Objective To investigate the relationship between the Clinical Frailty Scale (CFS) and prognosis in elderly patients with pelvic fractures who are treated conservatively. Methods Patients aged ≥65 years admitted to Chengdu Pidu District People’s Hospital between January 2015 and January 2023 with low-energy pelvic-ring fractures (Tile type A/B) who received non-operative management were retrospectively collected. The patients were stratified by CFS score on admission into robust (CFS 1-3), vulnerable (CFS 4), and frail (CFS 5-9) groups. Baseline characteristics (age, sex, smoking history, alcohol use, and so on) and outcomes (complications, discharge destination, and in-hospital mortality) were compared among groups. Binary logistic regression was used to assess the association between CFS and outcomes. Results A total of 197 patients were enrolled: 78 robust, 59 vulnerable, and 60 frail. Significant differences were observed among the robust, vulnerable, and frail groups in age [(68.72±2.53), (71.47±3.53), and (73.25±2.33) years, respectively; P<0.05], incidence of complications (28.2%, 33.9%, and 56.7%, respectively; P<0.05), and incidence of adverse discharge destinations (15.4%, 25.4%, and 38.3%, respectively; P<0.05). Logistic regression analysis revealed that frailty (CFS 5-9 vs. 1-3) was an independent predictor of any complications [odds ratio (OR)=3.342, 95% confidence interval (CI) (1.390, 8.037), P=0.007] and adverse discharge destination [OR=4.871, 95%CI (1.762, 13.469), P=0.002]. Conclusion CFS-assessed frailty correlates with the adverse discharge destination and any complication in elderly patients undergoing conservative treatment for pelvic fractures.
The incidence of sarcopenia and frailty in maintenance hemodialysis patients are high, and there are often comorbidities, which easily lead to more complications, thus increasing the hospitalization rate and reducing the quality of life of patients. This article reviews the definition, physiological mechanism, incidence and diagnosis, relationship and treatment strategies of sarcopenia and frailty in maintenance hemodialysis patients, in order to better prevent and intervene the occurrence of sarcopenia and frailty and provide a reference for prevention and treatment.
ObjectiveTo systematically review the associations of cognitive frailty with mortality and hospitalization in the elderly. MethodsThe VIP, PubMed, CNKI, WanFang Data, CBM, Embase, Cochrane Library and Web of Science databases were electronically searched to collect cohort studies on the association of cognitive frailty with mortality or hospitalization in the elderly from inception to May, 2023. Two reviewers independently screened the literature, extracted data and assessed risk of bias of the included studies. Meta-analysis was performed by R 4.2.2 software. ResultsA total of 19 cohort studies involving 63 624 elderly were included. The results of meta-analysis showed that compared with healthy elder, the elder with cognitive frailty had a higher mortality (OR=2.75, 95%CI 2.10 to 3.59, P<0.01) and hospitalization (OR=1.67, 95%CI 1.40 to 2.00, P<0.01). Subgroup analysis showed that cognitive frailty was related to the risk of death in different status of frailty and cognitive function, different assessment tools, different countries of development, different follow-up time and research sites. At the same time, different status of frailty and cognitive function and different levels of development of countries were related to the risk of hospitalization. ConclusionCurrent evidence shows that cognitive frailty can increase the risk of hospitalization and mortality in the elderly. It is suggested that early screening and intervention of cognitive frailty should be carried out to effectively reduce the risk of adverse consequences, so as to achieve healthy aging.
Frailty and cognitive impairment are two major risk factors for adverse outcomes in elderly patients with diabetes. In the elderly, physical frailty and cognitive impairment frequently coexist, and have similar pathophysiological pathways, so the new concept of " cognitive debilitation” has been proposed. Physical frailty and cognitive impairment could accelerate the decline of function among elderly diabetic patients, and seriously affect their quality of life. Early identification and appropriate intervention of cognitive frailty may improve the adverse outcomes of elderly patients with diabetes. This article reviews the research progress of cognitive frailty and senile diabetes.
The coexistence of cognitive impairment and physical frailty in maintenance hemodialysis (MHD) patients is known as cognitive frailty. It has emerged as a novel complication in MHD patients and increases the risk of adverse outcomes such as falls, fractures, functional impairment and death. Timely intervention can delay or even reverse the development of cognitive frailty to dementia, thereby reducing the risk of adverse outcomes and improving the quality of life of patients. Based on this literature review method, this article summarizes the domestic and foreign research progress on the epidemiology, assessment tools, influencing factors and intervention measures of cognitive frailty in MHD patients, aiming to provide reference for clinical staff to carry out early screening and intervention of cognitive frailty in MHD patients.
Gut microbiota plays an important role in development of diabetes with frailty. Therefore, it is of great significance to study the structural and functional characteristics of gut microbiota in Chinese with frailty. Totally 30 middle-aged and the aged participants in communities with diabetes were enrolled in this study, and their feces were collected. At the same time, we developed a metagenome analysis to explore the different of the structural and functional characteristics between diabetes with frailty and diabetes without frailty. The results showed the alpha diversity of intestinal microbiota in diabetes with frailty was lower. Collinsella and Butyricimonas were more abundant in diabetes with frailty. The functional characteristics showed that histidine metabolism, Epstein-Barr virus infection, sulfur metabolism, and biosynthesis of type Ⅱ polyketide products were upregulated in diabetes with frailty. Otherwise, butanoate metabolism and phenylalanine metabolism were down-regulated in diabetes with frailty. This research provides theoretical basic for exploring the mechanism of the gut microbiota on the occurrence and development of diabetes with frailty, and provides a basic for prevention and intervention of it.
ObjectiveTo summarize the research progress on the impact of postoperative adjuvant chemotherapy on frailty, cognitive function, and quality of life in older patients with breast cancer.MethodCollected literatures about the impact of postoperative adjuvant chemotherapy on frailty, cognitive function, and quality of life in older patients with breast cancer to make an review.ResultsElderly breast cancer patients were likely to benefit from postoperative adjuvant chemotherapy without undergoing significant impairment of frailty, cognitive function, and quality of life. However, postoperative adjuvant chemotherapy might cause an aggravation of the frailty in patients who was already with it.ConclusionWe should develop personalized treatment plans for elderly breast cancer patients after multidisciplinary assessment.
Objective To investigate the status of frailty in patients with coronavirus disease 2019 (COVID-19), and to analyze the influence of COVID-19 disease on the prevalence of frailty. Methods This study was conducted using a cross-sectional survey method. COVID-19 patients admitted to a centralized isolation point in Guangzhou were selected for an questionnaire survey by “questionnaire star”, between November and December 2022. The questionnaire included the general information questionnaire, Tilburg Frailty Indicator (TFI), the COVID-19 symptom scale and Mental Resilience Scale (RS-11). Multi-model logistic regression analysis was used to explore the influence of COVID-19 on the occurrence of debilitation. Results A total of 667 questionnaires were distributed, of which 594 were valid, with an effective rate of 89.1%. There were 150 patients (25.3%) were frail, 444 patients (74.7%) were non-frail, and 51 patients (8.6%) were newly frail after infected COVID-19. The median TFI score before COVID-19 was 3 (2, 4) points, 16.7% (99/594) were in a weak state. The median TFI score after COVID-19 was 3 (2, 5) points, 25.3% (150/594) were in a weak state. There were statistically significant differences in TFI scores (Z=−6.596, P＜0.001) and the incidence of debilitation (χ2=351.648, P＜0.001) before and after COVID-19. The results of multivariate logistic regression analysis showed that after controlling disease factors, demographic factors and psychosocial factors, the score of the COVID-19 symptom score was always the influencing factor of COVID-19 patients. The overall change trend of COVID-19 symptom score was statistically significant (P<0.001). Conclusions The COVID-19 symptom score is an important risk factor or predictor of frailty in patients with COVID-19. As the level of COVID-19 symptom score increases, the risk of frailty in COVID-19 patients increases.
ObjectiveThe re-hospitalization and death events of patients heart failure caused by coronary heart disease are characterized by non-independence, heterogeneity, and censored data. A joint frailty model is established to jointly model the events, explore the risk factors affecting the prognosis of patients, and reduce the re-hospitalization rate and mortality of patients. MethodsThe sample included 4 682 patients with heart failure caused by coronary heart disease in two tertiary hospitals from January 2014 and June 2019. The electronic medical record information of patients during hospitalization and their follow-up information were collected. The Cox model, conditional frailty model and joint frailty model were used to analyze patient re-hospitalization and death. ResultsThe joint frailty model identified patients with a higher risk of both relapse and death (θ=0.209, P<0.001). Risk factors for re-hospitalization were advanced age, grade 3 hypertension, mental work, no medical insurance, high cystatin C, low ejection fraction, and low free thyroxine-3 and thyroxine-4. Antiplatelet drugs and statins significantly reduced the risk of re-hospitalization. Risk factors for death were advanced age, New York Heart Association classification Ⅲ to Ⅳ, no medical insurance, mental work, high cystatin C level, high troponin-I level, low free thyroxine-3, and low ejection fraction. Percutaneous coronary intervention, and taking antiplatelet drugs and statins significantly reduced the risk of death. ConclusionThe joint frailty model can simultaneously model recurring and terminal events, and accurately predict them. Our results suggest that thyroid hormone levels and cystatin C levels of patients should be considered more carefully. People with mental jobs should change bad working habits to reduce adverse outcomes.
Objective To understand the frailty status and main influencing factors of elderly Parkinson’s disease (PD) patients. Methods The elderly PD patients who attended the Department of Neurology of Changshu Hospital of Traditional Chinese Medicine between November 2023 and March 2024 were selected. The patients’ frailty conditions were investigated using general information questionnaire, Chinese version of Tilburg Frailty Indicator, Hoehn-Yahr Rating Scale, Mini-Nutritional Assessment Short Form, Movement Disorder Society-Unified PD Rating Scale Part Ⅲ, PD Sleep Scale-2, and Mini-Mental State Examination. Multiple linear regression analysis was used to further determine the influencing factors of the frailty status in elderly PD patients. Results A total of 170 PD patients were included. Among them, 117 cases (68.82%) had frailty, while 53 cases (31.18%) had not frailty. The average score for frailty was (6.48±3.34) points, the average score for nutritional status was (11.89±1.65) points, the average score for motor function was (27.40±13.73) points, the average score for sleep quality was (16.05±7.76) points, and the average score for cognitive status is (26.25±4.51) points. The Pearson correlation analysis results showed that PD patient frailty was positively correlated with motor function and sleep quality (P<0.01), and negatively correlated with nutritional status and cognitive status (P<0.01). The results of multiple linear regression analysis showed that age, education, place of residence, course of disease, Hoehn-Yahr Rating, nutritional status, motor function, cognitive status and sleep quality were the influencing factors of frailty in PD patients (P<0.05). Conclusions Elderly PD patients are prone to frailty. Healthcare professionals should pay attention to early screening for frailty in this population and provide timely and effective interventions to prevent or delay the onset of frailty in patients.