Virtual Consultation in Dermatology: Access Inequalities According to Socioeconomic Characteristics and the Place of Residence.

Virtual consultation has been implemented as a tool to improve the cooperation and coordination between primary care and other specialties. However, in its use in dermatology, inequities have been described. The aim of this study was to identify individual and geographical factors affecting the likelihood of accessing this resource. We conducted a cross-sectional study. The study population was individuals living in Aragón, a region in the north-east of Spain, who were users of the Aragon Health Service in 2021. To explore the differences in individual and area characteristics, between patients with virtual and non-virtual dermatology consultation, we performed bivariate analyses. To analyse the use of virtual consultation in dermatology, a multilevel methodology stratified by sex was developed. We analysed 39,174 dermatology visits, with 16,910 being virtual (43.17%). The rates of virtual consultation were higher in urban areas and the most affluent areas, for older persons, chronic complex patients and people with more advantageous socioeconomic positions. The best multilevel model conducted showed inequalities by socioeconomic position and area of residence. There are individual and area inequalities in the use of teledermatology. As this tool should improve equity of access, teledermatology interventions must address and adapt to the needs of the local patient population.

Exploring sex variations in the incidence of cardiovascular events: a counterfactual decomposition analysis.

BACKGROUND: Some cardiovascular risk factors (CVRFs) that occur differently in men and women can be addressed to reduce the risk of suffering a major adverse cardiovascular event (MACE). Furthermore, the development of MACE is highly influenced by social determinants of health. Counterfactual decomposition analysis is a new methodology that has the potential to be used to disentangle the role of different factors in health inequalities. This study aimed to assess sex differences in the incidence of MACE and to estimate how much of the difference could be attributed to the prevalence of diabetes, hypertension, hypercholesterolaemia and socioeconomic status (SES). METHODS: Descriptive and counterfactual analyses were conducted in a population of 278 515 people with CVRFs. The contribution of the causal factors was estimated by comparing the observed risk ratio with the causal factor distribution that would have been observed if men had been set to have the same factor distribution as women. The study period was between 2018 and 2021. RESULTS: The most prevalent CVRF was hypercholesterolaemia, which was similar in both sexes, while diabetes was more prevalent in men. The incidence of MACE was higher in men than in women. The main causal mediating factors that contributed to the sex differences were diabetes and SES, the latter with an offsetting effect. CONCLUSIONS: This result suggests that to reduce the MACE gap between sexes, diabetes prevention programmes targeting men and more gender-equal salary policies should be implemented.

Influence of cardiovascular risk factors and treatment exposure on cardiovascular event incidence: Assessment using machine learning algorithms.

Assessment of the influence of cardiovascular risk factors (CVRF) on cardiovascular event (CVE) using machine learning algorithms offers some advantages over preexisting scoring systems, and better enables personalized medicine approaches to cardiovascular prevention. Using data from four different sources, we evaluated the outcomes of three machine learning algorithms for CVE prediction using different combinations of predictive variables and analysed the influence of different CVRF-related variables on CVE prediction when included in these algorithms. A cohort study based on a male cohort of workers applying populational data was conducted. The population of the study consisted of 3746 males. For descriptive analyses, mean and standard deviation were used for quantitative variables, and percentages for categorical ones. Machine learning algorithms used were XGBoost, Random Forest and Naïve Bayes (NB). They were applied to two groups of variables: i) age, physical status, Hypercholesterolemia (HC), Hypertension, and Diabetes Mellitus (DM) and ii) these variables plus treatment exposure, based on the adherence to the treatment for DM, hypertension and HC. All methods point out to the age as the most influential variable in the incidence of a CVE. When considering treatment exposure, it was more influential than any other CVRF, which changed its influence depending on the model and algorithm applied. According to the performance of the algorithms, the most accurate was Random Forest when treatment exposure was considered (F1 score 0.84), followed by XGBoost. Adherence to treatment showed to be an important variable in the risk of having a CVE. These algorithms could be applied to create models for every population, and they can be used in primary care to manage interventions personalized for every subject.

Patterns of statin adherence in primary cardiovascular disease prevention during the pandemic.

Background: Study of medication adherence patterns can help identify patients who would benefit from effective interventions to improve adherence. Objectives: To identify and compare groups of statin users based on their adherence patterns before and during the COVID-19 pandemic, to characterize the profile of users in each group, and to analyze predictors of distinct adherence patterns. Methods: Participants of the CARhES (CArdiovascular Risk factors for HEalth Services research) cohort, comprising individuals aged >16 years, residing in Aragón (Spain), with hypertension, diabetes mellitus and/or dyslipidemia, took part in this observational longitudinal study. Individuals who began statin therapy during January-June 2019 were selected and followed up until June 2021. Those with a cardiovascular event before or during follow-up were excluded. Data were obtained from healthcare system data sources. Statin treatment adherence during the implementation phase was estimated bimonthly using the Continuous Medication Availability (CMA9) function in the AdhereR package. Group-based trajectory models were developed to group statin users according to their adherence pattern during July 2019-June 2021. Group characteristics were compared and predictors of each adherence pattern were analyzed using multinomial logistic regression. Results: Of 15,332 new statin users, 30.8% had a mean CMA9 ≥80% for the entire study period. Four distinct adherence patterns were identified: high adherence (37.2% of the study population); poor adherence (35.6%); occasional use (14.9%); and gradual decline (12.3%). The latter two groups included users who showed a change in adherence (increase or decrease) during the pandemic emergence. Users with suboptimal adherence were likely to be younger, not pensioners, not institutionalized, with low morbidity burden and a low number of comorbidities. Female sex and switching between statins of different intensity increased the likelihood of belonging to the occasional use group, in which improved adherence coincided with the pandemic. Conclusion: We identified four distinct adherence patterns in a population of new statin users; two of them modified their adherence during the pandemic. Characterization of these groups could enable more effective distribution of resources in future similar crisis and the routine implementation of patient-centered interventions to improve medication adherence.

Understanding the COVID-19 Pandemic in Nursing Homes (Aragón, Spain): Sociodemographic and Clinical Factors Associated With Hospitalization and Mortality.

Old people residing in nursing homes have been a vulnerable group to the coronavirus disease 2019 (COVID-19) pandemic, with high rates of infection and death. Our objective was to describe the profile of institutionalized patients with a confirmed COVID-19 infection and the socioeconomic and morbidity factors associated with hospitalization and death. We conducted a retrospective cohort study including data from subjects aged 65 years or older residing in a nursing home with a confirmed COVID-19 infection from March 2020 to March 2021 (4,632 individuals) in Aragón (Spain). We analyzed their sociodemographic and clinical profiles and factors related to hospitalization and mortality at 7, 30, and 90 days of COVID-19 diagnosis using logistic regression analyses. We found that the risk of hospitalization and mortality varied according to sociodemographic and morbidity profile. There were inequalities in hospitalization by socioeconomic status and gender. Patients with low contributory pensions and women had a lower risk of hospitalization. Diabetes mellitus, heart failure, and chronic kidney disease were associated with a higher risk of hospitalization. On the contrary, people with dementia showed the highest risk of mortality with no hospitalization. Patient-specific factors must be considered to develop equitable and effective measures in nursing homes to be prepared for future health threats.

Effectiveness of Statins for Primary Prevention of Cardiovascular Disease in Low- and Medium-Risk Males: A Causal Inference Approach with Observational Data.

In this study, we analyzed the effectiveness of statin therapy for the primary prevention of cardiovascular disease (CVD) in low- and medium-risk patients. Using observational data, we estimated effectiveness by emulating a hypothetical randomized clinical trial comparing statin initiators with statin non-initiators. Two approaches were used to adjust for potential confounding factors: matching and inverse probability weighting in marginal structural models. The estimates of effectiveness were obtained by intention-to-treat and per-protocol analysis. The intention-to-treat analysis revealed an absolute risk reduction of 7.2 (95% confidence interval (CI95%), -6.6-21.0) events per 1000 subjects treated for 5 years in the matched design, and 2.2 (CI95%, -3.9-8.2) in the marginal structural model. The per-protocol analysis revealed an absolute risk reduction of 16.7 (CI95%, -3.0-36) events per 1000 subjects treated for 5 years in the matched design and 5.8 (CI95%, 0.3-11.4) in the marginal structural model. The indication for statin treatment for primary prevention in individuals with low and medium cardiovascular risk appears to be inefficient, but improves with better adherence and in subjectvs with higher risk.

La opinión pública colombiana sobre el acuerdo de paz 2016-2020: punitivismo, desconfianza y ostracismo / Colombian public opinion on the 2016-2020 peace agreement: punitivism, distrust and ostracism / Opinião pública colombiana sobre o acordo de paz de 2016-2020: punitivismo, desconfiança e ostracismo

Después de varias décadas de conflicto armado en Colombia, el Gobierno colombiano y las Farc-EP firmaron, en 2016, el Acuerdo Final para la terminación del conflicto y la construcción de una paz estable y duradera. No obstante, este acuerdo no fue refrendado por la ciudadanía, en un plebiscito celebrado ese mismo año. En 2018, ganó las elecciones presidenciales un candidato que prometió cambiar las condiciones del Acuerdos Final y modificar uno de sus principales instrumentos: la Jurisdicción Especial para la Paz (JEP). En ese contexto esta investigación se pregunta: ¿cuál es la opinión de los colombianos sobre el Acuerdo Final y la JEP? La investigación indaga en las opiniones de los colombianos a través de un análisis estadístico comparativo de tres encuestas de opinión de 2016, 2018 y 2020. Los resultados detallan los cambios actitudinales ocurridos en esos años, como la disminución del rechazo frontal a los Acuerdos de Paz y el leve incremento de las posibilidades de reintegración de los excombatientes a la vida civil. También, expone algunas reticencias al cambio, como la desconfianza persistente, la reafirmación del rechazo al indulto de los excombatientes (punitivismo) y a su participación política (ostracismo).

After several decades of armed conflict in Colombia, the Colombian Government and the Farc-EP signed, in 2016, the Final Agreement for the termination of the conflict and the construction of a stable and lasting peace. However, this agreement was not endorsed by the citizenry, in a plebiscite held that same year. In 2018, the presidential elections were won by a candidate who promised to change the conditions of the Final Agreement and to modify one of its main instruments: the Special Jurisdiction for Peace (JEP). In this context, this research asks: what is the opinion of Colombians on the Final Agreement and the SJP? The research inquiries into the opinions of Colombians through a comparative statistical analysis of three opinion polls from 2016, 2018 and 2020. The results detail the attitudinal changes that occurred in those years, such as the decrease in the frontal rejection of the Peace Accords and the slight increase in the possibilities of reintegration of ex-combatants to civilian life. It also exposes some reluctance to change, such as persistent distrust, the reaffirmation of the rejection of pardoning ex-combatants (punitivism) and their political participation (ostracism).

Após várias décadas de conflito armado na Colômbia, o governo colombiano e as FARC-EP assinaram, em 2016, o Acordo Final para o fim do conflito e a construção de uma paz estável e duradoura. Entretanto, este acordo não foi endossado pelos cidadãos em um plebiscito realizado no mesmo ano. Em 2018, as eleições presidenciais foram ganhas por um candidato que prometeu mudar as condições do Acordo Final e modificar um de seus principais instrumentos: a Jurisdição Especial para a Paz (JEP). Neste contexto, esta pesquisa pergunta: qual é a opinião dos colombianos sobre o Acordo Final e o SJP? A pesquisa investiga as opiniões dos colombianos através de uma análise estatística comparativa de três pesquisas de opinião de 2016, 2018 e 2020. Os resultados detalham as mudanças de atitude que ocorreram nesses anos, tais como a diminuição da rejeição direta dos Acordos de Paz e o leve aumento das possibilidades de reintegração de ex-combatentes na vida civil. Também expõe alguma relutância em mudar, como a desconfiança persistente, a reafirmação da rejeição do perdão de ex-combatentes (punitivismo) e de sua participação política (ostracismo).

COVID-19 Inequalities: Individual and Area Socioeconomic Factors (Aragón, Spain).

It is essential to understand the impact of social inequalities on the risk of COVID-19 infection in order to mitigate the social consequences of the pandemic. With this aim, the objective of our study was to analyze the effect of socioeconomic inequalities, both at the individual and area of residence levels, on the probability of COVID-19 confirmed infection, and its variations across three pandemic waves. We conducted a retrospective cohort study and included data from all individuals tested for COVID-19 during the three waves of the pandemic, from March to December 2020 (357,989 individuals) in Aragón (Spain). We studied the effect of inequalities on the risk of having a COVID-19 confirmed diagnosis after being tested using multilevel analyses with two levels of aggregation: individuals and basic healthcare area of residence (deprivation level and type of zone). Inequalities in the risk of COVID-19 confirmed infection were observed at both the individual and area level. There was a predominance of low-paid employees living in deprived areas. Workers with low salaries, unemployed and people on minimum integration income or who no longer receive the unemployment allowance, had a higher probability of COVID-19 infection than workers with salaries ≥ €18,000 per year. Inequalities were greater in women and in the second wave. The deprivation level of areas of residence influenced the risk of COVID-19 infection, especially in the second wave. It is necessary to develop individual and area coordinated measures by areas in the control, diagnosis and treatment of the epidemic, in order to avoid an increase in the already existing inequalities.

Evolution of Cardiovascular Risk Factors in a Worker Cohort: A Cluster Analysis.

The identification of the cardiovascular risk factor (CVRF) profile of individual patients is key to the prevention of cardiovascular disease (CVD), and the development of personalized preventive approaches. Using data from annual medical examinations in a cohort of workers, the aim of the study was to characterize the evolution of CVRFs and the CVD risk score (SCORE) over three time points between 2009 and 2017. For descriptive analyses, mean, standard deviation, and quartile values were used for quantitative variables, and percentages for categorical ones. Cluster analysis was performed using the Kml3D package in R software. This algorithm, which creates distinct groups based on similarities in the evolution of variables of interest measured at different time points, divided the cohort into 2 clusters. Cluster 1 comprised younger workers with lower mean body mass index, waist circumference, blood glucose values, and SCORE, and higher mean HDL cholesterol values. Cluster 2 had the opposite characteristics. In conclusion, it was found that, over time, subjects in cluster 1 showed a higher improvement in CVRF control and a lower increase in their SCORE, compared with cluster 2. The identification of subjects included in these profiles could facilitate the development of better personalized medical approaches to CVD preventive measures.

Pharmacological Primary Cardiovascular Prevention and Subclinical Atherosclerosis in Men: Evidence from the Aragon Workers' Health Study.

The objective of this study is to describe the profile of primary preventive treatment for cardiovascular disease in adult males and to analyze the association between treatment profile and subclinical atherosclerosis. We selected male workers who had undergone ultrasound imaging and had no previous history of cardiovascular disease (n = 2138). Data on the consumption of primary cardiovascular drugs from the previous year were obtained. We performed bivariate analyses to compare patient characteristics according to cardiovascular treatment and the presence of subclinical atherosclerosis, and logistic regression models to explore the association between these two variables. Among participants with no personal history of cardiovascular disease, subclinical atherosclerosis was present in 77.7% and 31.2% had received some form of preventive treatment. Of those who received no preventive treatment, 73.6% had subclinical atherosclerosis. Cardiovascular preventive treatment was associated only with CACS > 0 (odds ratio (OR), 1.37; 95% confidence interval (95% CI), 1.06-1.78). Statin treatment was associated with a greater risk of any type of subclinical atherosclerosis (OR, 1.73) and with CACS > 0 (OR, 1.72). Subclinical atherosclerosis existed in almost 75% of men who had no personal history of cardiovascular disease and had not received preventive treatment for cardiovascular disease.

Identifying Clusters of Adherence to Cardiovascular Risk Reduction Behaviors and Persistence with Medication in New Lipid-Lowering Drug Users. Impact on Healthcare Utilization.

We sought to identify specific profiles of new lipid-lowering drug users based on adherence to a healthy lifestyle and persistence with medication, and to characterize co-morbidities, co-treatments, and healthcare utilization for each of the profiles identified. Observational study in 517 participants in the Aragon Workers' Health Study (AWHS) without previous cardiovascular disease (CVD) and who initiated lipid-lowering therapy. Data were collected from workplace medical examinations and administrative health databases (2010-2018). Using cluster analysis, we identified distinct patient profiles based on persistence with therapy and lifestyle. We then compared characteristics, morbidity, and healthcare utilization across clusters. Participants were aggregated into four clusters based on persistence with therapy, smoking status, adherence to Mediterranean diet, and physical activity. In cluster 1 (n = 113), comprising those with a healthiest lifestyle (14.2% smokers, 84.0% with medium-high adherence to Mediterranean diet, high physical activity), 16.8% were persistent. In cluster 3 (n = 108), comprising patients with the least healthy lifestyle (100% smokers, poor adherence to the Mediterranean diet, low level of physical activity), all were non-persistent. Clusters 2 (n = 150) and 4 (n = 146) both comprised patients with intermediate lifestyle behaviors, but differed in terms of persistence (100 and 0%, respectively). Compared with other clusters, the burden of morbidity, cardiovascular score, and healthcare utilization were lower in cluster 1. The healthy adherer effect was only observed in new lipid-lowering drug users of certain profiles. Furthermore, we found that differences in adherence to lifestyle and medication recommendations for CVD prevention influenced morbidity burden and healthcare utilization.

New Male Users of Lipid-Lowering Drugs for Primary Prevention of Cardiovascular Disease: The Impact of Treatment Persistence on Morbimortality. A Longitudinal Study.

The objective of this study was to analyse persistence to lipid-lowering drug use for primary prevention of cardiovascular disease (CVD) in a new users cohort, to explore all-cause and cardiovascular related morbidity, comorbidity and mortality in this group and, finally, to study the relationship between persistence and morbimortality. We selected subjects who started lipid-lowering treatment for primary prevention of CVD between 1 January 2010 and 31 December 2017 (N = 1424), and classified them as treatment-persistent or -nonpersistent. Bivariate analyses were performed to compare sociodemographic and clinical variables, morbimortality and time to event between groups. The association between morbidities was explored using comorbidity network analysis. The effect of persistence was analysed using logistic regression and Cox survival analyses. Only 38.7% of users were persistent with treatment. Persistent and nonpersistent users had similar sociodemographic and clinical profiles, although differed in age, smoking status, and glycemia. Comorbidity networks revealed that the number of co-occurring diagnoses was higher in nonpersistent than persistent users. Adjusted analyses indicated a protective effect of treatment persistence, especially against major adverse cardiovascular events (MACE), but this effect was not statistically significant. Observational studies are crucial to characterize real-world effectiveness.