Zhao Lina, Li Yun, Wang Yunying, Gao Qian, Ge Zengzheng, Sun Xibo, Li Yi
Emergency Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Department of Critical Care Medicine, Chifeng Municipal Hospital, Chifeng Clinical Medical College of Inner Mongolia Medical University, Chifeng, China.
Front Microbiol. 2021 Aug 19;12:737066. doi: 10.3389/fmicb.2021.737066. eCollection 2021.
Hospital mortality is high for patients with encephalopathy caused by microbial infection. Microbial infections often induce sepsis. The damage to the central nervous system (CNS) is defined as sepsis-associated encephalopathy (SAE). However, the relationship between pathogenic microorganisms and the prognosis of SAE patients is still unclear, especially gut microbiota, and there is no clinical tool to predict hospital mortality for SAE patients. The study aimed to explore the relationship between pathogenic microorganisms and the hospital mortality of SAE patients and develop a nomogram for the prediction of hospital mortality in SAE patients.
The study is a retrospective cohort study. The lasso regression model was used for data dimension reduction and feature selection. Model of hospital mortality of SAE patients was developed by multivariable Cox regression analysis. Calibration and discrimination were used to assess the performance of the nomogram. Decision curve analysis (DCA) to evaluate the clinical utility of the model.
Unfortunately, the results of our study did not find intestinal infection and microorganisms of the gastrointestinal (such as: Escherichia coli) that are related to the prognosis of SAE. Lasso regression and multivariate Cox regression indicated that factors including respiratory failure, lactate, international normalized ratio (INR), albumin, SpO, temperature, and renal replacement therapy were significantly correlated with hospital mortality. The AUC of 0.812 under the nomogram was more than that of the Simplified Acute Physiology Score (0.745), indicating excellent discrimination. DCA demonstrated that using the nomogram or including the prognostic signature score status was better than without the nomogram or using the SAPS II at predicting hospital mortality.
The prognosis of SAE patients has nothing to do with intestinal and microbial infections. We developed a nomogram that predicts hospital mortality in patients with SAE according to clinical data. The nomogram exhibited excellent discrimination and calibration capacity, favoring its clinical utility.
微生物感染所致脑病患者的医院死亡率很高。微生物感染常诱发脓毒症。对中枢神经系统（CNS）的损害被定义为脓毒症相关性脑病（SAE）。然而，致病微生物与SAE患者预后之间的关系仍不清楚，尤其是肠道微生物群，且尚无临床工具可预测SAE患者的医院死亡率。本研究旨在探讨致病微生物与SAE患者医院死亡率之间的关系，并建立一个预测SAE患者医院死亡率的列线图。
本研究为回顾性队列研究。采用套索回归模型进行数据降维和特征选择。通过多变量Cox回归分析建立SAE患者医院死亡率模型。采用校准和鉴别来评估列线图的性能。采用决策曲线分析（DCA）评估模型的临床实用性。
遗憾的是，我们的研究结果未发现肠道感染及胃肠道微生物（如：大肠杆菌）与SAE的预后相关。套索回归和多变量Cox回归表明，呼吸衰竭、乳酸、国际标准化比值（INR）、白蛋白、SpO、体温和肾脏替代治疗等因素与医院死亡率显著相关。列线图下的AUC为0.812，高于简化急性生理学评分（0.745），表明具有良好的鉴别能力。DCA表明，在预测医院死亡率方面，使用列线图或纳入预后特征评分状态比不使用列线图或使用急性生理学和慢性健康状况评分系统II（SAPS II）更好。
SAE患者的预后与肠道及微生物感染无关。我们根据临床数据建立了一个预测SAE患者医院死亡率的列线图。该列线图具有良好的鉴别和校准能力，有利于其临床应用。
