Physical, psychological, cognitive, social health outcomes, and health-related quality of life in out-of-hospital cardiac arrest survivors and their caregivers: Protocol of the quality cardiac arrest survivorship cohort study (QualiCAS)
Bibliographic record
Abstract
Background: Out-of-hospital cardiac arrest (OHCA) is an emergency with historically low survival rates. Advances in resuscitation and post-resuscitation care have improved survival, precipitating greater scientific interest in OHCA patients' survivorship. However, there is insufficient high-quality population-based long-term survivorship data and limited research on the impact of OHCA sequelae on survivors' caregivers. Objective: Our primary aim is to determine neurological function, physical, psychological, cognitive, social outcomes, and health-related quality of life (HRQoL) of OHCA survivors in Singapore. Secondary aims are to quantify caregivers' burden and its association with their HRQoL, and psychological well-being. Methods: The Quality Cardiac Arrest Survivorship Cohort Study (QualiCAS) is a prospective population-based cohort study of OHCA survivors and their caregivers in Singapore. Participants aged ≥18 years and caregivers aged ≥21 years will be recruited from all public hospitals in Singapore. Health outcomes will be evaluated at 3, 6, and 12 months, and 3 and 5 years using the Hospital Anxiety and Depression Scale, PTSD Checklist for DSM-5, Fatigue Severity Scale, Montreal Cognitive Assessment Tool, EQ-5D-5L, Community Integration Questionnaire-Revised, Barthel Index, Lawton's Instrumental Activities of Daily Living, Timed Up and Go Test, Handgrip strength assessment, and Zarit Burden Interview. Discussion: This study allows us to understand the natural history of OHCA survivorship and quantify the burdens on patients and their caregivers. Findings can guide clinical follow-up, identify high-risk patients, intervention targets, and inform rehabilitation strategies for OHCA sequelae.
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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 | 0.013 | 0.007 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".