Abstract: Objective  To construct a nomogram model for predicting survival rates in patients with aneurysmal subarachnoid hemorrhage, and to achieve individualized risk assessment for patients.
Methods  This retrospective cohort study enrolled consecutive patients diagnosed with aneurysmal subarachnoid hemorrhage at the First Affiliated Hospital of Dali University between September 1, 2016 and August 31, 2021. The clinical data and survival data were collected, with follow-up assessments conducted at 1 year, 3 years, and 5 years after onset. The median survival time of patients was estimated using the life table method, the survival curve was plotted using the Kaplan-Meier method, and the prognostic factors were analyzed using the Cox regression model to construct a nomogram model for predicting survival rates in aneurysmal subarachnoid hemorrhage patients. 
Results  A total of 441 patients were included in this study, 166 of whom were male, with a mean age of (58.0±10.4) years. The median survival time was 60 months by life table analysis, with cumulative survival probabilities of 63%, 56%, and 51% at 1-year, 3-years, and 5-years follow-up, respectively. Cox regression model results showed that advanced age, interventions (both surgical and non-surgical), prolonged time from onset to surgery, high acute-phase blood glucose level, large responsible aneurysm, prolonged duration of hyponatremia, re-ruptured aneurysm, and high Hunt-Hess grade were independent risk factors for the survival rates of aneurysmal subarachnoid hemorrhage. The nomogram model showed good discrimination and goodness of fit upon internal validation.
Conclusions  The nomogram model for survival rates in patients with aneurysmal subarachnoid hemorrhage constructed in this study can predict the survival probabilities of aSAH patients at 1 year, 3 years, and 5 years after onset and demonstrates good discrimination and goodness of fit.

Key words: Aneurysmal subarachnoid hemorrhage; Nomogram; Survival analysis; Multi-factor analysis; Prediction model construction

摘要： 目的 构建预测动脉瘤性蛛网膜下腔出血患者生存率的列线图模型，实现对患者的个体化风险评估。
方法 回顾性连续纳入2016年9月1日—2021年8月31日在大理大学第一附属医院诊断为动脉瘤性蛛网膜下腔出血的患者作为研究对象，收集其疾病资料和生存资料，并于发病后1年、3年、5年进行随访。通过寿命表法估计患者的中位生存时间，通过Kaplan-Meier法绘制生存曲线，通过Cox回归模型分析患者的预后影响因素，并构建用于预测动脉瘤性蛛网膜下腔出血患者生存率的列线图模型。
结果 本研究共纳入441例患者，其中男性166例，患者平均年龄为（58.0±10.4）岁。寿命表法分析中位生存时间为60个月，随访1年、3年、5年累计生存概率分别为63%、56%和51%。Cox回归模型结果表明，高龄、干预手段（包括手术方法和非手术方法）、发病到手术时间长、急性期血糖高、责任动脉瘤大、低钠血症时间长、动脉瘤再破裂和Hunt-Hess分级高是动脉瘤性蛛网膜下腔出血患者生存率的独立危险因素。列线图模型内部验证结果显示，其区分度和拟合度良好。
结论 本研究构建的动脉瘤性蛛网膜下腔出血患者生存率列线图模型，可预测aSAH患者发病后1年、3年、5年生存概率，且具有较好的区分度和拟合度。

关键词: 动脉瘤性蛛网膜下腔出血; 列线图; 生存分析; 多因素分析; 预测模型构建