We assessed the impact of the COVID-19 pandemic in Spain on new cases of diseases and conditions commonly seen in primary care. In 2020, there were significant reductions from 2017-2019 in the annual incidences of hypertension (40% reduction), hypercholesterolemia (36%), type 2 diabetes (39%), chronic kidney disease (43%), ischemic heart disease (48%), benign prostatic hypertrophy (38%), osteoporosis (40%), hypothyroidism (46%), chronic obstructive pulmonary disease (50%), alcohol use disorder (46%), benign colon polyps and tumors (42%), and melanomas (45%). Prioritization of COVID-19 care changed the physician-patient relationship to the detriment of face-to-face scheduled visits for chronic disease detection and monitoring, which fell by almost 41%. To return to prepandemic levels of diagnosis and management of chronic diseases, primary health care services should reorganize and carry out specific actions for groups at higher risk.

We determined the feasibility of abdominal aortic aneurysm (AAA) screening program led by family physicians in public primary healthcare setting using hand-held ultrasound device. The potential study population was 11,214 men aged ≥ 60 years attended by three urban, public primary healthcare centers. Participants were recruited by randomly-selected telephone calls. Ultrasound examinations were performed by four trained family physicians with a hand-held ultrasound device (Vscan^®). AAA observed were verified by confirmatory imaging using standard ultrasound or computed tomography. Cardiovascular risk factors were determined. The prevalence of AAA was computed as the sum of previously-known aneurysms, aneurysms detected by the screening program and model-based estimated undiagnosed aneurysms. We screened 1,010 men, with mean age of 71.3 (SD 6.9) years; 995 (98.5%) men had normal aortas and 15 (1.5%) had AAA on Vscan^®. Eleven out of 14 AAA-cases (78.6%) had AAA on confirmatory imaging (one patient died). The total prevalence of AAA was 2.49% (95%CI 2.20 to 2.78). The median aortic diameter at diagnosis was 3.5 cm in screened patients and 4.7 cm (p<0.001) in patients in whom AAA was diagnosed incidentally. Multivariate logistic regression analysis identified coronary heart disease (OR = 4.6, 95%CI 1.3 to 15.9) as the independent factor with the highest odds ratio. A screening program led by trained family physicians using hand-held ultrasound was a feasible, safe and reliable tool for the early detection of AAA.

The objective was to estimate the prevalence of chronic widespread pain (CWP) and compare the quality-of-life (QoL), cardiovascular risk factors, comorbidity, complexity, and health costs with the reference population. A multicenter case-control study was conducted at 3 primary care centers in Barcelona between January and December 2012: 3048 randomized patients were evaluated for CWP according to the American College of Rheumatology definition. Questionnaires on pain, QoL, disability, fatigue, anxiety, depression, and sleep quality were administered. Cardiovascular risk and the Charlson index were calculated. We compared the complexity of cases and controls using Clinical Risk Groups, severity and annual direct and indirect health care costs. CWP criteria were found in 168 patients (92.3% women, prevalence 5.51% [95% confidence interval: 4.75%-6.38%]). Patients with CWP had worse QoL (34.2 vs 44.1, P < 0.001), and greater disability (1.04 vs 0.35; P < 0.001), anxiety (43.9% vs 13.3%; P < 0.001), depression (27% vs 5.8%; P < 0.001), sleep disturbances, obesity, sedentary lifestyle, high blood pressure, diabetes mellitus, and number of cardiovascular events (13.1% vs 4.8%; P = 0.028) and higher rates of complexity, severity, hospitalization, and mortality. Costs were &OV0556;3751 per year in patients with CWP vs &OV0556;1397 in controls (P < 0.001). In conclusion, the average patient with CWP has a worse QoL and a greater burden of mental health disorders and cardiovascular risk. The average annual cost associated with CWP is nearly 3 times higher than that of patients without CWP, controlling for other clinical factors. These findings have implications for disease management and budgetary considerations.

. The 13-item Patient Activation Measure (PAM-13) is an instrument that assesses people’s knowledge, skills and confidence for self-management of their health and health care. Scores on the PAM-13 have been shown to predict adherence to health behaviours, health-related outcomes and health care costs. . To develop a European Spanish adaptation of the original PAM-13 and to examine its psychometric properties in a sample of chronic patients. . The PAM-13 was forward-backward translated and then completed by chronic patients attending a primary health care centre. Data were analysed with a Rasch model. We assessed the functioning of the rating scale, its reliability, the item goodness-of-fit, differential item functioning (DIF), local dependence, unidimensionality and correlation analysis. . A total of 208 patients (80%) completed the questionnaire. Data showed a fit to the Rasch model. More than 50% of patients endorsed all the items. Item rank for the Spanish sample was similar to the original, with few differences. We found significant differences (P < 0.05) in PAM-13 measures according to adherence to prescribed medicines and positive correlations with self-efficacy and physical quality of life. . The European Spanish PAM-13 is a reliable and valid instrument for assessing activation in patients with chronic disease in Spain. We suggest adding new items to the instrument so as to examine patients with higher activation levels in the future. Further studies are needed to evaluate the usefulness of this new Spanish PAM-13 in different settings and populations, as well as to examine the relationship between PAM-13 scores and other health-related outcomes.

TCF7L2 is the susceptibility gene for Type 2 diabetes (T2D) with the largest effect on disease risk that has been discovered to date. However, the mechanisms by which TCF7L2 contributes to the disease remain largely elusive. In addition, epigenetic mechanisms, such as changes in DNA methylation patterns, might have a role in the pathophysiology of T2D. This study aimed to investigate the differences in terms of DNA methylation profile of TCF7L2 promoter gene between type 2 diabetic patients and age- and Body Mass Index (BMI)- matched controls. We included 93 type 2 diabetic patients that were recently diagnosed for T2D and exclusively on diet (without any pharmacological treatment). DNA was extracted from whole blood and DNA methylation was assessed using the Sequenom EpiTYPER system. Type 2 diabetic patients were more insulin resistant than their matched controls (mean HOMA IR 2.6 vs 1.8 in controls, P<0.001) and had a poorer beta-cell function (mean HOMA B 75.7 vs. 113.6 in controls, P<0.001). Results showed that 59% of the CpGs analyzed in TCF7L2 promoter had significant differences between type 2 diabetic patients and matched controls. In addition, fasting glucose, HOMA-B, HOMA-IR, total cholesterol and LDL-cholesterol correlated with methylation in specific CpG sites of TCF7L2 promoter. After adjustment by age, BMI, gender, physical inactivity, waist circumference, smoking status and diabetes status uniquely fasting glucose, total cholesterol and LDL-cholesterol remained significant. Taken together, newly diagnosed, drug-naïve type 2 diabetic patients display specific epigenetic changes at the TCF7L2 promoter as compared to age- and BMI-matched controls. Methylation in TCF7L2 promoter is further correlated with fasting glucose in peripheral blood DNA, which sheds new light on the role of epigenetic regulation of TCF7L2 in T2D.

Prediabetes and old age are both high risk factors for developing Type 2 Diabetes (T2D), while obesity is one of the most important factors triggering the disease. Nutritional interventions are the most effective tool for preventing T2D, as they improve different biochemical and anthropometric outcomes and growth-promoting/inhibiting gut microbiota populations. However, to date there are no specific dietary recommendations to stop the development of T2D in elderly groups, for whom hypocaloric diets and other commonly used weight-loss programs could be considered dangerous. The objective of our study, thus, was to understand the impact of dietary patterns on T2D risk as related to gut microbiota profile in obese and non-obese elderly prediabetic subjects. A cross-sectional study was performed in 182 subjects ≥65 years old with prediabetes, divided into obese (OB) or non-obese (NOB) subgroups, and their risk of developing T2D was measured according to FINDRISK score and biochemical parameters. Also, clusters into different dietary patterns in each group by PCA analysis was related with gut microbiota, which was analyzed from stool samples by qPCR. The creation of clusters was used to re-evaluate T2D risk. OB was at higher risk of developing T2D and showed worse metabolic outcomes. Unhealthier and healthier dietary pattern clusters were observed for both OB (OB-6 and OB-5 respectively) and NOB (NOB-2 and NOB-3 respectively) groups. Results obtained from the gut microbiota showed that only Prevotella was higher in NOB, but when comparisons were made between clusters, a clear relation with dietary pattern was observed; showing in healthier dietary clusters a decrease in Prevotella, an increase of Faecalibacterium prausnitzii and an increase in lactic acid bacteria. T2D risk was greater in the obese group between unhealthier dietary clusters. No difference between healthier dietary clusters was observed. A healthy dietary pattern and the growth-promoting beneficial and growth-inhibiting disadvantageous gut microbiota populations linked to it provide protection against the development of T2D in an obese population with advanced age and preDM.