Analysis of Prognostic Factors for Patients with Acute Cerebral Infarction and Construction of Risk Column Chart Model
Objective To explore the prognostic factors for patients with acute cerebral infarction(ACI)and to construct a risk column chart model.Methods A total of 170 ACI patients admitted to the hospital from January 2020 to January 2023 were selected as the study objects,and the patients were divided into good prognosis group and poor prognosis group according to the prognosis results.Serum levels of copeptin,osteopontin(OPN)and glial fibrillary acidic protein(GFAP)were detected in the two groups,and clinical data and laboratory indicators were collected.Logistic regression analysis was used to identify the risk factors for poor prognosis in ACI patients,and a prognostic risk nomogram prediction model for ACI patients was constructed based on independent risk factors.Receiver operating characteristic(ROC)curve,Bootstrap method and Calibration curve were used to evaluate the prediction efficiency,differentiation and calibration of the prediction model.Results Among the 170 patients,70 had a Glasgow outcome scale(GOS)score of ≤3,with a poor prognosis rate of 41.18％(70/170).The proportion of aged ≥60 years old,platelet to lymphocyte ratio(PLR)＞2.83,neutrophil to lymphocyte ratio(NRL)＞130.50,infarct degree(severity),and copeptin,OPN,GFAP levels in the poor prognosis group were higher than those in the good prognosis group(P＜0.05).Logistic regression analysis showed that aged ≥60 years old,PLR＞2.83,NRL＞130.50,copeptin＞34.26 pmol·L-1,OPN＞7.21 μg·L-1,GFAP＞7.51 μg·L-1,infarct degree(severity)were independent risk factors for poor prognosis in ACI patients(P＜0.05).According to the results of logistic regression analysis,a prognosis prediction model for ACI patients was constructed,and the model was well differentiated by Bootstrap method(C-index=0.815).Calibration curve analysis showed a good fit(Hosmer-Lemeshow x2=1.325,P=0.157).ROC curve showed that area under the curve,sensitivity,specificity and Jorden index of the prediction model were 0.827(95％CI:0.726-0.964),90.40％,79.30％and 70.70％,respectively.Conclusion Aged ≥ 60 years old,PLR＞2.83,NRL＞130.50,copeptin＞34.26 pmol·L-1,OPN＞7.21 μg·L-1,GFAP＞7.51 μg·L-1,infarct degree(severity)were all independent risk factors for poor prognosis in ACI patients.The prediction model based on the nomogram has good differentiation and calibration degree,and the model has high predictive efficiency for the occurrence of poor prognosis in ACI patients.
万方数据
维普
