Inequitable distribution of implantable cardioverter defibrillators in Ontario
Bibliographic record
Abstract
OBJECTIVES: Implantable cardioverter defibrillator (ICD) therapy reduces the risk of sudden death in patients with ischemic cardiomyopathy, but their novelty and cost may represent barriers to utilization. The objective of this study was to examine the influence of age, gender, place of residence, and socioeconomic status on rates of ICD implantation for the primary prevention of death. METHODS: We conducted a population-based retrospective cohort study involving the entire province of Ontario, Canada. Patients were eligible if they had survived following hospitalization for heart failure from 1 January 1993, to 31 March 2004, and previously sustained an acute coronary syndrome within 5 years. Patients with an existing ICD or a documented history of cardiac arrest were excluded, as were patients who died in the hospital. Primary outcome was ICD implantation. RESULTS: We identified 48,426 patients hospitalized for heart failure who survived to hospital discharge. Of these, 440 received an ICD, with a gradual 30-fold increase in implantation rates over the study period (.12-3.9 percent). ICD recipients were more likely to be men (odds ratio [OR]=4.14; 95 percent confidence interval [CI], 3.24-5.30), younger than 75 years of age (OR=3.19; 95 percent CI, 2.57-3.96), reside in a metropolitan area (OR=1.42; 95 percent CI, 1.04-1.9), and live in a higher socioeconomic neighborhood (OR=1.32; 95 percent CI, 1.08-1.61). CONCLUSIONS: Among patients with heart failure and a previous myocardial infarction, ICD use is increasing in Ontario. However, the application of this technology is characterized by major sociodemographic inequities. The causes and consequences of the pronounced age and gender discrepancies, in particular, warrant further investigation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".