Resilience improvement through a multicomponent physical and cognitive intervention for older people: the DanzArTe emotional well-being technology project.

BACKGROUND: Resilience is a crucial component of successful aging. However, which interventions might increase resilience in older adults is yet unclear. AIMS: This study aims to assess the feasibility and the physical and psychological effects of a technology-based multicomponent dance movement intervention that includes physical, cognitive, and sensory activation in older people living in community-dwelling and nursing home. METHODS: DanzArTe program consists of four sessions on a weekly basis, using a technological platform that integrates visual and auditory contents in real time. 122 participants (mean age = 76.3 ± 8.8 years, 91 females = 74.6%) from seven nursing homes and community-dwelling subjects were assessed, before and after the intervention, with the Resilience Scale-14 items (RES-14), the Multidimensional Prognostic Index (MPI), the Psychological General Well-Being Index (PGWBI-S), and the Client Satisfaction Questionnaire-8 (CSQ-8). Mann-Whitney and Wilcoxon signed-ranks tests were used for statistical analyses. RESULTS: At baseline significant differences in MPI and RES-14 between community-dwelling and nursing home residents were observed (p < 0.001 for both analyses). After the intervention, resilience significantly increased in total sample (RES-14 mean T1 = 74.6 Vs. T2 = 75.7) and in the nursing home residents (RES-14 mean T1 = 68.1 Vs. T2 = 71.8). All participants showed high overall satisfaction for DanzArTe program (CSQ-8 mean = 23.9 ± 4.4). No differences in MPI and PGWBI-S were observed. DISCUSSION: DanzArTe was a feasible intervention and high appreciated by all older adults. Nursing home residents revealed improvements in resilience after DanzArTe program. CONCLUSION: The DanzArTe technology-based multi-component intervention may improve resilience in older people living in nursing homes.

Validation of a Brief Form of the Self-Administered Multidimensional Prognostic Index: The SELFY-BRIEF-MPI Project.

In clinical practice, self-administered and brief tools to promptly identify older people at risk of frailty are required. The Multidimensional Prognostic Index (MPI), derived from the Comprehensive Geriatric Assessment (CGA) seems reliable enough to serve this purpose, but despite the several versions developed over the past 15 years, it lacks a self-administered and brief version. In this study, we aimed to evaluate the agreement between an abbreviated form of the SELFY-MPI (i.e., SELFY-BRIEF-MPI) and the standard version of the MPI. Four Italian hospitals consecutively enrolled outpatients and inpatients >65 years. The sample included 105 participants (mean age = 78.8 years, 53.3% females). Overall, the two versions showed non-statistically significant differences (Standard-MPI 0.42 ± 0.19 vs.. SELFY-BRIEF-MPI 0.41 ± 0.18; p = 0.104) and a very strong correlation (R = 0.86, p < 0.001). The Bland-Altman Plot revealed that only 5/105 measurements (4.76%) were outside the limits of agreement. The accuracy of the SELFY-BRIEF-MPI in identifying frail people (defined as a Standard-MPI > 0.66) was optimal (area under the curve, AUC = 0.90, p < 0.001). To predict multidimensional frailty, a SELFY-BRIEF-MPI score of 0.60 exhibited the greatest sensitivity/specificity ratio. In conclusion, the SELFY-BRIEF-MPI reported a good agreement with the standard version of the MPI, indicating its application in the screening of multidimensional frailty among older people.

Frailty trajectories in community-dwelling older adults during COVID-19 pandemic: The PRESTIGE study.

BACKGROUND: Frailty has been recognized as potential surrogate of biological age and relevant risk factor for COVID-19 severity. Thus, it is important to explore the frailty trajectories during COVID-19 pandemic and understand how COVID-19 directly and indirectly impacts on frailty condition. METHODS: We enrolled 217 community-dwelling older adults with available information on frailty condition as assessed by multidimensional frailty model both at baseline and at one-year follow-up using Multidimensional Prognostic Index (MPI) tools. Pre-frail/frail subjects were identified at baseline as those with MPI score >0.33 (MPI grades 2-3). Frailty worsening was defined by MPI difference between 12 months follow-up and baseline ≥0.1. Multivariable logistic regression was modelled to identify predictors of worsening of frailty condition. RESULTS: Frailer subjects at baseline (MPI grades 2-3 = 48.4%) were older, more frequently female and had higher rates of hospitalization and Sars-CoV-2 infection compared to robust ones (MPI grade 1). Having MPI grades 2-3 at baseline was associated with higher risk of further worsening of frailty condition (adjusted odd ratio (aOR): 13.60, 95% confidence interval (CI): 4.01-46.09), independently by age, gender and Sars-CoV-2 infection. Specifically, frail subjects without COVID-19 (aOR: 14.84, 95% CI: 4.26-51.74) as well as those with COVID-19 (aOR: 12.77, 95% CI: 2.66-61.40, p = 0.001) had significantly higher risk of worsening of frailty condition. CONCLUSIONS: Effects of COVID-19 pandemic among community-dwelling frailer individuals are far beyond the mere infection and disease, determining a significant deterioration of frailty status both in infected and non-infected subjects.

Multidimensional Frailty Predicts Mortality Better than Physical Frailty in Community-Dwelling Older People: A Five-Year Longitudinal Cohort Study.

Frailty is a common syndrome in older people that carries an increased risk of mortality. Two main models describe frailty, either as a loss of physical functions or as an accumulation of multiple deficits. The aim of our study was to compare the physical frailty index developed in the Cardiovascular Health Study (CHS) with a multidimensional frailty tool, the Multidimensional Prognostic Index (MPI), in predicting death in community-dwelling older subjects. Four hundred and seven community-dwelling older subjects were enrolled. Each subject underwent a comprehensive geriatric assessment (CGA) with calculation of the MPI and CHS index. Mortality was recorded over the following 5 years. In the overall sample (mean age of 77.9 ± 4.5 years; 51.6% female), 53 subjects (13%) died during the 5-year follow-up period. Both the MPI and CHS index were able to predict mortality; however, the MPI was significantly more accurate than the CHS index in predicting mortality (C-index = 0.69 and 0.59, respectively; p < 0.001), with a statistically significant difference of 10%. In conclusion, multidimensional frailty, assessed by the MPI, predicts five-year mortality in community-dwelling older people better than physical frailty, as assessed by the CHS index. These findings suggest the usefulness of assessing frailty by means of CGA-based tools to predict relevant health-negative outcomes in older people.

Validation and implementation of telephone-administered version of the Multidimensional Prognostic Index (TELE-MPI) for remote monitoring of community-dwelling older adults.

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 telephone-based 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.

Multidimensional prognostic index (MPI) predicts successful application for disability social benefits in older people.

AIM: The economic recognition of disability is of importance in daily practice, but the tools used in older people are still limited. Therefore, we aimed to investigate the effectiveness of the multidimensional prognostic index (MPI) to identify frail older subjects to be submitted to civil invalidity application for disability benefits including Attendance Allowance (AA) indemnity, Carer's Leave (Law 104) and/or Parking Card for people with disabilities. METHODS: From March 2018 to January 2019, 80 older people were included. The MPI was calculated from comprehensive geriatric assessment information including eight different domains. Civil benefits included attendance allowance (AA) indemnity by the Local Medico-Legal Committee (MLC-NHS) and by the National Institute of Social Security Committee (INPS), Carer's Leave (Law 104), and Parking Card for people with disabilities. RESULTS: MPI values were associated with an increased probability to obtain a 100% civil disability, AA indemnity, Carer's Leave and a parking card for people with disabilities. MPI score showed a very good accuracy in predicting the civil invalidity benefits with a area-under-curve (AUC) of 87.3 (95% CI 80.6-97.4) to predict the release of AA indemnity, 81.3 (95% CI 68.5-91.1) to predict Care's leave and 70.7 (95% CI 59.4-84.7) to predict the Parking Card release. Moreover, data showed that a cut-off score of MPI ≥ 0.75 could identify the 100% of older subjects who successfully obtained the indemnity release. CONCLUSION: MPI is an excellent predictor of social benefits' release by local and national agencies.

Development and validation of a robotic multifactorial fall-risk predictive model: A one-year prospective study in community-dwelling older adults.

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 parameters-were identified by means of a cross-validation method. RESULTS: Of the 100 subjects initially enrolled, 96 (62 females, mean age 77.17±.49 years) completed the follow-up and were included. Within one year, 32 participants (33%) experienced at least one fall ("fallers"), while 64 (67%) did not ("non-fallers"). The best classifier model to emerge from cross-validated fall-risk estimation included eight clinical variables (age, sex, history of falling in the previous 12 months, TUG, Tinetti, SPPB, Low GS, number of drugs) and 20 robotic parameters, and displayed an area under the receiver operator characteristic (ROC) curve of 0.81 (95% CI: 0.72-0.90). Notably, the model that included only three of these clinical variables (age, history of falls and low GS) plus the robotic parameters showed similar accuracy (ROC AUC 0.80, 95% CI: 0.71-0.89). In comparison with the best classifier model that comprised only clinical parameters (ROC AUC: 0.67; 95% CI: 0.55-0.79), both models performed better in predicting fall risk, with an estimated Net Reclassification Improvement (NRI) of 0.30 and 0.31 (p = 0.02), respectively, and an estimated Integrated Discrimination Improvement (IDI) of 0.32 and 0.27 (p<0.001), respectively. The best model that comprised only robotic parameters (the 20 parameters identified in the final model) achieved a better performance than the clinical parameters alone, but worse than the combination of both clinical and robotic variables (ROC AUC: 0.73, 95% CI 0.63-0.83). CONCLUSION: A multifactorial fall-risk assessment that includes clinical and hunova robotic variables significantly improves the accuracy of predicting the risk of falling in community-dwelling older people. Our data suggest that combining clinical and robotic assessments can more accurately identify older people at high risk of falls, thereby enabling personalized fall-prevention interventions to be undertaken.

Relationship between multidimensional prognostic index and incident depressive symptoms in older people: Findings from the Irish Longitudinal Study on Ageing.

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.

Robotic balance assessment in community-dwelling older people with different grades of impairment of physical performance.

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.

Primary hyperparathyroidism and neuropsychiatric alterations in a nonagenarian woman.

Whether elderly patients with asymptomatic or minimally symptomatic primary hyperparathyroidism (PHPT) should be treated or not is still under debate. Several literature reports have shown improvements in terms of bone density and physical and mental well-being after surgical resolution of PHPT. Here, we present the case of a 93-year-old hypertensive woman, who had suffered for one year from cognitive impairment, accompanied during the last month by behavioral alterations (and polyuria and polydipsia), which resulted in sopor leading to hospitalization. A CT brain scan evidenced cortical atrophy and cerebrovascular disease, and biochemical analyses were remarkable for hypercalcemia (11.4-12.6 mg/dL, corrected for albumin levels) associated with increased parathormone levels (95.4-100.6 pg/mL). A diagnosis of PHPT was established. Densitometry evaluation of radius showed osteopenia. Withdrawal of psycho-therapy drugs and thiazidic, together with i.v. saline hydration and loop diuretics, significantly improved the patient's mental state and resolved behavioral alterations. As the patient and her relatives refused the surgical option, and the clinical situation improved after medical normalization of calcium levels, PHPT was managed conservatively, and calcium levels were maintained within the normal range through i.v. administration of zoledronate at 8-week intervals. Our case highlights the importance of considering hypercalcemia as the cause of onset of behavioral alterations and worsening of mental condition in elderly patients with cognitive decline. Therapy with bisphosphonates in patients with PHPT who are unfit for or refuse surgery seems advisable, but needs further study.