Sensitivity Patterns of Bacterial Pathogens Isolated from Blood Cultures of Under-Five Children with Pneumonia and Clinical Sepsis
Bibliographic record
Abstract
Treatment options for pneumonia and sepsis by antibiotics are limited due to the development of multidrug-resistant bacterial strains. This unmatched case-control study determined the antibiotic sensitivity against bacterial isolates obtained from septic and nonseptic children with pneumonia. Children of either sex aged 0–59 months with a history of cough or shortness of breath and radiologically confirmed pneumonia were enrolled in this study. Cases with clinical signs of sepsis at admission (n = 151) were compared to cases without sepsis as controls (n = 107). A total of 205 children had a performance of blood culture, with 123 children suffering from clinical sepsis. Blood cultures showed bacterial growth in 19% of the septic samples, with 8% coagulase-negative staphylococci and 2.4% Acinetobacter species. Only 1.6% of the cases were infected by Streptococcus pneumonia, Haemophilus influenzae, Salmonella typhi and Klebsiella. In contrast, children without sepsis presented positive blood cultures with growth of Salmonella typhi in 2.4% of the cases and growth of Klebsiella in 1.2%. Bacteria were sensitive to imipenem in 100% of the cases (86% for meropenem, 83% for ceftazidime and 76% for ciprofloxacin). The mortality rate was significantly higher in children with pneumonia complicated by sepsis (odds ratio (OR) = 3.02, 95% confidence interval (CI), 1.11–8.64, p < 0.027). Knowledge about specific laboratory characteristics in children with pneumonia will facilitate an early diagnosis and treatment of sepsis and reduce mortality.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".