原发性脑出血患者脑微出血发生风险预测列线图模型构建与验证

Construction and Validation of Nomogram Model for Predicting the Risk of Cerebral Microbleeds in Patients with Primary Cerebral Hemorrhage

目的 构建原发性脑出血患者脑微出血(CMBs)发生风险预测列线图模型,并验证其有效性。方法 选取2018年6月至2021年6月淮安市第二人民医院收治的原发性脑出血患者140例为研究对象,根据是否发生CMBs将其分为CMBs组(46例)和无CMBs组(94例)。收集患者临床资料,采用多因素Logistic回归分析探讨原发性脑出血患者发生CMBs的影响因素;基于多因素Logistic回归分析结果,采用R 3.6.3软件及rms程序包构建原发性脑出血患者CMBs发生风险预测列线图模型;绘制ROC曲线以评估该列线图模型预测原发性脑出血患者发生CMBs的区分度;采用Hosmer-Lemeshow拟合优度检验评估该列线图模型预测原发性脑出血患者发生CMBs的一致性。结果 CMBs组年龄大于无CMBs组,有高血压史、脑出血史者占比及超敏C反应蛋白(hs-CRP)、白蛋白高于无CMBs组(P<0.05)。多因素Logistic回归分析结果显示,年龄、高血压史、脑出血史、hs-CRP、白蛋白是原发性脑出血患者发生CMBs的影响因素(P<0.05)。基于多因素Logistic回归分析结果,将年龄、高血压史、脑出血史、hs-CRP、白蛋白引入R 3.6.3软件,建立原发性脑出血患者CMBs发生风险预测列线图模型。ROC曲线分析结果显示,该列线图模型预测原发性脑出血患者发生CMBs的曲线下面积为0.798〔95%CI(0.717,0.879)〕。Hosmer-Lemeshow拟合优度检验结果显示,该列线图模型预测原发性脑出血患者CMBs发生率与原发性脑出血患者CMBs实际发生率比较,差异无统计学意义(P>0.05)。结论 年龄增长、高血压史、脑出血史、hs-CRP升高、白蛋白升高是原发性脑出血患者发生CMBs的危险因素,基于上述危险因素构建的原发性脑出血患者CMBs发生风险预测列线图模型,对原发性脑出血患者发生CMBs具有一定预测价值和较好的准确性。

Objective To construct a nomogram model for predicting the risk of cerebral microbleeds(CMBs)in patients with primary cerebral hemorrhage,and to verify its validity.Methods A total of 140 patients with primary intracerebral hemorrhage who were admitted to Huaian Second People's Hospital from June 2018 to June 2021 were selected as the research objects,and they were divided into CMBs group(46 cases)and non-CMBs group(94 cases)according to whether CMBs occurred or not.The clinical data of the patients were collected,and multivariate Logistic regression analysis was used to explore the influencing factors of CMBs in patients with primary cerebral hemorrhage.Based on the results of multivariate Logistic regression analysis,R 3.6.3 software and rms program package were used to construct a nomogram model for predicting the risk of CMBs in patients with primary cerebral hemorrhage.The ROC curve was drawn to evaluate the discrimination of this nomogram model in predicting CMBs in patients with primary intracerebral hemorrhage.The Hosmer-Lemeshow goodness-of-fit test was used to evaluate the consistency of the nomogram model in predicting CMBs in patients with primary intracerebral hemorrhage.Results The age of the CMBs group was older than that of the non-CMBs group,and the proportion of patients with history of hypertension and cerebral hemorrhage, hypersensitive C-reactive protein (hs-CRP) and albumin were higher than those of the non-CMBs group (P < 0.05) . Multivariate Logistic regression analysis results showed that age, history of hypertension, history of cerebral hemorrhage, hs-CRP and albumin were the influencing factors of CMBs in patients with primary cerebral hemorrhage (P < 0.05) . Based on the results of multivariate Logistic regression analysis, age, history of hypertension, history of cerebral hemorrhage, hs- CRP, and albumin were introduced into R 3.6.3 software, and the nomogram model for predicting the risk of CMBs in patients with primary cerebral hemorrhage was established. The results of ROC curve analysis showed that the area under curve of nomogram model for predicting CMBs in patients with primary intracerebral hemorrhage was 0.798 [95%CI (0.717, 0.879) ] . The results of the Hosmer-Lemeshow goodness of fit test showed that there was no significant difference between the incidence of CMBs predicted by nomogram model and the actual incidence of CMBs in patients with primary cerebral hemorrhage (P > 0.05) . Conclusion Increased age, history of hypertension, history of cerebral hemorrhage, elevated hs-CRP, and elevated albumin are risk factors for CMBs in patients with primary cerebral hemorrhage. The nomogram model for predicting the risk of CMBs in patients with primary cerebral hemorrhage constructed based on the above risk factors has certain predictive value and good accuracy for CMBs in patients with primary cerebral hemorrhage.