Previous studies have confirmed a correlation between physical frailty and impairment of activities of daily living (ADL) in the elderly, but it is still unclear whether there is a correlation of psychological and social frailty in the elderly with their ADL impairment.

To investigate the multi-dimensional frailty of the elderly in rural areas and the correlation of dimensions with ADL impairment, so as to provide evidence for preventing disability rural older adults.

A cross-sectional study was conducted, older adults aged ≥60 years from 30 administrative villages in 2 cities of Guizhou Province were selected for the study from July to September 2021 (n=1 298) by using a multi-stage cluster sampling method. The demographic characteristics, prevalence of chronic diseases and sleep quality of the subjects were collected by questionnaire, and the multi-dimensional frailty of the elderly was assessed by Chinese version of Tilburg debilitating scale, ADL scale was used to assess the impairment of ADL in the elderly, multivariate Logistic regression was used to analyze the effects of multi-dimensional frailty and its dimensions on the impairment of ADL in the elderly, and the multifactor-adjusted population attributable risk percentage (PARc%) was calculated.

Of the 1 298 older adults, 498 (38.37%) were with ADL impairment, 40 (3.08%) were with BADL impairment, 494 (38.06%) were with IADL impairment; 382 (29.43%) were with multi-dimensional frailty, 319 (24.58%) were with physical frailty, 567 (43.68%) were with psychological frailty, and 69 (5.32%) were with social frailty. After adjusting for confounding factors of age, gender, education level, marital status, and sleep quality, the results of binary Logistic regression analysis showed that multi-dimensional frailty, physical frailty, and psychological frailty in older adults had effects on and ADL, BADL and IADL impairments (P<0.05). Further analysis of the population attribution risk of multi-dimensional frailty, physical frailty, and psychological frailty for ADL showed that multi-dimensional frailty had the greatest population attributable risk for BALD impairment [PARc% (95%CI) =24.6 (19.1-27.1) ], psychological frailty had a relatively high population attributable risk for ADL impairment [PARc% (95%CI) =18.4 (12.1-24.5) ], BADL impairment [PARc% (95%CI) =23.6 (3.2-33.7) ], and IADL impairment [PARc% (95%CI) =19.4 (12.4-24.7) ] .

The multi-dimensional frailty, physical frailty and psychological frailty of the rural elderly in Guizhou province are related to the impairment of ADL, BADL and IADL, with greater attribution of psychological frailty for disability. Enhancing screening and interventions for multi-dimensional frailty in older adults, particularly psychological frailty, may reduce the risk of disability in older adults.

Previous studies have shown that self-rated health would be used as a simple assessment indicator for frailty, and individuals with poor self-rated health status are at higher risk of frailty. However, the association between self-rated health and frailty may be different and the effectiveness of self-rated health in frailty assessment may vary in apathetic older adults.

To explore the moderating role of apathy in the association between self-rated health and frailty among community-dwelling older adults, so as to provide theoretical guidance for the application of the self-rated health in the assessment of frailty in apathetic older adults.

From November 2021 to March 2022, a total of 384 community-dwelling older adults were selected as respondents by convenience sampling method, including 179 cases in Nanjing Dongshan Community and 205 cases in Lianyungang Qinghu Community. Questionnaire surveys were conducted using the General Information Questionnaire, Fried Frailty Phenotyp (FFP) , Geriatric Depression Scale (GDS-3) , and the self-reported health (SRH) . Generalized linear model was used to analyze the association between self-rated health and frailty of community-dwelling older adults. The model 1 of the SPSS macro program process compiled by Hayes was used to analyze the moderating role of apathy on the association between the self-rated health and frailty, with simple slope analyze performed and simple slope graphs plotted.

The median FFP and SRH item scores of 384 community-dwelling older adults were 1.00 (2.00) and 4.00 (1.00) , respectively, with the detection rate of apathy of 55.5% (213/384) . The results of the generalized linear model showed that the relationship between the self-rated health and frailty of community-dwelling older adults was significant (b=0.310, P<0.001) . The results of the moderating effect test showed that apathy played a moderating role in the relationship between self-rated health status and frailty in community-dwelling older adults (b=0.355, t=3.074, P=0.002) , and the results of simple slope analysis showed that the simple slope of the non-apathy group and apathy group was 0.100 (t=1.209, P=0.228) and 0.455 (t=5.206, P<0.001) respectively.

There is an association between self-rated health and frailty in community-dwelling older adults, and the application of the self-rated health can help community health workers assess frailty in older adults. Apathy plays a moderating role in the relationship between self-rated health and frailty. Compared with the non-apathetic older adults, the association between self-rated health and frailty is significant in apathetic older adults. Strengthening the self-rated health assessment of older adults is beneficial to the identification of their frailty.

The prevalence of comorbidity in the elderly is showing a rising trend year by year with the acceleration of population aging. Comorbidity is a key risk factor for frailty in the elderly. Then frailty only increases the risk of adverse health outcomes for patients with comorbidity, but also significantly increases their family medical expenses. It has a certain guiding value for the management of comorbidity to identify the frailty conditions of elderly patients with comorbidity as early as possible.

To systematically review the prevalence of frailty in elderly patients with comorbidity.

CNKI, VIP, CBM, WanFang, PubMed, EmBase, Web of Science and Cochrane Library were searched in December 2021 for the investigation studies on the current status of frailty in elderly patients with comorbidity published from inception to December 4, 2021. Two researchers performed literature screening and data extraction independently. The cross-sectional study quality rating scale and Newcastle-Ottawa Scale (NOS) recommended by Agency for Healthcare Research and Quality (AHRQ) were used to assess the risk of bias of the included studies and Stata 14.0 was adopted for meta-analysis.

A total of 25 studies involving 16 062 elderly patients with comorbidity were included. Meta-analysis results showed that the prevalence of frailty and pre-frailty in elderly patients with comorbidity was 26.7%〔95%CI (21.9%, 31.5%) 〕and 47.7%〔95%CI (43.9%, 51.4%) 〕. Subgroup analysis showed that the prevalence of frailty in older adults with≥2, ≥3, ≥4, and≥5 chronic diseases was 25.1%〔95%CI (19.3%, 30.8%) 〕, 27.4%〔95%CI (13.7%, 41.0%) 〕, 60.7%〔95%CI (29.0%, 92.4%) 〕, and 23.5%〔95%CI (8.6%, 38.5%) 〕, respectively. The prevalence of frailty in elderly patients with comorbidity in Oceania (52.1%) and Asia (31.3%) were significantly higher than Europe (16.9%) and South America (13.2%) . The prevalence of frailty in elderly patients with comorbidity in hospital (26.2%) was significantly higher than community (23.2%) . The prevalence of frailty in elderly patients with comorbidity screened by Clinical Frailty Scale (CFS) , Fried frailty phenotype scale and FRAIL Scale was 42.8%〔95%CI (38.4%, 47.1%) 〕, 22.2%〔95%CI (17.8%, 26.7%) 〕and 8.5%〔95%CI (6.3%, 10.6%) 〕, respectively. The prevalence of frailty in elderly patients surveyed in 2001—2010, 2011—2015, and 2016—2020 was 21.0%〔95%CI (13.2%, 28.8%) 〕, 19.0%〔95%CI (13.1%, 24.8%) 〕and 37.7%〔95%CI (22.6%, 52.9%) 〕, respectively.

The prevalence of frailty in elderly patients with comorbidity is gradually increasing, with differences by number of co-morbidities, continents, assessment tools and study sites. Therefore, relevant personnel should pay attention to early screening of frailty in elderly patients with comorbidity and take timely measures to prevent the development of frailty in elderly patients with comorbidity.

At present, there are few intervention studies on cognitive frailty in elderly diabetic patients. This study aims to explore the application effect of Baduanjin combined with cognitive training in elderly diabetic patients with cognitive frailty, in order to provide reference for the management of this population.

To explore the intervention effect of Baduanjin combined with cognitive training on elderly diabetic patients with cognitive frailty.

A total of 84 elderly diabetic patients with cognitive frailty hospitalized in the Department of Endocrinology, Shanxi Provincial People's Hospital from October 2021 to April 2022 were selected as research subjects by convenient sampling method, and randomly divided into the experimental group (n=42) and the control group (n=42) according to the random number table method. The patients in the experimental group received Baduanjin exercise combined with cognitive training, 3 times per week for 12 weeks; patients in the control group were given routine exercise and health education. General data of the patients were collected, including gender, age, education level, marital status, residential status, personal monthly income, type of medical insurance and number of comorbid chronic diseases. The Montreal Cognitive Assessment (MoCA) score, Frailty Phenotype (FP) score, gait speed, grip strength and glycated hemoglobin A1c (HbA_1c) were compared at baseline, 6 weeks and 12 weeks of intervention between the two groups.

During the study period, 3 cases were lost to follow-up in the control group and 2 cases were lost in the experimental group, a total of 79 patients were finally included (39 cases in the control group and 40 cases in the experimental group) . There was no significant difference in the general data between the two groups (P>0.05) . There were interaction effects of group and time on MoCA score, FP score, gait speed and grip strength (P<0.05) . MoCA score of patients in the experimental group was higher than that in the control group at 12 weeks of intervention (P<0.05) , and higher than that at baseline and 6 weeks of intervention (P<0.05) . FP score of patients in the experimental group was lower than that in the control group at 12 weeks of intervention, and lower than that at baseline and 6 weeks of intervention (P<0.05) . Gait speed and grip strength of patients in the experimental group were higher than those in the control group at 12 weeks of intervention, and higher than those at baseline and 6 weeks of intervention (P<0.05) . HbA_1c level of patients in the experimental group was lower than that in the control group, and lower than that at baseline at 12 weeks of intervention (P<0.05) .

Baduanjin combined with cognitive training can slow down the decline of cognitive function in elderly diabetic patients, improve physical frailty and reduce the blood glucose level of patients, which is suitable for vigorously promoting in the clinical and community settings.

With the aggravation of population aging in China, the number of elderly perioperative orthopedic patients is increasing, and the growing prevalence of frailty in older patients undergoing orthopedic surgery has attracted increasing attention. Early preoperative assessment and intervention of frailty are of great significance for improving postoperative prognosis and reducing the occurrence of complications in this population.

To perform a scoping review of frailty assessment tools for elderly orthopedic inpatients, and to provide a reference for the selection of frailty assessment tools for this group.

Seven databases (PubMed, CINAHL, PsycINFO, Scopus, Embase, CNKI and Wanfang Data) were searched for studies on frailty assessment tools for older orthopedic inpatients from 2006 to 2021. Two researchers independently screened the literature and extracted the basic characteristics of the literature (the flint author, publication time, country, basic information, research tools and outcome indicators) and the basic characteristics of involved frailty assessment tools (name, study country, study type, scale dimension, number of items, assessment cut-off value, assessment time, etc.) .

A total of 1733 studies were retrieved, and 25 of them with 12 frailty assessment tools were included. The analysis showed that there are a variety of assessment tools, and different studies have used different frailty assessment tools. Frailty Phenotype and Frailty Index are the two common tools. The application of accurate and effective tools for frailty screening is crucial to improving preoperative risk stratification and postoperative prognosis. Frailty assessment using the Reported Edmonton Frail Scale, FRAIL Scale, PRISMA-7 Questionnaire or the Groningen Frailty Index can be completed without the use of additional measuring equipment and surveyors with an experience of training.

The selection of an optimal frailty assessment tool for elderly orthopedic inpatients should be in accordance with patient features, clinical resources and the performance of the tool. However, there is still lack of a gold standard for frailty assessment. Future studies are needed to assess the reliability and validity of existing frailty assessment scales or to develop frailty assessment tools applicable to Chinese older orthopedic inpatients.

Frailty can increase the risk of negative health-related outcomes in older adults. Protein supplementation may be an effective way to improve frailty, but there is disagreement about its effects on frailty.

To systematically evaluate the effects of protein supplementation on muscle mass, strength, and physical function in frail/pre-frail older adults.

Electronic databases of CNKI, Wanfang Data, CQVIP, PubMed, Embase, Web of Science, Cochrane Library, CINAHL and Medline were retrieved for randomized controlled trials (RCTs) of the effects of protein supplementation on muscle mass, strength and physical function in frail/pre-frail older adults published from inception to June 2022. After literature screening, the quality of eligible RCTs was evaluated, and from which relevant data were extracted. RevMan 5.4 was performed to explore the effects of protein supplementation on muscle mass, muscle strength and physical function in frail/pre-frail older adults. And for the outcome indicator of muscle strength (grip strength) , due to large amount of reported literature, this study will be based on the amount of protein supplementation (<30 g/d subgroup and≥30 g/d subgroup) , frailty status (pre-frailty subgroup, frailty subgroup, frailty and pre-frailty subgroup) , frailty assessment tool 〔frailty phenotype assessment tool (FP) subgroup and non-FP subgroup〕, population (Asian subgroup and European subgroup) , and mean age (70-<75 years subgroup, 75-<80 years subgroup, and 80-<85 years subgroup) for subgroup analysis to further explore the effect of protein supplementation on grip strength in different subgroups.

A total of 12 RCTs were included (2 literatures for pre-frailty, 3 literatures for frailty, 7 literatures for frailty and pre-frailty) , with a total of 833 older adults (422 in the protein supplementation group and 411 in the control group) . Meta-analysis results showed that protein supplementation improved gait speed in frail/pre-frail older adults〔MD=0.03, 95%CI (0, 0.06) , P=0.05〕, but in improving muscle mass (appendicular lean mass) , muscle strength (grip strength) , other physical functions (assessment results of balance test, the timed up and go test, Short Physical Performance Battery) and frailty scores, the differences were not statistically significant (P>0.05) . The results of subgroup analysis showed that the effect of protein supplementation on the grip strength of the Asian population subgroup was significantly different from that of the European population subgroup in between-group comparisons (χ²=5.76, P=0.02) .

Protein supplementation may improve gait speed in frail/pre-frail older adults, but it does not show a significant advantage in improving their muscle mass, muscle strength and other physical functions. It is recommended to further investigate the effects of longer durations of supplementation, different types of protein supplemented, different amounts of supplementation and different regional populations on older adults with different frailty states, in order to find the best pattern of protein supplementation and provide a more sufficient evidence-based basis for frailty management.

As an important modifiable factor that can be intervened, nutrition is closely related to the occurrence of frailty. Early identification of frailty through nutrition evaluation and reversal of its occurrence is of great significance for improving clinical outcomes. There are few available studies on the predictive value of nutrition-related parameters for frailty among older patients in the emergency department (ED) .

To evaluate the relationship between commonly used nutrition-related parameters and frailty among older adults in the ED.

Two hundred and ten people aged≥65 years were recruited from the Department of Emergency Medicine, China Rehabilitation Research Center (Beijing Bo'Ai Hospital) from January to October 2021. The demographic data were recorded. Fasting venous blood sample was collected within 24 hours after admission to measure routine indicators. The nutritional risk was assessed by Nutrition Risk Screening 2002 (NRS2002) . The basic activities of daily living were evaluated by Barthel Index (BI) . The Clinical Frailty Scale (CFS) was used to assess frailty, and individuals with CFS levels 1-4 (n=68) and those with CFS levels 5-9 (n=142) were assigned to non-frail group and frail group, respectively. Multivariable Logistic regression was used to analyze the factors associated with frailty in older patients in the ED. Hosmer-Lemeshow test and receiver operating characteristic (ROC) curve were used to evaluate the predictive validity of nutrition-related parameters for frailty in older patients in the ED. Nonparametric DeLong test was used to compare the area under the ROC curve (AUC) of each parameter.

There were statistically significant differences between frail and non-frail patients in mean age, sex ratio, mean body mass index (BMI) , prevalence of coronary heart disease, mean levels of hemoglobin (HGB) , albumin (ALB) , prealbumin (PA) , high-sensitivity C-reactive protein (hs-CRP) and 25-hydroxyvitamin D〔25 (OH) D〕, and mean score of NRS2002, as well as mean BI and length of hospital stay (P<0.05) . Multivariable Logistic regression analysis showed that higher PA〔OR=0.943, 95%CI (0.891, 0.998) , P=0.041〕 and 25 (OH) D〔OR=0.909, 95%CI (0.844, 0.979) , P=0.012〕were protective factors of frailty in older patients in the ED. The risk of frailty decreased by 44.6% for every 100 mg/L increase in PA, and decreased by 61.7% for every 10 μg/L increase in 25 (OH) D. However, higher NRS2002 score〔OR=1.701, 95%CI (1.353, 2.138) , P<0.001〕was the risk factor of frailty in older patients in the ED, and the risk of frailty increased by 70.1% for every one score increase in NRS2002 score. Hosmer-Lemeshow test showed PA (χ²=6.120, P=0.634) , 25 (OH) D (χ²=5.386, P=0.716) and NRS2002 score (χ²=4.758, P=0.446) had good goodness of fit. ROC analysis demonstrated showed that the optimal cutoff values of PA, 25 (OH) D and NRS2002 score for predicting frailty in older patients in the ED were 211.9 mg/L, 7.06 μg/L and 3 points, respectively, and the AUCs of them were 0.749, 0.670 and 0.835, respectively. Nonparametric DeLong test showed that the AUC of NRS2002 score was greater than that of PA (Z=2.241, P=0.025) and 25 (OH) D (Z=3.400, P<0.001) .

As frail patients have poor nutritional status, nutritional assessment contributes to early identification of frailty. Among the nutrition-related parameters, PA, 25 (OH) D and NRS2002 score can effectively predict frailty in older patients in the ED, and NRS2002 score may have the strongest predictive ability.

Frailty is common in cancer patients, which seriously affects their prognosis. However, the factors associated with frailty in cancer patients are not clear at present.

To identify the factors associated with frailty in cancer patients by a meta-analysis, to provide a scientific basis for the development and implementation of related interventions.

The databases of China National Knowledge Infrastructure (CNKI), CQVIP, WanFang Data, PubMed, Web of Science, Cochrane Library, CINAHL and Embase were comprehensively and systematically searched from inception to August 2022 for included cross-sectional studies, cohort studies or case-control studies reporting associated factors of frailty in cancer patients. Two researchers screened the literature and performed quality evaluation and data extraction. Stata 17.0 and RevMan 5.4 were used for meta-analysis.

Eleven studies were included, among which nine were cross-sectional studies and the other two were cohort studies. Altogether, 2 898 cancer patients were studied, among whom 1 025 were frail, and 12 associated factors of frailty were reported. Meta-analysis showed that the prevalence of frailty in all cancer patients, lung cancer patients, digestive cancer patients, and other cancer patients was 34%〔95%CI (23%, 45%) 〕, 31%〔95%CI (25%, 36%) 〕, 42%〔95%CI (26%, 59%) 〕, and 12%〔95%CI (9%, 16%) 〕, respectively. The risk of frailty in cancer rose with advanced age〔OR=1.16, 95%CI (1.05, 1.27) 〕, combined with other diseases〔OR=1.46, 95%CI (1.28, 1.67) 〕, high BMI〔OR=1.13, 95%CI (1.05, 1.21) 〕, poor nutritional status〔OR=2.77, 95%CI (1.27, 6.06) 〕, high syndrome group scores〔OR=1.07, 95%CI (1.04, 1.09) 〕and depression〔OR=1.27, 95%CI (1.12, 1.44) 〕, but decreased with high education level〔OR=0.78, 95%CI (0.68, 0.90) 〕, albumin level≥35 g/L〔OR=0.33, 95%CI (0.12, 0.90) 〕and high level of instrumental activities of daily living (IADL) 〔OR=0.50, 95%CI (0.42, 0.59) 〕. Egger's test assessing the potential publication bias in 11 studies via funnel plot asymmetry showed that there was a certain publication bias (t=-4.12, P=0.003) .

This meta-analysis revealed that age, education level, comorbidity, BMI, albumin, nutritional status, syndrome group, depression and IADL were the associated factors of frailty in cancer patients. It is necessary for health professionals to pay more attention to cancer patients with advanced age, low education level, combined with other diseases, high BMI, albumin level <35 g/L, poor nutritional status, with syndrome group, depression or low-level activities of daily living, so as to prevent the occurrence of frailty.

Early diagnosis of frailty is of great value in helping the elderly to regain their health, as it is a non-specific state of reduced physiological reserve, resistance to disease and ability to recover from stress caused by the impairment in homeostasis maintained by multiple systems with sarcopenia as the basic characteristic. Recent developments in multiomic techniques provide new approaches to the detection of potentially specific, stable and reliable biomarkers of pre-frailty. We collected and reviewed recent advances in multiomic techniques for identifying frailty biomarkers, involving genomics, transcriptomics, proteomics and metabolomics, which can assist in assessing the risk of frailty, exploring potential mechanisms of frailty and developing targeted interventions to support healthy aging.

Preoperative frailty is a severely unhealthy status that reflects the reduction of overall physiological reserve, which is highly prevalent in elderly patients with gastric cancer. Understanding the perceived influencing factors of preoperative frailty can provide an important basis for developing individualized intervention plans.

To perform a qualitative descriptive study to identity the perceived influencing factors of preoperative frailty among elderly gastric cancer patients using the theory of health ecology.

A qualitative descriptive study was conducted based on health ecology theory. Purposive sampling method was used to select 29 frail elderly patients who would undergo gastric cancer surgery in the First Affiliated Hospital with Nanjing Medical University from February to June 2021 for semi-structured interview. Directed content analysis was used for data analysis.

Five themes and thirteen sub-themes were extracted: physiological traits, including accumulated aging-related losses, obvious gastrointestinal symptoms, and successive attacks of multiple diseases; behavioral characteristics, including lack of exercise behavior and overexertion; interpersonal networks, including insufficient peer social interaction, lack of parent-child interaction, and lack of communication and self-disclosure between couples; living and working conditions, including heavy individual financial burden, heavy unplanned family care tasks, insufficient information resources for health and disease management; macro factors, including limited medical services and medical insurance support.

This study described the effects of different perceived factors on preoperative frailty among elderly gastric cancer patients from the perspective of health ecology. Medical workers should formulate and implement systematic prehabilitation programs based on the above factors to improve the patients' preoperative anti-stress capacity and postoperative outcomes.

Due to great differences in physiological reserve, psychological status and social functioning, frailty in elderly patients with gastric cancer may present various subtypes. The relationship between preoperative frailty and postoperative adverse outcomes in them still remains to be further explored.

To explore the relationship between preoperative frailty subtypes and postoperative adverse outcomes〔total complications, prolonged length of stay (PLOS), low quality of life (QOL), and disability〕among elderly patients with gastric cancer.

From March to October 2021, 404 elderly gastric cancer patients were selected from Department of Gastric Surgery, the First Affiliated Hospital with Nanjing Medical University by convenience sampling. The General Demographic Data Questionnaire and Tilburg Frailty Indicator were used to collect demographics and frailty status before surgery. Total complications and PLOS were collected from the electronic medical records, and the status of disability and QOL were obtained using a telephone follow-up at one month after discharge. Univariate Logistic regression was performed to explore the influencing factors of postoperative adverse outcomes. Multivariate Logistic regression analysis was performed to analyze the association of preoperative frailty subtypes with postoperative adverse outcomes, with potential confounders adjusted.

Two hundred and eighty-five cases were found with preoperative frailty, and the frailty subtypes in them were classified into eight classes: exclusive physical frailty〔77 (19.1%) 〕, exclusive psychological frailty〔78 (19.3%) 〕, exclusive social frailty〔23 (5.7%) 〕, physical and psychological frailty〔63 (15.6%) 〕, physical and social frailty〔13 (3.2%) 〕, psychological and social frailty〔16 (4.0%) 〕, multidimensional frailty (physical, psychological, and social frailty) 〔15 (3.7%) 〕. The other 119 (29.5%) cases had no preoperative frailty. In the univariate Logistic regression, age was the factor influencing total complications〔OR=1.063, 95%CI (1.021, 1.106), P=0.003〕. History of pharmacological treatment〔OR=1.549, 95%CI (1.016, 2.362), P=0.042〕and surgical approach〔OR=2.103, 95%CI (1.191, 3.712), P=0.010〕were the factors influencing PLOS. Marital status〔OR=4.611, 95%CI (1.079, 19.706), P=0.039〕, living in an urban area〔OR=1.614, 95%CI (1.009, 2.582), P=0.046〕, having at least two comorbidities〔OR=1.694, 95%CI (1.038, 2.766), P=0.035〕were the factors influencing postoperative low QOL. Living in an urban area〔OR=0.601, 95%CI (0.390, 0.926), P=0.021〕, history of pharmacological treatment〔OR=1.663, 95%CI (1.082, 2.558), P=0.020〕, and advanced TNM stages〔OR=1.659, 95%CI (1.017, 2.706), P=0.043〕were the factors influencing postoperative disability. In the multivariate Logistic regression, the preoperative multidimensional frailty was independently associated with total complications, with age adjusted〔OR=5.344, 95%CI (1.715, 16.656), P=0.004〕. The preoperative physical frailty〔OR=2.048, 95%CI (1.078, 3.891), P=0.029〕, preoperative psychological frailty〔OR=2.077, 95%CI (1.103, 3.913), P=0.024〕and preoperative multidimensional frailty〔OR=8.321, 95%CI (2.400, 28.848), P<0.001〕were independently associated with PLOS, with history of pharmacological treatment and surgical approach adjusted. Preoperative psychological frailty〔OR=2.620, 95%CI (1.267, 5.418), P=0.009〕, preoperative psychological and social frailty〔OR=11.122, 95%CI (3.253, 38.028), P<0.001〕and preoperative multidimensional frailty〔OR=11.579, 95%CI (2.835, 47.302), P<0.001〕were independently associated with postoperative low QOL, with marital status, living in an urban area, and having at least two comorbidities adjusted.

Medical professionals should pay attention to preoperative frailty prevalence in elderly gastric cancer patients, and assess preoperative frailty in these patients using tools with the multidimensional frailty scale included, and attach great importance to those with exclusive physical frailty, exclusive psychological frailty, psychological and social frailty, and multidimensional frailty before surgery. A targeted prerehabilitation intervention program can be delivered to those with preoperative frailty according to their subtypes of frailty to improve postoperative adverse outcomes and QOL.

Frailty is associated with aging, which has recently become a health issue needs to be addressed urgently in the aging population. Neutrophil-to-lymphocyte ratio (NLR) and red cell distribution width (RDW) are novel inflammatory markers that are readily available clinically. Understanding the association of them with frailty is helpful to identify and monitor the development of frailty. There are few studies on the association of NLR and RDW with frailty, and they are not appropriate for traditional meta-analysis due to great heterogeneity between the study results.

To perform a scoping review of studies on NLR and RDW as potential biomarkers of frailty, so as to provide a reference for clarifying the pathogenesis of frailty and developing or improving frailty-related assessment tools.

Studies on the association of NLR and RDW with frailty were searched in eight databases (PubMed, Embase, Cochrane Library, Web of Science, CNKI, Wanfang Data, VIP and SinoMed) from inception to March 1, 2022. The studies on NLR and RDW as potential biomarkers of frailty was independently screened by two investigators, and the first author, publication time, country or region of publication, sample information, study methods, assessment tools, and assessment results were extracted. The quality of the literature was assessed using the Newcastle-Ottawa Scale and the AHRQ checklist for cross-sectional studies.

A total of fourteen studies were enrolled, including five cross-sectional studies, four longitudinal studies, one cohort study and four case-control studies, which were all rated≥4 points in terms of methodological quality, indicating that they were high quality. Nine studies examined the association between NLR and frailty, and seven of them showed that elevated NLR was independently associated with increased risk of frailty, and could predict its progression. Seven studies analyzed the association between RDW and frailty, and five of them showed that elevated RDW was independently associated with increased risk of frailty, and could predict its progression.

Some studies have shown that the risk of frailty increased with the elevation of NLR or RDW in different populations, and its progression could be predicted by NLR or RDW. As potential biomarkers of frailty, NLR and RDW could provide evidence for the pathogenesis of frailty, and a new theoretical basis for the development or improvement of frailty assessment tools. However, the optimal cut-off value of both for predicting frailty in different age groups and sex groups needs to be studied further.

Older adults with apathy have a high risk of falls and are prone to repeated falls . Few interventions could achieve satisfactory effects on improving apathy, although improved apathy is associated with a reduced risk of falls. Improving frailty may be a new method for reducing the risk of falls in older adults with apathy.

To investigate the mediating effect of frailty between apathy and risk of falls in older adults in the community, so as to provide a new idea for reducing the fall risk in this group.

A total of 212 community-dwelling older adults were selected to attend a survey by convenience sampling from November 2021 to March 2022, including 128 from Dongshan Community Health Center, Nanjing, and 84 from Qinghu Town, Donghai County, Lianyungang. A self-developed Demographic Information Questionnaire, the Fried Frailty Phenotype (FFP) , Geriatric Depression Scale (GDS-3) , Stopping Elderly Accidents, Deaths & Injuries Tool Kit (STEADI) were used to collect demographics, frailty prevalence, apathy prevalence, and risk of falls, respectively. The intermediary role of frailty in apathy and fall risk was analyzed.

One hundred and ninety-two cases (90.6%) who responded effectively to the survey were included for analysis. The average total STEADI score, average total GDS-3 score, and FFP score of the respondents were 2.0 (0, 4.0) , (1.6±0.9) , and 0 (0, 2.0) , respectively. Fifty-six (29.2%) and other 136 cases (70.8%) were assessed with and without fall risk, respectively. Spearman rank correlation analysis showed that apathy was positively correlated with frailty and fall risk, (r_s=0.303, 0.388, P<0.05) , and frailty was positively correlated with fall risk (r_s=0.424, P<0.05) . The analysis using intermediary Model 4 showed that apathy had a significant positive effect on fall risk (B=1.011, t=5.207, P<0.05) ; apathy significantly positively influenced frailty (B=0.324, t=3.800, P<0.05) ; frailty had a significant positive effect on fall risk (B=0.679, t=4.173, P<0.05) . Bootstrap test showed that the effect size of frailty in the path of "apathy→frailty→fall risk" was 0.22 〔95%CI (0.08, 0.40) 〕, indicating that frailty played a mediational role between apathy and risk of falls. Apathy could directly affect the fall risk, and could indirectly affect the fall risk through frailty. The total effect was 1.01, in which the size of direct effect was 0.79, the size of mediator effect was 0.22 (accounting for 21.78%) .

Frailty may be a mediator between apathy and fall risk in older adults in the community, and improving frailty is an important way to reduce risk of falling.

Cognitive frailty is a cognitive impairment state between normal aging and dementia. Cognitive frailty is associated with higher possibility of negative clinical events than simple frailty or cognitive impairment in older people. As cognitive frailty could be reversible toa certain degree, early identification of high-risk groups and timely intervention are particularly important in reducing adverse prognoses and improving the quality of life of elderly patients in their later years.

To investigate the prevalence and influencing factors of cognitive frailty, and its relationship with two-year post-discharge mortality in hospitalized elderly patients with comorbidities.

The data were collected from part of the project "Research and Demonstration of Clinical Management and Community-based Continuing Care Models for Older People with Comorbidities", involving a cluster sample of older inpatients with comorbidity aged≥60 years recruited from Department of Gerontology, Chengdu Fifth People's Hospital from November 2015 to January 2018. Demographics, chronic disease prevalence, and comprehensive geriatric assessment results were collected. Cognitive frailty was assessed by the FRAIL scale and Mini-Mental State Examination. Binary Logistic regression was used to analyze the influencing factors of cognitive frailty. The survival status was investigated at the end of a two-year follow-up after discharge. Cox regression was used to analyze the relationship of cognitive frailty with two-year post-discharge mortality.

A total of 554 cases were included, and 15.9% (88/554) of them had cognitive frailty. Compared with non-cognitive frailty group, cognitive frailty group had older average age, lower prevalence of high school education or above, lower average family care score, higher prevalence of malnutrition, depression, dependence in activities of daily living and balance dysfunction (P<0.05) . Binary Logistic regression analysis showed that malnutrition, balance dysfunction, and family care disorder were independent factors of cognitive frailty. During the follow-up period, 456 patients (82.3%) survived, 81 (14.6%) died, and 17 (3.1%) were lost to follow-up. After controlling for confounding factors, Cox regression analysis indicated that, the risk of two-year post-discharge mortality in cognitive frailty group was 2.039〔95%CI (1.060, 3.922) 〕times higher than that of those with normal cognitive function and non-frailty, and was 5.266〔95%CI (3.159, 8.778) 〕times higher than that of those with simple cognitive frailty (P<0.05) .

Cognitive frailty is common among elderly inpatients with comorbid conditions, and it can increase the relative risk of two-year post-discharge mortality. Clinical medical workers should pay more attention to this group to identify high-risk individuals of cognitive frailty as soon as possible and give them preventive interventionsin time.

Both frailty and potentially inappropriate medication (PIM) are relatively highly prevalent in adults with mild cognitive impairment (MCI) in the community, but the association of PIM with frailty in MCI population remains to be further explored.

To examine the association between PIM and frailty in older adults with MCI in the community.

This study was conducted between March to July 2021. By use of multistage sampling, older adults with MCI (n=230) were recruited from Baohe District, Hefei City. Sociodemographics, lifestyle indicators and physical functions of the subjects were collected by using the General Information Questionnaire developed by our research team. Frailty was assessed by the Comprehensive Frailty Assessment Instrument. PIM was assessed by the 2017 Criteria of Potentially Inappropriate Medications for Older Adults in China. Logistic regression analysis was applied to analyze the association of the number and types of PIM with frailty.

The prevalence of frailty and PIM in these older adults with MCI was 59.1% (136/230) and 59.1% (136/230) , respectively. The prevalence of PIM in the frailty group was much higher than that of non-frailty group〔80.9% (110/136) vs 27.7% (26/94) 〕 (P<0.05) . Multivariate Logistic regression analysis demonstrated that compared with MCI older adults without PIM, the risk of frailty was 4.591 times higher in those with only one PIM〔95%CI (1.903, 11.076) 〕, and 8.859 times higher in those with two or more PIMs〔95%CI (2.589, 30.321) 〕. Compared with MCI older adults with neurological disease but without PIM, the risk of frailty was 5.310 times higher in those with PIM〔95%CI (1.011, 27.877) 〕. The risk of frailty was 3.108 times higher in those with cardiovascular disease and PIM than that in those without PIM〔95%CI (1.173, 8.241) 〕.

The prevalence of frailty and PIM was higher in older adults with MCI in the community, and PIM was significantly associated with frailty. To decrease the prevalence of frailty and delay the progression of dementia in this population via reducing the prevalence of PIM, community-based health efforts should be made to strengthen the screening for frailty, enhance the identification of frailty related to medication use, and promote medication review and management.

The somatic symptom clusters may be associated with increased risk of adverse outcomes in frail elderly people. Relevant studies in China have mainly adopted a cross-sectional design with neglect of the trajectory of somatic symptom clusters in this group.

To explore the characteristics of somatic symptom clusters at different time points and influencing factors in elderly people with frailty in nursing homes in Chengdu.

From November 2019 to January 2020, 206 frail elderly people were selected from 6 nursing homes in Chengdu by convenience sampling, and surveyed using the general data questionnaire and Memory Symptom Assessment Scale (MSAS) for 3 times〔at baseline (T0) , 6 (T1) , and 12 months later (T2) 〕. Exploratory factor analysis was carried out for symptoms with an incidence of ≥20% at different time points. Latent growth mixture model (LGMM) was used to identify the change trajectory of somatic symptom clusters across the above-mentioned three time points. Logistic regression analysis was used to identify the potential factors associated with the trajectory category.

By exploratory factor analysis, 5 factors were extracted at each of the three time points. Neurological symptom cluster, energy deficiency symptom cluster, respiratory symptom cluster and digestive symptom cluster all appeared at the three time points. In addition, senescence-related symptom cluster also occurred at T0 and T1, and other symptom cluster occurred at T2. The MSAS score of each symptom cluster differed significantly across three time points (P<0.05) . Four heterogeneous trajectories of frailty symptom clusters were obtained by LGMM model fitting, which were named as "high decline" "low rise" "medium maintenance" and "high rise", accounting for 16.5%, 12.5%, 66.0% and 5.0%, respectively. Multivariate Logistic regression analysis showed that the number of chronic diseases was independently associated with the "high decline" or "high rise" trajectory, and the number of medications was independently associated with the "high rise" trajectory (P<0.05) .

There are various trajectories of somatic symptom clusters in frail elderly people in nursing homes, and each of the trajectories has a different independently associated factor. To provide more appropriate services for this population, medical workers in nursing homes can dynamically adjust nursing services according to the trajectories and associated factors of somatic symptom clusters.