Exercise intervention in cancer patients with sleep disturbances scheduled for elective surgery: Systematic review
Bibliographic record
Abstract
BACKGROUND & OBJECTIVES: Sleep disturbance is one of the patients' major complaints after major surgery and can impair postoperative recovery. Pre-operative exercise has been shown to increase functional capacity and resilience in cancer patients; scarce knowledge is available on the effects of pre-operative exercise on sleep disturbances. This systematic review aims to determine the impact of pre-operative exercise training alone or as part of multimodal prehabilitation on sleep disturbances and sleep quality in cancer patients. METHODS: A systematic search including Biosis, Cochrane Library and CENTRAL, EMBASE, MEDLINE, and clinical trial registries (clinicaltrials.gov, International Clinical Trials Registry Platform) was performed to identify studies involving a pre-operative exercise intervention in cancer patients awaiting surgery. Trials had to contain at least one sleep measure, assessed subjectively and objectively were included in the systematic review. The quality of the included trials was assessed using the Cochrane Risk of Bias Tool for assessing the risk of bias in randomized trials tool and the ROBINS-I tool for evaluating the risk of bias in non-randomized studies. RESULTS: Seven studies were included (1 RCT, 2 non-RCTs and 4 single-arm design). Due to substantial heterogeneity in the interventions across studies, a meta-analysis was not conducted. The available empirical evidence on the presurgical effect of exercise on sleep outcomes is scarce and, overall, suggests that it has a limited effect. Besides, non-significant improvement of the pre-operative exercise on sleep was unique to the studies that used subjective measures to assess sleep disturbances changes during cancer treatment. CONCLUSION: There are conflicting results and a lack of quality data proving the pre-operative exercise on sleep quality and disturbances. More research is needed in the pre-operative period using clinical sleep disturbances such as insomnia as an inclusion criterion, subjectively and objectively assessed.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".