The Association Between Frailty and Short-Term Outcomes in an Intensive Care Unit Rehabilitation Trial: An Exploratory Analysis
Bibliographic record
Abstract
BACKGROUND: Physical therapy initiated early in an ICU stay may reduce functional deficits in critically ill patients; however, the association of frailty with outcomes in those receiving early in-ICU rehabilitation is unknown. OBJECTIVE: To estimate the association between frailty and 3 outcomes in patients enrolled in an ICU randomized clinical trial (RCT). DESIGN: Exploratory secondary analyses of the CYCLE pilot RCT (NCT02377830). SETTING: 7 Canadian ICUs. PARTICIPANTS: Previously ambulatory critically ill adults. INTERVENTION: Participants were randomized to early in-bed cycling plus routine physiotherapy versus early routine physiotherapy alone. MEASUREMENTS: Using regression analyses, we modelled the association between pre-hospital Clinical Frailty Scale (CFS) scores, Physical Function in ICU Test-scored (PFIT-s), muscle strength, and mortality at hospital discharge, adjusting for illness severity (APACHE II) and the randomized intervention. We explored the influence of imputing mean PFIT-s and strength scores for decedents, and with listwise deletion of decedents in a sensitivity analysis. RESULTS: Of 66 patients, 2 had missing data, 2 had incomplete data, and 21 died by hospital discharge. At hospital discharge for 66 patients, frailty was not associated with PFIT-s (mean difference (MD) [95% CI]=0.20, [-2.08, 2.74]) or muscle strength (1.96, [-12.6, 16.6]). A sensitivity analysis yielded consistent results. Frailty was also not associated with hospital mortality (odds ratio 0.91, [0.28 to 2.93]). CONCLUSION: We found no association between pre-hospital frailty, physical function, strength, or mortality at hospital discharge in critically ill patients enrolled in an early rehabilitation trial. Larger sample sizes are needed to further explore the association of frailty with these outcomes at hospital discharge.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".