Ya-Ying Zeng1,2, Wen-Bo Zhang3, Lin Cheng1,2, Li Wang4, Dan-Dan Geng2, Wen-Jie Tang5, Jin-Cai He6, Bin-Bin Deng7. 1. Department of Neurology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China. 2. First School of Clinical Medicine, Wenzhou Medical University, Wenzhou, China. 3. Department of Neurosurgery, The Children's Hospital of Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China. 4. Department of Gastroenterology and Hepatology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China. 5. First School of Clinical Medicine, Wenzhou Medical University, Wenzhou, China. 13606777777@163.com. 6. Department of Neurology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China. hjc@wmu.edu.cn. 7. Department of Neurology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China. dbinbin@aliyun.com.
Abstract
BACKGROUND: Although large artery atherosclerosis (LAA) is the most common type of cerebral infarction, non-LAA is not uncommon. The purpose of this paper is to investigate the prognosis of patients with non-LAA and to establish a corresponding nomogram. PATIENTS AND METHODS: Between June 2016 and June 2017, we had 1101 admissions for acute ischemic stroke (AIS). Of these, 848 were LAA and 253 were non-LAA. Patients were followed up every 3 months with a minimum of 1 year of follow-up. After excluding patients who were lost follow-up and patients who did not meet the inclusion criteria, a total of 152 non-LAA patients were included in this cohort study. After single-factor analysis and multifactor logistic regression analysis, the risk factors associated with prognosis were derived and different nomograms were developed based on these risk factors. After comparison, the best model is derived. RESULTS: Logistics regression found that the patient's National Institutes of Health Stroke Scale (NIHSS) score, ejection fraction (EF), creatine kinase-MB (CK-MB), age, neutrophil-to-lymphocyte ratio (NLR), aspartate aminotransferase (AST), and serum albumin were independently related to the patient's prognosis. We thus developed three models: model 1: single NIHSS score, AUC = 0.8534; model 2, NIHSS + cardiac parameters (CK-MB, EF), AUC = 0.9325; model 3, NIHSS + CK-MB + EF + age + AST + NLR + albumin, AUC = 0.9598. We compare the three models: model 1 vs model 2, z = - 2.85, p = 0.004; model 2 vs model 3, z = - 1.58, p = 0.122. Therefore, model 2 is considered to be the accurate and convenient model. CONCLUSIONS: Predicting the prognosis of patients with non-LAA is important, and our nomogram, built on the NIHSS and cardiac parameters, can predict the prognosis accurately and provide a powerful reference for clinical decision making.
BACKGROUND: Although large artery atherosclerosis (LAA) is the most common type of cerebral infarction, non-LAA is not uncommon. The purpose of this paper is to investigate the prognosis of patients with non-LAA and to establish a corresponding nomogram. PATIENTS AND METHODS: Between June 2016 and June 2017, we had 1101 admissions for acute ischemic stroke (AIS). Of these, 848 were LAA and 253 were non-LAA. Patients were followed up every 3 months with a minimum of 1 year of follow-up. After excluding patients who were lost follow-up and patients who did not meet the inclusion criteria, a total of 152 non-LAA patients were included in this cohort study. After single-factor analysis and multifactor logistic regression analysis, the risk factors associated with prognosis were derived and different nomograms were developed based on these risk factors. After comparison, the best model is derived. RESULTS: Logistics regression found that the patient's National Institutes of Health Stroke Scale (NIHSS) score, ejection fraction (EF), creatine kinase-MB (CK-MB), age, neutrophil-to-lymphocyte ratio (NLR), aspartate aminotransferase (AST), and serum albumin were independently related to the patient's prognosis. We thus developed three models: model 1: single NIHSS score, AUC = 0.8534; model 2, NIHSS + cardiac parameters (CK-MB, EF), AUC = 0.9325; model 3, NIHSS + CK-MB + EF + age + AST + NLR + albumin, AUC = 0.9598. We compare the three models: model 1 vs model 2, z = - 2.85, p = 0.004; model 2 vs model 3, z = - 1.58, p = 0.122. Therefore, model 2 is considered to be the accurate and convenient model. CONCLUSIONS: Predicting the prognosis of patients with non-LAA is important, and our nomogram, built on the NIHSS and cardiac parameters, can predict the prognosis accurately and provide a powerful reference for clinical decision making.
Authors: E Murat Arsava; Johanna Helenius; Ross Avery; Mine H Sorgun; Gyeong-Moon Kim; Octavio M Pontes-Neto; Kwang Yeol Park; Jonathan Rosand; Mark Vangel; Hakan Ay Journal: JAMA Neurol Date: 2017-04-01 Impact factor: 18.302
Authors: Valery L Feigin; Carlene M M Lawes; Derrick A Bennett; Suzanne L Barker-Collo; Varsha Parag Journal: Lancet Neurol Date: 2009-02-21 Impact factor: 44.182