Reports of Symptoms Associated with Supraventricular Arrhythmias as a Serious Adverse Drug Reaction in the Spanish Pharmacovigilance Database.

This study aimed to determine the type of drugs reported as suspected of causing severe supraventricular arrhythmias from the Spanish Human Pharmacovigilance System database. A total of 1053 reports were analysed, of which 526 (50%) were on men and 516 (49%) were on women. The most affected age group was the over-65s, with 593 reports (56%). Of the 1613 drugs, those belonging to the cardiovascular system (ATC Group C) were the most numerous (414 reports, 26%), with digoxin being the most frequent drug (49 reports, 12%). Other common groups were antiinfectives for systemic use (ATC Group J; 306 reports, 19%), antineoplastic and immunomodulating agents (ATC Group L; 198 reports, 12%), and nervous system drugs (ATC Group N; 185 reports, 11%). The most common supraventricular arrhythmia was atrial fibrillation (561 reports, 51%). Regarding outcomes, 730 (66%) patients recovered, 76 (7%) did not recover, 25 (3%) recovered but with sequelae, and 23 (2%) resulted in death. This study revealed that certain drugs have reported to be associated more frequently to supraventricular arrhythmias as serious adverse reactions, especially in the older population. Proper clinical management and effective strategies to ensure medication appropriateness should always be considered to improve patient safety when prescribing drugs.

Drug Repurposing in Oncology: A Systematic Review of Randomized Controlled Clinical Trials.

Quality pharmacological treatment can improve survival in many types of cancer. Drug repurposing offers advantages in comparison with traditional drug development procedures, reducing time and risk. This systematic review identified the most recent randomized controlled clinical trials that focus on drug repurposing in oncology. We found that only a few clinical trials were placebo-controlled or standard-of-care-alone-controlled. Metformin has been studied for potential use in various types of cancer, including prostate, lung, and pancreatic cancer. Other studies assessed the possible use of the antiparasitic agent mebendazole in colorectal cancer and of propranolol in multiple myeloma or, when combined with etodolac, in breast cancer. We were able to identify trials that study the potential use of known antineoplastics in other non-oncological conditions, such as imatinib for severe coronavirus disease in 2019 or a study protocol aiming to assess the possible repurposing of leuprolide for Alzheimer's disease. Major limitations of these clinical trials were the small sample size, the high clinical heterogeneity of the participants regarding the stage of the neoplastic disease, and the lack of accounting for multimorbidity and other baseline clinical characteristics. Drug repurposing possibilities in oncology must be carefully examined with well-designed trials, considering factors that could influence prognosis.

Prescribed Drugs and Self-Directed Violence: A Descriptive Study in the Spanish Pharmacovigilance Database.

Self-inflicted violence is a major and growing public health problem and its prediction and prevention is challenging for healthcare systems worldwide. Our aim was to identify prescribed drugs associated with self-directed violent behaviors in Spain. A descriptive, longitudinal and retrospective study of spontaneous reports of adverse drug reactions corresponding to self-directed violence was recorded in the Spanish Pharmacovigilance Database (FEDRA®) from 1984 to 31 March 2021. A total of 710 cases were reported in the study period. The mean age was 45.52 years (range 1-94). There were no gender differences except in children, where most reports were of male children. The main therapeutic groups that were involved included drugs for the nervous system (64.5%) and anti-infectives for systemic use (13.2%). The most commonly reported drugs were varenicline, fluoxetine, lorazepam, escitalopram, venlafaxine, veralipride, pregabalin, roflumilast and bupropion. There were reports of montelukast, hydroxychloroquine, isotretinoin, methylphenidate, infliximab, natalizumab, ribavirin and efavirenz, which were less known to be involved in self-directed violence. This study shows that self-directed violence is a rare adverse drug reaction, and can be related to the use of some medicines. It is important for healthcare professionals to consider this risk in their clinical praxis, implementing person-centred approaches. Further studies are needed, considering comorbidities and potential interactions.

Clinical characteristics of heart failure patients with mid-range ejection fraction.

BACKGROUND: We aimed to characterise and compare the clinical profile of heart failure (HF) with mid-range (HFmrEF), reduced (HFrEF) and preserved (HFpEF) left-ventricular ejection fraction. METHODS: We conducted a descriptive, observational study in 267 HF patients admitted to the Internal Medicine department of a tertiary hospital during 2010-2016. The study population was divided into three groups according to the ejection fraction rate: HFrEF (<40%), HFmrEF (40-49%), and HFpEF (≥50%). We analysed and compared their demographic, clinical, and analytical characteristics. RESULTS: The mean age of the study population was 79.5 (standard deviation, 8.14) years; 56.6% were males. The most common phenotype was HFpEF (58.1%), followed by HFrEF (21.7%) and HFmrEF (20.2%). Ischaemic cardiopathy was the primary aetiology in the HFmrEF and HFrEF groups, and arterial hypertension in the HFpEF group. The most common comorbidities among HFmrEF patients were diabetes (43.4%), chronic obstructive pulmonary disease (35.8%), and anaemia (35.8%); 49.1% had impairment of segmental myocardial contractility, and 35.8% ventricular dilatation. No differences in HF outcomes were observed among the three phenotypes. CONCLUSION: HFmrEF shows characteristics similar to both HFpEF and HFrEF. Further large-scale studies with longer follow-up are needed to ascertain if it is worth distinguishing this phenotype in clinical practice in terms of management and prognosis.

LESS-PHARMA Study: Identifying and Deprescribing Potentially Inappropriate Medication in the Elderly Population with Excessive Polypharmacy in Primary Care.

Potentially inappropriate medication (PIM) increases adverse drug reactions and mortality, especially in excessively polymedicated patients. General practitioners are often in charge of this process. Some tools have been created to support them in this matter. This study aimed to measure the amount of potentially inappropriate medication among excessively polymedicated patients using several supporting tools and assess the feasibility of these tools in primary care. Several explicit deprescribing criteria were used to identify potentially inappropriate medications. The level of agreement between all the criteria and the acceptance by the general practitioner (GP) was also measured. We analysed whether the drugs proposed for deprescribing were eventually withdrawn after twelve months. The total number of drugs prescribed was 2038. Six hundred and forty-nine drugs (31.8%) were considered potentially inappropriate by at least one of the tools. GPs agreed with the tools in 56.7% of the cases. In a 12-month period, 109 drugs, representing 29.6% of the drugs that GPs agreed to deprescribe, were withdrawn. Elderly excessively polymedicated patients accumulated a great number of PIMs. The use of deprescribing supporting tools, such as explicit criteria, is feasible in primary care, and these tools are well accepted by the GPs. However, eventual withdrawal was carried out in less than half of the cases.

Multimorbidity Clusters in the Oldest Old: Results from the EpiChron Cohort.

Multimorbidity is challenging for both patients and healthcare systems due to its increasing prevalence and high impact on people's health and well-being. The risk of multimorbidity increases with age, but there is still more to discover regarding the clinical profile of the oldest old. In this study, we used information from the EpiChron Cohort Study to identify multimorbidity patterns in individuals who died during the period 2010-2019 at the ages of 80-89, 90-99, and ≥100. This cohort links the demographic, clinical, and drug dispensation information of public health system users in Aragón, Spain. We saw a significantly lower number of chronic diseases and drugs and a lower prevalence of polypharmacy in centenarians compared to those aged 80-99. K-means clustering revealed different multimorbidity clusters by sex and age group. We observed clusters of cardiovascular and metabolic diseases, obstructive pulmonary conditions, and neoplasms, amongst other profiles. One in three octogenarian women had a metabolic pattern (diabetes, dyslipidaemia, and other endocrine-metabolic disorders) with the highest number of diseases (up to seven) and prevalence of polypharmacy (64%). We observed clusters of dementia and genitourinary disorders in individuals on medication with anticholinergic activity. Our study offers an opportunity to better understand the urgency of adequately addressing multimorbidity in our older adults.

Multimorbidity Profiles and Infection Severity in COVID-19 Population Using Network Analysis in the Andalusian Health Population Database.

Identifying the population at risk of COVID-19 infection severity is a priority for clinicians and health systems. Most studies to date have only focused on the effect of specific disorders on infection severity, without considering that patients usually present multiple chronic diseases and that these conditions tend to group together in the form of multimorbidity patterns. In this large-scale epidemiological study, including primary and hospital care information of 166,242 patients with confirmed COVID-19 infection from the Spanish region of Andalusia, we applied network analysis to identify multimorbidity profiles and analyze their impact on the risk of hospitalization and mortality. Our results showed that multimorbidity was a risk factor for COVID-19 severity and that this risk increased with the morbidity burden. Individuals with advanced cardio-metabolic profiles frequently presented the highest infection severity risk in both sexes. The pattern with the highest severity associated in men was present in almost 28.7% of those aged ≥ 80 years and included associations between cardiovascular, respiratory, and metabolic diseases; age-adjusted odds ratio (OR) 95% confidence interval (1.71 (1.44-2.02)). In women, similar patterns were also associated the most with infection severity, in 7% of 65-79-year-olds (1.44 (1.34-1.54)) and in 29% of ≥80-year-olds (1.35 (1.18-1.53)). Patients with mental health patterns also showed one of the highest risks of COVID-19 severity, especially in women. These findings strongly recommend the implementation of personalized approaches to patients with multimorbidity and SARS-CoV-2 infection, especially in the population with high morbidity burden.

Identifying multimorbidity profiles associated with COVID-19 severity in chronic patients using network analysis in the PRECOVID Study.

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.

Chronic diseases associated with increased likelihood of hospitalization and mortality in 68,913 COVID-19 confirmed cases in Spain: A population-based cohort study.

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.

Baseline Drug Treatments as Indicators of Increased Risk of COVID-19 Mortality in Spain and Italy.

This study aims to identify baseline medications that, as a proxy for the diseases they are dispensed for, are associated with increased risk of mortality in COVID-19 patients from two regions in Spain and Italy using real-world data. We conducted a cross-country, retrospective, observational study including 8570 individuals from both regions with confirmed SARS-CoV-2 infection between 4 March and 17 April 2020, and followed them for a minimum of 30 days to allow sufficient time for the studied event, in this case death, to occur. Baseline demographic variables and all drugs dispensed in community pharmacies three months prior to infection were extracted from the PRECOVID Study cohort (Aragon, Spain) and the Campania Region Database (Campania, Italy) and analyzed using logistic regression models. Results show that the presence at baseline of potassium-sparing agents, antipsychotics, vasodilators, high-ceiling diuretics, antithrombotic agents, vitamin B12, folic acid, and antiepileptics were systematically associated with mortality in COVID-19 patients from both countries. Treatments for chronic cardiovascular and metabolic diseases, systemic inflammation, and processes with increased risk of thrombosis as proxies for the conditions they are intended for can serve as timely indicators of an increased likelihood of mortality after the infection, and the assessment of pharmacological profiles can be an additional approach to the identification of at-risk individuals in clinical practice.

Drug Prescription Profiles in Patients with Polypharmacy in Spain: A Large-Scale Pharmacoepidemiologic Study Using Real-World Data.

We aimed to identify and compare medication profiles in populations with polypharmacy between 2005 and 2015. We conducted a cross-sectional study using information from the Computerized Database for Pharmacoepidemiologic Studies in Primary Care (BIFAP, Spain). We estimated the prevalence of therapeutic subgroups in all individuals 15 years of age and older with polypharmacy (≥5 drugs during ≥6 months) using the Anatomical Therapeutic Chemical classification system level 4, by sex and age group, for both calendar years. The most prescribed drugs were proton-pump inhibitors (PPIs), statins, antiplatelet agents, benzodiazepine derivatives, and angiotensin-converting enzyme inhibitors. The greatest increases between 2005 and 2015 were observed in PPIs, statins, other antidepressants, and ß-blockers, while the prevalence of antiepileptics was almost tripled. We observed increases in psychotropic drugs in women and cardiovascular medications in men. By patient´s age groups, there were notable increases in antipsychotics, antidepressants, and antiepileptics (15-44 years); antidepressants, PPIs, and selective ß-blockers (45-64 years); selective ß-blockers, biguanides, PPIs, and statins (65-79 years); and in statins, selective ß-blockers, and PPIs (80 years and older). Our results revealed important increases in the use of specific therapeutic subgroups, like PPIs, statins, and psychotropic drugs, highlighting opportunities to design and implement strategies to analyze such prescriptions' appropriateness.

Changes in Multimorbidity and Polypharmacy Patterns in Young and Adult Population over a 4-Year Period: A 2011-2015 Comparison Using Real-World Data.

The pressing problem of multimorbidity and polypharmacy is aggravated by the lack of specific care models for this population. We aimed to investigate the evolution of multimorbidity and polypharmacy patterns in a given population over a 4-year period (2011-2015). A cross-sectional, observational study among the EpiChron Cohort, including anonymized demographic, clinical and drug dispensation information of all users of the public health system ≥65 years in Aragon (Spain), was performed. An exploratory factor analysis, stratified by age and sex, using an open cohort was carried out based on the tetra-choric correlations among chronic diseases and dispensed drugs during 2011 and compared with 2015. Seven baseline patterns were identified during 2011 named as: mental health, respiratory, allergic, mechanical pain, cardiometabolic, osteometabolic, and allergic/derma. Of the epidemiological patterns identified in 2015, six were already present in 2011 but a new allergic/derma one appeared. Patterns identified in 2011 were more complex in terms of both disease and drugs. Results confirmed the existing association between age and clinical complexity. The systematic associations between diseases and drugs remain similar regarding their clinical nature over time, helping in early identification of potential interactions in multimorbid patients with a high risk of negative health outcomes due to polypharmacy.

Multimorbidity clusters in patients with chronic obstructive airway diseases in the EpiChron Cohort.

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.

Multimorbidity networks of chronic obstructive pulmonary disease and heart failure in men and women: Evidence from the EpiChron Cohort.

Patients with heart failure (HF) and/or chronic obstructive pulmonary disease (COPD) constitute a complex population with different phenotypes based on pathophysiology, comorbidity, sex and age. We aimed to compare the multimorbidity patterns of HF and COPD in men and women using network analysis. Individuals aged 40 years or older on 2015 of the EpiChron Cohort (Aragon, Spain) were stratified by sex and as having COPD (n = 28,608), HF (n = 13,414), or COPD and HF (n = 3952). We constructed one network per group by obtaining age-adjusted phi correlations between comorbidities. For each sex, networks differed between the three study groups; between sexes, similarities were found for the two HF groups. We detected some specific diseases highly connected in all networks (e.g., cardio-metabolic, respiratory diseases, and chronic kidney failure), and some others that were group-specific that would require further study. We identified common clusters (i.e., cardio-metabolic, cardiovascular, cancer, and neuro-psychiatric) and others specific and clinically relevant in COPD patients (e.g., behavioral risk disorders were systematically associated with psychiatric diseases in women and cancer in men). Network analysis represents a powerful tool to analyze, visualize, and compare the multimorbidity patterns of COPD and HF, also facilitated by developing an ad hoc website.

Association between mental health comorbidity and health outcomes in type 2 diabetes mellitus patients.

Type 2 diabetes mellitus (T2D) is often accompanied by chronic diseases, including mental health problems. We aimed at studying mental health comorbidity prevalence in T2D patients and its association with T2D outcomes through a retrospective, observational study of individuals of the EpiChron Cohort (Aragón, Spain) with prevalent T2D in 2011 (n = 63,365). Participants were categorized as having or not mental health comorbidity (i.e., depression, anxiety, schizophrenia, and/or substance use disorder). We performed logistic regression models, controlled for age, sex and comorbidities, to analyse the likelihood of 4-year mortality, 1-year all-cause hospitalization, T2D-hospitalization, and emergency room visit. Mental health comorbidity was observed in 19% of patients. Depression was the most frequent condition, especially in women (20.7% vs. 7.57%). Mortality risk was higher in patients with mental health comorbidity (odds ratio 1.24; 95% confidence interval 1.16-1.31), especially in those with substance use disorder (2.18; 1.84-2.57) and schizophrenia (1.82; 1.50-2.21). Mental health comorbidity also increased the likelihood of all-cause hospitalization (1.16; 1.10-1.23), T2D-hospitalization (1.51; 1.18-1.93) and emergency room visit (1.26; 1.21-1.32). These results suggest that T2D healthcare management should include specific strategies for the early detection and treatment of mental health problems to reduce its impact on health outcomes.

Baseline Chronic Comorbidity and Mortality in Laboratory-Confirmed COVID-19 Cases: Results from the PRECOVID Study in Spain.

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.

Multimorbidity Patterns in the General Population: Results from the EpiChron Cohort Study.

The correct management of patients with multimorbidity remains one of the main challenges for healthcare systems worldwide. In this study, we analyze the existence of multimorbidity patterns in the general population based on gender and age. We conducted a cross-sectional study of individuals of all ages from the EpiChron Cohort, Spain (1,253,292 subjects), and analyzed the presence of systematic associations among chronic disease diagnoses using exploratory factor analysis. We identified and clinically described a total of 14 different multimorbidity patterns (12 in women and 12 in men), with some relevant differences in the functions of age and gender. The number and complexity of the patterns was shown to increase with age in both genders. We identified associations of circulatory diseases with respiratory disorders, chronic musculoskeletal diseases with depression and anxiety, and a very consistent pattern of conditions whose co-occurrence is known as metabolic syndrome (hypertension, diabetes, obesity, and dyslipidaemia), among others. Our results demonstrate the potential of using real-world data to conduct large-scale epidemiological studies to assess the complex interactions among chronic conditions. This could be useful in designing clinical interventions for patients with multimorbidity, as well as recommendations for healthcare professionals on how to handle these types of patients in clinical practice.