Background Falls in the elderly are a major public health concern because of their high incidence, the involvement of many risk factors, the considerable post-fall morbidity and mortality, and the health-related and social costs. Given that many falls are preventable, the early identification of older adults at risk of falling is crucial in order to develop tailored interventions to prevent such falls. To date, however, the fall-risk assessment tools currently used in the elderly have not shown sufficiently high predictive validity to distinguish between subjects at high and low fall risk. Consequently, predicting the risk of falling remains an unsolved issue in geriatric medicine. This one-year prospective study aims to develop and validate, by means of a cross-validation method, a multifactorial fall-risk model based on clinical and robotic parameters in older adults. Methods Community-dwelling subjects aged � 65 years were enrolled. At the baseline, all subjects were evaluated for history of falling and number of drugs taken daily, and their gait and balance were evaluated by means of the Timed "Up & Go" test (TUG), Gait Speed (GS), Short Physical Performance Battery (SPPB) and Performance-Oriented Mobility Assessment (POMA). They also underwent robotic assessment by means of the hunova robotic device to evaluate the various components of balance. All subjects were followed up for one-year and the number of falls was recorded. The models that best predicted falls-on the basis of: i) only clinical parameters; ii) only robotic parameters; iii) clinical plus robotic parameterswere identified by means of a cross-validation method.

Background During the recent lockdown measures adopted by national authorities to contain the COVID-19 pandemic, many vulnerable older patients with chronic conditions, normally followed in ambulatory setting, needed to be monitored and managed in alternative ways, including telemedicine. Aims In the framework of a telemedicine program, we aimed to validate and implement a telephone-administered version of the Multidimensional Prognostic Index (TELE-MPI) among community-dwelling older outpatients. Method From March 9 to May 11, 2020, 131 older patients (82.1 years; 74% females) were interviewed using a telephonebased survey to calculate the TELE-MPI. The standard MPI was performed face-to-face three months apart. The Bland-Altman methodology measured the agreement between the two tools. Multivariate logistic regression models were built to ascertain the prognostic value of TELE-MPI and TELE-MPI classes (low, moderate, or severe risk) on negative outcomes occurring during the lockdown period. Results Mean MPI and TELE-MPI values were 0.523 and 0.522, respectively. Lower and upper 95% limits of agreement were − 0.122 and + 0.124, respectively, with only 4.6% of observations outside the limits. Each 0.1 increase of TELE-MPI score was significantly correlated with higher incidence of psychiatric disorders [odd ratio (OR): 1.57; 95% confidence interval (CI) 1.27, 1.95] and falls (OR: 1.41; 95% CI 1.08, 1.82) in community-dwelling-older adults. Discussion TELE-MPI showed a strong agreement with the standard MPI and was able to predict psychiatric disorders and falls during lockdown period. Conclusion TELE-MPI may represent a useful way to follow by remote the health status of older adults.

Background Impaired physical performance is common in older adults and has been identified as a major risk factor for falls. To date, there are no conclusive data on the impairment of balance parameters in older subjects with different levels of physical performance. Aims The aim of this study was to investigate the relationship between different grades of physical performance, as assessed by the Short Physical Performance Battery (SPPB), and the multidimensional balance control parameters, as measured by means of a robotic system, in community-dwelling older adults. Methods This study enrolled subjects aged ≥ 65 years. Balance parameters were assessed by the hunova robot in static and dynamic (unstable and perturbating) conditions, in both standing and seated positions and with the eyes open/closed. Results The study population consisted of 96 subjects (62 females, mean age 77.2 ± 6.5 years). According to their SPPB scores, subjects were separated into poor performers (SPPB < 8, n = 29), intermediate performers (SPPB = 8-9, n = 29) and good performers (SPPB > 9, n = 38). Poor performers displayed significantly worse balance control, showing impaired trunk control in most of the standing and sitting balance tests, especially in dynamic (both with unstable and perturbating platform/seat) conditions. Conclusions For the first time, multidimensional balance parameters, as detected by the hunova robotic system, were significantly correlated with SPPB functional performances in community-dwelling older subjects. In addition, balance parameters in dynamic conditions proved to be more sensitive in detecting balance impairments than static tests.

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Objectives The multidimensional prognostic index (MPI) is a useful prognostic tool for evaluating adverse health outcomes in older individuals. However, the association between MPI and depressive symptoms has never been explored, despite depression being a common condition in older people. We therefore aimed to evaluate whether MPI may predict incident depressive symptoms. Methods Longitudinal, cohort study, with 2 years of follow‐up (W1: October 2009‐February 2011; W2: April 2012‐January 2013), including people aged ≥65 years without depressive symptoms at baseline. A comprehensive geriatric assessment including information on functional, nutritional, cognitive status, mobility, comorbidities, medications, and cohabitation status was used to calculate the MPI dividing the participants into low, moderate, or severe risk. Those who scored ≥16/60 with the Center of Epidemiology Studies Depression (CES‐D) tool were considered to have depressive symptoms. Multivariable logistic regression models were built to explore the association between MPI and incident depressive symptoms. Results The sample consisted of 1854 participants (mean age: 72.8 ± SD 5.1 years; females: 52.1%). The prevalence of incident depressive symptoms by MPI tertiles at baseline were: low 2.5%, moderate 3.9%, and severe 6.7%. In multivariable analyses, baseline MPI values were significantly associated with incident depressive symptoms (increase in 0.1 points in MPI: odds ratio, OR = 1.47; 95% confidence intervals, CI: 1.17‐1.85; MPI tertile severe vs low: OR = 2.96; 95%CI: 1.50‐5.85). Conclusion Baseline MPI values were associated with incident depressive symptoms indicating that multidimensional assessment of older people may lead to early identification of individuals at increased risk of depression onset.