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Record W4360602124 · doi:10.1515/jom-2022-0141

Effects of the Strong Hearts program after a major cardiovascular event in patients with cardiovascular disease

2023· article· en· W4360602124 on OpenAlexaboutno aff
Bruce E. Murphy, Peyton D. Card, Leybi Ramirez-Kelly, Amanda M. Xaysuda, R. Eric Heidel

Bibliographic record

VenueJournal of Osteopathic Medicine · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCanadian Cardiovascular SocietyHeart failureMyocardial infarctionAnginaEjection fractionCoronary artery diseaseInternal medicineContext (archaeology)Physical therapyCardiologyPsychological interventionRehabilitationConventional PCI

Abstract

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CONTEXT: Cardiac rehabilitation (CR) and intensive cardiac rehabilitation (ICR) are secondary prevention interventions for cardiovascular disease (CVD) with a class 1a indication yet suboptimal utilization. To date, there are only three approved ICR programs. Alternative programing should be explored to increase enrollment and adherence in these interventions. OBJECTIVES: This study aims to evaluate the effectiveness of the Strong Hearts program in cardiovascular patients following a major cardiovascular event. METHODS: One hundred ninety-seven (n = 197) participants were enrolled in this prospective, nonrandomized study. Patients were eligible for participation if they were referred by a physician after a major cardiovascular event, defined as any of the following: (1) acute myocardial infarction (MI) within the preceding 12 months; (2) current stable or unstable angina pectoris; (3) heart valve procedure; (4) percutaneous intervention of any kind; (5) heart transplant; (6) coronary artery bypass grafting (CABG); or (7) congestive heart failure (CHF) with reduced or preserved ejection fraction. Participants were asked to attend program visits four times per week for 9 weeks. Visits consisted of individualized exercise and intensive healthy lifestyle education. Paired t tests were utilized to compare pre- and postprogram outcome measures. RESULTS: One hundred twenty-eight (n = 128) participants completed the program within the 9-week time frame and their outcome measures were included in the data analysis. Among this, 35.2% participants were female and 64.8% were male. The mean age was 65 (range, 19-88). Qualifying diagnoses were percutaneous coronary intervention (PCI; 60, 46.9%), CABG (33, 25.8%), angina (24, 18.8%), valve procedures (8, 6.2%), and CHF (3, 2.3%). After implementation of the intervention, statistically significant decreases in weight (P < .001), body mass index (BMI, P < .001), waist circumference (P < .001), triglycerides (P = .01), systolic blood pressure (SBP, P <.001), diastolic blood pressure (DBP, P = .002), total fat mass (P < .001), Dartmouth Quality of Life Index P < .001), and cardiac depression scores (P = .044) were detected. In other instances, there were statistically significant increases across time for the clinical parameters of high-density lipoprotein (HDL, P = .02), Vitamin D (P = .001), metabolic equivalents (METS, P < .001), Duke activity scores (P < .001), and Rate Your Plate nutrition scores (P < .001). There were no significant changes across time for total cholesterol (P = .17), low-density lipoprotein (LDL, P = .21), A1c (P = .27), or dual-energy X-ray absorptiometry (DXA) total lean mass (P = .86). CONCLUSIONS: The 9-week structured program resulted in significant cardiovascular benefit to patients with CVD by reducing cardiac risk factors, increasing exercise capacity, and improving quality of life.

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)0.001
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.008
GPT teacher head0.267
Teacher spread0.260 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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