Non-adherence to prescribed medication is a serious limitation of long-term treatment in patients after myocardial infarction (MI), which can be associated with medical, social and economical consequences. Improvement of medication adherence has been shown to be a challenge for healthcare providers. The aim of this study was to evaluate changes in medication adherence and variability of adherence determinants during follow-up in patients after MI. A single-center, cohort observational study was conducted in 225 post-MI patients treated with primary coronary intervention (PCI) (27% women and 73% men) aged 30-91 years. Adherence was defined as availability of evaluated drugs within 1-year after discharge from hospital, based on completed prescriptions data obtained from the National Health Fund. The analysis of therapeutic plan realization (adherence to medication prescribed at discharge from hospital) embraced only reimbursed drugs: ACEIs (ramipril, perindopril), P2Y12 receptor inhibitors (clopidogrel) and statins (atorvastatin, simvastatin, rosuvastatin). Sufficient adherence was defined as ≥ 80%. During 1-year follow-up, adherence for all three drug classes was 64 ± 25%, with 67 ± 32% for ACEIs, 62 ± 34% for P2Y12 receptor inhibitor and 64 ± 32% for statins. A gradual decline in adherence was observed from 65% ± 26% in the first quarter of follow-up to 51% ± 34% in the last quarter of follow-up (p < 0.00001). Sufficient adherence for all drugs classes was found only in 29% of patients throughout the whole follow-up period (44% for ACEI, 36% for P2Y12 receptor inhibitor and 41% for statins). According to a multivariate analysis, age, prior CABG, level of education, place of residence, economic status and marital status were independent predictors of drug adherence. Whereas patients > 65 years and having a history of prior CABG more often had an insufficient adherence to drugs, married and hypertensive patients, city inhabitants and patients with higher education tended to have a sufficient drug adherence. Adherence to pharmacotherapy after myocardial infarction decreases over time in a similar manner for all pivotal groups of drugs prescribed after MI. A number of socioeconomic and clinical factors have been identified to affect medication adherence over time. The long-term treatment of patients after myocardial infarction (MI) is based on implementation of a therapeutic plan including lifestyle changes and pharmacotherapy 1-3. According to the of European Society of Cardiology guidelines for the management of patients with acute myocardial infarction, therapy in this subset of patients includes dual antiplatelet treatment (DAPT) for 12 months, angiotensin-converting enzyme inhibitors (ACEI) or angiotensin receptor blockers (ARB) if ACEI are contraindicated, beta-blockers, and statins 4. However, data available on patient adherence to the therapeutic plan (medication prescribed at discharge from hospital) raise concern. A meta-analysis by Naderi et al. 5 including 20 studies and assessing the extent of adherence ...

Introduction. Patients' adherence to long-term therapies is low. It translates into reduced quality of life and significant deterioration of health economics. Identification of potential barriers of medication-related adherence is a starting point allowing implementation of more advanced interventions directed to adherence improvement. Aim. The purpose of our study was to create and validate a simple instrument used to assess patients' adherence to recommended medications. Material and methods. The Adherence Scale in Chronic Diseases is a self-reported questionnaire with 8 items and with proposed 5 sets of answers. The total score in the Adherence Scale in Chronic Diseases ranges from 0 to 32 points. Three levels of adherence were considered (low: scores of 0 to 20; medium 21 to 25; high > 26). The validation of the questionnaire was conducted in accordance with the validation procedure. Assessment of the internal consistency was performed using a-Cronbach coefficient. In order to conduct the factor analysis, we assessed: the determinant of correlation matrix, Kaiser-Mayer-Olkin (K-M-O) statistic and the Bartlett's test of sphericity. Factor analysis was conducted using principal component analysis with Oblimin rotation. The Kaiser criterion and scree plot were used in order to determine components of the questionnaire. Adherence levels were determined based on the percentiles. Results. Grand total of 413 patients with a cardiovascular disease were included in the study. The reliability and homogeneity of the questionnaire were confirmed by a-Cronbach coefficient (0.739). Factor analysis showed that in this questionnaire we can extract two components. The analysis of factor loadings indicated excluding item 2 from the questionnaire. After exclusion of the mentioned item, we repeated the validation procedure. For such a new dataset, according to the Kaiser criterion, only one component was extracted. Conclusions. The Adherence Scale in Chronic Diseases is a practical, reliable, consistent and well validated instrument for identifying specific obstacles to medication adherence. Its simplicity causes that it can be successfully applied in daily practice by health care professionals. Our survey has the potential to improve patient-health care professional communication and relationship.

Morning increase in the occurrence of myocardial infarction, stroke and sudden cardiac death is a well-recognized phenomenon, which is in line with a morning enhancement of platelet aggregation. We investigated whether platelet inhibition during clopidogrel and aspirin therapy varies during the day. Fifty-nine consecutive patients (45 men and 14 women) with first ST-segment elevation myocardial infarction (STEMI) treated with primary percutaneous coronary interventions (pPCI) on dual antiplatelet therapy were prospectively enrolled into the study. Blood samples were collected 4 days after start of clopidogrel treatment at 6.00 a.m., 10.00 a.m., 2.00 p.m. and 7.00 p.m. Arachidonic acid and adenosine diphosphate (ADP)-induced platelet aggregation were assessed by impedance aggregometry. Platelet inhibition by clopidogrel was lowest in the midmorning: median ADP-induced platelet aggregation was 55%, 17% and 27% higher at 10.00 a.m. compared to 6.00 a.m., 2.00 p.m. and 7.00 p.m., respectively (p < 0.002). Nonresponsiveness to clopidogrel defined according to the device manufacturer was 2.4-fold more frequent in the midmorning than in the early morning. We observed a more pronounced midmorning increase in ADP-induced platelet aggregation in diabetic patients when compared to non-diabetics. In contrast, no diurnal variation in the antiplatelet effect of aspirin was observed. In conclusion, in patients presenting with STEMI undergoing pPCI, platelet inhibition by clopidogrel is less strong in the midmorning hours. This periodicity in platelet aggregation in patients on dual antiplatelet therapy should be taken into consideration when assessing platelet function in clinical studies.

Diagnosis of deficient areas in the functioning of patient with chronic disease is necessary to undertake the adequate therapeutic actions. The aim of the study was to validate a new self-reported questionnaire for patients with chronic disease assessing the impact of the disease on the patient, the patient's impact on the disease and the impact of the disease on patient's attitudes. Results: The internal consistency of the questionnaire expressed by a-Cronbach coefficient = 0.855, indicates its high reliability and homogeneity. The set of 24 items fulfilled the assumption of factor analysis: the determinant of correlation matrix was 0.001, Kaiser-Mayer-Olkin (K-M-O) statistic was 0.843 and the Bartlett' test of sphericity was statistically significant. The factor analysis was conducted using the principal component analysis with Varimax rotation. The scale and subscale levels were determined based on the percentiles scale. Conclusion: The validation procedure revealed that FCIS is a reliable and homogeneous tool to measure patient's physical and mental functioning in the chronic illness. The set of items divided into 3 subscales allows evaluation of: the impact of the disease on the patient, the patient's impact on the disease and the impact of the disease on the patient's attitudes.