Evidence map›Paper›PMID 36759812›Full record

ArticleBMC pediatrics2023

Development a prediction model for identifying bacterial meningitis in young infants aged 29-90 days: a retrospective analysis.

Jiahui Wu, Ting Shi, Yongfei Yue, Xiaoxing Kong, Fangfang Cheng, Yanqun Jiang, Yuanxi Bian, Jianmei Tian

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC pediatrics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.1field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 5 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Jiahui WuDepartment of Infectious Diseases, Children's Hospital of Soochow University, No. 92, Zhongnan Street, Suzhou, 215025, China.
Ting ShiDepartment of Infectious Diseases, Children's Hospital of Soochow University, No. 92, Zhongnan Street, Suzhou, 215025, China.
Yongfei YueDepartment of Obstetrics and Gynecology, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China.
Xiaoxing KongDepartment of Infectious Diseases, Children's Hospital of Soochow University, No. 92, Zhongnan Street, Suzhou, 215025, China.
Fangfang ChengDepartment of Infectious Diseases, Children's Hospital of Soochow University, No. 92, Zhongnan Street, Suzhou, 215025, China.
Yanqun JiangDepartment of Infectious Diseases, Children's Hospital of Soochow University, No. 92, Zhongnan Street, Suzhou, 215025, China.
Yuanxi BianDepartment of Infectious Diseases, Children's Hospital of Soochow University, No. 92, Zhongnan Street, Suzhou, 215025, China.
Jianmei TianDepartment of Infectious Diseases, Children's Hospital of Soochow University, No. 92, Zhongnan Street, Suzhou, 215025, China. jian_meitian@163.com.
Soochow University · CNNanjing Medical University · CN

Funding

Maternal and children's health research project of Jiangsu Province F202108Suzhou Municipal Health Commission SZS2020310
6 · The paper itself

Abstract

backgroundThe early diagnosis and treatment of bacterial meningitis (BM) in young infants was very critical. But, it was difficult to make a definite diagnosis in the early stage due to nonspecific clinical symptoms. Our objectives were to find the risk factors associated with BM and develop a prediction model of BM especially for young infants.

methodsWe retrospectively reviewed the clinical data of young infants with meningitis between January 2011 and December 2020 in Children's Hospital of Soochow University. The independent risk factors of young infants with BM were screened using univariate and multivariate logistic regression analyses. The independent risk factors were used to construct a new scoring model and compared with Bacterial Meningitis Score (BMS) and Meningitis Score for Emergencies (MSE) models.

resultsAmong the 102 young infants included, there were 44 cases of BM and 58 of aseptic meningitis. Group B Streptococcus (22, 50.0%) and Escherichia coli (14, 31.8%) were the main pathogens of BM in the young infants. Multivariate logistic regression analysis identified procalcitonin (PCT), cerebrospinal fluid (CSF) glucose, CSF protein as independent risk factors for young infants with BM. We assigned one point for CSF glucose ≤ 1.86 mmol/L, two points were assigned for PCT ≥ 3.80 ng/ml and CSF protein ≥ 1269 mg/L. Using the not low risk criterion (score ≥ 1) with our new prediction model, we identified the young infantile BM with 100% (95% CI 91.9%-100%) sensitivity and 60.3% (95% CI 46.4%-72.9%) specificity. Compared with BMS and MSE model, our prediction model had larger area under receiver operating characteristic curve and higher specificity, the differences were statistically significant.

conclusionOur new scoring model for young infants can facilitate early identification of BM and has a better performance than BMS and MSE models.

Indexed as

Meningitis, BacterialChildDiagnosis, DifferentialGlucoseHumansInfantProcalcitoninRetrospective StudiesROC CurveSensitivity and SpecificityGlucoseProcalcitoninBacterial meningitisCerebrospinal fluid pleocytosisPredictionYoung infants

Identifiers

PMID36759812
PMCPMC9909842
OpenAlexW4319752847

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.