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A nomogram for screening sarcopenia in Chinese type 2 diabetes mellitus patients
Mingzhong Yu1, Min Pan1, Yebei Liang1
1Department of Geriatrics, The First Affiliated Hospital of Fujian Medical University, Fuzhou, People's Republic of China; Department of Geriatrics, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, People's Republic of China; Branch of National Clinical Research Center for Aging and Medicine, The First Affiliated Hospital of Fujian Medical University, Fuzhou, People's Republic of China; Clinical Research Center for Geriatric Hypertension Disease of Fujian province, The First Affiliated Hospital of Fujian Medical University, Fuzhou, People's Republic of China.
Objective:
Diabetes is an important risk factor for sarcopenia and contributes to poor prognosis; it is important for clinicians to identify sarcopenia early in the population with type 2 diabetes mellitus. Our aim was to establish a clinical screening model of sarcopenia in Chinese patients with type 2 diabetes mellitus.
Methods:
A cross-sectional study was conducted involving 1131 hospitalized patients (62.67 ± 11.25 years) with type 2 diabetes mellitus, including 560 men and 571 women. All muscle/fat parameters were measured by dual energy X-ray absorptiometry and the clinical correlation with sarcopenia was evaluated. The least absolute shrinkage and selection operator was used to select optimal variables and build a nomogram chart of the sarcopenic screening model for patients with type 2 diabetes mellitus, respectively. The area under the receiver operating characteristic curve (AUC), the calibration curve, the analysis of the decision curve, the clinical impact curve, and external validations were used to evaluate discriminative ability and clinical applicability.
Results:
The prevalence of sarcopenia in patients with type 2 diabetes mellitus was 30.06 % (340/1131). Compared to the non-sarcopenic group, the sarcopenic group was older, more likely to be men, and had a higher heart rate and lower body mass index (BMI), waist-hip ratio (WHR), upper limb muscle mass, lower limb muscle mass and fat paraments (all P < 0.05). Five independent variables (age, sex, BMI, WHR and heart rate) were selected to construct a nomogram prediction model. The AUC was 0.907 (95 % CI: 0.890-0.925). The calibration curve, decision curve analysis, and clinical impact curves showed a wide range of nomograms with good clinical applicability under threshold probability. Additionally, internal validation showed a good AUC of 0.908 (95 % CI: 0.886-0.928) in the training set and 0.904 (95 % CI: 0.868-0.941) in the testing set, as well as an accuracy of 93.2 % for the screening of sarcopenia in the external validation set.
Conclusions:
Age, sex, BMI, WHR, and heart rate were used to detect sarcopenia in patients with type 2 diabetes mellitus. The novel screening model is an accurate, easy-to-implement and low-cost tool for early identification of sarcopenia in Chinese patients with type 2 diabetes mellitus.
