Evaluation of Febrile Infant

PEDIATRICS ◽  
1993 ◽  
Vol 91 (3) ◽  
pp. 678-678
Author(s):  
TRACY LIEU ◽  
MARC BASKIN ◽  
GARY FLEISHER
Keyword(s):  
Bacterial Meningitis ◽  
Cell Count ◽  
Febrile Infant ◽  
Original Analysis ◽  
Imperfect Sensitivity

In Reply.— We appreciate Dr Levin's contribution to our analysis for febrile infants and agree that including the imperfect sensitivity of the CSF cell count in identifying meningitis improves the model's completeness. However, taken in perspective, the addition does not substantially alter our findings. In the original analysis, All Sepsis Tests + IV Antibiotics prevented 78% of sequelae, and All Sepsis Tests + IM Ceftriaxone prevented 76% of sequelae.1 Rodewald's study2 reported that a CSF cell count ≥6 had a sensitivity of 98.4% in identifying bacterial meningitis.

scholarly journals Phosphatidylcholine PC ae C44:6 in cerebrospinal fluid is a sensitive biomarker for bacterial meningitis

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Leonardo Silva de Araujo ◽  
Kevin Pessler ◽  
Kurt-Wolfram Sühs ◽  
Natalia Novoselova ◽  
Frank Klawonn ◽  
...  
Keyword(s):  
Cerebrospinal Fluid ◽  
Bacterial Meningitis ◽  
Cell Count ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Characteristic Curve ◽  
Viral Meningitis ◽  
Acute Bacterial Meningitis ◽  
Membrane Phospholipids ◽  
Cns Disorders

Abstract Background The timely diagnosis of bacterial meningitis is of utmost importance due to the need to institute antibiotic treatment as early as possible. Moreover, the differentiation from other causes of meningitis/encephalitis is critical because of differences in management such as the need for antiviral or immunosuppressive treatments. Considering our previously reported association between free membrane phospholipids in cerebrospinal fluid (CSF) and CNS involvement in neuroinfections we evaluated phosphatidylcholine PC ae C44:6, an integral constituent of cell membranes, as diagnostic biomarker for bacterial meningitis. Methods We used tandem mass spectrometry to measure concentrations of PC ae C44:6 in cell-free CSF samples (n = 221) from patients with acute bacterial meningitis, neuroborreliosis, viral meningitis/encephalitis (herpes simplex virus, varicella zoster virus, enteroviruses), autoimmune neuroinflammation (anti-NMDA-receptor autoimmune encephalitis, multiple sclerosis), facial nerve and segmental herpes zoster (shingles), and noninflammatory CNS disorders (Bell’s palsy, Tourette syndrome, normal pressure hydrocephalus). Results PC ae C44:6 concentrations were significantly higher in bacterial meningitis than in all other diagnostic groups, and were higher in patients with a classic bacterial meningitis pathogen (e.g. Streptococcus pneumoniae, Neisseria meningitidis, Staphylococcus aureus) than in those with less virulent or opportunistic pathogens as causative agents (P = 0.026). PC ae C44:6 concentrations were only moderately associated with CSF cell count (Spearman’s ρ = 0.45; P = 0.009), indicating that they do not merely reflect neuroinflammation. In receiver operating characteristic curve analysis, PC ae C44:6 equaled CSF cell count in the ability to distinguish bacterial meningitis from viral meningitis/encephalitis and autoimmune CNS disorders (AUC 0.93 both), but had higher sensitivity (91% vs. 41%) and negative predictive value (98% vs. 89%). A diagnostic algorithm comprising cell count, lactate and PC ae C44:6 had a sensitivity of 97% (specificity 87%) and negative predictive value of 99% (positive predictive value 61%) and correctly diagnosed three of four bacterial meningitis samples that were misclassified by cell count and lactate due to low values not suggestive of bacterial meningitis. Conclusions Increased CSF PC ae C44:6 concentrations in bacterial meningitis likely reflect ongoing CNS cell membrane stress or damage and have potential as additional, sensitive biomarker to diagnose bacterial meningitis in patients with less pronounced neuroinflammation.

Early (chemical) diagnosis of bacterial meningitis--cerebrospinal fluid glucose, lactate, and lactate dehydrogenase compared.

1981 ◽  
Vol 27 (8) ◽  
pp. 1431-1434 ◽  
Author(s):  
J A Knight ◽  
S M Dudek ◽  
R E Haymond
Keyword(s):  
Cerebrospinal Fluid ◽  
Lactate Dehydrogenase ◽  
Bacterial Meningitis ◽  
Cell Count ◽  
Reference Intervals ◽  
Fluid Cell ◽  
Early Indicators

Abstract Both lactate and lactate dehydrogenase are more sensitive as early indicators of bacterial meningitis than is glucose, and both appear to help differentiate aseptic from bacterial meningitis. In selected cases, lactate dehydrogenase may be more sensitive than lactate. We also give reference intervals for cerebrospinal fluid cell count, glucose, lactate, and lactate dehydrogenase.

scholarly journals A Diagnostic Scoring System for Distinguishing between Tuberculous and Bacterial Meningitis Based on Clinical and Laboratory Findings

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Yongyan He ◽  
Yueli Zou ◽  
Junying He ◽  
Hui Bu ◽  
Yaling Liu
Keyword(s):  
Cerebrospinal Fluid ◽  
Bacterial Meningitis ◽  
Cell Count ◽  
Tuberculous Meningitis ◽  
Scoring System ◽  
White Cell Count ◽  
Characteristic Curve ◽  
Chinese Patients ◽  
Laboratory Findings ◽  
Microbial Resources

It is very difficult to diagnose and distinguish tuberculous meningitis, and the current laboratory methods are unsubstantial in developing countries. The study is aimed at creating a scoring system on the basis of basic laboratory and clinical achievements that could be used as diagnostic aid for tuberculous meningitis for Chinese patients. A retrospective study of cases was conducted for comparison between clinical characteristics and laboratory features of 241 patients on admission who conformed to inclusion criteria of tuberculous meningitis ( n = 141 ) or bacterial meningitis ( n = 100 ). Logistic regression was employed to establish a diagnostic formula to distinguish between tuberculous meningitis and bacterial meningitis. The receiver operating characteristic curve analysis was applied to determine the best diagnostic critical point of the diagnostic formula. It was found that five variables (disease course, white blood cell count, serum sodium, total white cell count of cerebrospinal fluid, and neutrophil proportion in cerebrospinal fluid) were independently associated with tuberculous meningitis. The 87% sensitivity and 94% specificity were included in the diagnostic scoring system derived from these variables. Especially in the case of limited microbial resources, doctors can use this diagnostic scoring system to distinguish tuberculous meningitis from bacterial meningitis.

scholarly journals Clinical and laboratorial characteristics of bacterial meningitis in children

1996 ◽  
Vol 54 (4) ◽  
pp. 571-576 ◽  
Author(s):  
Rita Lucena ◽  
Irênio Gomes ◽  
Adriana Ferreira ◽  
Julieta Góes ◽  
Ismara Araújo ◽  
...  
Keyword(s):  
Bacterial Meningitis ◽  
Cell Count ◽  
Etiologic Agent ◽  
Causal Agent ◽  
Acute Bacterial Meningitis ◽  
Poor Outcome ◽  
Classic Triad ◽  
Meningitis In Children

Data from the records of 528 children under 15 years old with diagnosis of acute bacterial meningitis, admitted at the Hospital Couto Maia between 1990 and 1992 were analyzed. Bacterial meningitis was more frequent in children under the age of 1 year (37.8%). The most common etiologic agent was H. influenzae (42.2%). The global letality was 20.9%. Individual predictors of poor outcome were: absence of the "classic triad", CSF cell count under 1000 /mm³, age under 2 years, presence of seizures, depressed sensorium, and S. pneumoniae as causal agent.

scholarly journals Diagnostic Model for Discrimination Between Tuberculous Meningitis and Bacterial Meningitis

2021 ◽  
Vol 12 ◽  
Author(s):  
Ying Luo ◽  
Ying Xue ◽  
Qun Lin ◽  
Liyan Mao ◽  
Guoxing Tang ◽  
...  
Keyword(s):  
Bacterial Meningitis ◽  
Cell Count ◽  
Tuberculous Meningitis ◽  
Roc Curve ◽  
Operating Characteristic ◽  
Specific Antigen ◽  
Diagnostic Model ◽  
City Hospital ◽  
Roc Curve Analysis ◽  
New City

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.

COMPARING CSF PARAMETERS BETWEEN CHILDREN DIAGNOSED WITH BACTERIALAND ASEPTIC MENINGITIS

2021 ◽  
pp. 56-58
Author(s):  
Love Kumar Sah ◽  
Subin Manandhar ◽  
Prince Pareek ◽  
Sanjay Shah ◽  
Reema Garegrat
Keyword(s):  
Bacterial Meningitis ◽  
Cell Count ◽  
Aseptic Meningitis ◽  
Neutrophil Count ◽  
Blood Levels ◽  
P Value ◽  
Protein Levels ◽  
Glucose Levels ◽  
Meningitis In Children ◽  
Csf Examination

Introduction: Diagnosis of meningitis in children cannot rely on clinical examination. Present study aimed to evaluate the role of CSF examination in differentiating bacterial from aseptic meningitis in children less than 14 years of age. Methodology: This observational crosssectional study included children aged 1 month to 14 years with a diagnosis of meningitis. Children were classied as bacterial meningitis or aseptic meningitis. CSF examination was conducted to measure CRP, cell count, neutrophil count, lymphocytes, glucose levels and protein levels. Statistical comparison was made between children with bacterial meningitis and aseptic meningitis. Results: Children aged less than 2 years had the highest incidence of meningitis to the extent of 30.6%. CSF examination revealed than CRP was found to be positive in 81.82% of the patients with bacterial meningitis, while only 3.45% of the patients with aseptic meningitis had a positive CRP (p value < 0.001). It was observed that median cell count and neutrophil count were signicantly higher among patients with bacterial meningitis as compared to those with aseptic meningitis. While, median lymphocyte count was signicantly lower in patients with bacterial meningitis as compared to those with aseptic meningitis (p value < 0.001). Furthermore, we observed that CSF glucose less than 50% of that blood levels was observed in 81.82% of the patients with bacterial meningitis, which was signicantly higher than those diagnosed with aseptic meningitis (p value < 0.05). Conclusions: CSF CRP and biochemical parameters like cell count, neutrophils and glucose levels can aid in differentiating bacterial from aseptic meningitis

White Blood Cell Count in the Evaluation of the Febrile Infant

2017 ◽  
Vol 171 (11) ◽  
pp. e172796 ◽  
Author(s):  
Matthew Mischler ◽  
Francis McBee Orzulak ◽  
Jessica Hanks
Keyword(s):  
Blood Cell ◽  
Cell Count ◽  
White Blood Cell Count ◽  
White Blood Cell ◽  
Blood Cell Count ◽  
Febrile Infant
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