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Morphine and P2Y12 receptor inhibitors are both recommended in patients with acute myocardial infarction. Morphine may impede gastrointestinal absorption of several oral drugs including P2Y12 platelet receptor inhibitors. The aim of this review was to critically discuss drug-drug interactions between oral P2Y12 receptor inhibitors and morphine according to currently available knowledge based on the findings of experimental, observational and randomized clinical studies. The morphine-clopidogrel pharmacodynamic interaction has been observed in numerous trials and it has been proposed as an explanation for the negative impact of morphine on the clinical outcomes in patients with acute coronary syndromes. An analogous morphine interaction with ticagrelor and prasugrel was found in several observational studies and finally proven in randomized trials in healthy volunteers and acute myocardial infarction patients. Morphine delays and attenuates exposure and antiplatelet action of oral P2Y12 receptor inhibitors in patients with myocardial infarction. Although this interaction may have potentially harmful consequences, routine avoidance of morphine cannot be recommended until clinically powered trials are completed.

Antiplatelet agents are the mainstay treatment in the prevention and management of atherothrombotic complications. However, a substantial interpatient variability in response to clopidogrel has been reported. Furthermore, patients with coronary artery disease and lesser platelet inhibition in response to clopidogrel are at increased risk for cardiovascular events. Clopidogrel after absorption requires two-step oxidation by the hepatic cytochrome P450 to generate its active metabolite. Polymorphisms of genes encoding the cytochrome enzymes and P-glycoprotein involved in clopidogrel absorption are regarded as major determinants of the interindividual variability in the clopidogrel-induced platelet inhibition. In our review we discuss the prevalence and clinical significance of various alleles of the genes: CYP2C19 and ABCB1 in the setting of coronary artery disease. Allele CYP2C19*2 is associated with excess of ischaemic events including myocardial infarction and stent thrombosis. On the other hand, CYP2C19*17 allele poses a serious threat of bleeding. Data concerning the prognostic value of genetic variant 3435C→T of ABCB1 remain inconclusive.

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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 ...

The poor response to clopidogrel is multifactorial and includes, amongst others, low patient adherence to medication. The aim of this study was to assess the reported patient adherence to treatment with clopidogrel and confront it with adherence assessed by drug availability. We evaluated determinants of adherence and its impact on platelet aggregation and clinical outcome. The study population comprised 184 patients treated with primary percutaneous coronary intervention for acute myocardial infarction. Follow-up visits were scheduled at 3, 6 and 9 months after discharge. Patient adherence to clopidogrel was defined according to self-reported drug intake and verified based on data from the National Health Fund regarding the purchase of prescribed drugs. The patients were judged as adherent when the proportion of drug availability exceeded 80%. According to drug availability, 100 (54.3%) patients were adherent and 84 (45.7%) were nonadherent. The analysis identified the following factors as predictors of low adherence (<80%): adenosine diphosphate-induced platelet aggregation (ADP-PA) during hospitalization ≤45 U, male gender and occurrence of ST-elevation myocardial infarction [(STEMI) vs. non-STEMI (NSTEMI)], while three-vessel disease was predictive of high adherence to medication. Compared with drug availability-based assessment, self-reported drug intake was significantly different: 172 (94.5%) patients reported regular and 10 (5.5%) patients reported irregular intake of clopidogrel. Clinical follow-up suggested that the self-reported nonregular clopidogrel intake may discriminate patients with a high risk of cardiovascular events. We demonstrated a huge discrepancy between the two most widely used methods for the evaluation of adherence to clopidogrel in secondary prevention treatment in patients after STEMI and NSTEMI. ADP-PA during hospitalization ≤45 U, male gender and STEMI (vs. NSTEMI) were independent predictors of nonadherence while three-vessel disease was independently predictive of adherence to treatment with clopidogrel in the investigated population.

Background: The highest priority in preventive cardiology is given to patients with established coronary artery disease (CAD). The aim of the study was to assess the current implementation of the guidelines for secondary prevention in everyday clinical practice by evaluating control of the main risk factors and the cardioprotective medication prescription rates in patients following hospitalization for CAD. Methods: Fourteen departments of cardiology participated in the study. Patients (aged ≤ 80 years) hospitalized due an acute coronary syndrome or for a myocardial revascularization procedure were recruited and interviewed 6-18 months after the hospitalization. Results: Overall, 947 patients were examined 6-18 months after hospitalization. The proportion of patients with high blood pressure (≥ 140/90 mmHg) was 42%, with high low-density lipoprotein cholesterol (LDL-C ≥ 1.8 mmol/L) 62%, and with high fasting glucose (≥ 7.0 mmol/L) 22%, 17% of participants were smokers and 42% were obese. The proportion of patients taking an antiplatelet agent 6-18 months after hospitalization was 93%, beta-blocker 89%, angiotensin converting enzyme inhibitor or sartan 86%, and a lipid-lowering drug 90%. Only 2.3% patients had controlled all the five main risk factors well (non-smoking, blood pressure < 140/90 mmHg, LDL-C < 1.8 mmol/L and glucose < 7.0 mmol/L, body mass index < 25 kg/m 2), while 17.9% had 1 out of 5, 40.9% had 2 out of 5, and 29% had 3 out of 5 risk factors uncontrolled. Conclusions: The documented multicenter survey provides evidence that there is considerable potential for further reductions of cardiovascular risk in CAD patients in Poland. A revision of the state funded cardiac prevention programs seems rational.

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.