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Groeneveld NS, Bijlsma MW, van Zeggeren IE, Staal SL, Tanck MWT, van de Beek D, Brouwer MC. Diagnostic prediction models for bacterial meningitis in children with a suspected central nervous system infection: a systematic review and prospective validation study. BMJ Open 2024; 14:e081172. [PMID: 39117411 DOI: 10.1136/bmjopen-2023-081172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/10/2024] Open
Abstract
OBJECTIVES Diagnostic prediction models exist to assess the probability of bacterial meningitis (BM) in paediatric patients with suspected meningitis. To evaluate the diagnostic accuracy of these models in a broad population of children suspected of a central nervous system (CNS) infection, we performed external validation. METHODS We performed a systematic literature review in Medline to identify articles on the development, refinement or validation of a prediction model for BM, and validated these models in a prospective cohort of children aged 0-18 years old suspected of a CNS infection. PRIMARY AND SECONDARY OUTCOME MEASURES We calculated sensitivity, specificity, predictive values, the area under the receiver operating characteristic curve (AUC) and evaluated calibration of the models for diagnosis of BM. RESULTS In total, 23 prediction models were validated in a cohort of 450 patients suspected of a CNS infection included between 2012 and 2015. In 75 patients (17%), the final diagnosis was a CNS infection including 30 with BM (7%). AUCs ranged from 0.69 to 0.94 (median 0.83, interquartile range [IQR] 0.79-0.87) overall, from 0.74 to 0.96 (median 0.89, IQR 0.82-0.92) in children aged ≥28 days and from 0.58 to 0.91 (median 0.79, IQR 0.75-0.82) in neonates. CONCLUSIONS Prediction models show good to excellent test characteristics for excluding BM in children and can be of help in the diagnostic workup of paediatric patients with a suspected CNS infection, but cannot replace a thorough history, physical examination and ancillary testing.
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Affiliation(s)
- Nina S Groeneveld
- Department of Neurology, Amsterdam UMC Location AMC, Amsterdam, The Netherlands
| | - Merijn W Bijlsma
- Department of Pediatrics, Amsterdam UMC Location AMC, Amsterdam, The Netherlands
| | | | - Steven L Staal
- Department of Neurology, Amsterdam UMC Location AMC, Amsterdam, The Netherlands
| | - Michael W T Tanck
- Department of Epidemiology and Data Science, Amsterdam UMC-Locatie AMC, Amsterdam, The Netherlands
| | | | - Matthijs C Brouwer
- Department of Neurology, Amsterdam UMC Location AMC, Amsterdam, The Netherlands
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Anne RP, Dutta S, Balasubramanian H, Aggarwal AN, Chadha N, Kumar P. Meta-analysis of Cerebrospinal Fluid Cell Count and Biochemistry to Diagnose Meningitis in Infants Aged < 90 Days. Am J Perinatol 2024; 41:e1962-e1975. [PMID: 37196663 DOI: 10.1055/a-2095-6729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/19/2023]
Abstract
OBJECTIVE Cerebrospinal fluid (CSF) white blood cell (WBC) count, protein, and glucose (cytochemistry) are performed to aid in the diagnosis of meningitis in young infants. However, studies have reported varying diagnostic accuracies. We assessed the diagnostic accuracy of CSF cytochemistry in infants below 90 days and determined the certainty of evidence. STUDY DESIGN We searched PubMed, Embase, Cochrane Library, Ovid, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and Scopus databases in August 2021. We included studies that evaluated the diagnostic accuracy of CSF cytochemistry compared with CSF culture, Gram stain, or polymerase chain reaction in neonates and young infants <90 days with suspected meningitis. We pooled data using the hierarchical summary receiver operator characteristic (ROC) model. RESULTS Of the 10,720 unique records, 16 studies were eligible for meta-analysis, with a cumulative sample size of 31,695 (15 studies) for WBC, 12,936 (11 studies) for protein, and 1,120 (4 studies) for glucose. The median (Q1, Q3) specificities of WBC, protein, and glucose were 87 (82, 91), 89 (81, 94), and 91% (76, 99), respectively. The pooled sensitivities (95% confidence interval [CI]) at median specificity of WBC count, protein, and glucose were 90 (88, 92), 92 (89, 94), and 71% (54, 85), respectively. The area (95% CI) under ROC curves were 0.89 (0.87, 0.90), 0.87 (0.85, 0.88), and 0.81 (0.74, 0.88) for WBC, protein, and glucose, respectively. There was an unclear/high risk of bias and applicability concern in most studies. Overall certainty of the evidence was moderate. A bivariate model-based analysis to estimate the diagnostic accuracy at specific thresholds could not be conducted due to a paucity of data. CONCLUSION CSF WBC and protein have good diagnostic accuracy for the diagnosis of meningitis in infants below 90 days of age. CSF glucose has good specificity but poor sensitivity. However, we could not identify enough studies to define an optimal threshold for the positivity of these tests. KEY POINTS · Median specificity of CSF leucocyte count, protein and glucose are similar in young infants.. · At median specificity, CSF leukocyte count and protein are more sensitive than glucose.. · Owing to inadequate data, bivariate modelling to suggest optimal diagnostic thresholds is not possible..
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Affiliation(s)
- Rajendra P Anne
- Department of Pediatrics, Division of Neonatology, Kasturba Medical College, Manipal, Karnataka, India
| | - Sourabh Dutta
- Department of Pediatrics, Neonatology Unit, Postgraduate Institute of Medical Education and Research, Chandigarh, India
| | | | - Ashutosh N Aggarwal
- Department of Pulmonology, Postgraduate Institute of Medical Education and Research, Chandigarh, India
| | - Neelima Chadha
- Dr. Tulsi Das Library, Postgraduate Institute of Medical Education and Research, Chandigarh, India
| | - Praveen Kumar
- Department of Pediatrics, Neonatology Unit, Postgraduate Institute of Medical Education and Research, Chandigarh, India
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Rajial T, Batra P, Harit D, Singh NP. Utility of Cerebrospinal Fluid and Serum Procalcitonin for the Diagnosis of Neonatal Meningitis. Am J Perinatol 2022; 39:373-378. [PMID: 32920797 DOI: 10.1055/s-0040-1716406] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
OBJECTIVE Positive CSF culture is the gold standard for the diagnosis of meningitis but it carries poor sensitivity. CSF procalcitonin (PCT) is shown to have some utility for the diagnosis of meningitis though there are limited studies in neonatal age group. We planned this study to compare CSF, serum, and CSF to serum PCT levels in neonates with confirmed, probable, and nonmeningitis groups to determine its optimal cut-off in CSF and serum for diagnosing meningitis. STUDY DESIGN Sixty-seven neonates who qualified for lumbar puncture were enrolled in the study. Neonates were categorized into confirmed meningitis, i.e., CSF cytochemistry and culture positive (N = 17), probable meningitis, i.e., CSF cytochemistry positive but culture negative (N = 25) and nonmeningitis, i.e., both cytochemistry and culture negative (N = 25). CSF and serum samples were stored at -80°C for PCT assay. RESULTS Significant difference was seen in mean of CSF PCT in neonates with confirmed (0.31 ng/mL), probable (0.22 ng/mL), and nonmeningitis (0.11 ng/mL) groups. Similarly, significant difference was observed in serum PCT levels also, though the ratio of serum to CSF PCT was comparable. At cut-off of 0.2 ng/mL, CSF PCT had sensitivity of 95.2% and specificity of 96% in the diagnosis of meningitis. CONCLUSION CSF PCT is more specific marker for the diagnosis of neonatal meningitis as compared with serum PCT and CSF to serum PCT ratio. KEY POINTS · CSF procalcitonin is a better marker than serum procalcitonin for diagnosing neonatal meningitis.. · It is better than serum procalcitonin and CSF to serum procalcitonin ratio.. · At cut-off of >0.2 ng/mL CSF procalcitonin can diagnose neonatal meningitis with 96% specificity..
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Affiliation(s)
- Tanuja Rajial
- Department of Pediatrics, University College of Medical Sciences and Guru Teg Bahadur Hospital, Delhi, India
| | - Prerna Batra
- Department of Pediatrics, University College of Medical Sciences and Guru Teg Bahadur Hospital, Delhi, India
| | - Deepika Harit
- Department of Pediatrics, University College of Medical Sciences and Guru Teg Bahadur Hospital, Delhi, India
| | - Narendra Pal Singh
- Department of Microbiology, University College of Medical Sciences and Guru Teg Bahadur Hospital, Delhi, India
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Accuracy of Clinical and Cerebrospinal Fluid Indicators in the Diagnosis of Bacterial Meningitis in Infants <90 Days of Age in Luanda, Angola. Pediatr Infect Dis J 2021; 40:e462-e465. [PMID: 34561386 DOI: 10.1097/inf.0000000000003305] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND The diagnosis of bacterial meningitis (BM) is problematic in young infants, as clinical features may be nonspecific or even absent. Cerebrospinal fluid (CSF) analysis usually confirms the diagnosis, but the CSF parameters can be normal also in culture-proven BM. Our objective was to identify the clinical and CSF indices, that quickly and without laboratory likely lead to the diagnosis of confirmed of probable BM in young infants in Angola. METHODS We conducted a prospective, observational, single-site study from February 2016 to October 2017 in the Pediatric Hospital of Luanda. All assessed infants showed symptoms and signs compatible of BM or neonatal sepsis and were <90 days of age. RESULTS Of the 1088 infants, 212 (19%) showed bacteria in CSF, while 88 (8%) had probable BM. Independent clinical indicators of BM were not-clear CSF, seizures, weight <2500 g and illness >7 days. In infants with BM, CSF leukocytes were >10 × 106/L in 46%, CSF glucose <25 mg/dL in 43% and CSF protein >120 mg/dL in 58%. All measured parameters were in normal range in 25% of patients. In 515 infants with normal CSF parameters, bacteria were found in 74 (14%). In these infants, illness >7 days, weight <2500 g and malnutrition increased the probability of BM. CONCLUSIONS Our study confirms and underlines the problems in diagnosing BM in young infants. While the CSF parameters were normal in 25% of infants, the easily recognizable unclear appearance of CSF was the single strongest predictor of BM.
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Chen Y, Yin Z, Gong X, Li J, Zhong W, Shan L, Lei X, Zhang Q, Zhou Q, Zhao Y, Chen C, Zhang Y. A sequential guide to identify neonates with low bacterial meningitis risk: a multicenter study. Ann Clin Transl Neurol 2021; 8:1132-1140. [PMID: 33836125 PMCID: PMC8108426 DOI: 10.1002/acn3.51356] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Revised: 03/12/2021] [Accepted: 03/16/2021] [Indexed: 11/08/2022] Open
Abstract
Objective To derive and validate a predictive algorithm integrating clinical and laboratory parameters to stratify a full‐term neonate's risk level of having bacterial meningitis (BM). Methods A multicentered dataset was categorized into derivation (689 full‐term neonates aged ≤28 days with a lumbar puncture [LP]) and external validation (383 neonates) datasets. A sequential algorithm with risk stratification for neonatal BM was constructed. Results In the derivation dataset, 102 neonates had BM (14.8%). Using stepwise regression analysis, fever, infection source absence, neurological manifestation, C‐reactive protein (CRP), and procalcitonin were selected as optimal predictive sets for neonatal BM and introduced to a sequential algorithm. Based on the algorithm, 96.1% of BM cases (98 of 102) were identified, and 50.7% of the neonates (349 of 689) were classified as low risk. The algorithm’s sensitivity and negative predictive value (NPV) in identifying neonates at low risk of BM were 96.2% (95% CI 91.7%–98.9%) and 98.9% (95% CI 97.6%–99.6%), respectively. In the validation dataset, sensitivity and NPV were 95.9% (95% CI 91.0%–100%) and 98.8% (95% CI 97.7%–100%). Interpretation The sequential algorithm can risk stratify neonates for BM with excellent predictive performance and prove helpful to clinicians in LP‐related decision‐making.
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Affiliation(s)
- Yan Chen
- Department of Neonatology, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Zhanghua Yin
- Department of Neonatology, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Xiaohui Gong
- Department of Neonatology, Children's Hospital of Shanghai, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Jing Li
- Department of Neonatology, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Wenhua Zhong
- Department of Neonatology, The Maternal and Child Health Hospital of Jiaxing, Jiaxing, China
| | - Liqin Shan
- Department of Neonatology, The Maternal and Child Health Hospital of Jiaxing, Jiaxing, China
| | - Xiaoping Lei
- Department of Neonatology, The Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Qian Zhang
- Department of Neonatology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Qin Zhou
- Department of Neonatology, The Affiliated Wuxi Maternity and Child Health Care Hospital of Nanjing Medical University, Wuxi, China
| | - Youyan Zhao
- Department of Neonatology, Children's Hospital of Nanjing Medical University, Nanjing, China
| | - Chao Chen
- Department of Neonatology, Children's Hospital of Fudan University, Shanghai, China
| | - Yongjun Zhang
- Department of Neonatology, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
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Li H, Xiao R, Javed R, Li K, Ye W, Zhou W, Liang H. Evaluation of cerebrospinal fluid and blood parameters finding in early diagnosis and drug therapy of suspected bacterial meningitis in neonates. JOURNAL OF RESEARCH IN MEDICAL SCIENCES 2020; 25:77. [PMID: 33088314 PMCID: PMC7554534 DOI: 10.4103/jrms.jrms_470_19] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/04/2019] [Revised: 11/26/2019] [Accepted: 04/18/2020] [Indexed: 11/17/2022]
Abstract
Background: Whether early lumbar puncture (LP) and blood indicators are suitable as diagnostic criteria and helpful to treatment strategies for newborns remains to be solved. The study was to evaluate the value of cerebrospinal fluid (CSF) at the first LP and blood indicators at the similar time in the early diagnosis and the drug therapy of neonatal bacterial meningitis. Materials and Methods: We conducted a retrospective observational study of 997 infants with suspected bacterial meningitis between June 2012 and June 2018. CSF and blood parameters were evaluated by three stepwise logistic models to assess their ability: to distinguish bacterial meningitis from nonbacterial meningitis, to distinguish positive CSF culture from negative, and to distinguish Gram-positive bacteria from negative. Results: Of the 997 neonates, 236 (23.67%) were later diagnosed as bacterial meningitis. Of the neonates with meningitis, 54 (22.88%) had positive CSF culture results. And of neonates with positive CSF culture, 27 (50%) had Gram-positive results. One or more CSF indicators were added to the three models. Only blood hypersensitive C-reactive protein and blood lactate dehydrogenase were added to the first model, while no blood parameters was added to the other two models. The areas under the effect-time curves of the three models were 0.91 (95% confidence interval [CI]: 0.89–0.92, P < 0.001), 0.69 (95% CI: 0.63–0.75, P < 0.001), and 0.86 (95% CI: 0.74–0.94, P < 0.001), respectively. Conclusion: LP was irreplaceable predictor of bacterial meningitis, and comprehensive analysis of CSF indicators can predict the offending organism, which enables refinement of therapy.
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Affiliation(s)
- Huixian Li
- Guangzhou Women and Children's Medical Center, Institute of Pediatrics, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Rui Xiao
- Department of Respiration, Guangzhou Panyu Central Hospital, Guangzhou, Guangdong, China
| | - Ruheena Javed
- Guangzhou Women and Children's Medical Center, Institute of Pediatrics, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Kuanrong Li
- Guangzhou Women and Children's Medical Center, Institute of Pediatrics, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Weitao Ye
- Public Health School, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Wei Zhou
- Guangzhou Women and Children's Medical Center, Neonatal Intensive Care Unit, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Huiying Liang
- Guangzhou Women and Children's Medical Center, Institute of Pediatrics, Guangzhou Medical University, Guangzhou, Guangdong, China
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