Abstract:

Objective　To investigate the influencing factors of rebleeding in patients with spontaneous intracerebral hemorrhage in intensive care unit (ICU), and to establish a nomogram prediction model. Methods　The clinical data of 173 patients with spontaneous cerebral hemorrhage in ICU of Wuxi Second People's Hospital from June 2019 to June 2022 were retrospectively analyzed. According to whether the patients had rebleeding or not, they were divided into a rebleeding group (38 cases) and a non-rebleeding group (135 cases). The general data of the two groups were compared. Multivariate logistic regression analysis was used to analyze the influencing factors of rebleeding in patients with spontaneous intracerebral hemorrhage in ICU. R3.4.3 software package was used to draw the nomogram model, and the receiver operating characteristic curve (ROC) was drawn to evaluate the predictive efficacy of the nomogram model. The calibration curve was drawn to evaluate the discrimination of the nomogram model, and the Bootstrap method was used to test the consistency of the prediction nomogram model. t test and χ² test were used. Results　In the rebleeding group, there were 24 males and 14 females, aged (61.57±7.53) years. In the non-rebleeding group, there were 75 males and 60 females, aged (59.08±7.39) years. There were no statistically significant differences in the gender, age, body mass index (BMI), smoking history, drinking history, diabetes history, etiology classification, Glasgow Coma Scale (GCS) score, hematoma shape, hematoma location, bleeding volume, operation mode, preoperative systolic blood pressure, preoperative diastolic blood pressure, preoperative platelet count, and postoperative use of hemostatic drugs between the rebleeding group and the non-rebleeding group (all P>0.05). In the rebleeding group, the ratios of long-term use of anticoagulants, uneven hematoma density, operation timing of 3-6 h, unsatisfactory postoperative blood pressure control, and postoperative agitation and levels of preoperative blood glucose and preoperative D-dimer were higher than those in the non-rebleeding group [47.37% (18/38) vs. 24.44% (33/135), 71.05% (27/38) vs. 43.70% (59/135), 31.58% (12/38) vs. 10.37% (14/135), 18.42% (7/38) vs. 2.96% (4/135), 42.11% (16/38) vs. 22.96% (31/135), (6.39±1.02) mmol/L vs. (5.95±1.25) mmol/L, (0.51±0.04) mg/L vs. (0.43±0.05) mg/L], with statistically significant differences (χ²=7.496, 8.872, 10.476, 12.924, and 5.491, t=1.990 and 9.073; all P<0.05). Multivariate logistic regression analysis showed that long-term use of anticoagulants, uneven hematoma density, operation timing of 3-6 h, elevated preoperative D-dimer level, unsatisfactory postoperative blood pressure control, and postoperative agitation were all risk factors for rebleeding in ICU patients with spontaneous cerebral hemorrhage (all P<0.05). ROC analysis results showed that the area under the curve (AUC), sensitivity, and specificity of the nomogram for predicting rebleeding in ICU patients with spontaneous cerebral hemorrhage were 0.848 (95%CI 0.799 - 0.887), 76.32%, and 84.44%, respectively. The Bootstrap method was used to verify the model, and the consistency index (C-index) was 0.829. The calibration curve was in good agreement with the standard curve. Conclusions　Long-term use of anticoagulants, uneven hematoma density, operation timing of 3-6 h, elevated D-dimer level, unsatisfactory postoperative blood pressure control, and postoperative agitation are all risk factors for rebleeding in patients with spontaneous cerebral hemorrhage in ICU. The nomogram model based on the above influencing factors has good predictive efficacy, which is conducive to early clinical screening of rebleeding in ICU patients with spontaneous cerebral hemorrhage.

Key words:

Intensive care unit, Spontaneous cerebral hemorrhage, Rebleeding, Nomogram, Prediction model

摘要：

目的　探讨重症监护室（ICU）自发性脑出血患者再出血的影响因素，并依此建立列线图预测模型。方法　回顾性分析2019年6月至2022年6月无锡市第二人民医院收治的173例ICU自发性脑出血患者的临床资料，根据患者有无再出血将其分为再出血组（38例）和未再出血组（135例）。比较两组患者一般资料，采用多因素logistic回归分析法分析ICU自发性脑出血患者再出血的影响因素，并采用R3.4.3软件包绘制列线图模型，另绘制受试者操作特征曲线（ROC）以评估列线图模型的预测效能，绘制校准曲线图评估列线图的区分度，采用Bootstrap法检验预测列线图模型的一致性。采用t检验、χ²检验。结果　再出血组男24例、女14例，年龄（61.57±7.53）岁；未再出血组男75例、女60例，年龄（59.08±7.39）岁。两组患者性别、年龄、体质量指数（BMI）、吸烟史、饮酒史、糖尿病史、病因分型、格拉斯哥昏迷量表（GCS）评分、血肿形状、血肿位置、出血量、手术方式、术前收缩压、术前舒张压、术前血小板计数、术后使用止血药比较，差异均无统计学意义（均P>0.05）；再出血组长期使用抗凝药、血肿密度不均匀、手术时机3～6 h、术后血压控制不理想、术后躁动占比及术前血糖、术前D-二聚体水平均高于未再出血组［47.37%（18/38）比24.44%（33/135）、71.05%（27/38）比43.70%（59/135）、31.58%（12/38）比10.37%（14/135）、18.42%（7/38）比2.96%（4/135）、42.11%（16/38）比22.96%（31/135）、（6.39±1.02）mmol/L比（5.95±1.25）mmol/L、（0.51±0.04）mg/L比（0.43±0.05）mg/L］，差异均有统计学意义（χ²=7.496、8.872、10.476、12.924、5.491，t=1.990、9.073；均P<0.05）。多因素logistic回归分析显示，长期使用抗凝药、血肿密度不均匀、手术时机为3～6 h、术前D-二聚体水平升高、术后血压控制不理想、术后躁动均是ICU自发性脑出血患者再出血的危险因素（均P<0.05）。ROC分析结果显示，列线图预测ICU自发性脑出血患者再出血的曲线下面积（AUC）为0.848（95%CI 0.799～0.887），灵敏度为76.32%，特异度为84.44%。经Bootstrap法对模型进行验证，其一致性指数（C-index）为0.829，校正曲线与标准曲线贴合度较好。结论　长期使用抗凝药、血肿密度不均匀、手术时机为3～6 h、术前D-二聚体水平升高、术后血压控制不理想、术后躁动均是ICU自发性脑出血患者再出血的危险因素，基于以上影响因素构建的列线图模型具有较好的预测效能，有利于临床早期筛选ICU自发性脑出血患者再出血。

关键词:

重症监护室, 自发性脑出血, 再出血, 列线图, 预测模型