Relationship Between Anticoagulant Medication Adherence and Satisfaction in Patients With Stroke
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Bibliographic record
Abstract
AIM: The aim of this study was to investigate the accuracy of the self-reported measure of adherence and the relation between adherence to warfarin use, demographic and clinical variables, and the satisfaction with the treatment in patients affected by stroke. METHODS: This is a correlational, quantitative, and cross-sectional study, carried out in the outpatient clinics of a public university hospital from October 2017 to April 2018. Sociodemographic and clinical data were collected through interviews and hospital charts, as well as by applying the Measurement of Treatment Adherence (MTA) and the Duke Anticoagulation Satisfaction Scale, in their Brazilian versions. Results of the international normalized ratio (INR) were collected. Measurements of accuracy of the MTA scale were calculated in relation to the INR classification. RESULTS: Of 99 patients (55.6% male with a mean age of 58.6 years), 57.6% presented with therapeutic INR values and 75.8% of the patients were adherent to the oral anticoagulant therapy according to the MTA. The accuracy analysis of the measurement provided by the MTA scale in relation to the INR classification showed a sensitivity of 77.2% and a specificity of 26.2%. The patients' satisfaction with the treatment was high. The Duke Anticoagulation Satisfaction Scale had an average total score of 46.4, with the dimension impact in the field having the highest score (20.3). CONCLUSION: Stroke patients were adherent and satisfied with the oral anticoagulant therapy. The MTA had good sensitivity and poor specificity. Sociodemographic and clinical characteristics identified were not associated with adherence and satisfaction with treatment.
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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 | 0.000 | 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 it