Access to myocardial revascularization procedures: Closing the gap with time?
Bibliographic record
Abstract
BACKGROUND: Early access to revascularization procedures is known to be related to a more favorable outcome in myocardial infarction (MI) patients, but access to specialized care varies widely amongst the population. We aim to test if the early gap found in the revascularization rates, according to distance between patients' location and the closest specialized cardiology center (SCC), remains on a long term basis. METHODS: We conducted a population-based cohort study using data from the Quebec's hospital discharge register (MED-ECHO). The study population includes all patients 25 years and older living in the province of Quebec, who were hospitalized for a MI in 1999 with a follow up time of one year after the index hospitalization. The main variable is revascularization (percutaneous transluminal coronary angioplasty or a coronary artery bypass graft). The population is divided in four groups depending how close they are from a SCC (< 32 km, 32-64 km, 64-105 km and > or = 105 km). Revascularization rates are adjusted for age and sex. RESULTS: The study population includes 11,802 individuals, 66% are men. The one-year incidence rate of MI is 244 individuals per 100,000 inhabitants. At index hospitalization, a significant gap is found between patients living close (< 32 km) to a SCC and patients living farther (> or = 32 km). During the first year, a gap reduction can be observed but only for patients living at an intermediate distance from the specialized center (64-105 km). CONCLUSION: The gap observed in revascularization rates at the index hospitalization for MI is in favour of patients living closer (< 32 km) to a SCC. This gap remains unchanged over the first year after an MI except for patients living between 64 and 105 km, where a closing of the gap can be noticed.
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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".