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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).

ABSTRACTBackground:Certain studies have shown the beneficial effects of methotrexate (MTX) in asthma patients. Here we describe the drug''s tolerance and oral corticosteroid sparing capacity in a long-term observational study.Methods:Forty-four patients with steroid-dependent asthma treated with 10 mg per week of oral MTX were prospectively followed for 91.3 ± 39.5 months. Intervention: blood analysis each 3 months; spirometry monthly during the first 3 months and then every 3–6 months; liver ultrasound when an accumulated dose of 1500 mg was reached or whenever hepatic function was altered.Results:Two patients who dropped out early were excluded. Mean accumulated dose of MTX was 3.499 ± 2.207 mg. Corticosteroid use was reduced from 15.1 ± 8.2 to 2.64 ± 5.35 mg (p < 0.008) and was withdrawn in 25 patients. In the remaining 17 patients, the dose was reduced from 17.1 ± 9.1 mg to 6.5 ± 6.8 mg. FEV1( predicted) was 66.2 ± 19.7 at the beginning and 65.7 ± 19.1 at the end. Haematology was normal and only a mild increase in hepatic enzymes was observed in four patients, which normalized after treatment discontinuation. Hair loss was observed in one case.Conclusions:In our series, a substantial, safe decrease in oral corticosteroid requirements was observed, probably due, to some extent, to MTX therapy. Oral corticosteroids were withdrawn completely in 59 of patients. Liver function was impaired in some patients; however, it recovered after MTX withdrawal and MTX could be safely reintroduced. The association of oral corticosteroids and MTX did not increase the number of side-effects and immunity was not affected. We were unable to identify a factor that could predict which patients would benefit most from MTX treatment. Some limitations of the study include the lack of control of asthma exacerbations and the lack of booster courses of corticosteroids. [ABSTRACT FROM AUTHOR]