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Record W3131488610 · doi:10.1532/hsf.3261

Health-Related Quality of Life of Coronary Artery Disease Patients under Secondary Prevention: A Cross-Sectional Survey from South India

2021· article· en· W3131488610 on OpenAlexaff
Remya Sudevan, Manu Raj, Vasudevan Damodaran, Rajesh Thachathodiyl, M Vijayakumar, Jabir Abdullakutty, Paul V. Thomas, Vijo George, Conrad Kabali

Bibliographic record

VenueThe Heart Surgery Forum · 2021
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsMedicineCoronary artery diseaseCross-sectional studyQuality of life (healthcare)Diabetes mellitusDiseaseInternal medicinePhysical therapyMental healthPsychiatryPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Health-related quality of life (HRQOL) is emerging as an important outcome among patients with documented coronary artery disease (CAD). The primary objective of this study was to report the HRQOL of CAD patients under secondary prevention-related treatment and follow-up using the 36-Item Short Form (SF-36) tool. METHODS: This was an analytical cross-sectional survey done in a hospital/clinic setting. We recruited CAD patients 30 to 80 years old with 1 to 6 years of follow-up. Patients self-reported HRQOL using SF-36. RESULTS: We recruited 1206 patients, among whom 879 (72.9%) were male. The mean age of patients was 61.3 (9.6) years. Mean (± standard deviation) scores for physical functioning, role limitations due to physical health, pain, and general health were 66.48 ± 29.41, 78.96 ± 28.01, 80.96 ± 21.15, and 51.49 ± 20.19, respectively. The scores for role limitations due to emotional problems, energy/fatigue, emotional well-being, and social functioning were 76.62 ± 28.0, 66.18 ± 23.92, 76.91 ± 20.47, and 74.49 ± 23.55. In subgroup analysis, age, sex, type of CAD, and treatment showed no significant association with any of the 8 domains of QOL. In addition, hypertension and diabetes showed no significant association with the individual domains of HRQOL. CONCLUSION: Patients with coronary artery disease under secondary prevention-related treatment have suboptimal HRQOL under both physical and mental domains. The role of demographic factors, comorbidities, disease subtypes, and treatment options in modifying HRQOL among patients with CAD appears to be minimal.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.871

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 integrity0.0000.000
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 head0.072
GPT teacher head0.354
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

Citations4
Published2021
Admission routes1
Has abstractyes

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