Muscular Tenderness in the Anterior Chest Wall in Patients With Stable Angina Pectoris is Associated With Normal Myocardial Perfusion
Bibliographic record
Abstract
OBJECTIVE: This study examines the relationship between the existence of chest wall tenderness evoked by palpation and the absence of ischemic heart disease defined by myocardial perfusion imaging in patients with known or suspected stable angina pectoris. METHODS: Two hundred seventy-five patients were recruited. Myocardial perfusion imaging was performed on 273 of the subjects. Chest pain was classified according to type by criteria given by the Danish Society of Cardiology and severity by the Canadian Cardiovascular Society. Pectoralis major and pectoralis minor were palpated for tenderness using a standardized procedure. RESULTS: The association between tenderness and myocardial perfusion imaging (normal vs abnormal) produced an odds ratio (OR) of 2.24 (confidence interval, 1.26-3.99; P = .009). The OR was the same magnitude and significance when stratified by sex, age, type of pain, or class. When adjusting simultaneously for sex, age, type of pain, and class, the association between tenderness and myocardial perfusion imaging (normal vs abnormal) was still present (OR = 2.57; confidence interval, 1.342-4.902; P = .004). CONCLUSION: Presence of tenderness in the anterior chest wall is associated with a higher prevalence of normal myocardial perfusion imaging in patients with known or suspected angina pectoris, and this association cannot be explained by a common association to age, sex, or pain.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".