Quality of the reporting of exercise interventions in solid organ transplant recipients: a systematic review
Bibliographic record
Abstract
Background:Exercise training programs must be described in detail to facilitate replication and implementation. This study aimed to evaluate the quality of exercise training program description in randomized controlled trials (RCTs) involving solid organ transplant (SOT) recipients. Methods: We evaluated 21 RCTs reporting on exercise interventions in SOT recipients that were included in a recent systematic review/meta-analysis conducted by the research team. This previous review investigated the effects of exercise training (versus no training) in adult SOT recipients. Several databases (MEDLINE, EMBASE, CINAHL, and Cochrane Central Register of Controlled Trials) were searched from inception to May 2019. Three reviewers independently rated the exercise programs for SOT using the Consensus on Exercise Reporting Template (CERT). Results: Mean score of the CERT was 6/19. None of the RCTs described all items of the CERT. Items of crucial importance, such as adherence, whether the exercise was done individually or in a group, whether there were home program or non-exercise components, and the type and number of adverse events, were either not mentioned or not described in detail. Conclusion: RCTs in exercise in SOT recipients did not satisfactorily report their exercise protocols, which can lead to difficulties in replication by researchers and implementation by clinicians.
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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 | 0.229 | 0.605 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.010 |
| Bibliometrics | 0.012 | 0.015 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".