Early cognitive and psychological symptoms in cardiac arrest survivors and mental health outcomes among relatives: findings from the REVIVAL cohort
Bibliographic record
Abstract
Aim To investigate whether early cognitive impairment and symptoms of traumatic distress, anxiety, and depression in out-of-hospital cardiac arrest (OHCA) survivors are associated with clinical symptoms of psychopathology in relatives at follow-up. Methods This study is a predefined analysis of a multicenter cohort study of OHCA survivors and relatives that took place from January 2018 to February 2022 at three cardiac arrest centers. Applying the Montreal Cognitive Assessment (MoCA), the Impact of Event Scale-Revised (IES-R), and the Hospital Anxiety and Depression Scale (HADS), cognition and symptoms of psychopathology were assessed in survivors during hospitalisation. At three-month follow-up, we evaluated clinical symptoms of post-traumatic stress disorder (PTSD) using IES-R, and clinical symptoms of anxiety and depression with HADS in relatives. Logistic regression models were applied. Results At follow-up, 146 relatives (84% females) from 297 OHCA survivors participated. Median age was 55 years (IQR 21-79 years). Overall, relatives were found with clinical symptoms of PTSD (25%), anxiety (27%), and depression (14%). In unadjusted analysis, early cognitive impairment (MoCA score < 26) in survivors was associated with higher odds of clinical symptoms of PTSD in relatives (OR (95% CI) 2.61 (1.09-6.24, p = .03) at three-months follow-up. This association was no longer significant after adjusting for age. Conclusion Clinical symptoms of PTSD and anxiety were common in relatives of survivors at three months post-cardiac arrest. Further research is needed to identify factors that may be associated with mental health challenges in relatives to support these families early in the cardiac arrest survivorship.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".