Meng L, Zhu X, Yang L, Li X, Cheng S, Guo S, Zhuang X, Zou H, Cui W
Department of Nephrology, Second Hospital of Jilin University, Changchun 130041, China.
Department of Nephrology, Second Division of First Hospital of Jilin University, Changchun 130031, China.
Nan Fang Yi Ke Da Xue Xue Bao. 2022 Apr 20;42(4):546-553. doi: 10.12122/j.issn.1673-4254.2022.04.10.
To develop and validate a risk prediction model of treatment failure in patients with peritoneal dialysis-associated peritonitis (PDAP).
We retrospectively analyzed the data of patients undergoing peritoneal dialysis (PD) in 3 dialysis centers in Jilin Province who developed PDAP between January 1, 2013 and December 31, 2019. The data collected from the Second Hospital of Jilin University and Second Division of First Hospital of Jilin University) were used as the training dataset and those from Jilin Central Hospital as the validation dataset. We developed a nomogram for predicting treatment failure using a logistic regression model with backward elimination. The performance of the nomogram was assessed by analyzing the C-statistic and the calibration plots. We also plotted decision curves to evaluate the clinical efficacy of the nomogram.
A total of 977 episodes of PDAP were included in the analysis (625 episodes in the training dataset and 352 episodes in the validation dataset). During follow-up, 78 treatment failures occurred in the training dataset and 35 in the validation dataset. A multivariable logistic regression prediction model was established, and the predictors in the final nomogram model included serum albumin, peritoneal dialysate white cell count on day 5, PD duration, and type of causative organisms. The nomogram showed a good performance in predicting treatment failure, with a C-statistic of 0.827 (95% : 0.784-0.871) in the training dataset and of 0.825 (95% : 0.743-0.908) in the validation dataset. The nomogram also performed well in calibration in both the training and validation datasets.
The established nomogram has a good accuracy in estimating the risk of treatment failure in PDAP patients.
建立并验证腹膜透析相关性腹膜炎（PDAP）患者治疗失败的风险预测模型。
我们回顾性分析了2013年1月1日至2019年12月31日期间吉林省3个透析中心接受腹膜透析（PD）且发生PDAP的患者数据。从吉林大学第二医院和吉林大学第一医院第二分院收集的数据用作训练数据集，从吉林市中心医院收集的数据用作验证数据集。我们使用逐步向后消除的逻辑回归模型开发了用于预测治疗失败的列线图。通过分析C统计量和校准图来评估列线图的性能。我们还绘制了决策曲线以评估列线图的临床疗效。
分析共纳入977例PDAP发作（训练数据集625例，验证数据集352例）。随访期间，训练数据集中发生78例治疗失败，验证数据集中发生35例。建立了多变量逻辑回归预测模型，最终列线图模型中的预测因素包括血清白蛋白、第5天腹膜透析液白细胞计数、PD持续时间和致病菌类型。列线图在预测治疗失败方面表现良好，训练数据集中的C统计量为0.827（95%：0.784 - 0.871），验证数据集中为0.825（95%：0.743 - 0.908）。列线图在训练和验证数据集中的校准方面也表现良好。
所建立的列线图在估计PDAP患者治疗失败风险方面具有良好的准确性。
