ICES Report: Do Ontario Patients with Heart Failure Have Equal Access to Life-Saving Technology?
Bibliographic record
Abstract
Sudden cardiac death (SCD) is a major cause of mortality, and many such events are due to lethal heart rhythm disturbances or ventricular arrhythmias. Patients with a prior heart attack and left ventricular dysfunction are at particularly high risk of SCD. Although the majority of drug therapies have been ineffective in preventing sudden cardiac death, the implantable cardioverter defibrillator (ICD) – a device similar in size to a pacemaker that allows for heart monitoring and immediate cardiac shock if necessary – has been found to significantly reduce the chance of mortality and arrhythmic death in those at increased risk of cardiac events. Randomized trials of the ICD found that it substantially improved outcome in cardiac arrest survivors. The ICD was also found to offer significant survival benefits when used for primary prevention (i.e., in heart failure patients with no history of a cardiac arrest). The recommendations for ICDs were, therefore broadened to include those who have never had a cardiac arrest, but had reduced cardiac pump function and prior heart attack or heart failure. However, there may be disparities in access to this technology because of its novelty and high cost (approximately $30,000 per device). To better explore possible inequities in the use of implantable defibrillators in a universal healthcare environment, scientists at the Institute for Clinical Evaluative Sciences (ICES) examined the use of such procedures for the primary prevention of sudden cardiac death in Ontario from 1993 to 2004. The Study Using the Canadian Institute for Health Information Discharge
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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".