Peri-Operative Wearables in Elder Recover after Surgery (POWERS) study: a protocol for a multicentre, prospective cohort study to evaluate perioperative activity with postoperative disability in older adults after non-cardiac surgery
Bibliographic record
Abstract
INTRODUCTION: The ageing population has led to an increasing proportion of surgical patients with greater frailty and comorbidity. Complications and mortality within 30 days of a surgical procedure are often used to evaluate success in the perioperative period however these measures can potentially underestimate a substantial level of morbidity associated with surgery. Personal wearable technologies are now readily available and can offer detailed information on activity intensity, sedentary behaviour and sleeping patterns. These devices may provide important information perioperatively by acting as a non-invasive, and cost-efficient means to risk stratify patients. METHODS AND ANALYSIS: The Peri-Operative Wearables in Elder Recover After Surgery (POWERS) study is a multicentre observational study of 200 older adults (≥65 years) having major elective non-cardiac surgery. The objectives are to characterise the association between preoperative and postoperative activity monitor measurements with postoperative disability and recovery, as well as characterise trajectories of activity and sleep in the perioperative period. Activity will be monitored with the ActiGraph GT3X device and measured for 7-day increments, preoperatively, and at 1 week, 1 month and 3 months postoperatively. Disability will be assessed using the WHO Disability Assessment Schedule 2.0 assessed at 1 week, 1 month and 3 months postoperatively. ETHICS AND DISSEMINATION: The POWERS study received research ethics board approval at all participating sites on 1 August 2019 (REB # 19-121 (CTO 1849)). Renewal was granted on 19 May 2022.
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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 | 0.020 | 0.015 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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".