Yunnan Key Laboratory of Urology, Yunnan Urology Speciality Hospital, The Second Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, People's Republic of China.
Sci Rep. 2020 Jul 9;10(1):11337. doi: 10.1038/s41598-020-68430-3.
To discuss the mechanisms of infection complications in different degrees after percutaneous nephrolithotomy (PCNL) through predicting and comparing post-PCNL infections based on nomograms, a retrospective cohort study was conducted among 969 cases who underwent PCNL from Dec 5, 2016 to Dec 25, 2017 in Kunming, Yunnan Province. We examined clinical features, urine routine, blood routine, blood biochemistry, imaging studies and operative information and recorded the examination results before surgery for univariate and multivariate logistic regression. We applied receiver operating characteristic curves, calibration curves, accuracy, specificity, sensitivity, positive predictive value and negative predictive value to evaluate and compare the models. Nomograms were used to visualize the different degrees of postoperative infection complications. The risk scores of the three groups were compared by diabetes mellitus distribution. Our results suggest that the more severe the infection is, the more accurate the model predicts and that the occurrence of severe infection mostly is related to the patients' homeostasis. Hence, we developed an online post-PCNL sepsis dynamic nomogram which can achieve visualization and dynamically predict the incidence of sepsis in postoperative patients.
为探讨经皮肾镜碎石取石术（PCNL）后不同程度感染并发症的机制，通过列线图预测并比较 PCNL 术后感染，我们对 2016 年 12 月 5 日至 2017 年 12 月 25 日在云南省昆明市接受 PCNL 的 969 例患者进行了回顾性队列研究。我们检查了临床特征、尿常规、血常规、血液生化、影像学研究和手术信息，并记录了手术前的检查结果，进行单因素和多因素逻辑回归分析。我们应用受试者工作特征曲线、校准曲线、准确性、特异性、敏感性、阳性预测值和阴性预测值来评估和比较模型。列线图用于可视化术后不同程度的感染并发症。通过糖尿病分布比较三组的风险评分。我们的结果表明，感染越严重，模型预测越准确，严重感染的发生主要与患者的内稳态有关。因此，我们开发了一种在线 PCNL 脓毒症动态列线图，可以实现可视化并动态预测术后脓毒症的发生率。
