Abstract 18656: The Effect of Targeted Temperature Management is Dependent Upon the Duration of Out-of-hospital Cardiac Arrest
Bibliographic record
Abstract
Introduction: Targeted temperature management (TTM) reduces neurologic injury from out-of-hospital cardiac arrest (OHCA). As the risk of neurologic injury increases with prolonged cardiac arrests, the benefit of TTM may depend upon cardiac arrest duration. We hypothesized that there is a time-dependent effect of TTM on neurologic outcomes from OHCA. Methods: Retrospective, observational study of the Toronto RescuNET Epistry-Cardiac Arrest database from 2007 to 2014. We included adult (>18) OHCA of presumed cardiac etiology that remained comatose (GCS<10) after a return of spontaneous circulation. We used multivariable logistic regression to determine the effect of TTM and the duration of cardiac arrest on good neurologic outcome (Modified Rankin Scale (mRS) 0-3) and survival to hospital discharge while controlling for other known predictors. Results: There were 1496 patients who met our inclusion criteria, of whom 981 (66%) received TTM. Of the patients who received TTM, 59% had a good neurologic outcome compared to 39% of patients who did not receive TTM (p< 0.001). After adjusting for the Utstein variables, use of TTM was associated with improved neurologic outcome (OR 1.60, 95% CI 1.10-2.32; p = 0.01) but not with survival to discharge (OR 1.23, 95% CI 0.90-1.67; p = 0.19). The impact of TTM on neurologic outcome was dependent on the duration of cardiac arrest (p<0.05) (Fig 1). Other significant predictors of good neurologic outcome were younger age, public location, initial shockable rhythm, and shorter duration of cardiac arrest (all p values < 0.05). A subgroup analysis found the use of TTM to be associated with neurologic outcome in both shockable (p = 0.01) and non-shockable rhythms (p = 0.04) but was not associated with survival to discharge in either group (p = 0.12 and p = 0.14 respectively). Conclusion: The use of TTM was associated with improved neurologic outcome at hospital discharge. Patients with prolonged durations of cardiac arrest benefited more from TTM.
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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 | 0.008 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".