载脂蛋白AⅠ对肺栓塞患者预后的影响

Influence of apoAⅠon prognosis of patients with pulmonary embolism

摘要:

目的： 探讨入院时载脂蛋白AⅠ（apolipoprotein AⅠ，apoAⅠ）水平对肺栓塞（pulmonary embolism，PE）患者预后的影响。方法： 回顾性收集2013年8月1日至2019年8月15日于西南医科大学附属医院住院并首诊为PE的患者161例。运用受试者工作特征（receiver operating characteristic，ROC）曲线计算apoAⅠ预测全因死亡的最适截断值，根据其结果分为高水平组和低水平组。以入院时间为起始点，2019年9月15日为随访截止时间，研究截点事件为全因死亡。采用Kaplan-Meier分析法描绘生存曲线及使用log-rank检验比较2条生存曲线，应用单因素及多因素Cox回归模型分析apoAⅠ等对PE患者预后的影响。结果： 患者随访期间死亡39例，病死率24.22%。ROC曲线计算apoAⅠ最佳截断值为0.965 g/L，曲线下面积（area under the curve，AUC）为0.716，95%CI=0.616～0.815。高水平组（≥0.965 g/L，112例）、低水平组（<0.965 g/L，49例）患者分别死亡15例、24例。高水平组PE患者病死率约为13.39%，低水平组病死率为48.98%。使用单因素Cox分析，对PE患者预后有意义的指标包括年龄、危险分层、TC、恶性肿瘤史、使用他汀类药物、apoAⅠ水平（P<0.2）。多因素Cox回归模型分析显示影响PE预后的独立因素为年龄（P=0.001）、使用他汀类药物（P=0.003）、恶性肿瘤史（P=0.001）、apoAⅠ水平（P=0.004）。apoAⅠ<0.965 g/L对PE患者预后有一定预测价值。Log-rank检验显示，低水平组apoAⅠ生存率明显低于高水平组，差异有统计学意义（P=0.000）。结论： 入院时apoAⅠ的降低与PE患者死亡风险增加有关，能够预测其预后。

Abstract:

Objective: To investigate the influence of apolipoprotein AⅠ (apoAⅠ) at admission on the prognosis of patients with pulmonary embolism (PE). Methods: A total of 161 patients who were hospitalized with initial diagnosis of PE in our hospital from August 1, 2013 to August 15, 2019 were retrospectively screened. The receiver operating characteristic (ROC) curve was used to calculate the optimal cut-off value of apoA I and patients were divided respectively into 2 groups which contained the low level group and the high level group. Follow-up was started with the admission time, and the deadline was September 15, 2019. The end-event was all-cause death. Kaplan-Meier method was applied to draw the survival curves and log-rank test was used to compare two curves. Univariate and multivariate Cox proportional hazards regression model analysis was used to analyze variables included apoAⅠwhich potentially influenced the prognosis. Results: During the follow-up period, 39 patients died by all-cause, with fatality rate of 24.22%. The optimal cut-off of ROC was 0.965 g/L and the area under the curve (AUC) was 0.716 (95%CI=0.616-0.815). The cases of dead patients in the high level apoAⅠgroup (≥0.965 g/L, n=112), and low level apoAⅠgroup (<0.965 g/L, n=49) were 15 and 24, respectively. The fatality rate of patients in the low level group was 48.98%and in the high level group was 13.39%. Univariate Cox proportional hazards regression model analysis showed that age, total cholesterol, malignant tumor, the use of statins and the level of apoAⅠhad significance to prognosis of patients (P<0.2). Multivariate Cox proportional hazards regression model analysis concluded that age (P=0.001), the use of statins (P=0.003), malignant tumor (P=0.001) and level of apoAⅠ (P=0.004) were independent factors influencing PE prognosis, indicating that apoAⅠ<0.965 g/L was of predictive value to the prognosis of patients with PE. Log-rank test indicated that survival rate in the low level group was significantly lower than that in the high level group, with statistically significant difference (P=0.000). Conclusion: The decrease of apoAⅠlevel detected in admission is related with the increase of mortality risk, which can predict the prognosis of patients with PE.