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IntroductionThere is a growing interest in the effect of Long-COVID (LC) on cognition, and neuroimaging allows us to gain insight into the structural and functional changes underlying cognitive impairment in LC. We used multimodal neuroimaging data in combination with neuropsychological evaluations to study cognitive complaints in a cohort of LC patients with mild to moderate severity symptoms.MethodsWe conducted a 3T brain magnetic resonance imaging (MRI) study with diffusion tensor imaging (DTI) and functional MRI (fMRI) sequences on 53 LC patients 1.8 years after acute COVID-19 onset. We administered neuropsychological tests to evaluate cognitive domains and examined correlations with Tract-Based Spatial Statistics (TBSS) and resting state.ResultsWe included 53 participants with LC (mean age, 48.23 years; 88.7% females). According to the Frascati criteria, more than half of the participants had deficits in the executive (59%) and attentional (55%) domains, while 40% had impairments in the memory domain. Only one participant (1.89%) showed problems in the visuospatial and visuoconstructive domain. We observed that increased radial diffusivity in different white matter tracts was negatively correlated with the memory domain. Our results showed that higher resting state activity in the fronto-parietal network was associated with lower memory performance. Moreover, we detected increased functional connectivity among the bilateral hippocampus, the right hippocampus and the left amygdala, and the right hippocampus and the left middle temporal gyrus. These connectivity patterns were inversely related to memory and did not survive false discovery rate (FDR) correction.DiscussionPeople with LC exhibit cognitive impairments linked to long-lasting changes in brain structure and function, which justify the cognitive alterations detected.

BackgroundThe neurological symptoms of Long COVID (LC) and the impact of neuropsychological manifestations on people’s daily lives have been extensively described. Although a large body of literature describes symptoms, validating this with objective measures is important. This study aims to identify and describe the effects of Long COVID on cognition, balance, and the retinal fundus, and determine whether the duration of symptoms influences cognitive impairment.MethodsThis cross-sectional study involved LC volunteers with cognitive complaint from public health centers in northern Barcelona who participated between January 2022 and March 2023. This study collected sociodemographic characteristics, information on substance use, comorbidities, and clinical data related to COVID-19. We measured five cognitive domains using a battery of neuropsychological tests. Balance was assessed through posturography and retinal vascular involvement by retinography.ResultsA total of 166 people with LC and cognitive complaints participated, 80.72% were women and mean age was 49.28 ± 8.39 years. The most common self-reported symptoms were concentration and memory deficit (98.80%), brain fog (82.53%) and insomnia (71.17%). The 68.67% presented cognitive deficit in at least one domain, with executive functions being the most frequent (43.98%). The 51.52% of the participants exhibited a dysfunctional pattern in balance, and 9.2% showed some alteration in the retina. There were no statistically significant differences between cognitive impairment and symptom duration.ConclusionOur findings contribute to a more comprehensive understanding of the pathology associated with Long COVID. They highlight the diversity of self-reported symptoms, the presence of abnormal balance patterns, and some cognitive impairment. These findings underscore the necessity of addressing the clinical management of this condition in primary care through follow-up and the pursuit of multidisciplinary and comprehensive treatment.

Abstract Background SARS-CoV-2 breakthrough infections (BI) after vaccine booster dose are a relevant public health issue. Methods Multicentric longitudinal cohort study within the ORCHESTRA project, involving 63,516 health workers (HW) from 14 European settings. The study investigated the cumulative incidence of SARS-CoV-2 BI after booster dose and its correlation with age, sex, job title, previous infection, and time since third dose. Results 13,093 (20.6%) BI were observed. The cumulative incidence of BI was higher in women and in HW aged 130 days. Conclusions The risk of BI after booster is significantly reduced by previous infection, heterologous vaccination, and older ages. Immunosuppression is relevant for increased BI incidence. Time elapsed from booster affects BI severity, confirming the public health usefulness of booster. Further research should focus on BI trend after 4th dose and its relationship with time variables across the epidemics.

Introduction Congenital cytomegalovirus (cCMV) is the leading cause of non-genetic sensorineural hearing loss and one of the main causes of neurological disability. Despite this, no universal screening programme for cCMV has been implemented in Spain. A recent study has shown that early treatment with valaciclovir, initiated in the first trimester and before the onset of signs in the fetus, reduces the risk of fetal infection. This finding favours the implementation of a universal screening programme for cCMV.The aim of this study is to evaluate the performance of a universal screening programme for cCMV during the first trimester of pregnancy in a primary care setting.Methods and analysis This is an observational multicentre cohort study. The study will be conducted in four primary care settings from the Northern Metropolitan Barcelona area and three related hospitals and will last 3 years and will consist of a recruitment period of 18 months.In their first pregnancy visit, pregnant women will be offered to add a CMV serology test to the first trimester screening tests. Pregnant women with primary infection will be referred to the reference hospital, where they will continue treatment and follow-up according to the clinical protocol of the referral hospital, which includes treatment with valacyclovir. A CMV-PCR will be performed at birth on newborns of mothers with primary infection, and those who are infected will undergo neonatal follow-up for at least 12 months of life.For the analysis, the acceptance rate, the prevalence of primary CMV infections and the CMV seroprevalence in the first trimester of pregnancy will be studied.Ethics and dissemination Ethical approval was obtained from the University Institute Foundation for Primary Health Care Research Jordi Gol i Gurina Ethics Committee 22/097-P dated 27 April 2022.

Purpose: To compare the effect of discontinuing bisphosphonate treatment on fracture risk in postmenopausal women at high versus low risk of fracture. Design: Retrospective, longitudinal and population-based cohort study. Setting: Barcelona City Primary Care. Catalan Health Institute. Participants: All women attended by primary care teams who in January 2014 had received bisphosphonate treatment for at least five years were included and followed for another five years. Intervention: Patients were classified according to their risk of new fractures, defined as those who had a history of osteoporotic fracture and/or who received treatment with an aromatase inhibitor, and the continuity or deprescription of the bisphosphonate treatment was analyzed over fiver year follow-up. Main measurements: The cumulative incidence of fractures and the incidence density were calculated and analyzed using logistic regression and Cox models. Results: We included 3680 women. There were no significant differences in fracture risk in high-risk women who discontinued versus continued bisphosphonate treatment (hazard ratio [HR] 1.17, 95% confidence interval [CI] 0.87–1.58 for total osteoporotic fractures). However, discontinuers at low risk had a lower incidence of fracture than continuers. This difference was significant for vertebral fractures (HR 0.64, 95% CI 0.47–0.88) and total fractures (HR 0.77, 95% CI 0.64–0.92). Conclusion: Our results suggest that deprescribing bisphosphonates in women who have already received five years of treatment does not increase fracture risk. In low-risk women, continuing this treatment might could even favor the appearance of new osteoporotic fractures. Resumen: Objetivo: Comparar el efecto de la desprescripción de bifosfonatos sobre el riesgo de fractura en mujeres posmenopáusicas con alto y bajo riesgo de fractura. Diseño: Estudio de cohortes retrospectivo, longitudinal y de base poblacional. Emplazamiento: Atención primaria Barcelona. Institut Català de la Salut. Participantes: Se incluyeron todas las mujeres atendidas por los equipos de atención primaria que a enero de 2014 habían recibido tratamiento con bifosfonatos durante al menos cinco años. Intervención: Se clasificó a las pacientes según su riesgo de nuevas fracturas, definido como presencia de antecedentes de fractura osteoporótica y/o tratamiento con un inhibidor de la aromatasa, y se analizó la continuidad o desprescripción del tratamiento con bifosfonatos a lo largo de cinco años de seguimiento. Mediciones principales: La incidencia acumulada de fracturas y la densidad de incidencia se calcularon y analizaron mediante regresión logística y modelos de Cox. Resultados: Se incluyeron 3.680 mujeres. No hubo diferencias significativas en el riesgo de fractura en mujeres de alto riesgo que desprescribieron el bisfosfonato comparado con aquellas que continuaron (hazard ratio [HR] 1,17, intervalo de confianza [IC] de 95% 0,87-1,58 para fracturas osteoporóticas totales). Sin embargo, los que discontinuaron con bajo riesgo tuvieron una menor incidencia de fractura que los que continuaron. Esta diferencia fue significativa para fracturas vertebrales (HR 0,64, IC 95% 0,47-0,88) y fracturas totales (HR 0,77, IC 95% 0,64-0,92). Conclusiones: Nuestros resultados sugieren que la desprescripción de bifosfonatos en mujeres que ya han recibido cinco años de tratamiento no aumenta el riesgo de fractura. En mujeres de bajo riesgo, la continuación de este tratamiento podría incluso favorecer la aparición de nuevas fracturas osteoporóticas.

Abstract Background Understanding the immune response to the SARS-CoV-2 virus is critical for efficient monitoring and control strategies. The ProHEpic-19 cohort provides a fine-grained description of the kinetics of antibodies after SARS-CoV-2 infection with an exceptional resolution over 17 months. Methods We established a cohort of 769 healthcare workers including healthy and infected with SARS-CoV-2 in northern Barcelona to determine the kinetics of the IgM against the nucleocapsid (N) and the IgG against the N and spike (S) of SARS-CoV-2 in infected healthcare workers. The study period was from 5 May 2020 to 11 November 2021.We used non-linear mixed models to investigate the kinetics of IgG and IgM measured at nine time points over 17 months from the date of diagnosis. The model included factors of time, gender, and disease severity (asymptomatic, mild-moderate, severe-critical) to assess their effects and their interactions. Findings 474 of the 769 participants (61.6%) became infected with SARS-CoV-2. Significant effects of gender and disease severity were found for the levels of all three antibodies. Median IgM(N) levels were already below the positivity threshold in patients with asymptomatic and mild-moderate disease at day 270 after the diagnosis, while IgG(N and S) levels remained positive at least until days 450 and 270, respectively. Kinetic modelling showed a general rise in both IgM(N) and IgG(N) levels up to day 30, followed by a decay with a rate depending on disease severity. IgG(S) levels remained relatively constant from day 15 over time. Interpretation IgM(N) and IgG(N, S) SARS-CoV-2 antibodies showed a heterogeneous kinetics over the 17 months. Only the IgG(S) showed a stable increase, and the levels and the kinetics of antibodies varied according to disease severity. The kinetics of IgM and IgG observed over a year also varied by clinical spectrum can be very useful for public health policies around vaccination criteria in adult population. Funding Regional Ministry of Health of the Generalitat de Catalunya (Call COVID19-PoC SLT16_04; NCT04885478).

BackgroundMultimorbidity and frailty are characteristics of aging that need individualized evaluation, and there is a 2-way causal relationship between them. Thus, considering frailty in analyses of multimorbidity is important for tailoring social and health care to the specific needs of older people. ObjectiveThis study aimed to assess how the inclusion of frailty contributes to identifying and characterizing multimorbidity patterns in people aged 65 years or older. MethodsLongitudinal data were drawn from electronic health records through the SIDIAP (Sistema d’Informació pel Desenvolupament de la Investigació a l’Atenció Primària) primary care database for the population aged 65 years or older from 2010 to 2019 in Catalonia, Spain. Frailty and multimorbidity were measured annually using validated tools (eFRAGICAP, a cumulative deficit model; and Swedish National Study of Aging and Care in Kungsholmen [SNAC-K], respectively). Two sets of 11 multimorbidity patterns were obtained using fuzzy c-means. Both considered the chronic conditions of the participants. In addition, one set included age, and the other included frailty. Cox models were used to test their associations with death, nursing home admission, and home care need. Trajectories were defined as the evolution of the patterns over the follow-up period. ResultsThe study included 1,456,052 unique participants (mean follow-up of 7.0 years). Most patterns were similar in both sets in terms of the most prevalent conditions. However, the patterns that considered frailty were better for identifying the population whose main conditions imposed limitations on daily life, with a higher prevalence of frail individuals in patterns like chronic ulcers &peripheral vascular. This set also included a dementia-specific pattern and showed a better fit with the risk of nursing home admission and home care need. On the other hand, the risk of death had a better fit with the set of patterns that did not include frailty. The change in patterns when considering frailty also led to a change in trajectories. On average, participants were in 1.8 patterns during their follow-up, while 45.1% (656,778/1,456,052) remained in the same pattern. ConclusionsOur results suggest that frailty should be considered in addition to chronic diseases when studying multimorbidity patterns in older adults. Multimorbidity patterns and trajectories can help to identify patients with specific needs. The patterns that considered frailty were better for identifying the risk of certain age-related outcomes, such as nursing home admission or home care need, while those considering age were better for identifying the risk of death. Clinical and social intervention guidelines and resource planning can be tailored based on the prevalence of these patterns and trajectories.

Abstract Objective To create an electronic frailty index (eFRAGICAP) using electronic health records (EHR) in Catalunya (Spain) and assess its predictive validity with a two-year follow-up of the outcomes: homecare need, institutionalization and mortality in the elderly. Additionally, to assess its concurrent validity compared to other standardized measures: the Clinical Frailty Scale (CFS) and the Risk Instrument for Screening in the Community (RISC). Methods The eFRAGICAP was based on the electronic frailty index (eFI) developed in United Kingdom, and includes 36 deficits identified through clinical diagnoses, prescriptions, physical examinations, and questionnaires registered in the EHR of primary health care centres (PHC). All subjects > 65 assigned to a PHC in Barcelona on 1st January, 2016 were included. Subjects were classified according to their eFRAGICAP index as: fit, mild, moderate or severe frailty. Predictive validity was assessed comparing results with the following outcomes: institutionalization, homecare need, and mortality at 24 months. Concurrent validation of the eFRAGICAP was performed with a sample of subjects (n = 333) drawn from the global cohort and the CFS and RISC. Discrimination and calibration measures for the outcomes of institutionalization, homecare need, and mortality and frailty scales were calculated. Results 253,684 subjects had their eFRAGICAP index calculated. Mean age was 76.3 years (59.5% women). Of these, 41.1% were classified as fit, and 32.2% as presenting mild, 18.7% moderate, and 7.9% severe frailty. The mean age of the subjects included in the validation subsample (n = 333) was 79.9 years (57.7% women). Of these, 12.6% were classified as fit, and 31.5% presented mild, 39.6% moderate, and 16.2% severe frailty. Regarding the outcome analyses, the eFRAGICAP was good in the detection of subjects who were institutionalized, required homecare assistance, or died at 24 months (c-statistic of 0.841, 0.853, and 0.803, respectively). eFRAGICAP was also good in the detection of frail subjects compared to the CFS (AUC 0.821) and the RISC (AUC 0.848). Conclusion The eFRAGICAP has a good discriminative capacity to identify frail subjects compared to other frailty scales and predictive outcomes.

Short summaryWe investigated changes in serologic measurements after COVID-19 vaccination in 19,422 subjects. An individual-level analysis was performed on standardized measurements. Age, infection, vaccine doses, time between doses and serologies, and vaccine type were associated with changes in serologic levels within 13 months.BackgroundPersistence of vaccine immunization is key for COVID-19 prevention.MethodsWe investigated the difference between two serologic measurements of anti-COVID-19 S1 antibodies in an individual-level analysis on 19,422 vaccinated healthcare workers (HCW) from Italy, Spain, Romania, and Slovakia, tested within 13 months from first dose. Differences in serologic levels were divided by the standard error of the cohort-specific distribution, obtaining standardized measurements. We fitted multivariate linear regression models to identify predictors of difference between two measurements.ResultsWe observed a progressively decreasing difference in serologic levels from

Background: The effectiveness of the immunity provided by SARS-CoV-2 vaccines is an important public health issue. We analyzed the determinants of 12-month serology in a multicenter European cohort of vaccinated healthcare workers (HCW). Methods: We analyzed the sociodemographic characteristics and levels of anti-SARS-CoV-2 spike antibodies (IgG) in a cohort of 16,101 vaccinated HCW from eleven centers in Germany, Italy, Romania, Slovakia and Spain. Considering the skewness of the distribution, the serological levels were transformed using log or cubic standardization and normalized by dividing them by center-specific standard errors. We fitted center-specific multivariate regression models to estimate the cohort-specific relative risks (RR) of an increase of one standard deviation of log or cubic antibody level and the corresponding 95% confidence interval (CI) for different factors and combined them in random-effects meta-analyses. Results: We included 16,101 HCW in the analysis. A high antibody level was positively associated with age (RR = 1.04, 95% CI = 1.00–1.08 per 10-year increase), previous infection (RR = 1.78, 95% CI 1.29–2.45) and use of Spikevax [Moderna] with combinations compared to Comirnaty [BioNTech/Pfizer] (RR = 1.07, 95% CI 0.97–1.19) and was negatively associated with the time since last vaccine (RR = 0.94, 95% CI 0.91–0.98 per 30-day increase). Conclusions: These results provide insight about vaccine-induced immunity to SARS-CoV-2, an analysis of its determinants and quantification of the antibody decay trend with time since vaccination.

Understanding antibody persistence concerning multimorbidity is crucial for vaccination policies. Our goal is to assess the link between multimorbidity and serological response to SARS-CoV-2 nine months post-first vaccine. We analyzed Healthcare Workers (HCWs) from three cohorts from Italy, and one each from Germany, Romania, Slovakia, and Spain. Seven groups of chronic diseases were analyzed. We included 2941 HCWs (78.5% female, 73.4% ≥ 40 years old). Multimorbidity was present in 6.9% of HCWs. The prevalence of each chronic condition ranged between 1.9% (cancer) to 10.3% (allergies). Two regression models were fitted, one considering the chronic conditions groups and the other considering whether HCWs had diseases from ≥2 groups. Multimorbidity was present in 6.9% of HCWs, and higher 9-months post-vaccine anti-S levels were significantly associated with having received three doses of the vaccine (RR = 2.45, CI = 1.92–3.13) and with having a prior COVID-19 infection (RR = 2.30, CI = 2.15–2.46). Conversely, lower levels were associated with higher age (RR = 0.94, CI = 0.91–0.96), more time since the last vaccine dose (RR = 0.95, CI = 0.94–0.96), and multimorbidity (RR = 0.89, CI = 0.80–1.00). Hypertension is significantly associated with lower anti-S levels (RR = 0.87, CI = 0.80–0.95). The serological response to vaccines is more inadequate in individuals with multimorbidity.

Summary: Background: Prevalence of both multimorbidity and frailty increases with age, but more evidence is needed to elucidate their relationship and their association with other health-related outcomes. We analysed the dynamics of both conditions as people age and calculate the associated risk of death, nursing home admission, and need for home care. Methods: Data were drawn from the primary care electronic health records of a longitudinal cohort of people aged 65 or older in Catalonia in 2010–2019. Frailty and multimorbidity were measured using validated instruments (eFRAGICAP, a cumulative deficit model; and SNAC-K, respectively), and their longitudinal evolution was described. Cox regression models accounted for the competing risk of death and adjusted by sex, socioeconomical status, and time-varying age, alcohol and smoking. Findings: We included 1 456 052 patients. Prevalence of multimorbidity was consistently high regardless of age, while frailty almost quadrupled from 65 to 99 years. Frailty worsened and also changed with age: up to 84 years, it was more related to concurrent diseases, and afterwards, to frailty-related deficits. While concurrent diseases contributed more to mortality, frailty-related deficits increased the risk of institutionalisation and the need for home care. Interpretation: The nature of people’s multimorbidity and frailty vary with age, as does their impact on health status. People become frailer as they age, and their frailty is more characterised by disability and other symptoms than by diseases. Mortality is most associated with the number of comorbidities, whereas frailty-related deficits are associated with needing specialised care. Funding: Instituto de Salud Carlos III through PI19/00535, and the PFIS Grant FI20/00040 (Co-funded by European Regional Development Fund/European Social Fund).

Abstract This study aimed to analyse the trajectories and mortality of multimorbidity patterns in patients aged 65 to 99 years in Catalonia (Spain). Five year (2012–2016) data of 916,619 participants from a primary care, population-based electronic health record database (Information System for Research in Primary Care, SIDIAP) were included in this retrospective cohort study. Individual longitudinal trajectories were modelled with a Hidden Markov Model across multimorbidity patterns. We computed the mortality hazard using Cox regression models to estimate survival in multimorbidity patterns. Ten multimorbidity patterns were originally identified and two more states (death and drop-outs) were subsequently added. At baseline, the most frequent cluster was the Non-Specific Pattern (42%), and the least frequent the Multisystem Pattern (1.6%). Most participants stayed in the same cluster over the 5 year follow-up period, from 92.1% in the Nervous, Musculoskeletal pattern to 59.2% in the Cardio-Circulatory and Renal pattern. The highest mortality rates were observed for patterns that included cardio-circulatory diseases: Cardio-Circulatory and Renal (37.1%); Nervous, Digestive and Circulatory (31.8%); and Cardio-Circulatory, Mental, Respiratory and Genitourinary (28.8%). This study demonstrates the feasibility of characterizing multimorbidity patterns along time. Multimorbidity trajectories were generally stable, although changes in specific multimorbidity patterns were observed. The Hidden Markov Model is useful for modelling transitions across multimorbidity patterns and mortality risk. Our findings suggest that health interventions targeting specific multimorbidity patterns may reduce mortality in patients with multimorbidity.

The co-occurrence of chronic diseases in the same person increases the risk of negative health events. Here authors show that grouping people based on their underlying disease patterns helps to identify homogeneous groups of people with similar needs and prognosis, facilitating personalized approaches.

Abstract Background The implementation of individual clinical practice guidelines in patients with multimorbidity often results in polypharmacy. Our aim was to analyse medication use according to longitudinal multimorbidity patterns (MP) and determine during a 5-year period (2012–16) which MP are associated with abnormal liver and kidney function in primary care patients over 65 years of age living in Catalonia. Methods Design: Longitudinal study (years 2012 to 2016) based on the electronic health records contained in Information System for Research in Primary Care database of the Catalan Institute of Health (SIDIAP). Variables: age, sex, MP, medication and polypharmacy (drug exposure obtained from the Pharmacy Invoice Registry). Medicines were classified in accordance with the Anatomical Therapeutic Chemical Classification System (ATC). Glomerular filtration rate was used to determine abnormal kidney function, and serum levels of alkaline phosphatase, alanine transaminase and gamma-glutamyl transpeptidase were used to diagnose abnormal liver function. Statistics: For medication use in MP, we calculated annual mean packages of each drug in each MP, and observed/expected ratios were obtained by dividing mean packages in the cluster by mean packages of the same drug in the overall population. Logistic regression models were fitted to estimate the association between MP at baseline and abnormal kidney and liver function tests during follow up. Results Nine hundred sixteen thousand six hundred nineteen patients were included, and 743,827 completed the follow up. We identified one polypharmacy profile per MP, and concluded that the most prescribed drugs in each pattern corresponded to the diseases overrepresented in that specific MP. The median of drugs ranged from 3 (Cluster 1 - Non-Specific) to 8 (Cluster 10 - Multisystem Pattern). Abnormal kidney function was most commonly observed in the Cluster 4 - Cardio-Circulatory and Renal (Odds Ratio [OR] 2.19; Confidence interval [CI] 95% 2.15–2.23) and Cluster 3 - Minority Metabolic Autoimmune-Inflammatory (OR 2.16; CI 95% 2.12–2.20) MP. A higher risk of abnormal liver function was observed in the Cluster 8 - Digestive (OR 3.39; CI 95% 3.30–3.49), and Cluster 4 - Cardio-Circulatory and Renal (OR 1.96; CI 95% 1.91–2.02) MP. Conclusions A higher risk of abnormal kidney and liver function was observed in specific MP. The long-term characterisation of MP and polypharmacy illustrates the burden of chronic multimorbidity and polypharmacy in the elderly population.

Resumen: Objetivo: Explorar las debilidades, amenazas, fortalezas y oportunidades (DAFO) para el desarrollo de la participación de la ciudadanía en los proyectos de investigación gestionados por el Institut Universitari d’Investigació en Atenció Primària Jordi Gol (IDIAPJGol) según los investigadores de atención primaria de salud de Cataluña. Método: Estudio transversal realizado en 2017 con 36 equipos de investigación de atención primaria de salud acreditados por el IDIAPJGol y su personal de gestión. Se diseñó y pilotó un cuestionario abierto (papel y online) para desarrollar una técnica DAFO. Se obtuvieron 65 respuestas (14 en papel y 51 online). Se realizó un análisis de contenido temático. Resultados: La mayoría de informantes considera la participación de la ciudadanía en la investigación una estrategia útil, innovadora, viable e imprescindible, pero exige un cambio de mentalidad y un alejamiento del paradigma jerárquico. Puede ser difícil su ejecución y complicar los estudios. Les preocupa a qué ciudadanos implicar, cómo seleccionarlos, los posibles conflictos de intereses y las necesidades de formación. Las principales propuestas para su implementación son difundir estrategias previas, fomentar la motivación y las sinergias entre ciudadanos, investigadores e instituciones, y clarificar los roles de los actores implicados. El IDIAPJGol debería elaborar recomendaciones para la participación de la ciudadanía en la investigación, incentivar su inclusión, disponer de un referente y asesorar a los equipos investigadores. Conclusiones: A pesar de los retos, desarrollar la participación de la ciudadanía en la investigación en atención primaria de salud es imprescindible y factible, pero partiendo de una estrategia participativa con todos los actores. La ciudadanía puede participar en cualquier diseño y fase de la investigación adaptando cada proyecto, siendo la atención primaria un ámbito privilegiado para desarrollar la participación ciudadana en la investigación. Abstract: Objective: Explore the strengths, weaknesses, opportunities and threats (SWOT) for development of public involvement in research by Institut Universitari d’Investigació en Atenció Primària Jordi Gol (IDIAPJGol) according to primary health care researchers in Catalonia (Spain). Methods: Cross-sectional study carried out in 2017 with 36 primary health care research teams accredited by IDIAPJGol and its management staff. An open questionnaire (paper and online) was designed and piloted to develop a SWOT technique, and 65 answers were obtained (14 in paper and 51 online). A thematic content analysis was carried out. Results: Most informants consider public involvement in research a useful, innovative, viable and essential strategy, but it requires a change of mentality and a move away from the hierarchical paradigm. It can be difficult to execute and can complicate studies. They are concerned about which citizens should be involve, how to select them, possible conflicts of interest and training needs. The main proposals for its implementation are to disseminate previous strategies, encourage motivation and synergies among citizens, researchers and institutions, and to clarify the roles of the actors involved. IDIAPJGol should develop recommendations for the public involvement in research, encourage their inclusion, have a mentor and advise the research teams. Conclusions: Despite the challenges, developing public involvement in research in primary health care is essential and feasible, what it is more should be based on a participatory strategy with all actors. The citizens can participate in any kind of design and phase of the research, adapting each project, being the primary health care a privileged area to develop the public involvement in research. Palabras clave: Atención primaria de salud, DAFO, Investigación, Participación ciudadana, Keywords: Primary health care, SWOT, Research, Citizen participation

Objectives To estimate the frequency of chronic conditions and geriatric syndromes in older patients admitted to hospital because of an exacerbation of their chronic conditions, and to identify multimorbidity clusters in these patients.Design Multicentre, prospective cohort study.Setting Internal medicine or geriatric services of five general teaching hospitals in Spain.Participants 740 patients aged 65 and older, hospitalised because of an exacerbation of their chronic conditions between September 2016 and December 2018.Primary and secondary outcome measures Active chronic conditions and geriatric syndromes (including risk factors) of the patient, a score about clinical management of chronic conditions during admission, and destination at discharge were collected, among other variables. Multimorbidity patterns were identified using fuzzy c-means cluster analysis, taking into account the clinical management score. Prevalence, observed/expected ratio and exclusivity of each chronic condition and geriatric syndrome were calculated for each cluster, and the final solution was approved after clinical revision and discussion among the research team.Results 740 patients were included (mean age 84.12 years, SD 7.01; 53.24% female). Almost all patients had two or more chronic conditions (98.65%; 95% CI 98.23% to 99.07%), the most frequent were hypertension (81.49%, 95% CI 78.53% to 84.12%) and heart failure (59.86%, 95% CI 56.29% to 63.34%). The most prevalent geriatric syndrome was polypharmacy (79.86%, 95% CI 76.82% to 82.60%). Four statistically and clinically significant multimorbidity clusters were identified: osteoarticular, psychogeriatric, cardiorespiratory and minor chronic disease. Patient-level variables such as sex, Barthel Index, number of chronic conditions or geriatric syndromes, chronic disease exacerbation 3 months prior to admission or destination at discharge differed between clusters.Conclusions In older patients admitted to hospital because of the exacerbation of chronic health problems, it is possible to define multimorbidity clusters using soft clustering techniques. These clusters are clinically relevant and could be the basis to reorganise healthcare circuits or processes to tackle the increasing number of older, multimorbid patients.Trial registration number NCT02830425.

(1) Introduction: Cardiovascular disease is associated with high mortality, especially in older people. This study aimed to characterize the evolution of combined multimorbidity and polypharmacy patterns in older people with different cardiovascular disease profiles. (2) Material and methods: This longitudinal study drew data from the Information System for Research in Primary Care in people aged 65 to 99 years with profiles of cardiovascular multimorbidity. Combined patterns of multimorbidity and polypharmacy were analysed using fuzzy c-means clustering techniques and hidden Markov models. The prevalence, observed/expected ratio, and exclusivity of chronic diseases and/or groups of these with the corresponding medication were described. (3) Results: The study included 114,516 people, mostly men (59.6%) with a mean age of 78.8 years and a high prevalence of polypharmacy (83.5%). The following patterns were identified: Mental, behavioural, digestive and cerebrovascular; Neuropathy, autoimmune and musculoskeletal; Musculoskeletal, mental, behavioural, genitourinary, digestive and dermatological; Non-specific; Multisystemic; Respiratory, cardiovascular, behavioural and genitourinary; Diabetes and ischemic cardiopathy; and Cardiac. The prevalence of overrepresented health problems and drugs remained stable over the years, although by study end, cohort survivors had more polypharmacy and multimorbidity. Most people followed the same pattern over time; the most frequent transitions were from Non-specific to Mental, behavioural, digestive and cerebrovascular and from Musculoskeletal, mental, behavioural, genitourinary, digestive and dermatological to Non-specific. (4) Conclusions: Eight combined multimorbidity and polypharmacy patterns, differentiated by sex, remained stable over follow-up. Understanding the behaviour of different diseases and drugs can help design individualised interventions in populations with clinical complexity.

Abstract Background Older adults suffer from various chronic conditions which make them particularly vulnerable. The proper management of multiple drug use is therefore crucial. The aim of our study was to describe drug prescription and medication patterns in this population. Methods A cross-sectional study in Barcelona (Spain) using electronic health records from 50 primary healthcare centres. Participants were aged 65 to 94 years, presenting multimorbidity (≥2 chronic diseases), and had been prescribed at least 1 drug for 6 months or longer during 2009. We calculated the prevalence of prescribed drugs and identified medication patterns using multiple correspondence analysis and k-means clustering. Analyses were stratified by sex and age (65–79, 80–94 years). Results We studied 164,513 patients (66.8% women) prescribed a median of 4 drugs (interquartile range [IQR] = 3–7) in the 65–79 age-group and 6 drugs (IQR = 4–8) in the 80–94 age-group. A minimum of 45.9% of patients aged 65–79 years, and 61.8% of those aged 80–94 years, were prescribed 5 or more drugs. We identified 6 medication patterns, a non-specific one and 5 encompassing 8 anatomical groups (alimentary tract and metabolism, blood, cardiovascular, dermatological, musculo-skeletal, neurological, respiratory, and sensory organ). Conclusions Drug prescription is widespread among the elderly. Six medication patterns were identified, 5 of which were related to one or more anatomical group, with associations among drugs from different systems. Overall, guidelines do not accurately reflect the situation of the elderly multimorbid, new strategies for managing multiple drug uses are needed to optimize prescribing in these patients.

An amendment to this paper has been published and can be accessed via the original article.

The diagnosis of the post-COVID condition is usually achieved by excluding other diseases; however, cognitive changes are often found in the post-COVID disorder. Therefore, monitoring and treating the recovery from the post-COVID condition is necessary to establish biomarkers to guide the diagnosis of symptoms, including cognitive impairment. Our study employs a prospected cohort and nested case–control design with mixed methods, including statistical analyses, interviews, and focus groups. Our main aim is to identify biomarkers (functional and structural neural changes, inflammatory and immune status, vascular and vestibular signs and symptoms) easily applied in primary care to detect cognitive changes in post-COVID cases. The results will open up a new line of research to inform diagnostic and therapeutic decisions with special considerations for cognitive impairment in the post-COVID condition.

Abstract Background The purpose of this study was to ascertain multimorbidity patterns using a non-hierarchical cluster analysis in adult primary patients with multimorbidity attended in primary care centers in Catalonia. Methods Cross-sectional study using electronic health records from 523,656 patients, aged 45–64 years in 274 primary health care teams in 2010 in Catalonia, Spain. Data were provided by the Information System for the Development of Research in Primary Care (SIDIAP), a population database. Diagnoses were extracted using 241 blocks of diseases (International Classification of Diseases, version 10). Multimorbidity patterns were identified using two steps: 1) multiple correspondence analysis and 2) k-means clustering. Analysis was stratified by sex. Results The 408,994 patients who met multimorbidity criteria were included in the analysis (mean age, 54.2 years [Standard deviation, SD: 5.8], 53.3% women). Six multimorbidity patterns were obtained for each sex; the three most prevalent included 68% of the women and 66% of the men, respectively. The top cluster included coincident diseases in both men and women: Metabolic disorders, Hypertensive diseases, Mental and behavioural disorders due to psychoactive substance use, Other dorsopathies, and Other soft tissue disorders. Conclusion Non-hierarchical cluster analysis identified multimorbidity patterns consistent with clinical practice, identifying phenotypic subgroups of patients.

Abstract Background Multimorbidity is the coexistence of more than two chronic diseases in the same individual; however, there is no consensus about the best definition. In addition, few studies have described the variability of multimorbidity patterns over time. The aim of this study was to identify multimorbidity patterns and their variability over a 6-year period in patients older than 65 years attended in primary health care. Methods A cohort study with yearly cross-sectional analysis of electronic health records from 50 primary health care centres in Barcelona. Selected patients had multimorbidity and were 65 years of age or older in 2009. Diagnoses (International Classification of Primary Care, second edition) were extracted using O’Halloran criteria for chronic diseases. Multimorbidity patterns were identified using two steps: 1) multiple correspondence analysis and 2) k-means clustering. Analysis was stratified by sex and age group (65–79 and ≥80 years) at the beginning of the study period. Results Analysis of 2009 electronic health records from 190,108 patients with multimorbidity (59.8% women) found a mean age of 71.8 for the 65–79 age group and 84.16 years for those over 80 (Standard Deviation [SD] 4.35 and 3.46, respectively); the median number of chronic diseases was seven (Interquartil range [IQR] 5–10). We obtained 6 clusters of multimorbidity patterns (1 nonspecific and 5 specifics) in each group, being the specific ones: Musculoskeletal, Endocrine-metabolic, Digestive/Digestive-respiratory, Neurological, and Cardiovascular patterns. A minimum of 42.5% of the sample remained in the same pattern at the end of the study, reflecting the stability of these patterns. Conclusions This study identified six multimorbidity patterns per each group, one nonnspecific pattern and five of them with a specific pattern related to an organic system. The multimorbidity patterns obtained had similar characteristics throughout the study period. These data are useful to improve clinical management of each specific subgroup of patients showing a particular multimorbidity pattern.

ObjectivesThe aim of this study was to identify, with soft clustering methods, multimorbidity patterns in the electronic health records of a population ≥65 years, and to analyse such patterns in accordance with the different prevalence cut-off points applied. Fuzzy cluster analysis allows individuals to be linked simultaneously to multiple clusters and is more consistent with clinical experience than other approaches frequently found in the literature.DesignA cross-sectional study was conducted based on data from electronic health records.Setting284 primary healthcare centres in Catalonia, Spain (2012).Participants916 619 eligible individuals were included (women: 57.7%).Primary and secondary outcome measuresWe extracted data on demographics, International Classification of Diseases version 10 chronic diagnoses, prescribed drugs and socioeconomic status for patients aged ≥65. Following principal component analysis of categorical and continuous variables for dimensionality reduction, machine learning techniques were applied for the identification of disease clusters in a fuzzy c-means analysis. Sensitivity analyses, with different prevalence cut-off points for chronic diseases, were also conducted. Solutions were evaluated from clinical consistency and significance criteria.ResultsMultimorbidity was present in 93.1%. Eight clusters were identified with a varying number of disease values: nervous and digestive; respiratory, circulatory and nervous; circulatory and digestive; mental, nervous and digestive, female dominant; mental, digestive and blood, female oldest-old dominant; nervous, musculoskeletal and circulatory, female dominant; genitourinary, mental and musculoskeletal, male dominant; and non-specified, youngest-old dominant. Nuclear diseases were identified for each cluster independently of the prevalence cut-off point considered.ConclusionsMultimorbidity patterns were obtained using fuzzy c-means cluster analysis. They are clinically meaningful clusters which support the development of tailored approaches to multimorbidity management and further research.

Aging, multimorbidity, and polypharmacy are associated with medication-related problems (MRPs). This study aimed to assess the association that multimorbidity and mortality have with MRPs in older people over time. We followed multimorbid, older (65–99 years) people in Catalonia from 2012 to 2016, using longitudinal data and Cox models to estimate adjusted hazard ratios (HR). We reviewed electronic health records to collect explanatory variables and MRPs (duplicate therapy, drug–drug interactions, potentially inappropriate medications (PIM), and contraindicated drugs in chronic kidney disease (CKD) or liver disease). There were 723,016 people (median age: 74 years; 58.9% women) who completed follow-up. We observed a significant (p < 0.001) increase in the proportion with at least one MRP (2012: 66.9% to 2016: 75.5%); contraindicated drugs in CKD (11.1 to 18.5%) and liver disease (3.9 to 5.3%); and PIMs (62.5 to 71.1%), especially drugs increasing fall risk (67.5%). People with ≥10 diseases had more MRPs (in 2016: PIMs, 89.6%; contraindicated drugs in CKD, 34.4%; and in liver disease, 9.3%). All MRPs were independently associated with mortality, from duplicate therapy (HR 1.06; 95% confidence interval (CI) 1.04–1.08) to interactions (HR 1.60; 95% CI 1.54–1.66). Ensuring safe pharmacological treatment in elderly, multimorbid patient remains a challenge for healthcare systems.

Objetivo: Identificar los patrones de multimorbilidad en pacientes de 19-44 años atendidos en atención primaria en Cataluña en el año 2010. Diseño: Estudio descriptivo transversal. Emplazamiento: Doscientos cincuenta y un centros de salud. Participantes: Fueron 530.798 personas con multimorbilidad de 19-44 años. Mediciones principales: La multimorbilidad fue definida como la coexistencia de ≥2 diagnósticos de la Clasificación Internacional de Enfermedades registrados en la historia clínica informatizada. Los patrones de multimorbilidad fueron identificados a través de un análisis jerárquico de clústeres y descritos por sexo y grupos de edad (19-24 y 25-44 años). Resultados: De las 882.708 personas de la población inicial, 530.798 (60,1%) presentaron multimorbilidad. La media de edad fue de 33,0 años (DT: 7,0) y el 53,3% fueron mujeres. La multimorbilidad fue más alta en el grupo de 25-44 años respecto al grupo más joven (60,5 vs. 58,1%, p

The purpose of this study was to identify clusters of diagnoses in elderly patients with multimorbidity, attended in primary care.Cross-sectional study.251 primary care centres in Catalonia, Spain.Individuals older than 64 years registered with participating practices.Multimorbidity, defined as the coexistence of 2 or more ICD-10 disease categories in the electronic health record. Using hierarchical cluster analysis, multimorbidity clusters were identified by sex and age group (65-79 and ≥80 years).322,328 patients with multimorbidity were included in the analysis (mean age, 75.4 years [Standard deviation, SD: 7.4], 57.4% women; mean of 7.9 diagnoses [SD: 3.9]). For both men and women, the first cluster in both age groups included the same two diagnoses: Hypertensive diseases and Metabolic disorders. The second cluster contained three diagnoses of the musculoskeletal system in the 65- to 79-year-old group, and five diseases coincided in the ≥80 age group: varicose veins of the lower limbs, senile cataract, dorsalgia, functional intestinal disorders and shoulder lesions. The greatest overlap (54.5%) between the three most common diagnoses was observed in women aged 65-79 years.This cluster analysis of elderly primary care patients with multimorbidity, revealed a single cluster of circulatory-metabolic diseases that were the most prevalent in both age groups and sex, and a cluster of second-most prevalent diagnoses that included musculoskeletal diseases. Clusters unknown to date have been identified. The clusters identified should be considered when developing clinical guidance for this population.

BackgroundThe aim of the present study is to evaluate the impact of glucose-lowering agents in the risk of cancer in a large type 2 diabetic population.MethodsA nested case-control study was conducted within a defined cohort (275,164 type 2 diabetic patients attending 16 Primary Health Care Centers of Barcelona). Cases (n = 1,040) comprised those subjects with any cancer diagnosed between 2008 and 2010, registered at the Cancer Registry of Hospital Vall d'Hebron (Barcelona). Three control subjects for each case (n = 3,120) were matched by age, sex, diabetes duration, and geographical area. The treatments analyzed (within 3 years prior to cancer diagnosis) were: insulin glargine, insulin detemir, human insulin, fast-acting insulin and analogues, metformin, sulfonylureas, repaglinide, thiazolidinediones, dipeptidyl peptidase-4 inhibitors, and alpha glucosidase inhibitors. Conditional logistic regressions were used to calculate the risk of cancer associated with the use of each drug adjusted by age, BMI, dose and duration of treatment, alcohol use, smoking habit, and diabetes duration.ResultsNo differences were observed between case and control subjects for the proportion, dose or duration of exposure to each treatment. None of the types of insulin and oral agents analyzed showed a significant increase in the risk of cancer. Moreover, no cancer risk was observed when glargine was used alone or in combination with metformin.ConclusionsOur results suggest that diabetes treatment does not influence the risk of cancer associated with type 2 diabetes. Therefore, an eventual increase of cancer should not be a reason for biasing the selection of any glucose-lowering treatment in type 2 diabetic population.