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Comparing Medication Adherence Tools for the Direct Oral Anticoagulants Rivaroxaban and Apixaban

2017· article· en· W2788028374 on OpenAlexaffabout
Lana A. Castellucci, Philip Chiang, Amanda Pecarskie, Grégoire Le Gal, Marc Rodger

Bibliographic record

VenueBlood · 2017
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsApixabanRivaroxabanMedicineDosingPillMedical prescriptionAnticoagulantRandomized controlled trialPharmacyInternal medicineEmergency medicineWarfarinAtrial fibrillationPharmacology

Abstract

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Abstract Introduction: Predictable pharmacokinetics and fixed dosing regimens of direct oral anticoagulants (DOACs) have simplified venous thromboembolism (VTE) treatment. Rivaroxaban and apixaban both target Factor Xa, yet an important difference lies in their dosing frequency. The impact of twice daily vs once daily DOAC dosing on adherence, and the potential differences on clinical efficacy and safety are unknown. Medication adherence was evaluated in the COBRRA (COmparison of Bleeding Risk between Rivaroxaban and Apixaban) Pilot study (NCT02559856). Aim: We compared anticoagulation adherence in patients with acute VTE using three different medication adherence assessment tools of variable cost. Methods: Patients with acute VTE were randomized to apixaban (10 mg twice daily for one week, then 5 mg twice daily) or rivaroxaban (15 mg twice daily for 3 weeks, then 20 mg daily). Participants at the sponsor site (The Ottawa Hospital) had anticoagulation adherence measured using eCAP™, medication diaries, and pill counts. eCAP™ is an electronic prescription bottle cap that records each time the vial is opened to take a tablet. The information was downloaded to a desktop reader at follow up visits to determine medication adherence. Medication diaries were completed by patients and recorded date and time of taking anticoagulant. Pill counts were conducted by the research coordinator at follow up visits and adherence was determined using the following calculation: number of pills taken/number of pills dispensed. Anticoagulation adherence was assessed at day 30 and end of treatment. Measurements of Results: Forty patients were enrolled and data is available for 39. Twenty patients were randomized to apixaban with mean age 59 years; 19 patients were randomized to rivaroxaban and had mean age of 64 years. In patients receiving twice daily apixaban, all adherence tools demonstrated similar anticoagulation adherence rates at day 30 follow up with mean of 95.7% for eCAP™, 97% for diaries, and 97.8% by pill count. End of treatment measures were also similar: 91.1%, 98%, and 90.4%, respectively. All three tools showed comparable adherence rates at 30 days with mean of 99.3% by eCAP™, 97.5% with diaries, and 99.4% by pill counts in patients on rivaroxaban treatment. By end of treatment, anticoagulation adherence rates were similar between different measurement tools: 95.8%, 97.5%, and 99.5%, respectively (Table 1). Conclusions: In patients with acute VTE, anticoagulation adherence rates were comparable regardless of the adherence assessment tool used. We also demonstrated that simple tools such as medication diaries and pill counts are comparable to expensive electronic device measures. Download : Download high-res image (155KB) Download : Download full-size image Disclosures Castellucci: BMS: Honoraria; Bayer: Honoraria; Leo Pharma: Honoraria; Boehringer-Ingelheim: Honoraria; Pfizer: Honoraria. Le Gal: Bayer: Honoraria; BMS: Honoraria.

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)0.007
metaresearch head score (Gemma)0.014
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 score0.007
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.690
GPT teacher head0.579
Teacher spread0.112 · 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".

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Citations1
Published2017
Admission routes2
Has abstractyes

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