Is It Time to Update How Suspected Angina Is Evaluated prior to the Use of Specialized Tests? Implications Based on a Systematic Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: Appropriate use of specialized tests to assess chest pain is based classically on minimal information such as age, gender and the patient's description of pain. This approach has not been reevaluated in decades. We examined the relationship between history, examination and routine laboratory tests to identify factors warranting prospective validation as predictors of underlying coronary artery disease (CAD). METHODS: Studies linking obstructive CAD (≥50% diameter stenosis of at least one vessel by invasive angiography or cardiac computed tomographic angiography) and elements of history, examination and laboratory tests were identified. RESULTS: Forty-one prospectively identified papers were analyzed. Advanced age, gender and chest pain descriptors were extremely important, although the last was less so in women, in whom the presence of risk factors may be more important. Physical examination and chest X-ray were largely noncontributory. Laboratory tests were of variable utility other than to identify risk factors not already known from the history. However, biomarkers such as troponin, brain natriuretic factor and inflammatory markers were promising. The electrocardiogram was mainly important for the identification of ST-T abnormalities. CONCLUSIONS: This review identifies the most promising factors warranting prospective validation for improving the pretest probability estimation of CAD, so appropriate use criteria for the utilization of specialized diagnostic tests can be updated and improved.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.003 |
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 it