Abstract 14128: Predictors of Long-Term Mortality for Survivors of Out-Of-Hospital Cardiac Arrest
Bibliographic record
Abstract
Background: Although outcomes of out-of-hospital cardiac arrest (OHCA) patients have improved substantially over time, little is known regarding factors that may influence their longer term prognosis. The main objective of this study was to examine independent predictors of long-term mortality for OHCA survivors. Methods: A population-based study was conducted using the Toronto Rescu Epistry database with linkage to administrative data in Ontario, Canada. OHCA patients who survived to hospital discharge in the Great Toronto Area from 2005 to 2010 were included. Multivariable hierarchical regression models were constructed to determine the independent association of factors predicting 1-year and 3-years mortality. Results: Among the 13,755 OHCA patients who were eligible for study inclusion, 704 patients were alive at discharge and were included in this analysis. Their mean age was 60 years old, 27% were women, 35% had diabetes, and 9.4% had previous myocardial infarction. Mortality rates were 11.5% at one year and 19.6% at three years. Older age, cerebrovascular disease (OR = 2.74), renal disease (OR = 4.12) were significantly associated with higher mortality at one year (Table). In contrast, patients who had shockable initial rhythm (OR = 0.31), those who received coronary revascularization (OR = 0.41), or implantable cardioverter defibrillator (OR = 0.19) were associated with substantially lower risk of mortality. Factors associated with 3-year mortality were mostly similar as compared to one year, except for cancer which was highly significant for 3-year mortality (OR = 6). These models had high discrimination ability with area under the ROC of 0.89 for 1-year model and 0.88 for 3-year model. Conclusions: Non-cardiac comorbidities are the main drivers of adverse mortality for long term survivors of OHCA. Invasive cardiac procedures such as coronary revascularizations and ICD implantations are associated with significantly improved outcomes.
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 | 0.000 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".