Background: Multimorbidity and frailty are characteristics of aging that need individualized evaluation, and there is a 2-way causal relationship between them. Thus, considering frailty in analyses of multimorbidity is important for tailoring social and health care to the specific needs of older people.Objective: This study aimed to assess how the inclusion of frailty contributes to identifying and characterizing multimorbidity patterns in people aged 65 years or older.Methods: Longitudinal data were drawn from electronic health records through the SIDIAP (Sistema d’Informacio pel Desenvolupament de la Investigacio a l’Atencio Primaria) primary care database for the population aged 65 years or older from 2010 to 2019 in Catalonia, Spain. Frailty and multimorbidity were measured annually using validated tools (eFRAGICAP, a cumulative deficit model; and Swedish National Study of Aging and Care in Kungsholmen [SNAC-K], respectively). Two sets of 11 multimorbidity patterns were obtained using fuzzy c-means. Both considered the chronic conditions of the participants. In addition, one set included age, and the other included frailty. Cox models were used to test their associations with death, nursing home admission, and home care need. Trajectories were defined as the evolution of the patterns over the follow-up period.Results: The study included 1,456,052 unique participants (mean follow-up of 7.0 years). Most patterns were similar in both sets in terms of the most prevalent conditions. However, the patterns that considered frailty were better for identifying the population whose main conditions imposed limitations on daily life, with a higher prevalence of frail individuals in patterns like chronic ulcers & peripheral vascular. This set also included a dementia-specific pattern and showed a better fit with the risk of nursing home admission and home care need. On the other hand, the risk of death had a better fit with the set of patterns that did not include frailty. The change in patterns when considering frailty also led to a change in trajectories. On average, participants were in 1.8 patterns during their follow-up, while 45.1% (656,778/1,456,052) remained in the same pattern.Conclusions: Our results suggest that frailty should be considered in addition to chronic diseases when studying multimorbidity patterns in older adults. Multimorbidity patterns and trajectories can help to identify patients with specific needs. The patterns that considered frailty were better for identifying the risk of certain age-related outcomes, such as nursing home admission or home care need, while those considering age were better for identifying the risk of death. Clinical and social intervention guidelines and resource planning can be tailored based on the prevalence of these patterns and trajectories.

BACKGROUND: Different multimorbidity patterns present with different prognoses, but it is unknown to what extent they may influence the effectiveness of an individualized multicomponent exercise program offered to hospitalized older adults. METHODS: This study is a secondary analysis of a randomized controlled trial conducted in the Department of Geriatric Medicine of a tertiary hospital. In addition to the standard care, an exercise-training multicomponent program was delivered to the intervention group during the acute hospitalization period. Multimorbidity patterns were determined through fuzzy c-means cluster analysis, over 38 chronic diseases. Functional, cognitive and affective outcomes were considered. RESULTS: Three hundred and six patients were included in the analyses (154 control; 152 intervention), with a mean age of 87.2 years, and 58.5% being female. Four patterns of multimorbidity were identified: heart valves and prostate diseases (26.8%); metabolic diseases and colitis (20.6%); psychiatric, cardiovascular and autoimmune diseases (16%); and an unspecific pattern (36.6%). The Short Physical Performance Battery (SPPB) test improved across all patterns, but the intervention was most effective for patients in the metabolic/colitis pattern (2.48-point difference between intervention/control groups, 95% CI 1.60-3.35). Regarding the Barthel Index and the Mini Mental State Examination (MMSE), the differences were significant for all multimorbidity patterns, except for the psychiatric/cardio/autoimmune pattern. Differences concerning quality of life were especially high for the psychiatric/cardio/autoimmune pattern (16.9-point difference between intervention/control groups, 95% CI 4.04, 29.7). CONCLUSIONS: Patients in all the analyzed multimorbidity patterns improved with this tailored program, but the improvement was highest for those in the metabolic pattern. Understanding how different chronic disease combinations are associated with specific functional and cognitive responses to a multicomponent exercise intervention may allow further tailoring such interventions to older patients’ clinical profile.

Objective: An increased interarm blood pressure difference (IAD) (>= 10 mmHg) has been associa-ted with increased cardiovascular morbidity and mortality. There are few studies determining how IAD has to be measured and its reliability between visits. The objectives of our study were twofold. First, to evaluate the concordance between two automatic oscillometric devices for IAD measurement (two OMRON devices and one Microlife WatchBPTM device (WBPTM)) and to analyse the reproducibility of IAD between visits in the general population attending a primary care centre.Design: Descriptive cross-sectional study of concordance between the two methods and repro-ducibility of IAD between two visits separated by one week.Site: Parets del Valles primary care centre (Barcelona).Participants: General population aged 35-74 years. Interventions and main measurements: One hundred and forty-nine patients completed the two visits. At each visit, IAD was measured three times with both methods and the mean of the three determinations was considered. Other variables such as sociodemographic and anth-ropometric variables, pathological antecedents and pharmacological treatment were collected through a review of the medical history and an interview with the patient. Concordance between the two devices and between visits reproducibility were calculated using the Lin concordance coefficient (CCL) for IAD expressed continuously and kappa(k) indices for IAD categorised as normal or pathological.Results: Concordance for IAD expressed continuously was low: CCL = 0.13 (0.02-0.24). Concor-dance was also low for IAD categorised as normal or pathological (k = -0.03 (-0.05-0.00)). Reproducibility between visits was low for both methods and for both continuous and cate-gorised IAD: with OMRONTM CCL = 0.19 (0.03-0.34) and k = -0.02 (-0.16-0.12) and for WBPTM CCL = 0.14 (-0.01-0.29) and k = 0.49 (0.33-0.64).Conclusions: Concordance between two automatic oscillometers in the simultaneous IAD mea-surement was low. Reproducibility between visits was also low for both methods.(c) 2022 The Authors. Published by Elsevier Espana, S.L.U. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Background: The persistence of antibody levels after COVID-19 vaccination has public health relevance. We analyzed the determinants of quantitative serology at 9 months after vaccination in a multicenter cohort. Methods: We analyzed data on anti-SARS-CoV-2 spike antibody levels at 9 months from the first dose of vaccinated HCW from eight centers in Italy, Germany, Spain, Romania and Slovakia. Serological levels were log-transformed to account for the skewness of the distribution and normalized by dividing them by center-specific standard errors. We fitted center-specific multivariate regression models to estimate the cohort-specific relative risks (RR) of an increase of one standard deviation of log antibody level and the corresponding 95% confidence interval (CI), and combined them in random-effects meta-analyses. Finally, we conducted a trend analysis of 1 to 7 months’ serology within one cohort. Results: We included 20,216 HCW with up to two vaccine doses and showed that high antibody levels were associated with female sex (p = 0.01), age (RR = 0.87, 95% CI = 0.86-0.88 per 10-year increase), 10-day increase in time since last vaccine (RR = 0.97, 95% CI 0.97-0.98), previous infection (3.03, 95% CI = 2.92-3.13), two vaccine doses (RR = 1.22, 95% CI = 1.09-1.36), use of Spikevax (OR = 1.51, 95% CI = 1.39-1.64), Vaxzevria (OR = 0.57, 95% CI = 0.44-0.73) or heterologous vaccination (OR = 1.33, 95% CI = 1.12-1.57), compared to Comirnaty. The trend in the Bologna cohort, based on 3979 measurements, showed a decrease in mean standardized antibody level from 8.17 to 7.06 (1-7 months, p for trend 0.005). Conclusions: Our findings corroborate current knowledge on the determinants of COVID-19 vaccine-induced immunity and declining trend with time.