The influence of general health status and social support on symptomatic outcome following coronary artery bypass grafting
Bibliographic record
Abstract
OBJECTIVES: To assess health status, level of social support, and presence of coronary artery disease risk factors before and after coronary artery bypass grafting (CABG); to assess symptomatic relief approximately 12 months postoperatively; and to examine the association between preoperative health status and recurrence of symptoms. DESIGN: Observational study. SETTING: Preoperatively, in hospital outpatient department (1995-1996); postoperatively, at home (1996-97). SUBJECTS AND METHODS: Patients awaiting elective CABG were recruited one month before the expected date of operation. Preoperative assessment included severity of symptoms, coronary artery disease risk factors, short form 36 (SF-36) questionnaire, and social activities questionnaire. The presence and severity of angina and breathlessness were reported postoperatively (mean 16.4 months). Multiple regression analysis was used to identify factors associated with improved outcome following CABG. MAIN OUTCOME MEASURE: Patient reported presence and severity of angina and breathlessness. RESULTS: 183 patients were followed for a mean of 16. 4 months after CABG. Angina and breathlessness were completely relieved in 55% and 36% of patients, respectively. In patients with residual symptoms, the severity was significantly reduced (angina p < 0.001; breathlessness, p = 0.02). Patients with low SF-36 scores and low social network scores preoperatively were less likely to be relieved of symptoms (p < 0.001). Health status and social support levels preoperatively were lower than in other reported coronary artery disease patients groups. Preoperatively, coronary artery disease risk factors were higher than recommended in current guidelines: 67.4% had raised plasma cholesterol, 39.0% were hypertensive, 80% were moderately obese, and 22.9% were smokers. CONCLUSIONS: Recurrence of symptoms exceeded other published studies. Patients' perception of general health, symptoms, and social support influences outcome.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".