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Record W4412378801 · doi:10.1136/bmjph-2024-002383

Severe infection incidence among young infants in Dhaka, Bangladesh: an observational cohort study

2025· article· en· W4412378801 on OpenAlex
Alastair Fung, Cole Heasley, Lisa G. Pell, Diego G. Bassani, Prakesh S Shah, Shaun K. Morris, Davidson H. Hamer, Mohammad Shahidul Islam, Abdullah Al Mahmud, Eleanor Pullenayegum, Samir K. Saha, Rashidul Haque, Md. Iqbal Hossain, Chun-Yuan Chen, Abby Emdin, Karen M O’Callaghan, Miranda G. Loutet, Shamima Sultana, S M Masum Billah, S. M. Abdul Gaffar, Enamul Karim, Sharika Sayed, Sultana Yeasmin, Md. Mahbubul Hoque, Tahmeed Ahmed, Shafiqul Alam Sarker, Daniel Roth

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBMJ Public Health · 2025
Typearticle
Languageen
FieldMedicine
TopicNeonatal and Maternal Infections
Canadian institutionsMount Sinai HospitalInstitute for Clinical Evaluative SciencesUniversity of TorontoSickKids FoundationHospital for Sick ChildrenPublic Health Ontario
FundersInternational Centre for Diarrhoeal Disease Research, BangladeshHospital for Sick ChildrenBill and Melinda Gates Foundation
KeywordsMedicineIncidence (geometry)ReferralSepsisBlood culturePediatricsPsychological interventionCohortInternal medicineAntibioticsFamily medicine

Abstract

fetched live from OpenAlex

Introduction: Heterogeneity in definitions of severe infection, sepsis and serious bacterial infection (SBI) in infants limits the comparability of randomised controlled trials (RCTs) of infection prevention interventions. To inform the design of infection prevention RCTs for infants in low-resource settings, we estimated the incidence of severe infection and death among Bangladeshi infants aged 0-60 days using variations in case definitions. Methods: Among 1939 infants born generally healthy in Dhaka, Bangladesh, severe infection was identified through up to 12 scheduled community health worker home visits from 0 to 60 days of age or through caregiver self-referral. The primary severe infection case definition combined physician documentation of standardised clinical signs and/or diagnosis of sepsis/SBI, plus either a positive blood culture or parenteral antibiotic treatment for ≥5 days. Incidence rates were estimated for the primary severe infection definition, the WHO definition of possible SBI, blood culture-confirmed infection and five alternative definitions including non-injury death. Results: Severe infection incidence per 1000 infant-days was 1.2 (95% CI 0.97 to 1.4) using the primary definition, 0.84 (0.69 to 1.0) using the WHO definition of possible SBI, 0.026 (0.0085 to 0.081) using blood culture-confirmed infection and 0.061 (0.029 to 0.13) for death. One-third of cases met criteria for the primary severe infection definition through physician diagnosis of sepsis/SBI rather than the standardised clinical signs, and 85% of cases were identified following caregiver self-referral despite frequent scheduled visits. Conclusions: Severe infection incidence in infants varied considerably by case definition. Using a clinical sign-based definition may miss a substantial proportion of cases identified by physician diagnosis of sepsis/SBI. A consensus definition of severe infection in infants that balances permissiveness and stringency and can be operationalised in low-resource countries would improve the comparability of RCTs. If health facilities are accessible and caregivers readily seek care for infant illness, frequently scheduled home assessments may not be necessary.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.022
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.086
GPT teacher head0.404
Teacher spread0.318 · 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