Neonatal Sepsis, Antibiotic Susceptibility Pattern, and Treatment Outcomes among Neonates Treated in Two Tertiary Care Hospitals of Yangon, Myanmar from 2017 to 2019
Bibliographic record
Abstract
Neonatal sepsis is a leading cause of morbidity and mortality in developing countries. This study aimed to assess the proportion of culture-confirmed sepsis, bacteriological pathogen profile, culture report turnaround times, antibiotic susceptibility patterns, and treatment outcomes of all with neonatal sepsis admitted in two tertiary care hospitals in Yangon, Myanmar, 2017–2019. This was a cross sectional study utilizing a standardized electronic database and paper-based records. Bacteriological profiles and associated factors were analyzed with descriptive statistics and Poisson Regression. Of those with suspected sepsis, 42% were bacteriologically confirmed and 74% of confirmed sepsis was resistant to at least first-line antibiotics. Neonates with late onset sepsis (LOS) (aPR: 1.2 (95% CI: 1.1–1.4, p = 0.008)) were more likely to have bacteriologically confirmed sepsis (45%) versus early onset sepsis (38%). Gram-negative organisms were most commonly isolated (63%), associated with multidrug-resistant organisms and with a high case-fatality rate (64%). These findings suggest that enhanced national guidance regarding infection control and prevention, antibiotic stewardship, and first-line antibiotic choices need to be provided. The link between LOS with infection and prevention protocols needs to be further explored in this context to decrease sepsis risk, neonatal mortality, and reduce further antimicrobial resistance.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".