Association Between Symptoms of Chronic Psychological Distress and Myocardial Ischemia Induced by Mental Stress in Patients With Coronary Artery Disease
Bibliographic record
Abstract
Background Mental stress-induced myocardial ischemia is a frequent phenomenon in patients with coronary artery disease and is associated with a greater risk of future cardiovascular events. The association between chronic symptoms of psychological distress and mental stress-induced ischemia is not clear. Methods and Results We used a composite score of psychological distress derived from symptoms of depression, posttraumatic stress disorder, anxiety, anger, and perceived general stress. Participants underwent myocardial perfusion imaging with both mental (public speaking task) and conventional (exercise or pharmacological) stress testing. Overall, 142 (15.9%) patients experienced mental stress-induced myocardial ischemia. After adjusting for demographic factors, medical history, and medication use, patients in the highest tertile of psychological distress score had 35% higher odds of having mental stress-induced ischemia compared to those in the lowest tertile (odds ratio [OR], 1.35 [95% CI, 1.06-2.22]). Stratified analyses showed that the association between psychological distress score and mental stress-induced myocardial ischemia was significantly associated only within the subgroup of patients with a prior myocardial infraction, with patients with a prior myocardial infarction in the highest tertile having a 93% higher odds of developing myocardial ischemia with mental stress (95% CI, 1.07-3.60). There was no significant association between psychological distress and conventional stress-induced ischemia (OR, 1.19 [95% CI, 0.87-1.63]). Conclusions Among patients with a history of myocardial infarction, a higher level of psychosocial distress is associated with mental stress-induced myocardial ischemia but not with ischemia induced by a conventional stress test.
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 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".