ORIGINAL RESEARCH article
Front. Med.
Sec. Nephrology
This article is part of the Research TopicOutcome of Sepsis and Prediction of Mortality Risk - Volume IIView all 13 articles
Construction and validation of nomogram prediction model for clinical efficacy of high-dose continuous renal replacement therapy in sepsis patients based on inflammatory response and microcirculation
Provisionally accepted
- Ganzhou People's Hospital, Ganzhou, China
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Objective: To construct a nomogram model for predicting the clinical efficacy of high-dose continuous renal replacement therapy (CRRT) in sepsis patients based on inflammatory response and microcirculation, and to explore its clinical application value. Methods: A total of 162 sepsis patients who received high-dose CRRT in our hospital were randomly divided into a training set (n=113) and a validation set (n=49) according to a 7:3 ratio. In the training set, multivariate logistic regression was used to analyze the risk factors affecting the treatment effect to construct the nomogram prediction model. The predictive efficacy of the model was assessed using receiver operating characteristic (ROC) curve and calibration curve, which were verified in the validation set. Meanwhile, the decision curve analysis (DCA) was used to evaluate its clinical application value. Results: The percentages of patients with poor efficacy in the training set and the validation set were 29.20% (33 cases) and 26.53% (13 cases), respectively. Multivariate Logistic analysis of the training set showed that high Acute Physiology and Chronic Health Evaluation II (APACHE-II) score, high white blood cell (WBC), procalcitonin (PCT), C-reactive protein (CRP), tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6) levels, and high Sequential Organ Failure Assessment (SOFA) score were the independent risk factors for poor therapeutic effects (all P<0.05). The nomogram model was constructed based on the above results. The model had good calibration and fit in the training set and validation set, with the C-index index of 0.865 and 0.836, respectively, the average absolute error of the calibration curve of 0.137 and 0.149, and the P value of Hosmer-Lemeshow test of 0.406 and 0.099, respectively. The area under the ROC curve (AUC) was 0.864 and 0.836 in the training and validation sets, respectively, and the sensitivities and specificities were 0.929, 0.788, and 0.800 and 0.607, respectively. Conclusion: The nomogram prediction model based on the inflammatory response and microcirculation can effectively predict the clinical efficacy of high-dose CRRT in the treatment of sepsis in patients at an early stage.
Keywords: Sepsis, continuous renal replacement therapy, Inflammatory reactions, Microcirculation, Nomogram prediction model
Received: 23 Jan 2025; Accepted: 14 Nov 2025.
Copyright: © 2025 Huang, Huang, Ye, Liu and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Qinglan Li, 13763913125@163.com
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