Negative association between resting blood pressure and chest pain in people undergoing exercise stress testing for coronary artery disease
Bibliographic record
Abstract
Sustained and acute increases in blood pressure can dampen pain in experimental animals and humans. The most important clinical implication of this relationship may be the phenomenon of silent cardiac ischemia. High blood pressure is common in people at risk for cardiac ischemia and may reduce angina, the key symptom of life-threatening ischemia. The relationship between resting blood pressure and angina was examined in 904 people undergoing exercise stress testing for coronary artery disease. The presence or absence of ischemia was documented with single photon emission computed tomography (SPECT). Participants with ischemia had higher scores on the McGill Pain Questionnaire (MPQ) following exercise though this was moderated significantly by diastolic blood pressure (DBP), especially in women. People with higher pre-exercise resting DBP who displayed SPECT-diagnosed ischemia had MPQ scores comparable to people who did not display ischemia, independent of age, exercise duration, medication, and cardiac history. Awareness of the potential association between blood pressure and angina may provide patients with coronary artery disease and their physicians' important guidance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.002 | 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".