Evaluating blood culture collection practice in children hospitalized with acute illness at a tertiary hospital in Malawi
Bibliographic record
Abstract
BACKGROUND: Blood culture collection practice in low-resource settings where routine blood culture collection is available has not been previously described. METHODOLOGY: We conducted a secondary descriptive analysis of children aged 2-23 months enrolled in the Malawi Childhood Acute Illness and Nutrition (CHAIN) study, stratified by whether an admission blood culture had been undertaken and by nutritional status. Chi-square test was used to compare the differences between groups. RESULTS: A total of 347 children were included, of whom 161 (46%) had a blood culture collected. Children who had a blood culture collected, compared to those who did not, were more likely to present with sepsis (43% vs. 20%, p < 0.001), gastroenteritis (43% vs. 26%, p < 0.001), fever (86% vs. 73%, p = 0.004), and with poor feeding/weight loss (30% vs. 18%, p = 0.008). In addition, hospital stay in those who had a blood culture was, on average, 2 days longer (p = 0.019). No difference in mortality was observed between those who did and did not have a blood culture obtained. CONCLUSION: Blood culture collection was more frequent in children with sepsis and gastroenteritis, but was not associated with mortality. In low-resource settings, developing criteria for blood culture based on risk factors rather than clinician judgement may better utilize the existing resources.
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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 | 0.002 | 0.010 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".