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Early identification and intervention of the frailty of the elderly will help lighten the burden of social medical care and improve the quality of life of the elderly. Therefore, we used machine learning (ML) algorithm to develop models to predict frailty risk in the elderly.
A prospective cohort study.
We collected data on 6997 elderly people from Chinese Longitudinal Healthy Longevity Study wave 6–7 surveys (2011–2012, 2014). After the baseline survey in 1998 (wave 1), the project conducted follow-up surveys (wave 2–8) in 2000–2018. The osteoporotic fractures index was used to assess frailty. Four ML algorithms (random forest [RF], support vector machine, XGBoost and logistic regression [LR]) were used to develop models to identify the risk factors of frailty and predict the risk of frailty. Different ML models were used for the prediction of frailty risk in the elderly and frailty risk was trained on a cohort of 4385 elderly people with frailty (split into a training cohort [75%] and internal validation cohort [25%]). The best-performing model for each study outcome was tested in an external validation cohort of 6997 elderly people with frailty pooled from the surveys (wave 6–7). Model performance was assessed by receiver operating curve and F2-score.
Among the four ML models, the F2-score values were similar (0.91 vs. 0.91 vs. 0.88 vs. 0.90), and the area under the curve (AUC) values of RF model was the highest (0.75), followed by LR model (0.74). In the final two models, the AUC values of RF and LR model were similar (0.77 vs. 0.76) and their accuracy was identical (87.4% vs. 87.4%).
Our study developed a preliminary prediction model based on two different ML approaches to help predict frailty risk in the elderly.
The presented models from this study can be used to inform healthcare providers to predict the frailty probability among older adults and maybe help guide the development of effective frailty risk management interventions.
Detecting frailty at an early stage and implementing timely targeted interventions may help to improve the allocation of health care resources and to reduce frailty-related burden. Identifying risk factors for frailty could be beneficial to provide tailored and personalized care intervention for older adults to more accurately prevent or improve their frail conditions so as to improve their quality of life.
The study has adhered to STROBE guidelines.
No patient or public contribution.
To explore the effect of clinical nursing pathway on wound infection in patients undergoing knee or hip replacement surgery. Computerised searches of PubMed, Web of Science, Cochrane Library, Embase, Wanfang, China Biomedical Literature Database, China National Knowledge Infrastructure databases were conducted, from database inception to September 2023, on the randomised controlled trials (RCTs) of application of clinical nursing pathway to patients undergoing knee and hip arthroplasty. Literature was screened and evaluated by two researchers based on inclusion and exclusion criteria, and data were extracted from the final included literature. RevMan 5.4 software was employed for data analysis. Overall, 48 RCTs involving 4139 surgical patients were included, including 2072 and 2067 in the clinical nursing pathway and routine nursing groups, respectively. The results revealed, compared with routine nursing, the use of clinical nursing pathways was effective in reducing the rate of complications (OR = 0.17, 95%CI: 0.14–0.21, p < 0.001) and wound infections (OR = 0.29, 95%CI: 0.16–0.51, p < 0.001), shortens the hospital length of stay (MD = −4.11, 95%CI: −5.40 to −2.83, p < 0.001) and improves wound pain (MD = −1.34, 95%CI: −1.98 to −0.70, p < 0.001); it also improve patient satisfaction (OR = 7.13, 95%CI: 4.69–10.85, p < 0.001). The implementation of clinical nursing pathways in clinical care after knee or hip arthroplasty can effectively reduce the incidence of complications and wound infections, and also improve the wound pain, while also improving treatment satisfaction so that patients can be discharged from the hospital as soon as possible.
by Bingqian Du, Yuting Li, Yun Xia, Shan Wu, Yuan Wei, Zhihao Wang, Shupei Wang, Jiao Guo, Qing Zhu, Tianran Shen, Qingsong Chen
Previous studies showed that physical activity (PA) is concerned with hypertension (HTN). However, the mediation and interaction role of the obesity index: body mass index (BMI), waist-hip ratio (WHR), body fat rate (BFR) and visceral fat index (VFI) between PA and HTN has never been studied. Therefore, the purpose of this study was to assess the mediation and interaction of the obesity index between moderate-vigorous recreational physical activity (MVRPA) and HTN. We conducted a cross-sectional study of 4710 individuals aged 41 or older in Torch Development Zone, Zhongshan City. The mediation and interaction of the obesity index were evaluated by a four-way decomposition. 48.07% of participants had HTN among these groups. In the adjusted linear regression model, MVRPA was significantly correlated with WHR (β±SE = -0.005±0.002; POR) = 1.35), 95% (confidence interval (CI) = 1.17–1.56), insufficient MVRPA increased the risk of developing HTN. Furthermore, there were associations between BMI, WHR, BFR, VFI and HTN where the adjusted ORs and 95% CIs were 1.11 (1.09–1.13), 6.23 (2.61–14.90), 1.04 (1.03–1.06), 1.07 (1.06–1.09), respectively. The mediation analyses suggested that the impact of MVRPA on HTN risk may partly be explained by changes in obesity index, with a pure indirect mediation of WHR between MVRPA and HTN (PAs neurosurgery has advanced technologically, more and more neurosurgical implants are being employed on an aging patient population with several comorbidities. As a result, there is a steady increase in the frequency of infections linked to neurosurgical implants, which causes serious morbidity and mortality as well as abnormalities of the skull and inadequate brain protection. We discuss infections linked to internal and external ventricular and lumbar cerebrospinal fluid drainages, neurostimulators, craniotomies, and cranioplasty in this article. Biofilms, which are challenging to remove, are involved in all implant-associated illnesses. It takes a small quantity of microorganisms to create a biofilm on the implant surface. Skin flora bacteria are implicated in the majority of illnesses. Microorganisms that cause disruptions in wound healing make their way to the implant either during or right after surgery. In about two thirds of patients, implant-associated infections manifest early (within the first month after surgery), whereas the remaining infections present later as a result of low-grade infections or by direct extension from adjacent infections (per continuitatem) to the implants due to soft tissue damage. Except for ventriculo-atrial cerebrospinal fluid shunts, neurosurgical implants are rarely infected by the haematogenous route. This research examines established and clinically validated principles that are applicable to a range of surgical specialties using implants to treat biofilm-associated infections in orthopaedic and trauma cases. Nevertheless, there is little evidence and no evaluation in sizable patient populations to support the success of this extrapolation to neurosurgical patients. An optimal microbiological diagnostic, which includes sonicating removed implants and extending culture incubation times, is necessary for a positive result. Additionally, a strategy combining surgical and antibiotic therapy is needed. Surgical procedures involve a suitable debridement along with implant replacement or exchange, contingent on the biofilm's age and the state of the soft tissue. A protracted biofilm-active therapy is a component of antimicrobial treatment, usually lasting 4–12 weeks. This idea is appealing because it allows implants to be changed or kept in place for a single surgical procedure in a subset of patients. This not only enhances quality of life but also lowers morbidity because each additional neurosurgical procedure increases the risk of secondary complications like intracerebral bleeding or ischemia.
by Chengchao Wang, Xianqiang Song, Dongshen Luo, Xu Dan, Tingting Lin
Landscape changes driven by cash crop plantations have been prevalent in tropical and subtropical regions worldwide in recent decades. Investigating the landscape changes and concluding livelihood outcomes are fundamental to figure out the solutions for rural sustainability. This paper examined the landscape changes which was caused by land use changes in tea plantations as well as investigated the resultant livelihood impacts, based on a case study in Fuding City, Southeast China. A questionnaire survey of 114 rural households in four sampled villages was conducted. Results demonstrated that expansion and intensification of tea plantations were two major proximate causes of landscape changes in recent decade. Our survey indicated that some existing intensively-managed tea plantations had derived from intensification and expansion of tea plantations, respectively. We identified four underlying driving forces of landscape changes, including economic benefit, governmental policies, wildlife destruction on grain crops, and rural return migration. Our study confirmed that landscape changes have significant positive effects on farmers’ livelihoods, including increasing employment and incomes, raising living standards, enhancing livelihood assets and livelihood sustainability. Especially, the aged rural populations could have a relatively decent living standard. Meanwhile, the excessive expansion of tea plantations may impair livelihood resilience. Lastly, three policy suggestions based on different time scales have been put forward to promote rural households’ livelihood sustainability and resilience.
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