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ObjectivesThe primary objective of this study was to identify the existence of chronic disease multimorbidity patterns in the primary care population, describing their clinical components and analysing how these patterns change and evolve over time both in women and men. The secondary objective of this study was to generate evidence regarding the pathophysiological processes underlying multimorbidity and to understand the interactions and synergies among the various diseases.MethodsThis observational, retrospective, multicentre study utilised information from the electronic medical records of 19 primary care centres from 2008. To identify multimorbidity patterns, an exploratory factor analysis was carried out based on the tetra-choric correlations between the diagnostic information of 275,682 patients who were over 14 years of age. The analysis was stratified by age group and sex.ResultsMultimorbidity was found in all age groups, and its prevalence ranged from 13% in the 15 to 44 year age group to 67% in those 65 years of age or older. Goodness-of-fit indicators revealed sample values between 0.50 and 0.71. We identified five patterns of multimorbidity: cardio-metabolic, psychiatric-substance abuse, mechanical-obesity-thyroidal, psychogeriatric and depressive. Some of these patterns were found to evolve with age, and there were differences between men and women.ConclusionsNon-random associations between chronic diseases result in clinically consistent multimorbidity patterns affecting a significant proportion of the population. Underlying pathophysiological phenomena were observed upon which action can be taken both from a clinical, individual-level perspective and from a public health or population-level perspective.

BackgroundThe epidemiologic study of comorbidities of an index health problem represents a methodological challenge. This study cross-sectionally describes and analyzes the comorbidities associated with dementia in older patients and reviews the existing similarities and differences between identified comorbid diseases using the statistical methods most frequently applied in current research.MethodsCross-sectional study of 72,815 patients over 64 seen in 19 Spanish primary care centers during 2008. Chronic diseases were extracted from electronic health records and grouped into Expanded Diagnostic Clusters®. Three different statistical methods were applied (i.e., analysis of prevalence data, multiple regression and factor analysis), stratifying by sex.ResultsThe two most frequent comorbidities both for men and women with dementia were hypertension and diabetes. Yet, logistic regression and factor analysis demonstrated that the comorbidities significantly associated with dementia were Parkinson’s disease, congestive heart failure, cerebrovascular disease, anemia, cardiac arrhythmia, chronic skin ulcers, osteoporosis, thyroid disease, retinal disorders, prostatic hypertrophy, insomnia and anxiety and neurosis.ConclusionsThe analysis of the comorbidities associated with an index disease (e.g., dementia) must not be exclusively based on prevalence rates, but rather on methodologies that allow the discovery of non-random associations between diseases. A deep and reliable knowledge about how different diseases are grouped and associated around an index disease such as dementia may orient future longitudinal studies aimed at unraveling causal associations.

BackgroundThe coexistence of several chronic diseases in one same individual, known as multimorbidity, is an important challenge facing health care systems in developed countries. Recent studies have revealed the existence of multimorbidity patterns clustering systematically associated distinct clinical entities. We sought to describe age and gender differences in the prevalence and patterns of multimorbidity in men and women over 65 years.MethodsObservational retrospective multicentre study based on diagnostic information gathered from electronic medical records of 19 primary care centres in Aragon and Catalonia. Multimorbidity patterns were identified through exploratory factor analysis. We performed a descriptive analysis of previously obtained patterns (i.e. cardiometabolic (CM), mechanical (MEC) and psychogeriatric (PG)) and the diseases included in the patterns stratifying by sex and age group.Results67.5% of the aged population suffered two or more chronic diseases. 32.2% of men and 45.3% of women were assigned to at least one specific pattern of multimorbidity, and 4.6% of men and 8% of women presented more than one pattern simultaneously. Among women over 65 years the most frequent pattern was the MEC pattern (33.3%), whereas among men it was the CM pattern (21.2%). While the prevalence of the CM and MEC patterns decreased with age, the PG pattern showed a higher prevalence in the older age groups.ConclusionsSignificant gender differences were observed in the prevalence of multimorbidity patterns, women showing a higher prevalence of the MEC and PG patterns, as well as a higher degree of pattern overlapping, probably due to a higher life expectancy and/or worse health. Future studies on multimorbidity patterns should take into account these differences and, therefore, the study of multimorbidity and its impact should be stratified by age and sex.

This study aims to analyse the influence of these factors (multimorbidity, polypharmacy, and multiple referrals) on the frequency of ADEs, as an indicator of therapeutic safety, in the context of a national healthcare system. METHODThis was a multicentre observational study of patients treated at seven urban primary care centres in Zaragoza, Spain. Selection of centres to participate in this study was conducted based on the following quality inclusion criteria: (a) centres with computerised records for all appointments Research Abstract BackgroundThe consequences of multimorbidity include polypharmacy and repeated referrals for specialised care, which may increase the risk of adverse drug events (ADEs).

We aimed to analyze baseline socio-demographic and clinical factors associated with an increased likelihood of mortality in men and women with coronavirus disease (COVID-19). We conducted a retrospective cohort study (PRECOVID Study) on all 4412 individuals with laboratory-confirmed COVID-19 in Aragon, Spain, and followed them for at least 30 days from cohort entry. We described the socio-demographic and clinical characteristics of all patients of the cohort. Age-adjusted logistic regressions models were performed to analyze the likelihood of mortality based on demographic and clinical variables. All analyses were stratified by sex. Old age, specific diseases such as diabetes, acute myocardial infarction, or congestive heart failure, and dispensation of drugs like vasodilators, antipsychotics, and potassium-sparing agents were associated with an increased likelihood of mortality. Our findings suggest that specific comorbidities, mainly of cardiovascular nature, and medications at the time of infection could explain around one quarter of the mortality in COVID-19 disease, and that women and men probably share similar but not identical risk factors. Nonetheless, the great part of mortality seems to be explained by other patient- and/or health-system-related factors. More research is needed in this field to provide the necessary evidence for the development of early identification strategies for patients at higher risk of adverse outcomes.

Background/ObjectivesThe clinical status of older individuals with multimorbidity can be further complicated by concomitant geriatric syndromes. This study explores multimorbidity patterns, encompassing both chronic diseases and geriatric syndromes, in geriatric patients attended in an acute hospital setting.DesignRetrospective observational study.SettingUnit of Social and Clinical Assessment (UVSS), Miguel Servet University Hospital (HUMS), Zaragoza (Spain). Year, 2011.ParticipantsA total of 924 hospitalized patients aged 65 years or older.MeasurementsData on patients’ clinical, functional, cognitive and social statuses were gathered through comprehensive geriatric assessments. To identify diseases and/or geriatric syndromes that cluster into patterns, an exploratory factor analysis was applied, stratifying by sex. The factors can be interpreted as multimorbidity patterns, i.e., diseases non-randomly associated with each other within the study population. The resulting patterns were clinically assessed by several physicians.ResultsThe mean age of the study population was 82.1 years (SD 7.2). Multimorbidity burden was lower in men under 80 years, but increased in those over 80. Immobility, urinary incontinence, hypertension, falls, dementia, cognitive decline, diabetes and arrhythmia were among the 10 most frequent health problems in both sexes, with prevalence rates above 20%. Four multimorbidity patterns were identified that were present in both sexes: Cardiovascular, Induced Dependency, Falls and Osteoarticular. The number of conditions comprising these patterns was similar in men and women.ConclusionThe existence of specific multimorbidity patterns in geriatric patients, such as the Induced Dependency and Falls patterns, may facilitate the early detection of vulnerability to stressors, thus helping to avoid negative health outcomes such as functional disability.

Lower use of PHC among immigrants could be due to better health or to access barriers, and should be further studied, especially for the oldest immigrants. Adjusted high frequency of use may be appropriate, but it might also be a signal of non-effective contacts.