Decline in the Incidence of Neonatal Sepsis in Rural Gadchiroli, India During the Twenty-one Years (1998–2019) Following the Home-based Neonatal Care Field-trial
Bibliographic record
Abstract
BACKGROUND: Sepsis is a leading cause of neonatal mortality globally. The home-based neonatal care (HBNC) field trial (1995-1998) in rural Gadchiroli demonstrated a reduction in the incidence of neonatal sepsis. The current study examines the trend of neonatal sepsis during the twenty-one years (1998-2019) following the trial's completion. METHODS: We conducted a retrospective cohort study based on the HBNC program data in rural Gadchiroli, India, from April 1998 to March 2019. All live-born neonates who spent all or part of the neonatal period in the 39 study villages and received HBNC were eligible for inclusion. Sepsis was diagnosed during regular home visits by trained village health workers if pre-specified clinical criteria were present. Sepsis incidence was computed for seven 3-year periods. Trend analyses were conducted using the Mann-Kendall test. RESULTS: Of the total 17,289 live births, 16,339 (94.5%) home visited were included. In this cohort, 1069 (65 per 1000 live births) neonates were diagnosed with sepsis. The incidence of neonatal sepsis declined from 111 per 1000 live births in 1998 to 2001 to 19 per 1000 live births in 2016 to 2019, an 82.9% decrease (P < 0.0001), mean 4% decrease per year. The incidence of neonatal sepsis declined for early-onset sepsis (P < 0.0001), late-onset sepsis (P < 0.0001), home births (P = 0.006), facility births (P < 0.0001), preterm neonates (P < 0.0001) and full-term neonates (P < 0.0001). CONCLUSIONS: The incidence of neonatal sepsis in rural Gadchiroli has continued to decline during the past twenty-one years. We hypothesize that the decline is due to the ongoing practice of HBNC, improved socioeconomic conditions, and new governmental health policies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".