The analysis of risk factors for stress ulcers after the surgery of acute cerebral hemorrhage and construction of Nomogram prediction model

Abstract

Objective To analysis of risk factors for stress ulcers after the surgery of acute cerebral hemorrhage, and use these factors to construct a Nomogram model. Methods In this study, 300 patients with acute cerebral hemorrhage treated in The First Affiliated Hospital of University of Science and Technology of China between January 2015 and November 2020 were recruited and divided into stress ulcers group (53 patients) and non⁃ulcers group (247 patients) according to whether the postoperative period was complicated by stress ulcers. Univariate and multivariate stepwise Logistic regression were used to assess the risk factors for stress ulcers after the surgery of acute cerebral hemorrhage and the Nomogram model was established. The receiver operating characteristic (ROC) curve and calibration curve of the model were plotted, and Hosmer⁃Lemeshow goodness of fit test was performed. Results Logistic regression showed that age increased (OR=1.043, 95%CI: 1.059-1.086; P=0.042), Glasgow Coma Scale (GCS) score≤8 (OR=2.809, 95%CI: 1.018-7.740; P=0.044), the cerebral hemorrhage volume≥30 ml (OR=3.830, 95%CI: 1.342-10.933; P=0.012), neutrophil to lymphocyte ratio (NLR) increased (OR=1.090, 95%CI:1.032-1.151; P=0.002), the increase of postoperative systolic blood pressure (OR=1.031, 95%CI: 1.008-1.055; P=0.008) and postoperative intracranial infection (OR=2.809, 95%CI: 1.006-7.847; P=0.049) were the risk factors for stress ulcers after the surgery of acute cerebral hemorrhage. The Nomogram model was established based on the 6 risk factors, and the area under curve (AUC) of ROC was 0.881 (95%CI: 0.821-0.942, P=0.001); the best cut⁃off value for predicting the risk of acute postoperative cerebral hemorrhage complicated by stress ulcers was 137. The calibration curves showed good agreement between the predicted and actual probabilities, and the Hosmer⁃Lemeshow goodness of fit test showed there was no statistical difference (χ2=7.891, P=0.445), indicating that the Nomogram model has good discrimination, calibration and stability. Conclusions Over⁃age, GCS score≤8, cerebral hemorrhage volume≥30 ml, NLR increase, postoperative systolic blood pressure increase and intracranial infection were the risk factors for stress ulcers after the surgery of acute cerebral hemorrhage. In conclusion, this Nomogram model is able to individually, visually and briefly predict the risk of postoperative complications of stress ulcers in patients after the surgery of acute cerebral hemorrhage.

Keywords

• cerebral hemorrhage
• ulcer
• logistic models
• nomograms