Sarcopenia is associated with postoperative infection and delayed recovery from colorectal cancer resection surgery
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Bibliographic record
Abstract
BACKGROUND: Skeletal muscle depletion (sarcopenia) predicts morbidity and mortality in the elderly and cancer patients. METHODS: We tested whether sarcopenia predicts primary colorectal cancer resection outcomes in stage II-IV patients (n=234). Sarcopenia was assessed using preoperative computed tomography images. Administrative hospitalisation data encompassing the index surgical admission, direct transfers for inpatient rehabilitation care and hospital re-admissions within 30 days was searched for International Classification of Disease (ICD)-10 codes for postoperative infections and inpatient rehabilitation care and used to calculate length of stay (LOS). RESULTS: Overall, 38.9% were sarcopenic; 16.7% had an infection and 9.0% had inpatient rehabilitation care. Length of stay was longer for sarcopenic patients overall (15.9 ± 14.2 days vs 12.3 ± 9.8 days, P=0.038) and especially in those ≥ 65 years (20.2 ± 16.9 days vs 13.1 ± 8.3 days, P=0.008). Infection risk was greater for sarcopenic patients overall (23.7% vs 12.5%; P=0.025), and especially those ≥ 65 years (29.6% vs 8.8%, P=0.005). Most (90%) inpatient rehabilitation care was in patients ≥ 65 years. Inpatient rehabilitation was more common in sarcopenic patients overall (14.3% vs 5.6%; P=0.024) and those ≥ 65 years (24.1% vs 10.7%, P=0.06). In a multivariate model in patients ≥ 65 years, sarcopenia was an independent predictor of both infection (odds ratio (OR) 4.6, (95% confidence interval (CI) 1.5, 13.9) P<0.01) and rehabilitation care (OR 3.1 (95% CI 1.04, 9.4) P<0.04). CONCLUSION: Sarcopenia predicts postoperative infections, inpatient rehabilitation care and consequently a longer LOS.
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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 | 0.000 | 0.000 |
| 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 it