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Abstract Purpose Multimorbidity and polypharmacy in older adults converts the detection and adequacy of potentially inappropriate drug prescriptions (PIDP) in a healthcare priority. The objectives of this study are to describe the clinical decisions taken after the identification of PIDP by clinical pharmacists, using STOPP/START criteria, and to evaluate the degree of accomplishment of these decisions. Methods Multicenter, prospective, non-comparative cohort study in patients aged 65 and older, hospitalized because of an exacerbation of their chronic conditions. Each possible PIDP was manually identified by the clinical pharmacist at admission and an initial decision was taken by a multidisciplinary clinical committee. At discharge, criteria were re-applied and final decisions recorded. Results From all patients (n = 674), 493 (73.1%) presented at least one STOPP criteria at admission, significantly reduced up to 258 (38.3%) at discharge. A similar trend was observed for START criteria (36.7% vs. 15.7%). Regarding the top 10 most prevalent STOPP criteria, the clinical committee initially agreed to withdraw 257 (34.2%) prescriptions and to modify 93 (12.4%) prescriptions. However, the evaluation of final clinical decisions revealed that 503 (67.0%) of those STOPP criteria were ultimately amended. For the top 10 START criteria associated PIDP, the committee decided to initiate 149 (51.7%) prescriptions, while a total of 198 (68.8%) were finally introduced at discharge. Conclusions The clinical committee, through a pharmacotherapy review, succeeded in identifying and reducing the degree of prescription inadequacy, for both STOPP and START criteria, in older patients with high degree of multimorbidity and polypharmacy. Trial Registration NCT02830425.

Abstract Background Multimorbidity is associated with negative results and poses difficulties in clinical management. New methodological approaches are emerging based on the hypothesis that chronic conditions are non-randomly associated forming multimorbidity patterns. However, there are few longitudinal studies of these patterns, which could allow for better preventive strategies and healthcare planning. The objective of the MTOP (Multimorbidity Trajectories in Older Patients) study is to identify patterns of chronic multimorbidity in a cohort of older patients and their progression and trajectories in the previous 10 years. Methods A retrospective, observational study with a cohort of 3988 patients aged > 65 was conducted, including suspected and confirmed COVID-19 patients in the reference area of Parc Taulí University Hospital. Real-world data on socio-demographic and diagnostic variables were retrieved. Multimorbidity patterns of chronic conditions were identified with fuzzy c-means cluster analysis. Trajectories of each patient were established along three time points (baseline, 5 years before, 10 years before). Descriptive statistics were performed together with a stratification by sex and age group. Results 3988 patients aged over 65 were included (58.9% females). Patients with ≥ 2 chronic conditions changed from 73.6 to 98.3% in the 10-year range of the study. Six clusters of chronic multimorbidity were identified 10 years before baseline, whereas five clusters were identified at both 5 years before and at baseline. Three clusters were consistently identified in all time points (Metabolic and vascular disease, Musculoskeletal and chronic pain syndrome, Unspecific); three clusters were only present at the earliest time point (Male-predominant diseases, Minor conditions and sensory impairment, Lipid metabolism disorders) and two clusters emerged 5 years before baseline and remained (Heart diseases and Neurocognitive). Sex and age stratification showed different distribution in cluster prevalence and trajectories. Conclusions In a cohort of older patients, we were able to identify multimorbidity patterns of chronic conditions and describe their individual trajectories in the previous 10 years. Our results suggest that taking these trajectories into consideration might improve decisions in clinical management and healthcare planning. Trial registration number NCT05717309.

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).

Abstract Objectives The objectives of the present analyses are to estimate the frequency of potentially inappropriate prescribing (PIP) at admission according to STOPP/START criteria version 2 in older patients hospitalised due to chronic disease exacerbation as well as to identify risk factors associated to the most frequent active principles as potentially inappropriate medications (PIMs). Methods A multicentre, prospective cohort study including older patients (≥65) hospitalized due to chronic disease exacerbation at the internal medicine or geriatric services of 5 hospitals in Spain between September 2016 and December 2018 was conducted. Demographic and clinical data was collected, and a medication review process using STOPP/START criteria version 2 was performed, considering both PIMs and potential prescribing omissions (PPOs). Primary outcome was defined as the presence of any most frequent principles as PIMs, and secondary outcomes were the frequency of any PIM and PPO. Descriptive and bivariate analyses were conducted on all outcomes and multilevel logistic regression analysis, stratified by participating centre, was performed on the primary outcome. Results A total of 740 patients were included (mean age 84.1, 53.2% females), 93.8% of them presenting polypharmacy, with a median of 10 chronic prescriptions. Among all, 603 (81.5%) patients presented at least one PIP, 542 (73.2%) any PIM and 263 (35.5%) any PPO. Drugs prescribed without an evidence-based clinical indication were the most frequent PIM (33.8% of patients); vitamin D supplement in older people who are housebound or experiencing falls or with osteopenia was the most frequent PPO (10.3%). The most frequent active principles as PIMs were proton pump inhibitors (PPIs) and benzodiazepines (BZDs), present in 345 (46.6%) patients. This outcome was found significantly associated with age, polypharmacy and essential tremor in an explanatory model with 71% AUC. Conclusions PIMs at admission are highly prevalent in these patients, especially those involving PPIs or BZDs, which affected almost half of the patients. Therefore, these drugs may be considered as the starting point for medication review and deprescription. Trial registration number NCT02830425

Background: Faecal microbiota transplantation (FMT) is a novel potential therapy for inflammatory bowel diseases, but it is poorly characterised. Methods: We evaluated the performance of the mouse and rat as a pre-clinical model for human microbiota engraftment. We then characterised the effect of a single human stool transfer (HST) on a humanised model of DSS-induced colitis. Colonic and faecal microbial communities were analysed using the 16S rRNA approach and clinical manifestations were assessed in a longitudinal setting. Findings: The microbial community of rats showed greater similarity to that of humans, while the microbiome of mice showed less similarity to that of humans. Moreover, rats captured more human microbial species than mice after a single HST. Using the rat model, we showed that HST compensated faecal dysbiosis by restoring alpha-diversity and by increasing the relative abundance of health-related microbial genera. To some extent, HST also modulated the microbial composition of colonic tissue. These faecal and colonic microbial communities alterations led to a relative restoration of colon length, and a significant decrease in both epithelium damage and disease severity. Remarkably, stopping inflammation by removing DSS before HST caused a faster and greater recovery of both microbiome and clinical manifestation features. Interpretation: Our results indicate that the rat outperforms the mouse as a model for human microbiota engraftment and show that the efficacy of HST can be enhanced when inflammation stimulation is withdrawn. Finally, our findings support a new therapeutic strategy based on the use FMT combined with anti-inflammatory drugs. Keywords: Inflammatory bowel disease, Faecal microbiota transplantation, Rat model of colitis

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