Functional testing after percutaneous transluminal coronary angioplasty in Canada and the United States: a survey of practice patterns.
Bibliographic record
Abstract
BACKGROUND: Authorities recommend various strategies to identify restenosis in patients who have undergone percutaneous transluminal coronary angioplasty (PTCA). Some authorities recommend a routine functional testing strategy, while others recommend a clinically driven strategy. MATERIALS AND METHODS: To examine the patterns of use of post-PTCA functional testing, 89 directors of cardiac catheterization laboratories in Canada and the United States were surveyed. RESULTS: Demographic characteristics of the Canadian and American respondents were similar, including median age (43 and 45 years, respectively) and median number of PTCAs performed each year (200 each). Canadians were more likely to employ a routine functional testing strategy than Americans (62% versus 38%), while Americans were more likely to employ stress imaging studies than Canadians (49% versus 35%). Overall, close to half (44%) of all the cardiologists employed a routine functional testing strategy. Physicians who employed a routine functional testing strategy performed the first functional test a median of three months after PTCA and the second a median of six months after PTCA. Both Canadian and American cardiologists tended to underestimate the incidence of restenosis after PTCA (33% without a stent and 18% with a stent) and to overestimate the sensitivity of exercise treadmill testing for the detection of restenosis (63%). CONCLUSIONS: The use of functional testing after PTCA varies widely. Canadian cardiologists are more likely to employ a routine functional testing strategy than American cardiologists. Close to half of the cardiologists surveyed employed a routine functional testing strategy. These results indicate that there is little consensus regarding the use of functional testing after PTCA.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".