Antibiotic use for pneumonia among children under-five at a pediatric hospital in Dhaka city, Bangladesh
Bibliographic record
Abstract
BACKGROUND: Pneumonia has been the leading cause of morbidity and mortality among children under 5 for more than 3 decades, particularly in low-income countries like Bangladesh. The World Health Organization (WHO) developed a pneumonia case management strategy which included the use of antibiotics for both primary and hospital-based care. This study aims to describe antibiotic usage for treating pneumonia in children in a private pediatric teaching hospital in Dhaka, Bangladesh. METHODS: We conducted this cross-sectional study among children <5 years old who were admitted to a private pediatric hospital in Dhaka with a diagnosis of pneumonia in November 2012. RESULTS: We enrolled 80 children during the study period. Among them, 28 (35.4%) were underweight, 14 (17.7%) were moderately underweight, and 13 (16.5%) were severely under-weight. On the basis of WHO classification (2005), 43 children (54%) had severe pneumonia and 37 (46%) had very severe pneumonia, as diagnosed by the research physician. Among the prescribed antibiotics in the hospital, parenteral ceftriaxone was the most common 40 (50%), followed by cefotaxime plus amikacin 14 (17.5%), cefuroxime 7 (8.8%), ceftazidime plus amikacin 6 (7.5%), ceftriaxone plus amikacin 3 (3.8%), meropenem 2 (2.5%), cefepime 2 (2.5%), and cefotaxime 2 (2.5%). CONCLUSION: Despite the WHO pneumonia treatment strategy, the inappropriate use of higher-generation cephalosporin and carbapenem was high in the study hospital. The results underscore the noncompliance with the WHO guidelines of antibiotic use and the importance of enforcing regulatory policy of the rational use of antibiotics for treating hospitalized children with pneumonia. Following these guidelines may help prevent increased antimicrobial resistance.
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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 | 0.000 |
| 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".