Shared biological pathways for frailty and cognitive impairment: A systematic review

Cognitive frailty: A comprehensive clinical paradigm beyond cognitive decline

Cognitive frailty is an emerging concept in research and clinical practice that incorporates both physical frailty and mild cognitive impairment (MCI) or subjective cognitive decline (SCD). Unlike traditional approaches that separate physical frailty and dementia, cognitive frailty treats these domains as interrelated and coexisting, with significant implications for clinical outcomes and predicting cognitive decline. Despite growing recognition of this interrelationship, a dualistic view of physical and cognitive processes persists. The paradigm of cognitive frailty holds promise as a biomarker- like amyloid plaques or neurofibrillary tangles- but with the advantage of identifying risk at a prefrail stage, before clinical signs of MCI or dementia emerge. This review examines the pathophysiological and clinical dimensions of cognitive frailty and promotes for its integration into routine assessments in memory clinics.

Predicting cognitive frailty in community-dwelling older adults: a machine learning approach based on multidomain risk factors

Cognitive frailty (CF), a clinical syndrome involving both physical frailty (PF) and impaired cognition (IC), is associated with adverse health outcomes in older adults. This study aimed to identify key predictors of CF and develop a machine learning-based model for CF risk assessment using data from 2404 community-dwelling older adults in the Korean Frailty and Aging Cohort Study (2016-2017). PF was evaluated using Fried frailty phenotype, while IC was assessed using Mini-Mental State Examination (MMSE). Participants exhibiting at least one frailty phenotype and MMSE score ≤ 24 were classified as having CF. A comprehensive analysis encompassing sociodemographic, clinical, and health status characteristics was conducted. A machine learning approach incorporating recursive feature elimination and bootstrapping was employed to develop the prediction model. Among the diverse CF-associated characteristics, the machine learning-based model identified six optimal features (key predictors): motor capacity, education level, physical function limitation, nutritional status, balance confidence, and activities of daily living. The model demonstrated robust predictive performance, achieving an area under the curve of 84.34%, with high sensitivity, specificity, and accuracy. These findings underscore the importance of comprehensive health assessments for early CF detection and demonstrate the potential of predictive modeling in facilitating personalized interventions for at-risk older adults.

Association of Cognitive Frailty With Subsequent All-Cause Mortality Among Middle-Aged and Older Adults in 17 Countries

OBJECTIVES

Cognitive frailty refers to the co-occurrence of cognitive impairment and frailty without concurrent Alzheimer's disease or dementia. Studies of cognitive frailty and mortality have been limited to single country or older people. However, frailty and cognitive decline may occur much earlier. We aimed to examine the association between different cognitive frailty status and subsequent all-cause mortality among middle-aged and older people in 17 countries.

METHODS

Participants aged 50 and over were drawn from six prospective cohorts of aging. We classified participants according to their cognitive impairment and frailty status into the following groups: none, only cognitive impairment, only frailty and cognitive frailty. Competing-risks regression models were used to evaluate the association of different cognitive frailty status at baseline with subsequent all-cause mortality.

RESULTS

The cognitive frailty group had a higher mortality risk compared to those without cognitive impairment and frailty groups. Meta-analysis results showed participants with cognitive frailty (pooled subhazard ratio [SHR] = 2.34, 95% confidence interval [CI]: 2.01-2.72, I2 = 68.0%) had a higher mortality risk compared with those with only cognitive impairment status (pooled SHR = 1.36, 95% CI: 1.25-1.48, I2 = 3.0%) or only frailty status (pooled SHR = 1.83, 95% CI: 1.72-1.95, I2 = 31.0%). The association between cognitive frailty and mortality were stronger among those who were aged 70 years and older, males, single and nonconsumers of alcohol.

CONCLUSIONS

Cognitive frailty, frailty or cognitive impairment alone, is associated with an increased risk of all-cause mortality in Asian, European and American countries. Physical and cognitive function screening should be conducted as early as possible in middle-aged and older people, and targeted intervention approaches should be developed to reduce the incidence of adverse health outcomes.

Interocular retinal asymmetry and cognitive frailty: A prospective cohort study

INTRODUCTION

The retinal nerve fiber layer (RNFL) or ganglion cell-inner plexiform layer (GC-IPL) is associated with cognitive impairment. However, the relationship between retinal asymmetry and cognitive frailty (CF) remains unknown.

METHODS

Two hundred twenty-two community-dwelling older adults were assessed starting in 2015 and underwent biennial cognitive and frailty evaluations until 2022. Retinal asymmetry was defined as the absolute interocular retinal difference. Generalized linear mixed models estimated the risk of CF over time.

RESULTS

Among the participants, 158 completed the 4-year follow-up. Greater baseline GC-IPL asymmetry was associated with worsening CF over time (adjusted odds ratio = 1.06; 95% confidence interval [CI] = 1.03, 1.10), with handgrip strength asymmetry significantly modifying this association (pinteraction = 0.02). GC-IPL asymmetry was associated with cognitive impairment (β ̂ $\hat{\beta }$ = -1.69 × 10-2; 95% CI = -3.13 × 10-2, -0.25 × 10-2) but not with physical frailty. RNFL showed no significant association with CF.

DISCUSSION

Interocular GC-IPL asymmetry might be a new biomarker for CF in older adults.

HIGHLIGHTS

Interocular ganglion cell-inner plexiform layer (GC-IPL) asymmetry was associated with impaired memory-frailty, with handgrip strength asymmetry significantly modifying this association. Interocular GC-IPL asymmetry was associated with cognitive impairment. Interocular retinal asymmetry might be a structural biomarker of cognitive frailty.

Multimorbidity and Depression Increase Prevalence of Frailty of Community-dwelling Indonesian Older Adults: Indonesia Care Networks Study

Background

Older adults with frailty have an increased risk of multiple negative health outcomes, such as disability, falls, and morbidity when exposed to physical stressors. The present study investigated the prevalence of frailty and associated risk factors among community-dwelling Indonesian older adults in several districts in Jakarta, Indonesia.

Methods

This cross-sectional study was done in several urban villages in Jakarta, Indonesia. It involved community-dwelling Indonesian older adults aged 60 and over. Sociodemographic and multiple health data were assessed and measured by a trained interviewer. Frailty was evaluated using Fried's criteria.

Results

The data analysis found a 14.7% prevalence of frailty among 518 participants. Multivariate analysis showed that frailty was independently associated with females (OR 3.62, 95% CI: 1.73-7.55), having multimorbidity (OR 2.01, 95% CI: 1.21-3.35), and clinical depression (OR 2.13, 95% CI: 1.24-3.65).

Conclusions

Early interventions in younger older adults, especially women in their early 50s or 60s, might decrease frailty risk over age 60. Controlling chronic disease and better mental education and support to reduce depression risk could reduce frailty risk.

Frailty increases depression risk independently of cognitive decline: Insights from Mendelian randomization and cross-sectional analysis

BACKGROUND

Frailty, cognitive decline, and depression are common syndromes among the elderly and are closely interconnected. However, it is still unclear whether the impact of frailty on depression depends on the role of cognitive decline.

METHOD

We conducted the Mendelian randomization (MR) analysis based on the instrumental variables (IVs) from the genome-wide association study (GWAS) databases, and we also performed a cross-sectional study consisting of 1362 older adults aged ≥65 for validation.

RESULTS

The results of the multivariable MR analysis showed that frailty significantly increased the risk of depression, even after controlling for the influence of cognitive performance. Conversely, after controlling for frailty, the effect of cognitive performance on depression risk was noticeably reduced. In the cross-sectional study, frailty mediated 24.04 % of the relationship between cognition and depression, and cognition mediated 7.63 % of the relationship between frailty and depression.

CONCLUSIONS

We provide evidence that frailty could increase depression risk independently of cognitive decline. Further research with a larger sample size is necessary.

Understanding exogenous factors and biological mechanisms for cognitive frailty: A multidisciplinary scoping review

Cognitive frailty (CF) is the conjunction of cognitive impairment without dementia and physical frailty. While predictors of each element are well-researched, mechanisms of their co-occurrence have not been integrated, particularly in terms of relationships between social, psychological, and biological factors. This interdisciplinary scoping review set out to categorise a heterogenous multidisciplinary literature to identify potential pathways and mechanisms of CF, and research gaps. Studies were included if they used the definition of CF OR focused on conjunction of cognitive impairment and frailty (by any measure), AND excluded studies on specific disease populations, interventions, epidemiology or prediction of mortality. Searches used Web of Science, PubMed and Science Direct. Search terms included "cognitive frailty" OR (("cognitive decline" OR "cognitive impairment") AND (frail*)), with terms to elicit mechanisms, predictors, causes, pathways and risk factors. To ensure inclusion of animal and cell models, keywords such as "behavioural" or "cognitive decline" or "senescence", were added. 206 papers were included. Descriptive analysis provided high-level categorisation of determinants from social and environmental through psychological to biological. Patterns distinguishing CF from Alzheimer's disease were identified and social and psychological moderators and mediators of underlying biological and physiological changes and of trajectories of CF development were suggested as foci for further research.

Factors associated with frailty in older people: an umbrella review

BACKGROUND

The number of frail older people is increasing worldwide, and all countries will be confronted with their growing needs for healthcare and social support. The aim of this umbrella review was to summarize the evidence on the factors associated with frailty in older people, using a socioecological approach.

METHODS

PubMed (MEDLINE), Scopus, Web of Science, ScienceDirect, Hinari (research4life), and the Trip database were systematically searched up to April 2023. Systematic reviews of observational studies that explored factors associated with frailty in older adults aged 60 years and over were considered for inclusion. No language, geographical or setting restrictions were applied. However, we excluded systematic reviews that investigated frailty factors in the context of specific diseases. The Joanna Briggs Institute Critical Appraisal Checklist for Systematic Reviews and Research Syntheses and the ROBIS tool were used to assess the quality and risk of bias in the included studies.

RESULTS

Forty-four systematic reviews were included, covering 1,150 primary studies with approximately 2,687,911 participants overall. Several risk factors, protective factors and biomarkers were found to be associated with frailty, especially in community-dwelling older people, including 67 significant associations from meta-analyses. The certainty of the evidence was rated as moderate or reached moderate levels for seven factors relevant to older people. These factors include depression (OR 4.66, 95% CI 4.07 to 5.34), loneliness (OR 3.51, 95% CI 2.70 to 4.56), limitations in activities of daily living (OR 2.59, 95% CI 1.71 to 3.48), risk of malnutrition (OR 3.52, 95% CI 2.96 to 4.17), Dietary Inflammatory Index score (OR 1.24, 95% CI 1.16 to 1.33), maximal walking speed (Standardized Mean Difference (SMD) -0.97, 95% CI -1.25 to -0.68), and self-reported masticatory dysfunction (OR 1.83, 95% CI 1.55 to 2.18). Additionally, only greater adherence to a Mediterranean diet showed a high level of evidence (OR 0.44, 95% CI 0.31 to 0.64).

CONCLUSIONS

This umbrella review will provide guidance for prevention strategies and clinical practice by promoting healthy lifestyles and addressing all modifiable risk factors associated with frailty. Future systematic reviews should consider heterogeneity and publication bias, as these were the main reasons for downgrading the level of evidence in our review.

REGISTRATION

PROSPERO 2022, CRD42022328902.

Definition and assessment of psychological frailty in older adults: A scoping review

OBJECTIVES

The confusion surrounding psychological frailty and its components prompts the need for a standardized conceptual definition. To address this, we aimed to (1) identify the psychological variables included in multicomponent frailty assessment instruments used with older adults and examine their operationalization; and (2) formulate a thorough conceptualization of psychological frailty based on the variables identified.

METHODS

This study followed the most recent recommendations for conducting scoping reviews and is reported in accordance with PRISMA-ScR guidelines. We systematically searched the CINAHL, MEDLINE, PsycInfo, Scopus, and Web of Science databases, with additional searches in Google Scholar and reference lists.

RESULTS

Sixteen instruments were identified. The results suggested that: (1) In multicomponent frailty assessment instruments, psychological variables are poorly represented; (2) A wide variety of psychological variables are included in the instruments, the most frequent being cognitive functioning and affective functioning (e.g., depressive symptoms, emotional loneliness, anxiety symptoms, poor coping, and suicidal ideation); and (3) The way in which variables are referred to and operationalized varies across instruments.

CONCLUSIONS

Including both cognitive and affective variables in psychological frailty assessments may lead to inaccuracies. We suggest distinguishing between two separate dimensions within psychological frailty: cognitive frailty and affective frailty. A conceptual definition for each dimension is provided. This proposal aims to advance the debate regarding the conceptualization and assessment of psychological frailty, with further research and discussion needed to ensure its practical applicability.

Dissecting the shared genetic architecture between Alzheimer's disease and frailty: a cross-trait meta-analyses of genome-wide association studies

Introduction: Frailty is the most common medical condition affecting the aging population, and its prevalence increases in the population aged 65 or more. Frailty is commonly diagnosed using the frailty index (FI) or frailty phenotype (FP) assessments. Observational studies have indicated the association of frailty with Alzheimer's disease (AD). However, the shared genetic and biological mechanism of these comorbidity has not been studied. Methods: To assess the genetic relationship between AD and frailty, we examined it at single nucleotide polymorphism (SNP), gene, and pathway levels. Results: Overall, 16 genome-wide significant loci (15 unique loci) (p meta-analysis < 5 × 10-8) and 22 genes (21 unique genes) were identified between AD and frailty using cross-trait meta-analysis. The 8 shared loci implicated 11 genes: CLRN1-AS1, CRHR1, FERMT2, GRK4, LINC01929, LRFN2, MADD, RP11-368P15.1, RP11-166N6.2, RNA5SP459, and ZNF652 between AD and FI, and 8 shared loci between AD and FFS implicated 11 genes: AFF3, C1QTNF4, CLEC16A, FAM180B, FBXL19, GRK4, LINC01104, MAD1L1, RGS12, ZDHHC5, and ZNF521. The loci 4p16.3 (GRK4) was identified in both meta-analyses. The colocalization analysis supported the results of our meta-analysis in these loci. The gene-based analysis revealed 80 genes between AD and frailty, and 4 genes were initially identified in our meta-analyses: C1QTNF4, CRHR1, MAD1L1, and RGS12. The pathway analysis showed enrichment for lipoprotein particle plasma, amyloid fibril formation, protein kinase regulator, and tau protein binding. Conclusion: Overall, our results provide new insights into the genetics of AD and frailty, suggesting the existence of non-causal shared genetic mechanisms between these conditions.

Inflammatory Markers Associated with Physical Frailty and Cognitive Impairment

In older adults, physical frailty and cognitive impairment contribute to adverse outcomes. However, the research on mechanisms underlying physical frailty and cognitive impairment is limited. Low-grade chronic inflammation is a characteristic of aging. Particularly, an imbalance in pro- and anti-inflammatory mechanisms may be involved in frailty and neurodegenerative disorders. Therefore, exploring the inflammatory markers of physical frailty and cognitive impairment is crucial to fully understanding these mechanisms and establishing a substantial link between these two disorders. Notably, few studies have focused on exploring inflammatory markers in both physical frailty and cognitive impairment, posing a major challenge in elucidating the link between them. Therefore, substantial efforts are required for the better prevention of physical frailty and cognitive impairment. In this review, we explored the role of inflammatory markers as a potential link between frailty and cognitive impairment.

Moving towards the detection of frailty with biomarkers: A population health study

Aging adults experience increased health vulnerability and compromised abilities to cope with stressors, which are the clinical manifestations of frailty. Frailty is complex, and efforts to identify biomarkers to detect frailty and pre-frailty in the clinical setting are rarely reproduced across cohorts. We developed a predictive model incorporating biological and clinical frailty measures to identify robust biomarkers across data sets. Data were from two large cohorts of older adults: "Invecchiare in Chianti (Aging in Chianti, InCHIANTI Study") (n = 1453) from two small towns in Tuscany, Italy, and replicated in the Atherosclerosis Risk in Communities Study (ARIC) (n = 6508) from four U.S. communities. A complex systems approach to biomarker selection with a tree-boosting machine learning (ML) technique for supervised learning analysis was used to examine biomarker population differences across both datasets. Our approach compared predictors with robust, pre-frail, and frail participants and examined the ability to detect frailty status by race. Unique biomarker features identified in the InCHIANTI study allowed us to predict frailty with a model accuracy of 0.72 (95% confidence interval (CI) 0.66-0.80). Replication models in ARIC maintained a model accuracy of 0.64 (95% CI 0.66-0.72). Frail and pre-frail Black participant models maintained a lower model accuracy. The predictive panel of biomarkers identified in this study may improve the ability to detect frailty as a complex aging syndrome in the clinical setting. We propose several concrete next steps to keep research moving toward detecting frailty with biomarker-based detection methods.

Biological and Physical Performance Markers for Early Detection of Cognitive Impairment in Older Adults

Dementia is a major cause of poor quality of life, disability, and mortality in old age. According to the geroscience paradigm, the mechanisms that drive the aging process are also involved in the pathogenesis of chronic degenerative diseases, including dementia. The dissection of such mechanisms is therefore instrumental in providing biological targets for interventions and new sources for biomarkers. Within the geroscience paradigm, several biomarkers have been discovered that can be measured in blood and that allow early identification of individuals at risk of cognitive impairment. Examples of such markers include inflammatory biomolecules, markers of neuroaxonal damage, extracellular vesicles, and DNA methylation. Furthermore, gait speed, measured at a usual and fast pace and as part of a dual task, has been shown to detect individuals at risk of future dementia. Here, we provide an overview of available biomarkers that may be used to gauge the risk of cognitive impairment in apparently healthy older adults. Further research should establish which combination of biomarkers possesses the highest predictive accuracy toward incident dementia. The implementation of currently available markers may allow the identification of a large share of at-risk individuals in whom preventive interventions should be implemented to maintain or increase cognitive reserves, thereby reducing the risk of progression to dementia.

Application of the (fr)AGILE scale in the evaluation of multidimensional frailty in elderly inpatients from internal medicine wards: a cross-sectional observational study

Background

With the rapid growth of an aging global population and proportion, the prevalence of frailty is constantly increasing. Therefore, finding a frailty assessment tool suitable for clinical application by physicians has become the primary link in the comprehensive management of frailty in elderly patients. This study used the (fr)AGILE scale to investigate the frailty status of elderly patients from internal medicine wards and identified relevant factors that affect the severity of frailty.

Method

In this study, 408 elderly inpatients in internal medicine departments of Qilu Hospital of Shandong University from May 2021 to August 2022 were enrolled as research subjects, and a cross-sectional observational study was conducted. Researchers evaluated the frailty based on the (fr)AGILE scale score. The general condition, past medical history, physical examination, laboratory examination, nutrition control score, intervention and treatment measures and other elderly patient information was collected. Logistic regression analysis was used to analyze the relevant factors that affect the severity of frailty and hospitalization costs.

Results

According to the (fr)AGILE scale score, the elderly patients were divided into groups to determine whether they were frail and the severity of the frailty. Among them, 164 patients were in the prefrailty stage, which accounted for 40.2%. There were 188 cases of mild frailty that accounted for 46.1%, and 56 cases of moderate to severe frailty that accounted for 13.7%. Decreased grip strength, elevated white blood cell levels, and low sodium and potassium are independent risk factors affecting the severity of frailty. As the severity of frailty increases, the proportion of sodium, potassium, albumin supplementation as well as anti-infection gradually increases.

Conclusion

Frailty is a common elderly syndrome with a high incidence among elderly patients in internal medicine departments. The main manifestations of frailty vary with different severity levels. Inflammation, anemia, and poor nutritional status can lead to an increase in the severity of frailty as well as blood hypercoagulability, myocardial damage, and additional supportive interventions. This ultimately leads to prolonged hospitalization and increased hospitalization costs.

Navigating and diagnosing cognitive frailty in research and clinical domains

While physical frailty has been recognized as a clinical entity for some time, the concept of cognitive frailty (CF) is now gaining increasing attention in the geriatrics research community. CF refers to the co-occurrence of physical frailty and cognitive impairment in older adults, which has been suggested as a potential precursor to both dementia and adverse physical outcomes. However, this condition represents a challenge for researchers and clinicians, as there remains a lack of consensus regarding the definition and diagnostic criteria for CF, which has limited its utility. Here, using insights from both the physical frailty literature and cognitive science research, we describe emerging research on CF. We highlight areas of agreement as well as areas of confusion and remaining knowledge gaps, and provide our perspective on fine-tuning the current construct, aiming to stimulate further discussion in this developing field.

Risk Factors and Prediction Nomogram of Cognitive Frailty with Diabetes in the Elderly

Purpose

Diabetes is a well-recognized risk factor for cognitive frailty. This study aimed to investigate the influencing factors of cognitive frailty in elderly patients with diabetes and develop a nomogram for its assessment.

Methods

We collected the clinical data of diabetic patients aged 60 years or older and the patients were divided into training and validation cohorts at a ratio of 7:3. In the training cohort, logistic regression was used to screen out the influencing factors of cognitive frailty in elderly diabetic patients, and a risk prediction model and nomogram were constructed and verified in the validation cohort. The performance of the model was evaluated using various measures, including the area under the receiver operating characteristic curve, calibration curve, Hosmer-Lemeshow test and decision curve analysis.

Results

A total of 315 elderly diabetic patients were included, of which 87 (27.6%) patients had cognitive frailty. Age, albumin levels, calf circumference, duration of diabetes, intellectual activity, and depressive state were identified as independent risk factors for cognitive frailty in older patients with diabetes (P < 0.05). The training cohort and validation cohort demonstrated area under curve (AUC) values of 0.866 and 0.821, respectively.

Conclusion

Older patients with diabetes have a higher prevalence of cognitive frailty. The nomogram model exhibited satisfactory calibration and identification, providing a reliable tool for assessing the risk of cognitive frailty in individuals with diabetes.

A genome-wide association study of frailty identifies significant genetic correlation with neuropsychiatric, cardiovascular, and inflammation pathways

Frailty is an aging-related clinical phenotype defined as a state in which there is an increase in a person's vulnerability for dependency and/or mortality when exposed to a stressor. While underlying mechanisms leading to the occurrence of frailty are complex, the importance of genetic factors has not been fully investigated. We conducted a large-scale genome-wide association study (GWAS) of frailty, as defined by the five criteria (weight loss, exhaustion, physical activity, walking speed, and grip strength) captured in the Fried Frailty Score (FFS), in 386,565 European descent participants enrolled in the UK Biobank (mean age 57 [SD 8] years, 208,481 [54%] females). We identified 37 independent, novel loci associated with the FFS (p < 5 × 10-8), including seven loci without prior described associations with other traits. The variants associated with FFS were significantly enriched in brain tissues as well as aging-related pathways. Our post-GWAS bioinformatic analyses revealed significant genetic correlations between FFS and cardiovascular-, neurological-, and inflammation-related diseases/traits, and subsequent Mendelian Randomization analyses identified causal associations with chronic pain, obesity, diabetes, education-related traits, joint disorders, and depressive/neurological, metabolic, and respiratory diseases. The GWAS signals were replicated in the Health and Retirement Study (HRS, n = 9,720, mean age 73 [SD 7], 5,582 [57%] females), where the polygenic risk score built from UKB GWAS was significantly associated with the FFS in HRS individuals (OR per SD of the score 1.27, 95% CI 1.22-1.31, p = 1.3 × 10-11). These results provide new insight into the biology of frailty by comprehensively evaluating its genetic architecture.

Malnutrition, Depression, Poor Sleep Quality, and Difficulty Falling Asleep at Night Are Associated with a Higher Risk of Cognitive Frailty in Older Adults during the COVID-19 Restrictions

The COVID-19 restrictions, such as social isolation and disruption of daily routines, can have detrimental effects, including increased stress, anxiety, sleep disturbance, and physical and cognitive decline among older adults. This study aimed to examine the association between nutritional status, depression, sleep quality, falling asleep at night, and cognitive frailty (CF) among older Thai adults during the COVID-19 pandemic. This cross-sectional study included 408 older adults with an average age of 70.54 (5.49) years. CF was determined using Fried's frailty phenotype and the Montreal Cognitive Assessment Basic. The Mini Nutritional Assessment-Short Form, Pittsburgh Sleep Quality Index, and geriatric depression assessment were used for assessment. Multiple logistic regression analysis demonstrated that participants who were malnourished (OR 3.786; 95%CI 1.719-8.335), depressed (OR 5.003; 95%CI 2.399-10.434), had poor sleep quality (OR 1.613; 95%CI 1.041-2.500), and engaged in difficulty falling asleep (OR 1.809; 95%CI 1.022-3.203) had a higher risk of CF compared to those who did not exhibit these factors. Therefore, malnutrition, depression, poor sleep quality, and difficulty falling asleep were identified as risk factors for CF among older adults in Thailand linked to the impact of the COVID-19 pandemic. It is crucial to develop interventions to prevent CF resulting from the mentioned variables.

Cognitive and physical impairment in spinal cord injury: A scoping review and call for new understanding

Study Design: Scoping review.Objective: To examine potential underlying mechanisms of cognitive and physical impairment in patients with spinal cord injury and identify current research gaps.Methods: A scoping review of the literature was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension for scoping reviews to identify primary studies that explored mechanisms of cognitive and/or physical impairment after spinal cord injury. The databases searched were PubMed/MEDLINE, EMBASE (OVID), Cumulative Index to Nursing and Allied Health Literature (CINAHL; EBSCO), Web of Science, Scopus, and PsycInfo. These databases were searched from inception through December 20, 2021.Results: Accumulating research suggests that neuroinflammation and neurodegeneration after a traumatic event may be possible mechanisms for cognitive impairment among patients with SCI. In addition, lack of physical activity due to impaired mobility is associated with an increased risk of cognitive impairment.Conclusion: While the results establish a foundation for understanding how cognitive impairment, mental health, and physical function independently affect patients with SCI, further research is warranted to understand how these factors systemically impact the patient and discover refined targets for future rehabilitation therapies. Studies should also explore potential predisposing factors for the relationship between cognitive and physical impairment among patients with SCI.

Blood pressure and dementia risk by physical frailty in the elderly: a nationwide cohort study

BACKGROUND

Midlife hypertension has been recognized as a modifiable risk factor for dementia, but association between blood pressure (BP) in late life and dementia has been inconclusive. In addition, few studies have investigated effects of BP control on dementia incidence in the frail elderly. Thus, this study aimed to investigate the association of BP and dementia incidence with concomitant consideration of physical frailty in the young elderly population.

METHODS

Using the Korean National Health Information Database, we identified 804,024 subjects without history of dementia at age 66. Dementia diagnosis was defined with prescription records of anti-dementia drugs and dementia-related diagnostic codes. Physical frailty was measured using the Timed Up and Go test. Association of BP and dementia incidence with concomitant consideration of physical frailty was investigated using Cox hazards analyses.

RESULTS

The risks of Alzheimer's and vascular dementia increased from systolic BP ≥ 160 and 130-139 mmHg, respectively; a significant association of dementia incidence with low BP was not observed. In the analyses stratified by the physical frailty status, low BP was not associated with increased risks of dementia within the groups both with and without physical frailty.

CONCLUSIONS

High BP was associated with increased risks of dementia, especially for vascular dementia, while low BP was not associated with increased risks of any type of dementia in young elderly people, even in those with physical frailty. This study suggests the need for tight BP control in young elderly people, irrespective of frailty status, to prevent dementia and supports the current clinical guidelines of hypertension treatment.

Depressive Symptoms Partially Mediate the Association of Frailty Phenotype Symptoms and Cognition for Females but Not Males

OBJECTIVES

We aimed to evaluate whether depressive symptoms mediated the relationship between frailty phenotype and cognitive function by sex.

METHODS

Data came from the Health and Retirement Study from 2012-2016. The outcome was measured by Fried's frailty criteria, our outcome was continuous global cognition, and mediator was depressive symptoms. We used mediation analysis, stratified by sex, to estimate the direct and indirect effects of frailty symptoms on cognition mediated by depressive symptoms.

RESULTS

Males had a larger total effect (β= -0.43; 95% CI: -0.66, -0.02) for lower cognitive score for each increase in frailty symptom compared to females (β= -0.28; 95% CI: -0.47, -0.08). A significant indirect effect from frailty phenotype to cognition was found through depressive symptoms for females but not males.

CONCLUSION

These results highlight the importance of identifying individuals with frailty and depressive symptoms to monitor and provide interventions to preserve cognitive function.

Status of cognitive frailty in elderly patients with chronic kidney disease and construction of a risk prediction model: a cross-sectional study

OBJECTIVE

To investigate the risk factors of cognitive frailty in elderly patients with chronic kidney disease (CKD), and to establish an artificial neural network (ANN) model.

DESIGN

A cross-sectional design.

SETTING

Two tertiary hospitals in southern China.

PARTICIPANTS

425 elderly patients aged ≥60 years with CKD.

METHODS

Data were collected via questionnaire investigation, anthropometric measurements, laboratory tests and electronic medical records. The 425 samples were randomly divided into a training set, test set and validation set at a ratio of 5:3:2. Variables were screened by univariate and multivariate logistic regression analyses, then an ANN model was constructed. The accuracy, specificity, sensitivity, receiver operating characteristic (ROC) curve and area under the ROC curve (AUC) were used to evaluate the predictive power of the model.

RESULTS

Barthel Index (BI) score, albumin, education level, 15-item Geriatric Depression Scale score and Social Support Rating Scale score were the factors influencing the occurrence of cognitive frailty (p<0.05). Among them, BI score was the most important factor determining cognitive frailty, with an importance index of 0.30. The accuracy, specificity and sensitivity of the ANN model were 86.36%, 88.61% and 80.65%, respectively, and the AUC of the constructed ANN model was 0.913.

CONCLUSION

The ANN model constructed in this study has good predictive ability, and can provide a reference tool for clinical nursing staff in the early prediction of cognitive frailty in a high-risk population.

Association of Obesity with Cognitive Impairment and Depression among Oldest Old Population having Frailty syndrome

Objectives

The objectives were to estimate prevalence of obesity among frail individuals aged ≥80 years and examine the association of obesity with cognitive impairment and depression among frail individuals aged ≥80 years.

Methods

Two-hundred community-dwelling participants aged ≥80 years, were enrolled; 166 frail participants were further analyzed. Obesity and adiposity were determined by Body Mass Index (BMI), Waist Circumference (WC) and Body Fat Percentage (BF%). Cognitive impairment and Depression were assessed using Mini Mental State Examination (MMSE) and Geriatric Depression Scale (GDS-15). Frailty was assessed by Fried criteria. Chi-Square, t-test, trend-analysis and Logistic Regression (LR) were done.

Results

Obesity among Frail individuals aged ≥80 years was 40% using BMI and 73.2% using WC. Obesity was inversely associated with cognitive impairment and depression among frail individuals. Severity of cognitive impairment and depression was lower among obese frail than non-obese frail. Trend-analysis showed decreasing cognitive impairment and depression with increasing BF%. On LR, obesity among frail individuals had inverse association with cognitive impairment and depression.

Conclusion

Obesity among frail individuals aged ≥80 years was associated with lower odds of cognitive impairment and depression in our population. Positive effects of weight gain in oldest old frail individuals and development of cognitive impairment and dementia should be explored in further researches.

Association between frailty and cognitive function in older Chinese people: A moderated mediation of social relationships and depressive symptoms

BACKGROUND

To date, few studies have focused on examining either the direct or indirect effect of physical frailty on cognitive impairment. This study aimed to investigate the moderating effects of social relationships, including their individual components in the role of depressive symptoms as a mediator between frailty and cognitive impairment.

METHODS

This study included a total of 7525 Chinese older adults from the 2017-2018 wave of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Mediation analyses and moderated mediation effect analysis fully adjusted for all potential confounding factors were conducted.

RESULTS

Significant correlations were found between frailty, depression, social relationships, and cognitive function. Depression partially mediated the association of frailty with cognitive function [B = -0.198; 95 % confidence interval (CI): (-0.258, -0.143)]. Social relationships moderated the effect of frailty on cognitive function through both path b (depression-cognitive function) [B = 0.137; 95 % CI: (0.045, 0.230)], and path c' (frailty-cognitive function) [B = 0.870; 95 % CI: (0.562, 1.178)]. In addition, social activities and social networks moderated both the direct and indirect effect of the moderated mediation model. Social support only moderated the direct effect.

LIMITATIONS

The cross-sectional design of this study precludes any conclusion from the results as to the causality of cognitive impairment.

CONCLUSIONS

Social relationships moderated both the direct and indirect effects of depressive symptoms on the association between frailty and cognitive impairment. The findings suggest that interventions, such as paying attention to the mental health of old people and improving the quality of social relationships, may help break the link between frailty and cognitive impairment.

Impact of frailty, mild cognitive impairment and cognitive frailty on adverse health outcomes among community-dwelling older adults: A systematic review and meta-analysis

Aims

This study analyzes the impact of frailty, mild cognitive impairment, and cognitive frailty on adverse outcomes in community-dwelling older adults.

Methods

This systematic review and meta-analysis were conducted using the PRISMA guidelines and MOOSE statement. We developed a specific search strategy for each electronic database and searched PubMed, Web of Science, MEDLINE, and Embase from initial records to July 2021. The studies on adverse outcomes of frailty, pre-frailty, mild cognitive impairment, and mild cognitive impairment with pre-frailty and cognitive frailty were included. Two researchers independently extracted data based on a spreadsheet and assessed the risk of bias. The primary outcomes were mortality, dementia, disability, and hospitalization. The second outcome included quality of life and falls. All analysis was conducted by using Review Manager (RevMan) 5.3 software.

Results

A total of 22 cohort studies (71,544 older adults with mean age ranging from 65.1 to 93.6 years) were included with a low risk of bias and high methodological quality with a NOS score ≥7. Compared to robust elders, individuals identified as frailty were associated with a higher risk of mortality (RR = 2.11, 95% CI: 1.57–2.83) and disability (RR = 5.91, 95% CI: 2.37–14.74). Mild cognitive impairment with pre-frailty was associated with mortality (RR = 1.74, 95% CI: 1.48–2.05) and dementia (RR = 4.15, 95% CI: 1.87–9.20). Pre-frailty was associated with a higher risk of mortality (RR = 1.29, 95% CI: 1.11–1.50). Cognitive frailty was associated with higher risk of incident mortality (RR = 2.41, 95% CI: 1.97–2.94), dementia (RR = 3.67, 95% CI: 2.81–4.78), disability (RR = 11.32, 95% CI: 4.14–30.97), and hospitalization (RR = 2.30, 95% CI: 1.60–3.32), as well as poor quality of life.

Conclusion

Cognitive frailty could be a comprehensive psychosomatic predictor for adverse outcomes among older people. Interactions between frailty, mild cognitive impairment, and cognitive frailty on adverse outcomes must be further explored.

Systematic review registration

[https://inplasy.com/inplasy-2022-5-0064/], identifier [INPLASY202250064].

Longitudinal Relationship Between Frailty and Cognitive Impairment in Chinese Older Adults: A Prospective Study

We aimed to examine the longitudinal association between frailty and cognitive impairment in the older Chinese population. This prospective cohort study used data from the Chinese Longitudinal Healthy Longevity Study 2011 wave. We calculated the follow-up duration as 3 years from the baseline year. Frailty was measured using the frailty index, and cognitive function was calculated by Mini-Mental State Examination Scale. Participants who were non-frailty and those with normal cognitive function were included in 2011 and followed up in 2014, respectively. Frailty was an independent risk factor for early-onset cognitive impairment. Age, hearing impairment, and a decreased ability to perform daily activities were the main risk factors for cognitive impairment, while affluent economic status was a protective factor. Cognitive impairment was not found to be an independent risk factor for frailty. We concluded that the frailty index is a significant predictor of cognitive impairment among community-dwelling older adults.

Biomarkers of Frailty: miRNAs as Common Signatures of Impairment in Cognitive and Physical Domains

The past years have seen an increasing concern about frailty, owing to the growing number of elderly people and the major impact of this syndrome on health and social care. The identification of frail people passes through the use of different tests and biomarkers, whose concerted analysis helps to stratify the populations of patients according to their risk profile. However, their efficiency in prognosis and their capability to reflect the multisystemic impairment of frailty is discussed. Recent works propose the use of miRNAs as biological hallmarks of physiological impairment in different organismal districts. Changes in miRNAs expression have been described in biological processes associated with phenotypic outcomes of frailty, opening intriguing possibilities for their use as biomarkers of fragility. Here, with the aim of finding reliable biomarkers of frailty, while considering its complex nature, we revised the current literature on the field, for uncovering miRNAs shared across physical and cognitive frailty domains. By applying in silico analyses, we retrieved the top-ranked shared miRNAs and their targets, finally prioritizing the most significant ones. From this analysis, ten miRNAs emerged which converge into two main biological processes: inflammation and energy homeostasis. Such markers, if validated, may offer promising capabilities for early diagnosis of frailty in the elderly population.

Brain structural alterations and clinical features of cognitive frailty in Japanese community-dwelling older adults: the Arao study (JPSC-AD)

Cognitive frailty (CF) is a clinical condition defined by the presence of both mild cognitive impairment (MCI) and physical frailty (PF). Elderly with CF are at greater risk of dementia than those with MCI or PF alone, but there are few known clinical or neuroimaging features to reliably distinguish CF from PF or MCI. We therefore conducted a population-based cross-sectional study of community elderly combining physical, cognitive, neuropsychiatric, and multisequence magnetic resonance imaging (MRI) evaluations. The MRI evaluation parameters included white matter (WM) lesion volumes, perivascular and deep subcortical WM lesion grades, lacunar infarct prevalence, microbleed number, and regional medial temporal lobe (MTL) volumes. Participants were divided into 4 groups according to the presence or absence of MCI and PF-(1) no MCI, PF (n = 27); (2) no PF, MCI (n = 119); (3) CF (MCI + PF) (n = 21), (4) normal controls (n = 716). Unique features of CF included shorter one-leg standing time; severe depressive symptoms; and MRI signs of significantly more WM lesions, lacunar infarcts, small-vessel disease lesions, microbleeds, and reduced MTL volumes. These unique deficits suggest that interventions for CF prevention and treatment should focus on motor skills, depressive symptoms, and vascular disease risk factor control.

The longitudinal association between cognitive impairment and incident visual impairment in a multiethnic Asian population: a prospective cohort study

BACKGROUND

The relationship between baseline cognitive impairment (CI) and incident visual impairment (VI) in Asians is unclear.

OBJECTIVE

To determine the associations between baseline CI with incident VI and visual acuity (VA) at 6-year follow-up in multiethnic Asians.

DESIGN

Cohort.

SETTING

Population-based.

SUBJECTS

Two thousand three hundred and twenty-four adults aged ≥60 years from the Singapore Epidemiology of Eye Diseases Study (response rate 64%).

METHODS

CI was defined using the validated Abbreviated Mental Test (AMT). VA was objectively measured using a LogMAR chart. Any incident VI was defined as having no VI (Snellen's VA better than or equal to 20/40) at baseline but present (VA worse than 20/40) at 6-year follow-up. VI severity was defined according to the International Classification of Diseases, 11th Revision. Associations were assessed using logistic and linear regression models.

RESULTS

Of the 2,324 participants, 248 had CI at baseline. Presence of baseline CI was associated with more than twice the odds of any incident VI, incident mild and moderate-severe VI (OR [95% confidence interval]: 2.48 [1.55-3.90], 2.07 [1.17-3.55], and 2.61 [1.36-4.93], respectively) and worse VA (β [95% confidence interval]: 0.026 [0.006-0.046]) at 6-year follow-up. The leading causes of incident VI were cataract and under-corrected refractive error.

CONCLUSIONS

Older adults with CI had more than double the odds of VI development and poorer VA than their cognitively intact counterparts, and most causes of incident VI were correctable. Strategies such as targeted vision screening and early intervention for early detection and management of vision loss in patients with cognitive decline are warranted.

Trajectories of physical frailty and cognitive impairment in older adults in United States nursing homes

Background

U.S. nursing homes provide long-term care to over 1.2 million older adults, 60% of whom were physically frail and 68% had moderate or severe cognitive impairment. Limited research has examined the longitudinal experience of these two conditions in older nursing home residents.

Methods

This national longitudinal study included newly-admitted non-skilled nursing care older residents who had Minimum Data Set (MDS) 3.0 (2014–16) assessments at admission, 3 months, and 6 months (n = 266,001). Physical frailty was measured by FRAIL-NH and cognitive impairment by the Brief Interview for Mental Status. Separate sets of group-based trajectory models were fitted to identify the trajectories of physical frailty and trajectories of cognitive impairment, and to estimate the association between older residents’ characteristics at admission with each set of trajectories. A dual trajectory model was used to quantify the association between the physical frailty trajectories and cognitive impairment trajectories.

Results

Over the course of the first six months post-admission, five physical frailty trajectories [“Consistently Frail” (prevalence: 53.0%), “Consistently Pre-frail” (29.0%), “Worsening Frailty” (7.6%), “Improving Frailty” (5.5%), and “Consistently Robust” (4.8%)] and three cognitive impairment trajectories [“Consistently Severe Cognitive Impairment” (35.5%), “Consistently Moderate Cognitive Impairment” (31.8%), “Consistently Intact/Mild Cognitive Impairment” (32.7%)] were identified. One in five older residents simultaneously followed the trajectories of “Consistently Frail” and “Consistently Severe Cognitive Impairment”. Characteristics associated with higher odds of the “Improving Frailty”, “Worsening Frailty”, “Consistently Pre-frail” and “Consistently Frail” trajectories included greater at-admission cognitive impairment, age ≥ 85 years, admitted from acute hospitals, cardiovascular/metabolic diagnoses, neurological diagnoses, hip or other fractures, and presence of pain. Characteristics associated with higher odds of the “Consistently Moderate Cognitive Impairment” and “Consistently Severe Cognitive Impairment” included worse at-admission physical frailty, neurological diagnoses, hip fracture, and receipt of antipsychotics.

Conclusions

Findings provided information regarding the trajectories of physical frailty, the trajectories of cognitive impairment, the association between the two sets of trajectories, and their association with residents’ characteristics in older adults’ first six months post-admission to U.S. nursing homes. Understanding the trajectory that the residents would most likely follow may provide information to develop a comprehensive care approach tailored to their specific healthcare goals.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-03012-8.

Association of preoperative frailty with postoperative delirium in elderly orthopedic trauma patients

BACKGROUND

Among elderly orthopedic trauma patients, the prevalence of delirium during hospitalization has been reported to be as high as 60%. Frail elderly patients have an increased risk of delirium after elective surgery; however, such an association remains underexplored among trauma patients.

AIM

Our goal was to investigate whether preoperative frailty is associated with postoperative delirium (POD) in elderly orthopedic trauma patients.

METHODS

We conducted a single-center, retrospective, cross-sectional study. All patients were ≥ 65 years of age and were admitted to the hospital between 01/01/2017 and 08/31/2018 for surgical intervention of a significant extremity fracture. Frailty was assessed using the fatigue, resistance, ambulation, illness, and loss of weight questionnaire. Delirium was assessed using the Confusion Assessment Method. POD was defined as new-onset delirium that occurred within 24 h after surgery. To investigate whether frailty is associated with POD, we performed a multiple variable logistic regression, controlling for biologically relevant confounders.

RESULTS

Five hundred fifty-six patients comprised the analytic cohort. Incidence of POD was 14% (n = 80). Multiple variable regression analysis demonstrated that each unit increment in FRAIL score was associated with a 33% higher likelihood of POD (OR 1.33; 95% CI 1.02-1.72, p = 0.03).

CONCLUSIONS

Our results suggest that preoperative frailty increases the risk of POD in hospitalized, elderly, orthopedic trauma patients. Future studies are needed to determine whether perioperative interventions focused on improving frailty can reduce the risk of POD and improve outcomes in this rapidly growing cohort of patients.

An update on cognitive frailty: Its definition, impact, associated factors and underlying mechanisms, and interventions

Since the concept and operational definition of "cognitive frailty" (simultaneous presence of physical frailty and cognitive impairment without concurrent dementia) were proposed by the International Academy of Nutrition and Aging and the International Association of Gerontology and Geriatrics, cognitive frailty has been widely investigated. This review is intended to address the operational definition of cognitive frailty, its consequences, contributing factors and underlying mechanisms, as well as interventions for cognitive frailty. Although the definitions and assessments of cognitive frailty vary among researchers, older adults with both physical frailty and cognitive impairment are shown to be at higher risk of adverse health outcomes, including death, disability, hospitalization and incident dementia, than those with either condition alone. While the underlying mechanisms of cognitive frailty are still unclear, factors shown to be associated with cognitive frailty include sociodemographic factors, social status, nutritional status, geriatric syndrome, physical and cognitive activities, functional status, comorbidities, medication use, gut-derived metabolites and structural changes in the brain. Accumulating evidence indicates the need for comprehensive geriatric assessment that helps identify the possible causes of cognitive frailty and develop a multimodal individualized intervention to prevent adverse health outcomes for older adults with cognitive frailty. Further studies are required to clarify the mechanisms through which physical frailty and cognitive impairment interact to accelerate adverse health outcomes, particularly cognitive outcomes. In addition, for older adults with cognitive frailty, an effective flow diagram from primary screening through comprehensive assessment to multidimensional intervention needs to be developed for future implementation in both clinical and community settings. Geriatr Gerontol Int 2021; ••: ••-••.

The Potential Role of miRNAs in Cognitive Frailty

Frailty is an aging related condition, which has been defined as a state of enhanced vulnerability to stressors, leading to a limited capacity to meet homeostatic demands. Cognitive impairment is also frequent in older people, often accompanying frailty. Age is the main independent risk factor for both frailty and cognitive impairment, and compelling evidence suggests that similar age-associated mechanisms could underlie both clinical conditions. Accordingly, it has been suggested that frailty and cognitive impairment share common pathways, and some authors proposed "cognitive frailty" as a single complex phenotype. Nevertheless, so far, no clear common underlying pathways have been discovered for both conditions. microRNAs (miRNAs) have emerged as key fine-tuning regulators in most physiological processes, as well as pathological conditions. Importantly, miRNAs have been proposed as both peripheral biomarkers and potential molecular factors involved in physiological and pathological aging. In this review, we discuss the evidence linking changes of selected miRNAs expression with frailty and cognitive impairment. Overall, miR-92a-5p and miR-532-5p, as well as other miRNAs implicated in pathological aging, should be investigated as potential biomarkers (and putative molecular effectors) of cognitive frailty.

Studying the relationship between cognitive impairment and frailty phenotype: a cross-sectional analysis of the Bushehr Elderly Health (BEH) program

BACKGROUND

Some pathophysiological effects of physical frailty and cognitive impairment might be similar; therefore, finding the associations in epidemiologic studies could guide clinicians and researchers to recognize effective strategies for each type of frailty such as frailty phenotype and frailty index, which in turn will result in a preventive approach. The study aimed to reveal which components of frailty phenotype are more associated with cognitive impairment. The findings of this study may help other researchers clarify the related pathways.

METHODS

This is a cross-sectional analysis of the results of the second phase of Bushehr Elderly Health Program; a community-based elderly prospective cohort study conducted in 2015-2016. The participants were selected through a multistage stratified cluster random sampling method. Frailty was assessed based on the Fried frailty phenotype criteria. Cognitive impairment was assessed by the Mini-Mental State Examination (MMSE), the Mini-Cog, and the Category Fluency Test (CFT). Multiple logistic regression models were applied to determine the association between frailty and cognitive impairment. Depression trait was assessed using the Patient Health Questionnaire-9 (PHQ-9). Activities of daily living were assessed using the Barthel Index and Instrumental Activities of Daily Living (IADLs) using Lawton's IADL.

RESULTS

The studyp conducted among people ≥ 60 years old (N = 2336) with women consisting 51.44% of the sample group. The mean age of the participants was 69.26 years old. The prevalence of pre-frailty and frailty were 42.59% and 7.66%, respectively. In the fully adjusted model, the odds ratio of the association between pre-frailty and frailty with cognitive impairment was 1.239, 95% CI: 1.011 - 1.519 and 1.765, 95% CI: 1.071 - 2.908, respectively (adjusted for age, sex, education, body mass index, smoking, diabetes mellitus, PHQ- 9, Barthel Index, and IADLs). In the fully adjusted multiple logistic regression models, all of the components of Fried frailty phenotype were significantly related to cognitive impairment except weight loss.

CONCLUSION

Cognitive impairment may be associated with frailty phenotype. Moreover, low strength and function of muscles had a stronger association with cognitive impairment. It seems that a consideration of cognitive impairment assessment in older people along with frailty and vice versa in clinical settings is reasonable.

Psychological and Social Factors Associated with Coexisting Frailty and Cognitive Impairment: A Systematic Review

Those living with coexistent frailty and cognitive impairment are at risk of poorer health outcomes. Research often focuses on identifying biological factors. This review sought to identify the association psychological and social factors have with coexisting physical and cognitive decline. Six databases were systematically searched in July 2020. Studies included individuals aged 60 years or older identified as being both frail and cognitively impaired. A narrative synthesis examined patterns within the data. Nine studies were included, most employed a cross-sectional design. Depression was investigated by all nine studies, those with coexistent frailty and cognitive impairment had higher levels of depressive symptoms than peers. Findings were mixed on social factors, although broadly indicate lower education, living alone and lower material wealth were more frequent in those living with coexistent decline. Further research is needed to explore potentially modifiable psychological and social factors which could lead to the development of supportive interventions.

Clusters of Physical Frailty and Cognitive Impairment and Their Associated Comorbidities in Older Primary Care Patients

(1) Objectives: We aimed to identify clusters of physical frailty and cognitive impairment in a population of older primary care patients and correlate these clusters with their associated comorbidities. (2) Methods: We used a latent class analysis (LCA) as the clustering technique to separate different stages of mild cognitive impairment (MCI) and physical frailty into clusters; the differences were assessed by using a multinomial logistic regression model. (3) Results: Four clusters (latent classes) were identified: (1) highly functional (the mean and SD of the “frailty” test 0.58 ± 0.72 and the Mini-Mental State Examination (MMSE) test 27.42 ± 1.5), (2) cognitive impairment (0.97 ± 0.78 and 21.94 ± 1.95), (3) cognitive frailty (3.48 ± 1.12 and 19.14 ± 2.30), and (4) physical frailty (3.61 ± 0.77 and 24.89 ± 1.81). (4) Discussion: The comorbidity patterns distinguishing the clusters depend on the degree of development of cardiometabolic disorders in combination with advancing age. The physical frailty phenotype is likely to exist separately from the cognitive frailty phenotype and includes common musculoskeletal diseases.

The Bidirectional Relationship between Vision and Cognition: A Systematic Review and Meta-analysis

TOPIC

Visual impairment (VI) and cognitive impairment (CIM) are prevalent age-related conditions that impose substantial burden on the society. Findings on the hypothesized bidirectional association of VI and CIM remains equivocal. Hence, we conducted a systematic review and meta-analysis to examine this bidirectional relationship.

CLINICAL RELEVANCE

Sixty percent risk of CIM has not been well elucidated in the literature. A bidirectional relationship between VI and CIM may support the development of strategies for early detection and management of risk factors for both conditions in older people.

METHODS

PubMed, Embase, and Cochrane Central registers were searched systematically for observational studies, published from inception until April 6, 2020, in adults 40 years of age or older reporting objectively measured VI and CIM assessment using clinically validated cognitive screening tests or diagnostic evaluation. Meta-analyses on cross-sectional and longitudinal associations between VI and CIM outcomes (any CIM assessed using screening tests and clinically diagnosed dementia) were examined. Random effect models were used to generate pooled odds ratios (ORs) and 95% confidence intervals (CIs). We also examined study quality, publication bias, and heterogeneity.

RESULTS

Forty studies were included (n = 47 913 570). Meta-analyses confirmed that persons with VI were more likely to have CIM, with significantly higher odds of: (1) any CIM (cross-sectional: OR, 2.38 [95% CI, 1.84-3.07]; longitudinal: OR, 1.66 [95% CI, 1.46-1.89]) and (2) clinically diagnosed dementia (cross-sectional: OR, 2.43 [95% CI, 1.48-4.01]; longitudinal: OR, 2.09 [95% CI, 1.37-3.21]) compared with persons without VI. Significant heterogeneity was explained partially by differences in age, sex, and follow-up duration. Also, some evidence suggested that individuals with CIM, relative to cognitively intact persons, were more likely to have VI, with most articles (8/9 [89%]) reporting significantly positive associations; however, meta-analyses on this association could not be conducted because of insufficient data.

DISCUSSION

Overall, our work suggests that VI is a risk factor of CIM, although further work is needed to confirm the association of CIM as a risk factor for VI. Strategies for early detection and management of both conditions in older people may minimize individual clinical and public health consequences.

Does the impact of intensive lifestyle intervention on cognitive function vary depending baseline level of frailty? An ancillary study to the Action for Health in Diabetes (Look AHEAD) Trial

AIMS

To assess whether there is an opportune window when intensive lifestyle intervention (ILI) benefits cognitive function.

METHODS

Standardized cognitive assessments were collected following ≥8 years of either ILI or a control condition of diabetes support and education (DSE) in 3708 individuals, ages 45-76 years at enrollment, with type 2 diabetes and overweight or obesity. Frailty index (FI) scores were used to group individuals at baseline into tertiles according to their age-related health status. Linear models were used to describe intervention adherence and cognitive function, with interaction terms to examine the consistency of relationships among tertiles.

RESULTS

Worse baseline FI scores were associated with poorer subsequent performance in tests of attention, processing speed, and executive function. No differences in any measure of cognitive function were observed between intervention groups within any FI tertile (all p > 0.10). Among individuals with worse baseline FI scores, weight gain was associated with poorer global cognitive function among participants assigned to DSE. There was no association between weight changes and cognitive function among participants assigned to ILI.

CONCLUSIONS

Among adults with type 2 diabetes and overweight/obesity, we found no evidence that there is a window of opportunity based on FI when ILI benefits cognitive function.

Anticholinergic Drug Induced Cognitive and Physical Impairment: Results from the InCHIANTI Study

BACKGROUND

The aims of this study were to evaluate the relationship between anticholinergic drug burden (ACB) cognitive impairment, physical frailty, and cognitive frailty, and to determine if ACB is predictive of these phenotypes when modeled with biological and genomic biomarkers.

METHODS

In a retrospective cohort study, a total of 1,453 adults aged 20-102 years were used to examine ACB as a predictor for cognitive impairment, physical frailty, and cognitive frailty. Anticholinergic burden is examined as a predictor for all phenotypes in a cross-sectional analysis using logistic, ordinal regression models, and Extreme Gradient Boosting for population predictive modeling.

RESULTS

A significant association was found between ACB and cognitive decline (p = .02), frailty (p < .001), and cognitive frailty (p < .001). The odds of cognitive impairment increased by 1.21 (95% confidence interval [CI] = 1.06-1.37, p < .001), odds of being frail increased by 1.33 (95% CI = 1.18-1.50, p < .001), and odds of having cognitive frailty increased by 1.36 (95% CI = 1.21-1.54, p < .001). Population modeling results indicated ACB score as one of the stronger predictors for cognitive impairment, physical frailty, and cognitive frailty with area under the curves ranging from 0.81 to 0.88.

CONCLUSIONS

Anticholinergic medications are a potentially modifiable risk factor for the prevention of cognitive and physical decline. Identification of reversible causes for cognitive and physical impairment is critical for the aging population. These findings encourage new research that may lead to effective interventions for deprescribing programs for the prevention of cognitive and physical decline in older adults.

Prospective Associations between Plasma Amyloid-Beta 42/40 and Frailty in Community-Dwelling Older Adults

BACKGROUND

Brain amyloid-beta (Aβ) plaques, a hallmark of the pathophysiology of Alzheimer's disease, have been associated with frailty. Whether the plasma Aβ markers show similar relationship with frailty is unknown.

OBJECTIVES

To investigate the prospective associations between plasma Aβ42/40 ratio and overtime frailty in community-dwelling older adults.

METHODS

From the 5-year Multidomain Alzheimer Preventive Trial (MAPT), we included 477 adults ≥70 years with available data on plasma Aβ42/40 ratio (lower is worse). Fried frailty phenotype (robust, pre-frail and frail) was assessed at the same time-point of plasma Aβ measures and after until the end of follow-up. The outcomes of interest were the change in the frailty phenotype over time (examined by mixed-effect ordinal logistic regressions) and incident frailty (examined by Cox proportional hazard models).

RESULTS

Plasma Aβ42/40 did not show significant associations with incident frailty; however, after adjusting for Apolipoprotein E (APOE) ε4 genotype, people in the lower quartile of plasma Aβ42/40 (≤0.103) had higher risk of incident frailty (HR=2.63; 95% CI, 1.00 to 6.89), compared to those in the upper quartile (>0.123). Exploratory analysis found a significant association between the lower quartile of plasma Aβ42/40 and incident frailty among APOE ε4 non-carriers (HR=3.48; 95% CI, 1.19 to 10.16), but not among carriers. No associations between plasma Aβ42/40 and evolution of frailty were observed.

CONCLUSION

No significant associations between plasma Aβ42/40 and frailty were found when APOE ε4 status was not accounted into the model. Nevertheless, APOE ε4 non-carriers with high Aβ burden might be more susceptible to develop frailty.

Cross-Sectional Association Between Cognitive Frailty and White Matter Hyperintensity Among Memory Clinic Patients

BACKGROUND

Cognitive frailty (CF) is defined as simultaneous presence of physical frailty (PF) and cognitive impairment among older adults without dementia. Although white matter hyperintensities (WMH) as expressions of cerebral small vessel disease are associated with physical and cognitive decline and could manifest as CF, this association remains yet to be clarified.

OBJECTS

To clarify the association between CF and WMH among memory clinic patients.

METHODS

The subjects of this cross-sectional study were 121 cognitively normal (CN) and 212 mildly cognitively impaired (MCI) patients who presented to the Memory Clinic at the National Center for Geriatrics and Gerontology of Japan. PF status was defined based on the definition proposed by Fried and colleagues. CF was defined as simultaneous presence of pre-PF or PF and MCI. WMH volumes were measured using an automatic segmentation application. Multiple liner regression analyses with adjustment for cardiovascular risk factors were performed.

RESULTS

Of all subjects, 77 (63.6%) and 22 (18.2%) CN patients and 132 (62.3%) and 65 (30.7%) MCI patients were categorized into pre-PF and PF, respectively. Multiple liner regression analysis showed that those with CF had higher WMH volumes than those without (β= 0.23). When categorized into six groups according to PF and cognitive status, the PF/CN (β= 0.15), pre-PF/MCI (β= 0.41), and PF/MCI (β= 0.34) groups had higher WMH volumes than the non-PF/CN group.

CONCLUSIONS

This study showed increased WMH volumes in CF and PF, indicating that WMH could be one of the key underlying brain pathologies of CF.

A possible effect of montelukast on neurological aging examined by the use of register data

Background The leukotriene receptor antagonist montelukast has been shown to rejuvenate aged brains in rats; however, data on humans are still scarce. Objective To investigate if montelukast may alleviate degenerative neurological changes using a register data. Setting Norwegian registry data analyses. Method The present observational study was based on data from the Norwegian Prescription Database and the Tromsø Study. The former has information regarding the use of prescription medicine; the latter includes tests for brain function such as subjective memory and finger-tapping. Multivariate linear regression analyses were performed to see how the use of various medications correlated with the test results, correcting for likely confounders. Main outcome measure Results on seven different tests considered relevant for neurological health were used as outcome. Results Previous use of montelukast correlated with improved scores on cognitive or neurological functioning (F = 2.20, p = 0.03 in a multivariate test). A range of other medications were tested with the same algorithm, including drugs acting on the immune system, but none of them correlated with (overall) significantly improved test results. Conclusion The present data suggest that montelukast may alleviate degenerative neurological changes associated with human aging.

Cognitive Frailty Among Elderly Chinese Patients With Cerebral Small Vessel Disease: A Structural MRI Study

Cognitive frailty (CF) is gaining an increasing amount of attention in geriatric research. CF refers to the co-occurrence of physical frailty and cognitive impairment in people without dementia. Neuroimaging of elderly people has revealed the presence of numerous white matter lesions, which is a typical biomarker of cerebral small vessel disease (SVD) on magnetic resonance images. The aim of the present study was to estimate the prevalence of CF in elderly Chinese patients with SVD. One hundred and thirty elderly patients with SVD were recruited for this cross-sectional observational study. Participants who met three to five of the Fried criteria of the physical frailty (PF) phenotype (shrinking, weakness, slowness, self-reported exhaustion, or low physical activity) were classified as having PF. Then, individuals with PF were defined as having CF if mild cognitive impairment was discovered by the Mini-Mental State Examination. Lastly, a series of cognitive function tests and the dual-task walking paradigm were examined. Based on the CF diagnostic criteria, the frequency of CF was 23.08% among elderly Chinese patients with SVD. Furthermore, CF-positive patients had a more significant SVD burden, based on magnetic resonance imaging findings. Logistic regression analysis, which was adjusted for age, sex, education, and comorbidities, showed that CF was negatively correlated with the dual-task walking speed in elderly people with SVD. Thus, SVD burden might be an indicator of CF phenotype. In elderly patients with SVD, CF was associated with dual task walking performance.

Shared mechanisms for cognitive impairment and physical frailty: A model for complex systems

INTRODUCTION

We describe findings from a large study that provide empirical support for the emerging construct of cognitive frailty and put forth a theoretical framework that may advance the future study of complex aging conditions. While cognitive impairment and physical frailty have long been studied as separate constructs, recent studies suggest they share common etiologies. We aimed to create a population predictive model to gain an understanding of the underlying biological mechanisms for the relationship between physical frailty and cognitive impairment.

METHODS

Data were obtained from the longitudinal "Invecchaiare in Chianti" (Aging in Chianti, InCHIANTI Study) with a representative sample (n = 1453) of older adults from two small towns in Tuscany, Italy. Our previous work informed the candidate 132 single nucleotide polymorphisms (SNPs) and 155 protein biomarkers we tested in association with clinical outcomes using a tree boosting, machine learning (ML) technique for supervised learning analysis.

RESULTS

We developed two highly accurate predictive models, with a Model I area under the curve (AUC) of 0.88 (95% confidence interval [CI] 0.83-0.90) and a Model II AUC of 0.86 (95% CI 0.80-0.90). These models indicate cognitive frailty is driven by dysregulation across multiple cellular processes including genetic alterations, nutrient and lipid metabolism, and elevated levels of circulating pro-inflammatory proteins.

DISCUSSION

While our results establish a foundation for understanding the underlying biological mechanisms for the relationship between cognitive decline and physical frailty, further examination of the molecular pathways associated with our predictive biomarkers is warranted. Our framework is in alignment with other proposed biological underpinnings of Alzheimer's disease such as genetic alterations, immune system dysfunction, and neuroinflammation.

An opinion paper on the maintenance of robustness: Towards a multimodal and intergenerational approach using digital twins

The increasing number of frail elderly people in our aging society is becoming problematic: about 11% of community‐dwelling older persons are frail and another 42% are pre‐frail. Consequently, a major challenge in the coming years will be to test people over the age of 60 years to detect pre‐frailty at the earliest stage and to return them to robustness using the targeted interventions that are becoming increasingly available. This challenge requires individual longitudinal monitoring (ILM) or follow‐up of community‐dwelling older persons using quantitative approaches. This paper briefly describes an effort to tackle this challenge. Extending the detection of the pre‐frail stages to other population groups is also suggested. Appropriate algorithms have been used to begin the tracing of faint physiological signals in order to detect transitions from robustness to pre‐frailty states and from pre‐frailty to frailty states. It is hoped that these studies will allow older adults to receive preventive treatment at the correct institutions and by the appropriate professionals as early as possible, which will prevent loss of autonomy. Altogether, ILM is conceived as an emerging property of databases (“digital twins”) and not the reverse. Furthermore, ILM should facilitate a coordinated set of actions by the caregivers, which is a complex challenge in itself. This approach should be gradually extended to all ages, because frailty has no age, as is testified by overwork, burnout, and post‐traumatic syndrome.

Physical Frailty and Fall Risk in Community-Dwelling Older Adults: A Cross-Sectional Study

Introduction

Frailty is a condition in older adults with decreased physical and cognitive performance that can affect health outcomes associated with fracture, disability, and falls. The aim of this study was to compare fall risk with different physical frailty statuses and investigate factors associated with fall risk in community-dwelling older adults.

Methods

The population studied included 367 older adults (mean age = 73.2 years ± 7.0; 237 females (64.6%) and 130 males (35.4%)) who live in Chiang Mai, Thailand. This study was of cross-sectional design. Fried's phenotype was used to screen the physical frailty status. The physiological profile assessment (PPA) was used to screen for fall risk. One-way ANOVA analysis was used to compare the fall risk between the different levels of frailty status. Linear regression analysis was used to assess the association between frailty status and fall risk.

Results

The prevalence of the frailty group was 8.7% and that of the prefrailty group was 76.8%. The three statuses of frailty identified were found to have different levels of risk of falling. The frailty group had a higher fall risk than the nonfrailty group and the prefrailty group. In addition, the nonfrailty group had a lower fall risk than the prefrailty group.

Conclusion

The frailty group had the highest fall risk in this cohort of older adults living in a community-dwelling facility. Therefore, it is important to assess the frailty status among older adults as it can be a predictor for fall risk. This assessment will therefore lead to a reduction in the rate of disability and death in the community.

Laboratory-Based Gait Variability and Habitual Gait Entropy Do Not Differentiate Community-Dwelling Older Adults from Those with Subjective Memory Complaints

BACKGROUND

Age-related cognitive decline may be delayed with appropriate interventions if those at high risk can be identified prior to clinical symptoms arising. Gait variability assessment has emerged as a promising candidate prognostic indicator, however, it remains unclear how sensitive gait variability is to early changes in cognitive abilities.

RESEARCH QUESTION

Do community-dwelling adults over 65 years of age with subjective memory complaints differ from those with no subjective memory concerns in terms of laboratory-measured or free-living gait variability?

METHODS

This cross-sectional study recruited 24 (age = 73.5(SD 6.4) years) community-dwelling people with subjective memory complaints and twenty seven (age = 70.9(4.3) years) individuals with no subjective memory concerns. A sample of 9 individuals with diagnosed mild dementia were also assessed (age = 86.5(7.0) years). Gait variability was assessed in a laboratory during walking at preferred pace (single-task) and while counting backward by seven (dual-task). Sixteen passes over a 4.88 m walkway in each condition were recorded and step length and duration variability was analysed. Free-living gait was assessed with a waist-worn accelerometer by identifying gait bouts of at least one min duration, and the mean multiscale sample entropy in one mins non-overlapping epochs is reported. Statistical inferences were based on analysis of variance using sex and group as the factors.

RESULTS

No difference between those with subjective memory complaints and those without were observed in either laboratory- or free-living gait variability estimates. Both laboratory- and free-living gait variability were higher in those with mild dementia compared to the other groups.

SIGNIFICANCE

Assuming that subjective memory complaints are on the pathway from cognitively intact to cognitively frail, the findings raise the hypothesis that subjective memory complaints occur earlier in the pathophysiology than measurable changes in laboratory or free living gait. Alternatively the gait variability assessments utilised may have been too insensitive.

The Sequence of Physical and Cognitive Impairment and the Association with Mortality Among Unimpaired Older Mexican Adults

BACKGROUND

Many older adults become physically and cognitively impaired. However, it is unclear whether unimpaired older adults are more likely to become physically or cognitively impaired first and if this sequence impacts mortality risk.

METHODS

Data came from the Mexican Health and Aging Study. The sample included 1,283 participants aged ≥60 years who were physically and cognitively unimpaired in 2001. Multinomial logistic regression was used to estimate probabilities of being unimpaired, cognitively impaired only, physically impaired only, or cognitively-physically impaired in 2003. Proportional hazard models were used to estimate mortality risk through 2015 according to physical and cognitive status in 2003.

RESULTS

The probabilities for being unimpaired, physically impaired only, cognitively impaired only, and cognitively-physically impaired in 2003 were 0.45, 0.22, 0.19, and 0.13, respectively. Older age, female sex, and arthritis were associated with significantly greater probability of becoming physically impaired only than cognitively impaired only in 2003. Cognitive impairment only (hazard ratio [HR] = 1.42, 95% confidence interval [CI] = 1.09-1.85) in 2003 but not physical impairment only (HR = 1.22, 95% CI = 0.94-1.58) was associated with greater mortality than being unimpaired in 2003. Cognitively-physically impaired participants had higher mortality risk than participants who were physically (HR = 1.58, 95% CI = 1.18-2.12) or cognitively (HR = 1.36, 95% CI = 1.01-1.84) impaired only.

DISCUSSION

The likelihood of becoming only physically or cognitively impaired over 2 years varies by demographic and health characteristics. The mortality risk for unimpaired older adults who become cognitively impaired only is similar to those who become physically impaired only. Research should determine if the sequence of cognitive and physical impairments is associated with other outcomes.