Incident diuretic drug use and adverse respiratory events among older adults with chronic obstructive pulmonary disease
Bibliographic record
Abstract
AIMS: Diuretic drugs may theoretically improve respiratory health outcomes in chronic obstructive pulmonary disease (COPD) through several possible mechanisms, but they might also lead to respiratory harm. We evaluated the association of incident oral diuretic drug use with respiratory-related morbidity and mortality among older adults with COPD. METHODS: This was a population-based, retrospective cohort study using health administrative data from Ontario, Canada, for the period 2008-2013. We identified adults aged 66 years and older with nonpalliative COPD using a validated algorithm. Respiratory-related morbidity and mortality were evaluated within 30 days of incident oral diuretic drug use compared to nonuse using Cox proportional hazard regression and applying inverse probability of treatment weighting using the propensity score to minimize confounding. RESULTS: Out of 99 766 individuals aged 66 years and older with COPD identified, incident diuretic receipt occurred in 51.7%. Relative to controls, incident diuretic users had significantly increased rates for hospitalization for COPD or pneumonia [hazard ratio (HR) 1.22, 95% confidence interval (CI) 1.07-1.40], as well as more emergency room visits for COPD or pneumonia (HR 1.35, 95% CI 1.18-1.56), COPD or pneumonia-related mortality (HR 1.41; 95% CI 1.04-1.92) and all-cause mortality (HR 1.20, 95% CI 1.06-1.35). The increased respiratory-related morbidity and mortality observed were specifically as a result of loop diuretic use. CONCLUSIONS: Incident diuretic drugs, and more specifically loop diuretics, were associated with increased rates of respiratory-related morbidity and mortality among older adults with nonpalliative COPD. Further studies are needed to determine if this association is causative or due to unresolved confounding.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".