The REVIVE Project: From Survival to Holistic Recovery—A Prospective Multicentric Evaluation of Cognitive, Emotional, and Quality-of-Life Outcomes in Out-of-Hospital Cardiac Arrest Survivors
Bibliographic record
Abstract
Background/Objectives: Most survivors of out-of-hospital cardiac arrest (OHCA) may suffer from cognitive, mental difficulties, and fatigue, which negatively impact their quality of life, despite a good physical recovery. However, no definitive data are available on this topic, so this study aims to assess the feasibility and acceptability of a centralized, sub-regional screening system for OHCA survivors in Italy and the prevalence of these disorders. Methods: OHCA survivors discharged with good neurological outcomes (Cerebral Performance Category (CPC) ≤ 2 and modified Ranking Scale (mRS) ≤ 3) from hospitals in the “Lombardia CARe” registry will be evaluated by a clinical psychologist using the Montreal Cognitive Assessment (MoCA), Hospital Anxiety and Depression Scale (HADS), EQ-5D-5L for quality of life, and the Impact of Event Scale-Revised (IES-R) at pre-discharge or within 15 days and then at 1, 3, 6, and 12 months. Patients with clinical issues will be referred for psychological support or to a community rehabilitation program. Feasibility will be defined as a recruitment rate ≥ 80% and acceptability as a retention rate ≥ 50% over 12 months. Results: Based on historical data from the Lombardia CARe, an estimated 350 eligible survivors are expected, which will allow estimation of a prevalence ranging between 20% and 30% with 5% precision and 95% confidence. Conclusions: This study will be the first in Italy to evaluate the feasibility and acceptability of a centralized, sub-regional system for pre-/post-discharge evaluation of cognitive impairment, mental health, and quality of life in a large cohort of OHCA survivors, documenting the prevalence of these disorders.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".