Partially supervised exercise programmes for fall prevention improve physical performance of older people at risk of falling: a three-armed multi-centre randomised controlled trial.

BACKGROUND: Falls have a major impact on individual patients, their relatives, the healthcare system and related costs. Physical exercise programmes that include multiple categories of exercise effectively reduce the rate of falls and risk of falling among older adults. METHODS: This 12-month, assessor-blinded, three-armed multicentre randomised clinical trial was conducted in adults aged ≥ 65 years identified as at risk of falling. Four hundred and five participants were randomly allocated into 3 groups: experimental group (n = 166) with the Test&Exercise partially supervised programme based on empowerment delivered with a tablet, illustrated manual and cards, reference group (n = 158) with the Otago partially supervised programme prescribed by a physiotherapist delivered with an illustrated manual and control group (n = 81) with the Helsana self-administrated programme delivered with cards. Experimental and reference groups received partially supervised programmes with 8 home sessions over 6 months. Control group received a self-administered program with a unique home session. The 3 groups were requested to train independently 3 times a week for 12 months. Primary outcome was the incidence rate ratio of self-reported falls over 12 months. Secondary outcomes were fear of falling, basic functional mobility and balance, quality of life, and exercise adherence. RESULTS: A total of 141 falls occurred in the experimental group, 199 in the reference group, and 42 in the control group. Incidence rate ratios were 0.74 (95% CI 0.49 to 1.12) for the experimental group and 0.43 (95% CI 0.25 to 0.75) for the control group compared with the reference group. The Short Physical Performance Battery scores improved significantly in the experimental group (95% CI 0.05 to 0.86; P = 0.027) and in the reference group (95% CI 0.06 to 0.86; P = 0.024) compared with the control group. CONCLUSION: The self-administered home-based exercise programme showed the lowest fall incidence rate, but also the highest dropout rate of participants at high risk of falling. Both partially supervised programmes resulted in statistically significant improvements in physical performance compared with the self-administered programme. TRIAL REGISTRATION: NCT02926105. CLINICALTRIALS: gov. Date of registration: 06/10/2016.

Validation of a fall rate prediction model for community-dwelling older adults: a combined analysis of three cohorts with 1850 participants.

BACKGROUND: Fragility fractures in older adults are often caused by fall events. The estimation of an expected fall rate might improve the identification of individuals at risk of fragility fractures and improve fracture prediction. METHODS: A combined analysis of three previously developed fall rate models using individual participant data (n = 1850) was conducted using the methodology of a two-stage meta-analysis to derive an overall model. These previously developed models included the fall history as a predictor recorded as the number of experienced falls within 12 months, treated as a factor variable with the levels 0, 1, 2, 3, 4 and ≥ 5 falls. In the first stage, negative binomial regression models for every cohort were fit. In the second stage, the coefficients were compared and used to derive overall coefficients with a random effect meta-analysis. Additionally, external validation was performed by applying the three data sets to the models derived in the first stage. RESULTS: The coefficient estimates for the prior number of falls were consistent among the three studies. Higgin's I2 as heterogeneity measure ranged from 0 to 55.39%. The overall coefficient estimates indicated that the expected fall rate increases with an increasing number of previous falls. External model validation revealed that the prediction errors for the data sets were independent of the model to which they were applied. CONCLUSION: This analysis suggests that the fall history treated as a factor variable is a robust predictor of estimating future falls among different cohorts.

Development of a personalized fall rate prediction model in community-dwelling older adults: a negative binomial regression modelling approach.

BACKGROUND: Around a third of adults aged 65 and older fall every year, resulting in unintentional injuries in 30% of the cases. Fractures are a frequent consequence of falls, primarily caused in individuals with decreased bone strength who are unable to cushion their falls. Accordingly, an individual's number of experienced falls has a direct influence on fracture risk. The aim of this study was the development of a statistical model to predict future fall rates using personalized risk predictors. METHODS: In the prospective cohort GERICO, several fall risk factor variables were collected in community-dwelling older adults at two time-points four years apart (T1 and T2). Participants were asked how many falls they experienced during 12 months prior to the examinations. Rate ratios for the number of reported falls at T2 were computed for age, sex, reported fall number at T1, physical performance tests, physical activity level, comorbidity and medication number with negative binomial regression models. RESULTS: The analysis included 604 participants (male: 122, female: 482) with a median age of 67.90 years at T1. The mean number of falls per person was 1.04 and 0.70 at T1 and T2. The number of reported falls at T1 as a factor variable was the strongest risk factor with an unadjusted rate ratio [RR] of 2.60 for 3 falls (95% confidence interval [CI] 1.54 to 4.37), RR of 2.63 (95% CI 1.06 to 6.54) for 4 falls, and RR of 10.19 (95% CI 6.25 to 16.60) for 5 and more falls, when compared to 0 falls. The cross-validated prediction error was comparable for the global model including all candidate variables and the univariable model including prior fall numbers at T1 as the only predictor. CONCLUSION: In the GERICO cohort, the prior fall number as single predictor information for a personalized fall rate is as good as when including further available fall risk factors. Specifically, individuals who have experienced three and more falls are expected to fall multiple times again. TRIAL REGISTRATION: ISRCTN11865958, 13/07/2016, retrospectively registered.

Asynchronous calibration of a CT scanner for bone mineral density estimation: sources of error and correction.

The estimation of BMD with CT scans requires a calibration method, usually based on a phantom. In asynchronous calibration, the phantom is scanned separately from the patient. A standardized acquisition protocol must be used to avoid variations between patient and phantom. However, variations can still be induced, for example, by temporal fluctuations or patient characteristics. Based on the further use of 739 forensic and 111 clinical CT scans, this study uses the proximal femur BMD value ("total hip") to assess asynchronous calibration accuracy, using in-scan calibration as ground truth. It identifies the parameters affecting the calibration accuracy and quantifies their impact. For time interval and table height, the impact was measured by calibrating the CT scan twice (once using the phantom scan with closest acquisition parameters and once using a phantom scan with standard values) and comparing the calibration accuracy. For other parameters such as body weight, the impact was measured by computing a linear regression between parameter values and calibration accuracy. Finally, this study proposes correction methods to reduce the effect of these parameters and improve the calibration accuracy. The BMD error of the asynchronous calibration, using the phantom scan with the closest acquisition parameters, was -1.2 ± 1.7% for the forensic and - 1.6 ± 3.5% for the clinical dataset. Among the parameters studied, time interval and body weight were identified as the main sources of error for asynchronous calibration, followed by table height and reconstruction kernel. Based on these results, a correction method was proposed to improve the calibration accuracy.

Corrigendum: History of falls and fear of falling are predictive of future falls: Outcome of a fall rate model applied to the Swiss CHEF trial cohort.

[This corrects the article DOI: 10.3389/fragi.2022.1056779.].

History of falls and fear of falling are predictive of future falls: Outcome of a fall rate model applied to the Swiss CHEF Trial cohort.

Background: A third of adults aged 65 years and older fall every year, and falls are a common cause of unintentional injuries. Accurate identification of people at risk of falling is an important step in the implementation of preventive strategies. Objective: Our aim was to investigate the association of fall risk factors with number of reported falls in terms of incidence rate ratios and to develop a fall rate prediction model. Methods: In the randomized controlled trial Swiss CHEF, multiple fall risk variables were assessed in community-dwelling older adults at baseline examination, including age, sex, body mass index, fear of falling, number of falls during the prior 12 months, scores on several physical performance tests, comorbidities, and quality of life. Over the following 6 months, interventions were administered in the form of three home-based exercise programs. Participants were subsequently followed up for another 6 months. Falls were reported prospectively using monthly calendars. Incidence rate ratios were derived via negative binomial regression models. Variable selection for the prediction model was conducted using backward elimination and the least absolute shrinkage and selection operator method; the model with the smallest prediction error was then identified. Results: Associations with the number of reported falls were found for number of prior falls, fear of falling, balance and gait deficits, and quality of life. The final model was derived via backward elimination, and the predictors included were prior number of falls and a measure of fear of falling. Outcome: Number of prior falls and fear of falling can be used as predictors in a personalized fall rate estimate for community-dwelling older adults. Recurrent fallers having experienced four or more falls are especially at risk of falling again.

Uncovering the secretome of mesenchymal stromal cells exposed to healthy, traumatic, and degenerative intervertebral discs: a proteomic analysis.

BACKGROUND: Mesenchymal stromal cells (MSCs) have been introduced as promising cell source for regenerative medicine. Besides their multilineage differentiation capacity, MSCs release a wide spectrum of bioactive factors. This secretome holds immunomodulatory and regenerative capacities. In intervertebral disc (IVD) cells, application of MSC secretome has been shown to decrease the apoptosis rate, induce proliferation, and promote production of extracellular matrix (ECM). For clinical translation of secretome-based treatment, characterization of the secretome composition is needed to better understand the induced biological processes and identify potentially effective secretomes. METHODS: This study aimed to investigate the proteome released by bone marrow-derived MSCs following exposure to a healthy, traumatic, or degenerative human IVD environment by mass spectroscopy and quantitative immunoassay analyses. Exposure of MSCs to the proinflammatory stimulus interleukin 1ß (IL-1ß) was used as control. RESULTS: Compared to MSC baseline secretome, there were 224 significantly up- or downregulated proteins following healthy, 179 following traumatic, 223 following degenerative IVD, and 160 proteins following IL-1ß stimulus. Stimulation of MSCs with IVD conditioned media induced a more complex MSC secretome, involving more biological processes, compared to stimulation with IL-1ß. The MSC response to stimulation with IVD conditioned medium was dependent on their pathological status. CONCLUSIONS: The MSC secretome seemed to match the primary need of the IVD: homeostasis maintenance in the case of healthy IVDs, versus immunomodulation, adjustment of ECM synthesis and degradation disbalance, and ECM (re) organization in the case of traumatic and degenerative IVDs. These findings highlight the importance of cell preconditioning in the development of tailored secretome therapies. The secretome of human bone marrow-derived mesenchymal stromal cells (MSCs) stimulated with intervertebral disc (IVD) conditioned medium was analyzed by proteomic profiling. Depending on the pathological state of the IVD, the MSC secretome protein composition indicated immunomodulatory or anabolic activity of the secretome. These findings may have implications for tailored secretome therapy for the IVD and other tissues.