Return to work after coronary artery bypass surgery
Bibliographic record
Abstract
The aim of this study was to assess the possible reasons for not returning to work after coronary artery bypass surgery. A total of 134 patients (aged 65 years and younger) who underwent coronary bypass surgery in 2003 were examined. The analysis was performed in three groups of the patients: Group I, patients who were employed before surgery and returned to work after it (n=51); Group II, patients who were employed before surgery but did not return to work after surgery (n=55); and Group III, patients who were unemployed before and remained unemployed after surgery due to health problems (n=28). Number of injured coronary arteries, the extent of operation, postoperative complications, risk factors for ischemic heart disease, clinical status of patients (angina pain and heart failure), physical tolerance, and return to work within one year after coronary bypass surgery were analyzed. It was found that 48.1% of patients who were employed before surgery returned to work after myocardial revascularization. About 30% of patients experienced recurrent symptoms of angina after 12 months. Logistic regression analysis revealed that return to work was significantly influenced by female gender, physical pattern of work, age, and severity of heart failure.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".