Chen Jiajia, Shen Cheng, Xue Haiyan, Yuan Benyin, Zheng Bing, Shen Lianglan, Fang Xingxing
Department of Nephrology, Affiliated Hospital 2 of Nantong University, Nantong, 226001, China.
Department of Urology, Affiliated Hospital 2 of Nantong University, Nantong, China.
Sci Rep. 2025 Mar 26;15(1):10434. doi: 10.1038/s41598-025-95287-1.
Hemodialysis patients (HD) frequently experience nausea and vomiting as side effects, which can make the procedure uncomfortable for them and cause it to end too soon. There are no known predictors of vomiting. We aim to create a nomogram that can anticipate vomiting in hemodialysis patients. We conducted a retrospective screening of patients with end-stage renal disease (ESRD) who received regular hemodialysis at the First People's Hospital of Nantong from January 1, 2023, to October 31, 2024. The outcome of the nomogram indicated vomiting, which was evaluated using the Korttila scale. The least absolute shrinkage selection operator (LASSO) method and Boruta feature selection were employed for the optimal prediction of predictors. Multiple logistic regression was employed to construct predictive models presented as nomograms. The efficacy of nomograms was evaluated using receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). The model underwent internal validation by assessing the validation cohort's performance. The study included 281 patients. Ninety-two patients, representing 32.74%, exhibited symptoms of vomiting. Participants were randomly assigned to training (n = 196) and validation (n = 85) groups. The nomogram incorporated predictors such as sex, height, heart rate, spKt.V, lymphocytes, and lactate dehydrogenase. The ROC curves for both the training and verification groups demonstrate strong recognition capability, while the calibration curves indicate that the correction outcomes for both groups are highly satisfactory. This nomogram assists clinicians in identifying high-risk populations and supports the formulation of effective preventive strategies.
血液透析患者（HD）经常出现恶心和呕吐等副作用，这会使治疗过程让他们感到不适，并导致治疗过早结束。目前尚无已知的呕吐预测指标。我们旨在创建一种列线图，能够预测血液透析患者的呕吐情况。我们对2023年1月1日至2024年10月31日在南通市第一人民医院接受定期血液透析的终末期肾病（ESRD）患者进行了回顾性筛查。列线图的结果指标为呕吐，采用科尔蒂拉量表进行评估。采用最小绝对收缩选择算子（LASSO）方法和博鲁塔特征选择法对预测指标进行最佳预测。采用多因素逻辑回归构建以列线图呈现的预测模型。使用受试者工作特征（ROC）曲线、校准图和决策曲线分析（DCA）评估列线图的效能。通过评估验证队列的表现对模型进行内部验证。该研究纳入了281例患者。92例患者（占32.74%）出现呕吐症状。参与者被随机分为训练组（n = 196）和验证组（n = 85）。列线图纳入了性别、身高、心率、spKt.V、淋巴细胞和乳酸脱氢酶等预测指标。训练组和验证组的ROC曲线均显示出较强的识别能力，而校准曲线表明两组的校正结果都非常令人满意。这种列线图有助于临床医生识别高危人群，并支持制定有效的预防策略。
