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Background the aim of this study was to examine the cross-sectional and longitudinal associations of different multimorbidity patterns with physical frailty in older adults. Methods we used data from the Swedish National study on Aging and Care in Kungsholmen to generate a physical frailty measure, and clusters of participants with similar multimorbidity patterns were identified through fuzzy c-means cluster analyses. The cross-sectional association (n = 2,534) between multimorbidity clusters and physical frailty was measured through logistic regression analyses. Six- (n = 2,122) and 12-year (n = 2,140) longitudinal associations were determined through multinomial logistic regression analyses. Results six multimorbidity patterns were identified at baseline: psychiatric diseases; cardiovascular diseases, anaemia and dementia; sensory impairments and cancer; metabolic and sleep disorders; musculoskeletal, respiratory and gastrointestinal diseases; and an unspecific pattern lacking any overrepresented diseases. Cross-sectionally, each pattern was associated with physical frailty compared with the unspecific pattern. Over 6 years, the psychiatric diseases (relative risk ratio [RRR]: 3.04; 95% confidence intervals [CI]: 1.59–5.79); cardiovascular diseases, anaemia and dementia (RRR 2.25; 95% CI: 1.13–4.49) and metabolic and sleep disorders (RRR 1.99; 95% CI: 1.25–3.16) patterns were associated with incident physical frailty. The cardiovascular diseases, anaemia and dementia (RRR: 4.81; 95% CI: 1.59–14.60); psychiatric diseases (RRR 2.62; 95% CI: 1.45–4.72) and sensory impairments and cancer (RRR 1.87; 95% CI: 1.05–3.35) patterns were more associated with physical frailty, compared with the unspecific pattern, over 12 years. Conclusions we found that older adults with multimorbidity characterised by cardiovascular and neuropsychiatric disease patterns are most susceptible to developing physical frailty.

The evolution of multimorbidity patterns during aging is still an under-researched area. We lack evidence concerning the time spent by older adults within one same multimorbidity pattern, and their transitional probability across different patterns when further chronic diseases arise. The aim of this study is to fill this gap by exploring multimorbidity patterns across decades of age in older adults, and longitudinal dynamics among these patterns.Longitudinal study based on the Swedish National study on Aging and Care in Kungsholmen (SNAC-K) on adults ≥60 years (N=3,363). Hidden Markov Models were applied to model the temporal evolution of both multimorbidity patterns and individuals' transitions over a 12-year follow-up.Within the study population (mean age 76.1 years, 66.6% female), 87.2% had ≥2 chronic conditions at baseline. Four longitudinal multimorbidity patterns were identified for each decade. Individuals in all decades showed the shortest permanence time in anOur findings highlight the dynamism and heterogeneity underlying multimorbidity by quantifying the varying permanence times and transition probabilities across patterns in different decades. With increasing age, older adults experience decreasing stability and progressively shorter permanence time within one same multimorbidity pattern.

Resumen Objetivo El objetivo de este estudio es analizar el uso, la efectividad, la seguridad y los costes de la prevencion de ictus en fibrilacion auricular (FA) no valvular en pacientes que inician tratamiento con dabigatran o antagonistas de la vitamina K (AVK). Emplazamiento Atencion Primaria (AP) del Instituto Catalan de la Salud (ICS), en Cataluna, durante el periodo 2011-2013. Participantes Todos los pacientes atendidos en los centros de AP del ICS con diagnostico de FA que inician dabigatran o AVK. Intervenciones No aplica (estudio observacional). Mediciones principales Numero de prescripciones y facturaciones de dabigatran y AVK, incidencia de ictus y eventos tromboembolicos, incidencia de hemorragias mayores, incidencia de muertes durante el seguimiento, numero de bajas laborales y medida de los costes asociados a estas variables. Resultados Se incluyo a 14.930 pacientes en el estudio; el 94,6% inicio AVK y el 5,4%, dabigatran. Estos ultimos eran pacientes mas jovenes y con menos comorbilidades asociadas. No hubo diferencias estadisticamente significativas entre AVK y dabigatran en el riesgo de ictus, hemorragias y mortalidad. Los costes asociados al manejo de la FA eran mayores para visitas de AP en el grupo de AVK y mayores para laboratorio, y farmacia en el grupo de dabigatran, aunque los costes totales no fueron estadisticamente diferentes. Conclusiones La mayoria de los pacientes iniciaron AVK. No hubo diferencias entre AVK y dabigatran en el riesgo de ictus, hemorragias y mortalidad.

BackgroundUnderstanding humoral responses and seroprevalence in SARS-CoV-2 infection is essential for guiding vaccination strategies in both infected and uninfected individuals.MethodsWe determine the kinetics of IgM against the nucleocapsid (N) and IgG against the spike (S) and N proteins of SARS-CoV-2 in a cohort of 860 health professionals (healthy and infected) in northern Barcelona. We model the kinetics of IgG and IgM at nine time points over 13.5 months from infection, using non-linear mixed models by sex and clinical disease severity.ResultsOf the 781 participants who were followed up, 478 (61.2%) became infected with SARS-CoV-2. Significant differences were found for the three antibodies by disease severity and sex. At day 270 after diagnosis, median IgM(N) levels were already below the positivity threshold in patients with asymptomatic and mild-moderate disease, while IgG(N, S) levels remained positive to days 360 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 whose rate depended on disease severity. IgG(S) levels increased at day 15 and remained relatively constant over time.ConclusionsWe describe kinetic models of IgM(N) and IgG(N, S) SARS-CoV-2 antibodies at 13.5 months from infection and disease spectrum. Our analyses delineate differences in the kinetics of IgM and IgG over a year and differences in the levels of IgM and IgG as early as 15 days from symptoms onset in severe cases. These results can inform public health policies around vaccination criteria.Funded by the regional Ministry of Health of the Generalitat de Catalunya (Call COVID19-PoC SLT16_04; NCT04885478)

Altres ajuts: Pla Estratègic de Recerca i Innovació en Salut (PERIS), SLT002/16/00058 Background: The acquisition of multiple chronic diseases, known as multimorbidity, is common in the elderly population, and it is often treated with the simultaneous consumption of several prescription drugs, known as polypharmacy. These two concepts are inherently related and cause an undue burden on the individual. The aim of this study was to identify combined multimorbidity and polypharmacy patterns for the elderly population in Catalonia. Methods: A cross-sectional study using electronic health records from 2012 was conducted. A mapping process was performed linking chronic disease categories to the drug categories indicated for their treatment. A soft clustering technique was then carried out on the final mapped categories. Results: 916,619 individuals were included, with 93.1% meeting the authors' criteria for multimorbidity and 49.9% for polypharmacy. A seven-cluster solution was identified: one non-specific (Cluster 1) and six specific, corresponding to diabetes (Cluster 2), neurological and musculoskeletal, female dominant (Clusters 3 and 4) and cardiovascular, cerebrovascular and renal diseases (Clusters 5 and 6), and multi-system diseases (Cluster 7). Conclusions: This study utilized a mapping process combined with a soft clustering technique to determine combined patterns of multimorbidity and polypharmacy in the elderly population, identifying overrepresentation in six of the seven clusters with chronic disease and chronic disease-drug categories. These results could be applied to clinical practice guidelines in order to better attend to patient needs. This study can serve as the foundation for future longitudinal regarding relationships between multimorbidity and polypharmacy.

Background/Objectives To assess the adherence to reporting confidence intervals (CI) for measures of association in multivariable regression models (MRM) in articles with observational design indexed in MEDLINE. Material and methods A literature search was conducted using the MEDLINE bibliographic database to obtain a representative sample of studies with observational design and applying MRM (logistic, linear, and Cox regression) (n = 428). Proportions and 95% CI of articles reporting CI for measures of association in MRM were calculated. Percentage ratios (PRs) were also calculated to describe the change in CI reporting before and after the publication of the STROBE statement. Results 188 of the 236 abstracts with measures of association (79.7%; 95% CI 74.5, 84.8) and 360 of the 428 main texts (84.1%; 80.6, 87.6) were provided with CI. A non-significant increase of 1% in the abstract, PR = 1.01 (0.77, 1.29), and 7% in the main text, PR = 1.07 (0.87, 1.28), occurred in the CI reporting after the publication of the STROBE guideline. Conclusions The STROBE guideline recommendation on reporting CI should be more thoroughly followed.

Ambulatory blood pressure (BP) is associated with mortality, but it is also interesting to expand its association with cardiovascular morbidity. This study sought to evaluate association with cardiovascular morbidity and cardiovascular mortality. Patients without cardiovascular disease who had a first 24-hour ambulatory BP monitoring were followed-up until the onset of the first event (a combined variable of cardiovascular mortality, coronary heart disease, cerebrovascular disease, peripheral arteriopathy, or hospital admission for heart failure). Changes in antihypertensive treatment couldn't be collected. Cox regression analysis was adjusted for risk factors and office BP. We included 3907 patients (mean age, 58.0, SD 13.8 years), of whom 85.5% were hypertensive. The follow up period was 6.6 (95% CI 5.0-8.5) years. A total of 496 (12.7%) events were recorded. The incidence rate was 19.3 (95% CI 17.7-21.1) cases per 1000 person-years. The patients with an event compared to the rest of patients were mostly men, older, with higher office and ambulatory systolic BP, higher prevalence of diabetes, chronic kidney disease, dyslipidemia, and non-dipper or riser circadian profile. In the fully adjusted model, office BP loses its significant association with the main variable. Ambulatory BP association remained significant with cardiovascular morbidity and mortality, HR 1.494 (1.326-1.685) and 0.767 (0.654-0.899) for 24-hour systolic and diastolic BP, respectively. Nighttime systolic BP also maintained this significant association, 1.270 (1.016-1.587). We conclude that nighttime systolic BP and 24-hour BP are significantly associated with cardiovascular events and cardiovascular mortality in patients without cardiovascular disease attended under conditions of routine clinical practice.

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 &lt, 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.

Funding: Swedish National study on Aging and Care; Ministry of Health and Social Affairs; Swedish Research Council, Grant/Award Number: 2016-00981; Swedish Research Council for Health,Working Life andWelfare, Grant/Award Number: 2017-01764; Italian Ministry of Health, Grant/Award Number: PE-2016-02364885 We investigate dementia risk in older adults with different disease patterns and explore the role of inflammation and apolipoprotein E (APOE) genotype. A total of 2,478 dementia-free participants with two or more chronic diseases (ie, multimorbidity) part of the Swedish National study on Aging and Care in Kungsholmen (SNAC-K) were grouped according to their multimorbidity patterns and followed to detect clinical dementia. The potential modifier effect of C-reactive protein (CRP) and apolipoprotein E (APOE) genotype was tested through stratified analyses. People with neuropsychiatric, cardiovascular, and sensory impairment/cancer multimorbidity had increased hazards for dementia compared to the unspecific (Hazard ration (HR) 1.66, 95% confidence interval [CI] 1.13-2.42; 1.61, 95% CI 1.17-2.29; 1.32, 95% CI 1.10-1.71, respectively). Despite the lack of statistically significant interaction, high CRP increased dementia risk within these patterns, and being APOE ε4 carriers heightened dementia risk for neuropsychiatric and cardiovascular multimorbidity. Individuals with neuropsychiatric, cardiovascular, and sensory impairment/cancer patterns are at increased risk for dementia and APOE ε4, and inflammation may further increase the risk. Identifying such high-risk groups might allow tailored interventions for dementia prevention.

Background: The changes in shield strategies, treatments, emergence variants, and healthcare pathways might shift the profile and outcome of patients hospitalized with COVID-19 in successive waves of the outbreak. Methods: We retrospectively analysed the characteristics and in-hospital outcomes of all patients admitted with COVID-19 in eight university hospitals of Catalonia (North-East Spain) between Feb 28, 2020 and Feb 28, 2021. Using a mathematical model, we split admissions into four waves, one of them (summer wave) with little incidence. The main hospital outcomes included 30-day mortality and admission to intensive care unit (ICU). Findings: The analysis included 17,027 subjects admitted during the first wave (6,800; 39.9%), summer wave (1,807; 10.6%), second wave (3,804; 22.3%), and third wave (4,616; 27.1%). The highest 30-day mortality rate was reported during the first wave (17%) and decreased afterwards, remaining stable at 13% in the second and third waves (overall 30% reduction); the lowest mortality was reported during the summer wave (8%, 50% reduction). ICU admission became progressively more frequent during successive waves. In Cox regression analysis, the main independent predictors of 30-day mortality were the epidemic wave, followed by gender, age, diabetes, chronic kidney disease, and neoplasms. Interpretation: In-hospital COVID-19 mortality has decreased substantially after the first wave, but continues to be high and is highly dependent of patient’s characteristics and ICU availability. Highest mortality reductions occurred during a wave characterized by younger individuals, an increasingly frequent scenario as vaccination campaigns progress. Funding Information: This work was partially funded by the grant COVID19 6_17 (to Francesc Vidal), Direccio General de Recerca i Innovacio en Salut (Departament de Salut) and BIOCAT, Generalitat de Catalunya. Declaration of Interests: KK is a member of the UK Scientific Advisory Group for Emergencies. All other authors have nothing to declare. Ethics Approval Statement: The study protocol was approved by the independent ethics committee of the Hospital Germans Trias i Pujol (Badalona, Spain), which waived obtaining informed consent.

The presence of multiple chronic conditions (i.e., multimorbidity) increases the risk of hospitalisation in older adults. We aimed to examine the association between different multimorbidity patterns and unplanned hospitalisations over 5 years. To that end, 2,250 community-dwelling individuals aged 60 years and older from the Swedish National Study on Aging and Care in Kungsholmen (SNAC-K) were studied. Participants were grouped into six multimorbidity patterns using a fuzzy c-means cluster analysis. The associations between patterns and outcomes were tested using Cox models and negative binomial models. After 5 years, 937 (41.6%) participants experienced at least one unplanned hospitalisation. Compared to participants in the unspecific multimorbidity pattern, those in the cardiovascular diseases, anaemia and dementia pattern, the psychiatric disorders pattern and the metabolic and sleep disorders pattern presented with a higher hazard of first unplanned hospitalisation (hazard ratio range: 1.49&ndash, 2.05, p &lt, 0.05 for all), number of unplanned hospitalisations (incidence rate ratio (IRR) range: 1.89&ndash, 2.44, 0.05 for all), in-hospital days (IRR range: 1.91&ndash, 3.61, 0.05 for all), and 30-day unplanned readmissions (IRR range: 2.94&ndash, 3.65, 0.05 for all). Different multimorbidity patterns displayed a differential association with unplanned hospital care utilisation. These findings call for a careful primary care follow-up of older adults with complex multimorbidity patterns.

Objectives The aim was to evaluate patterns of multimorbidity that increase the risk of institutionalization in older persons, also exploring the potential buffering effect of formal and informal care. Design Prospective cohort study. Setting and Participants The population-based Swedish National study on Aging and Care in Kungsholmen, Stockholm, Sweden. Measures In total, 2571 community-dwelling older adults were grouped at baseline according to their underlying multimorbidity patterns, using a fuzzy c-means cluster algorithm, and followed up for 6 years to test the association between multimorbidity patterns and institutionalization. Results Six patterns of multimorbidity were identified: psychiatric diseases; cardiovascular diseases, anemia, and dementia; metabolic and sleep disorders; sensory impairments and cancer; musculoskeletal, respiratory, and gastrointestinal diseases; and an unspecific pattern including diseases of which none were overrepresented. In total, 110 (4.3%) participants were institutionalized during the follow-up, ranging from 1.7% in the metabolic and sleep disorders pattern to 8.4% in the cardiovascular diseases, anemia, and dementia pattern. Compared with the unspecific pattern, only the cardiovascular diseases, anemia, dementia pattern was significantly associated with institutionalization [relative risk ratio (RRR) = 2.23; 95% confidence interval (CI) 1.07‒4.65)], after adjusting for demographic characteristics and disability status at baseline. In stratified analyses, those not receiving formal care in the psychiatric diseases pattern (RRR 3.34; 95% CI 1.20‒9.32) and those not receiving formal or informal care in the ‘cardiovascular diseases, anemia, dementia’ pattern (RRR 2.99; 95% CI 1.20‒7.46; RRR 2.79; 95% CI 1.16‒6.71, respectively) had increased risks of institutionalization. Conclusions and Implications Older persons suffering from specific multimorbidity patterns have a higher risk of institutionalization, especially if they lack formal or informal care. Interventions aimed at preventing the clustering of diseases could reduce the associated burden on residential long-term care. Formal and informal care provision may be effective strategies in reducing the risk of institutionalization.

Multimorbidity—the co-occurrence of multiple diseases—is associated to poor prognosis, but the scarce knowledge of its development over time hampers the effectiveness of clinical interventions. Here we identify multimorbidity clusters, trace their evolution in older adults, and detect the clinical trajectories and mortality of single individuals as they move among clusters over 12 years. By means of a fuzzy c-means cluster algorithm, we group 2931 people ≥60 years in five clinically meaningful multimorbidity clusters (52%). The remaining 48% are part of an unspecific cluster (i.e. none of the diseases are overrepresented), which greatly fuels other clusters at follow-ups. Clusters contribute differentially to the longitudinal development of other clusters and to mortality. We report that multimorbidity clusters and their trajectories may help identifying homogeneous groups of people with similar needs and prognosis, and assisting clinicians and health care systems in the personalization of clinical interventions and preventive strategies., 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.

Altres ajuts: Department of Health of the Catalan Government/SLT002/16/00058 The aim of this study was to determine medication-related problems (MRPs) in primary care patients over 65 years of age. Cross-sectional study based on the electronic health records of patients (65-99 years of age) visited in 284 primary health care centers during 2012 in Catalonia. Variables: age, sex, sociodemographic variables, number of drugs, kidney and liver function and MRPs (duplicate therapy, drug-drug interactions, potentially inappropriate medications [PIMs] and drugs contraindicated in chronic kidney disease and in liver diseases). Unconditional logistic regression models were used to identify the factors associated with MRPs in patients with multimorbidity. 916 619 older people were included and 853 085 of them met the criteria for multimorbidity. Median age was 75 years and 57.7% of them were women. High percentages of MRPs were observed: PIMs (62.8%), contraindicated drugs in chronic kidney disease (12.1%), duplicate therapy (11.1%), contraindicated drugs in liver diseases (4.2%), and drug-drug interactions (1.0%). These numbers were higher in the subgroup of patients with ≥10 diseases. The most common PIMs were connected to drugs that increase the risk of fall (66.8%), antiulcer agents without criteria for gastroprotection (40.6%), and the combination of drugs with anticholinergic effects (39.7%). In the multivariate analysis, the variables associated with all MRPs among the patients with multimorbidity were the number of drugs and the number of visits. The coexistence of multimorbidity and polypharmacy is associated with an elevated risk of MRPs in older people. Medication safety for older patients constitutes a pressing concern for health services.

Background The aim of this study is to identify clusters of older persons based on their multimorbidity patterns and to analyze differences among clusters according to sociodemographic, lifestyle, clinical, and functional characteristics. Methods We analyzed data from the Swedish National Study on Aging and Care in Kungsholmen on 2,931 participants aged 60 years and older who had at least two chronic diseases. Participants were clustered by the fuzzy c-means cluster algorithm. A disease was considered to be associated with a given cluster when the observed/expected ratio was ≥2 or the exclusivity was ≥25%. Results Around half of the participants could be classified into five clinically meaningful clusters: respiratory and musculoskeletal diseases (RESP-MSK) 15.7%, eye diseases and cancer (EYE-CANCER) 10.7%, cognitive and sensory impairment (CNS-IMP) 10.6%, heart diseases (HEART) 9.3%, and psychiatric and respiratory diseases (PSY-RESP) 5.4%. Individuals in the CNS-IMP cluster were the oldest, with the worst function and more likely to live in a nursing home; those in the HEART cluster had the highest number of co-occurring diseases and drugs, and they exhibited the highest mean values of serum creatinine and C-reactive protein. The PSY-RESP cluster was associated with higher levels of alcoholism and neuroticism. The other half of the cohort was grouped in an unspecific cluster, which was characterized by gathering the youngest individuals, with the lowest number of co-occurring diseases, and the best functional and cognitive status. Conclusions The identified multimorbidity patterns provide insight for setting targets for secondary and tertiary preventative interventions and for designing care pathways for multimorbid older people.

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. This work was supported by a research grant from the Carlos III Institute of Health, Ministry of Economy and Competitiveness (Spain), awarded for the 2016 call under the Health Strategy Action 2013–2016, within the National Research Program oriented to Societal Challenges, within the Technical, Scientifc and Innovation Research National Plan 2013–2016 ‘[grant number PI16/00639]’, co-funded with European Union ERDF funds (European Regional Development Fund) and the Department of Health of the Catalan Government, in the call corresponding to 2017 for the granting of subsidies from the Strategic Plan for Research in Health (Pla Estratègic de Recerca i Innovació en Salut, PERIS) 2016–2020, modality research oriented to Primary care ‘[grant number SLT002/16/00058]’ and by the Catalan Government ‘[Grant Number AGAUR 2017 SGR 578].

Tumor cells can modify the immune response in primary tumors and in the axillary lymph nodes with metastasis (ALN+) in breast cancer (BC), influencing patient outcome. We investigated whether patterns of immune cells in the primary tumor and in the axillary lymph nodes without metastasis (ALN-) differed between patients diagnosed without ALN+ (diagnosed-ALN-) and with ALN+ (diagnosed-ALN+) and the implications for clinical outcome. Eleven immune markers were studied using immunohistochemistry, tissue microarray, and digital image analysis in 141 BC patient samples (75 diagnosed-ALN+ and 66 diagnosed-ALN-). Two logistic regression models were derived to identify the clinical, pathologic, and immunologic variables associated with the presence of ALN+ at diagnosis. There are immune patterns in the ALN- associated with the presence of ALN+ at diagnosis. The regression models revealed a small subgroup of diagnosed-ALN+ with ALN- immune patterns that were more similar to those of the ALN- of the diagnosed-ALN-. This small subgroup also showed similar clinical behavior to that of the diagnosed-ALN-. Another small subgroup of diagnosed-ALN- with ALN- immune patterns was found whose members were more similar to those of the ALN- of the diagnosed-ALN+. This small subgroup had similar clinical behavior to the diagnosed-ALN+. These data suggest that the immune response present in ALN- at diagnosis could influence the clinical outcome of BC patients.

Purpose To describe the characteristics of new users of cilostazol in Europe with the aim to support the evaluation of its benefit/risk as used in regular clinical practice before the implementation of labeling changes recommended by the European Medicines Agency. Methods New users of cilostazol were identified in populations enrolled in five European health automated databases in the UK (The Health Improvement Network [THIN]), Spain (EpiChron cohort and Information System for the Improvement of Research in Primary Care [SIDIAP]), Sweden (National Registers), and Germany (German Pharmacoepidemiological Research Database [GePaRD]) between 2002 and 2012. New users were characterized according to the prevalence of cardiovascular disease and other comorbidities, concurrent use of interacting medications, new contraindications, duration of use, and potential off-label prescribing. Results We identified 22 593 new users of cilostazol. The median age was between 68.0 (THIN) and 73.7 (Sweden) years. More than 78% of users had concomitant cardiovascular disease, and between 78.8% (GePaRD) and 91.6% (THIN) were treated with interacting medications. Prevalence of new cardiovascular contraindications ranged from 1.5% (THIN) to 11.6% (GePaRD), and concurrent use of two or more antiplatelet drugs ranged from 6.3% (SIDIAP) to 13.5% (EpiChron cohort). Between 39.4% (Sweden) and 52.9% (THIN) of users discontinued cilostazol in the first 3 months. Between 41.0% (SIDIAP) and 93.4% (THIN) were considered to have received cilostazol according to the European Medicines Agency labeling. Conclusions In this collaborative European study, most cilostazol users were elderly patients with a high prevalence of cardiovascular diseases and other comorbidity and concurrent use of interacting drugs, indicating that this is a vulnerable population at high risk of complications, especially cardiovascular events. © 2017 The Authors. Pharmacoepidemiology and Drug Safety Published by John Wiley & Sons Ltd.

Purpose The aim of this study was to assess effectiveness and safety of antithrombotics for stroke prevention in non-valvular atrial fibrillation in real-use conditions. Methods We used a population-based retrospective cohort study. Information emerges from SIDIAP, a database containing anonymized information from electronic health records from 274 primary healthcare centres of the Catalan Health Institute, Catalonia (Spain), with a reference population of 5 835 000 people. Population includes all adults with a new diagnosis of non-valvular atrial fibrillation registered in SIDIAP from 2007 to 2012. The main outcome of antithrombotics' effectiveness was stroke. The main outcomes of safety were cerebral and gastrointestinal haemorrhages. We also estimated all-cause mortality. We used multivariable Cox proportional hazard models to examine association between antithrombotic treatment and main outcomes. Results We included 22 205 subjects with non-valvular atrial fibrillation; 40.8% initiated on vitamin K antagonists (VKA), 33.4% on antiplatelets and 25.8% untreated. We found stroke-risk reduction with VKA, hazard ratio (HR) 0.72 (95% confidence interval (CI), 0.58–0.91), also seen in patients with CHADS2 ≥ 2, HR 0.65 (95%CI, 0.49–0.86), and CHA2DS2-VASc ≥ 2, HR 0.66 (95%CI, 0.52–0.84). We observed a higher risk of digestive bleeding with antiplatelets, HR 1.32 (95%CI, 1.01–1.73). Both VKA and antiplatelets were associated with reduction of all-cause mortality risk; HR 0.55 (95%CI, 0.49–0.62) and HR 0.89 (95%CI, 0.80–0.97), respectively. Conclusions This study found a stroke-risk reduction associated with VKA and an increased risk of gastrointestinal bleeding associated with platelet-aggregation inhibitors in comparison with untreated patients. Both antithrombotic groups showed a reduction in all-cause mortality. Copyright © 2016 John Wiley & Sons, Ltd.

Resumen Fundamentos En el ambito de la investigacion medica los modelos de regresion logistica, lineal, Cox y Poisson son tecnicas estadisticas ampliamente conocidas. El objetivo de este trabajo es describir la evolucion de estas tecnicas de regresion en los articulos observacionales indexados en PubMed (1970-2013) y revisar los requerimientos de las normas de autor de revistas espanolas para conocer si requieren el cumplimiento de la guia STROBE. Metodos Se realizo una busqueda dirigida en PubMed para identificar los articulos que utilizaron modelos de regresion logistica, lineal, Cox y Poisson. Ademas, se revisaron las normas de autor de las revistas editadas en Espana indexadas en PubMed e incluidas en Web Of Science. Resultados El 6,1% de los articulos de estudios observacionales contenian algun termino relativo a los modelos seleccionados, pasando del 0,14% en 1980 hasta un 12,3% en 2013. Este ultimo ano, un 6,7% de los articulos contenian algun termino referido a regresion logistica, un 2,5% a lineal, un 3,5% a Cox y un 0,31% a Poisson. Por otro lado, el 12,8% de las normas de autor de las revistas revisadas recomendaban explicitamente seguir la guia STROBE, y el 35,9%, la guia CONSORT. Conclusiones Los modelos de regresion multivariantes en estudios observacionales publicados, tales como la regresion logistica, lineal, Cox y Poisson, son cada vez mas utilizados tanto a nivel global como en revistas publicadas en lengua espanola. Ademas, un porcentaje bajo de las revistas cientificas espanolas indexadas en PubMed incluyen en las normas de autoria el requerimiento de la guia STROBE.

Purpose The purpose of this study is to describe the pharmacologic management of rate and rhythm and assess which factors are associated with the prescription of these drugs in patients with nonvalvular atrial fibrillation (AF) from the Effectiveness, Safety, and Costs in Atrial Fibrillation study. Methods This retrospective, cross-sectional study describes the pharmacologic rate and rhythm control management strategies adopted during 2012 in all patients diagnosed as having nonvalvular AF in 2007 to 2011. The data source is the Information System for the Improvement of Research in Primary Care database, which is based on primary care electronic health records. To answer the study objectives, 3 multivariate regression models to assess the independent factors associated with the prescription of these drugs were conducted for 2012. The rate and rhythm control drugs assessed were β-blockers, nondihydropyridine calcium channel blockers, antiarrhythmic agents, and digoxin. Findings A total of 21,304 patients were diagnosed as having nonvalvular AF; 11,638 (54.6%) had at least one heart rate measure during 2012. Of them, 7777 (66.8%) received one or more rate and/or rhythm control drugs during 2012. Most patients (5751 [73.9%] of 7777) received only one drug for rate and/or rhythm control. Rate control agents were the most frequently used in 2012, with β-blockers the most prescribed group (4091 patients [52.6%]). A variety of different variables were associated with the prescription of rate and/or rhythm control drugs in the multivariate regression models. Implications The most used pharmacologic treatment of rate and rhythm control in our AF population is β-blockers, indicating that a rate control strategy is preferred in our setting, as widely recommended.

Cilostazol; Intermittent claudication; Peripheral artery disease; Risk minimization Claudicació intermitent; Malaltia vascular perifèrica; Minimització del risc Claudicación intermitente; Enfermedad vascular periférica; Minimización del riesgo Purpose: The purpose of the study is to evaluate the effectiveness of risk minimization measures—labeling changes and communication to health care professionals—recommended by the European Medicines Agency for use of cilostazol for the treatment of intermittent claudication in Europe. Methods: Observational study of cilostazol in The Health Improvement Network (United Kingdom), EpiChron Cohort (Spain), SIDIAP (Spain), Swedish National Databases, and GePaRD (Germany). Among new users of cilostazol, we compared the prevalence of conditions targetedby the risk minimization measures in the periods before (2002‐2012) and after (2014) implementation. Conditions evaluated were prevalence of smoking, cardiovascular conditions, concurrent use of≥2 antiplatelet agents, concurrent use of potentCYP3A4/CYP2C19 inhibitors and high‐dose cilostazol, early monitoring of all users, and continuous monitoring of users at high cardiovascular risk. Results: We included 22593 and 1821 new users of cilostazol before and afterimplementation of risk minimization measures, respectively. After implementation, the frequency of several conditions related to the labeling changes improved in all the study populations: prevalence of use decreased between 13% (EpiChron) and 57% (SIDIAP), frequency of cardiovascular contraindications decreased between 8% (GePaRD) and 84% (EpiChron), and concurrent use of high‐dose cilostazol and potent CYP3A4/CYP2C19 inhibitors decreased between 6% (Sweden) and 100% (EpiChron).The frequency of other conditions improved in most study populations, except smoking, which decreased only in EpiChron (48% reduction). Conclusions: This study indicates that the risk minimization measures implemented by the EMA for the use of cilostazol have been effective in all European countries studied, except for smoking cessation before initiating cilostazol, which remains an area of improvement Otsuka Pharmaceutical Europe Ltd.

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 The project has been funded by the Instituto de Salud Carlos III of the Ministry of Economy and Competitiveness (Spain) through the Network for Prevention and Health Promotion in Primary Health Care (redIAPP, RD12/0005), by a grant for research projects on health from ISCiii (PI12/00427) and co-financed with European Union ERDF funds). Jose M. Valderas was supported by the National Institute for Health Research Clinician Scientist Award NIHR/CS/010/024

Cardiovascular diseases are highly represented in multimorbidity patterns. Nevertheless, few studies have analysed the burden of these diseases in the population with multimorbidity. The objective of this study was to identify and describe the cardiovascular diseases among the patients with multimorbidity. Methods We designed a cross-sectional study in patients ≥19 years old assigned to 251 primary health care centres in Catalonia, Spain. The main outcome was cardiovascular morbidity burden, defined as the presence of one or more of 24 chronic cardiovascular diseases in multimorbid patients (≥2 chronic conditions). Two groups were defined, with and without multimorbidity; the multimorbidity group was further divided into cardiovascular and non-cardiovascular subgroups. The secondary outcomes were: modifiable major cardiovascular risk factors (smoking, hypertension, hypercholesterolaemia, diabetes) and cardiovascular risk score (REGICOR, Registre Gironí del Cor). Other variables analysed were: sex, age (19–24, 25–44, 45–64, 65–79, and 80+ years), number of chronic diseases, urban setting, active toxic habits (smoking and alcohol), physical parameters and laboratory tests. Results A total of 1,749,710 individuals were included (mean age, 47.4 years [SD: 17.8]; 50.7 % women), of which nearly half (46.8 %) had multimorbidity (95 % CI: 46.9–47.1). In patients with multimorbidity,, the cardiovascular burden was 54.1 % of morbidity (95 % CI: 54.0–54.2) and the four most prevalent cardiovascular diseases were uncomplicated hypertension (75.3 %), varicose veins of leg (20.6 %), “other” heart disease (10.5 %) and atrial fibrillation/flutter (6.7 %). In the cardiovascular morbidity subgroup, 38.2 % had more than one cardiovascular disease. The most prevalent duet and triplet combinations were uncomplicated hypertension & lipid disorder (38.8 %) and uncomplicated hypertension & lipid disorder & non-insulin dependent diabetes (11.3 %), respectively. By age groups, the same duet was the most prevalent in patients aged 45–80 years and in men aged 25–44 years. In women aged 19–44, varicose veins of leg & anxiety disorder/anxiety was the most prevalent; in men aged 19–24, it was uncomplicated hypertension & obesity. Patients with multimorbidity showed a higher cardiovascular risk profile than the non-multimorbidity group. Conclusions More than 50 % percent of patients with multimorbidity had cardiovascular diseases, the most frequent being hypertension. The presence of cardiovascular risk factors and the cardiovascular risk profile were higher in the multimorbidity group than the non-multimorbidity group. Hypertension, diabetes and dyslipidaemia constituted the most prevalent multimorbidity pattern

Multimorbidity is an emerging topic in public health policy because of its increasing prevalence and socio-economic impact. However, the age- and gender-dependent trends of disease associations at fine resolution, and the underlying genetic factors, remain incompletely understood. Here, by analyzing disease networks from electronic medical records of primary health care, we identify key conditions and shared genetic factors influencing multimorbidity. Three types of diseases are outlined: “central”, which include chronic and non-chronic conditions, have higher cumulative risks of disease associations; “community roots” have lower cumulative risks, but inform on continuing clustered disease associations with age; and “seeds of bursts”, which most are chronic, reveal outbreaks of disease associations leading to multimorbidity. The diseases with a major impact on multimorbidity are caused by genes that occupy central positions in the network of human disease genes. Alteration of lipid metabolism connects breast cancer, diabetic neuropathy and nutritional anemia. Evaluation of key disease associations by a genome-wide association study identifies shared genetic factors and further supports causal commonalities between nervous system diseases and nutritional anemias. This study also reveals many shared genetic signals with other diseases. Collectively, our results depict novel population-based multimorbidity patterns, identify key diseases within them, and highlight pleiotropy influencing multimorbidity.

This manuscript constitutes a part of the PhD thesis of MGC in the Public Health Department of the Universitat Autònoma de Barcelona. This work was supported by a pre-doctoral grant from Catalan Health Institute in Barcelona; by the Catalan Society of General Practitioners (CAMFiC) and by SIDIAP grant to MGC in 2015; this latter organization allowed us to explore their dataset to obtain the results. The funders had no role in the study design or data collection, analysis, and interpretation, writing of the manuscript, and decision to submit for publication. 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. 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. 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. 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. The online version of this article (10.1186/s12877-018-0705-7) contains supplementary material, which is available to authorized users.