BACKGROUND: Because of their high prevalence, chronic respiratory diseases, like asthma and chronic obstructive pulmonary disease, represent main public health problems. They are mainly treated through inhaled therapy. There is low adherence to such therapy, resulting in poor control of chronic respiratory diseases. However, more research is needed on the association of several factors with low adherence. The purpose of this study was to estimate the association of age, sex, type of drug, and frequency of administration with low adherence to inhaled therapy. In order to do this, we performed a cross-sectional study. METHODS: We selected all patients treated with long-acting anticholinergics (LAMA), long-acting ß2-adrenergics (LABA), LAMA/LABA, or inhaled corticosteroid (ICS)/LABA in the Health Area of Lleida on 16 March 2017. For each treatment, we determined the percentage of patients showing low adherence to therapy (less than 50%), calculated as drug boxes collected from the pharmacy with respect to the prescribed ones. Then, we analysed the association of age, sex, type of drug, and frequency of administration, with low adherence to therapy through a multivariate linear model. RESULTS: 11,128 people had electronic prescriptions for one of the inhaled therapy; of them, 24.6% (2,741) showed low adherence. The highest percentage of people with low adherence was found among young patients and women. Women 25-34 years of age included the highest percentage of patients with low adherence. As for drugs, the highest percentage of patients with low adherence was found among the ones treated with LABA and ICS/LABA. Finally, a higher percentage of patients with an administration frequency of 12 h presented low adherence, in comparison with patients treated every 24 h, in general and in the LABA and ICS/LABA groups. CONCLUSIONS: The differences that we observed in adherence to inhaled therapy according to the different factors analysed should be considered when managing chronic respiratory diseases and their impact on patients’ clinical burden, quality of life, and costs for the health system.

BACKGROUND: During the COVID-19 pandemia, the imaging test of choice to diagnose COVID-19 pneumonia as chest computed tomography (CT). However, access was limited in the hospital setting and patients treated in Primary Care (PC) could only access the chest x-ray as an imaging test. Several scientific articles that demonstrated the sensitivity of lung ultrasound, being superior to chest x-ray [Cleverley J et al., BMJ 370, 202013] and comparable to CT scan [Tung-Chen Y et al., Ultrasound Med Biol 46:2918-2926, 2020], promoted the incorporation of this technique in the assessment of COVID-19 patients in PC. [Pérez J et al., Arch. Bronconeumol 56:27-30, 2020; Gargani L et al., Eur Heart J Cardiovasc Imaging 21:941-8, 2020, Soldati G et al., J Ultrasound Med 39:1459, 2020] A prior study in our territory (Lleida, Spain) was designed to predict complications (hospital admission) of COVID-19 pneumonia in PC patients, being different patterns of Lung ultrasounds (LUS) risk factors for hospital admission. [Martínez Redondo J et al., Int J Environ Res Public Health 18:3481, 2021] The rationale for conducting this study lies in the urgent need to understand the determinants of severity and prognosis in COVID-19 patients with interstitial pneumonia, according to its lung ultrasound patterns. This research is crucial to provide a deeper understanding of how these pre-existing ultrasound patterns related to disease progression influence the medical treatment. METHODS: The objective of the study is to generate predictive models of lung ultrasound patterns for the prediction of lung areas characteristics associated with hospitalizations and admissions to the Intensive Care Unit (ICU) associated with COVID-19 disease, using ultrasound, sociodemographic and medical data obtained through the computerized medical history. RESULTS: A single relevant variable has been found for the prediction of hospitalization (number of total regions with potentially pathological presence of B lines) and one for the prediction of ICU admission (number of regions of the right lung with potentially pathological presence of B lines). In both cases it has been determined that the optimal point for classification was 2 or more lung affected areas. Those areas under the curve have been obtained with good predictive capacity and consistency in both cohorts. CONCLUSIONS: The results of this study will contribute to the determination of the ultrasound prognostic value based on the number of lung areas affected, the presence of pulmonary condensation or the irregularity of pleural effusion patterns in COVID-19 patients, being able to be extended to other lung viral infections with similar patterns.

Introduction Type 2 diabetes mellitus (T2DM) is a highly heterogeneous and complex metabolic disease harbouring different metabolic characteristics. Adequate characterisation of subjects is essential to allow the implementation of precision medicine for the prevention, diagnosis, prognosis and treatment of this condition. Methods and analysis This prospective observational cohort study aims to identify and characterise relevant clinical clusters that are reproducibly associated with various clinical outcomes in T2DM in our Mediterranean region. The COPERNICAN study will include 1200 subjects with newly diagnosed T2DM from 28 primary care centres from the city of Barcelona and the healthcare district of Lleida in Catalonia (Spain). Participants will undergo a comprehensive phenotypic evaluation including, among others, six relevant variables: age, antibodies against glutamic acid decarboxylase, body mass index, glycated haemoglobin (HbA1c), indexes of insulin sensibility (HOMA2-IR) and secretion (HOMA2-beta). We will collect additional comprehensive data on glucose-lowering and other drug treatments, clinical evaluation (including complications), laboratory parameters, advanced lipoprotein profile, dietary habits and physical activity. The linkage with the population database will be done to perform a pragmatic follow-up of participants as part of their usual clinical care. A state-of-the-art cluster analysis (k-means and hierarchical clustering) will be performed. Ethics and dissemination The present study complies with all the ethical aspects and protection of participant subjects complying with all current local and European Union legislation. All Ethics Committees from the institutions involved in the study (IR Sant Pau Ethics Committee, Ethics Committee for Drug Research at IDIAP Jordi Gol and University Hospital of Bellvitge Ethics Committee for Research) approved this protocol. Confidentiality and anonymity of the data are ensured according to the current Spanish Organic Law 3/2018 of 05 December.

Background and Objectives: Many studies have analyzed the impact of rurality on the incidence and consequences of COVID-19 infection. However, these studies have not considered the impact of different numbers of nursing homes in rural, semi-urban, or urban areas. Our objective was to analyze the effect of the factor of rurality on the incidence and mortality of COVID-19 while accounting for the impact of the variable of nursing home residency. In addition, we performed a comparative analysis of the infected population in semi-urban and rural areas. Methods: We first analyzed COVID-19 infection in all populations in the Balaguer Primary Health Care Area before examining the impact of rurality using Bayesian logistic regression analysis, specifically excluding the population living in nursing homes. We also performed an epidemiological and clinical analysis comparing rural and semi-urban areas. Results: We found higher incidence of and higher relative and absolute mortality from COVID-19 infection in semi-urban areas than in rural areas. After excluding nursing home residents from our sample, the Bayesian analysis indicated that rurality was not protective against COVID-19 infection or mortality. The incidence rates, specific mortality rates, and case fatality rates were similar in semi-urban and rural areas. All comorbidities, except chronic obstructive pulmonary disease, were associated with higher mortality, while no symptoms were associated with higher mortality. Conclusions: Excluding the population residing in nursing homes from the analysis, we found that rurality was not a protective factor against either infection or mortality during the first COVID-19 wave. Our Bayesian model analysis confirmed that rurality alone did not enhance survival among residents of rural areas.

Background/Objectives: The increasing global prevalence of inflammatory bowel disease (IBD) presents significant challenges to healthcare systems. Our objective was to identify the sociodemographic and clinical characteristics of IBD patients in Catalonia. Methods: A cross-sectional analytical study was carried out on patients diagnosed with IBD in Catalonia (2021). The database of the Information System for the Development of Research in Primary Care of Catalonia was used. Results: In Catalonia, the prevalence of IBD was 474 cases per 100,000 people (pcm), with an average diagnosis age of 42.9 years. Crohn’s disease (CD) represented 34.34% of cases, and 21.2% were smokers and 1% were alcoholics. Nutritional status showed 3% underweight, 36.2% overweight, and 20% obese, with only 0.27% diagnosed as malnutrition. Mental health issues are notable; 36,531 pcm patients were diagnosed with anxiety and 14,656 pcm with depression, and 8.24% had a high risk of mortality measured by the Charlson index. The most prevalent vaccine-preventable infections were influenza (19,356 pcm), herpes zoster (8099 pcm), and varicella zoster (6946 pcm), with 4.56% of patients requiring hospitalisation for one of these reasons and 32.8% of patients for IBD complications, with higher rates observed in cases of CD. Conclusions: The prevalence of IBD was high, especially in urban areas, and patients showed a relevant number of comorbidities. IBD requires a comprehensive evaluation and interdisciplinary management to improve disease control.