Do acute changes in ambient air pollution increase the risk of potentially fatal cardiac arrhythmias in patients with implantable cardioverter defibrillators?
Bibliographic record
Abstract
Abstract Background Daily changes in ambient air pollution have been associated with cardiac morbidity and mortality. Precipitating a cardiac arrhythmia in susceptible individuals may be one mechanism. We investigated the influence of daily changes in air pollution in the Province of Ontario, Canada on the frequency of discharges from implantable cardio defibrillators (ICDs) which occur in response to potentially life threatening arrhythmias. Methods Using a case- crossover design, we compared ambient air pollution concentrations on the day of an ICD discharge to other days in the same month and year in 1952 patients. We adjusted for weather, lagged the exposure data from 0 to 3 days, and stratified the results by several patient-related characteristics. Results Median (interquartile range) for ozone (O3), fine particulate matter (PM2.5), sulphur dioxide (SO2) and nitrogen dioxide (NO2) were 26.0 ppb (19.4, 33.0), 6.6 μg/m3 (4.3, 10.6), 1.00 ppb (0.4,2.1), 10.0 ppb (6.0,15.3) respectively. Unlagged odds ratios (95%) for an ICD discharge associated with an interquartile range increase in pollutant were 0.97 (0.86, 1.09) for O3, 0.99 (0.92, 1.06) for PM2.5, 0.97 (0.91, 1.03) for SO2, and 1.00 (0.89, 1.12) for NO2. Conclusion We found no evidence that the concentrations of ambient air pollution observed in our study were a risk factor for potentially fatal cardiac arrhythmias in patients with ICDs.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".