The aim of the present study is to identify microRNAs (miRs) with high potential to be used as biomarkers in plasma and/or serum to clinically diagnose, or provide accurate prognosis for survival in, patients with atherosclerosis, coronary artery disease, and acute coronary syndrome (ACS). A systematic search of published original research yielded a total of 72 studies. After review of the risk of bias of the published studies, according to Cochrane Collaboration and the QUADUAS Group standards, 19 studies were selected. Overall 52 different miRs were reported. In particular, miR-133a/b (5 studies), miR-208a/b (6 studies), and miR-499 (7 studies) were well studied and found to be significant diagnostic and/or prognostic markers across different cardiovascular disease progression stages. miR-1 and miR-145b are potential biomarkers of ACS; miR-1 with higher sensitivity for all acute myocardial infarction (AMI), and miR-145 for STEMI and worse outcome of AMI. But when miRs were studied across different ACS study populations, patients had varying degrees of coronary stenosis, which was identified as an important confounder that limited the ability to quantitatively pool the study results. The identified miRs were found to regulate endothelial function and angiogenesis (miR-1, miR-133), vascular smooth muscle cell differentiation (miR-133, miR-145), communication between vascular smooth muscle and endothelial cell to stabilize plaques (miR-145), apoptosis (miR-1, miR-133, miR-499), cardiac myocyte differentiation (miR-1, miR-133, miR-145, miR-208, miR-499), and to repress cardiac hypertrophy (miR-133). Their role in these processes may be explained by regulation of shared RNA targets such as cyclin-dependent kinase inhibitor 1A (or p21), ETS proto-oncogene 1, fascin actin-bundling protein 1, hyperpolarization-activated cyclic nucleotide-gated potassium channel 4, insulin-like growth factor 1 receptor LIM and SH3 protein 1, purine nucleoside phosphorylase, and transgelin 2. These mechanistic data further support the clinical relevance of the identified miRs. miR-1, miR-133a/b, miR-145, miR-208a/b, and miR-499(a) in plasma and/or serum show some potential for diagnosis of cardiovascular disease. However, biased selection of miRs in most studies and unexplained contrasting results are major limitations of current miR research. Inconsistencies need to be addressed in order to definitively identify clinically useful miRs. Therefore, this paper presents important aspects to improve future miR research, including unbiased selection of miRs, standardization/normalization of reference miRs, adjustment for patient comorbidities and medication, and robust protocols of data-sharing plans that could prevent selective publication and selective reporting of miR research outcomes.

Multimorbidity, which is defined as the co-occurrence of two or more chronic conditions, has moved onto the priority agenda for many health policymakers and healthcare providers. Patients with multimorbidity are high utilizers of healthcare resources and are some of the most costly and difficult-to-treat patients in Europe. Preventing and improving the way multimorbidity is managed is now a key priority for many countries, and work is at last underway to develop more sustainable models of care. Unfortunately, this effort is being hampered by a lack of basic knowledge about the aetiology, epidemiology, and risk factors for multimorbidity, and the efficacy and cost-effectiveness of different interventions. The European Commission recognizes the need for reform in this area and has committed to raising awareness of multimorbidity, encouraging innovation, optimizing the use of existing resources, and coordinating the efforts of different stakeholders across the European Union. Many countries have now incorporated multimorbidity into their own healthcare strategies and are working to strengthen their prevention efforts and develop more integrated models of care. Although there is some evidence that integrated care for people with multimorbidity can create efficiency gains and improve health outcomes, the evidence is limited, and may only be applicable to high-income countries with relatively strong and well-resourced health systems. In low- to middle-income countries, which are facing the double burden of infectious and chronic diseases, integration of care will require capacity building, better quality services, and a stronger evidence base.

Patients with multimorbidity have complex health needs but, due to the current traditional disease-oriented approach, they face a highly fragmented form of care that leads to inefficient, ineffective, and possibly harmful clinical interventions. There is limited evidence on available integrated and multidimensional care pathways for multimorbid patients. An expert consensus meeting was held to develop a framework for care of multimorbid patients that can be applied across Europe, within a project funded by the European Union; the Joint Action on Chronic Diseases and Promoting Healthy Ageing across the Life Cycle (JA-CHRODIS). The experts included a diverse group representing care providers and patients, and included general practitioners, family medicine physicians, neurologists, geriatricians, internists, cardiologists, endocrinologists, diabetologists, epidemiologists, psychologists, and representatives from patient organizations. Sixteen components across five domains were identified (Delivery of Care; Decision Support; Self Management Support; Information Systems and Technology; and Social and Community Resources). The description and aim of each component are described in these guidelines, along with a summary of key characteristics and relevance to multimorbid patients. Due to the lack of evidence-based recommendations specific to multimorbid patients, this care model needs to be assessed and validated in different European settings to examine specifically how multimorbid patients will benefit from this care model, and whether certain components have more importance than others.

The correct management of patients with multimorbidity remains one of the main challenges for healthcare systems worldwide. In this study, we analyze the existence of multimorbidity patterns in the general population based on gender and age. We conducted a cross-sectional study of individuals of all ages from the EpiChron Cohort, Spain (1,253,292 subjects), and analyzed the presence of systematic associations among chronic disease diagnoses using exploratory factor analysis. We identified and clinically described a total of 14 different multimorbidity patterns (12 in women and 12 in men), with some relevant differences in the functions of age and gender. The number and complexity of the patterns was shown to increase with age in both genders. We identified associations of circulatory diseases with respiratory disorders, chronic musculoskeletal diseases with depression and anxiety, and a very consistent pattern of conditions whose co-occurrence is known as metabolic syndrome (hypertension, diabetes, obesity, and dyslipidaemia), among others. Our results demonstrate the potential of using real-world data to conduct large-scale epidemiological studies to assess the complex interactions among chronic conditions. This could be useful in designing clinical interventions for patients with multimorbidity, as well as recommendations for healthcare professionals on how to handle these types of patients in clinical practice.