The role of frailty in outcomes from critical illness
Bibliographic record
Abstract
PURPOSE OF REVIEW: Frailty is a multidimensional syndrome characterized by loss of physiologic reserves that gives rise to vulnerability to adverse events. RECENT FINDINGS: Frailty has been described in older patients undergoing geriatric assessment and in noncardiac and cardiac surgical settings, in which it closely correlates with heightened risk for major morbidity including functional decline, postoperative complications, institutionalization, and short-term and long-term mortality. Critically ill patients may represent a population with similar vulnerabilities to older frail patients. Prior data have described the association with less favorable outcomes and poor premorbid functional status (i.e., activities of daily living, cognitive impairment, body mass index), used perhaps as a surrogate for frailty. Preliminary epidemiologic data suggest the prevalence of frailty (and intermediate frail states) among critically ill patients is high and likely to increase with the greater demand placed on ICU resources associated with population demographic transition. SUMMARY: The concept of frailty, as a marker of biologic age and physiologic reserve, may have direct relevance to critical care, and clearly identifies a population at greater risk of adverse events, morbidity, and mortality. Its recognition in critical care settings may enable improved prognostication and shared decision-making and identify vulnerable subgroups with specific needs who might benefit from targeted follow-up.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".