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Predicting the Benefits of Percutaneous Coronary Intervention on 1-Year Angina and Quality of Life in Stable Ischemic Heart Disease

2018· article· en· W2799289118 on OpenAlexaff
Zugui Zhang, Philip G. Jones, William S. Weintraub, G.B. John Mancini, Steven P. Sedlis, David J. Maron, Koon Teo, Pamela Hartigan, William J. Kostuk, Daniel S. Berman, William E. Boden, John A. Spertus

Bibliographic record

VenueCirculation Cardiovascular Quality and Outcomes · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsLondon Health Sciences CentreMcMaster University
Fundersnot available
KeywordsMedicineCardiologyStable anginaPercutaneous coronary interventionInternal medicineAnginaDiseaseQuality of life (healthcare)PercutaneousCoronary heart diseaseMyocardial infarctionNursing

Abstract

fetched live from OpenAlex

Background: Percutaneous coronary intervention (PCI) is a therapy to reduce angina and improve quality of life in patients with stable ischemic heart disease. However, it is unclear whether the quality of life after PCI is more dependent on the PCI or other patient-related factors. To address this question, we created models to predict angina and quality of life 1 year after PCI and medical therapy. Methods and Results: Using data from the 2287 stable ischemic heart disease patients randomized in the COURAGE trial (Clinical Outcomes Utilizing Revascularization and Aggressive Drug Evaluation) to PCI plus optimal medical therapy (OMT) versus OMT alone, we built prediction models for 1-year Seattle Angina Questionnaire angina frequency, physical limitation, and quality of life scores, both as continuous outcomes and categorized by clinically desirable states, using multivariable techniques. Although most patients improved regardless of treatment, marked variability was observed in Seattle Angina Questionnaire scores 1 year after randomization. Adding PCI conferred a greater mean improvement (about 2 points) in Seattle Angina Questionnaire scores that were not affected by patient characteristics ( P values for all interactions >0.05). The proportion of patients free of angina or having very good/excellent physical limitation (physical function) or quality of life at 1 year was 57%, 58%, 66% with PCI+OMT and 50%, 55%, 59% with OMT alone group, respectively. However, other characteristics, such as baseline symptoms, age, diabetes mellitus, and the magnitude of myocardium subtended by narrowed coronary arteries were as, or more, important than revascularization in predicting symptoms (partial R 2 =0.07 versus 0.29, 0.03 versus 0.22, and 0.05 versus 0.24 in the domain of angina frequency, physical limitation, and quality of life, respectively). There was modest/good discrimination of the models (C statistic=0.72–0.82) and excellent calibration (coefficients of determination for predicted versus observed deciles=0.83–0.97). Conclusions: The health status outcomes of stable ischemic heart disease patients treated by OMT+PCI versus OMT alone can be predicted with modest accuracy. Angina and quality of life at 1 year is improved by PCI but is more strongly associated with other patient characteristics. Clinical Trial Registration: URL: https://www.clinicaltrials.gov . Unique identifier: NCT00007657.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.350

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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 head0.063
GPT teacher head0.350
Teacher spread0.288 · 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

Citations25
Published2018
Admission routes1
Has abstractyes

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