Type-2 diabetes mellitus (T2DM) is a chronic metabolic disorder. The incidence and prevalence of patients with T2DM are increasing worldwide, even reaching epidemic values in most high- and middle-income countries. T2DM could be a risk factor of developing complications in other diseases. Indeed, some studies suggest a bidirectional interaction between T2DM and COVID-19. A growing body of evidence shows that COVID-19 prognosis in individuals with T2DM is worse compared with those without. Moreover, various studies have reported the emergence of newly diagnosed patients with T2DM after SARS-CoV-2 infection. The most common treatments for T2DM may influence SARS-CoV-2 and their implication in infection is briefly discussed in this review. A better understanding of the link between TD2M and COVID-19 could proactively identify risk factors and, as a result, develop strategies to improve the prognosis for these patients.

Atherosclerosis is a chronic inflammatory and degenerative process that mainly occurs in large- and medium-sized arteries and is morphologically characterized by asymmetric focal thickenings of the innermost layer of the artery, the intima. This process is the basis of cardiovascular diseases (CVDs), the most common cause of death worldwide. Some studies suggest a bidirectional link between atherosclerosis and the consequent CVD with COVID-19. The aims of this narrative review are (1) to provide an overview of the most recent studies that point out a bidirectional relation between COVID-19 and atherosclerosis and (2) to summarize the impact of cardiovascular drugs on COVID-19 outcomes. A growing body of evidence shows that COVID-19 prognosis in individuals with CVD is worse compared with those without. Moreover, various studies have reported the emergence of newly diagnosed patients with CVD after COVID-19. The most common treatments for CVD may influence COVID-19 outcomes. Thus, their implication in the infection process is briefly discussed in this review. A better understanding of the link among atherosclerosis, CVD, and COVID-19 could proactively identify risk factors and, as a result, develop strategies to improve the prognosis for these patients.

Objectives: To develop an algorithm to identify pregnancy episodes in women at childbearing age using SIDIAP (Information System for the Improvement of Research in Primary Care) data (Catalunya, Spain). To describe drugs dispensed during gestation. Design: Construction of an algorithm to identify all pregnancy episodes occurred from January 2011 to June 2020 in women aged 12–50. The variables used to create the algorithm include first day of last menstrual period, reasons for pregnancy termination and diagnoses registered in the primary healthcare records. Population-based cohort study including the pregnancy episodes identified by the algorithm. Setting: Catalonia, Spain. Participants: All women aged 12–50 with at least one pregnancy episode occurred during January 2011–June 2020. Interventions: No interventions performed. Primary and secondary outcome measures: Identification of pregnancy episodes through an algorithm and description of drug exposure. Results: We identified 327 865 pregnancy episodes in 250 910 people with a mean age of 31.3 years. During the study period, 83.4% of the episodes were exposed to at least one drug. The most frequent groups dispensed were iron preparations (48% of pregnancy episodes), iodine therapy (40.2%), analgesics and antipyretics (28%), penicillins (19.8%), vitamin B₁₂ plus folic acid (19.7%) and non-steroidal anti-inflammatory drugs (NSAIDs, 15.1%). The supplements were more frequently dispensed at least twice, and the drugs for acute conditions were mainly dispensed only once during the pregnancy episode. Conclusions: We developed an algorithm to automatically identify the pregnancy periods in SIDIAP. We described prescription drugs used during pregnancy. The most used ones were supplements, analgesics, NSAID or antibiotics. SIDIAP might be an efficient database to study drug safety during pregnancy and the consequences of drug use in the offspring. Trial registration number: EUPAS37675.

Background: Adherence problems have negative effects on health, but there is little information on the magnitude of non-initiation and single dispensing. Objective: The aim of this study was to estimate the prevalence of non-initiation and single dispensation and identify associated predictive factors for the main treatments prescribed in Primary Care (PC) for cardiovascular disease (CVD) and diabetes. Methods: Cohort study with real-world data. Patients who received a first prescription (2013–2014) for insulins, platelet aggregation inhibitors, angiotensin-converting enzyme inhibitors (ACEI) or statins in Catalan PC were included. The prevalence of non-initiation and single dispensation was calculated. Factors that explained these behaviours were explored. Results: At three months, between 5.7% (ACEI) and 9.1% (antiplatelets) of patients did not initiate their treatment and between 10.6% (statins) and 18.4% (ACEI) filled a single prescription. Body mass index, previous CVD, place of origin and having a substitute prescriber, among others, influenced the risk of non-initiation and single dispensation. Conclusions: The prevalence of non-initiation and single dispensation of CVD medications and insulin prescribed in PC in is high. Patient and health-system factors, such as place of origin and type of prescriber, should be taken into consideration when prescribing new medications for CVD and diabetes.

Background: A possible link between influenza immunization and susceptibility to the complications of COVID-19 infection has been previously suggested owing to a boost in the immunity against SARS-CoV-2. Objective: This study aimed to investigate whether individuals with COVID-19 could have benefited from vaccination against influenza. We hypothesized that the immunity resulting from the previous influenza vaccination would boost part of the immunity against SARS-CoV-2. Methods: We performed a population-based cohort study including all patients with COVID-19 with registered entries in the primary health care (PHC) electronic records during the first wave of the COVID-19 pandemic (March 1 to June 30, 2020) in Catalonia, Spain. We compared individuals who took an influenza vaccine before being infected with COVID-19, with those who had not taken one. Data were obtained from Information System for Research in Primary Care, capturing PHC information of 5.8 million people from Catalonia. The main outcomes assessed during follow-up were a diagnosis of pneumonia, hospital admission, and mortality. Results: We included 309,039 individuals with COVID-19 and compared them on the basis of their influenza immunization status, with 114,181 (36.9%) having been vaccinated at least once and 194,858 (63.1%) having never been vaccinated. In total, 21,721 (19%) vaccinated individuals and 11,000 (5.7%) unvaccinated individuals had at least one of their outcomes assessed. Those vaccinated against influenza at any time (odds ratio [OR] 1.14, 95% CI 1.10-1.19), recently (OR 1.13, 95% CI 1.10-1.18), or recurrently (OR 1.10, 95% CI 1.05-1.15) before being infected with COVID-19 had a higher risk of presenting at least one of the outcomes than did unvaccinated individuals. When we excluded people living in long-term care facilities, the results were similar. Conclusions: We could not establish a protective role of the immunity conferred by the influenza vaccine on the outcomes of COVID-19 infection, as the risk of COVID-19 complications was higher in vaccinated than in unvaccinated individuals. Our results correspond to the first wave of the COVID-19 pandemic, where more complications and mortalities due to COVID-19 had occurred. Despite that, our study adds more evidence for the analysis of a possible link between the quality of immunity and COVID-19 outcomes, particularly in the PHC setting.