Objectives: Before being used in clinical practice, a prediction model should be tested in patients whose data were not used in model development. Previously, we developed the ADFICE_IT models for predicting any fall and recurrent falls, referred as Any_fall and Recur_fall. In this study, we externally validated the models and compared their clinical value to a practical screening strategy where patients are screened for falls history alone. Design: Retrospective, combined analysis of 2 prospective cohorts. Setting and Participants: Data were included of 1125 patients (aged ≥65 years) who visited the geriatrics department or the emergency department. Methods: We evaluated the models' discrimination using the C-statistic. Models were updated using logistic regression if calibration intercept or slope values deviated significantly from their ideal values. Decision curve analysis was applied to compare the models’ clinical value (ie, net benefit) against that of falls history for different decision thresholds. Results: During the 1-year follow-up, 428 participants (42.7%) endured 1 or more falls, and 224 participants (23.1%) endured a recurrent fall (≥2 falls). C-statistic values were 0.66 (95% CI 0.63-0.69) and 0.69 (95% CI 0.65-0.72) for the Any_fall and Recur_fall models, respectively. Any_fall overestimated the fall risk and we therefore updated only its intercept whereas Recur_fall showed good calibration and required no update. Compared with falls history, Any_fall and Recur_fall showed greater net benefit for decision thresholds of 35% to 60% and 15% to 45%, respectively. Conclusions and Implications: The models performed similarly in this data set of geriatric outpatients as in the development sample. This suggests that fall-risk assessment tools that were developed in community-dwelling older adults may perform well in geriatric outpatients. We found that in geriatric outpatients the models have greater clinical value across a wide range of decision thresholds compared with screening for falls history alone.@en

Background studies suggest that estimated glomerular filtration rate (eGFR) is less reliable in older persons and that a low serum-creatinine might reflect reduced muscle mass rather than high kidney function. This study investigates the possible relationship between eGFR and multiple elements of physical performance in older fallers. Methods baseline data of the IMPROveFALL-study were examined in participants ≥65 years. Serum-creatinine based eGFR was classified as normal (≥90 ml/min), mildly reduced (60–89 ml/min) or moderately–severely reduced (<60 ml/min). Timed-Up-and-Go-test and Five-Times-Sit-to-Stand-test were used to assess mobility; calf circumference and handgrip strength to assess muscle status. Ancova models adjusted for age, sex, Charlson comorbidity index and body mass index were performed. Results a total of 578 participants were included. Participants with a normal eGFR had lower handgrip strength than those with a mildly reduced eGFR (−9.5%, P < 0.001) and those with a moderately–severely reduced eGFR (−6.3%, P = 0.033) with mean strengths of 23.4, 25.8 and 24.9 kg, respectively. Participants with a normal eGFR had a smaller calf circumference than those with a mildly reduced eGFR (35.5 versus 36.5 cm, P = 0.006). Mean time to complete the mobility tests did not differ. Conclusions in this study we found that older fallers with an eGFR ≥ 90 ml/min had smaller calf circumference and up to 10% lower handgrip strength than those with a reduced eGFR. This lower muscle mass is likely to lead to an overestimation of kidney function. This outcome therefore supports the search for biomarkers independent of muscle mass to estimate kidney function in older persons. @en