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Record W7133410146

Epidemiology and prognostic implications of panic disorder and generalized anxiety disorder in patients with coronary artery disease: rationale and design for a longitudinal cohort study

2021· article· en· W7133410146 on OpenAlexfundno aff
Guillaume Foldes‑Busque, Clermont E. Dionne, Stéphane Turcotte, Phillip John Tully, Marie‑Andree Tremblay, Paul Poirier, Isabelle Denis

Bibliographic record

VenueRUNE (Research UNE) · 2021
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchInstitut universitaire de cardiologie et de pneumologie de Québec, Université Laval
KeywordsPanic disorderAnxietyGeneralized anxiety disorderIncidence (geometry)EpidemiologyQuality of life (healthcare)Coronary artery diseaseCohort studyPanic
DOInot available

Abstract

fetched live from OpenAlex

Background: Anxiety is associated with poorer prognosis in patients with coronary artery disease (CAD). Due to their severity and chronic course, anxiety disorders, particularly generalized anxiety disorder (GAD) and panic disorder (PD), are of considerable interest and clinical importance in this population. This study has two main objectives: (1) to estimate the prevalence and incidence of GAD and PD in patients with CAD over a 2-year period and (2) to prospectively assess the association between PD or GAD and adverse cardiac events, treatment adherence, CAD-related health behaviors, quality of life and psychological distress.Design/Method: This is a longitudinal cohort study in which 3610 participants will be recruited following a CAD-related revascularization procedure. They will complete an interview and questionnaires at 5 time points over a 2-year period (baseline and follow-ups after 3, 6, 12 and 24 months). The presence of PD or GAD, adherence to recommended treatments, health behaviors, quality of life and psychological distress will be assessed at each time point. Data regarding mortality and adverse cardiac events will be collected with a combination of interviews and review of medical files.Discussion: This study will provide essential information on the prevalence and incidence of anxiety disorders in 
 patients with CAD and on the consequences of these comorbidities. Such data is necessary in order to develop clear clinical recommendations for the management of PD and GAD in patients with CAD. This will help improve the prognosis of patients suffering from both conditions.

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)0.001
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 score0.009
Threshold uncertainty score0.355

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.087
GPT teacher head0.408
Teacher spread0.321 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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