd aan de Meningitisstichting.

Implementatie

Aanbeveling

Tijdspad voor implementatie:
< 1 jaar,

1 tot 3 jaar of

> 3 jaar

Verwacht effect op kosten

Randvoorwaarden voor implementatie (binnen aangegeven tijdspad)

Mogelijke barrières voor implementatie¹

Te ondernemen acties voor implementatie²

Verantwoordelijken voor acties³

Overige opmerkingen

Bepaal als biochemische diagnostiek bij verdenking op een community acquired bacteriële meningitis het celgetal, totaal eiwit en glucosegehalte in de liquor cerebrospinalis na een lumbaalpunctie.

Niet van toepassing. De aanbeveling verschilt niet van de huidige praktijk.

Voeg vooralsnog geen procalcitonine en lactaat routinematig toe aan liquor bepalingen.

Niet van toepassing. De aanbeveling verschilt niet van de huidige praktijk

¹ Barrières kunnen zich bevinden op het niveau van de professional, op het niveau van de organisatie (het ziekenhuis) of op het niveau van het systeem (buiten het ziekenhuis). Denk bijvoorbeeld aan onenigheid in het land met betrekking tot de aanbeveling, onvoldoende motivatie of kennis bij de specialist, onvoldoende faciliteiten of personeel, nodige concentratie van zorg, kosten, slechte samenwerking tussen disciplines, nodige taakherschikking, et cetera.

² Denk aan acties die noodzakelijk zijn voor implementatie, maar ook acties die mogelijk zijn om de implementatie te bevorderen. Denk bijvoorbeeld aan controleren aanbeveling tijdens kwaliteitsvisitatie, publicatie van de richtlijn, ontwikkelen van implementatietools, informeren van ziekenhuisbestuurders, regelen van goede vergoeding voor een bepaald type behandeling, maken van samenwerkingsafspraken.

³ Wie de verantwoordelijkheden draagt voor implementatie van de aanbevelingen, zal tevens afhankelijk zijn van het niveau waarop zich barrières bevinden. Barrières op het niveau van de professional zullen vaak opgelost moeten worden door de beroepsvereniging. Barrières op het niveau van de organisatie zullen vaak onder verantwoordelijkheid van de ziekenhuisbestuurders vallen. Bij het oplossen van barrières op het niveau van het systeem zijn ook andere partijen, zoals de NZA en zorgverzekeraars, van belang.

Werkwijze

AGREE

Deze richtlijnmodule is opgesteld conform de eisen vermeld in het rapport Medisch Specialistische Richtlijnen 2.0 van de adviescommissie Richtlijnen van de Raad Kwaliteit. Dit rapport is gebaseerd op het AGREE II instrument (Appraisal of Guidelines for Research & Evaluation II; Brouwers, 2010).

Knelpuntenanalyse en uitgangsvragen

Tijdens de voorbereidende fase inventariseerde de werkgroep de knelpunten in de zorg voor patiënten met bacteriële meningitis. De werkgroep beoordeelde de aanbeveling(en) uit de eerdere richtlijnmodules (NVN, 2013) op noodzaak tot revisie. Tevens zijn er knelpunten aangedragen door Lareb en het NHG via een enquête.

Op basis van de uitkomsten van de knelpuntenanalyse zijn door de werkgroep concept-uitgangsvragen opgesteld en definitief vastgesteld.

Uitkomstmaten

Na het opstellen van de zoekvraag behorende bij de uitgangsvraag inventariseerde de werkgroep welke uitkomstmaten voor de patiënt relevant zijn, waarbij zowel naar gewenste als ongewenste effecten werd gekeken. Hierbij werd een maximum van acht uitkomstmaten gehanteerd. De werkgroep waardeerde deze uitkomstmaten volgens hun relatieve belang bij de besluitvorming rondom aanbevelingen, als cruciaal (kritiek voor de besluitvorming), belangrijk (maar niet cruciaal) en onbelangrijk. Tevens definieerde de werkgroep tenminste voor de cruciale uitkomstmaten welke verschillen zij klinisch (patiënt) relevant vonden.

Methode literatuursamenvatting

Een uitgebreide beschrijving van de strategie voor zoeken en selecteren van literatuur en de beoordeling van de risk-of-bias van de individuele studies is te vinden onder ‘Zoeken en selecteren’ onder Onderbouwing. De beoordeling van de kracht van het wetenschappelijke bewijs wordt hieronder toegelicht.

Beoordelen van de kracht van het wetenschappelijke bewijs

De kracht van het wetenschappelijke bewijs werd bepaald volgens de GRADE-methode. GRADE staat voor ‘Grading Recommendations Assessment, Development and Evaluation’ (zie http://www.gradeworkinggroup.org/). De basisprincipes van de GRADE-methodiek zijn: het benoemen en prioriteren van de klinisch (patiënt) relevante uitkomstmaten, een systematische review per uitkomstmaat, en een beoordeling van de bewijskracht per uitkomstmaat op basis van de acht GRADE-domeinen (domeinen voor downgraden: risk of bias, inconsistentie, indirectheid, imprecisie, en publicatiebias; domeinen voor upgraden: dosis-effect relatie, groot effect, en residuele plausibele confounding).

GRADE onderscheidt vier gradaties voor de kwaliteit van het wetenschappelijk bewijs: hoog, redelijk, laag en zeer laag. Deze gradaties verwijzen naar de mate van zekerheid die er bestaat over de literatuurconclusie, in het bijzonder de mate van zekerheid dat de literatuurconclusie de aanbeveling adequaat ondersteunt (Schünemann, 2013; Hultcrantz, 2017).

GRADE	Definitie
Hoog	er is hoge zekerheid dat het ware effect van behandeling dicht bij het geschatte effect van behandeling ligt; het is zeer onwaarschijnlijk dat de literatuurconclusie klinisch relevant verandert wanneer er resultaten van nieuw grootschalig onderzoek aan de literatuuranalyse worden toegevoegd.
Redelijk	er is redelijke zekerheid dat het ware effect van behandeling dicht bij het geschatte effect van behandeling ligt; het is mogelijk dat de conclusie klinisch relevant verandert wanneer er resultaten van nieuw grootschalig onderzoek aan de literatuuranalyse worden toegevoegd.
Laag	er is lage zekerheid dat het ware effect van behandeling dicht bij het geschatte effect van behandeling ligt; er is een reële kans dat de conclusie klinisch relevant verandert wanneer er resultaten van nieuw grootschalig onderzoek aan de literatuuranalyse worden toegevoegd.
Zeer laag	er is zeer lage zekerheid dat het ware effect van behandeling dicht bij het geschatte effect van behandeling ligt; de literatuurconclusie is zeer onzeker.

Bij het beoordelen (graderen) van de kracht van het wetenschappelijk bewijs in richtlijnen volgens de GRADE-methodiek spelen grenzen voor klinische besluitvorming een belangrijke rol (Hultcrantz, 2017). Dit zijn de grenzen die bij overschrijding aanleiding zouden geven tot een aanpassing van de aanbeveling. Om de grenzen voor klinische besluitvorming te bepalen moeten alle relevante uitkomstmaten en overwegingen worden meegewogen. De grenzen voor klinische besluitvorming zijn daarmee niet één op één vergelijkbaar met het minimaal klinisch relevant verschil (Minimal Clinically Important Difference, MCID). Met name in situaties waarin een interventie geen belangrijke nadelen heeft en de kosten relatief laag zijn, kan de grens voor klinische besluitvorming met betrekking tot de effectiviteit van de interventie bij een lagere waarde (dichter bij het nuleffect) liggen dan de MCID (Hultcrantz, 2017).

Overwegingen (van bewijs naar aanbeveling)

Om te komen tot een aanbeveling zijn naast (de kwaliteit van) het wetenschappelijke bewijs ook andere aspecten belangrijk en worden meegewogen, zoals aanvullende argumenten uit bijvoorbeeld de biomechanica of fysiologie, waarden en voorkeuren van patiënten, kosten (middelenbeslag), aanvaardbaarheid, haalbaarheid en implementatie. Deze aspecten zijn systematisch vermeld en beoordeeld (gewogen) onder het kopje ‘Overwegingen’ en kunnen (mede) gebaseerd zijn op expert opinion. Hierbij is gebruik gemaakt van een gestructureerd format gebaseerd op het evidence-to-decision framework van de internationale GRADE Working Group (Alonso-Coello, 2016a; Alonso-Coello, 2016b). Dit evidence-to-decision framework is een integraal onderdeel van de GRADE-methodiek.

Formuleren van aanbevelingen

De aanbevelingen geven antwoord op de uitgangsvraag en zijn gebaseerd op het beschikbare wetenschappelijke bewijs en de belangrijkste overwegingen, en een weging van de gunstige en ongunstige effecten van de relevante interventies. De kracht van het wetenschappelijk bewijs en het gewicht dat door de werkgroep wordt toegekend aan de overwegingen, bepalen samen de sterkte van de aanbeveling. Conform de GRADE-methodiek sluit een lage bewijskracht van conclusies in de systematische literatuuranalyse een sterke aanbeveling niet a priori uit, en zijn bij een hoge bewijskracht ook zwakke aanbevelingen mogelijk (Agoritsas, 2017; Neumann, 2016). De sterkte van de aanbeveling wordt altijd bepaald door weging van alle relevante argumenten tezamen. De werkgroep heeft bij elke aanbeveling opgenomen hoe zij tot de richting en sterkte van de aanbeveling zijn gekomen.

In de GRADE-methodiek wordt onderscheid gemaakt tussen sterke en zwakke (of conditionele) aanbevelingen. De sterkte van een aanbeveling verwijst naar de mate van zekerheid dat de voordelen van de interventie opwegen tegen de nadelen (of vice versa), gezien over het hele spectrum van patiënten waarvoor de aanbeveling is bedoeld. De sterkte van een aanbeveling heeft duidelijke implicaties voor patiënten, behandelaars en beleidsmakers (zie onderstaande tabel). Een aanbeveling is geen dictaat, zelfs een sterke aanbeveling gebaseerd op bewijs van hoge kwaliteit (GRADE gradering HOOG) zal niet altijd van toepassing zijn, onder alle mogelijke omstandigheden en voor elke individuele patiënt.

Implicaties van sterke en zwakke aanbevelingen voor verschillende richtlijngebruikers
	Sterke aanbeveling	Zwakke (conditionele) aanbeveling
Voor patiënten	De meeste patiënten zouden de aanbevolen interventie of aanpak kiezen en slechts een klein aantal niet.	Een aanzienlijk deel van de patiënten zouden de aanbevolen interventie of aanpak kiezen, maar veel patiënten ook niet.
Voor behandelaars	De meeste patiënten zouden de aanbevolen interventie of aanpak moeten ontvangen.	Er zijn meerdere geschikte interventies of aanpakken. De patiënt moet worden ondersteund bij de keuze voor de interventie of aanpak die het beste aansluit bij zijn of haar waarden en voorkeuren.
Voor beleidsmakers	De aanbevolen interventie of aanpak kan worden gezien als standaardbeleid.	Beleidsbepaling vereist uitvoerige discussie met betrokkenheid van veel stakeholders. Er is een grotere kans op lokale beleidsverschillen.

Organisatie van zorg

In de knelpuntenanalyse en bij de ontwikkeling van de richtlijnmodule is expliciet aandacht geweest voor de organisatie van zorg: alle aspecten die randvoorwaardelijk zijn voor het verlenen van zorg (zoals coördinatie, communicatie, (financiële) middelen, mankracht en infrastructuur). Randvoorwaarden die relevant zijn voor het beantwoorden van deze specifieke uitgangsvraag zijn genoemd bij de overwegingen.

Commentaar- en autorisatiefase

De conceptrichtlijnmodule werd aan de betrokken (wetenschappelijke) verenigingen en (patiënt) organisaties voorgelegd ter commentaar. De commentaren werden verzameld en besproken met de werkgroep. Naar aanleiding van de commentaren werd de conceptrichtlijnmodule aangepast en definitief vastgesteld door de werkgroep. De definitieve richtlijnmodule werd aan de deelnemende (wetenschappelijke) verenigingen en (patiënt) organisaties voorgelegd voor autorisatie en door hen geautoriseerd dan wel geaccordeerd.

Literatuur

Agoritsas T, Merglen A, Heen AF, Kristiansen A, Neumann I, Brito JP, Brignardello-Petersen R, Alexander PE, Rind DM, Vandvik PO, Guyatt GH. UpToDate adherence to GRADE criteria for strong recommendations: an analytical survey. BMJ Open. 2017 Nov 16;7(11):e018593. doi: 10.1136/bmjopen-2017-018593. PubMed PMID: 29150475; PubMed Central PMCID: PMC5701989.

Alonso-Coello P, Schünemann HJ, Moberg J, Brignardello-Petersen R, Akl EA, Davoli M, Treweek S, Mustafa RA, Rada G, Rosenbaum S, Morelli A, Guyatt GH, Oxman AD; GRADE Working Group. GRADE Evidence to Decision (EtD) frameworks: a systematic and transparent approach to making well informed healthcare choices. 1: Introduction. BMJ. 2016 Jun 28;353:i2016. doi: 10.1136/bmj.i2016. PubMed PMID: 27353417.

Alonso-Coello P, Oxman AD, Moberg J, Brignardello-Petersen R, Akl EA, Davoli M, Treweek S, Mustafa RA, Vandvik PO, Meerpohl J, Guyatt GH, Schünemann HJ; GRADE Working Group. GRADE Evidence to Decision (EtD) frameworks: a systematic and transparent approach to making well informed healthcare choices. 2: Clinical practice guidelines. BMJ. 2016 Jun 30;353:i2089. doi: 10.1136/bmj.i2089. PubMed PMID: 27365494.

Brouwers MC, Kho ME, Browman GP, Burgers JS, Cluzeau F, Feder G, Fervers B, Graham ID, Grimshaw J, Hanna SE, Littlejohns P, Makarski J, Zitzelsberger L; AGREE Next Steps Consortium. AGREE II: advancing guideline development, reporting and evaluation in health care. CMAJ. 2010 Dec 14;182(18):E839-42. doi: 10.1503/cmaj.090449. Epub 2010 Jul 5. Review. PubMed PMID: 20603348; PubMed Central PMCID: PMC3001530.

Hultcrantz M, Rind D, Akl EA, Treweek S, Mustafa RA, Iorio A, Alper BS, Meerpohl JJ, Murad MH, Ansari MT, Katikireddi SV, Östlund P, Tranæus S, Christensen R, Gartlehner G, Brozek J, Izcovich A, Schünemann H, Guyatt G. The GRADE Working Group clarifies the construct of certainty of evidence. J Clin Epidemiol. 2017 Jul;87:4-13. doi: 10.1016/j.jclinepi.2017.05.006. Epub 2017 May 18. PubMed PMID: 28529184; PubMed Central PMCID: PMC6542664.

Medisch Specialistische Richtlijnen 2.0 (2012). Adviescommissie Richtlijnen van de Raad Kwaliteit. http://richtlijnendatabase.nl/over_deze_site/over_richtlijnontwikkeling.html

Neumann I, Santesso N, Akl EA, Rind DM, Vandvik PO, Alonso-Coello P, Agoritsas T, Mustafa RA, Alexander PE, Schünemann H, Guyatt GH. A guide for health professionals to interpret and use recommendations in guidelines developed with the GRADE approach. J Clin Epidemiol. 2016 Apr;72:45-55. doi: 10.1016/j.jclinepi.2015.11.017. Epub 2016 Jan 6. Review. PubMed PMID: 26772609.

Schünemann H, Brożek J, Guyatt G, et al. GRADE handbook for grading quality of evidence and strength of recommendations. Updated October 2013. The GRADE Working Group, 2013. Available from http://gdt.guidelinedevelopment.org/central_prod/_design/client/handbook/handbook.html.

Zoekverantwoording

Zoekacties zijn opvraagbaar. Neem hiervoor contact op met de Richtlijnendatabase.

Bacteriële meningitis

Bacteriële meningitis

Uitgangsvraag

Aanbeveling

Overwegingen

Onderbouwing

Achtergrond

Conclusies

Samenvatting literatuur

Zoeken en selecteren

Referenties

Evidence tabellen

Verantwoording

Autorisatiedatum en geldigheid

Initiatief en autorisatie

Algemene gegevens

Samenstelling werkgroep

Belangenverklaringen

Inbreng patiëntenperspectief

Implementatie

Werkwijze

Zoekverantwoording

Bijlagen

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