Non-treatment of children with community health worker-diagnosed fast-breathing pneumonia in rural Malawi: exploratory subanalysis of a prospective cohort study
Bibliographic record
Abstract
Despite recent progress, pneumonia remains the largest infectious killer of children globally. This paper describes outcomes of not treating community-diagnosed fast-breathing pneumonia on patient recovery.We conducted an exploratory subanalysis of an observational prospective cohort study in Malawi. We recruited children (2-59 months) diagnosed by community health workers with fast-breathing pneumonia using WHO integrated community case management (iCCM) guidelines. Children were followed at days 5 and 14 with a clinical assessment of recovery. We conducted bivariate and multivariable logistic regression for the association between treatment of fast-breathing pneumonia and recovery, adjusting for potential confounders.We followed up 847 children, of whom 78 (9%) had not been given antibiotics (non-treatment). Non-treatment cases had higher baseline rates of diarrhoea, non-severe hypoxaemia and fever. Non-recovery (persistence or worsening of symptoms) was 13% and 23% at day 5 in those who did receive and those who did not receive co-trimoxazole. Non-recovery, when defined as worsening of symptoms only, at day 5 was 7% in treatment and 10% in non-treatment cases. For both definitions, combined co-trimoxazole and lumefantrine-artemether (LA) treatment trended towards protection (adjusted OR (aOR) 0.28; 95% CI 0.12 to 0.68/aOR 0.29; 95% CI 0.08 to 1.01).We found that children who did not receive co-trimoxazole treatment had worse clinical outcomes; malaria co-diagnosis and treatment also play a significant role in non-recovery. Further research into non-treatment of fast-breathing pneumonia, using a pragmatic approach with consideration for malaria co-diagnosis and HIV status is needed to guide refinement of community treatment algorithms in this region.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".