Long-term effects of coarse particulate matter and modifications by temperature and relative humidity on all-cause mortality in a MDR-TB cohort
Bibliographic record
Abstract
Background: The association between ambient coarse particulate matter (PM2.5-10) and mortality in MDR-TB patients has not yet been studied. The modifying effects of temperature and humidity on this association are completely unknown. This study aims to evaluate the effects of long-term PM2.5-10 exposures, and their modifications by temperature and humidity on mortality among MDR-TB patients. Methods: A Chinese cohort of 3,469 MDR-TB patients was followed up from diagnosis until death, loss to follow-up, or the study’s end, averaging 2,567 days per patient. PM2.5-10 concentrations were derived from the difference between PM10 and PM2.5. Cox proportional hazard models estimated hazard ratios (HRs) per 3.74 μg/m3 (IQR) exposure to PM2.5-10 and mortality for the full cohort and individuals at distinct long-term and short-term temperature and humidity levels, adjusting for other air pollutants and potential covariates. Exposure-response relationships were quantified using smoothed splines. Results: Hazard ratios of 1.733 (95% CI, 1.407, 2.135) and 1.427 (1.114, 1.827) were observed for mortality in association with PM2.5-10 exposures for the full cohort under long-term and short-term exposures to temperature and humidity. Modifying effects by temperature and humidity were heterogenous across sexes, age, treatment history, and environment. Nonlinear exposure-response curves suggested a cumulative risk of PM2.5-10-related mortality starting from a low exposure concentration around 15 μg/m3. Conclusion: Immediate surveillance of PM2.5-10 is crucial to mitigate the progression of MDR-TB severity due to co-exposures.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".