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Record W2319258598

Population-based evaluation of the management of antithrombotic therapy for atrial fibrillation.

2005· article· en· W2319258598 on OpenAlexaffabout
David R. Anderson, Martin J. Gardner, Wayne Putnam, Davinder S. Jassal, Brenda Brownell, Gordon Flowerdew, Seema Nagpal, Kara Thompson, Jafna L. Cox

Bibliographic record

VenuePubMed · 2005
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsQueen Elizabeth II Health Sciences Centre
Fundersnot available
KeywordsMedicineAtrial fibrillationAntithromboticMedical prescriptionManagement of atrial fibrillationStroke (engine)PopulationCohortEmergency medicineNova scotiaInternal medicinePediatrics
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: Oral anticoagulation is an effective therapy for the prevention of cardioembolic complications in patients with atrial fibrillation. However, previous practice reviews have indicated that oral anticoagulants are often underused in this setting. Most of those reports have focused on reviews of hospitalized and institutionalized patients, or small geographical areas. OBJECTIVES: To determine the use of antithrombotic therapy for the treatment of atrial fibrillation in Nova Scotia and to survey the knowledge of antithrombotic therapy for atrial fibrillation among a concurrent cohort of primary care and specialist physicians involved in the management of patients with atrial fibrillation. PATIENTS AND METHODS: Patients with atrial fibrillation were identified through outpatient electrocardiography clinics held throughout Nova Scotia. Following consent of the primary care physicians, patients were contacted and completed a survey about their current management. Family physicians and specialists in Nova Scotia were also surveyed about the management of atrial fibrillation with antithrombotic therapy through the receipt of one of four case scenarios. RESULTS: Four hundred twenty-five patients participated in the cross-sectional survey. The mean patient age was 70.6 years, 255 (60%) were male and 398 (93.6%) had at least one risk factor for stroke in addition to atrial fibrillation. Two hundred ninety-four patients (69.2%) were receiving oral anticoagulants either alone (61.9%) or in combination with acetylsalicylic acid (ASA) (7.3%). An additional 85 patients (20%) received ASA alone. There was no difference in the rates of prescription of oral anticoagulants between elderly patients (75 years of age and older) and those younger than 75 years (71.7% versus 67.3%, 95% CI -13.1% to 4.5%; P=0.34). Overall, 72.0% of patients were receiving antithrombotic therapy in accordance with the 2001 guidelines of the American College of Chest Physicians, with no difference in the rates between individuals younger than 75 years (72.2%) and those over 75 years of age (71.7%) (absolute difference -0.5%, 95% CI -9.2% to 8.1%). Physician responses to case scenarios indicated that knowledge was high among both general practitioners and specialists regarding the appropriate use of oral anticoagulants for the prevention of thrombotic complications associated with atrial fibrillation. CONCLUSIONS: The appropriate use of oral antithrombotic therapy for the prevention of thrombotic complications of atrial fibrillation occurs in approximately 72% of patients studied in Nova Scotia, and physician knowledge about this indication is high. There was no bias against prescribing oral anticoagulants to elderly patients. The findings suggest that with time, education and evidence have positively impacted the use of antithrombotic therapy in these patients.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.141
Threshold uncertainty score0.281

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.000
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 head0.102
GPT teacher head0.359
Teacher spread0.257 · 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 source (direct Gemma or distilled Codex), 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

Citations15
Published2005
Admission routes2
Has abstractyes

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