Intensive Care Unit Functional Status and Long-term Mortality in Critical Care Survivors
Bibliographic record
Abstract
Abstract Rationale: Despite increasing complexity and disease severity of critical illness admissions to the intensive care unit (ICU), more people are surviving critical illness than in previous decades; however, post intensive care mortality remains high. There are currently no prognostic tools that are used to predict long-term outcomes in post-ICU survivors. Functional status, a measure of an individual's physical independence, is used prognostically to inform clinical decision making in diseases with high risk of long-term mortality, such as cardiorespiratory diseases and cancer. Thus, the purpose of this study was to investigate the prognostic significance of ICU functional status to predict long-term mortality in critical illness survivors. Methods: Using a retrospective design, functional status measured daily in patients who were in the ICU at St. Paul's Hospital in Vancouver, B.C. between 2019-2022 were collected. Patients were classified as having a high peak ICU functional status (i.e., standing or walking; n=311) or a low peak functional status (peak mobility of awake but supine; n=328). Patients were excluded if they were admitted to the ICU for <48 hours and if there were multiple admissions for an individual, only the index admission was included. Kaplan Meier estimates were performed to determine the independent association between functional status and survival. A multivariable cox proportional model was used to determine risk of all-cause mortality with adjustment for important covariates such as age, ICU length of stay, disease severity at ICU entry (APACHE II score), length of mechanical ventilation, the use of vasoactive drugs, and the presence of delirium. Results: There was a total of 2584 admissions to the ICU between 2019-2022. Of those, 311 were classified as having a high functional status and 328 as having low functional status. Median follow-up time was 24 months; 244 deaths were reported during this period. High ICU functional status was an independent predictor of overall survival in the Kaplan Meier analysis (p=0.024). Compared with low ICU functional status, the adjusted Hazard Ratio (HR) for all-cause mortality was 0.76 (CI, 0.58-0.9) for the high functional status group. Conclusions: Peak ICU functional status predicts long-term survival probability. Individuals with high ICU functional status experience a significantly lower risk of mortality after ICU discharge.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".