Effect of non-pharmacological interventions in people with cognitive frailty: a systematic review and network meta-analysis.

ABSRTACT: OBJECTIVE: To evaluate the effects of various non-pharmacological interventions on patients with cognitive impairment by systematic search and network meta-analysis, and to rank the effects of the included non-pharmacological interventions. METHODS: The databases of PubMed, Cochrane Library, EMbase, Web of Science, CNKI, VIP, WANFANG, and SinoMed were searched by computer. All randomized controlled trials (RCTs) of non-pharmacological interventions for people with cognitive frailty were collected. The search was conducted from 2000 to February 2024. Two reviewers independently screened the studies, extracted data, and assessed the risk of bias of the included studies, and then used Stata15 and R4.3.1 software to conduct network meta-analysis, with physical function and cognitive function as the main outcome indicators. RESULTS: A total of 19 randomized controlled trials involving 1738 patients were included. The results of network meta-analysis showed that among the non-pharmacological interventions, nutritional support had the best effect on improving frailty scores and cognitive function scores in patients with cognitive frailty. Aerobic training combined with resistance training is best for improving grip strength. For improving the patient's motor status, cognitive training had the best effect on improving TUG test scores. High-speed resistance training is best for improving walking speed. CONCLUSION: This review analyses the current study of non-pharmacological interventions to improve physical performance in patients with cognitive frailty. Current evidence suggests that nutritional support is most effective at improving physical frailty and cognitive decline in patients with cognitive frailty, and that exercise and cognitive training interventions significantly improve grip strength and motor ability. TRIAL REGISTRATION: This meta-analysis was prospectively registered with PROSPERO (registration number: CRD42023486881).

Association of preoperative frailty with risk of postoperative delirium in older patients undergoing craniotomy: a prospective cohort study.

BACKGROUND: Preoperative frailty is a risk factor associated with postoperative delirium (POD), which has attracted more attention from clinicians, but no research has shown that it is related to elderly patients undergoing craniotomy. Therefore, the aim of this study was to determine the effect of preoperative frailty on POD in older patients, especially those who underwent craniotomy. METHODS: From October 2022 to May 2023, older patients who underwent elective craniotomy were collected. Assess the occurrence of frailty using the FRAIL scale one day before surgery. Evaluate the occurrence of POD using the Confusion Assessment Method (CAM) within three days after surgery. Participants were divided into two groups, one group being POD, Logistic regression analysis was used to find the risk variables for POD, and the predictive value of preoperative frailty to POD was determined by using the operating characteristic curve of the subjects. RESULTS: A total of 300 patients were included in this study, among whom 83 patients (27.7%) exhibited preoperative frailty and 69 patients (23.0%) experienced POD. The results of the multivariate logistic regression analysis indicate that preoperative frailty (OR: 8.816, 95% CI: 3.972-19.572), preoperative hypoalbuminemia (OR: 0.893, 95% CI: 0.811-0.984), low BMI (OR: 0.793, 95% CI: 0.698-0.901), and prolonged operative duration (OR: 1.007, 95% CI: 1.004-1.010) are independent risk factors for POD in older patients who underwent craniotomy. We constructed a risk prediction model using these factors, which had an area under the ROC curve of 0.908 (95% CI: 0.869-0.947, P < 0.001). Preoperative frailty enhanced the discriminative ability of the prediction model by 0.037. POD was associated with a longer length of hospital stay and higher hospitalization costs. CONCLUSIONS: Preoperative frailty is an independent risk factor for POD in older patients undergoing elective craniotomy and can predict the occurrence of POD to a certain extent. In addition, early identification of patients at risk of malnutrition and appropriate surgical planning can reduce the incidence of POD.

Association of dietary inflammatory index, composite dietary antioxidant index, and frailty in elderly adults with diabetes.

BACKGROUND: We aimed to examine the relationship of 2 dietary scores [dietary inflammatory index (DII) and composite dietary antioxidant index (CDAI)] with frailty in elderly adults with diabetes. METHODS: Data were gathered from the National Health and Nutrition Examination Survey (NHANES) between 2007 and 2018. The frailty index was calculated using 49 deficits across various systems to define frailty. To examine the relationship of 2 dietary scores (DII and CDAI) with frailty in elderly adults with diabetes, multiple logistic regression analyses were performed. In logistic regression model, DII and CDAI were calculated as both continuous and tertiles. Subgroup analyses were performed to demonstrate stability of results. Restricted cubic splines were utilized to examine the non-linear correlations. RESULTS: A total of 2,795 elderly adults with diabetes were included in this study. In the multivariate logistic regression model, the odds ratio (OR) of DII for risk of frailty was 1.08 (95% CI 1.02-1.15) and the OR of CDAI for risk of frailty was 0.96 (95% CI 0.93-0.99). The ORs of DII for risk of frailty were 1.36 (95% CI 1.09-1.70) and 1.33 (95% CI 1.04-1.70) for tertiles 2 and 3, respectively (p for trend 0.027). The ORs of CDAI for risk of frailty were 0.94 (95% CI 0.75-1.17) and 0.75 (95% CI 0.58-0.98) for tertiles 2 and 3, respectively (p for trend 0.036). The subgroup analysis demonstrated reliable and enduring connections between 2 dietary scores and frailty (all p for interaction > 0.05). In the restricted cubic spline analyses, we discovered the non-linear relationship between DII and frailty (P for nonlinearity = 0.045) and linear relationship between CDAI and frailty (P for nonlinearity = 0.769). CONCLUSION: The research showed connections between 2 dietary scores (DII and CDAI) and frailty as measured by frailty index in elderly adults with diabetes.

Ability of Heart Rate Recovery and Gait Kinetics in a Single Wearable to Predict Frailty: Quasiexperimental Pilot Study.

BACKGROUND: Aging is a risk factor for falls, frailty, and disability. The utility of wearables to screen for physical performance and frailty at the population level is an emerging research area. To date, there is a limited number of devices that can measure frailty and physical performance simultaneously. OBJECTIVE: The aim of this study is to evaluate the accuracy and validity of a continuous digital monitoring wearable device incorporating gait mechanics and heart rate recovery measurements for detecting frailty, poor physical performance, and falls risk in older adults at risk of falls. METHODS: This is a substudy of 156 community-dwelling older adults ≥60 years old with falls or near falls in the past 12 months who were recruited for a fall prevention intervention study. Of the original participants, 22 participants agreed to wear wearables on their ankles. An interview questionnaire involving demographics, cognition, frailty (FRAIL), and physical function questions as well as the Falls Risk for Older People in the Community (FROP-Com) was administered. Physical performance comprised gait speed, timed up and go (TUG), and the Short Physical Performance Battery (SPPB) test. A gait analyzer was used to measure gait mechanics and steps (FRAIL-functional: fatigue, resistance, and aerobic), and a heart rate analyzer was used to measure heart rate recovery (FRAIL-nonfunctional: weight loss and chronic illness). RESULTS: The participants' mean age was 74.6 years. Of the 22 participants, 9 (41%) were robust, 10 (46%) were prefrail, and 3 (14%) were frail. In addition, 8 of 22 (36%) had at least one fall in the past year. Participants had a mean gait speed of 0.8 m/s, a mean SPPB score of 8.9, and mean TUG time of 13.8 seconds. The sensitivity, specificity, and area under the curve (AUC) for the gait analyzer against the functional domains were 1.00, 0.84, and 0.92, respectively, for SPPB (balance and gait); 0.38, 0.89, and 0.64, respectively, for FRAIL-functional; 0.45, 0.91, and 0.68, respectively, for FROP-Com; 0.60, 1.00, and 0.80, respectively, for gait speed; and 1.00, 0.94, and 0.97, respectively, for TUG. The heart rate analyzer demonstrated superior validity for the nonfunctional components of frailty, with a sensitivity of 1.00, specificity of 0.73, and AUC of 0.83. CONCLUSIONS: Agreement between the gait and heart rate analyzers and the functional components of the FRAIL scale, gait speed, and FROP-Com was significant. In addition, there was significant agreement between the heart rate analyzer and the nonfunctional components of the FRAIL scale. The gait and heart rate analyzers could be used in a screening test for frailty and falls in community-dwelling older adults but require further improvement and validation at the population level.

Multidomain Intervention for the Reversal of Cognitive Frailty Using a Personalized Approach (AGELESS Trial): Recruitment and Baseline Characteristics of Participants.

BACKGROUND: Reversal of cognitive frailty through a multidomain intervention is desirable to prevent dementia. AGELESS Trial was conducted to determine the effectiveness of a comprehensive, multidomain intervention on older adults with cognitive frailty in Malaysia. However, conducting a clinical trial, particularly during and after Covid-19, posed unique challenges. OBJECTIVE: We aimed to investigate the recruitment process and baseline characteristics of the AGELESS Trial participants to better understand an at-risk population and those who agree to participate in an intervention. DESIGN/SETTING: 24-month, randomized controlled trial. PARTICIPANTS: Community-dwelling older adults with independent mobility, aged ≥ 60 years, with a mini mental state examination score of 19-25, a clinical dementia rating of 0.5 ≥ 1 Fried's physical frailty criteria, and < 22 Beck depression inventory. INTERVENTION: Participants were randomized 1:1 to a structured multidomain intervention consisting of vascular management, diet, exercise, cognitive and psychosocial stimulation, or to the arm, including routine care and general health consultation. MEASUREMENT: We analyzed the group differences between (1) cognitive frailty and non- cognitive frailty screened subjects, (2) recruited and non-recruited participants, (3) baseline characteristics of participants by arm, (4) adherence to AGELESS intervention at 12 months, and (5) preliminary findings on the effectiveness of the intervention at 12 months. RESULTS: A total of 957 older adults from two locations, i.e., urban (n = 764) and rural (n = 193) areas, were screened, of whom 38.9% had cognitive frailty and were eligible to participate. Those with cognitive frailty had fewer years of education (B = -0.08; 95%CI = 0.88-0.97; p = 0.002), and lower functioning cognition (B = -0.24; 95%CI = 0.74-0.84; p < 0.001). Among those from urban areas, only 33.1% (n = 106) agreed to participate, particularly those with multimorbidity (B = 0.86; 95%CI = 1.31-4.30; p = 0.01), higher physical activity (B = -1.02; 95%CI = 0.19-0.69; p = 0.002), slower walking speed (B = 1.26; 95%CI = 1.62-7.61; p = 0.001), and higher systolic blood pressure (B = 0.02; 95%CI = 1.00-1.03; p = 0.03). At baseline, participants' mean age was 68.1±5.6, years of education was 8.3±3.9, body mass index was 27.5±5.3 kg/m2, and mini mental state examination score was 22.7±4.0. Generally, there were no significant differences between the intervention and control groups for the main outcomes, except those in the intervention group had higher body mass index, mid-upper-arm circumference, and waist circumference (p < 0.05 for all parameters). Overall intervention adherence at 12 months was 52.8%, ranging from 52.8%-90.6% for each of the modules. Preliminary analysis of the effectiveness of the intervention at 12 months was positive on most of the cognitive domains, some of the nutrient intake and food groups, physical function, and vascular outcomes (p < 0.05 for all parameters). CONCLUSION: Despite the challenges posed by the pandemic, screening, recruitment, and 12-month intervention delivery were achieved in a Malaysian multidomain preventive randomized controlled trial in older adults at risk of dementia, with a satisfactory adherence rate and cognitive benefits at 12 months.

Frailty; Time for Global Action : Commentary on "Frailty and its Association with Long-Term Mortality among Community-Dwelling older adults aged 75 years and Over".

This commentary examines the study "Frailty and Its Association with Long-Term Mortality Among Community-Dwelling Older Adults Aged 75 Years and Over" by Lewis et al. The retrospective cohort study utilized data from a primary healthcare provider in Israel to investigate frailty using the Frailty Index (FI) and its correlation with long-term mortality. Nearly half of the older adult cohort was identified as frail, with a strong association between higher frailty levels and increased mortality risk. The commentary emphasizes the importance of routine frailty screening in clinical practice and health policy. Integrating FI calculations into electronic health records can facilitate timely care for high-risk individuals. However, presenting frailty data must be managed carefully and in conjunction with patients' preferences to avoid stigmatizing and negatively influencing clinical decisions. While the FI is a valuable tool, it should complement, not replace, other assessments that provide a more holistic view of the patient's health. Furthermore, the commentary strongly advocates for a more comprehensive approach to patient care, emphasizing that non-geriatricians must also be proficient in recognizing and managing frailty. Effectively addressing frailty can lead to significant cost savings for healthcare systems, reduced burden on healthcare facilities, and decreased need for long-term care.

Delirium and frailty in older adults: Clinical overlap and biological underpinnings.

Frailty and delirium are two common geriatric syndromes sharing several clinical characteristics, risk factors, and negative outcomes. Understanding their interdependency is crucial to identify shared mechanisms and implement initiatives to reduce the associated burden. This literature review summarizes scientific evidence on the complex interplay between frailty and delirium; clinical, epidemiological, and pathophysiological commonalities; and current knowledge gaps. We conducted a PubMed systematic search in June 2023, which yielded 118 eligible articles out of 991. The synthesis of the results-carried out by content experts-highlights overlapping risk factors, clinical phenotypes, and outcomes and explores the influence of one syndrome on the onset of the other. Common pathophysiological mechanisms identified include inflammation, neurodegeneration, metabolic insufficiency, and vascular burden. The review suggests that frailty is a risk factor for delirium, with some support for delirium associated with accelerated frailty. The proposed unifying framework supports the integration and measurement of both constructs in research and clinical practice, identifying the geroscience approach as a potential avenue to develop strategies for both conditions. In conclusion, we suggest that frailty and delirium might be alternative-sometimes coexisting-manifestations of accelerated biological aging. Clinically, the concepts addressed in this review can help approach older adults with either frailty or delirium from a different perspective. From a research standpoint, longitudinal studies are needed to explore the hypothesis that specific pathways within the biology of aging may underlie the clinical manifestations of frailty and delirium. Such research will pave the way for future understanding of other geriatric syndromes as well.

The temporal sequence and reciprocal relationships of frailty, social isolation and loneliness in older adults across 21 years.

BACKGROUND: It is unclear whether social isolation and loneliness may precede frailty status or whether frailty may precipitate social isolation and loneliness. We investigated the reciprocal and temporal sequence of social isolation, loneliness, and frailty among older adults across 21 years. METHODS: We used seven waves of the Longitudinal Aging Study Amsterdam from 2302 Dutch older adults (M = 72.6 years, SD = 8.6, 52.1% female) ages 55 or older. Using random intercept cross-lagged panel models, we investigated between- and within-person associations of social isolation and loneliness with frailty. Frailty was measured using the Frailty Index. Loneliness was measured using the 11-item De Jong Gierveld Loneliness Scale. Social isolation was measured using a multi-domain 6-item scale. RESULTS: Social isolation and loneliness were weakly correlated across waves. At the between-person level, individuals with higher levels of frailty tended to have higher levels of social isolation but not loneliness. At the within-person level, the cross-lagged paths indicated that earlier frailty status predicted future social isolation and loneliness over time. However, prior social isolation was not associated with subsequent frailty except at time point 5 (T5). Loneliness at specific time points (T1, T4 and T6) predicted greater frailty at later time points (T2, T5 and T7). The results also supported reciprocal and contemporaneous relations between social isolation, loneliness and frailty. CONCLUSIONS: Social isolation and loneliness are potential outcomes of frailty. Public health policies and health practitioners should prioritise interventions targeting social connection among older adults with pre-frailty or frailty.

Enhancing the convenience of frailty index assessment for elderly Chinese people with machine learning methods.

Frailty is a state that is closely associated with adverse health outcomes in the aging process. The frailty index (FI), which measures frailty in terms of cumulative deficits, has been widely used for frailty assessment in elderly people, and its advantage of self-reported information collection makes it applicable to a broader group of elderly people. Our study aims to simplify the Frailty Index Assessment Scale, while maintaining its reliability and accuracy, to easily and quickly assess frailty in elderly people. In this study, participants (age ≥ 65 years) from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), which had 13,339, 372 and 1214 participants in 2008, 2011, and 2014, respectively, were used. The 2008 dataset was split into 80% for training and 20% for internal validation, and the data from 2011 to 2014 as external validation. In order to obtain effective predictors, we used Lasso regression, Boruta algorithm and random forest classifier score for feature selection. We used six models for predictive model construction and evaluated the models in the validation dataset. Model performance was measured by area under the curve (AUC), accuracy and F1 score. Logistic regression was found to be the best performing and most interpretable algorithm with AUC, accuracy and F1 of 0.974, 0.932 and 0.880 for the validation dataset, respectively. The AUCs for the external independent validation dataset were 0.963 and 0.977, respectively. Subgroup analysis showed that the model had good predictive power in both males and females. The predictive power was stronger among the elderly people over 80 years old, with AUC, accuracy and F1 of 0.973,0.914, and 0.893, respectively. The model also obtained good predictive power in the case of FI measured by different indicators. The model showed good robustness in the follow-up assessment of frailty status in elderly people, with the AUC remaining above 0.95 and accuracy above 0.9 over the long-term follow-up. Using machine learning techniques, we have successfully developed a simple frailty assessment prediction model based on 10 key features to shorten the frailty assessment scale with near full-scale accuracy. A user-friendly website was created to facilitate the application of this prediction model ( https://healthy-aging.shinyapps.io/Frailty_Assessment/ ).

Association between physical activity and costs in very mild to moderately frail community-dwelling older adults: a cross-sectional study.

BACKGROUND: Physical activity (PA) plays a vital role in maintaining the functional ability that enables well-being in older age (healthy aging), potentially also saving costs for the healthcare system and society. The aim of this study was to examine the association between PA and healthcare and societal costs in a sample of very mild to moderately frail older adults. METHODS: This cross-sectional study is a secondary analysis using baseline data from the PromeTheus randomized-controlled trial, which included 385 very mild to moderately frail community-dwelling older adults (70 + years) from Germany. Participants self-reported their health-related resource use in the previous 6 months (FIMA questionnaire), which was monetarily valued using standardized unit costs. PA was also self-reported using the German Physical Activity Questionnaire for middle-aged and older adults (German-PAQ-50+) and categorized as 'insufficient'/'sufficient' or 'insufficient'/'moderate'/'high' in accordance with the World Health Organization guidelines for PA. Mean and median healthcare costs (including outpatient, inpatient, rehabilitation, formal care, and medication costs) and societal costs (healthcare costs plus informal care costs) for different PA groups were estimated using generalized linear models and quantile regression, with sociodemographic variables and physical capacity (Short Physical Performance Battery) as covariates. RESULTS: Of the sample, 24% were classified as insufficiently, 23% as moderately, and 54% as highly active. Sufficient PA, especially high PA, was associated with lower costs in the 6 months prior to data collection compared to insufficient PA (-€6,237, 95% CI [-10,656; -1,817] and -€8,333, 95% CI [-12,183; -4,483], respectively). The cost difference between PA intensity groups was largely driven by differences in informal care costs and decreased substantially when physical capacity was accounted for in the analyses; e.g., the mean difference in societal costs between sufficient and insufficient PA decreased from -€7,615 (95% CI [-11,404; -3,825]) to -€4,532 (95% CI [-7,930; -1,133]). CONCLUSION: Promoting PA throughout the lifespan as a means of promoting healthy aging and reducing dependency in old age could potentially provide economic benefits and help to mitigate the economic consequences of an aging population with increasing health and long-term care needs. Future longitudinal studies should attempt to disentangle the mediating and confounding role of physical capacity and health status in the association between PA and costs.

Regional variation in prevalence of frailty in India: Evidence from longitudinal ageing study in India (LASI) wave-1.

Background & objectives Frailty is a geriatric syndrome with clinical and public health implications. It represents the state of increased vulnerability. This study aimed to estimate the prevalence of frailty and pre-frailty by demographic characteristics and geographical regions in India. Furthermore, it also aimed to examine the association of this prevalence with selected health outcomes using data from the Longitudinal Ageing Study of India (LASI). Methods This is a secondary analysis of LASI wave-1 data. A total of 26,058 respondents aged ≥60 yr were included for analysis. Frailty was assessed using Fried's frailty phenotype, including slowness, shrinking, low physical activity, weakness, and low endurance. Descriptive statistics were used to study frailty distribution. The odds ratio (OR) of health events across the frailty categories was computed using ordinal logistic regression. Results The findings of this study suggest that the prevalence of frailty and pre-frailty was 29.2 and 58.8 per cent, respectively. The prevalence of frailty was higher among women (37.3%), illiterate (37%) and rural residents (31%). It ranged between 14.5 per cent in Uttarakhand and 41.3 per cent in Arunachal Pradesh. Frailty was strongly associated with depression [OR: 2.09, Confidence Interval (CI): 1.98-2.21] and activities of daily living (ADL) difficulty (OR: 1.75, CI: 1.64-1.86). Higher odds were reported for fracture (OR: 1.24, CI: 1.01-1.51) and multimorbidity (OR: 1.18, CI: 1.04-1.33) among frailty. Interpretation & conclusions The heterogeneity of frailty prevalence across States indicates the need for population-specific strategies. A sharp age-related increase in prevalence highlights the need for preventive measures. Furthermore, the high prevalence of frailty among women, illiterate and rural residents indicates the target population for receiving preventive interventions. Lastly, a heterogeneity in frailty prevalence across different States indicates the scope for region-specific programmes.

Association of Dietary Patterns, Suspected Sarcopenia, and Frailty Syndrome among Older Adults in Poland-A Cross-Sectional Study.

BACKGROUND: The association of sarcopenia and frailty syndrome with dietary patterns is not yet well recognized. THE AIM: The aim of the study was to evaluate the association among dietary patterns, suspected sarcopenia, and frailty syndrome among older people in Poland. METHODS: The study was conducted in 2022 and 2023 among people aged 55 and older. The sample was chosen arbitrarily. The following questionnaires were used in the study: the KomPAN (assessment of frequency of food intake and sociodemographic characteristics), the SARC-F (assessment of risk of sarcopenia), and the EFS (diagnosis of frailty syndrome). To confirm the suspicion of sarcopenia, muscle strength was assessed using the HGS and FTSST, and physical fitness was assessed using the GST. Based on the frequency of food consumption, 11 DPs (factors) were selected using PCA analysis. SARC-F, HGS, FTSST, and GST results were used to identify homogeneous groups (clusters) using cluster analysis, a k-means method. RESULTS: Two clusters were identified: cluster 1 (the non-sarcopenic cluster, or nSC) and cluster 2 (the sarcopenic cluster, or SC). Associations between variables were assessed using logistic regression. Suspected sarcopenia was found in 32.0% of respondents, more in men than women, and more among those either over 75 or 65 and under. EFS results showed that the risk (22.1%) or presence of frailty syndrome (23.8%) was more common in men than women and more common in those aged 75 and older than in other age groups. Male gender; older age; and unfavorable dietary patterns, i.e., consumption of white bread and bakery products, white rice and pasta, butter, and potatoes (factor 1) and cheese, cured meat, smoked sausages, and hot dogs (factor 9), increased the likelihood of sarcopenia and frailty syndrome, while the pattern associated with fruit and water consumption (factor 7) had the opposite effect. CONCLUSIONS: Confirmation of the importance of dietary patterns in the etiology and pathogenesis of sarcopenia and frailty syndrome should be documented in prospective cohort studies.

A hand-in-hand phenomenon in older adults: Increased risk of frailty in geriatric outpatients associated with handgrip strength asymmetry and weakness.

OBJECTIVES: Handgrip strength (HGS) is accepted as a predictor of overall health status and a biomarker of aging, besides negative health outcomes and mortality. While differences in HGS between the dominant and non-dominant hands are expected, substantial discrepancies may signal impaired muscle function. This study aims to investigate whether handgrip asymmetry can serve as a reliable indicator of frailty in a diverse population of older adults. DESIGN: Cross-sectional study. SETTING AND PARTICIPANTS: A total of 512 patients aged 65 years and older who were admitted to the geriatric medicine outpatient clinic of a university hospital were enrolled in the study. METHODS: The Clinical Frailty Scale (CFS) was used to assess the overall level of frailty of the study population. The highest recorded HGS values from the non-dominant and dominant hand were used to calculate the HGS ratio. Those with a HGS ratio of dominant and non-dominant hand <0.90 or >1.10 were defined as HGS asymmetry. RESULTS: Of the whole study group, 61.1% was female and the mean age was 73.2 ± 6.1 years. The ratio of the participants living with frailty was 57.6% (n = 219). The number of patients with HGS asymmetry was 264 (51.6%), and 48.4% (n = 248) of the study population had symmetric HGS. The normal and symmetric HGS was found in 40.2% of the non-frail group, whereas it was 23.7% in patients living with frailty. Furthermore, the ratio of low and asymmetric HGS was 16.3% in the non-frail group, and 35.0% in the patients living with frailty (p < 0.001). The presence of asymmetric and low HGS increased the risk of frailty three times independently of other confounding factors (OR:3.08; 95% CI:1.48-6.43; p = 0.003). CONCLUSIONS AND IMPLICATIONS: Identifying HGS asymmetry along with low HGS as potential indicators of frailty may provide clinicians with a clear and quantifiable criterion for assessing older patients.

Knowledge mapping of frailty and surgery: a bibliometric and visualized analysis.

PURPOSE: Frailty is common in surgical patients and is closely associated with postoperative outcomes. AIMS: This study employed bibliometric methods to summarize and analyze research related to frailty and surgery, comprehensively analyzing the research structure and providing visualized maps. METHODS: This study analyzed the volume of publications, countries, institutions, authors, journals, references, and keywords related to perioperative frailty in the Web of Science Core Collection from 1978 to 2024. Visual bibliometric analyses were conducted from multiple perspectives, including collaboration networks, citation analysis, and keyword clustering. RESULTS: From 1978 to 2024, 21,879 authors from 95 countries and regions published 4,119 papers on perioperative frailty in 973 journals worldwide. The United States has the most publications, while Italy has the highest degree of international collaboration. The University of California System has the highest number of publications. The University of Kansas Medical Center is the institution with the highest centrality. The top nine authors in terms of publication volume are all from the USA. Bowers Christian A. is the most prolific author. The Journal of Vascular Surgery is the journal with the most publications. Current research directions include preoperative risk assessment of frailty, the relationship between frailty and postoperative complications, elderly frailty, and the relationship between frailty and sarcopenia. Research hotspots include risk stratification, postoperative delirium, the elderly, and sarcopenia. CONCLUSION: This study has identified the research hotspots and trends in perioperative frailty. Our findings will enable researchers to understand this field's knowledge structure better and identify future research directions.

Independent and combined associations of depression and cognitive impairment with frailty in oldest-old adults.

BACKGROUND: Frailty is one of the most significant issues related to human aging. Although studies have confirmed the association of mental and cognitive disorders with frailty, the association might be influenced by age, since oldest-old adults are more likely to have adverse health outcomes. Thus, this study aimed to examine independent and combined associations of mental health and cognitive function with frailty in oldest-old adults using data from the Chinese Longitudinal Healthy Longevity Survey in 2018. METHODS: A sum of 6,891 and 3,171 older adults aged 80 and older were included in this study when analyzing the association of depression and cognitive impairment with frailty, respectively. Frailty was measured by the Study of Osteoporotic Fractures frailty index, depression was assessed by the Center for Epidemiologic Studies Depression Scale, and cognitive impairment was evaluated by the Chinese version of modified Mini-Mental State Examination. Independent sample t-test, Chi-square tests, and logistic regression analyses were used to examine the associations of depression and cognitive impairment with frailty. RESULTS: Older persons with depression or cognitive impairment had a higher chance of frailty. The adjusted odds ratio (OR) of frailty was 1.27 (95% CI: 1.01, 1.59, p = 0.044) in those with depression, and 1.85 (95% CI: 1.14, 3.01, p = 0.013) in those with cognitive impairment. Compared to adults who had neither depression nor cognitive impairment, those with either depression or cognitive impairment, and those with both depression and cognitive impairment had a significantly higher likelihood of frailty (adjusted OR: 1.61, 95% CI: 1.07, 2.41; and adjusted OR: 4.03, 95% CI: 2.05, 7.94). CONCLUSIONS: The findings suggest that depression and cognitive impairment are associated with frailty. The concurrence of depression and cognitive impairment has an additive effect on frailty in oldest-old population.

The association between frailty, care receipt and unmet need for care with the risk of hospital admissions.

BACKGROUND: Frailty is characterised by a decline in physical, cognitive, energy, and health reserves and is linked to greater functional dependency and higher social care utilisation. However, the relationship between receiving care, or receiving insufficient care among older people with different frailty status and the risk of unplanned admission to hospital for any cause, or the risk of falls and fractures remains unclear. METHODS AND FINDINGS: This study used information from 7,656 adults aged 60 and older participating in the English Longitudinal Study of Ageing (ELSA) waves 6-8. Care status was assessed through received care and self-reported unmet care needs, while frailty was measured using a frailty index. Competing-risk regression analysis was used (with death as a potential competing risk), adjusted for demographic and socioeconomic confounders. Around a quarter of the participants received care, of which approximately 60% received low levels of care, while the rest had high levels of care. Older people who received low and high levels of care had a higher risk of unplanned admission independent of frailty status. Unmet need for care was not significantly associated with an increased risk of unplanned admission compared to those receiving no care. Older people in receipt of care had an increased risk of hospitalisation due to falls but not fractures, compared to those who received no care after adjustment for covariates, including frailty status. CONCLUSIONS: Care receipt increases the risk of hospitalisation substantially, suggesting this is a group worthy of prevention intervention focus.

The Geriatric Patient: Frailty, Prehabilitation, and Postoperative Delirium.

Historically and for ease of classification, the geriatric patient has received a chronologic definition of a person 65 years and older. Chronologic age remains an independent risk of postoperative complications and adverse surgical outcomes. Frailty is an expression of an individual's biological age and as such a more reliable determination of their vulnerabilities or resilience to stress. The concept of prehabilitation has shown promise as a proactive approach to optimize a patient's functional, cognitive, nutritional, and emotional in preparation for surgical interventions. Postoperative delirium is the most common neuropsychological complication after surgery.

The application of machine learning for identifying frailty in older patients during hospital admission.

BACKGROUND: Early identification of frail patients and early interventional treatment can minimize the frailty-related medical burden. This study investigated the use of machine learning (ML) to detect frailty in hospitalized older adults with acute illnesses. METHODS: We enrolled inpatients of the geriatric medicine ward at Taichung veterans general hospital between 2012 and 2022. We compared four ML models including logistic regression, random forest (RF), extreme gradient boosting, and support vector machine (SVM) for the prediction of frailty. The feature window as well as the prediction window was set as half a year before admission. Furthermore, Shapley additive explanation plots and partial dependence plots were used to identify Fried's frailty phenotype for interpreting the model across various levels including domain, feature, and individual aspects. RESULTS: We enrolled 3367 patients. Of these, 2843 were frail. We used 21 features to train the prediction model. Of the 4 tested algorithms, SVM yielded the highest AUROC, precision and F1-score (78.05%, 94.53% and 82.10%). Of the 21 features, age, gender, multimorbidity frailty index, triage, hemoglobin, neutrophil ratio, estimated glomerular filtration rate, blood urea nitrogen, and potassium were identified as more impactful due to their absolute values. CONCLUSIONS: Our results demonstrated that some easily accessed parameters from the hospital clinical data system can be used to predict frailty in older hospitalized patients using supervised ML methods.