The Efficacy and Safety of In–Intensive Care Unit Leg-Cycle Ergometry in Critically Ill Adults. A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Abstract Background Survivors of critical illness may experience physical-function deficits after intensive care unit (ICU) discharge. In-ICU cycle ergometry may facilitate early mobilization and decrease functional impairment. Objective We conducted a systematic review and meta-analysis to understand the effect of in-ICU leg-cycle ergometry on patient-important and clinically relevant outcomes. Data Sources We searched eight electronic databases from inception until July 2019. Data Extraction We included randomized controlled trials (RCTs) and nonrandomized studies of critically ill adults admitted to the ICU for ≥24 hours, comparing cycling interventions to control arms that did not receive cycling. Main outcomes included physical function, mechanical ventilation (MV) duration, length of stay (LOS), quality of life (QoL), mortality, and safety. We conducted independent duplicate-citation screening, data abstraction, and risk-of-bias assessments. We pooled RCTs using a random-effects model and calculated the risk ratio (RR), mean difference (MD), or standardized MD with 95% confidence intervals (CIs). We assessed certainty of outcomes using the Grading of Recommendations Assessment, Development, and Evaluation approach. Results Of 6,531 citations, we included 12 RCTs and 2 nonrandomized studies (n = 926). Between the cycling and control groups, there were no differences in physical function at hospital discharge (3 RCTs; n = 225; standardized MD, 0.07 [95% CI, −0.38 to 0.53]; very low certainty), MV duration (9 RCTs; n = 676; MD, 0.01 [−1.04 to 1.07] days; moderate certainty), ICU LOS (10 RCTs; n = 511; MD, 0.23 [−1.44 to 1.89] days; moderate certainty), hospital LOS (7 RCTs; n = 393, MD −0.07 [−3.87 to 3.73] days; moderate certainty), QoL at 6 months after hospital discharge (2 RCTs; n = 103; MD, 9.13 [13.80 to 32.05] points higher; very low certainty), or hospital mortality (7 RCTs; n = 710; RR 1.09 [0.82 to 1.46]; moderate-certainty). The adverse event rate in cycling sessions was 0.16% across studies (10 studies; 5 of 3,117 sessions; very low certainty). Conclusions Cycling initiated in the ICU is probably safe; however, we did not find any differences in physical function, MV duration, LOS, QoL, or mortality compared with those not receiving cycling. Rigorously designed RCTs are needed to improve precision and further investigate the effect of cycling on patient-important outcomes.
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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 | 0.015 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.022 | 0.034 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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; 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".