Assessment and predictors of physical functioning post-hospital discharge in survivors of critical illness
Bibliographic record
Abstract
BACKGROUND: Prior studies of physical functioning after critical illness have been mostly limited to survivors of acute respiratory distress syndrome. The purpose of this study was to objectively assess muscle strength and physical functioning in survivors of critical illness from a general ICU and the associations of these measures to health-related quality of life (HRQL), mental health and critical illness variables. METHODS: This was a prospective cohort study of 56 patients admitted to a medical ICU (length of stay ≥4 days) from April 1, 2009, and March 31, 2010. Patients were assessed in clinic at 3 months post-hospital discharge. Muscle strength and physical functioning were measured using hand-held dynamometry and the 6-min walk test. HRQL was assessed using the short-form 36 (SF-36) and EuroQol-5D (EQ-5D) questionnaires. RESULTS: Three months post-hospital discharge, median age- and sex-matched muscle strength was reduced across all muscle groups. The median 6-min walk distance was 72 % of predicted. Physical functioning was associated with reductions in self-reported HRQL (SF-36, EQ-5D) and increased anxiety. Univariate regression modeling showed that reduced muscle strength and 6-min walk distance were associated with sepsis but not ICU length of stay. Multivariate regression modeling showed that sepsis and corticosteroid use were associated with a reduced 6-min walk distance, but again ICU length of stay was not. CONCLUSIONS: Survivors of critical illness have reduced strength in multiple muscle groups and impaired exercise tolerance impacting both HRQL and mental health. These outcomes were worsened by sepsis and corticosteroid use in the ICU but not ICU length of stay. Interventions to minimizing the burden of sepsis in critically ill patients may improve long-term 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".