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Epidemiology, microbiology and antibiotic treatment of bacterial and fungal meningitis among very preterm infants in China: a cross-sectional study

2024· article· en· W4402653565 on OpenAlexafffund
Ping Cheng, Aimin Qian, Hongbo Zhang, Yingying Wang, Shujuan Li, Mengya Sun, Jie Yang, Jian‐Guo Zhou, Liyuan Hu, Xiaoping Lei, Yu Hu, Ligang Zhou, Lizhong Du, Yun Cao, Shoo K. Lee, Wenhao Zhou, Wenqing Kang, Changlian Zhu, Huiqing Sun, Siyuan Jiang

Bibliographic record

VenueArchives of Disease in Childhood Fetal & Neonatal · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBacterial Infections and Vaccines
Canadian institutionsMount Sinai Hospital
FundersNational Key Research and Development Program of ChinaCanadian Institutes of Health ResearchChina Medical Board
KeywordsMeropenemMedicineMeningitisEpidemiologyAntibioticsIncidence (geometry)PediatricsLumbar punctureVancomycinGestational ageIntensive careInternal medicineMicrobiologyIntensive care medicineAntibiotic resistanceBiologyPregnancyBacteriaCerebrospinal fluid

Abstract

fetched live from OpenAlex

OBJECTIVE: Neonatal meningitis significantly contributes to neonatal morbidity and mortality, yet large-scale epidemiological data in developing countries, particularly among very preterm infants (VPIs), remain sparse. This study aimed to describe the epidemiology of meningitis among VPIs in China. DESIGN: Cross-sectional study using the Chinese Neonatal Network database from 2019 to 2021. SETTING: 79 tertiary neonatal intensive care units in China. PATIENTS: Infants with gestational age <32 weeks or birth weight <1500 g. MAIN OUTCOME MEASURES: Incidence, pathogen distribution, antimicrobial use and outcomes of bacterial and fungal meningitis. RESULTS: Of 31 915 VPIs admitted, 122 (0.38%) infants were diagnosed with culture-confirmed meningitis, with 14 (11.5%) being early-onset (≤6 days of age) and 108 (88.5%) being late-onset (>6 days of age). The overall in-hospital mortality was 18.0% (22/122). A total of 127 pathogens were identified, among which 63.8% (81/127) were Gram-negative bacteria, 24.4% (31/127) were Gram-positive bacteria and 11.8% (15/127) were fungi. In terms of empirical therapy (on the day of the first lumbar puncture), the most commonly used antibiotic was meropenem (54.9%, 67/122). For definitive therapy (on the sixth day following the first lumbar puncture, 86 cases with available antibiotic data), meropenem (60.3%, 35/58) and vancomycin (57.1%, 16/28) were the most used antibiotics for Gram-negative and Gram-positive bacterial meningitis, respectively. 44% of infants with Gram-positive bacterial meningitis and 52% with Gram-negative bacterial meningitis received antibiotics for more than 3 weeks. CONCLUSION: 0.38% of VPIs in Chinese neonatal intensive care units were diagnosed with meningitis, experiencing significant mortality and inappropriate antibiotic therapy. Gram-negative bacteria were the predominant pathogens, with fungi emerging as a significant cause.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.269
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2024
Admission routes2
Has abstractyes

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