Optimizing functional exercise capacity in the elderly surgical population
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE OF REVIEW: There are several studies on the effect of exercise post surgery (rehabilitation), but few studies have looked at augmenting functional capacity prior to surgical admission (prehabilitation). A programme of prehabilitation is proposed in order to enhance functional exercise capacity in elderly patients with the intent to minimize the postoperative morbidity and accelerate postsurgical recovery. RECENT FINDINGS: Few studies have looked at exercise prehabilitation to improve functional capacity prior to surgical admission. Prehabilitation prior to orthopaedic surgery does not seem to improve quality of life or recovery. However, prehabilitation prior to abdominal or cardiac surgery, based on 275 elderly patients, results in fewer postoperative complications, shorter postoperative length of stay, improved quality of life, and reduced declines in functional disability compared to sedentary controls. SUMMARY: A concentrated 3-month progressive exercise prehabilitation programme consisting of aerobic training at 45-65% of maximal heart rate reserve (%HRR) along with periodic high-intensity interval training ( approximately 90% HRR) four times per week, 30-50 minutes per session, is recommended for improving cardiovascular functioning. A strength training programme of about 10 different exercises focused on large, multi-jointed muscle groups should also be implemented twice per week at a mean training intensity of 80% of one-repetition maximum. Finally, a minimum of 140 g ( approximately 560 kcal) of carbohydrate (CHO) should be taken 3 h before training to increase liver and muscle glycogen stores and a minimum of about 200 kcal of mixed protein-CHO should be ingested within 30 min following training to enhance muscle hypertrophy.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| 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 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it