Adherence to therapy, lifestyle modification and medical support of cardiovascular patients
Bibliographic record
Abstract
Ai m . To study the quantitative parameters of adherence to lifestyle modification, medical support, and therapy in patients with cardiovascular diseases (CVD). Materia l and methods. This cross-sectional study included 683 respondents: 168 patients with hypertension (HTN); 196 patients with stable angina; 141 patients with atrial fibrillation (AF); 178 patients with heart failure (HF). We used N. A. Nikolaev questionnaire for adherence assessment. For all adherence parameters, the level ≤75% was regarded as insufficient. The study was carried out in accordance with Good Clinical Practice and Declaration ofHelsinki. The study protocol was approved by the Ethics Committees of all participating clinical centers. All patients signed written informed consent. R e sult s . Approximately 1/3 of respondents agreed to receive therapy. The adherence level was >75%. Patients with angina and AF were more likely to receive therapy. It turned out that that approximately 2/3 of patients were not ready for medical support. Patients with angina were less ready for medical support, while those with HTN and HF hadhigher values of adherence. Adherence to lifestyle modification was owest among analyzed parameters. Only 18,5% of hypertensive patients, 25,5% of patients with angina, 26,2% of AF patients and 23,1% of patients with HF were ready to change the lifestyle. Conclusion . The study revealed a significant number (~2/3) of CVD patients with insufficient adherence, which specifies the need to assess the effectiveness of therapy and course of the disease in conditions of low adherence and to develop individualized therapeutic strategies.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".