Unveiling frailty: comprehensive and sex-specific characterization in prematurely aging PolgA mice.

Frailty, a geriatric syndrome, is assessed using the frailty phenotype (FP) and frailty index (FI). While these approaches have been applied to aging mice, their effectiveness in prematurely aging mouse models such as PolgAD257A/D257A (PolgA) has not been completely explored. We demonstrated that frailty became evident in PolgA mice around 40 weeks, validated through body weight loss, reduced walking speed, decreased physical activity, and weaker grip strength. Moreover, we also identified sex differences in these mice with females exhibiting slightly more physical decline compared to males. Frailty prevalence in PolgA mice at 40 weeks parallels that observed in naturally aging mice at 27 months and aging humans at 65-70 years. These findings contribute to understanding frailty onset and sex-specific patterns in this prematurely aging mouse model, emphasizing the significance of the PolgA mouse model in investigating aging and related disorders.

Establishing a clinically applicable frailty phenotype screening tool for aging dogs.

Introduction: Frailty is a well-defined clinical syndrome in humans caused by accumulation of impairments which result in loss of reserve capacity and increased vulnerability to disability, dependence, and death. Dogs are of particular interest in studies of frailty due to the similarities they share with people in their environment, lifestyles, and age-related diseases. Materials and methods: The aim of this study was to develop a frailty phenotype screening tool, based on previously validated measures in dogs, which could be easily applied in the clinical setting, and which was predictive of all-cause, short term (6-month) mortality. The study was conducted in two phases. In phase 1, a retrospective cohort of 51 dogs was used to identify and evaluate potential measures for the five domains of frailty. This information was then used to develop a simple frailty phenotype based on examination findings and owner directed questions. In phase 2 of the study, this phenotype was evaluated in a prospective cohort of 198 dogs aged 9 years or older from multiple different specialty and primary care services to determine how the phenotype performed across a diverse canine population. Results: The developed frailty phenotype was predictive of all-cause, short-term mortality independent of age, sex, or weight (hazard ratio = 4.71; 95% CI, 2.66-8.8). Of the covariates evaluated only breed was significant, with purebred dogs having 1.85 times higher mortality than mixed breed dogs (95% CI, 1.04-3.31). The frailty phenotype performed similarly across all hospital services from which patients were enrolled. Conclusion: Based on these findings, the defined frailty phenotype represents a valuable screening tool for early risk identification and intervention, and can aid in clinical decision making for owners and veterinarians. Additionally, it will promote further research into the understanding and treatment of frailty in dogs.

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.

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.

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

BACKGROUND: Frailty 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. METHODS: This 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. RESULTS: We 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. CONCLUSIONS: Creating 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.

Association Between Sarcopenic Obesity and Frailty Risk in Community-Dwelling Older Women With Locomotive Syndrome: A Cross-Sectional Survey.

Background Concurrent sarcopenia and obesity in locomotive syndrome (LS) impair activities of daily living and decrease extremity muscle strength and motor function. However, the increased risk of frailty posed by sarcopenic obesity compared to either sarcopenia or obesity alone remains unclear. Objective To examine the association between sarcopenic obesity and frailty risk in community-dwelling older adult women with LS. Methods This cross-sectional study included 158 women aged ≥65 years with LS stage 1 (age, 74.0 yrs, body mass index, 22.7 kg/m2) according to the Japanese Orthopaedic Association criteria. Bioelectrical impedance analysis was used to measure the skeletal muscle mass index (SMI) and percent body fat (PBF). Participants were classified into four subtypes: normal (non-obesity, non-sarcopenia), sarcopenia (SMI < 5.7 kg/m2), obesity (PBF > 35%), and sarcopenic obesity (SMI < 5.7 kg/m2 and PBF > 35%). Logistic regression analysis was used to adjust for age, body mass index, back pain, knee pain, history of falls, and physical function. Results Among the participants, 52 individuals (32.9%) were classified as frailty risk. The percentage of body phenotypes was 30.4% normal, 32.9% were sarcopenia, 22.8% had obesity (RT1), and 13.9% had sarcopenic obesity. The odds ratios for frailty risk compared to normal were 3.97 (95% confidence interval (CI): 1.51 to 10.4), 1.71 (95% CI: 0.55 to 5.39), and 4.25 (95% CI: 1.34 to 13.5) for sarcopenia (RT2), obesity, and sarcopenic obesity subtypes, respectively, sarcopenia and sarcopenic obesity were significantly associated with frailty risk. Conclusion In older adult women with LS, the presence of sarcopenia or sarcopenic obesity may increase the risk of frailty; however, the addition of obesity does not always further increase this risk. Further investigation of the association between increased body fat and frailty in older adult women is warranted.

Burden of frailty and its correlates among the elderly: a cross-sectional study in a rural community of West Bengal.

Context: With the ageing of Indian society, providing a healthy life among older people is a public health precedence. Therefore, beforehand discovery and possible forestalment of frailty may help promote healthy ageing and dwindle the social, mental and financial burden of their families and caregivers. Aims: The study aimed to assess the proportion of frailty and its associated factors among the elderly aged 65 years and above in a rural community of West Bengal. Settings and Design: A community-based cross-sectional study was conducted among 270 elderlies selected from 15 villages out of a total 64 villages of Singur under the Hooghly District of West Bengal from January 2019 to February 2020. Materials and Methods: Cluster sampling technique was used. Data was collected using a pre-designed, pre-tested structured schedule including Fried frailty phenotype (FFP), geriatric depression scale short form (GDS 15) and mini nutritional assessment (MNA) tool. Statistical Analysis Used: Associated factors of frailty were assessed by univariate and multivariable logistic regression using SPSS version 16 software and MS Excel 2019. Results: The proportion of frailty was observed to be 23.7% and that of prefrailty 40.7%. Frailty was significantly associated with increasing age [AOR(CI) 1.2(1.1-1.3)], decreasing years of schooling [AOR(CI) 1.3(1.1-1.5)], loss of spouse [AOR(CI) 4.2(1.2-15.2)], financial dependency [AOR(CI) 19.3(2.7-139.0)], staying at home [AOR(CI) 16.3(2.7-98.2)], presence of anaemia [AOR(CI) 3.6(1.3-9.5)], at risk of malnutrition [AOR(CI) 6.5(1.9-22.3)], increasing number of falls in the last 1 year [AOR(CI) 4.3(1.2-15.6)], presence of 3 or more chronic diseases [AOR(CI) 154.7(12.1-1981.9)] and depression [AOR(CI) 8.3(2.5-27.0)]. Conclusion: The burden of frailty among the study population is relatively high. It's an intimidating situation that needs bettered screening provisions for early discovery with special stress on nutritive upliftment. Screening for depression should also be done regularly.

A pilot study to identify factors associated with frailty within the World Trade Center general responder cohort.

BACKGROUND: Given the significant exposures experienced by the World Trade Center (WTC) general responders, there is increasing interest in understanding the effect of these exposures on aging in this population. We aim to identify factors that may be associated with frailty, a clinical syndrome characterized by a decrease in one's reserve that has been linked to poor health outcomes. METHODS: WTC general responders enrolled in the WTC Health Program aged 50 and older provided informed consent. Validated frailty assessments, the Frailty Phenotype (with the Johns Hopkins Frailty Assessment Calculator) along with the FRAIL scale, categorized nonfrail from prefrail/frail. Fall risk, functional status, and cognition were also assessed. WTC variables, including an identified WTC-certified condition, were utilized. The risk of frailty was estimated using log binomial regression analysis. A 95% confidence interval (CI) was used to estimate the prevalence ratio (PR). RESULTS: One hundred and six participants were included; 38 (35.8%) were classified as pre-frail or frail. More of the pre-frail/frail group were obese (57.9% vs. 25%; p = 0.004) and had a WTC-certified condition (78.9% vs. 58.8%; p = 0.036). Obesity (PR = 2.43, 95% CI = 1.31, 4.53), a WTC-certified condition (PR = 1.77, 95% CI = 1.09, 2.89), and risk of falling (PR = 1.97, 95% CI = 1.01, 3.84) were independently associated with frailty. CONCLUSIONS: Obesity and having a WTC-certified condition were found to be risk factors for frailty in our pilot study. Future work may focus on further identifying risk factors for frailty in the larger WTC general responder population.

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.

Prevalence of Frailty Phenotypes in Older People Living with HIV: A Cross-Sectional Study from Brazil.

BACKGROUND: Frailty may affect people living with HIV (PLHIV) prematurely. Fried's frailty phenotype, composed of 5 criteria, is one of the most used instruments for its assessment. This study aimed to determine the prevalence of these criteria among PLHIV classified as prefrail and frail in Brazil. METHODS: A cross-sectional study analyzed the prevalence of the Frailty Phenotype in Brazil with 670 individuals aged ≥ 50 years and undetectable viral load. RESULTS: The prevalence of prefrail and frail individuals was 50.7% and 13.6%, respectively. A low level of physical activity was the most prevalent criterion (50.9%). Except for unintentional weight loss, all other criteria were more prevalent among individuals with lower education levels. All criteria were more prevalent among individuals of lower socioeconomic status than among those of moderate or high status (P < .05). CONCLUSIONS: A low level of physical activity was the component that most contributed to PLHIV being considered prefrail or frail.

The intersection of frailty and metabolism.

On average, aging is associated with unfavorable changes in cellular metabolism, which are the processes involved in the storage and expenditure of energy. However, metabolic dysregulation may not occur to the same extent in all older individuals as people age at different rates. Those who are aging rapidly are at increased risk of adverse health outcomes and are said to be "frail." Here, we explore the links between frailty and metabolism, including metabolic contributors and consequences of frailty. We examine how metabolic diseases may modify the degree of frailty in old age and suggest that frailty may predispose toward metabolic disease. Metabolic interventions that can mitigate the degree of frailty in people are reviewed. New treatment strategies developed in animal models that are poised for translation to humans are also considered. We suggest that maintaining a youthful metabolism into older age may be protective against frailty.

FRAIL scale as a screening tool and a predictor of mortality in non-dialysis dependent patients.

BACKGROUND: This study aimed to compare the diagnostic yield of the FRAIL scale with respect to the physical frailty phenotype measure and their association with mortality in non-dialysis-dependent patients. METHODS: In this prospective cohort study, non-dialysis dependent patients with chronic kidney disease (CKD) stages 3b-5 seen in the nephrology outpatient clinics of two university hospitals were included. The presence of frailty was evaluated by physical frailty phenotype measure and the FRAIL scale. Patients were evaluated for six months, and mortality was recorded. The Kappa test was used to evaluate the diagnostic properties between the methods, and logistic regression to test the association between frailty and mortality. RESULTS: One hundred fifty-three patients were evaluated; average age was 65 (56-70) years, 50.9% were women, and the all-cause mortality rate was 2.6%. Forty-six patients were classified as living with frailty according to the physical frailty phenotype while 36 patients were rated frail by the FRAIL scale. In adults < 60 years of age, the FRAIL scale showed good accuracy (84.9%) and specificity (93.2%) but had low sensitivity (41.3%) and moderate agreement (Kappa = 0.41; p < 0.001) compared to the definition of the physical frailty phenotype. The adjusted logistic regression model showed that the patients with frailty assessed by the FRAIL scale had a greater chance of mortality than the non-frail patients (OR: 6.8; CI95%:1.477-31.513; p = 0.014). CONCLUSION: Physical frailty phenotype identifies more patients as having pre-frailty and frailty in non-dialysis dependent patients as compared to the FRAIL scale. However, the FRAIL scale is a simple bedside tool that can be useful for screening for frailty and whose results were associated with mortality.

Frailty and Cognitive Function in Middle-Aged and Older Adults With Congenital Heart Disease.

BACKGROUND: Life expectancy of patients with congenital heart disease (CHD) has increased rapidly, resulting in a growing and aging population. Recent studies have shown that older people with CHD have higher morbidity, health care use, and mortality. To maintain longevity and quality of life, understanding their evolving medical and psychosocial challenges is essential. OBJECTIVES: The authors describe the frailty and cognitive profile of middle-aged and older adults with CHD to identify predictor variables and to explore the relationship with hospital admissions and outpatient visits. METHODS: Using a cross-sectional, multicentric design, we included 814 patients aged ≥40 years from 11 countries. Frailty phenotype was determined using the Fried method. Cognitive function was assessed by the Montreal Cognitive Assessment. RESULTS: In this sample, 52.3% of patients were assessed as robust, 41.9% as prefrail, and 5.8% as frail; 38.8% had cognitive dysfunction. Multinomial regression showed that frailty was associated with older age, female sex, higher physiologic class, and comorbidities. Counterintuitively, patients with mild heart defects were more likely than those with complex lesions to be prefrail. Patients from middle-income countries displayed more prefrailty than those from higher-income countries. Logistic regression demonstrated that cognitive dysfunction was related to older age, comorbidities, and lower country-level income. CONCLUSIONS: Approximately one-half of included patients were (pre-)frail, and more than one-third experienced cognitive impairment. Frailty and cognitive dysfunction were identified in patients with mild CHD, indicating that these concerns extend beyond severe CHD. Assessing frailty and cognition routinely could offer valuable insights into this aging population.

Prevalence, factors and early outcomes of frailty among hospitalized older patients with valvular heart disease: A prospective observational cohort study.

AIM: The aim was to investigate the prevalence of, and factors related to frailty, together with early clinical outcomes, in hospitalized older patients with valvular heart disease (VHD) in China. DESIGN: A prospective observational cohort study was conducted. METHODS: A validated prospective survey was conducted to assess the prevalence of frailty, factors associated with it, and early clinical outcomes in hospitalized older patients with VHD, utilizing Fried's criterion. A total of 207 consecutive participants aged 65 years and older who underwent cardiac surgery were included in the study, spanning from September 2021 to December 2021. RESULTS: Frailty was detected in 78 patients (37.7%). Patients with multimorbidity, a New York Heart Association (NYHA) class of III/IV, or masticatory dysfunction had a greater incidence of frailty (p < 0.05). Patients with a normal albumin level and a higher frequency of exercise had a lower incidence of frailty (p < 0.05). Patients with frailty had longer hospital and intensive care unit stays and greater hospitalization costs than did those without frailty (p < 0.05). The 30-day adverse event rate of the frail group was also greater (11.5% vs. 3.1%). Therefore, early screening for conditions such as multimorbidity, cardiac dysfunction, and hypoalbuminemia is urgently needed to effectively address frailty, as it has been linked to unfavourable early outcomes. Moreover, promoting exercise and improving masticatory function and nutrition are crucial for preventing and managing frailty in older patients with VHD.

Screening for Frailty Using the FRAIL Scale in Older Cancer Survivors: A Cross-sectional Comparison With the Fried Phenotype.

OBJECTIVES: To examine the diagnostic performance of the FRAIL Scale for frailty screening with reference to the Fried phenotype and investigate its association with health outcomes in older cancer survivors. DATA SOURCE: In this cross-sectional quantitative study, participants were post-treatment cancer survivors aged 65 or above. Measurements included the FRAIL Scale, Fried phenotype, Geriatric Depression Scale-15 item, Modified Barthel Inventory, and EORTC Core Quality of Life Questionnaire. Receiver operating characteristic curve analysis was performed to evaluate the diagnostic performance of the FRAIL Scale with reference to the Fried phenotype. Health outcomes associated with being frail as estimated by the FRAIL Scale and Fried phenotype were also examined using regressions. RESULTS: Based on 293 older cancer survivors, the area under curve (AUC) of the FRAIL Scale was 0.79, and the optimal cut-off of 1 yielded a sensitivity of 92% and specificity of 41%. According to regression results, the FRAIL Scale was modified by adding an item on time since cancer treatment completion (AUC = 0.81), and using a cut-off of 2 for older cancer survivors, which yielded a sensitivity of 74% and specificity of 67%. The modified FRAIL Scale was associated with depressive symptoms, functional independence, fatigue, dyspnea, physical functioning, and role functioning. CONCLUSIONS: The modified FRAIL Scale is proposed for use in older cancer survivors, and a cut-off of 2 should be used. IMPLICATIONS FOR NURSING PRACTICE: The modified FRAIL Scale can serve as a brief screening tool for identifying frailty among older cancer survivors in practice.

Comparison of three frailty measures for predicting hospitalization and mortality in the Canadian Longitudinal Study on Aging.

BACKGROUND: Few studies have compared different measures of frailty for predicting adverse outcomes. It remains unknown which frailty measurement approach best predicts healthcare utilization such as hospitalization and mortality. AIMS: This study aims to compare three approaches to measuring frailty-grip strength, frailty phenotype, and frailty index-in predicting hospitalization and mortality among middle-aged and older Canadians. METHODS: We analyzed baseline and the first 3-year follow-up data for 30,097 participants aged 45 to 85 years from the comprehensive cohort of the Canadian Longitudinal Study on Aging (CLSA). Using separate logistic regression models adjusted for multimorbidity, age and biological sex, we predicted participants' risks for overnight hospitalization in the past 12 months and mortality, at the first 3-year follow-up, using each of the three frailty measurements at baseline. Model discrimination was assessed using Harrell's c-statistic and calibration assessed using calibration plots. RESULTS: The predictive performance of all three measures of frailty were roughly similar when predicting overnight hospitalization and mortality risk among CLSA participants. Model discrimination measured using c-statistics ranged from 0.67 to 0.69 for hospitalization and 0.79 to 0.80 for mortality. All measures of frailty yielded strong model calibration. DISCUSSION AND CONCLUSION: All three measures of frailty had similar predictive performance. Discrimination was modest for predicting hospitalization and superior in predicting mortality. This likely reflects the objective nature of mortality as an outcome and the challenges in reducing the complex concept of healthcare utilization to a single variable such as any overnight hospitalization.

Preconditioning Frailty Phenotype Influences Survival and Relapse for Older Allogeneic Transplantation Recipients.

Hematologic malignancies disproportionately affect older adults. Hematopoietic cell transplantation (HCT) is potentially curative, but poor overall survival (OS) has limited its use in older adults. Fried's frailty phenotype (FFP) is a geriatric assessment tool that combines objective and subjective performance measures: gait speed, grip strength, activity level, exhaustion, and weight loss. People meeting ≥3 criteria are classified as frail; 1 or 2 criteria, as pre-frail; and 0 criteria, as fit. To evaluate the association of pre-HCT FFP with post-HCT outcomes, we assessed FFP prior to conditioning for 280 HCT recipients age ≥60 years with acute leukemia or a myeloid neoplasm at 3 institutions. When analyzing survival by age group, patients age ≥70 years had inferior OS compared to patients age 60 to 69 years (P = .002), with corresponding OS estimates of 38.9% (95% confidence interval [CI], 27.8% to 49.9%) and 59.3% (95% CI, 51.9% to 65.9%). Nonrelapse mortality (NRM) also was significantly higher in the older patients (P = .0005); the 2-year cumulative incidences of NRM were 38.5% (95% CI, 27.5% to 49.2%) and 17.2% (95% CI, 12.3% to 22.8%), for older and younger recipients, respectively. The cumulative incidences of relapse did not differ by age group (P = .3435). Roughly one-third (35.5%) of the patients were fit, 57.5% were pre-frail, and 7.5% were frail, with corresponding 2-year OS estimates of 68.4% (95% CI, 57.9% to 76.8%), 45.5% (95% CI, 37.4% to 53.2%), and 45.8% (95% CI, 23.4% to 65.8%) (P = .013). FFP was not significantly associated with NRM, but being frail or pre-frail was associated with a higher rate of disease-related deaths (33.3% and 27.3%, respectively, compared with 17.4% for fit patients; P = .043). In univariate modeling of restricted mean survival time with a 3-year horizon (RMST_3y), the factors that were significantly associated were FFP, age, Karnofsky Performance Status (KPS), Disease Risk Index (DRI), and HCT-specific Comorbidity Index (HCT-CI). Of those factors, only FFP (P = .006), age (P = .006), KPS (P = .004), and DRI (P = .005) were significantly associated in multivariate modeling of RMST_3y. Estimates of RMST_3y were computed and 5 risk-groups were created with survival ranging from 31.4 months for those who were age 60 to 69 years, fit, had KPS 90 to 100, and low/intermediate-risk DRI compared to 10.5 months for those who had high-risk features for all the evaluated factors. In univariate and multivariate analyses for restricted mean time to relapse with a 3-year horizon (RMRT_3y), FFP (pre-frail versus fit, P = .007; frail versus fit, P = .061) and DRI (P = .001) were the only significant factors. Predicted RMRT_3y was longest (30.6 months) for those who were fit and had low/intermediate-risk DRI scores and shortest (19.1 months) for those who were frail and had high-risk or very high-risk DRI scores. Both age and FFP impact survival after HCT. Incorporation of FFP into pre-HCT evaluations may improve decision-making and counseling regarding HCT risk for older adults. Our findings support future trials designed to reverse frailty, such as pre-HCT supervised exercise programs, and correlative analyses to unravel the connection of frailty and relapse to generate future targets for intervention. Finally, exploration of novel HCT platforms to reduce relapse in pre-frail and frail patients, as well as reduce NRM in adults age >70 years, are warranted.

Demographic and biological factors in interrelationships between physical, cognitive, psychological, and social frailty in community-dwelling older adults: Data from the Birjand Longitudinal Aging Study (BLAS).

Complex interrelationships may exist among different types of frailty. This study aimed to evaluate the demographic and biological factors that influence the different types of frailty in community-dwelling older adults in Iran through a cross-sectional analysis of data obtained from the Birjand Longitudinal Aging Study. This study is an ongoing cohort study of people aged 60 years and over and employed a multistage stratified cluster random sampling. Anthropometric measures were obtained by nurses. The "Fried frailty phenotype" was defined as physical frailty. Cognitive frailty was assessed using the Mini-Mental State Examination. Social frailty was evaluated by some questions, and psychological frailty was assessed using a patient health questionnaire. Blood samples were taken after overnight fasting. All statistical analyses were performed using Stata12 (Texas, USA) and Python. Some type of frailty had been experienced by 62.27 % of the older adults. Cognitive frailty was the dominant type of frailty (55.69 %). Based on multivariate regression analysis, age, sex, education, and marital status were the influencing factors in all types of frailty. Network analysis revealed that physical, cognitive, psychological, and social frailty had synergistic effects on each other, and age and sex had dominant interactions with frailty types. Cognitive frailty was dominant compared with other types of frailty, indicating the need to detect cognitive frailty at the earliest stage and to implement an appropriate program to manage cognitive frailty in older adults.

Movement patterns during gait initiation in older adults with various stages of frailty: a biomechanical analysis.

BACKGROUND: Gait initiation is challenging for older individuals with poor physical function, particularly for those with frailty. Frailty is a geriatric syndrome associated with increased risk of illness, falls, and functional decline. This study examines whether spatial and temporal parameters of gait initiation differ between groups of older adults with different levels of frailty, and whether fear of falling, and balance ability are correlated with the height of lifting the food during gait initiation. METHODS: Sixty-one individuals aged > 65 years, classified by Fried frailty phenotype, performed five self-paced gait initiation trials. Data was collected using a three-dimensional passive optical motion capture system, consisting of 10 cameras with the ability to perceive reflective markers, and two force plates. The total duration of gait initiation and the duration of its four sub-phases, the first step length, and the maximum foot clearance during the first step were derived, and compared statistically between groups. Additionally, an association analysis was conducted between foot clearance and fear of falling, and confidence in balance in older individuals. RESULTS: Frail individuals had significantly longer unloading durations, and total durations of gait initiation compared to non-frail older adults. Additionally, they had shorter first step lengths compared to non-frail older adults. Pre-frail older adults also showed shorter steps compared to the non-frail group. However, there were no significant differences between groups for the maximum foot clearance during the first step. Nevertheless, the maximum foot clearance of older individuals correlated significantly with their fear of falling and confidence in balance. CONCLUSION: Older adults with reduced physical function and signs of frailty mainly display longer duration of gait initiation and decreased first step length compared to non-frail older adults. The release phase is decreased as the double support phase is prolonged in frail patients. This information can guide the development of specialized exercise programs to improve mobility in this challenging motion between static and dynamic balance.