Long-term cognitive recovery after out-of-hospital cardiac arrest: Insights into improvement over six months and the role of arrest duration
Bibliographic record
Abstract
Abstract Background Out-of-hospital cardiac arrest (OHCA) is a significant cause of mortality and morbidity worldwide. While resuscitation advancements have increased survival, many survivors suffer cognitive impairments that affect their quality of life. Most research has focussed on neurological outcomes, while little attention has been paid to cognitive function. Aim To investigate the proportion of cognitive impairment in OHCA survivors at discharge and six months after cardiac arrest and to investigate the association between the duration of cardiac arrest and level of cognitive function. Methods In this prospective cohort study, 184 OHCA survivors were assessed using the Montreal Cognitive Assessment (MoCA) screening tool. Duration of cardiac arrest was defined by no-flow, low-flow and time to return of spontaneous circulation (ROSC). Multiple logistic regression analysis provided odds ratios (OR) and confidence intervals (CI). Results The study indicates a significant improvement in cognitive function among OHCA survivors from discharge to the six-month follow-up. The proportion of patients with normal cognitive function increased from 26% to 67%, while the number of patients with severe and moderate cognitive impairment decreased. These results suggest a general enhancement in cognitive function over time. No significant association was found between the duration of cardiac arrest and cognitive function, either at discharge or follow-up. Conclusions Cognitive function improved considerably within six months following cardiac arrest, with the proportion of patients exhibiting normal cognitive function increasing from 26% to 67%. This study found no association between the duration of cardiac arrest and cognitive function.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".