Functional capacity of prediabetic patients: effect of multimodal prehabilitation in patients undergoing colorectal cancer resection
Bibliographic record
Abstract
Background Prehabilitation is the process of increasing functional capacity (FC) before surgery. Poor glycemic control is associated with worse outcomes in patients undergoing surgery. Therefore, prediabetic patients could particularly benefit from prehabilitation.Methods This is a pooled analysis of individual patient data from three multimodal prehabilitation trials in colorectal cancer surgery. Following a baseline assessment using the 6-minute walking test (6MWT), subjects were randomized to multimodal prehabilitation or to a control group. Participants were reassessed 24 h before surgery and 4 weeks after surgery. Prediabetes (PreDM) was defined as HbA1c 5.7%–6.4%. Multivariable logistic regression was used to adjust for potentially confounding variables.Results Participation in a prehabilitation program was the most important predictive factor of clinical improvement in FC prior to surgery (Adjusted OR 2.42, 95% CI 1.18, 4.94); prediabetes was not a statistically significant predictor of improvement in FC after adjustments for covariates. Prehabilitation attenuated the loss of FC in unadjusted analyses after surgery in prediabetic patients (PreDM Control: median change −6 m [IQR −50–20] vs PreDM Prehab: median change +25 m [IQR −20–53], p = 0.045). Adjusted analyses also suggested the protective effect against loss of FC after surgery was stronger in prediabetic patients (PreDM Prehab vs PreDM Control: OR 5.5, 95% CI: 1.2–25.8; Normo Prehab vs Normo Control: OR 1.5, 95% CI: 0.53–4.52).Conclusions Multimodal prehabilitation favored clinical recovery of FC after surgery in CRC patients, especially prediabetic patients.
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How this classification was reachedexpand
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 | 0.001 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".