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成人肾移植受者感染性疾病预测的简易列线图。

A simple nomogram for predicting infectious diseases in adult kidney transplantation recipients.

机构信息

Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China.

Department of Critical Care Medicine, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.

出版信息

Front Public Health. 2022 Aug 31;10:944137. doi: 10.3389/fpubh.2022.944137. eCollection 2022.

Abstract

OBJECTIVE

To investigate the risk factors of infectious diseases in adult kidney transplantation recipients and to establish a simple and novel nomogram to guide the prophylactic antimicrobial therapy.

METHODS

Patients who received kidney transplantation between January 2018 and October 2021 were included in the study and were divided into a training and a testing set at a 1:1 ratio. Risk factors correlated to infectious diseases were selected using a Least Absolute Shrinkage and Selection Operator (LASSO) regression model. The prediction model was built by incorporating the variables selected by the LASSO model into a logistic regression equation. Calibration curves and receiver operating characteristic (ROC) curves were also applied to assess the model calibration and discrimination. A nomogram consisting of the selected factors was established to provide individualized risks of developing infections. Decision curve analysis (DCA) was adopted to estimate the net benefit and reduction in interventions for a range of clinically reasonable risk thresholds.

RESULTS

In all, 863 adult kidney recipients were included in the study, and 407 (47.16%) of them developed infectious diseases during the 3-year follow-up period. A total of 8 variables were selected using LASSO regression and were retained for subsequent model construction and infection prediction. The area under the curve (AUC) was 0.83 and 0.81 in the training and testing sets, with high F scores of 0.76 and 0.77, sensitivity of 0.76 and 0.81, and specificity of 0.88 and 0.74, respectively. A novel nomogram was developed based on 8 selected predictors (requirement for albumin infusion, requirement for red blood cell infusion, triglyceride, uric acid, creatinine, globulin, neutrophil percentage, and white blood cells). The net benefit indicated that the nomogram would reduce unnecessary interventions at a wide range of threshold probabilities in both sets.

CONCLUSIONS

Adult kidney transplantation recipients are high-risk hosts for infectious diseases. The novel nomogram consisting of 8 factors reveals good predictive performance and may promote the reasonable antimicrobial prescription. More external validations are required to confirm its effectiveness for further clinical application.

摘要

目的

探讨成人肾移植受者感染性疾病的危险因素,并建立一种简单新颖的列线图来指导预防性抗菌治疗。

方法

本研究纳入了 2018 年 1 月至 2021 年 10 月期间接受肾移植的患者,并以 1:1 的比例将其分为训练集和测试集。使用最小绝对值收缩和选择算子(LASSO)回归模型选择与感染性疾病相关的危险因素。通过将 LASSO 模型选择的变量纳入逻辑回归方程来构建预测模型。还应用校准曲线和受试者工作特征(ROC)曲线来评估模型的校准和区分能力。建立了一个包含选定因素的列线图,以提供感染风险的个体化估计。采用决策曲线分析(DCA)来评估在一系列合理的临床风险阈值范围内的净收益和干预措施的减少。

结果

共纳入 863 例成人肾移植受者,其中 407 例(47.16%)在 3 年随访期间发生感染性疾病。LASSO 回归共筛选出 8 个变量,用于后续模型构建和感染预测。在训练集和测试集中,曲线下面积(AUC)分别为 0.83 和 0.81,F 分数分别为 0.76 和 0.77,敏感性分别为 0.76 和 0.81,特异性分别为 0.88 和 0.74。基于 8 个选定的预测因子(白蛋白输注需求、红细胞输注需求、甘油三酯、尿酸、肌酐、球蛋白、中性粒细胞百分比和白细胞)开发了一种新的列线图。净收益表明,该列线图在两个数据集的广泛阈值概率范围内都可以减少不必要的干预。

结论

成人肾移植受者是感染性疾病的高危宿主。由 8 个因素组成的新列线图显示了良好的预测性能,可能有助于合理的抗菌药物处方。需要更多的外部验证来确认其在进一步临床应用中的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed2f/9471136/a59852310d73/fpubh-10-944137-g0001.jpg

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