摘要
目的建立一个可视化的列线图,以期早期预测腹腔感染的预后。方法本次研究选取2017年6月~2020年1月在新疆医科大学第一附属医院接受治疗的105例胃肠道相关的腹腔感染患者为研究对象,分为好转组和恶化组,分析患者的一般资料、临床特征检验指标、白细胞计数(WBC)、中性粒细胞百分比(NE)、血小板计数(PLT)、降钙素原(PCT)、血小板分布宽度(PDW)、谷草转氨酶(AST)、谷丙转氨酶(ALT)、尿素氮(UREA)、总胆红素(TBIL)、直接胆红素(CB)、非结合胆红素(UCB)、人血白蛋白(ALB)、血肌酐(CRE)、胱抑素C(CysC),对纳入的相关临床指标进行Logistic逐步回归分析,根据有统计学差异的指标得出回归方程式,利用R语言软件可视化处理逐步回归模型获得列线图,并通过受试者工作特征(ROC)曲线分析验证。结果经Logistic逐步回归分析模型的回归方程式为Y=10.988+3.702×休克-0.021×PLT7+0.202×UREA1+0.116×NE7。列线图总分超过106分有发生恶化的可能,总分超过150分发生恶化将高达99%以上。进一步通过ROC曲线分析验证,本研究建立的逐步回归模型的曲线下面积(AUC)预测恶化发生的灵敏度、特异度均优于NE、PLT、PCT、PDW、AST、UREA、TBIL、CRE、CysC单独预测。结论本研究建立的可视化列线图可能是预测腹腔感染预后的有效临床工具,逐步回归模型比各指标单独预测腹腔感染病情严重程度的灵敏度、特异度均更优。
Objective To establish a visual nomogram with early prognostic value for abdominal infection.Methods In this study,105 patients with gastroenteric related intra-abdominal infection who were treated in the First Affiliated Hospital of Xinjiang Medical University from June 2017 to January 2020 were selected as the research objects,and they were divided into improvement group and deterioration group.The general information and clinical characteristics,white blood cell count(WBC),neutrophil percentage(NE),platelet count(PLT)of the patients were counted and analyzed Procalcitonin(PCT),platelet distribution width(PDW),aspartate aminotransferase(AST),alanine aminotransferase(ALT),urea nitrogen(urea),total bilirubin(TBIL),direct bilirubin(CB),unconjugated bilirubin(UCB),human albumin(ALB),serum creatinine(CRE),Cystatin C(CysC).Logistic stepwise regression analysis was used to analyze the relevant clinical indicators.Regression equations were obtained according to the indicators with statistical differences.R language software was used to visualize the stepwise regression model to obtain nomogram,which was verified by receiver operating characteristic(ROC)curve analysis.Results The regression equation of Logistic step-up regression analysis model wasY=10.988+3.702×shock-0.021×PLT7+0.202×UREA1+0.116×NE7.The total score of the nomogram over 106 has the possibility of deterioration,and the total score over 150 has the possibility of deterioration over 99%.Further verified by ROC curve analysis,the sensitivity and specificity of AUC of the stepwise regression model established in this study were better than that of NE,PLT,PCT,PDW,AST,TBIL,CRE and CysC in predicting the occurrence of deterioration.Conclusion This nomogram may be an effective clinical tool to predict the prognosis of celiac infection,and the stepwise regression model has better sensitivity and specificity than each indicator alone to predict the severity of celiac infection.
作者
谷兴丽
唐丹丹
杨春波
于朝霞
GU Xingli;Tamg Dandan;YANG Chunbo;YU Zhaoxia(ICU,The First Affiliated Hospital of Xinjiang Medical University,Urumqi 830054,China;Xingjiang Medical Univeristy, Urumqi 830054,China)
出处
《西部医学》
2021年第6期865-868,共4页
Medical Journal of West China
基金
国家自然科学基金(81660005)。
关键词
腹腔感染
列线图
预后
临床特征
Intra-abdominal infections
The column chart
The prognosis
Clinical features
