Appropriateness of Dabigatran and Rivaroxaban Prescribing in Qatar: A 5-Year Experience
Bibliographic record
Abstract
INTRODUCTION: Over the past few years, direct oral anticoagulants (DOACs) have been gradually replacing warfarin. Inappropriate prescribing of DOACs in real-life practice settings can affect their perceived safety and efficacy, especially with the lack of a surrogate marker for guidance. OBJECTIVES: To describe the appropriateness of DOACs prescribing, compare dabigatran to rivaroxaban in terms of inappropriate prescribing, and determine other factors associated with inappropriate DOACs use. METHODS: In this cross-sectional retrospective study, 5-year DOAC prescriptions data were extracted. Appropriateness was evaluated based on approved dosing and indications in Canada and the United States. Descriptive and inferential statistics were performed using SPSS. RESULTS: From 2011 to 2015, there were 1049 DOACs prescriptions, among which 572 (54.5%) were for dabigatran and 477(45.5%) were for rivaroxaban. The DOACs were prescribed for inappropriate indication in 35 (3.3%) patients, while inappropriate dosing was found in 352 (33.6%) prescriptions. There were significantly more inappropriate dabigatran prescriptions compared to rivaroxaban both in terms of indication (4.7% vs 1.7%, P = .004) and dosing (50.9% vs 12.8%, P < .001). Logistic regression analysis confirmed that dabigatran prescribing was the only factor associated with inappropriate indications (odds ratio [OR] = 2.9, 95% confidence interval [CI]: 1.3-6.5). Factors associated with inappropriate dosing included dabigatran prescriptions (OR = 7.6, 95% CI: 5.5-10.5) and poor renal function (OR = 14.6, 95% CI: 3.6-58.4). CONCLUSION: Direct oral anticoagulants have been gradually replacing warfarin in Qatar; however, they are not always prescribed appropriately especially in patients on dabigatran and those with renal impairment. Educating health-care practitioners is necessary. Future studies comparing the clinical safety and effectiveness of the DOACs especially when used at an inappropriate dose are also warranted.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".