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Background: We evaluated whether frailty and multimorbidity predict in-hospital mortality in patients with COVID-19 beyond chronological age.Method: A total of 165 patients admitted from March 8th to April 17th, 2020, with COVID-19 in an acute geriatric ward in Italy were included. Predisease frailty was assessed with the Clinical Frailty Scale (CFS). Multimorbidity was defined as the co-occurrence of ≥2 diseases in the same patient. The hazard ratio (HR) of in-hospital mortality as a function of CFS score and number of chronic diseases in the whole population and in those aged 70+ years were calculated.Results: Among the 165 patients, 112 were discharged, 11 were transferred to intensive care units, and 42 died. Patients who died were older (81.0 vs 65.2 years, p < .001), more frequently multimorbid (97.6 vs 52.8%; p < .001), and more likely frail (37.5 vs 4.1%; p < .001). Less than 2.0% of patients without multimorbidity and frailty, 28% of those with multimorbidity only, and 75% of those with both multimorbidity and frailty died. Each unitary increment in the CFS was associated with a higher risk of in-hospital death in the whole sample (HR = 1.3; 95% CI = 1.05-1.62) and in patients aged 70+ years (HR = 1.29; 95% CI = 1.04-1.62), whereas the number of chronic diseases was not significantly associated with higher risk of death. The CFS addition to age and sex increased mortality prediction by 9.4% in those aged 70+ years.Conclusions: Frailty identifies patients with COVID-19 at risk of in-hospital death independently of age. Multimorbidity contributes to prognosis because of the very low probability of death in its absence. [ABSTRACT FROM AUTHOR]

Multimorbidity, the coexistence of multiple chronic diseases in an individual, is highly prevalent and challenging for healthcare systems. However, its risk factors remain poorly understood. To systematically review studies reporting multimorbidity risk factors. A PRISMA-compliant systematic review was conducted, searching electronic databases (MEDLINE, EMBASE, Web of Science, Scopus). Inclusion criteria were studies addressing multimorbidity transitions, trajectories, continuous disease counts, and specific patterns. Non-human studies and participants under 18 were excluded. Associations between risk factors and multimorbidity onset were reported. Of 20,806 identified studies, 68 were included, with participants aged 18–105 from 23 countries. Nine risk factor categories were identified, including demographic, socioeconomic, and behavioral factors. Older age, low education, obesity, hypertension, depression, low pysical function were generally positively associated with multimorbidity. Results for factors like smoking, alcohol consumption, and dietary patterns were inconsistent. Study quality was moderate, with 16.2% having low risk of bias. Several risk factors seem to be consistently associated with an increased risk of accumulating chronic diseases over time. However, heterogeneity in settings, exposure and outcome, and baseline health of participants hampers robust conclusions. • Multimorbidity, affects most older persons and is more prevalent in adults with low socioeconomic status • The identification of risk factors for multimorbidity may inform public health policies and prevention programs • Older age, low education, obesity, hypertension, depression, low pysical function were generally positively associated with multimorbidity. [ABSTRACT FROM AUTHOR]

Abstract Background Frailty and multimorbidity are both strongly associated with poor health-related outcomes, including mortality. Being multimorbidity one of the major determinants of frailty, we aimed to explore whether, and to what extent, frailty without multimorbidity plays an independent role in shortening life. Methods We used data from the Swedish National Study on Aging and Care in Kungsholmen (SNAC-K). Among the 3363 adults aged 60+ enrolled at baseline, those without multimorbidity (i.e.: less than two chronic diseases) (N = 1115) have been characterized according to Fried's frailty phenotype (i.e. robust, prefrail, and frail). The association between frailty and mortality was estimated using piecewise proportional hazard regression models in three five-year time periods. Results Among participants without multimorbidity, 424 (38%) were prefrail and 19 (2%) were frail. During the 15-year follow-up, 263 (24%) participants died: 19%, 29%, and 63% of those who were robust, prefrail, and frail at baseline, respectively. Within the first 5 years of follow-up, prefrail and frail participants had more than doubled mortality risk in comparison to robust ones (HR for pre-frailty 2.08, 95% CI 1.15–3.76; HR for frailty 2.69, 95% CI 1.22–5.97). Beyond 5 years, a trend of increased mortality rate was still detectable for prefrail and frail subjects in comparison to robust ones. Conclusions Physical frailty and pre-frailty are associated with short-term mortality in a cohort of older adults free from multimorbidity. Frailty could be a clinical indicator of increased risk of negative health outcomes even among subjects without multiple chronic conditions. Highlights • Forty percent of subjects without multimorbidity are frail or prefrail. • Frailty and pre-frailty increase mortality risk even in absence of multimorbidity. • Screening for frailty in individuals without multimorbidity might be beneficial. • Future research should focus on causes of frailty other than chronic diseases. [ABSTRACT FROM AUTHOR]

The presence of multiple chronic conditions (i.e., multimorbidity) increases the risk of hospitalisation in older adults. We aimed to examine the association between different multimorbidity patterns and unplanned hospitalisations over 5 years. To that end, 2,250 community-dwelling individuals aged 60 years and older from the Swedish National Study on Aging and Care in Kungsholmen (SNAC-K) were studied. Participants were grouped into six multimorbidity patterns using a fuzzy c-means cluster analysis. The associations between patterns and outcomes were tested using Cox models and negative binomial models. After 5 years, 937 (41.6%) participants experienced at least one unplanned hospitalisation. Compared to participants in the unspecific multimorbidity pattern, those in the cardiovascular diseases, anaemia and dementia pattern, the psychiatric disorders pattern and the metabolic and sleep disorders pattern presented with a higher hazard of first unplanned hospitalisation (hazard ratio range: 1.49–2.05; p < 0.05 for all), number of unplanned hospitalisations (incidence rate ratio (IRR) range: 1.89–2.44; p < 0.05 for all), in-hospital days (IRR range: 1.91–3.61; p < 0.05 for all), and 30-day unplanned readmissions (IRR range: 2.94–3.65; p < 0.05 for all). Different multimorbidity patterns displayed a differential association with unplanned hospital care utilisation. These findings call for a careful primary care follow-up of older adults with complex multimorbidity patterns. [ABSTRACT FROM AUTHOR]