The Frailty Phenotype and Palliative Care Needs of Older Survivors of Critical Illness
Bibliographic record
Abstract
OBJECTIVES: To assess symptoms in older intensive care unit (ICU) survivors and determine whether post-ICU frailty identifies those with the greatest palliative care needs. DESIGN: A prospective cohort study. SETTING: Urban tertiary care hospital and community hospital. PARTICIPANTS: Medical ICU survivors of mechanical ventilation aged 65 and older (N = 125). MEASUREMENTS: Baseline measurements of the Edmonton Symptom Assessment Scale (ESAS), categorized as mild (0-3), moderate (4-6), and severe (7-10), and the frailty phenotype were made during the week before hospital discharge. Functional recovery was defined as a return to a Katz activity of daily living dependency count less than or equal to the prehospitalization dependency count within 3 months. In the last 29 participants recruited, we made additional assessments of fatigue and ESAS both at baseline and 1 month after discharge. RESULTS: Fatigue was the most-prevalent moderate to severe symptom (74%), followed by dyspnea (53%), drowsiness (50%), poor appetite (47%), pain (45%), depression (42%), anxiety (36%), and nausea (17%). At 1-month follow-up, there were no significant differences in the proportions of participants with moderate to severe symptoms. Each increase in baseline ESAS fatigue severity category was associated with 55% lower odds of functional recovery (odds ratio = 0.45, 95% confidence interval = 0.24-0.84), independent of age, sex, comorbidities, and critical illness severity. Frail participants had a higher median baseline total ESAS symptom distress score (34, interquartile range (IQR) 23-44) than nonfrail participants (13, IQR 9-22) (P < .001). CONCLUSION: Older ICU survivors have a high burden of palliative care needs that persist 1 month after discharge. Fatigue is the most-prevalent symptom and may interfere with recovery. Post-ICU frailty may be a useful trigger for palliative care consultation and a treatment target.
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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 | 0.000 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".