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Jesús Díez-Manglano,1,2 María Berges Vidal,2 Lucía Martínez Barredo,3 Beatriz Poblador-Plou,2 Antonio Gimeno-Miguel,2 Pilar Martínez Heras,3 Alexandra Prados-Torres2 1Internal Medicine Department, Royo Villanova Hospital, Zaragoza, Spain; 2EpiChron Research Group, Aragon Health Sciences Institute, IIS Aragón, REDISSEC, Zaragoza, Spain; 3Internal Medicine Department, Miguel Servet University Hospital, Zaragoza, SpainCorrespondence: Jesús Díez-Manglano Duquesa Villahermosa nº 163, 8º D, Zaragoza 50009, SpainTel +34976466910Fax +34976466919Email jdiez@aragon.esPurpose: To determine whether chronic obstructive pulmonary disease (COPD) is a risk factor for hip fracture and identify other factors associated with hip fracture.Patients and Methods: Observational nested case–control study was conducted in Aragon, Spain in 2010. We included COPD patients aged > 40 years, in the EpiChron cohort. Each COPD patient was matched for age, sex, and number of comorbidities with a control subject without COPD. Patients with an existing diagnosis of osteoporosis and those with hip fracture before 2011 were excluded. We collected baseline demographic, comorbidity, and pharmacological treatment data. During a 5-year follow-up period, we recorded the incidence of hip fracture. A logistic regression model was constructed to identify factors associated with hip fracture.Results: The study population consisted of 26,517 COPD patients and the same number of controls (median [interquartile range] age, 74 [17] years; women, 24.7%). Smoking and heart failure were more frequent in COPD patients, and obesity, hypertension, diabetes, dyslipidemia, stroke, arthritis, and visual or hearing impairment were less frequent (all p< 0.001). Consumption of benzodiazepines (p=0.037), bronchodilators (p< 0.001), and corticosteroids (p< 0.001) was higher in the COPD group, while that of beta-blockers and thiazides was lower (both p< 0.001). During follow-up, 898 (1.7%) patients experienced hip fracture, with no differences observed between COPD and control patients. Multivariate analysis revealed that independent of COPD status, age, female sex, chronic liver disease, heart failure, and benzodiazepine use were independently associated with a higher risk of hip fracture, and obesity with a lower risk. In COPD patients, use of inhaled anticholinergics was independently associated with hip fracture (OR, 1.390; 95% CI 1.134– 1.702; p=0.001).Conclusion: COPD is not a risk factor for a hip fracture within 5 years. The association between the use of inhaled anticholinergics and risk of hip fracture warrants further study.Keywords: chronic obstructive pulmonary disease, hip fracture, case–control study, incidence

Enrica Menditto,1,* Caitriona Cahir,2,* Mercedes Aza-Pascual-Salcedo,3,4 Dario Bruzzese,5 Beatriz Poblador-Plou,3 Sara Malo,6 Elisio Costa,7 Francisca González-Rubio,3,4,6 Antonio Gimeno-Miguel,3 Valentina Orlando,1 Przemyslaw Kardas,8 Alexandra Prados-Torres3 1CIRFF, Center of Pharmacoeconomics, University of Naples Federico II, Naples, Italy; 2Division of Population Health Sciences, Royal College of Surgeons in Ireland, Dublin, Ireland; 3Aragon Health Sciences Institute (IACS), IIS Aragón, REDISSEC ISCIII, Madrid, Spain; 4Aragon Health Service (SALUD), Aragon, Spain; 5Department of Public Health, Federico II University, Naples, Italy; 6University of Zaragoza, Zaragoza, Spain; 7UCIBIO, REQUINTE, Faculty of Pharmacy, Porto4ageing Reference Site, University of Porto, Porto, Portugal; 8Department of Family Medicine, Medical University of Lodz, Lodz, Poland *These authors contributed equally to this workPurpose: The purpose of this study was to evaluate and compare medication adherence to chronic therapies in older populations across different regions in Europe.Methods: This explorative study applied a harmonized method of data extraction and analysis from pharmacy claims databases of three European countries to compare medication adherence at a cross-country level. Data were obtained for the period between January 1, 2010, and December 31, 2011. Patients (aged ≥65 years) who newly initiated to oral antidiabetics, antihyperlipidemics, or antiosteoporotics were identified and followed for over a 12-month period. Main outcome measures were medication adherence (medication possession ratio, [MPR]; implementation) and persistence on index treatment. All country-specific data sets were prepared by employing a common data input model. Outcome measures were calculated for each country and pooled using random effect models.Results: In total, 39,186 new users were analyzed. In pooled data from the three countries, suboptimal implementation (MPR 50% of older people non-adherent to antihyperlipidemics and antiosteoporotics in the three European cohorts. However, the degree of variability in adherence rates among the three countries was high. A harmonized method of data extraction and analysis across health-related database in Europe is useful to compare medication-taking behavior at a cross-country level. Keywords: drug utilization, medication adherence, medication persistence, prescribing

Abstract Male breast cancer (MBC) is a rare condition with unique characteristics compared to female breast cancer (FBC). Despite its scarceness, there is growing evidence that MBC should not be studied and treated as FBC due to factors like later diagnosis stage and distinct genetic makeup. Retrospective observational study in the EpiChron Cohort, selecting all the prevalent patients with breast cancer between 2010 and 2019. Logistic models were used to determine associated comorbidities. Between 2010 and 2019, 105 MBC and 11,657 FBC patients were found in the EpiChron Cohort. MBC patients had a high mean age at diagnosis and number of comorbidities. Paying attention to comorbidity prevalences in breast cancer patients, it was clear that MBC patients tended to be prone to cardio-metabolic coexisting diseases, while FBC patients were more prone to hormone-, bone- and mental diseases. There were nine chronic conditions associated to MBC patients, but after a year-by-birth matching only four associations remained. Two of them were associated previously [odds ratio (95% confidence interval)]: “Disorder of lipid metabolism” [1.65 (1.03–2.64)] and “Genitourinary symptoms and ill-defined conditions” [2.03 (1.07–3.87)]; and the other two were new, “Anxiety disorders” [2.05 (1.09–3.87)] and “Osteoporosis” [3.58 (1.26–10.14)]. After comparing associated comorbidities in FBC with those in MBC, it seems MBC patients share some of them, but they have their own particular set of coexisting diseases. In fact, once a year-by-birth matching was performed in MBC patient cohort, it was more obvious MBC comorbidities behave more similar to none-Breast-Cancer male population than to FBC patients. These findings highlight the distinct characteristics of the MBC patient population and the need for a tailored approach of managing MBC.

IntroductionThe presence of multiple chronic conditions, also referred to as multimorbidity, is a common finding in adults. Epidemiologic research can help identify groups of individuals with similar clinical profiles who could benefit from similar interventions. Many cross-sectional studies have revealed the existence of different multimorbidity patterns. Most of these studies were focused on the older population. However, multimorbidity patterns begin to form at a young age and can evolve over time following distinct multimorbidity trajectories with different impact on health. In this study, we aimed to identify multimorbidity patterns and trajectories in adults 18–65 years old.MethodsWe conducted a retrospective longitudinal epidemiologic study in the EpiChron Cohort, which includes all inhabitants of Aragón (Spain) registered as users of the Spanish National Health System, linking, at the patient level, information from electronic health records from both primary and specialised care. We included all 293,923 patients 18–65 years old with multimorbidity in 2011. We used cluster analysis at baseline (2011) and in 2015 and 2019 to identify multimorbidity patterns at four and eight years of follow-up, and we then created alluvial plots to visualise multimorbidity trajectories. We performed age- and sex-adjusted logistic regression analysis to study the association of each pattern with four- and eight-year mortality.ResultsWe identified three multimorbidity patterns at baseline, named dyslipidaemia & endocrine-metabolic, hypertension & obesity, and unspecific. The hypertension & obesity pattern, found in one out of every four patients was associated with a higher likelihood of four- and eight-year mortality (age- and sex-adjusted odds ratio 1.11 and 1.16, respectively) compared to the unspecific pattern. Baseline patterns evolved into different patterns during the follow-up.DiscussionWell-known preventable cardiovascular risk factors were key elements in most patterns, highlighting the role of hypertension and obesity as risk factors for higher mortality. Two out of every three patients had a cardiovascular profile with chronic conditions like diabetes and obesity that are linked to low-grade systemic chronic inflammation. More studies are encouraged to better characterise the relatively large portion of the population with an unspecific disease pattern and to help design and implement effective and comprehensive strategies towards healthier ageing.

The COVID-19 pandemic has created unprecedented challenges for health care systems globally. This study aimed to explore the presence of mental illness in a Spanish cohort of COVID-19-infected population and to evaluate the association between the presence of specific mental health conditions and the risk of death and hospitalization. This is a retrospective cohort study including all individuals with confirmed infection by SARS-CoV-2 from the PRECOVID (Prediction in COVID-19) Study (Aragon, Spain). Mental health illness was defined as the presence of schizophrenia and other psychotic disorders, anxiety, cognitive disorders, depression and mood disorders, substance abuse, and personality and eating disorders. Multivariable logistic regression models were used to examine the likelihood of 30-day all-cause mortality and COVID-19 related hospitalization based on baseline demographic and clinical variables, including the presence of specific mental conditions, by gender. We included 144,957 individuals with confirmed COVID-19 from the PRECOVID Study (Aragon, Spain). The most frequent diagnosis in this cohort was anxiety. However, some differences were observed by sex: substance abuse, personality disorders and schizophrenia were more frequently diagnosed in men, while eating disorders, depression and mood, anxiety and cognitive disorders were more common among women. The presence of mental illness, specifically schizophrenia spectrum and cognitive disorders in men, and depression and mood disorders, substance abuse, anxiety and cognitive and personality disorders in women, increased the risk of mortality or hospitalization after COVID-19, in addition to other well-known risk factors such as age, morbidity and treatment burden. Identifying vulnerable patient profiles at risk of serious outcomes after COVID-19 based on their mental health status will be crucial to improve their access to the healthcare system and the establishment of public health prevention measures for future outbreaks.

Background: Multimorbidity is one of the biggest challenges faced by modern medicine, especially when managing older patients who are also often taking multiple medications. Multimorbidity is influenced by social determinants of health, giving rise to health inequalities in the population. Here, we sought to determine the influence of social determinants of health on quality of life in patients with multimorbidity and polypharmacy. Methods and materials: This cross-sectional observational study included 573 patients aged 65–74 with multimorbidity (≥3 diseases) and polypharmacy (≥5 drugs). Corresponding data was taken drawn from the Spanish MULTIPAP study, and included social and demographic variables, and data on health-related quality of life and overall self-perceived health status, assessed using the 5-level version of the EuroQol 5-dimensional questionnaire (EQ-5D-5L). Descriptive, bivariate and multivariate analyses with logistic regression models were performed. Results: Mean patient age was 69.7 years, 55.8% of patients were female, 59.7% belonged to low social classes (V, VI), a monthly income of €1051–€1850 predominated, and the median number of diseases in the same patient was 6. Factors associated with higher quality of life were (odds ratio, OR) male gender (OR = 1.599, p = 0.013), a higher educational level (OR = 1.991, p = 0.036), an absence of urban vulnerability (OR = 1.605, p = 0.017), and the presence of medium social support (OR = 1.689, p = 0.017). Having a higher number of diseases was associated with poorer quality of life (OR = 0.912, p = 0.017). Conclusions: Our findings describe associations between social determinants of health and quality of life in patients aged 65–74 years with multimorbidity and polypharmacy. More illnesses, female gender, a lower education level, urban vulnerability, and less social support are associated with poorer quality of life, underscoring the need for a biopsychosocial approach in patient care. [ABSTRACT FROM AUTHOR]

Abstract A major risk factor of COVID-19 severity is the patient's health status at the time of the infection. Numerous studies focused on specific chronic diseases and identified conditions, mainly cardiovascular ones, associated with poor prognosis. However, chronic diseases tend to cluster into patterns, each with its particular repercussions on the clinical outcome of infected patients. Network analysis in our population revealed that not all cardiovascular patterns have the same risk of COVID-19 hospitalization or mortality and that this risk depends on the pattern of multimorbidity, besides age and sex. We evidenced that negative outcomes were strongly related to patterns in which diabetes and obesity stood out in older women and men, respectively. In younger adults, anxiety was another disease that increased the risk of severity, most notably when combined with menstrual disorders in women or atopic dermatitis in men. These results have relevant implications for organizational, preventive, and clinical actions to help meet the needs of COVID-19 patients.

Background Several chronic conditions have been identified as risk factors for severe COVID-19 infection, yet the implications of multimorbidity need to be explored. The objective of this study was to establish multimorbidity clusters from a cohort of COVID-19 patients and assess their relationship with infection severity/mortality. Methods The MRisk-COVID Big Data study included 14 286 COVID-19 patients of the first wave in a Spanish region. The cohort was stratified by age and sex. Multimorbid individuals were subjected to a fuzzy c-means cluster analysis in order to identify multimorbidity clusters within each stratum. Bivariate analyses were performed to assess the relationship between severity/mortality and age, sex, and multimorbidity clusters. Results Severe infection was reported in 9.5% (95% CI: 9.0–9.9) of the patients, and death occurred in 3.9% (95% CI: 3.6–4.2). We identified multimorbidity clusters related to severity/mortality in most age groups from 21 to 65 years. In males, the cluster with highest percentage of severity/mortality was Heart-liver-gastrointestinal (81–90 years, 34.1% severity, 29.5% mortality). In females, the clusters with the highest percentage of severity/mortality were Diabetes-cardiovascular (81–95 years, 22.5% severity) and Psychogeriatric (81–95 years, 16.0% mortality). Conclusion This study characterized several multimorbidity clusters in COVID-19 patients based on sex and age, some of which were found to be associated with higher rates of infection severity/mortality, particularly in younger individuals. Further research is encouraged to ascertain the role of specific multimorbidity patterns on infection prognosis and identify the most vulnerable morbidity profiles in the community. Trial registration NCT04981249. Registered 4 August 2021 (retrospectively registered).

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

Abstract Chronic obstructive airway diseases such as chronic obstructive pulmonary disease (COPD), asthma, rhinitis, and obstructive sleep apnea (OSA) are amongst the most common treatable and preventable chronic conditions with high morbidity burden and mortality risk. We aimed to explore the existence of multimorbidity clusters in patients with such diseases and to estimate their prevalence and impact on mortality. We conducted an observational retrospective study in the EpiChron Cohort (Aragon, Spain), selecting all patients with a diagnosis of allergic rhinitis, asthma, COPD, and/or OSA. The study population was stratified by age (i.e., 15–44, 45–64, and ≥ 65 years) and gender. We performed cluster analysis, including all chronic conditions recorded in primary care electronic health records and hospital discharge reports. More than 75% of the patients had multimorbidity (co-existence of two or more chronic conditions). We identified associations of dermatologic diseases with musculoskeletal disorders and anxiety, cardiometabolic diseases with mental health problems, and substance use disorders with neurologic diseases and neoplasms, amongst others. The number and complexity of the multimorbidity clusters increased with age in both genders. The cluster with the highest likelihood of mortality was identified in men aged 45 to 64 years and included associations between substance use disorder, neurologic conditions, and cancer. Large-scale epidemiological studies like ours could be useful when planning healthcare interventions targeting patients with chronic obstructive airway diseases and multimorbidity.

Background Clinical outcomes among COVID-19 patients vary greatly with age and underlying comorbidities. We aimed to determine the demographic and clinical factors, particularly baseline chronic conditions, associated with an increased risk of severity in COVID-19 patients from a population-based perspective and using data from electronic health records (EHR). Methods Retrospective, observational study in an open cohort analyzing all 68,913 individuals (mean age 44.4 years, 53.2% women) with SARS-CoV-2 infection between 15 June and 19 December 2020 using exhaustive electronic health registries. Patients were followed for 30 days from inclusion or until the date of death within that period. We performed multivariate logistic regression to analyze the association between each chronic disease and severe infection, based on hospitalization and all-cause mortality. Results 5885 (8.5%) individuals showed severe infection and old age was the most influencing factor. Congestive heart failure (odds ratio -OR- men: 1.28, OR women: 1.39), diabetes (1.37, 1.24), chronic renal failure (1.31, 1.22) and obesity (1.21, 1.26) increased the likelihood of severe infection in both sexes. Chronic skin ulcers (1.32), acute cerebrovascular disease (1.34), chronic obstructive pulmonary disease (1.21), urinary incontinence (1.17) and neoplasms (1.26) in men, and infertility (1.87), obstructive sleep apnea (1.43), hepatic steatosis (1.43), rheumatoid arthritis (1.39) and menstrual disorders (1.18) in women were also associated with more severe outcomes. Conclusions Age and specific cardiovascular and metabolic diseases increased the risk of severe SARS-CoV-2 infections in men and women, whereas the effects of certain comorbidities are sex specific. Future studies in different settings are encouraged to analyze which profiles of chronic patients are at higher risk of poor prognosis and should therefore be the targets of prevention and shielding strategies.

Objectives: Little is known about the specific comorbidities contributing to higher costs in patients with type-2 diabetes mellitus (T2DM), particularly in older cases. We aimed to evaluate the prevalence, type, and cost of comorbidities occurring in older T2DM patients versus older non-T2DM patients, and the factors associated with high cost (HC) T2DM patients.Methods: Retrospective cohort study using information from the Campania Region healthcare database. People aged ≥65 years who received ≥2 prescriptions for antidiabetic drugs were identified as “T2DM patients.” Comorbidities among T2DM and non-T2DM groups were assessed through the RxRiskV Index (modified version). T2DM individuals were classified according to the total cost distribution as HC or “non-high cost.” Two sub-cohorts of HC T2DM patients were assessed: above 90th and 80th percentile of the total cost. Age- and sex-adjusted logistic regression models were created.Results: Among the T2DM cohort, concordant and discordant comorbidities occurred significantly more frequently than in the non-T2DM cohort. Total mean annual cost per T2DM patient due to comorbidities was €7,627 versus €4,401 per non-T2DM patient. Among T2DM patients identified as being above 90th and 80th percentiles of cost distribution, the total annual costs were >€19,577 and >€2,563, respectively. The hospitalization cost was higher for T2DM cases. Strongest predictors of being a HC T2DM patient were having ≥5 comorbidities and renal impairment.Conclusion: HC patients accrued >80% of the total comorbidities cost in older T2DM patients. Integrated care models, with holistic and patient-tailored foci, could achieve more effective T2DM care.

Introduction Breast cancer has become a chronic disease due to survival improvement and the need to monitor the side effects of treatment and the disease itself. The aim of the SURBCAN study is to describe comorbidity, healthcare services use and adherence to preventive recommendations in long-term breast cancer survivors and to compare them with those in women without this diagnosis in order to improve and adapt the care response to this group of survivors.Methods and analysis Population-based retrospective cohort study using real-world data from cancer registries and linked electronic medical records in five Spanish regions. Long-term breast cancer survivors diagnosed between 2000 and 2006 will be identified and matched by age and administrative health area with women without this diagnosis. Sociodemographic and clinical variables including comorbidities and variables on the use of health services between 2012 and 2016 will be obtained from databases in primary and hospital care. Health services use will be assessed through the annual number of visits to primary care professionals and to specialists and through annual imaging and laboratory tests. Factors associated with healthcare utilisation and comorbidities will be analysed using multilevel logistic regression models. Recruitment started in December 2018.Ethics and dissemination This study was approved by the Ethics Committee of Parc de Salut Mar. The results of the study will be published in a peer-reviewed journal and will be presented at national and international scientific conferences and at patient associations.Trial registration number This protocol is registered in Clinical Trials.gov (identifier: NCT03846999).

The COVID–19 pandemic has created unprecedented challenges for health care systems globally. This study aimed to explore the presence of mental illness in a Spanish cohort of COVID-19-infected population and to evaluate the association between the presence of specific mental health conditions and the risk of death and hospitalization. This is a retrospective cohort study including all individuals with confirmed infection by SARS-CoV-2 from the PRECOVID (Prediction in COVID–19) Study (Aragon, Spain). Mental health illness was defined as the presence of schizophrenia and other psychotic disorders, anxiety, cognitive disorders, depression and mood disorders, substance abuse, and personality and eating disorders. Multivariable logistic regression models were used to examine the likelihood of 30-day all-cause mortality and COVID–19 related hospitalization based on baseline demographic and clinical variables, including the presence of specific mental conditions, by gender. We included 144,957 individuals with confirmed COVID–19 from the PRECOVID Study (Aragon, Spain). The most frequent diagnosis in this cohort was anxiety. However, some differences were observed by sex: substance abuse, personality disorders and schizophrenia were more frequently diagnosed in men, while eating disorders, depression and mood, anxiety and cognitive disorders were more common among women. The presence of mental illness, specifically schizophrenia spectrum and cognitive disorders in men, and depression and mood disorders, substance abuse, anxiety and cognitive and personality disorders in women, increased the risk of mortality or hospitalization after COVID–19, in addition to other well-known risk factors such as age, morbidity and treatment burden. Identifying vulnerable patient profiles at risk of serious outcomes after COVID–19 based on their mental health status will be crucial to improve their access to the healthcare system and the establishment of public health prevention measures for future outbreaks. [ABSTRACT FROM AUTHOR]

Takeover bids have recently given rise to administrative litigation in Spain. Ever since the National Court upheld the appeal against the decision to approve the Cementos Portland Valderrivas, S.A. takeover, the number of appeals against takeover bid approvals has escalated. This has resulted in various precedent-setting judgments by the National Court and the Supreme Court on essential issues regarding takeover bid regulations. This article analyses these and other imminent judgments. [ABSTRACT FROM AUTHOR]

OBJECTIVES:The objective was to identify the systematic associations among chronic diseases and drugs in the form of patterns and to describe and clinically interpret the constituted patterns with a focus on exploring the existence of potential drug-drug and drug-disease interactions and prescribing cascades. METHODS:This observational, cross-sectional study used the demographic and clinical information from electronic medical databases and the pharmacy billing records of all users of the public health system of the Spanish region of Aragon in 2015. An exploratory factor analysis was conducted based on the tetra-choric correlations among the diagnoses of chronic diseases and the dispensed drugs in 887,572 patients aged ≤65 years. The analysis was stratified by age and sex. To name the constituted patterns, assess their clinical nature, and identify potential interactions among diseases and drugs, the associations found in each pattern were independently reviewed by two pharmacists and two doctors and tested against the literature and the information reported in the technical medicinal forms. RESULTS:Six multimorbidity-polypharmacy patterns were found in this large-scale population study, named as respiratory, mental health, cardiometabolic, endocrinological, osteometabolic, and mechanical-pain. The nature of the patterns in terms of diseases and drugs differed by sex and age and became more complex as age advanced. CONCLUSIONS:The six clinically sound multimorbidity-polypharmacy patterns described in this non-elderly population confirmed the existence of systematic associations among chronic diseases and medications, and revealed some unexpected associations suggesting the prescribing cascade phenomenon as a potential underlying factor. These findings may help to broaden the focus and orient the early identification of potential interactions when caring for multimorbid patients at high risk of adverse health outcomes due to polypharmacy.