Frailty Phenotype Research Articles

The implications of frailty in older adults with epilepsy.

Older adults constitute a large proportion of people with epilepsy (PWE) due to the changing demographics worldwide and epilepsy's natural history. Aging-related pathophysiological changes lower the tolerance and increase our vulnerability to stressors, which manifests as frailty. Frailty is closely associated with adverse health outcomes. This narrative review examines the interplay between frailty and epilepsy, especially in older adults, emphasizing its clinical implications, including its role in managing PWE. Mechanistically, frailty develops through complex interactions among molecular and cellular damage, including genomic instability, mitochondrial dysfunction, and hormonal changes. These contribute to systemic muscle mass, bone density, and organ function decline. The concept of frailty has evolved from a primarily physical syndrome to include social, psychological, and cognitive dimensions. The "phenotypic frailty" model, which focuses on physical performance, and the "deficit accumulation" model, which quantifies health deficits, provide frameworks for understanding and assessing frailty. PWE are potentially more prone to developing frailty due to a higher prevalence of risk factors predisposing to frailty. These include, but are not limited to, polypharmacy, higher comorbidity, low exercise level, social isolation, low vitamin D, and osteoporosis. We lack commercial biomarkers to measure frailty but can diagnose it using self- or healthcare provider-administered frailty scales. Recent attempts to develop a PWE-specific frailty scale are promising. Unlike chronological age, frailty is reversible, so its management using multidisciplinary care teams should be strongly considered. Frailty can affect antiseizure medication (ASM) tolerance secondary to its impact on pharmacokinetics and pharmacodynamics. While frailty's effect on seizure control efficacy of ASM is poorly understood, its undoubted association with overall poor outcomes, including epilepsy surgery, behooves us to consider its presence and implication while treating older PWE. Incorporation of frailty measures in future research is essential to improve our understanding of frailty's role in PWE health. PLAIN LANGUAGE SUMMARY: Frailty is the declining state of the human body. People with epilepsy are more prone to it. It should be factored into their management.

Frailty Detection in Older Adults with Diabetes: A Scoping Review of Assessment Tools and Their Link to Key Clinical Outcomes.

Objectives: With the increasing prevalence of diabetes and frailty among older adults, there is an urgent need for precision medicine that incorporates comprehensive geriatric assessments, including frailty detection. This scoping review aims to map and synthesize the available evidence on validated tools for detecting pre-frailty and frailty in community-dwelling elderly individuals with diabetes and outpatient diabetes patients. Specifically, it addresses: (1) What validated tools are available for detecting pre-frailty and frailty in this population? (2) How are these tools associated with outcomes such as glycemic control, hypoglycemia, and metabolic phenotypes? (3) What gaps exist in the literature regarding these tools? Methods: The review followed PRISMA-ScR guidelines, conducting a systematic search across PubMed, Cochrane Library, and Web of Science. The inclusion criteria focused on studies involving individuals aged 70 years and older with diabetes, emphasizing tools with predictive capacity for disability and mortality. Results: Eight instruments met the inclusion criteria, including the Frailty Index, Physical Frailty Phenotype, and Clinical Frailty Scale. These tools varied in domains such as physical, psychological, and social aspects of frailty and their association with glycemic control, hypoglycemia, and metabolic phenotypes. The review identified significant gaps in predicting diabetes-related complications and their clinical application. Conclusions: Routine management of older adults with diabetes should incorporate frailty detection, as it is crucial for their overall health. Although widely used, the reviewed tools require refinement to address the unique characteristics of this population. Developing tailored instruments will enhance precision medicine, leading to more effective, individualized interventions for elderly individuals with diabetes.

Prognostic accuracy of eight frailty instruments for all-cause mortality in Australian primary care

AimTo investigate the ability of eight frailty instruments to accurately predict all-cause mortality and other adverse outcomes in Australian primary care patients. MethodsStudy participants included adults aged ≥75 years attending one of three primary care clinics in South Australia. Frailty instruments studied were Fried's frailty phenotype (FFP), the Frailty Index (FI) of cumulative deficits, Kihon Checklist (KCL), the Fatigue Resistance Ambulation Illness and Loss of weight (FRAIL) scale, Groningen Frailty Indicator (GFI), PRISMA-7, Reported Edmonton Frail Scale (REFS), and gait speed. Primary outcomes were all-cause mortality at 12- and 24-months. Secondary outcomes included falls, general practice attendance, hospital admission and emergency department (ED) presentation at 12-months. Results243 participants (55.6 % female) with a mean (SD) age of 80.2 (4.6) years were included. 29 participants (16.6 %) were classified as frail at baseline by FFP. All frailty instruments demonstrated a significant ability to predict 12- and 24-month mortality. The REFS showed the highest auROC for both 12- and 24-month mortality. The REFS, Frailty Index, Kihon Checklist, FRAIL scale, and gait speed showed excellent discriminative ability for 12-month mortality (auROC ≥ 0.8 - >0.9), while the remainder showed acceptable discrimination. All frailty instruments, with the exception of the GFI, showed an excellent discriminative ability for 24-month mortality (auROC 0.8-<0.9). ConclusionsAll frailty instruments possessed adequate discriminative ability for all-cause mortality predicting in older primary care patients. Frailty measurement is thus a valuable strategy to identify older patients at risk of mortality and can guide clinical decision-making in primary care settings.

Low food security is associated with frailty status and frailty components among people with HIV.

Low food security is common among people with HIV (PWH) and is associated with poorer health outcomes. Frailty, an aging-related outcome that is increasingly prevalent among PWH, may be stimulated by low food security. We assessed associations between food security and frailty among PWH. The Impact of Physical Activity Routines and Dietary Intake on the Longitudinal Symptom Experience of People Living with HIV (PROSPER-HIV) study follows PWH to evaluate how diet and physical activity impact symptoms. We utilized food security and frailty data from PROSPER-HIV Year 1 visits (January 2019 to July 2022) to estimate associations. Food security was measured via the validated two-item Food Security Questionnaire and categorized as Food Secure, Low Food Security, or Very Low Food Security. Frailty was measured with the Fried frailty phenotype, and categorized as robust, prefrail, and frail. We used relative risk regression to estimate associations between food security and frailty status, adjusted for demographic characteristics. Among 574 PWH, nearly one-quarter were women (22%), mean age was 52 years old, 8% were frail, and 46% prefrail. Low food security was reported among nearly one-third of PWH: 13% Low Food Security and 18% Very Low Food Security. Compared with being Food Secure, we found Low Food Security was associated with frailty [prevalence ratio: 4.06 (95% confidence interval (CI) 2.16-7.62] and Very Low Food Security was associated with both prefrailty [1.48 (1.23-1.78)] and frailty [5.61 (3.14-10.0)], as compared with robust status. Low food security was associated with increased frailty among PWH in this study, suggesting a potential intervention point to promote healthy aging.

Examining the Cycle of Physical Frailty in Falls Clinic Attendees Through Structural Equation Modeling.

In 1998, Fried and Walston introduced the Cycle of Frailty (CF) as a foundational concept for defining the physical frailty phenotype (FP). While the FP has been extensively validated, the CF hypothesis lacks equivalent support. This study aimed to internally validate the CF using structural equation modeling (SEM) in a clinical dataset of adults aged 50 or older attending an outpatient falls clinic. Measures included: age, morbidity, nutrition, sarcopenia by bioelectrical impedance, VO2max, handgrip strength, basal metabolic rate (BMR), 5-times chair stand test (5CST), physical activity, and total energy expenditure (TEE). The SEM, incorporating CF hypothesized causal pathways, was tested using IBM® SPSS® Amos 27.0.0 (maximum likelihood method) with a sample of 102 adults (mean age 69.8 years, 58.8% women). Overall, the SEM was supported by the data (χ2 = 44.4, df = 37, p = 0.189), with significant (p < 0.05) regression weights for morbidity→sarcopenia, age→sarcopenia, sarcopenia→VO2max, sarcopenia→handgrip strength, handgrip strength→5CST, physical activity→TEE, TEE→nutrition, and BMR→TEE. However, nutrition→sarcopenia, sarcopenia→BMR, VO2max→5CST, and 5CST→physical activity were not significant. Although the SEM was limited by inclusion of surrogate CF measures (e.g., 5CST instead of gait speed, VO2max based on age-predicted maximal/resting heart rate), it provided some internal support for the CF hypothesis.

Association of metabolic syndrome and frailty with postoperative complications in older gastric cancer patients: A body composition perspective.

To compare the characteristics of body compositions between metabolic syndrome (MetS) and frailty, and determine the independent and overlapping of MetS and frailty with postoperative complications among older patients with gastric cancer. A prospectively observational study. Two hundred and eighty six older patients from 60 to 80 years undergoing radical gastrectomy for the first time. MetS was diagnosed by the criteria from the 2020 edition of Chinese guideline for the prevention and treatment of type 2 diabetes mellitus, and frailty was defined by frailty phenotype. An InBody770 impedance analyzer was used to measure body compositions and with 10 fat- and muscle-related indicators being included in this study. Based on the presence of frailty and MetS, patients were divided into the frailty group, MetS group, frailty+MetS group, and normal group, and the body compositions indicators of these groups were compared. Clavien-Dindo classification was used to grade the severity of postoperative complications. Univariate and multivariate regression models were performed to explore the independent and joint association of MetS and frailty with postoperative complications. The incidence rate of MetS, frailty, and frailty+MetS being 20.3%, 15.7%, and 4.2% respectively. Compared with the normal group, both fat and muscle compositions were decreased significantly in the frailty group (p < 0.05), while the statistically significant difference of fat-to-muscle mass ratio (FMR) and skeletal muscle mass to visceral fat area ratio (SVR) were not observed (p > 0.05). In contrast, except SVR, the other indicators of the MetS group were higher than the normal group (p < 0.05). As to the frailty+MetS group, there was a significant increase in fat compositions and FMR, as well as a significant decline in SVR (p < 0.05), while the difference of muscle compositions was not statistically significant (p > 0.05). There was an association of frailty with postoperative total (OR = 3.068, 95% CI: 1.402-6.713) and severe (OR = 9.423, 95% CI: 2.725-32.589) complications, but no association was found of MetS alone. MetS coexisting with frailty was associated with the highest risk of both total (OR = 3.852, 95% CI: 1.020-14.539) and severe (OR = 12.096, 95% CI: 2.183-67.024) complications. Both frailty and MetS coexisting with frailty had adverse effects on postoperative complications, which appeared greatly different characteristics in body compositions and therefore reinforced the importance of targeted nutritional or metabolic intervention. Although MetS alone were not significantly associated with postoperative complications, it is essential to focus on the causal relationship and development trend between MetS and frailty to prevent MetS from shifting into frailty, considering the highest risk in their coexistence state.

Proteomics Identify Clinical Phenotypes and Predict Functional Outcomes in Heart Failure With Preserved Ejection Fraction: Insights From VITALITY-HFpEF.

Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome that may emerge from overlapping systemic processes associated with comorbidities. We assessed whether unique clusters of circulating proteins are associated with specific clinical characteristics and functional status at baseline and follow-up in a well-phenotyped cohort of patients with HFpEF. We evaluated 368 proteins associated with cardiovascular disease and inflammation in prerandomization blood samples from 763 VITALITY-HFpEF (Vericiguat to Improve Physical Functioning in Daily Living Activities of Patients With HFpEF) participants who had a left ventricular ejection fraction ≥45% and a heart failure decompensation event within 6 months. Proteins were clustered, and their associations with clinical characteristics, baseline, and 24-week functional outcomes (Kansas City Cardiomyopathy Questionnaire Physical Limitation Score, 6-minute walk distance [6MWD], and Fried frailty phenotype) were estimated with linear regression. Elastic net regression was used to derive a proteomic summary composite to predict changes in 24-week functional outcomes. Four unique protein clusters were identified, containing 24, 66, 197, and 81 proteins. At baseline, 2 protein clusters with the hub proteins caspase-3 and Dickkopf-related protein 1 were associated with increased frailty, whereas the cluster with tumor necrosis factor receptor 1 as a hub protein was associated with lower Kansas City Cardiomyopathy Questionnaire Physical Limitation Score and shorter 6MWD. By contrast, the cluster with protein C as a hub protein was associated with less frailty and longer a 6MWD. The 24-week increase in 6MWD was negatively correlated with the protein cluster with caspase-3; the protein C cluster was correlated with less frailty at 24 weeks. The baseline proteomic summary composite predicted observed changes in Kansas City Cardiomyopathy Questionnaire Physical Limitation Score and 6MWD at 24 weeks (r=0.42 and 0.30; P<0.001 for both). Proteomics differentiate specific baseline functional traits associated with HFpEF and may facilitate phenotyping in a heterogeneous disease. These proteins also provide insights into the diverse pathophysiology of HFpEF and which patients may improve functional status during follow-up. URL: https://www.clinicaltrials.gov; Unique identifier: NCT03547583.

Evaluation of Five Screening Tools in Detecting Physical Frailty in Cirrhosis and Their Prognostic Role.

Background: Physical frailty (PF) is a syndrome of decreased physical function and reserves, preventing patients from coping with stressful events. PF screening tools in patients with liver cirrhosis (LC) can help evaluate the risk of complications and death. The aim of this study was to assess the performance of five screening tools in detecting PF and their ability to predict 18-month mortality in LC. Methods: The Short Physical Performance Battery (SPPB), Fried frailty phenotype (FFP), Clinical Frailty Scale (CFS) and 6-Minute Walk Test (6MWT) were compared with the Liver Frailty Index (LFI) as the method of reference. Patients with an LFI ≥ 4.5, SPPB ≤ 8, FFP ≥ 3, CFS ≥ 6 points, and those walking <250 m, were considered frail. Results: A total of 109 consecutive patients with stable LC were included [63.3% male, median age 62 years, (IQR 52-70), MELD 9 (7-14.5), 46.8% with decompensated LC (DC)]. PF was present in 23.9%, 27.5%, 41.3%, 13.8%, and 28.4% as assessed by the LFI, SPPB, FFP, CFS, and 6MWT, respectively. Cohen's kappa measurement of agreement of four of the tools with LFI was 0.568, 0.334, 0.439, and 0.502, respectively (p < 0.001 for each). Kaplan-Meier survival curves at 18 months showed higher mortality in frail patients compared to non-frail patients by any method (log rank p < 0.05). In the multivariate models, PF defined by any method emerged as an independent prognostic factor of 18-month mortality after adjustment for age, gender, and MELD-score. Conclusions: Patients characterized as frail by five screening tools were not identical. However, PF defined by either method was proven to be an independent poor prognostic factor for long-term mortality after adjustment for covariates.

Multidimensional frailty assessment: Development and validation of the Tilburg Frailty Indicator-Indonesia version

The aim of this study was to develop and examine the psychometric properties of the Tilburg Frailty Indicator-Indonesian version (TFI-I). 308 community-dwelling older adults aged ≥60 years participated. The TFI-I exhibited favorable internal consistency (Cronbach's alpha = 0.775) and test–retest reliability (intraclass correlation coefficient = 0.94). The physical, psychological, and social domains of the TFI-I correlated closely with the similar constructs of other scales, including the Short Physical Performance Battery (P < .001), Fried Frailty Phenotype (P < 0.001), Geriatric Depression Scale (P < .001), and the World Health Organization Quality of Life scale (P = 0.041), indicating its favorable construct validity. Significant differences were identified between the robust and frailty groups on the Barthel Index (P = .001) and Lawton Instrumental Activity of Daily Living Scale (P < .001). Overall, the TFI-I is valid and reliable when used to evaluate frailty status in clinical and research settings.

Joint effects of physical frailty and traditional cardiovascular risk factor control on cardiovascular disease in patients with diabetes

ObjectivesPhysical frailty has been found to increase the risk of multiple adverse outcomes including cardiovascular disease (CVD) in diabetic patients, but whether this could be modified by traditional risk factor control remains unknown. We aimed to explore the joint and interaction effects of frailty and traditional risk factor control on the risk of CVD. DesignA population-based cohort study. Setting and participantsWe included 15,753 participants with type 2 diabetes at baseline from UK Biobank. MeasurementsPhysical frailty was assessed by Fried criteria’s frailty phenotype. The degree of risk factor control was determined by the numbers of the following factors controlled within the target range, including glycated hemoglobin, blood pressure, low-density lipoprotein cholesterol, smoking, and kidney condition. Incident CVD included coronary heart disease, stroke, or heart failure. Cox proportional hazard models were used to assess the individual and joint effects of frailty and risk factor control on the risk of CVD. ResultsAfter a median follow-up of 13.5 years, 1129 incident CVD events were observed. Compared with non-frailty, both prefrailty and frailty were significantly associated with increased risk of CVD (HR 1.22, 95% CI [1.13, 1.31] for pre-frailty and 1.70 [1.53, 1.90] for frailty). For the joint effects, participants with frailty and a low degree of risk factor control (control of 0−1 risk factors) had the highest risk of CVD (2.92 [2.04, 4.17]) compared to those with non-frailty and optimal risk factor control (control of 4−5 risk factors). Moreover, a significant additive interaction between frailty and risk factor control was observed, with around 3.8% of CVD risk attributed to the interactive effects. ConclusionsBoth prefrailty and frailty were associated with a higher risk of CVD in participants with type 2 diabetes. Moreover, physical frailty could interact with the degree of risk factor control in an additive manner to increase the CVD risk.

Impact of a comprehensive geriatric assessment to manage elderly patients with locally advanced non-small-cell lung cancers: a multicenter prospective study.

Concurrent chemoradiotherapy (cCRT) is the standard treatment for locally advanced and unresectable non-small-cell lung cancer. Population is aging, and Geriatric assessment (GA) has demonstrated its paper to select fit patients for active treatment and vulnerable, frail patients for interventions and/or palliative care in many histologies. Its role in locally advanced, unresectable non-small-cell lung cancer has been less explored. To assess the capability of GA to detect frail patients not suitable for active treatment, we developed this exploratory non-interventional prospective study. All patients ≥ 70years diagnosed with stage locally advanced and unresectable non-small-cell lung cancer were invited to undergo geriatric assessment. Secondary aims were description of population, exploring GA as prognostic factor, determination of toxicity profile and look for a frailty biomarker. From June 2017 to June 2020, 51 patients were included, of whom 35% (n:18) were classified as frail. Frail patients had less overall survival and more grade 3-4 toxicity. Exploratory results for frailty phenotype are described in the text. With the results of our study, we confirm that GA can detect frail patients unsuitable for treatment, with a higher risk of toxicity and less overall survival. A trend toward blood-test results for phenotype frailty can be hypothesis generation.

FRELSA: A dataset for frailty in elderly people originated from ELSA and evaluated through machine learning models

BackgroundFrailty is an age-related syndrome characterized by loss of strength and exhaustion and associated with multi-morbidity. Early detection and prediction of the appearance of frailty could help older people age better and prevent them from needing invasive and expensive treatments. Machine learning techniques show promising results in creating a medical support tool for such a task. MethodsThis study aims to create a dataset for machine learning-based frailty studies, using Fried's Frailty Phenotype definition. Starting from a longitudinal study on aging in the UK population, we defined a frailty label for each subject. We evaluated the definition by training seven different models for detecting frailty with data that were contemporary to the ones used for the definition. We then integrated more data from two years before to obtain prediction models with a 24-month horizon. Features selection was performed using the MultiSURF algorithm, which ranks all features in order of relevance to the detection or prediction task. ResultsWe present a new frailty dataset of 5303 subjects and more than 6500 available features. It is publicly available, provided one has access to the original English Longitudinal Study of Ageing dataset. The dataset is balanced after grouping frailty with pre-frailty, and it is suitable for multiclass or binary classification and prediction problems. The seven tested architectures performed similarly, forming a solid baseline that can be improved with future work. Linear regression achieved the best F-score and AUROC in detection and prediction tasks. ConclusionsCreating new frailty-annotated datasets of this size is necessary to develop and improve the frailty prediction techniques. We have shown that our dataset can be used to study and test machine learning models to detect and predict frailty. Future work should improve models' architecture and performance, consider explainability, and possibly enrich the dataset with older waves.

Assessing the causal relationship between frailty and sex hormone-binding globulin or insulin-like growth factor-1 levels: A sex-stratified bidirectional Mendelian Randomization study

BackgroundThe association between frailty and sex hormone-binding globulin (SHBG) or insulin-like growth factor-1(IGF-1) levels demonstrates sex differences with inconsistent conclusions. This study aims to explore the causal relationship between frailty and SHBG or IGF-1 levels through bidirectional Mendelian randomization (MR). MethodsWe conducted two-sample bidirectional sex-stratified MR analyses using summary-level data from genome-wide association studies (GWASs) to examine the causal relationship between frailty and IGF-1 or SHBG levels, as measured by frailty index (FI) and frailty phenotype (FP). We use the random-effects inverse-variance weighted (IVW), weighted median, MR-Egger, MR-Egger intercept, and leave-one-out approaches. ResultThe relationship between frailty and SHBG or IGF-1 levels is inversely related, with a significant decrease in SHBG levels in females. Specifically, SHBG levels significantly decrease with FI (β = −5.49; 95 % CI: −9.67 to −1.32; FDR = 0.02) and more pronounced with FP (β = −10.14; 95 % CI: −16.16 to −4.13; FDR = 0.01), as determined by the IVW approach. However, reverse analysis shows no significant effect of IGF-1 or SHBG levels on either FI or FP (p > 0.05). ConclusionOur study indicates a negative correlation between frailty and the levels of SHBG and IGF-1. It is suggested that further research is required to establish cut-off values for SHBG and IGF-1 levels in the frailty population. This is particularly important for females at higher risk, such as those undergoing menopause, to enable comprehensive assessment and early prevention efforts. While the findings imply that reduced IGF-1 and SHBG levels may not directly contribute to frailty, it is important not to overlook the underlying mechanisms through which they may indirectly influence frailty.

Frailty Assessment Scale for Heart Failure: Development and Psychometric Validation.

Frailty is common in patients with heart failure. Specific scales, including the Clinical Frailty Scale, exist but have not undergone thorough psychometric validation among patients with heart failure. The aim of this study was to develop and validate the Frailty Assessment Scale for Heart Failure (FAS-HF) in patients with heart failure. This study included 3 phases. In phase I, conceptualization and item generation, the FAS-HF was initially developed through the analysis of qualitative research data and a literature review. In phase II, item selection and content validity, the Delphi method was used to gather experts' opinions and suggestions regarding the FAS-HF. In phase III, field testing and psychometric evaluation, a cross-sectional study of 184 patients with heart failure in northern Taiwan was conducted to test the reliability and validity of the FAS-HF. The 15-item FAS-HF included the physical, psychological, and social frailty domains. The total score ranged from 0 to 45, with higher scores representing frailer individuals. Exploratory factor analysis revealed that the cumulative loading variance was 57.39%. In the confirmatory factor analysis, the goodness-of-fit index (0.91), adjusted goodness-of-fit index (0.87), and root mean square error of approximation (0.06) were acceptable for model fit. Acceptable reliability was found, with a Cronbach α coefficient of 0.87 and a test-retest reliability of 0.99. Compared with the Fried frailty phenotype, the area under the receiver operating characteristic curve was 0.94, and the optimal cutoff score for frailty was 20. The FAS-HF has good reliability, validity, and discrimination and can be used as a frailty indicator for patients with heart failure.

Frailty Is Associated with Malnutrition-Inflammation Syndrome in Older CKD Patients.

Patients affected by chronic kidney disease (CKD) are generally considered to be frailer than those with preserved renal function. We cross-sectionally evaluated the associations between frailty, malnutrition-inflammation syndrome and circulating inflammatory cytokines in 115 older individuals with advanced CKD. As for frailty definition, we adopted Fried's frailty phenotype (FP), while malnutrition-inflammation syndrome was assessed using the Malnutrition-Inflammation Score (MIS) and circulating inflammatory cytokines (IL-6; TNFα; MCP-1). A total of 48 patients were frail, and mean eGFR was comparable in both frail and non-frail patients (24 ± 10 vs. 25 ± 11 mL/min/1.73 m2; p = 0.63). Frail patients had higher MIS (6 [4-11] vs. 4 [3-5]; p < 0.0001) but cytokine concentrations were comparable in both groups. At multivariate regression, FP was independently associated with MIS, age, gender and pre-albumin but not with cytokines. However, we found some associations between inflammatory cytokines and some specific frailty criteria: weight loss and slowness were associated with MCP-1 (respectively p = 0.049 and p < 0.0001) and weakness with IL-6 (p = 0.005); in conclusion, in older patients with advanced CKD, frailty is strictly associated with malnutrition-inflammation syndrome but not with circulating inflammatory cytokines.

Physical Function and Mortality in Older Adults with Chronic Kidney Disease.

Accurate mortality prediction can guide clinical care for older adults with chronic kidney disease (CKD). Yet existing tools do not incorporate physical function, an independent predictor of death in older adults. We determined whether incorporating physical function measurements improve mortality prediction among older adults with CKD. We included Chronic Renal Insufficiency Cohort participants who were ≥65 years old, had estimated Glomerular Filtration Rate (eGFR) <60 mL/min/1.73m2, not receiving kidney failure replacement therapy (KFRT), and had least one gait speed assessment. Gait speed was measured at usual pace (≥0.84, 0.83-0.65, 0.64-0.47, ≤0.46 meters/second, or unable), and frailty was assessed using Physical Frailty Phenotype criteria (range 0 to 5 points, also known as Fried criteria). We modeled time to all-cause death over five years using Cox proportional hazard models, treating KFRT as censored and non-censored events in separate analyses. C-statistics assessed model discrimination. Among 2,338 persons, mean age was 70±4 years; 43% were female and 43% were Black. Mean eGFR was 42±13 mL/min/1.73m2 and median urine albumin-to-creatinine ratio was 33 mg/g [Q1 9, Q3 206]. Over a median follow-period of 5 years, 392 died and 164 developed KFRT. In censored analyses, adding gait speed or frailty improved mortality risk prediction. The C-statistic changed from 0.69 to 0.72 with gait speed scores, and from 0.70 to 0.73 with frailty scores. The performance of models with gait speed or frailty was similar in non-censored analyses. Among older adults with CKD, adding measures of physical function modestly improves mortality prediction.

The association between visceral fat obesity and prefrailty in Chinese older adults: a cross-sectional study

BackgroundThe prevalence of obesity is escalating. Previous research has concentrated on the link between frailty and obesity; however, the association between prefrailty and obesity has been less studied. Prefrailty screening and intervention may prevent or postpone frailty in older persons.ObjectiveThe study was to investigate into the relationship between prefrailty and several obesity indicators in Chinese community-dwelling older individuals.MethodsThis research employed the Frailty Screening Index to investigate the frailty phenotype of people living in Shanghai. Bioelectrical impedance analysis was used for evaluating body composition.ResultsThere were 510 participants (39.0%) with high visceral adipose areas. Participants with a high visceral adipose area showed a higher risk of prefrailty (adjusted OR, 1.53; 95% CI, 1.19–1.96), according to multivariate models. When body mass index (BMI) and visceral fat area (VFA) were combined, it was discovered that having an overweight BMI with normal VFA was a protective factor for prefrailty (corrected OR, 0.62; 95% CI, 0.43–0.90), but having a normal weight but excess VFA increased the risk of prefrailty (corrected OR, 1.87; 95% CI, 1.15–3.03).ConclusionVisceral fat obesity is an independent risk factor for prefrailty in Chinese older adults. Implementing targeted interventions, such as dietary modifications, increased physical activity, and other lifestyle changes, could play a crucial role in reducing the risk of prefrailty and improving overall health outcomes in this population.

Breathlessness, Frailty, and Sarcopenia in Older Adults

BackgroundBreathlessness shares aging mechanisms of frailty and sarcopenia. Research questionAre frailty and sarcopenia associated with breathlessness itself? Study design and MethodsWe analyzed data from a population-based, prospective cohort study of 780 community-dwelling older adults. Breathlessness was defined using the modified Medical Research Council Dyspnea Scale (≥2 points) and the Chronic Obstructive Pulmonary Disease Assessment Test (≥10 points). Frailty was defined by frailty index (FI), frailty phenotype, and FRAIL questionnaire. Sarcopenia was defined by the Asian Working Group for Sarcopenia 2019. Sarcopenia phenotype score quantifies the number of criteria met. The associations of frailty and sarcopenia with breathlessness was evaluated by logistic regression analyses. Adjusted odds ratio (aOR) were calculated, accounting for age, sex, chronic airway disease, smoking status, body mass index, lung functions, socioeconomic status (living alone, income, education), comorbid conditions (hypertension, diabetes, malignancy, myocardial infarction, heart failure), and other geriatric contributors (cognitive dysfunction, depression, malnutrition, polypharmacy, fall history in the past year). Institutionalization-free survival was compared by log-rank test. ResultsThe prevalence of frailty is higher in the breathlessness group compared to non-breathlessness group (42.6% vs. 10.5% by FI, 26.1% vs. 8.9% by frailty phenotype, and 23.0% vs. 4.2% by FRAIL) and sarcopenia (38.3% vs. 26.9%), with P < 0.01 for all comparisons. The multivariable logistic regression analyses showed that frailty (FI [aOR: 9.29], FRAIL questionnaire [aOR: 5.21], and frailty phenotype [aOR: 3.09]) and sarcopenia phenotype score (score 2 [aOR: 2.00] and score 3 [aOR: 2.04] compared to score 0) were associated with breathlessness. The cumulative incidence of institutionalization-free survival was higher in the breathlessness group than counterparts (P = 0.02). InterpretationThe findings suggest that frailty and sarcopenia strongly contribute to breathlessness in community-dwelling older adults. Measuring sarcopenia and frailty in older adults may offer opportunities to prevent age-related breathlessness.

Frailty in Medicare Advantage Beneficiaries and Traditional Medicare Beneficiaries

A growing proportion of the population is enrolling in Medicare Advantage (MA), which typically offers additional benefits compared with traditional Medicare (TM). To determine whether frailty and frailty trajectories differ between MA enrollees and TM enrollees. This retrospective cohort study used data from the National Health and Aging Trends Study (2015-2016). Analyses were conducted from August 2023 to March 2024. Participants were community-dwelling Medicare beneficiaries aged 65 years and older. Enrollment in MA vs TM. Frailty was calculated by a frailty index (FI) (range, 0-1, with higher values indicating greater frailty) and the Fried Frailty Phenotype (FFP) score (range, 0-5, with higher values indicating greater frailty). Physical performance, including Short Physical Performance Battery (SPPB) score (range, 0-12, with higher values indicating better performance), and gait speed (meters per second) were measured. The primary outcome was the difference in FI and FFP scores from the 2015 baseline assessment to the 2016 follow-up assessment. Secondary outcomes include the 1-year changes in SPPB and gait speed. The final cohort consisted of 7063 participants (2775 [23.1%] aged >80 years; 4040 [54.7%] female), representing a sample of the 38.8 million beneficiaries. There were 2583 (35.0%) MA enrollees (13.6 million) and 4480 (65.0%) TM enrollees (25.2 million). At baseline, the FI score was similar between MA and TM enrollees (mean [SD], 0.22 [0.15] vs 0.21 [0.14]), although MA enrollees had worse phenotypic frailty (496 participants [15.2%] vs 811 participants [13.7%] considered frail by FFP score), SPPB scores (mean [SD], 6.91 [3.34] vs 7.21 [3.27]), and gait speed (0.79 [0.24] m/s vs 0.82 [0.23] m/s) than TM enrollees. One year later, there were no differences between MA and TM enrollees in the 1-year change in FI score (mean [SD], 0.016 [0.071] vs 0.014 [0.066]; adjusted mean difference, 0.001 [95% CI, -0.004 to 0.005]), FFP score (mean [SD], 0.017 [1.004] vs 0.007 [0.958]; adjusted mean difference, -0.009 [95% CI, -0.067 to 0.049]), SPPB score (mean [SD], -0.144 [2.064] vs -0.211 [1.968]; adjusted mean difference, 0.068 [95% CI, -0.076 to 0.212]), and gait speed (mean [SD], -0.0160 [0.148] m/s vs -0.007 [0.148] m/s; adjusted mean difference, -0.010 m/s [95% CI, -0.067 to 0.049 m/s]). In this cohort study of Medicare beneficiaries from 2015, MA enrollees experienced similar declines in frailty over 1 year compared with TM enrollees. Future work should examine whether the specific types of services covered by health insurance can impact frailty and health trajectories for older adults.

The modified 5-item frailty index as a predictor of perioperative risk in patients undergoing percutaneous nephrolithotomy.

The modified 5-item frailty index is a relatively new tool to assess the post-operative complication risks. In urology, there is limited literature on the impact of frailty on percutaneous nephrolithotomy (PCNL) outcomes. We aimed to compare the predictive value of the modified 5-item frailty index (mFI-5) to identify high risk patients prior to PCNL. A database of patients undergoing PCNL, between 2015 and 2022, was analyzed. Patient frailty was assessed using the mFI-5 index. The mFI-5 index was calculated based on the presence of the five co-morbidities: congestive heart failure within 30days prior to surgery, diabetes mellitus, chronic obstructive pulmonary disease, partially dependent or totally dependent functional health status at time of surgery, and hypertension requiring medication. Patients were grouped as not frail (mFI-5 = 0), intermediate (mFI-5 = 1), and severely frail (mFI-5 ≥ 2). Primary outcomes were 30-day postoperative complications. Secondary outcomes were hospitalization: total hospital length of stay, reoperation, and unplanned readmission. From a total of 320 PCNL patients included for analysis, 54.06% (n = 173) were not frail, 17.81% (n = 57) were intermediate, and 28.12% (n = 90) were severely frail. Frail patients were likely to be older (p = 0.002) and have a higher American Society of Anesthesiologists score (p = 0.001), chronic kidney disease (p < 0.001). Patients of intermediate or severe frailty were more likely to exhibit postoperative sepsis (p = 0.042), significant blood loss (p = 0.036) and require intensive care units admissions (p = 0.0015). Frail patients had a longer hospital length of stay (p < 0.001) and tended to require reoperation (p = 0.001), and unplanned readmission (p = 0.02). Frailty assessment appears useful in stratifying those at risk of extended hospitalization, septic and hemorrhagic complications, readmission, or reoperation after PCNL. Preoperative assessment of frailty phenotype may give insight into treatment decisions and assist surgeons in counselling patients on expected course and hospital stay following PCNL.