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Record W7127569833 · doi:10.1093/eurheartj/ehaf784.623

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

2025· article· en· W7127569833 on OpenAlexaboutno aff

Bibliographic record

VenueEuropean Heart Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsnot available
Fundersnot available
KeywordsAnxietyQuality of life (healthcare)CognitionHospital Anxiety and Depression ScaleProspective cohort studyDepression (economics)ResuscitationCohort

Abstract

fetched live from OpenAlex

Abstract Background The average survival rate following an Out-of-Hospital Cardiac arrest (OHCA) is approximately 5-10%. While many survivors achieve good physical recovery, they often face mental and cognitive challenges, as well as fatigue, which can adversely affect their quality of life and that of their families. The European Resuscitation Council (ERC) Guidelines recommend systematic follow-up for OHCA survivors, including screening for cognitive and emotional problems, fatigue, and providing information to patients and their families. Despite these recommendations, there is a lack of structured global initiatives to implement comprehensive follow-up systems. Purpose This study aims to evaluate the feasibility and acceptability of a centralized, sub-regional system for screening psychological distress, cognitive impairment, fatigue and poor quality of life in an Italian cohort of OHCA patients’ survivors with a good neurological outcome, defined by a CPC (Cerebral Performance Category) score of 1-2 or mRS (modified Rankin Scale) ≤ 3. The secondary aim is to investigate the prevalence of the above disorders in this cohort. Methods This multicentric, prospective feasibility study will enroll OHCA survivors discharged with favorable neurological outcomes from 22 hospitals participating in the Lombardy region's Cardiac Arrest Registry ("Lombardia CARe" registry). Hospitals are categorized as main (Figure 1) or secondary recruiters based on historical discharge data. Consenting patients will undergo evaluations by clinical psychologists, either in-person or remotely, using the Montreal Cognitive Assessment (MoCA) for cognitive deficits, the Hospital Anxiety and Depression Scale (HADS) for anxiety and depression, the EQ-5D-5L for Quality of Life (QoL), and the Impact of Event Scale - Revised (IES-R) for trauma assessment. Assessments will be carried out pre-discharge or within 15 days after discharge, and subsequently at 1, 3, 6 and 12 months. Established cut-offs will be used to identify clinical issues. Where appropriate, patients will be offered psychological support sessions or referred onward to a community rehabilitation program. Results This study will provide the first data from a regional level about the epidemiology of psychological disorders among OHCA survivors and consequently about the need and the role of psychological support for peculiar cohort of patients. Conclusions This is the first study in Italy to explore the feasibility and acceptability of a centralized, sub-regional approach to pre- and post-discharge assessments of anxiety, depression, cognitive impairment, fatigue, and quality of life in a large cohort of OHCA survivors. It will also document the prevalence of these disorders, providing valuable insights into the long-term needs of this population.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.080
GPT teacher head0.388
Teacher spread0.308 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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