Impact of preoperative physical activity and depressive symptoms on post-cardiac surgical outcomes
Bibliographic record
Abstract
OBJECTIVE: To determine the independent and combined impact of preoperative physical activity and depressive symptoms with hospital length of stay (HLOS), and postoperative re-hospitalization and mortality in cardiac surgery patients. METHODS: A cohort study including 405 elective and in-house urgent cardiac surgery patients were analyzed preoperatively. Physical activity was assessed with the International Physical Activity Questionnaire to categorize patients as active and inactive. The Patient Health Questionnaire-9 was used to evaluate preoperative depressive symptoms and categorize patients as depressed and not depressed. Patients were separated into four groups: 1) Not depressed/active (n = 209), 2) Depressed/active (n = 48), 3) Not depressed/inactive (n = 101), and 4) Depressed/inactive (n = 47). Administrative data captured re-hospitalization and mortality data, and were combined into a composite endpoint. Models adjusted for demographics, comorbidities, and cardiac surgery type. Multiple imputation was used to impute missing values. RESULTS: Preoperative physical activity behavior and depression were not associated with HLOS examined in isolation or when analyzed by the physical activity/depressive symptom groups. Physical inactivity (HR: 1.60, 95% CI 1.05 to 2.42; p = 0.03), but not depressive symptoms, was independently associated with the composite outcome. Freedom from the composite outcome were 76.1%, 87.5%, 68.0%, and 61.7% in the Not depressed/active, Depressed/active, Not depressed/inactive, and Depressed/inactive groups, respectively (P = 0.02). The Active/Depressed group had a lower risk of the composite outcome (HR: 0.35 95% CI 0.14 to 0.89; p = 0.03) compared to the other physical activity/depression groups. CONCLUSION: Preoperative physical activity appears to be more important than depressive symptoms on short-term postoperative re-hospitalization and mortality.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".