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阿尔茨海默病中肌肉减少症的危险因素识别及预测列线图的构建

Identification of risk factors and development of a predictive nomogram for sarcopenia in Alzheimer's disease.

作者信息

Chen Sihui, Ou Ruwei, Wei Qianqian, Fu Jiajia, Zhao Bi, Chen Xueping, Shang Huifang

机构信息

Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, China.

出版信息

Alzheimers Dement. 2025 Feb;21(2):e14503. doi: 10.1002/alz.14503. Epub 2025 Jan 8.

Abstract

INTRODUCTION

Sarcopenia, with its complex diagnostic process, is a likely independent predictor of poor prognosis in patients with Alzheimer's disease (AD). However, research on the clinical characteristics and biomarkers of AD patients with sarcopenia (ADSA) is limited.

METHODS

This study included 180 ADSA and 188 AD patients without sarcopenia (ADNSA), and evaluated demographics, cognitive function, motor capacity, emotional state, and daily living abilities.

RESULTS

ADSA patients were older, with worse motor and cognitive functions, more severe depression, poorer social functioning, and lower daily living abilities compared to ADNSA patients. Multivariate regression identified age, low Frailty Rating Scale (FRS) scores, low serum albumin level, and low creatinine/cystatin C ratio (CCR) as risk factors for sarcopenia. A nomogram model based on these indicators demonstrated high discriminative power and clinical utility.

DISCUSSION

Sarcopenia significantly affects AD patients' various functions. The nomogram model aids in the early detection of and personalized interventions for sarcopenia in AD.

HIGHLIGHTS

Sarcopenia is a risk factor for Alzheimer's disease (AD), and the coexistence of sarcopenia affects various functions and quality of life in patients with AD. Serum albumin and Frailty Rating Scale (FRS) scores are significantly associated with both sarcopenia and cognitive assessment indicators in AD patients with sarcopenia (ADSA). The combined sarcopenia nomogram model with indexes of age at diagnosis, creatinine/cystatin C ratio (CCR), FRS score, and albumin levels can aid in effectively identifying and personalizing interventions for sarcopenia in the AD population.

摘要

引言

肌肉减少症诊断过程复杂,可能是阿尔茨海默病(AD)患者预后不良的独立预测因素。然而,关于伴有肌肉减少症的AD患者(ADSA)的临床特征和生物标志物的研究有限。

方法

本研究纳入了180例ADSA患者和188例无肌肉减少症的AD患者(ADNSA),并评估了人口统计学特征、认知功能、运动能力、情绪状态和日常生活能力。

结果

与ADNSA患者相比,ADSA患者年龄更大,运动和认知功能更差,抑郁更严重,社会功能更差,日常生活能力更低。多变量回归分析确定年龄、低衰弱评分量表(FRS)得分、低血清白蛋白水平和低肌酐/胱抑素C比值(CCR)为肌肉减少症的危险因素。基于这些指标的列线图模型显示出较高的判别能力和临床实用性。

讨论

肌肉减少症显著影响AD患者的各项功能。列线图模型有助于AD患者肌肉减少症的早期检测和个性化干预。

要点

肌肉减少症是阿尔茨海默病(AD)的危险因素,肌肉减少症的共存会影响AD患者的各项功能和生活质量。血清白蛋白和衰弱评分量表(FRS)得分与伴有肌肉减少症的AD患者(ADSA)的肌肉减少症和认知评估指标均显著相关。结合诊断年龄、肌酐/胱抑素C比值(CCR)、FRS得分和白蛋白水平等指标的肌肉减少症联合列线图模型有助于有效识别AD人群中的肌肉减少症并进行个性化干预。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a15/11848345/ddb4e13d582f/ALZ-21-e14503-g002.jpg

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