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Elevations of novel cytokines in bacterial meningitis in infants.

ABSTRACT: Bacterial meningitis is challenging to diagnose in infants, especially in the common setting of antibiotic pre-treatment, which diminishes yield of cerebrospinal fluid (CSF) cultures. Prior studies of diagnostic markers have not demonstrated sufficient accuracy. Interleukin-23 (IL-23), interleukin-18 (IL-18) and soluble receptor for advanced glycation end products (sRAGE) possess biologic plausibility, and may be useful as diagnostic markers in bacterial meningitis.In a prospective cohort study, we measured IL-23, IL-18 and sRAGE levels in CSF. We compared differences between infected and non-infected infants, and conducted receiver operating characteristic (ROC) analyses to identify individual markers and combinations of markers with the best diagnostic accuracy.189 infants <6 months, including 8 with bacterial meningitis, 30 without meningitis, and 151 with indeterminate diagnosis (due to antibiotic pretreatment) were included. CSF IL-23, IL-18 and sRAGE levels were significantly elevated in infants with culture proven meningitis. Among individual markers, IL-23 possessed the greatest accuracy for diagnosis of bacterial meningitis (area under the curve (AUC) 0.9698). The combination of all three markers had an AUC of 1.IL-23, alone and in combination with IL-18 and sRAGE, identified bacterial meningitis with excellent accuracy. Following validation, these markers could aid clinicians in diagnosis of bacterial meningitis and decision-making regarding prolongation of antibiotic therapy.

SUBMITTER: Srinivasan L

PROVIDER: S-EPMC5796685 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Elevations of novel cytokines in bacterial meningitis in infants.

Srinivasan Lakshmi L Kilpatrick Laurie L Shah Samir S SS Abbasi Soraya S Harris Mary C MC

PloS one 20180202 2

<h4>Background</h4>Bacterial meningitis is challenging to diagnose in infants, especially in the common setting of antibiotic pre-treatment, which diminishes yield of cerebrospinal fluid (CSF) cultures. Prior studies of diagnostic markers have not demonstrated sufficient accuracy. Interleukin-23 (IL-23), interleukin-18 (IL-18) and soluble receptor for advanced glycation end products (sRAGE) possess biologic plausibility, and may be useful as diagnostic markers in bacterial meningitis.<h4>Methods ...[more]

PMID: 29394248

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Project description:Differential diagnosis of bacterial meningitis (BM) and viral meningitis (VM) is a critical clinical challenge, as the early and accurate identification of the causative agent determines the appropriate treatment regimen and markedly improves patient outcomes. Clinical and experimental studies have demonstrated that the pathogen and the host immune response contribute to mortality and neurological sequelae. As BM is associated with the activation of an inflammatory cascade, the patterns of pro- and anti-inflammatory cytokines/chemokines (CTs/CKs) present in the cerebrospinal fluid (CSF) in response to the immune assault may be useful as sensitive markers for differentiating BM from VM. In the present study, the ability of CTs/CKs in the CSF to differentiate between BM and VM was investigated. For this, biochemical markers and CT/CK profiles were analysed in 145 CSF samples, divided into three groups: BM (n=61), VM (n=58) and the control group (C; n=26) comprising patients with meningism. The CSF concentrations of monocyte chemoattractant protein-1, interleukin (IL)-8, IL-1β, IL-6, macrophage inflammatory protein-1α (MIP-1α), epithelial-neutrophil activating peptide, IL-10, tumour necrosis factor-α (TNF-α), proteins and white blood cells were significantly higher and the CSF glucose level was significantly lower in the BM group compared with the VM and C groups (P<0.01). Correlation analysis identified 28 significant correlations between various CTs/CKs in the BM group (P<0.01), with the strongest positive correlations being for TNF-α/IL-6 (r=0.75), TNF-α/MIP-1α (r=0.69), TNF-α/IL-1β (r=0.64) and IL-1β/MIP-1α (r=0.64). To identify the optimum CT/CK patterns for predicting and classifying BM and VM, a dataset of 119 BM and VM samples was divided into training (n=90) and testing (n=29) subsets for use as input for a Random Forest (RF) machine learning algorithm. For the 29 test samples (15 BM and 14 VM), the RF algorithm correctly classified 28 samples, with 92% sensitivity and 93% specificity. The results show that the patterns of CT/CK levels in the CSF can be used to aid discrimination of BM and VM.

Project description:ObjectiveTo define early presenting features of bacterial meningitis in young infants in England and to review the adequacy of individual case management as compared with relevant national guidelines and an expert panel review.DesignRetrospective medical case note review and parental recall using standardised questionnaires.SettingEngland and Wales.ParticipantsInfants aged <90 days with bacterial meningitis diagnosed between July 2010 and July 2013.ResultsOf the 97 cases recruited across England and Wales, 66 (68%) were admitted from home and 31 (32%) were in hospital prior to disease onset. Almost all symptoms reported by parents appeared at the onset of the illness, with very few new symptoms appearing subsequently. Overall, 20/66 (30%) infants were assessed to have received inappropriate prehospital management. The median time from onset of first symptoms to first help was 5 hours (IQR: 2-12) and from triage to receipt of first antibiotic dose was 2.0 hours (IQR: 1.0-3.3), significantly shorter in infants with fever or seizures at presentation compared with those without (1.7 (IQR: 1.0-3.0) vs 4.2 (IQR: 1.8-6.3) hours, p=0.02). Overall, 26 (39%) infants had a poor outcome in terms of death or neurological complication; seizures at presentation was the only significant independent risk factor (OR, 7.9; 95% CI 2.3 to 207.0). For cases in hospital already, the median time from onset to first dose of antibiotics was 2.6 (IQR: 1.3-9.8) hours, and 12/31 (39%) of infants had serious neurological sequelae at hospital discharge. Hearing test was not performed in 23% and when performed delayed by ≥4 weeks in 41%.ConclusionsIn young infants, the non-specific features associated with bacterial meningitis appear to show no progression from onset to admission, whereas there were small but significant differences in the proportion of infants with more specific symptoms at hospital admission compared with at the onset of the illness, highlighting the difficulties in early recognition by parents and healthcare professionals alike. A substantial proportion of infants received inappropriate prehospital and posthospital management. We propose a targeted campaign for education and harmonisation of practice with evidence-based management algorithms.

Project description:BackgroundThe differential diagnosis between tuberculous meningitis (TBM) and bacterial meningitis (BM) remains challenging in clinical practice. This study aimed to establish a diagnostic model that could accurately distinguish TBM from BM.MethodsPatients with TBM or BM were recruited between January 2017 and January 2021 at Tongji Hospital (Qiaokou cohort) and Sino-French New City Hospital (Caidian cohort). The detection for indicators involved in cerebrospinal fluid (CSF) and T-SPOT assay were performed simultaneously. Multivariate logistic regression was used to create a diagnostic model.ResultsA total of 174 patients (76 TBM and 98 BM) and another 105 cases (39 TBM and 66 BM) were enrolled from Qiaokou cohort and Caidian cohort, respectively. Significantly higher level of CSF lymphocyte proportion while significantly lower levels of CSF chlorine, nucleated cell count, and neutrophil proportion were observed in TBM group when comparing with those in BM group. However, receiver operating characteristic (ROC) curve analysis showed that the areas under the ROC curve (AUCs) produced by these indicators were all under 0.8. Meanwhile, tuberculosis-specific antigen/phytohemagglutinin (TBAg/PHA) ratio yielded an AUC of 0.889 (95% CI, 0.840-0.938) in distinguishing TBM from BM, with a sensitivity of 68.42% (95% CI, 57.30%-77.77%) and a specificity of 92.86% (95% CI, 85.98%-96.50%) when a cutoff value of 0.163 was used. Consequently, we successfully established a diagnostic model based on the combination of TBAg/PHA ratio, CSF chlorine, CSF nucleated cell count, and CSF lymphocyte proportion for discrimination between TBM and BM. The established model showed good performance in differentiating TBM from BM (AUC: 0.949; 95% CI, 0.921-0.978), with 81.58% (95% CI, 71.42%-88.70%) sensitivity and 91.84% (95% CI, 84.71%-95.81%) specificity. The performance of the diagnostic model obtained in Qiaokou cohort was further validated in Caidian cohort. The diagnostic model in Caidian cohort produced an AUC of 0.923 (95% CI, 0.867-0.980) with 79.49% (95% CI, 64.47%-89.22%) sensitivity and 90.91% (95% CI, 81.55%-95.77%) specificity.ConclusionsThe diagnostic model established based on the combination of four indicators had excellent utility in the discrimination between TBM and BM.

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Elevations of novel cytokines in bacterial meningitis in infants.

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Elevations of novel cytokines in bacterial meningitis in infants.

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