Validation of the encephalitis criteria in adults with a suspected central nervous system infection: An updated score.

OBJECTIVES: We aimed to validate and refine the encephalitis criteria proposed by the International Encephalitis Consortium in a cohort of adults initially suspected of a central nervous system (CNS) infection. METHODS: We included patients from two prospective cohort studies consisting of adults suspected of a CNS infection whom underwent a diagnostic lumbar puncture. We evaluated the test characteristics of the criteria for both possible and probable encephalitis. The reference standard was a final clinical diagnosis of encephalitis. Recalibration of the criteria was done by adjusting the weight of each criterion based on their respective odds. RESULTS: In total 1446 episodes were evaluated, of whom 162 (11%) had a clinical diagnosis of encephalitis. Possible encephalitis had a sensitivity of 41% (95% CI 33-49) and a specificity of 88% (95% CI 86-90). Probable encephalitis had a sensitivity and specificity of respectively 27% (95% CI 20-34) and 95% (95% CI 94-96). Through odds-based weighting, we recalibrated the weight of each individual criterion, resulting in a model consisting of an altered mental status (weight of 2), seizures (weight of 3), elevated CSF leukocytes (weight of 5) and abnormalities on neuroimaging (weight of 9). We proposed a cut-off at 5 for possible encephalitis, (sensitivity 93% [95% CI 88-96]; specificity 51% [95% 49-54]), and at 8 for probable encephalitis (sensitivity 51% [95% CI 44-59]; specificity 91% [95% CI 89-92]). CONCLUSIONS: We validated and refined the existing diagnostic criteria for encephalitis, leading to a substantially enhanced sensitivity. These updated criteria hold promise to facilitate the accurate identification of encephalitis.

Granulocytes in cerebrospinal fluid of adults suspected of a central nervous system infection: a prospective study of diagnostic accuracy.

PURPOSE: Cerebrospinal fluid (CSF) granulocytes are associated with bacterial meningitis, but information on its diagnostic value is limited and primarily based on retrospective studies. Therefore, we assessed the diagnostic accuracy of CSF granulocytes. METHODS: We analyzed CSF granulocytes (index test) from all consecutive patients in two prospective cohort studies in the Netherlands. Both studies included patients ≥ 16 years, suspected of a central nervous system (CNS) infection, who underwent a diagnostic lumbar puncture. All episodes with elevated CSF leukocytes (≥ 5 cells per mm3) were selected and categorized by clinical diagnosis (reference standard). RESULTS: Of 1261 episodes, 625 (50%) had elevated CSF leukocytes and 541 (87%) were included. 117 of 541 (22%) were diagnosed with bacterial meningitis, 144 (27%) with viral meningoencephalitis, 49 (9%) with other CNS infections, 76 (14%) with CNS autoimmune disorders, 93 (17%) with other neurological diseases and 62 (11%) with systemic diseases. The area under the curve to discriminate bacterial meningitis from other diagnoses was 0.97 (95% confidence interval [CI] 0.95-0.98) for CSF granulocyte count and 0.93 (95% CI 0.91-0.96) for CSF granulocyte percentage. CSF granulocyte predominance occurred in all diagnostic categories. A cutoff at 50% CSF granulocytes gave a sensitivity of 94% (95% CI 90-98), specificity of 80% (95% CI 76-84), negative predictive value of 98% (95% CI 97-99) and positive predictive value of 57% (95% CI 52-62). CONCLUSION: CSF granulocytes have a high diagnostic accuracy for bacterial meningitis in patients suspected of a CNS infection. CSF granulocyte predominance occurred in all diagnostic categories, limiting its value in clinical practice.

Cerebrospinal fluid inflammatory markers to differentiate between neonatal bacterial meningitis and sepsis: A prospective study of diagnostic accuracy.

OBJECTIVES: We evaluated the diagnostic accuracy of cerebrospinal fluid (CSF) inflammatory markers for diagnosing bacterial meningitis in neonates with sepsis and/or meningitis. METHODS: Cases were identified from a prospective multicenter study including patients aged 0-3 months with Group B Streptococcal (GBS) or Escherichia coli culture positive sepsis/meningitis. CSF CXCL10, MDC, IL-6, IL-8, IL-10, TNF- α, MIF, IL-1RA, CXCL13, IL-1ß, CRP and procalcitonin concentrations were measured with Luminex technology. RESULTS: In 61/373 patients (17%) residual CSF from the lumbar puncture was available, of whom 16 (26%) had definitive meningitis, 15 (25%) probable meningitis and 30 (49%) had sepsis. All biomarkers were detectable in CSF and showed significantly higher concentrations in definitive meningitis versus sepsis patients and six biomarkers in probable meningitis versus sepsis patients. Discrimination between definitive meningitis and sepsis was excellent for IL-1RA (area under the receiver operating characteristic curve [AUC] 0.93), TNF-α (AUC 0.92), CXCL10 (AUC 0.90), IL-1ß (AUC 0.92), IL-6 (AUC 0.94), IL-10 (AUC 0.93) and a combination of IL-1RA, TNF-α, CXCL-10 and CSF leukocyte count (AUC 0.95). CSF leukocyte count remained the predictor with the highest diagnostic accuracy (AUC 0.96). CONCLUSION: CSF inflammatory markers can be used to differentiate between neonatal sepsis and meningitis.

Diagnostic accuracy of inflammatory markers in adults with suspected central nervous system infections.

OBJECTIVES: We aimed to determine diagnostic accuracy of inflammatory markers in plasma and cerebrospinal fluid (CSF) for the diagnosis of central nervous system (CNS) infections and specifically bacterial meningitis. METHODS: We analyzed 12 cytokines, chemokines, and acute phase reactants in CSF and plasma of 738 patients with suspected neurological infection included in a multicenter prospective cohort. We determined diagnostic accuracy for predicting any CNS infection and bacterial meningitis. RESULTS: We included 738 episodes between 2017 and 2022, split into a derivation (n = 450) and validation cohort (n = 288). Of these patients, 224 (30%) were diagnosed with CNS infection, of which 81 (11%) with bacterial meningitis, 107 (14%) with viral meningitis or encephalitis, and 35 patients (5%) with another CNS infection. Diagnostic accuracy of CRP, IL-6, and Il-1ß in CSF was high, especially for diagnosing bacterial meningitis. Combining these biomarkers in a multivariable model increased accuracy and provided excellent discrimination between bacterial meningitis and all other disorders (AUC = 0.99), outperforming all individual biomarkers as well as CSF leukocytes (AUC = 0.97). When applied to the population of patients with a CSF leukocyte count of 5-1000 cells/mm3, accuracy of the model also provided a high diagnostic accuracy (AUC model = 0.97 vs. AUC CSF leukocytes = 0.80) with 100% sensitivity and 92% specificity. These results remained robust in a temporal validation cohort. CONCLUSIONS: Inflammatory biomarkers in CSF are able to differentiate CNS infections and especially bacterial meningitis from other disorders. When these biomarkers are combined, their diagnostic accuracy exceeds that of CSF leukocytes alone and as such these markers have added value to current clinical practice.

Predictors of unfavourable outcome in adults with suspected central nervous system infections: a prospective cohort study.

Suspected central nervous system (CNS) infections may pose a diagnostic challenge, and often concern severely ill patients. We aim to identify predictors of unfavourable outcome to prioritize diagnostics and treatment improvements. Unfavourable outcome was assessed on the Glasgow Outcome Scale at hospital discharge, defined by a score of 1 to 4. Of the 1152 episodes with suspected CNS infection, from two Dutch prospective cohorts, the median age was 54 (IQR 37-67), and 563 episodes (49%) occurred in women. The final diagnoses were categorized as CNS infection (N = 358 episodes, 31%), CNS inflammatory disease (N = 113, 10%), non-infectious non-inflammatory neurological disorder (N = 388, 34%), non-neurological infection (N = 252, 22%), and other systemic disorder (N = 41, 4%). Unfavourable outcome occurred in 412 of 1152 (36%), and 99 died (9%). Predictors for unfavourable outcomes included advanced age, absence of headache, tachycardia, altered mental state, focal cerebral deficits, cranial nerve palsies, low thrombocytes, high CSF protein, and the final diagnosis of CNS inflammatory disease (odds ratio 4.5 [95% confidence interval 1.5-12.6]). Episodes suspected of having a CNS infection face high risk of experiencing unfavourable outcome, stressing the urgent need for rapid and accurate diagnostics. Amongst the suspected CNS infection group, those diagnosed with CNS inflammatory disease have the highest risk.

Seizures in adults with suspected central nervous system infection.

BACKGROUND: Seizures can be part of the clinical presentation of central nervous system (CNS) infections. We describe patients suspected of a neurological infection who present with a seizure and study diagnostic accuracy of clinical and laboratory features predictive of CNS infection in this population. METHODS: We analyzed all consecutive patients presenting with a seizure from two prospective Dutch cohort studies, in which patients were included who underwent cerebrospinal fluid (CSF) examination because of the suspicion of a CNS infection. RESULTS: Of 900 episodes of suspected CNS infection, 124 (14%) presented with a seizure. The median age in these 124 episodes was 60 years (IQR 45-71) and 53% of patients was female. CSF examination showed a leukocyte count ≥ 5/mm3 in 41% of episodes. A CNS infection was diagnosed in 27 of 124 episodes (22%), a CNS inflammatory disorder in 8 (6%) episodes, a systemic infection in 10 (8%), other neurological disease in 77 (62%) and in 2 (2%) episodes another systemic disease was diagnosed. Diagnostic accuracy of clinical and laboratory characteristics for the diagnosis of CNS infection in this population was low. CSF leukocyte count was the best predictor for CNS infection in patients with suspected CNS infection presenting with a seizure (area under the curve 0.94, [95% CI 0.88 - 1.00]). CONCLUSIONS: Clinical and laboratory features fail to distinguish CNS infections from other causes of seizures in patients with a suspected CNS infection. CSF leukocyte count is the best predictor for the diagnosis of CNS infection in this population.