The impact of socioeconomic and demographic factors on the utilization of smoking cessation medications in patients hospitalized with cardiovascular disease in Nova Scotia, Canada
Bibliographic record
Abstract
OBJECTIVE: To determine whether any demographic or socioeconomic factors affect the use of smoking cessation medications in patients hospitalized with heart disease. METHOD: Data were obtained from the Improving Cardiovascular Outcomes in Nova Scotia (ICONS) Canada database, which includes a registry of all hospitalized patients with a diagnosis of ischaemic heart disease, congestive heart failure, or atrial fibrillation since October 1997. Patients agreeing to provide follow-up were sent an enrollment survey to determine demographic and socioeconomic factors including household income, educational background and private drug insurance plans. RESULTS: Between 15 October 1997 and 31 December 2000, 5442 patients who were current smokers and 270 patients using a smoking cessation medication were admitted to hospital registered in the ICONS database. An enrollment survey was completed by 1071 current smokers and 77 patients using a smoking cessation agent. CONCLUSION: Higher education level, presence of private drug insurance plans, and less difficulty paying for basic needs were associated with higher use of smoking cessation medications.
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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 | 0.003 |
| 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 | 0.000 |
| 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".