Etiology of Bacteremia in Young Infants in Six Countries
Bibliographic record
Abstract
BACKGROUND: Neonatal illness is a leading cause of death worldwide; sepsis is one of the main contributors. The etiologies of community-acquired neonatal bacteremia in developing countries have not been well characterized. METHODS: Infants <2 months of age brought with illness to selected health facilities in Bangladesh, Bolivia, Ghana, India, Pakistan and South Africa were evaluated, and blood cultures taken if they were considered ill enough to be admitted to hospital. Organisms were isolated using standard culture techniques. RESULTS: Eight thousand eight hundred and eighty-nine infants were recruited, including 3177 0-6 days of age and 5712 7-59 days of age; 10.7% (947/8889) had a blood culture performed. Of those requiring hospital management, 782 (54%) had blood cultures performed. Probable or definite pathogens were identified in 10.6% including 10.4% of newborns 0-6 days of age (44/424) and 10.9% of infants 7-59 days of age (39/358). Staphylococcus aureus was the most commonly isolated species (36/83, 43.4%) followed by various species of Gram-negative bacilli (39/83, 46.9%; Acinetobacter spp., Escherichia coli and Klebsiella spp. were the most common organisms). Resistance to second and third generation cephalosporins was present in more than half of isolates and 44% of the Gram-negative isolates were gentamicin-resistant. Mortality rates were similar in hospitalized infants with positive (5/71, 7.0%) and negative blood cultures (42/557, 7.5%). CONCLUSIONS: This large study of young infants aged 0-59 days demonstrated a broad array of Gram-positive and Gram-negative pathogens responsible for community-acquired bacteremia and substantial levels of antimicrobial resistance. The role of S. aureus as a pathogen is unclear and merits further investigation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".