AUTHOR=Li Shao-jun , Feng Dan 

TITLE=Risk factors and nomogram-based prediction of the risk of limb weakness in herpes zoster

JOURNAL=Frontiers in Neuroscience

VOLUME=Volume 17 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2023.1109927

DOI=10.3389/fnins.2023.1109927

ISSN=1662-453X

ABSTRACT=Background 
Limb weakness is a less common complication of herpes zoster (HZ). There has been comparatively little study of limb weakness. The aim of this study is to develop a risk nomogram for limb weakness in HZ patients.
Methods
Limb weakness was diagnosed using the Medical Research Council (MRC) muscle power scale. The entire cohort was assigned to a training set (from January 1, 2018, to December 30, 2019, n=169) and a validation set (from October 1, 2020, to December 30, 2021, n=145). The least absolute shrinkage and selection operator (LASSO) regression analysis method and multivariable logistic regression analysis were used to identify the risk factors of limb weakness. A nomogram was established based on the training set. The discriminative ability and calibration of the nomogram to predict limb weakness were tested using the receiver operating characteristic (ROC) curve, calibration plots, and decision curve analysis (DCA). A validation set was used to further assess the model by external validation.
Results
Three hundred and fourteen patients with HZ of the extremities were included in the study. Three significant risk factors: age (OR=1.058, 95%CI: 1.021-1.100, p=0.003), VAS (OR=2.013, 95%CI: 1.101-3.790, p=0.024), involving C6 or C7 nerve roots (OR=3.218, 95%CI: 1.180-9.450, p=0.027) were selected by the LASSO regression analysis and the multivariable logistic regression analysis. The nomogram to predict limb weakness was constructed based on the three predictors. The area under the ROC was 0.751(95%CI: 0.673-0.829) in the training set and 0.705(95%CI: 0.619-0.791) in the validation set. The DCA indicated that using the nomogram to predict the risk of limb weakness would be more accurate when the risk threshold probability was 29- 68% in the training set and 32-57% in the validation set.
Conclusion
Age, VAS, and involving C6 or C7 nerve roots are of great value in terms of identifying risks for limb weakness in patients with HZ. Combined with the three indicators, we can modest accuracy predict the probability of limb weakness in patients with HZ.