Rationale and background
Globally, sexually transmitted infections (STIs) constitute a major public health concern, with more than one million acquired every day. In Catalonia, as also seen in Spain and Europe more broadly, rates of STIs have been increasing in recent years. In addition, the COVID-19 pandemic led to significant disruptions in sexual health services, which may have exacerbated existing barriers to health service access, particularly for those who were less engaged with the health service prior to COVID-19. Given the higher rates of STIs reported as well as the barriers migrants may face in accessing sexual health services, migrants comprise an important population for STI prevention and response. However, there is significant diversity among migrants as a group. In order to target interventions, it is crucial to better understand the characteristics of migrants most at risk of STIs as well as the impact of COVID-19 disruptions on access to and uptake of sexual health services.
Objectives
The aim of this study is to estimate time trends in the incidence and prevalence of sexually transmitted infections, including Chlamydia, Gonorrhoea, Syphilis, Trichomoniasis, Genital herpes, Mpox and HPV, in Spanish and non-Spanish primary care users in Catalonia and identify changes in key population groups at risk over time.
This aim will be addressed through three objectives:
1.Characterise Spanish and non-Spanish primary care users in Catalonia in terms of sex, age, socioeconomic status, geographic location, and country of origin.
2.Investigate the incidence and prevalence of STIs in Spanish and non-Spanish individuals by sex, age, socioeconomic status, geographic location and country of origin.
3.Explore the impact of COVID-19-related disruptions on access to sexual health services and STI positivity among migrants and non-migrants.
Methods
Study design
This study is a population-based observational cohort study using individual-level routinely collected Electronic Health Records from the SIDIAP database
Population
The study population will include all patients registered with primary care in Catalonia, with a recorded nationality, diagnosed with any of the following STIs, including chlamydia, syphilis, gonorrhoea, trichomoniasis, HPV, genital herpes, and mpox, from 1st January 2006 to end of data availability. Patients will need to have at least 365 days of data visibility prior to index date.
Variables
Primary outcome: diagnosis of STI including chlamydia, syphilis, gonorrhoea, trichomoniasis, human papillomavirus (HPV), genital herpes, and mpox.
Secondary outcomes: visits to sexual health services and uptake of HPV vaccination.
Relevant covariates: sex, age, socioeconomic deprivation, geographic location and region of origin.
Data Source
The Information System for Research on Primary Care (SIDIAP), Spain
Statistical analysis
We will firstly characterise participants in terms of nationality (Spanish vs. non-Spanish), sex, age, socioeconomic status, geographic area, and region of origin (in the case of non-Spanish individuals) at their index date. Then we will summarise incidence and prevalence rates by infection and overall by nationality (Spanish vs. non-Spanish) and calculate relative risks adjusted by sex, age and socioeconomic status. Lastly, we will conduct an interrupted time series analysis of the impact of COVID-19-related health service disruptions on access to STI services and diagnosis for migrants and non-migrants.
The statistical analyses will be performed based on OMOP-CDM mapped data using OHDSI R packages. A minimum cell counts of 5 will be used when reporting results, with any smaller count reported as <5.

Antecedents: La prevalença d’arteriopatia periférica (AP) presenta un increment a nivel mundial en la darrera dècada. Aquesta malatía representa una disminució tan en la qualitat com en l’esperança de vida. A més a més diversos estudis han demostrat que l’AP és un marcador de morbimortalitat.
Hipòtesi: La AP és una de les manifestacions clíniques de l’arteriosclerosi (malaltia crónica, sistémica i progresiva del sistema vascular). La presencia d’ AP a nivell d’extremitats inferiors està fortament associada a l’aparició d’esdeveniments vasculars, mortalitat vascular i per totes les causes. Tot i això aquesta malaltia està infradiagnosticada i encara que es coneixen els factors de risc associats a la mateixa i existeix evidencia sobre el seu abordatge terapèutic, no es tracten adequadament. L’exitència de guies amb evidència sobre l’abordatge de l’AP no garanteix que aquesta pràctica sigui implementada pels professionals. La quantificació en l’infradiagnòstic en pràctica clínica real i l’avaluació del control dels factors de risc associats a la mateixa en ajudarà a implementar i optimitzar estrategies de prevenció primaria per esdeveniments vasculars
Objectius: Conèixer la prevalença d’AP, la seva evolució, l’infradiagnòstic, el control dels factors de risc i la morbimortalitat associada.
Resultats esperats: Elevat infradiagnòstic i infratractament.
Aplicabilitat: Identificar a les persones que es poden beneficiar de mesures preventives o de diagnòstic precoç de manera efectiva i eficient.
Rellevància: Conèixer la pràctica clínica real en front d’aquesta malatía i conèixent l’infradiagnòstic i infratractament podrem crear estratègies de diagnòstic i tractament d’aquesta malatía abans que es produeixin els esdeveniments vasculars. Tot això amb un cost baix, convertint-se en una inversió molt eficient per al sistema sanitari del nostre país.

Antecedents: La prevalença d’arteriopatia periférica (AP) presenta un increment a nivel mundial en la darrera dècada. Aquesta malatía representa una disminució tan en la qualitat com en l’esperança de vida. A més a més diversos estudis han demostrat que l’AP és un marcador de morbimortalitat.
Hipòtesi: La AP és una de les manifestacions clíniques de l’arteriosclerosi (malaltia crónica, sistémica i progresiva del sistema vascular). La presencia d’ AP a nivell d’extremitats inferiors està fortament associada a l’aparició d’esdeveniments vasculars, mortalitat vascular i per totes les causes. Tot i això aquesta malaltia està infradiagnosticada i encara que es coneixen els factors de risc associats a la mateixa i existeix evidencia sobre el seu abordatge terapèutic, no es tracten adequadament. L’exitència de guies amb evidència sobre l’abordatge de l’AP no garanteix que aquesta pràctica sigui implementada pels professionals. La quantificació en l’infradiagnòstic en pràctica clínica real i l’avaluació del control dels factors de risc associats a la mateixa en ajudarà a implementar i optimitzar estrategies de prevenció primaria per esdeveniments vasculars
Objectius: Conèixer la prevalença d’AP, la seva evolució, l’infradiagnòstic, el control dels factors de risc i la morbimortalitat associada.
Resultats esperats: Elevat infradiagnòstic i infratractament.
Aplicabilitat: Identificar a les persones que es poden beneficiar de mesures preventives o de diagnòstic precoç de manera efectiva i eficient.
Rellevància: Conèixer la pràctica clínica real en front d’aquesta malatía i conèixent l’infradiagnòstic i infratractament podrem crear estratègies de diagnòstic i tractament d’aquesta malatía abans que es produeixin els esdeveniments vasculars. Tot això amb un cost baix, convertint-se en una inversió molt eficient per al sistema sanitari del nostre país.

Researching the co-existence of multiple chronic conditions in a single individual (multimorbidity) is challenging using conventional study designs. Confounding, bias and reverse causality are often complex and severe and may partly explain apparently paradoxical associations. People with type 2 diabetes and additional conditions, for example, tend to have lower HbA1c than those with diabetes alone, and we and others have shown that there is marked weight loss and declining blood pressure for a decade before diagnosis of dementia. Our vision is to address these challenges by combining genetic and conventional approaches and using large-scale data resources from the UK, Spain, US and Canada, including 3 multi-million patient GP data sources. We will identify clusters of disease, use novel causal inference methodology to identify shared biological determinants, and study in-depth a set of disease clusters. By understanding biological determinants of multimorbidity clustering and identifying which are associated with markedly altered clinical outcomes, we will help clarify which multi-morbidity combinations are of most clinical importance to understand.
We will define multimorbidity as the presence of 2 or more chronic conditions(1) but focus on those each occurring in >1% of men or women aged 40 plus and that are genetically correlated with other conditions. To address inequalities of multimorbidity we will study the excess burden in women and ethnic minorities. A multi-modal, data driven approach will be critical. Clustering that is consistent across genetic and observational data will be more reflective of shared determinants. Genetic approaches provide a test of lifelong exposure to risk factors and provide strong causal inferences. The widespread availability of genome wide information also means that we can study shared risk factors that are not measured in many studies (e.g. insulin resistance) and calculate disease clustering between, as well as within, databases(2).
To achieve our vision we have formed a new multi-disciplinary research team (supported by outstanding external advisors), including researchers with extensive experience in multimorbidity in three GP databases; physical and mental decline in the elderly; specialists in key diseases (diabetes, vascular, dementia, musculo-skeletal) and with expertise in genetics and causal inference.

OBJECTIVES

1. To identify disease clusters using a combined genetic and observational approach; and to test the hypotheses that: a) using multiple data sources and genetic correlations will provide more robust estimates of clustering than has been so far possible, and that b) patterns of clustering differ between the sexes and ethnic minorities.
2. To improve reproducibility of multimorbidity research, and working with other collaborative bids where relevant, to develop STATA and R packages to standardize the process of disease coding across GP databases, and to make these tools publicly accessible.
3. To develop and apply genetic and non-genetic “”instruments”” and causal inference methods to identify shared biological and non-biological determinants of disease clustering. These instruments will include clusters of genetic variants specific to potential shared disease processes and be randomized to disease incidence and adverse outcomes.
4. To identify a subset of emerging disease clusters for further, in depth study; to validate these clusters in additional datasets with different ascertainment criteria; and to test the hypothesis, using longitudinal data, that the timing sequences of the different disease components to the identified clusters differ from chance (life course).
5. To identify the cluster-associated outcomes of most impact, as informed by frequency, severity and our PPI advisors; to estimate the proportion of patients in each cluster who develop the most impactful outcomes and identify potential modifiable risk factors.
6. To identify the disease clusters that result in clinically meaningful differences in outcomes compared to patients with only one of the constituent diseases.

Researching the co-existence of multiple chronic conditions in a single individual (multimorbidity) is challenging using conventional study designs. Confounding, bias and reverse causality are often complex and severe and may partly explain apparently paradoxical associations. People with type 2 diabetes and additional conditions, for example, tend to have lower HbA1c than those with diabetes alone, and we and others have shown that there is marked weight loss and declining blood pressure for a decade before diagnosis of dementia. Our vision is to address these challenges by combining genetic and conventional approaches and using large-scale data resources from the UK, Spain, US and Canada, including 3 multi-million patient GP data sources. We will identify clusters of disease, use novel causal inference methodology to identify shared biological determinants, and study in-depth a set of disease clusters. By understanding biological determinants of multimorbidity clustering and identifying which are associated with markedly altered clinical outcomes, we will help clarify which multi-morbidity combinations are of most clinical importance to understand.
We will define multimorbidity as the presence of 2 or more chronic conditions(1) but focus on those each occurring in >1% of men or women aged 40 plus and that are genetically correlated with other conditions. To address inequalities of multimorbidity we will study the excess burden in women and ethnic minorities. A multi-modal, data driven approach will be critical. Clustering that is consistent across genetic and observational data will be more reflective of shared determinants. Genetic approaches provide a test of lifelong exposure to risk factors and provide strong causal inferences. The widespread availability of genome wide information also means that we can study shared risk factors that are not measured in many studies (e.g. insulin resistance) and calculate disease clustering between, as well as within, databases(2).
To achieve our vision we have formed a new multi-disciplinary research team (supported by outstanding external advisors), including researchers with extensive experience in multimorbidity in three GP databases; physical and mental decline in the elderly; specialists in key diseases (diabetes, vascular, dementia, musculo-skeletal) and with expertise in genetics and causal inference.

OBJECTIVES

1. To identify disease clusters using a combined genetic and observational approach; and to test the hypotheses that: a) using multiple data sources and genetic correlations will provide more robust estimates of clustering than has been so far possible, and that b) patterns of clustering differ between the sexes and ethnic minorities.
2. To improve reproducibility of multimorbidity research, and working with other collaborative bids where relevant, to develop STATA and R packages to standardize the process of disease coding across GP databases, and to make these tools publicly accessible.
3. To develop and apply genetic and non-genetic “”instruments”” and causal inference methods to identify shared biological and non-biological determinants of disease clustering. These instruments will include clusters of genetic variants specific to potential shared disease processes and be randomized to disease incidence and adverse outcomes.
4. To identify a subset of emerging disease clusters for further, in depth study; to validate these clusters in additional datasets with different ascertainment criteria; and to test the hypothesis, using longitudinal data, that the timing sequences of the different disease components to the identified clusters differ from chance (life course).
5. To identify the cluster-associated outcomes of most impact, as informed by frequency, severity and our PPI advisors; to estimate the proportion of patients in each cluster who develop the most impactful outcomes and identify potential modifiable risk factors.
6. To identify the disease clusters that result in clinically meaningful differences in outcomes compared to patients with only one of the constituent diseases.

Antecedents:
Tot i les nombroses publicacions existents, la evidencia sobre COVID-19 i esdeveniments cardiovasculars actualment es bastant inconsistent, degut a que és una malaltia emergent.
Entre altres coses, es produeix una resposta inflamatoria sistèmica (disfunció endotelial i microtrombosi) i hipercoagulabilitat (elevació D-dimer i fibrinògen). Aquesta inflamació incrementa el risc de ruptura de la placa arterioscleròtica i per tant aparició d’esdeveniments vasculars.
És important valorar les complicacions cardiovasculars que poden contribuir a la mortalitat associada a aquesta pandèmia.

Hipòtesi: Els pacients COVID-19 presenten una major incidència d’esdeveniments cardiovascular respecte als pacients no COVID-19.

Objectius: Conèixer la incidencia d’esdeveniments vasculars : infart de miocardi, ictus, tromboembolisme pulmonar, trombosi venosa profunda i mortalitat vascular i global associada en pacient COVID-19 i no COVID-19 durant el primer semestre de l’any 2020.
Comparar la incidència d’esdeveniments vasculars esmentats entre el primer semestre de l’any 2019 i el primer semestre de l’any 2020.
Analitzar els factors de risc associats a la mateixa.

Resultats esperats: Augment d’esdeveniments vasculars en pacients COVID-19 respecte a no COVID-19 i durant el primer semestre de l’any 2020.

Aplicabilitat:
Identificar els factors de risc assossiats a l’aparició d’un esdeveniment cardiovascular en persones amb la COVID-19 en població general mediterrània >15anys per tal de poder fer una major prevenció en front a nous brots d’aquesta malaltia.
Identificar a les persones més susceptibles per tal que es puguin beneficiar de mesures preventives o de diagnòstic precoç de manera efectiva i eficient.

Rellevància: Conèixer la incidència real d’esdeveniments vasculars i els factors associats a la seva aparició ens
ajudarà a implementar estrategies de prevenció i maneig d’aquesta malaItia abans que es produeixin els esdeveniments vasculars.

Supervivencia de cáncer de mama y otras neoplasias asociadas a receptores histáminicos y los medicamentos antihistamínicos. Objetivo 2). Identificar la asociación por métodos de machine learning del cáncer de mama y otras neoplasias asociadas a receptores histamínicos y los medicamentos antihistaminicos para predecir la muerte. Ámbito: atención primaria Cataluña. Periodo: 2010-19.Fuentes de información: Sistema de Información para el Desarrollo de la Investigación en Atención Primaria. Población: Personas ?65 años, muestra estimada: 916.619personas. Variables: problemas de salud (ICD-10), cáncer, medicamentos (ATC), antihistamínicos, edad, sexo, número de visitas, mortalidad. Resultados: supervivencia por cáncer de mama y otras neoplasias asociadas a receptores histáminicos Análisis estadístico: El objetivo 1) Se utilizará un modelo logístico basado en variables de confusión para calcular el Propensity Score (PS) y definir los grupos de usuarios y no usuarios.Se estimarán las tasas de mortalidad e incidencia del cáncer durante el seguimiento para cada cohorte, se reportaran los valores por cada 1.000 pacientes-año y su correspondiente intervalo de confianza (IC) del 95%. El análisis de la supervivencia se realizará utilizando métodos no paramétricos como Kaplan-Meier y el log-rank test. Se ajustarán modelos de regresión de riesgos proporcionales de Cox multivariados, ajustando los factores de confusión y predicción de cada cáncer. Se considerarán métodos de Imputación Múltiple (MICE), para poder minimizar el impacto de la presencia de valores faltantes en las variables de análisis. El objetivo 2) Se prevé usar técnicas de reducción de dimensionalidad y de modelos de clustering (Kmeans, jerárquico) que permitan por un lado el análisis exploratorio de los datos y por otro la identificación de grupos e interacciones. Respecto a la interacción de antihistamínicos con la muerte resultado del cáncer de mama y otras neoplasias asociadas a receptores histamínicos se construirán modelos predictivos basados en algoritmos de última generación como árboles de decisión, gradiente boost machine y aprendizaje profundo por medio de redes neuronales. Se proporcionarán medidas de calidad de los modelos construidos basadas en validación cruzada, métricas de accuracy y curvas ROC a ese año sumadas a los puntajes de predicción de salida obtenidos el año anterior.

Aquest projecte és farà amb les dades del projecte 4R16/029 i PI16/00639 . NO ES NECESSARI TONAR A DEMANAR DADES DEL SIDIAP. ES UN PROJECTE INICIAL PER EXPLORAR UNA HIPOTÉSIS , SI ÉS AFIRMATIVA ÉS DEMANARÀ UN SEGON PROJECTE AMB MÉS DADES.

Ageing is a major trend among people living with HIV PLWH, and due to the chronic inflammation and immune senescence caused by the virus and the ageing process, there is a higher prevalence of certain comorbidities, leading to more comorbidity burden. In this study, we intend to describe and compare comorbidity prevalence and incidence in PLWH over 40 against HIV negative population, compare overall multimorbidity patterns in PLWH over 40 years, and analyse multimorbidity pattern trajectories in PLWH over 40 against HIV negative population.
Study population will be general population over 40 years between January 1 2010 and December 31 2020. Chronic diseases will be coded according to the Swedish National study of Aging and Care in Kungsholmen (SNAC-K) (1). General population patients will be compared with a precious cohort of HIV patients.
Clinical, lab and drug related parameters will be extracted for the assessment of certain conditions. Death will be measured at date of event, regardless of the cause. A person not visited for over a year by the end of the follow-up period will be considered lost to follow-up (LTFU). Additional variables included are socio-demographic variables such as age at baseline, gender, socio-economic status, number of drugs dispensed at the pharmacy and number of visits to Primary Care. Polypharmacy will be described as five or more different drugs, not including antiretrovirals.
Descriptive statistics will used to summarize epidemiological characteristics and overall prevalence and incidence for every comorbidity group of patients. Cluster analysis will be run. To prevent including statistical noise and spurious findings, diseases with a prevalence?2% over-all prevalence.
This project is crucial so as to better understand changes in age-associated comorbid patterns and the differences in health-related quality of life between PLWH and non-infected general population, in order to make health policies decisions based on reliable and concise data to make evidence-based decisions on health policy, allocate scarce resources optimally, and establish specific clinical guidelines with the goal to address these changes.

ANTECEDENTES: Los trabajadores de la salud (PS) están en la primera línea de la lucha contra COVID-19, siendo más susceptibles a infectarse. En el estudio anterior, Prohepic-19, hicimos un seguimiento de 1471 TS durante 12 meses. La vacunación llega con muchas preguntas sobre su protección, reinfecciones y respuesta inmune. Ampliar el seguimiento de nuestra cohorte bien caracterizada inmunológicamente será decisivo para resolver estas cuestiones capitales.
? OBJETIVO: Generar información altamente confiable para mejorar las políticas de salud para prevenir la infección por CoV-2. Analizaremos la tasa de incidencia de la infección por CoV-2, la reinfección, la respuesta inmune a largo plazo para los trabajadores sanitarios infectados y no infectados relacionada con la vacuna en los trabajadores sanitarios expuestos, sanos e infectados.
? METODOLOGÍA: Una cohorte de PS (n = 1370 serán seguidos durante 24 meses, con dos brazos (sanos-expuestos = 1050; infectados = 320). Estadísticas: La incidencia relativa de la prueba de RT-PCR positiva y la nueva infección Se estimará de acuerdo con el nivel basal de los anticuerpos. Se analizará la cinética de IgG e IgM durante 24 meses, ajustando por edad, sexo y síntomas.
? RESULTADOS ESPERADOS: ProHEpiC-19 + se concibe como una estrategia para determinar la protección inmunológica a largo plazo frente a nuevas infecciones. Los resultados servirán de base

ANTECEDENTES: Los trabajadores de la salud (PS) están en la primera línea de la lucha contra COVID-19, siendo más susceptibles a infectarse. En el estudio anterior, Prohepic-19, hicimos un seguimiento de 1471 TS durante 12 meses. La vacunación llega con muchas preguntas sobre su protección, reinfecciones y respuesta inmune. Ampliar el seguimiento de nuestra cohorte bien caracterizada inmunológicamente será decisivo para resolver estas cuestiones capitales.
? OBJETIVO: Generar información altamente confiable para mejorar las políticas de salud para prevenir la infección por CoV-2. Analizaremos la tasa de incidencia de la infección por CoV-2, la reinfección, la respuesta inmune a largo plazo para los trabajadores sanitarios infectados y no infectados relacionada con la vacuna en los trabajadores sanitarios expuestos, sanos e infectados.
? METODOLOGÍA: Una cohorte de PS (n = 1370 serán seguidos durante 24 meses, con dos brazos (sanos-expuestos = 1050; infectados = 320). Estadísticas: La incidencia relativa de la prueba de RT-PCR positiva y la nueva infección Se estimará de acuerdo con el nivel basal de los anticuerpos. Se analizará la cinética de IgG e IgM durante 24 meses, ajustando por edad, sexo y síntomas.
? RESULTADOS ESPERADOS: ProHEpiC-19 + se concibe como una estrategia para determinar la protección inmunológica a largo plazo frente a nuevas infecciones. Los resultados servirán de base