How does prior health status (age, comorbidities and frailty) determine critical illness and outcome?
Bibliographic record
Abstract
PURPOSE OF REVIEW: Critical illness has a significant impact on an individual's physical and mental health. However, it is less clear to what degree outcomes after critical illness are due to patients' preexisting characteristics, rather than the critical illness itself. In this review, we summarize recent findings regarding the role of age, comorbidity and frailty on long-term outcomes after critical illness. RECENT FINDINGS: Age, comorbidity and frailty are all associated with an increased risk of critical illness. Although severity of illness drives the risk of acute mortality, recent data suggest that longer term outcomes are much more closely aligned with prior health status. There are growing data regarding the important role of noncardiovascular comorbidity, including psychiatric illness and obesity, in determining long-term outcomes. Finally, preadmission frailty is associated with poor long-term outcomes after critical illness; further data are needed to evaluate the attributable impact of critical illness on the health trajectories of frail individuals. SUMMARY: Age, comorbidity and frailty play a critical role in determining the long-term outcomes of patients requiring intensive care.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".