Virtual Prehabilitation in Patients With Cancer Undergoing Surgery During the COVID-19 Pandemic: Protocol for a Prospective Feasibility Study (Preprint)
Bibliographic record
Abstract
BACKGROUND Since the beginning of the COVID-19 pandemic, preoperative care, also termed prehabilitation, has become increasingly relevant due to the decreasing functional and psychosocial health of patients with cancer, which is a result of the pandemic restrictions. Concurrently, access to telehealth has improved; telehealth comprises all remote care delivery facilitated by information technologies (ie, virtually). OBJECTIVE The aim of this protocol is to describe the rationale and methodology for a major trial investigating the feasibility and safety of multimodal virtual prehabilitation services (ie, teleprehabilitation). METHODS This single-arm feasibility trial aims to recruit 100 patients with cancer to receive teleprehabilitation throughout their preoperative period. The inclusion criteria are as follows: (1) 18 years of age or older, (2) scheduled for elective cancer surgery and referred by a surgeon, (3) medically cleared by the referring physician to engage in physical activity, and (4) have a good comprehension of the English or French language. Feasibility will be assessed by documenting recruitment, adherence, and retention rates, in addition to patients’ motives for not participating in the trial, low participation, or discontinuation. The secondary outcome of safety will be assessed by reporting program-related adverse events. RESULTS The Montreal General Hospital Foundation funded the project in August 2020. The protocol was then approved by the Research Ethics Board of the McGill University Health Centre in January 2021 (ID No. 2021-6730). The first patient was recruited in March 2021, and recruitment is expected to end in September 2022. As of March 2022, 36 patients have been recruited, including 24 who have completed their participation. No adverse events have been reported. Data collection is expected to conclude in November 2022. Data analysis will be performed, and the results will be published by the beginning of 2023. CONCLUSIONS This trial will provide guidance on the use of telehealth in the administration of prehabilitation services. The trial will provide a large amount of information that will respond to gaps in the literature, as there are minimal reports on the use of telehealth rehabilitation and prehabilitation services among elderly populations and in acute contexts, such as the preoperative period. CLINICALTRIAL ClinicalTrials.gov NCT0479956; https://clinicaltrials.gov/ct2/show/NCT04799561 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/29936
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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 | 0.039 | 0.030 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.071 | 0.015 |
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".