Construction and validation of nomogram model for prolonged length of stay in patients with acute cerebral infarction based on total cerebral small vessel disease burden scores
10.3969/j.issn.1673-9701.2025.08.003
- VernacularTitle:基于脑小血管病影像学总负荷的急性脑梗死患者住院时间延长研究
- Author:
Erli ZHANG
1
;
Lanlan HE
;
Danyang LI
;
Li SHEN
;
Zhonghua WU
;
Jun ZHANG
;
Yongqiang YE
Author Information
1. 湖州学院附属南太湖医院放射科,浙江湖州 313000
- Publication Type:Journal Article
- Keywords:
Acute cerebral infarction;
Total burden score;
Prolonged length of stay;
Nomogram
- From:
China Modern Doctor
2025;63(8):9-13
- CountryChina
- Language:Chinese
-
Abstract:
Objective To construct a nomogram model for prolonged length of stay in patients with acute cerebral infarction(ACI)based on total cerebral small vessel disease(CSVD)burden scores,and validate its effectiveness.Methods A total of 462 ACI patients admitted to the Department of Neurology of South Taihu Hospital Affiliated To Huzhou College from January 2021 to December 2023 were selected as the study subjects.According to the ratio of 7:3,patients were divided into training group of 323 cases and validation group of 139 cases.Lasso-Logistic regression was used to analyze the risk factors for prolonged length of stay in ACI patients,construct a nomogram model and validate the model using validation data.Receiver operating characteristic(ROC)curve were used to evaluate the predictive performance of the model.Results Based on the training group data,Lasso regression screened four non-zero coefficient indicators,including baseline National Institutes of Health stroke scale(NIHSS)score,age-adjusted Charlson comorbidity index(aCCI)score,neutrophil to lymphocyte ratio(NLR)and total CSVD burden score.Multivariate Logistic regression analysis showed that baseline NIHSS score,aCCI score,NLR and total CSVD burden score were independent risk factors for prolonged length of stay in ACI patients(P＜0.05).Based on the above four indicators,a nomogram model was constructed.The results showed that the ROC curve area of the model predicted prolonged length of stay between training group and validation group were 0.812(95％CI:0.756-0.868)and 0.820(95％CI:0.730-0.909).Conclusion The nomogram model for prolonged length of stay in ACI patients based on total CSVD burden score has good predictive performance and can be used as a screening tool for evaluating the prolonged length of stay in ACI patients.
