Multicentre pilot randomised clinical trial of early in-bed cycle ergometry with ventilated patients
Bibliographic record
Abstract
Introduction: Acute rehabilitation in critically ill patients can improve post-intensive care unit (post-ICU) physical function. In-bed cycling early in a patient's ICU stay is a promising intervention. The objective of this study was to determine the feasibility of recruitment, intervention delivery and retention in a multi centre randomised clinical trial (RCT) of early in-bed cycling with mechanically ventilated (MV) patients. Methods: We conducted a pilot RCT conducted in seven Canadian medical-surgical ICUs. We enrolled adults who could ambulate independently before ICU admission, within the first 4 days of invasive MV and first 7 days of ICU admission. Following informed consent, patients underwent concealed randomisation to either 30 min/day of in-bed cycling and routine physiotherapy (Cycling) or routine physiotherapy alone (Routine) for 5 days/week, until ICU discharge. Our feasibility outcome targets included: accrual of 1-2 patients/month/site; >80% cycling protocol delivery; >80% outcomes measured and >80% blinded outcome measures at hospital discharge. We report ascertainment rates for our primary outcome for the main trial (Physical Function ICU Test-scored (PFIT-s) at hospital discharge). Results: Between 3/2015 and 6/2016, we randomised 66 patients (36 Cycling, 30 Routine). Our consent rate was 84.6 % (66/78). Patient accrual was (mean (SD)) 1.1 (0.3) patients/month/site. Cycling occurred in 79.3% (146/184) of eligible sessions, with a median (IQR) session duration of 30.5 (30.0, 30.7) min. We recorded 43 (97.7%) PFIT-s scores at hospital discharge and 37 (86.0%) of these assessments were blinded. Discussion: Our pilot RCT suggests that a future multicentre RCT of early in-bed cycling for MV patients in the ICU is feasible. Trial registration number: NCT02377830.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".