The PREPARE Study: Acceptability and Feasibility of a Telehealth Trimodal Prehabilitation Program for Women with Endometrial Neoplasia
Bibliographic record
Abstract
Patients with endometrial neoplasia (EN) often have multiple comorbidities and a higher surgical risk. Prehabilitation programs (PPs) combine various interventions to improve preoperative conditions and reduce impairment due to surgical stress. We conducted a pragmatic pilot study to evaluate the acceptability and feasibility of a trimodal telehealth PP (exercise, nutrition, and psychological support) for EN patients. The participants could select their exercise group: (1) a supervised PP (SPP), group sessions 3×/week; (2) a semi-supervised PP (SSPP), group session 1×/week, training alone 2×/week; or (3) a physical activity counseling session (PACS). Out of the 150 EN patients awaiting surgery screened during the 18 months of the study recruitment, 66% (99/150) were eligible, and 40% consented to participate (SPP, n = 13; SSPP, n = 17; PACS, n = 9). The overall dropout was low (13%; 5/39), with no significant differences across groups. No serious adverse events occurred. We observed a positive impact on different outcomes across the different groups, such as in the Functional Assessment of Cancer Therapy quality of life score (SPP; delta = 6.1 [CI: 0.9; 12.6]) and functional capacity measured using the 30″ sit-to-stand test (PACS delta = 2.4 [CI: 1.2; 3.6]). The same-day hospital leave was high in the SSPP group (54.5%). Our pilot telehealth PP seems to be safe, feasible, and well accepted and may procure clinical and patient-centered gains that need to be confirmed in a larger trial.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".