Quality of Care of International and Canadian Medical Graduates in Acute Myocardial Infarction
Bibliographic record
Abstract
BACKGROUND: International medical graduates (IMGs) make up a substantial proportion of the physician workforce and play an important role in the care of patients with acute myocardial infarction (AMI). There are concerns that IMGs may provide inferior medical care compared with locally trained medical graduates, but that has not been established. METHODS: We performed a retrospective cohort study of linked administrative databases containing health care claims of physicians' service payments, hospital discharge abstracts, and patients' vital status. We included 127,275 AMI patients admitted between April 1, 1992, and March 31, 2000, to acute care hospitals in Ontario. We then compared the risk-adjusted mortality rates and adjusted use of secondary prevention medications and cardiac invasive procedures in patients treated by IMGs vs Canadian medical graduates. RESULTS: Of the 127,275 admitted AMI patients, 28,061 (22.0%) were treated by IMGs and 99,214 (78.0%) by Canadian medical graduates. The risk-adjusted mortality rates of IMG- and Canadian medical graduate-treated patients were not significantly different at 30 days (13.3% vs 13.4%, P = .57) and at 1 year (21.8% vs 21.9%, P = .63). Furthermore, AMI patients treated by both groups had similar adjusted likelihood of receiving secondary prevention medications at 90 days and cardiac invasive procedures at 1 year. CONCLUSIONS: The use of secondary prevention medications and cardiac procedures and the mortality of AMI patients were similar, regardless of the origin of medical education of the admitting physician. This information places the care provided by IMGs into perspective and supports the ability of well-selected IMGs in caring for AMI patients.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".