Increased Childhood Morbidity After Measles Is Short-term in Urban Bangladesh
Bibliographic record
Abstract
In a 1995-1996 cohort study in the city of Dhaka, Bangladesh, morbidity in 117 hospitalized and 137 acute measles cases compared with age-matched children without measles (unexposed) was determined by weekly interview for 6 months. Compared with unexposed children, there were higher incidences of hospitalization (adjusted rate ratio (RR) = 3.1, 95% confidence interval (CI): 1.3, 7.6) and bloody diarrhea (adjusted RR = 2.7, 95% CI: 1.4, 5.1) in hospital measles cases during the 6 weeks after recruitment. Among community cohorts, there were higher incidences of bloody diarrhea (adjusted RR = 4.1, 95% CI: 1.1, 14.6), watery diarrhea (adjusted RR = 1.6, 95% CI: 0.9, 2.7), fast breathing (adjusted RR = 3.8, 95% CI: 2.1, 6.9), and the weekly point prevalence of pneumonia (adjusted prevalence ratio = 3.1, 95% CI: 1.0, 9.8) in measles cases during the same period. All measles cases regained lost weight within about 6 weeks. The prevalence of anergy to seven recall antigens 6 weeks after recruitment was higher in both hospital (adjusted odds ratio = 2.8, 95% CI: 1.2, 6.4) and community (adjusted odds ratio = 3.1, 95% CI: 1.1, 8.9) measles cases. Morbidity increased during the first 6-8 weeks after measles, but the authors found no consistent evidence of longer-term morbidity or wasting. The results support recent findings that measles is not associated with increased delayed 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 | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 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".