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Record W2327305934 · doi:10.1097/jcn.0b013e31822275c7

Predictors of Symptom Congruence Among Patients With Acute Myocardial Infarction

2012· article· en· W2327305934 on OpenAlexaff
Susan M. Fox-Wasylyshyn

Bibliographic record

VenueThe Journal of Cardiovascular Nursing · 2012
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsMedicineMyocardial infarctionChest painPsychological interventionCongruence (geometry)Medical historyInternal medicinePhysical therapyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: The extent of congruence between one's symptom experience and preconceived ideas about the nature of myocardial infarction symptoms (ie, symptom congruence) can influence when acute myocardial infarction (AMI) patients seek medical care. Lengthy delays impede timely receipt of medical interventions and result in greater morbidity and mortality. However, little is known about the factors that contribute to symptom congruence. Hence, the purpose of this study was to examine how AMI patients' symptom experiences and patients' demographic and clinical characteristics contribute to symptom congruence. PARTICIPANTS AND METHODS: Secondary data analyses were performed on interview data that were collected from 135 AMI patients. Hierarchical multiple regression analyses were used to examine how specific symptom attributes and demographic and clinical characteristics contribute to symptom congruence. Chest pain/discomfort and other symptom variables (type and location) were included in step 1 of the analysis, whereas symptom severity and demographic and clinical factors were included in step 2. In a second analysis, quality descriptors of discomfort replaced chest pain/discomfort in step 1. RESULTS: Although chest pain/discomfort, and quality descriptors of heaviness and cutting were significant in step 1 of their respective analyses, all became nonsignificant when the variables in step 2 were added to the analyses. Severe discomfort (β = .29, P < .001), history of AMI (β = .21, P < .01), and male sex (β = .17, P < .05) were significant predictors of symptom congruence in the first analysis. Only severe discomfort (β = .23, P < .01) and history of AMI (β = .17, P < .05) were predictive of symptom congruence in the second analysis. CONCLUSIONS: Although the location and quality of discomfort were important components of symptom congruence, symptom severity outweighed their importance. Nonsevere symptoms were less likely to meet the expectations of AMI symptoms by those experiencing this event. Those without a previous history of AMI also experienced lower levels of symptom congruence. Implications pertaining to these findings are discussed.

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 score0.027
Threshold uncertainty score0.327

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.007
GPT teacher head0.258
Teacher spread0.251 · 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

Citations9
Published2012
Admission routes1
Has abstractyes

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