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Record W4280500294 · doi:10.1093/eurjpc/zwac056.052

Secondary prevention of acute coronary syndrome by reducing depression and anxiety

2022· article· en· W4280500294 on OpenAlexaff
Kiera Liblik, Emilie T. Théberge, Nikita Menon, Zoya Gomes, John Gobran, Emily Burbidge, A. Johri

Bibliographic record

VenueEuropean Journal of Preventive Cardiology · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsDalhousie UniversityUniversity of British ColumbiaQueen's University
Fundersnot available
KeywordsMedicineAnxietyDepression (economics)Psychological interventionRandomized controlled trialPopulationAcute coronary syndromeQuality of life (healthcare)Systematic reviewDiseaseRehabilitationPhysical therapyIntensive care medicineMEDLINEPsychiatryInternal medicineMyocardial infarctionNursing

Abstract

fetched live from OpenAlex

Abstract Funding Acknowledgements Type of funding sources: None. Background/Introduction Cardiovascular disease is expected to reach an annual mortality rate of 23 million individuals by 2030, primarily due to acute coronary syndrome (ACS) and cerebrovascular events. Simply stating the mortality associated with cardiovascular disease underrepresents its true burden considering the associated disability, healthcare expenditure, and loss of quality of life. Specifically, there has been increasing interest in the prevalence of depression and anxiety post-ACS as depressive and anxious symptoms are seen in up to 45% and 30% of patients, respectfully. These symptoms are associated with increased morbidity and mortality as well as decreased quality of life. Thus, it is crucial that secondary prevention be prioritized in this population with a specific focus on psychological wellbeing. Purpose The purpose of the present systematic review is to summarize the current literature on secondary prevention following ACS via interventions aimed at reducing depression and anxiety. Methods A systematic review was conducted of the databases PubMed, EMBASE, Web of Science, ClinicalTrials.gov, and Cochrane for studies which implemented an intervention to improve depression or anxiety in patients following ACS. Results The initial literature search identified 6,536 studies, of which 97 were added for inclusion with a total of 23,965 participants. Study design comprised 83 randomized control trials, two quasi-experimental studies, and 12 non-randomized experimental studies. The majority of interventions which significantly reduced symptoms of post-ACS anxiety involved modified cardiac rehabilitation programs (20%), aromatherapy (13%), and initiation of a new therapeutic (11%). Conversely, the majority of post-ACS interventions which significantly improved depressive symptoms involved therapy (24%), modified cardiac rehabilitation (24%), and initiation of a new therapeutic (20%). Notably, all aromatherapy (n=6), arts-based (n=3), exercise (n=7), meditation (n=3), and nature therapy (n=1) intervention studies extracted reported significant improvement in either depression or anxiety scores. Conclusions Depressive and anxious symptoms following ACS are associated with increased risk of death, rehospitalization, and poor quality of life. Programs which involve modified cardiac rehabilitation programs, aromatherapy, therapeutic agents, and therapy may increase secondary prevention of ACS by improving symptoms of depression and anxiety. Due to the heterogeneity of the programs identified, significant differences in sample size across studies, and the variety of depression/anxiety scales used, a large-scale randomized control trial comparing intervention efficacy is needed. Such a trial, as well as the present systematic review, may improve secondary prevention of ACS by identifying strategies to reduce depression and anxiety in 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.632
Threshold uncertainty score0.411

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.294
Teacher spread0.281 · 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 teacher head, 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

Citations1
Published2022
Admission routes1
Has abstractyes

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