Predictors of Falls in Older Adults With and Without Dementia

Persons living with dementia (PLWD) have up to twice the risk for falling and three-times the risk of serious fall-related injuries as those without dementia. Falls are a leading cause of hospitalizations among PLWD, who are more likely to incur high costs and experience negative health consequences (e.g, delirium, in-hospital falls) than persons without dementia. Few studies have examined risk factors for falls comparing Americans with and without dementia. We used data from the 2015 and 2016 rounds of the National Health and Aging Trends Study (n=5,581) to prospectively identify risk factors for a single fall and recurrent (2+) falls over a 12-month period among community-living older adults ≥65 years with and without dementia in a series of bivariate logistic regressions. Overall, we identified fewer predictors of single or recurrent falls among PLWD compared to persons without dementia. For example, socioeconomic indicators (e.g., income, financial hardship) predicted recurrent falls in persons without dementia, but not in PLWD. Among PLWD, falling in the previous year was associated with both single (odds ratio (OR): 3.38, 95% confidence interval (CI): 1.77, 6.49) and recurrent falls (OR: 6.19, 95% CI: 3.50, 10.93). PLWD who experienced recurrent falls were also more likely to be identified as having a fear of falling (OR: 2.17, 95% CI: 1.33, 3.54), physical function impairments, depression symptoms (OR: 2.23, 95% CI: 1.34, 3.71), and anxiety symptoms (OR: 1.73, 95% CI: 1.14, 2.62). Further study of fall-risk factors could inform screening, caregiver education and support, and prevention strategies for PLWD.

The Effects of High-Intensity Interval Training (HIIT) on Fall Risk Factors in Healthy Older Adults: A Systematic Review

High-intensity interval training (HIIT) improves functional capacity, muscle power and physical performance in older adults with and without comorbidities. The aim of this study was to explore the effectiveness of HIIT as a method for reducing major fall risk factors (balance, muscle strength and physical activity) in older adults. A systematic literature search was conducted following the PRISMA guidelines. A computerized search was conducted using electronic databases (PubMed, CINAHL, Cochrane Library, APA PsycInfo, Web of Science, Scopus, PEDro, and AgeLine) published up to July 2021. Eleven papers (9 studies) of moderate quality (mean of 5.5 in Pedro scale) involving 328 healthy older adults met the inclusion criteria. Studies were characterized by high heterogeneity in terms of methodology, HIIT modality and protocol, subject characteristics, and outcome measures. Results indicate that HIIT cannot be recommended as a single modality for fall prevention in older adults due to insufficient data and no consensus among the studies. HIIT appears to be a safe and well-tolerated supplement to proven fall prevention programs, due to its effects on lower limb strength reflected in functional performance tests, and on dynamic balance and subjective balance perception. However, caution is warranted following HIIT, especially after the first session, due to possible temporary instability.

A Case Management Program at Home to Reduce Fall Risk in Older Fallers: A Single-blind Randomized Controlled Trial Protocol (Magic Study) (Preprint)

BACKGROUND Aim: to describe a randomized controlled trial protocol that aims to implement a home multifactorial program for reducing fall risk based on management of risk factors for falls, evaluate its effects on fall risk awareness, rate of falls, economic cost, adherence and satisfaction among older fallers. OBJECTIVE To describe a randomized controlled trial protocol that aims to implement a home multifactorial program for reducing fall risk based on management of risk factors for falls. METHODS This is a single-blind randomized controlled, parallel group trial protocol. Older people with a history of at least two falls in the last year will be divided into 2 groups. Intervention Group will receive a case management at home for reducing risk of falls, including multidimensional assessment, explanation of fall risk factors and elaboration and monitoring of an individualized intervention plan based on the identified fall risk factors, personal preferences and available resources. The Control Group will be monitored once a month. Assessments (clinical data, fall risk awareness, physical and mental factors, safety at home, feet and shoes, risk and rate of falls) will be carried out at baseline, after 16 weeks of intervention and at the post-trial 6-week and 1-year follow-up. After 16 weeks of intervention, satisfaction and adherence to the intervention will also be assessed. Economic health will be evaluated for the period up to the post-trial 1-year follow-up. RESULTS No Results. CONCLUSIONS This case management program will address multifactorial assessments using validated tools and the implementation of individualized intervention plans focused on reducing fall risk factors, and may provide reliable and valuable information about the effectiveness of case management for increasing fall risk awareness and reducing fall risk in older people. CLINICALTRIAL Clinical Trial Registration: REBEC: RBR - 3t85fd

Assessment of risk of falls and internal risk factors in elderly patients who need heart pacemarkers

The aim is to assess the frequency of falls and intrinsic fall risk factors in patients requiring pacemakers. Methodology. The research was conducted from November 2020 to February 2021. Participated patients were hospitalized at the LUHS hospital Kauno Klinikos Department of Cardiology and required heart pacemaker implantation. Total 82 patients participated in the study. The questionnaire was composed by the authors of the research. The study was obtained by the Bioethics Permit of the Medical Academy of LUHS (No. BEC-SL (B) -42). Results. Almost half of the patients fell (45.1%) at least once a year. Elderly patients (65 years and older) are more likely to experience falls than patients under 65 years of age p=0,006. Elderly patients are more often exposed to various internal risk factors of falls: urination at night (82,9 %), weakness (82,9 %), dizziness (76,8 %). Perceived decreased leg muscle strength was found in both women and men (69.6% and 52.8%, respectively, p = 0.002). Patients older than 65 years and therefore <65 years experienced leg pain (54,9% and 7,2%, respectively, p = 0.002), urination at night (68,4% and 14,6%, respectively, p = 0.009), and experienced fatigue (63,0% and 13,6%, p = 0.028). Conclusions. Almost half of the patients who were in need of heart pacemaker implantation experienced falls. ≥ 65 years old patients experienced falls more than once a year. It has been found that these patients often experience weakness, fatigue, and dizziness. A common intrinsic fall risk factor is urination at night. ≥ 65 years old patients have more internal falls risk factors than patients under 65 years old.

Development of an algorithm for assessing fall risk in a Japanese inpatient population

Falling is a representative incident in hospitalization and can cause serious complications. In this study, we constructed an algorithm that nurses can use to easily recognize essential fall risk factors and appropriately perform an assessment. A total of 56,911 inpatients (non-fall, 56,673; fall; 238) hospitalized between October 2017 and September 2018 were used for the training dataset. Correlation coefficients, multivariable logistic regression analysis, and decision tree analysis were performed using 36 fall risk factors identified from inpatients. An algorithm was generated combining nine essential fall risk factors (delirium, fall history, use of a walking aid, stagger, impaired judgment/comprehension, muscle weakness of the lower limbs, night urination, use of sleeping drug, and presence of infusion route/tube). Moreover, fall risk level was conveniently classified into four groups (extra-high, high, moderate, and low) according to the priority of fall risk. Finally, we confirmed the reliability of the algorithm using a validation dataset that comprised 57,929 inpatients (non-fall, 57,695; fall, 234) hospitalized between October 2018 and September 2019. Using the newly created algorithm, clinical staff including nurses may be able to appropriately evaluate fall risk level and provide preventive interventions for individual inpatients.

Sensor-based fall risk assessment in older adults with or without cognitive impairment: a systematic review

Background Higher age and cognitive impairment are associated with a higher risk of falling. Wearable sensor technology may be useful in objectively assessing motor fall risk factors to improve physical exercise interventions for fall prevention. This systematic review aims at providing an updated overview of the current research on wearable sensors for fall risk assessment in older adults with or without cognitive impairment. Therefore, we addressed two specific research questions: 1) Can wearable sensors provide accurate data on motor performance that may be used to assess risk of falling, e.g., by distinguishing between faller and non-faller in a sample of older adults with or without cognitive impairment?; and 2) Which practical recommendations can be given for the application of sensor-based fall risk assessment in individuals with CI? A systematic literature search (July 2019, update July 2020) was conducted using PubMed, Scopus and Web of Science databases. Community-based studies or studies conducted in a geriatric setting that examine fall risk factors in older adults (aged ≥60 years) with or without cognitive impairment were included. Predefined inclusion criteria yielded 16 cross-sectional, 10 prospective and 2 studies with a mixed design. Results Overall, sensor-based data was mainly collected during walking tests in a lab setting. The main sensor location was the lower back to provide wearing comfort and avoid disturbance of participants. The most accurate fall risk classification model included data from sit-to-walk and walk-to-sit transitions collected over three days of daily life (mean accuracy = 88.0%). Nine out of 28 included studies revealed information about sensor use in older adults with possible cognitive impairment, but classification models performed slightly worse than those for older adults without cognitive impairment (mean accuracy = 79.0%). Conclusion Fall risk assessment using wearable sensors is feasible in older adults regardless of their cognitive status. Accuracy may vary depending on sensor location, sensor attachment and type of assessment chosen for the recording of sensor data. More research on the use of sensors for objective fall risk assessment in older adults is needed, particularly in older adults with cognitive impairment. Trial registration This systematic review is registered in PROSPERO (CRD42020171118).