Abstract 15131: Early Withdrawal of Life-Sustaining Therapy for Perceived Neurological Prognosis is Associated With Excess Mortality After Out-of-Hospital Cardiac Arrest
Bibliographic record
Abstract
Introduction: Withdrawal of life-sustaining therapy because of perceived poor neurological prognosis (WLST-N) is a common cause of death after out-of-hospital cardiac arrest. Guidelines recommend against WLST-N before 72 h (WLST-N<72), but WLST-N<72 remains common and may increase mortality. Methods: We performed a secondary analysis of the Resuscitation Outcomes Consortium’s PRIMED trial including adults surviving >1h after hospital arrival. Our main exposure was WLST-N<72, which was collected for the original trial by chart review. Outcomes were survival to hospital discharge and functionally favorable survival (modified Rankin Score ≤ 3). We used two methods to determine predicted outcomes in the cohort exposed to WLST-N<72 if WLST-N were delayed until after 72h. First, we used pre-exposure covariates to create a propensity score modeling the probability of exposure to WLST-N<72 and propensity-matched exposed to unexposed subjects, treating subjects with WLST-N after 72h as unexposed. We then determined the probability of survival and functionally favorable survival in the unexposed matched cohort. Second, we fit adjusted logistic regression models using data from the unexposed cohort and used these models to predict outcomes in the exposed cohort. Results: Of 16,875 OHCA subjects, 4,265 (25%) met inclusion criteria. Of these, 1,490 (35%) survived to discharge and 1101 (26%) had a functionally favorable survival. WLST-N occurred in 1626 (59% of non-survivors), most commonly on hospital day 1, and 919 (33% of non-survivors) were exposed to WLST-N<72. After matching, there were no differences between the exposed and unexposed groups. In adjusted analyses, exposed subjects had an estimated 25-26% chance of survival and 16% functionally favorable survival had they not received WLST-N<72. Conclusion: In this large North American cohort, death associated with WLST-N<72 was common. Extrapolating to national epidemiological data, our findings indicate that approximately 4,500 Americans annually who would otherwise survive to discharge instead die because of WLST-N<72, nearly 2,900 (64%) of whom might have had functional recovery. Reducing WLST-N<72 may be an important means to decrease mortality after OHCA and improve public health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".