‘Choosing Wisely’ culture among Brazilian cardiologists
Bibliographic record
Abstract
OBJECTIVE: (i) To describe how aligned the 'Choosing Wisely' concept is with the medical culture among Brazilian cardiologists and (ii) to identify predictors for physicians' preference for avoiding wasteful care. DESIGN: Cross-sectional study. SETTING: Brazilian Society of Cardiology. PARTICIPANTS: Cardiologists who agree to fill a web questionary. INTERVENTION: A task force of 12 Brazilian cardiologists prepared a list of 13 'do not do' recommendations, which were made available on the Brazilian Society of Cardiology website for affiliates to assign a supported score of 1 to 10 to each recommendation. MAIN OUTCOME MEASUREMENT: Score average for supporting recommendations. RESULTS: Of 14 579 Brazilian cardiologists, 621 (4.3%) answered the questionnaire. The top recommendation was 'do not perform routine percutaneous coronary intervention in asymptomatic individuals' (mean score = 8.0 ± 2.9) while the one with the lowest support was 'do not use an intra-aortic balloon pump in infarction with cardiogenic shock' (5.8 ± 3.2). None of the 13 recommendations presented a mean grade >9 (strong support); 7 recommendations averaged 7-8 (moderate support) followed by 6 recommendations with an average of 5-7 (modest support). Multivariate analysis independently identified predictors of the score attributed to the top recommendation; being an interventionist and time since graduation were both negatively associated with support. CONCLUSIONS: (i) The support of Brazilian cardiologists for the 'Choosing Wisely' concept is modest to moderate, and (ii) older generations and enthusiasm towards the procedure one performs may be factors against the 'Choosing Wisely' philosophy.
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".