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INTRODUCTION: Frailty is a geriatric syndrome that is highly susceptible to adverse health outcomes and is a major burden that exacerbates society's medical care. By investigating the frailty trajectory within the older demographic and initially recognizing its clinical outcomes, we will have more tactics to manage the at-risk population. METHODS: We executed a systematic review of trajectory studies elucidating the connection between frailty and adverse outcomes among older individuals (≥ 65 years) and explored articles published in English and Chinese from the inception of the database until Jun 30, 2024, in PubMed, Web of Science, Embase, The Cochrane Library, CINAHL, Scopus, CNKI, China Online Journals, VIP Information, and SinoMed. RESULTS: The database survey unearthed 3522 articles, of which 21 were deemed eligible. The majority incorporated distinct assessment tools and statistical methodologies to classify frailty trajectories into three groups. Although these frailty trajectories produced inconsistent clinical outcomes, they did reveal trends in the frailty status of older adults. CONCLUSION: The link between frailty trajectories and adverse outcome is a multifaceted and complex process that is currently understudied. More comprehensive and in-depth longitudinal studies should be conducted to explore the mechanism of interaction between the two to obstruct the progression of the frailty trajectory and bolster support for interventions.

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AIMS: To systematically evaluate the predictive efficacy of clinical frailty scale (CFS) for postoperative mortality older surgical patients, and to evaluate the prevalence of frailty in the included studies. DESIGN: A systematic review and meta-analysis of observational studies was conducted, utilizing the MOOSE guidelines for the evaluation of both. Quality assessment of the articles was also performed. DATA SOURCES: The protocol was registered (CRD42023423552). Relevant English and Chinese language studies published until October 20th, 2023 were retrieved from PubMed, Web of Science, Embase, Medline, CINAHL,Cochrane, WAN FANG DATA, VIP Information, CNKI, and SinoMed databases. REVIEW METHODS: Study were included in which frailty was measured by the CFS and postoperative mortality was reported for older surgery patients. A meta-analysis to predict postoperative mortality and frailty prevalence was performed using STATA 17.0 software. RESULTS: Sixteen cohort studies were included (5,864 participants) from 1,513 records. All studies' Newcastle-Ottawa Scale (NOS) scores were above 6 points. It was found that the prevalence of surgical frailty in the older was 0.36(CI 0.20-0.52). Patients assessed as frail by the CFS were associated with higher all-cause mortality (OR:4.01; CI 2.59-6.23). Subgroup analysis shows that frailty was associated with1-month mortality (OR:3.85; CI 1.11-13.45) and 1-year mortality (OR:4.43; CI 2.18-8.99). CONCLUSIONS: The prevalence of frailty is high in older surgical patients, and CFS can effectively predict the mortality of older surgical patients with frailty.

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OBJECTIVE: The study investigates the impact of preoperative rehabilitation on the surgical prognosis of frail older patients. METHOD: The effect sizes of all studies retrieved and included by the nine databases were analyzed and expressed as RR and WMD. RESULTS: 8 studies with 902 participants met the criteria for inclusion. A significant reduction in total complications (RR = 0.84, 95 % CI = 0.73 to 0.97, P = 0.021) and the 6MWT after surgery (WMD = 74.76, 95 % CI = 44.75 to 104.77, P = 0.000) was observed in the prehabilitation group. But it had no differences in mortality(RR = 1.89, 95 % CI = 0.75 to 4.72, P = 0.176), readmission rates(RR = 1.04, 95 % CI = 0.56 to 1.91, P = 0.906) and LOS(WMD = -0.24, 95 % CI = -1.00 to 0.52, P = 0.540). CONCLUSIONS: Prehabilitation had positive effect on postoperative complications and functional recovery in frail older patients.

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Background: In rural China, there is now a huge gap between the supply and demand for old-age care. To close the gap, developing rural mutual old-age services is extremely important. The purpose of this study is to clarify the relationship among social support, mutual support need, and mutual support willingness. Methods: We conducted an online questionnaire survey using a Chinese Internet research company; 2,102 valid responses were received. The measures comprised the Social Support Rating Scale, the Mutual Support Willingness Questionnaire, and the Mutual Support Needs Scale. We calculated Pearson correlations to explore the association of social support with mutual-support need and mutual-support-need willingness. Multivariate analyses were also conducted using these factors as dependent variables. Results: The total score for the mutual support need for the adults in rural areas was 58.0 ± 12.1 and 36.96 ± 6.40 for social support, approximately 86.8% of the participants were willing to participate in mutual support. Furthermore, mutual support needs were positively correlated with subjective support (p < 0.01) and support utilization (p < 0.01), but negatively correlated with willingness to support each other (p < 0.05). The need for mutual support was also associated with age, sex, education level, dissatisfaction with the current economic situation, health status, and so on. Conclusion: It is necessary for government and health care providers to assess the different needs of rural older people and encourage individuals and organizations to provide mutual support for older people, especially to enhance emotional care for older people and improve their use of support. This is of great significance for developing mutual support services in rural China.

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Objective: To determine the effectiveness of traditional Chinese mind-body exercises in improving cognition, memory, and executive function in older adults with cognitive impairment. Data sources: Relevant English and Chinese language studies published until September 14th, 2022 were retrieved from PubMed, Web of Science, Cochrane Library, Embase, CINAHL, WAN FANG DATA, VIP Information, CNKI, and SinoMed databases. Review methods: Randomized controlled trials assessing traditional Chinese mind-body exercises (Tai Chi, Baduanjin, Qigong, Mind-Body Therapies, and Yijinjing) in older adults with cognitive impairment were included. Two researchers independently identified eligible studies and extracted data. A risk-of-bias assessment was performed using the Cochrane Risk of Bias Tool. Results: This study included 15 randomized controlled trials (1,127 participants) from China, Thailand and American. Most studies had a high risk of bias in the blinding of participants and researchers, one study had a high risk of bias in the random sequence generation and two studies had a high risk of bias in the incomplete outcome data. Compared with conventional therapy alone, traditional Chinese mind-body exercises significantly improved global cognitive function (p < 0.00001), and Baduanjin could improve the global cognitive function (p < 0.00001), memory function (p < 0.0001), and executive function (p < 0.0001) outcomes after treatment, and significantly improved some dimensional scores on the auditory verbal learning test after treatment (p = 0.04). Conclusion: Compared with conventional therapy, traditional Chinese mind-body exercises (Tai Chi, Baduanjin, and Qigong) significantly improved global cognitive function, and Baduanjin could improve global cognitive function, memory function, and executive function in older adults with cognitive impairment. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/#searchadvanced, CRD42022327563.

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BACKGROUND: This study aimed to assess the influence factors of the mutual-support willingness and identify the mutual-support needs of elderly living in rural areas of Hunan Province, China. METHODS: Using the Chi-square test and logistic regression to analyze factors influencing Participants' mutual-support willingness and needs. RESULTS: Factors influencing the mutual-support willingness and needs included individual characteristics, family environment, and so on. And the rural elderly's demand for mutual-support is at a relatively high level. The total score for social support for the aged was 36.944 ± 6.487, at a moderate level. CONCLUSIONS: It is necessary to objectively evaluate the factors related to mutual-support willingness and needs and take steps to enhance social support and meet elderly the needs of mutual-support, which is of great significance for improving the happiness of the elderly in their later years and alleviating the crisis of population aging in China.

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Community detection has been paid much attention in many fields in recent years, and a great deal of community-detection methods have been proposed. But the time consumption of some of them is heavy, limiting them from being applied to large-scale networks. On the contrary, there exist some lower-time-complexity methods. But most of them are non-deterministic, meaning that running the same method many times may yield different results from the same network, which reduces their practical utility greatly in real-world applications. To solve these problems, we propose a community-detection method in this paper, which takes both the quality of the results and the efficiency of the detecting procedure into account. Moreover, it is a deterministic method which can extract definite community structures from networks. The proposed method is inspired by the voting behaviours in election activities in the social society, in which we first simulate the voting procedure on the network. Every vertex votes for the nominated candidates following the proposed voting principles, densely connected groups of vertices can quickly reach a consensus on their candidates. At the end of this procedure, candidates and their own voters form a group of clusters. Then, we take the clusters as initial communities, and agglomerate some of them into larger ones with high efficiency to obtain the resulting community structures. We conducted extensive experiments on some artificial networks and real-world networks, the experimental results show that our proposed method can efficiently extract high-quality community structures from networks, and outperform the comparison algorithms significantly.