Long-Term Outcomes and Health Care Utilization after Prolonged Mechanical Ventilation
Bibliographic record
Abstract
RATIONALE: Limited data are available to characterize the long-term outcomes and associated costs for patients who require prolonged mechanical ventilation (PMV; defined here as mechanical ventilation for longer than 21 d). OBJECTIVES: To examine the association between PMV and mortality, health care utilization, and costs after critical illness. METHODS: Population-based cohort study of adults who received mechanical ventilation in an intensive care unit (ICU) in Ontario, Canada between 2002 and 2013. MEASUREMENT AND MAIN RESULTS: We used linked administrative databases to determine discharge disposition, and ascertain 1-year mortality (primary outcome), readmissions to hospital and ICU, and health care costs for hospital survivors. Overall, 11,594 (5.4%) patients underwent PMV, with 42.4% of patients dying in the hospital (vs. 27.6% of patients who did not undergo prolonged ventilation; P < 0.0001). Patients on prolonged ventilation were more frequently discharged to other facilities or home with health care support (84.8 vs. 43.5%, P < 0.0001). Among hospital survivors, estimated mortality was higher for patients who underwent PMV: 16.6 versus 11% at 1 year and 42.0 versus 30.4% at 5 years. At 1 year after hospital discharge, patients on prolonged ventilation had higher rates of hospital readmission (47.2 vs. 37.7%; adjusted odds ratio = 1.20; 95% confidence interval = 1.14-1.26), ICU readmission (19.0 vs. 11.6%; adjusted odds ratio = 1.49; 95% confidence interval: 1.39, 1.60), and total health care costs: median (interquartile range) Can $32,526 ($20,821-$56,102) versus Can $13,657 ($5,946-$38,022). Increasing duration of mechanical ventilation was associated with higher mortality and health care utilization. CONCLUSIONS: Critically ill patients who undergo mechanical ventilation in an ICU for longer than 21 days have high in-hospital mortality and greater postdischarge mortality, health care utilization, and health care costs compared with patients who undergo mechanical ventilation for a shorter period of time.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".