STATIN ADHERENCE IN REAL CLINICAL PRACTICE
Bibliographic record
Abstract
Objective: To study statin adherence and factors associated with in real clinical practice. Design and method: 53 statin taking patients with multimorbidity during their hospitalization were included. Mean age was 68,1 ± 10,2 years. All participants completed general questionnaires containing questions about their comorbidity and knowledge about statins, HADS (Hospital Anxiety and Depression Scale) and MoCa (The Montreal Cognitive Assessment) scale. Adherence was assessed by original questionare. Statistica 10.0 software was used for data management and statistical analysis. Results: 50,9% of patients were non-adherent, 22,6% were adherent, and 26,4% had insufficient adherence. 67,9% of respondents had some knowledge about statins, 32% had lack of information. Among informed patients answers of 91,7%, were correct, 8,3% had wrong information. 34,0% of patients took prescribed therapy for less than a year, 9,4% - from 1 year to two years, 22,6% - from 2 to 5 years, 17,0% - more than 5 years, the longest period of statin intake was 13 years. Long-standing course of statin administration (r = -0,30), level of total cholesterol (r = -0,30) and body mass index (BMI) (r = 0,28) were correlated with the score of adherence questionare. Patient awareness about statins were associated with gender (r = -0,33), smoking (r = -0,35), family history of cardiovascular diseases (r = 0,43), anxiety (r = 0,35), comorbidity (r = 0,41), initial insomnia (r = 0,38), sleeping quality disorder (r = 0,33), grade of hypertension (r = 0,39). There was correlation between correct patient knowledge and scores on the Moca scale (r = 0,46). Conclusions: About a half of all respondents were non-adherent to statin therapy and adherence of one-third was insufficient. Adherence to therapy was associated with the duration of taking statins, levels of total cholesterol and BMI. Due to the received correlations it was possible to identify male gender and smoking as markers of low awareness. Presence of family history of cardiovascular diseases, anxiety, comorbidity, initial insomnia and sleeping quality disorder, grade of hypertension were positively correlated with awareness about statins. Correct information about statins were also associated with the cognitive functions level.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".