Long-Term Association Between Frailty and Health-Related Quality of Life Among Survivors of Critical Illness
Bibliographic record
Abstract
OBJECTIVE: Frailty is a multidimensional syndrome characterized by loss of physiologic reserve that gives rise to vulnerability to poor outcomes. We aimed to examine the association between frailty and long-term health-related quality of life among survivors of critical illness. DESIGN: Prospective multicenter observational cohort study. SETTING: ICUs in six hospitals from across Alberta, Canada. PATIENTS: Four hundred twenty-one critically ill patients who were 50 years or older. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Frailty was operationalized by a score of more than 4 on the Clinical Frailty Scale. Health-related quality of life was measured by the EuroQol Health Questionnaire and Short-Form 12 Physical and Mental Component Scores at 6 and 12 months. Multiple logistic and linear regression with generalized estimating equations was used to explore the association between frailty and health-related quality of life. In total, frailty was diagnosed in 33% (95% CI, 28-38). Frail patients were older, had more comorbidities, and higher illness severity. EuroQol-visual analogue scale scores were lower for frail compared with not frail patients at 6 months (52.2 ± 22.5 vs 64.6 ± 19.4; p < 0.001) and 12 months (54.4 ± 23.1 vs 68.0 ± 17.8; p < 0.001). Frail patients reported greater problems with mobility (71% vs 45%; odds ratio, 3.1 [1.6-6.1]; p = 0.001), self-care (49% vs 15%; odds ratio, 5.8 [2.9-11.7]; p < 0.001), usual activities (80% vs 52%; odds ratio, 3.9 [1.8-8.2]; p < 0.001), pain/discomfort (68% vs 47%; odds ratio, 2.0 [1.1-3.8]; p = 0.03), and anxiety/depression (51% vs 27%; odds ratio, 2.8 [1.5-5.3]; p = 0.001) compared with not frail patients. Frail patients described lower health-related quality of life on both physical component score (34.7 ± 7.8 vs 37.8 ± 6.7; p = 0.012) and mental component score (33.8 ± 7.0 vs 38.6 ± 7.7; p < 0.001) at 12 months. CONCLUSIONS: Frail survivors of critical illness experienced greater impairment in health-related quality of life, functional dependence, and disability compared with those not frail. The systematic assessment of frailty may assist in better informing patients and families on the complexities of survivorship and recovery.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".