Cognitive Frailty as a Predictor of Future Falls in Older Adults: A Systematic Review and Meta-Analysis

Construction and validation of a nomogram for predicting fear of falling related activity restrictions in community-dwelling older adults

Fear of falling related activity restrictions are widespread among older adults, leading to several adverse effects. Given these consequences, there is an urgent need for a comprehensive assessment tool that integrates various risk factors to predict the likelihood of older adults experiencing such activity restrictions. This cross-sectional study investigated fear of falling related activity restrictions and its influencing factors, simultaneously constructed and validated a nomogram among older adults residing in the communities in China. The model includes variables like age, gender, self-rated health, past year injurious falls, gait stability, anxiety, and cognitive impairment. It showed an AUC of 0.892. Internal validation had an AUC of 0.893, and external validation had an AUC of 0.939. Calibration curve showed good fit, and decision curve showed high clinical benefits. It's an intuitive tool for medical professionals to identify older adults at high risk of activity restrictions due to fear of falling.

Blind Spots in Hospital Fall Prevention: Falls in Stroke Patients Occurred Not Only in Those at a High Risk of Falling

OBJECTIVES

Although the standard falls prevention strategy is to identify and respond to patients with high-risk conditions, it remains unclear whether falls in patients with high fall risk account for most observed falls. In this study, fall risk and number of falls were calculated based on patients' motor and cognitive abilities, and the relationship between the two was examined.

DESIGN

We conducted a retrospective cohort study.

SETTING AND PARTICIPANTS

We included 2518 consecutive patients with stroke who were admitted to a rehabilitation hospital.

METHODS

Data on falls during hospitalization and biweekly assessed Functional Independence Measure scores were retrieved from the medical records. The average Functional Independence Measure scores for the motor and cognitive items were obtained and categorized as complete dependence, modified dependence, and independence. The fall rate (falls/1000 person-days) and number of observed falls in each combined condition were investigated.

RESULTS

Modified dependence on motor ability and complete dependence on cognitive ability had the highest risk of falls, with a fall rate of 10.8/1000 person-days and 51 fall observations, which accounted for 4.3% of all falls. Independent motor and cognitive ability had the lowest risk of falls, a fall rate of 2.6/1000 person-days and 146 observed falls, accounting for 12.4% of all falls, which was 2.8 times higher than the number of falls observed in the highest risk of falls condition.

CONCLUSIONS AND IMPLICATIONS

The combined motor-cognitive ability with the highest risk of falls in stroke inpatients did not have the highest number of observed falls. Rather, the combined motor-cognitive ability with the lowest risk of falls tended to have a high number of observed falls. A different strategy is needed to reduce the total number of falls.

Cross-Lagged Panel Analysis between Physical Frailty, Cognitive Function, and Falls by Sex

OBJECTIVES

This study investigated the reciprocal longitudinal relationships between physical frailty (PF), cognitive function (CF), and falls among community-dwelling older adults, according to sex. The study proposed hypotheses that present PF and CF will affect the occurrence of falls 2 years later.

DESIGN

Secondary data analysis using the first (T1, 2016-2017) and second (T2, 2018-2019) waves of the Korean Frailty and Aging Cohort Study (KFACS).

SETTING AND PARTICIPANTS

A total of 2318 community-dwelling older adults aged 70-84 years in South Korea; mean (SD) age: 75.72 (3.83) years; 47.7% men.

METHODS

PF and CF were measured with the modified version of the Fried Frailty Phenotype and the Korean version of the Mini-Mental State Examination, respectively. The number of falls were assessed. Multigroup cross-lagged panel analysis was used.

RESULTS

The results showed that relationships between PF, CF, and falls were maintained over time through an autoregressive effect. PF at T1 had a statistically significant longitudinal relationship with fall experience at T2 [standardized regression coefficient (β) = 0.087, 95% CI 0.045-0.129; P < .001], and fall experience at T1 had a significant longitudinal relationship with PF at T2 (β = 0.041, 95% CI 0.006-0.076; P = .020). There was no statistically significant relationship between CF and fall experience. PF and CF had statistically significant reciprocal longitudinal relationships (all P < .001). Based on sex, there was a statistically significant longitudinal relationship between fall experience at T1 and PF at T2 for men only (β = 0.063, 95% CI 0.012-0.114; P = .015).

CONCLUSIONS AND IMPLICATIONS

Findings highlight that health care providers should plan fall prevention programs through early intervention for PF improvement along with improvement and maintenance of CF. Specifically, even if older men are currently healthy and have a low risk of falls, it is important to prevent future fatal PF through prior interventions, such as risk activities attention and concerns about falls.

Long-Term Survival of Ischemic Stroke Patients according to Prior Cognitive Status: Dijon Stroke Registry

INTRODUCTION

Understanding the influence of preexisting cognitive impairment on the poststroke outcome is a critical challenge in the context of current aging and growing population. This study aimed to assess long-term survival of patients with acute ischemic stroke (IS) according to their premorbid cognitive status and to identify contributing factors of death.

METHODS

Patients with IS were prospectively identified among residents of Dijon, France, using a population-based registry (2013-2017). The association between case fatality at 5 years and prestroke cognitive status was assessed by multivariable Cox models adjusted for other clinical characteristics and preexisting brain damage on the initial CT scan including leukoaraiosis, old vascular brain lesions, and cortical and central brain atrophy, as well as major arterial occlusion.

RESULTS

1,049 patients were included (mean age ± SD: 76.3 ± 15.2 years old, 54% women). Case fatality rates at 5 years were 38.1% in patients without cognitive impairment, 65.9% in patients with prior mild cognitive impairment (MCI, n = 132, 12.6%), and 86.6% in patients with dementia (n = 164, 15.6%) (p < 0.001). MCI (HR = 1.39; 95% CI: 1.06-1.81, p = 0.016) and dementia (HR = 1.89; 95% CI: 1.45-2.46, p < 0.001) were both independently associated with higher case fatality after adjustment for clinical variables. The association remained significant after further adjustment for preexisting brain damage and major arterial occlusion (HR = 1.47; 95% CI: 1.10-1.98, p = 0.009, for MCI and HR = 1.90; 95% CI: 1.43-2.53, p < 0.001, for dementia) among patients with available data on the CT scan (n = 916). Factors associated with death were roughly similar across groups.

CONCLUSION

This study highlighted a poor long-term survival of IS patients with preexisting cognitive impairment, independently of other contributing factors of death. It is critical to better understand the trajectory of IS patients with preexisting cognitive impairment and to identify prognostic markers to guide clinicians in their management strategies.

Evaluation of Clinical Characteristics and CT Decision Rules in Elderly Patients with Minor Head Injury: A Prospective Multicenter Cohort Study

Age is variably described as a minor or major risk factor for traumatic intracranial lesions after head injury. However, at present, no specific CT decision rule is available for elderly patients with minor head injury (MHI). The aims of this prospective multicenter cohort study were to assess the performance of existing CT decision rules for elderly MHI patients and to compare the clinical and CT characteristics of elderly patients with the younger MHI population. Thirty-day mortality between two age groups (cutoff ≥ 60 years), along with clinical and CT characteristics, was evaluated with four CT decision rules: the National Institute for Health and Care Excellence (NICE) guideline, the Canadian CT Head Rule (CCHR), the New Orleans Criteria (NOC), and the CT Head Injury Patients (CHIP) rule. Of the 5517 MHI patients included, 2310 were aged ≥ 60 years. Elderly patients experienced loss of consciousness (17% vs. 32%) and posttraumatic amnesia (23% vs. 31%) less often, but intracranial lesions (13% vs. 10%), neurological deterioration (1.8% vs. 0.2%), and 30-day mortality (2.0% vs. 0.1%) were more frequent than in younger patients (all p < 0.001). Elderly patients with age as their only risk factor showed intracranial lesions in 5% (NOC and CHIP) to 8% (CCHR and NICE) of cases. The sensitivity of decision rules in the elderly patients was 60% (CCHR) to 97% (NOC) when age was excluded as a risk factor. Current risk factors considered when evaluating elderly patients show lower sensitivity to identify intracranial abnormalities, despite more frequent intracranial lesions. Until age-specific CT decision rules are developed, it is advisable to scan every elderly patient with an MHI.

Association between cognitive frailty and falls among older community dwellers in China: A Chinese longitudinal healthy longevity survey-based study

Background

The combined effect of cognitive impairment (CoI) and frailty on falls is controversial. This study aimed to explore whether older adults with cognitive frailty (CF) were at a higher risk of falls than those with only CoI or frailty and to present a fall prediction model based on CF.

Methods

A total of 4,067 adults aged ≥ 60 years were included from the Chinese Longitudinal Healthy Longevity Survey through face-to-face interviews. Cognitive function and frailty were assessed using the mini-mental state examination scale and frailty index, respectively. Logistic regression was used to determine fall-associated risk factors and develop a fall prediction model. A nomogram was then plotted. The model performance was evaluated using the area under the curve (AUC), concordance index (C-index), and calibration curve. All analyses were performed using SPSS and R statistical packages.

Results

The prevalence of CF and falls were 1.4 and 19.4%, respectively. After adjusting for covariates, the odds ratio of CF, frailty only, and CoI only for falls were 2.27 (95% CI: 1.29-3.97), 1.41 (95% CI: 1.16-1.73), and 0.99 (95% CI: 0.43-2.29), respectively. CF, sex, age, hearing difficulty, depression, anxiety, disability in instrumental activities of daily living, and serious illness in the past 2 years were independently associated with falls. A prediction model based on these factors yielded an AUC of 0.646 and a C-index of 0.641.

Conclusion

Cognitive frailty (CF) exerted a cumulative effect on falls than did CoI or frailty alone. Joint assessments of cognitive function and frailty status may be beneficial for fall risk screening in community. A prediction model using CF as a factor could be helpful for this process.