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Record W2972695727

Knowledge, attitudes and current practices of Palestinian internists toward aspirin prescription

2019· article· en· W2972695727 on OpenAlexvenueno aff
Iyad Ali, Hamzeh Al Zabadi, Nisreen R. Dayyeh

Bibliographic record

VenueUniversity of Toronto Medical Journal · 2019
Typearticle
Languageen
FieldMedicine
TopicAntiplatelet Therapy and Cardiovascular Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsAspirinMedicineMedical prescriptionMyocardial infarctionDiseaseStroke (engine)AnginaCoronary artery diseaseIntensive care medicineFamily medicineInternal medicineNursing
DOInot available

Abstract

fetched live from OpenAlex

Background and Aim: Long-term aspirin therapy is crucial for patients at increased risk for cardiovascular diseases. However, differing perceptions among healthcare providers profoundly shape the challenges observed in risk assessment. This study assessed the knowledge, attitudes and current practices of internists who prescribe aspirin as a preventive measure for cardiovascular diseases. Methods: A questionnaire was distributed to a total of 38 internists working at healthcare centres in Nablus, Palestine. Results: The majority of physicians (95%) reported that they prescribe aspirin for patients following a coronary artery bypass graft. About 92% of physicians prescribe aspirin for patients with a peripheral vascular disease or acute myocardial infarction, and 85% of physicians prescribe aspirin if patients have a history of stroke and congestive heart failure, or stable angina. The prescribing of aspirin as prophylaxis for patients without cardiovascular disease, but with one or more risk factors, was reported by 61% to 79% of the physicians depending on the nature and number of risk factors. In some cases, the presence of additional diseases in association with cardiovascular diseases tended to hinder physicians from prescribing aspirin. Conclusions: The majority of Palestinian internal physicians recommend the use of aspirin as a primary prevention tool for cardiovascular disease in spite of its potential negative side effects. Our results revealed that physicians in Palestine tend to prescribe aspirin with varying patterns and therefore a set of evidence-based recommendations should be implemented.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.694
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.024
GPT teacher head0.306
Teacher spread0.282 · 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.

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
Published2019
Admission routes1
Has abstractyes

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