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Factors Influencing Patient Knowledge of Warfarin Therapy After Mechanical Heart Valve Replacement

2006· article· en· W2326913129 on OpenAlex
Amanda Hu, Chi-Ming Chow, Diem Dao, Lee Errett, Mary Keith

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Cardiovascular Nursing · 2006
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsSt. Michael's HospitalUniversity of Toronto
Fundersnot available
KeywordsWarfarinMedicineSocioeconomic statusMultivariate analysisUnivariate analysisAnalysis of variancePhysical therapyInternal medicinePopulationAtrial fibrillation

Abstract

fetched live from OpenAlex

BACKGROUND AND RESEARCH OBJECTIVE: Patients with mechanical heart valves must follow lifelong warfarin therapy. Warfarin, however, is a difficult drug to manage because it has a narrow therapeutic window and potentially serious side effects. Successful anticoagulation treatment is dependent upon the patient's knowledge of this drug; however, little is known regarding the determinants of such knowledge. Therefore, the purpose of this study was to determine the influence of both in-hospital teaching practices as well as socioeconomic status and demographic variables on patients' knowledge of warfarin therapy. SUBJECTS AND METHODS: A telephone survey was conducted among 100 patients 3 to 6 months after mechanical heart valve replacement. A previously validated 20-item questionnaire was used to measure the patient's knowledge of warfarin, its side effects, and vitamin K food sources. Demographic information, socioeconomic status data, and medical education information were also collected. Knowledge scores were compared using the Student t test or one-way analysis of variance. Variables with P < or = .2 on univariate analysis were entered in multiple stepwise regression analysis. RESULTS AND CONCLUSIONS: Sixty-one percent of participants had scores indicative of insufficient knowledge of warfarin therapy (score < or = 80%). Age was negatively related to warfarin knowledge scores (r = 0.27, P = .007). Patients with family incomes greater than $25,000, who had greater than a grade 8 education, and who were employed or self-employed had significantly higher warfarin knowledge scores (P = .007, P = .002, and P = .001, respectively). Gender, ethnicity, and warfarin therapy before surgery were not related to warfarin knowledge scores. Furthermore, none of the in-hospital teaching practices significantly influenced knowledge scores, whereas receiving postdischarge community counseling significantly improved knowledge scores (P = .001). Multivariate regression analysis revealed that understanding the concept of International Normalized Ratio, knowing the acronym, age, and receiving community counseling after discharge were the strongest predictors of warfarin knowledge. Accessing postdischarge counseling resulted in significantly improved warfarin knowledge scores. Because improved knowledge has been associated with improved compliance and control, our findings support the need to develop a comprehensive postdischarge education program or at least to ensure that patients have access to a community counselor to compliment the in-hospital education program.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.403
Threshold uncertainty score0.329

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
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 head0.045
GPT teacher head0.308
Teacher spread0.263 · 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