Deaths following withdrawal of life-sustaining therapy: Opportunities for quality improvement?
Bibliographic record
Abstract
BACKGROUND: Mortality is an important trauma center outcome. With many patients initially surviving catastrophic injuries and a growing proportion of geriatric patients, many deaths might occur following withdrawal of life-sustaining therapy (WLST). We utilized the American College of Surgeons Trauma Quality Improvement Program database to explore whether deaths following WLST might be preventable and to evaluate the impact of excluding patients who died following WLST on hospital performance. METHODS: A retrospective cohort study was conducted using data derived from American College of Surgeons Trauma Quality Improvement Program. Adult trauma patients treated at Levels I and II centers in 2016 were included. Three cohorts of deceased patients were created to assess differences in hospital performance. The first included all deaths, the second included only those who died without WLST, and the third included deaths without WLST and deaths with WLST where death was preceded by a major complication. Hospitals were ranked based on their observed-to-expected mortality ratio calculated using each of the three decedent cohorts. Outcomes included absolute change in hospital ranking and change in performance outlier status between cohorts. RESULTS: We identified 275,939 patients treated at 447 centers who met inclusion criteria. Overall mortality was 6.9% (n = 19,145). Withdrawal of life-sustaining therapy preceded 43.6% (n = 8,343) of deaths and 23% (n = 1,920) of these patients experienced a major complication before death. The median absolute change in hospital performance rank between the first and second cohort was 58 (p < 0.001), between the first and third cohort was 44 (p < 0.001), and between the second and third cohort was 23 (p < 0.001). Hospital performance outlier status changed significantly between cohorts. CONCLUSION: The exclusion of patients who die following WLST from benchmarking efforts leads to a major change in hospital ranks. Potentially preventable deaths, such as those following a major complication, should not be excluded. LEVEL OF EVIDENCE: Epidemiological study, level III.
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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 | 0.030 | 0.083 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".