Wang Yang, Zhou Yuchao, Huang Chunni, Wang Yonghong, Lou Lixuan, Zhao Liang, Xu Shutian, Zheng Mingzhu, Li Shijun
Kidney Intensive Care Unit, National Clinical Research Center of Kidney Diseases, Jinling Hospital, Nanjing University School of Medicine, Nanjing, 210032, Jiangsu, China.
Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, Jiangsu, China.
BMC Nephrol. 2025 Feb 13;26(1):78. doi: 10.1186/s12882-025-04002-9.
Immunosuppressive agents, although indispensable in the treatment of chronic kidney diseases (CKD), could compromise the patient's immune function. The risk factor for in-hospital mortality in immunocompromised CKD patients with severe infections remain elusive.
We conducted a retrospective analysis of the clinical data of CKD patients who received immunosuppressive agents and presented severe infections. The cohort comprised 272 patients, among whom 73 experienced mortalities during their hospitalization. Logistic regression was employed on the training set to identify key feature variables and construct a predictive model for in-hospital mortality among immunocompromised CKD patients following severe infections. To facilitate clinical application, we constructed a nomogram to visually represent the predictive model.
Our findings indicate that ventilator use, vasoactive drug administration, elevated lactate dehydrogenase (LDH), total bilirubin (TBIL) levels, and persistent lymphopenia(PL) are effective predictors of in-hospital mortality in immunocompromised patients with severe infections. These variables were subsequently incorporated to construct a robust prognostic model. Our model demonstrated excellent discriminative ability (AUC = 0.959, 95% CI, 0.924-0.994), significantly outperforming the Sequential Organ Failure Assessment (SOFA) score (AUC = 0.878, 95% CI, 0.825-0.930) and quick Pitt Bacteremia Score (qPBS) (AUC = 0.897, 95% CI, 0.846-0.947). Calibration curve analysis and the Hosmer-Lemeshow (HL) test corroborate the concordance of our model with empirical observations. Furthermore, decision curve analysis (DCA) underscores the superior clinical utility of our predictive model when compared to the SOFA score and qPBS score. Most importantly, our results showed that PL is the most important predictor of in-hospital mortality in immunocompromised patients following severe infection.
Our findings highlight PL as the most significant predictor of in-hospital mortality in immunocompromised CKD patients. A clinical prediction model incorporating PL as a key variable exhibited robust performance in terms of diagnostic accuracy and clinical utility.
免疫抑制剂虽然在慢性肾脏病（CKD）治疗中不可或缺，但可能会损害患者的免疫功能。免疫功能低下的CKD患者发生严重感染时院内死亡的危险因素仍不明确。
我们对接受免疫抑制剂治疗并发生严重感染的CKD患者的临床资料进行了回顾性分析。该队列包括272例患者，其中73例在住院期间死亡。在训练集上采用逻辑回归来识别关键特征变量，并构建免疫功能低下的CKD患者发生严重感染后院内死亡的预测模型。为便于临床应用，我们构建了列线图以直观呈现该预测模型。
我们的研究结果表明，使用呼吸机、使用血管活性药物、乳酸脱氢酶（LDH）升高、总胆红素（TBIL）水平升高以及持续性淋巴细胞减少（PL）是免疫功能低下的严重感染患者院内死亡的有效预测因素。随后将这些变量纳入构建一个强大的预后模型。我们的模型显示出优异的判别能力（AUC = 0.959，95% CI，0.924 - 0.994），显著优于序贯器官衰竭评估（SOFA）评分（AUC = 0.878，95% CI，0.825 - 0.930）和快速皮特菌血症评分（qPBS）（AUC = 0.897，95% CI，0.846 - 0.947）。校准曲线分析和Hosmer-Lemeshow（HL）检验证实了我们的模型与实际观察结果的一致性。此外，决策曲线分析（DCA）强调了我们的预测模型与SOFA评分和qPBS评分相比具有更高的临床实用性。最重要的是，我们的结果表明PL是免疫功能低下的严重感染患者院内死亡的最重要预测因素。
我们的研究结果突出了PL是免疫功能低下的CKD患者院内死亡的最重要预测因素。一个将PL作为关键变量的临床预测模型在诊断准确性和临床实用性方面表现出强大性能。
