Prehabilitation Before Gastrointestinal Cancer Surgery: Protocol for an Implementation Study
Bibliographic record
Abstract
BACKGROUND: Surgery remains the standard curative treatment for early-stage colorectal and upper gastrointestinal cancer. Reduced preoperative functional capacity, nutritional status, and psychological well-being are associated with poor postoperative outcomes. Prehabilitation aims to improve preoperative functional reserves through physical, nutritional, and psychological interventions. Yet, how it transitions from a trial setting to being integrated into a real-world health setting is unknown. OBJECTIVE: The primary aim is to evaluate the implementation of a multimodal (supervised exercise, nutrition, and nursing support) prehabilitation program into standard care for patients with gastrointestinal cancer (colorectal and upper gastrointestinal cancer) scheduled for curative intent surgery. The secondary aim is to determine the impact of a multimodal prehabilitation program on functional capacity, nutritional and psychological status, and surgical outcomes. METHODS: This is an implementation study that will investigate a multimodal prehabilitation intervention, in a nonblinded, nonrandomized, single-group, pre-post design. Patients diagnosed with colorectal and upper gastrointestinal cancer scheduled for potentially curative intent surgery at Concord Repatriation General Hospital, with ≥14 intervention days prior to surgery and are medically cleared to exercise will be eligible. The study will be evaluated using the Reach, Effectiveness, Adoption, Implementation, and Maintenance Evaluation Framework. RESULTS: The protocol was approved in December 2019 by the Concord Repatriation General Hospital Human Research Ethics Committee (reference number 2019/PID13679). Recruitment commenced in January 2020. In response to the COVID-19 pandemic, recruitment was paused in March 2020 and reopened in August 2020 with remote or telehealth intervention adaptations. Recruitment ended on December 31, 2021. Over the 16-month recruitment period, a total of 77 participants were recruited. CONCLUSIONS: Prehabilitation represents an opportunity to maximize functional capacity and improve surgical outcomes. The study will provide guidance and contribute to the evidence on the integration of prehabilitation into standard care using adaptive models of health care delivery including telehealth. TRIAL REGISTRATION: Australian and New Zealand Clinical Trials Registry ACTR 12620000409976; https://anzctr.org.au/Trial/Registration/TrialReview.aspx?id=378974&isReview=true. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/41101.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".