{"title":"Development and validation of a nomogram for predicting acute kidney injury in elderly patients in intensive care unit.","authors":"Li Zhao, Xunliang Li, Wenman Zhao, Deguang Wang","doi":"10.1080/0886022X.2025.2499911","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>This study aimed to develop and validate a nomogram for predicting acute kidney injury (AKI) in elderly patients in the intensive care unit (ICU).</p><p><strong>Methods: </strong>Population data regarding elderly patients in ICU were derived from the Medical Information Mart for Intensive Care IV database from 2008 to 2019. The nomogram model was constructed from the training set using LASSO regression and logistic regression analysis, and the performance of the model was evaluated by decision curve analysis, calibration curve, and receiver operating characteristic (ROC) curve.</p><p><strong>Results: </strong>According to inclusion and exclusion criteria, 14,373 elderly ICU patients were studied, of which 10,061 (70%) were assigned to the training set, and 4,312 (30%) were allocated to the validation set. Multivariate logistic analysis revealed that age, weight, myocardial infarction, congestive heart failure, dementia, diabetes, paraplegia, cancer, sepsis, body temperature, blood urea nitrogen, mechanical ventilation, urine volume, Sequential Organ Failure Assessment (SOFA) score, and Simplified Acute Physiology Score II (SAPS II) were independent risk factors for AKI in elderly ICU patients. The AUC values for the 15-factor nomogram were 0.812 (95% CI 0.802-0.822) and 0.802 (95% CI 0.787-0.818) in the training and validation sets, respectively. For clinical application, a simplified nomogram was constructed, which included age, weight, urine volume, SOFA score, and SAPS II, with the AUCs of 0.780 (95% CI 0.769-0.790) and 0.776 (95% CI 0.760-0.793), respectively. Calibration curve and decision curve analyses confirmed the models' high prediction accuracy and clinical value.</p><p><strong>Conclusions: </strong>The nomogram developed in this study shows excellent predictive performance for AKI in elderly patients in the ICU.</p>","PeriodicalId":20839,"journal":{"name":"Renal Failure","volume":"47 1","pages":"2499911"},"PeriodicalIF":3.0000,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12064126/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Renal Failure","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/0886022X.2025.2499911","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/5/8 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"UROLOGY & NEPHROLOGY","Score":null,"Total":0}
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Abstract
Background: This study aimed to develop and validate a nomogram for predicting acute kidney injury (AKI) in elderly patients in the intensive care unit (ICU).
Methods: Population data regarding elderly patients in ICU were derived from the Medical Information Mart for Intensive Care IV database from 2008 to 2019. The nomogram model was constructed from the training set using LASSO regression and logistic regression analysis, and the performance of the model was evaluated by decision curve analysis, calibration curve, and receiver operating characteristic (ROC) curve.
Results: According to inclusion and exclusion criteria, 14,373 elderly ICU patients were studied, of which 10,061 (70%) were assigned to the training set, and 4,312 (30%) were allocated to the validation set. Multivariate logistic analysis revealed that age, weight, myocardial infarction, congestive heart failure, dementia, diabetes, paraplegia, cancer, sepsis, body temperature, blood urea nitrogen, mechanical ventilation, urine volume, Sequential Organ Failure Assessment (SOFA) score, and Simplified Acute Physiology Score II (SAPS II) were independent risk factors for AKI in elderly ICU patients. The AUC values for the 15-factor nomogram were 0.812 (95% CI 0.802-0.822) and 0.802 (95% CI 0.787-0.818) in the training and validation sets, respectively. For clinical application, a simplified nomogram was constructed, which included age, weight, urine volume, SOFA score, and SAPS II, with the AUCs of 0.780 (95% CI 0.769-0.790) and 0.776 (95% CI 0.760-0.793), respectively. Calibration curve and decision curve analyses confirmed the models' high prediction accuracy and clinical value.
Conclusions: The nomogram developed in this study shows excellent predictive performance for AKI in elderly patients in the ICU.
背景：本研究旨在开发和验证预测重症监护病房（ICU）老年患者急性肾损伤（AKI）的nomogram。方法：2008 - 2019年ICU老年患者人口数据来源于重症监护医学信息市场IV数据库。利用LASSO回归和logistic回归分析对训练集构建nomogram模型，并通过决策曲线、校准曲线和受试者工作特征（ROC）曲线对模型的性能进行评价。结果：按照纳入和排除标准，共纳入14373例老年ICU患者，其中10061例（70%）分配到训练集，4312例（30%）分配到验证集。多因素logistic分析显示，年龄、体重、心肌梗死、充血性心力衰竭、痴呆、糖尿病、瘫瘫、癌症、败血症、体温、血尿素氮、机械通气、尿量、顺序器官衰竭评估（SOFA）评分、简化急性生理评分II （SAPS II）是老年ICU患者AKI的独立危险因素。在训练集和验证集上，15因素nomogram AUC值分别为0.812 （95% CI 0.802-0.822）和0.802 （95% CI 0.787-0.818）。为了临床应用，我们构建了一个简化的nomogram，包括年龄、体重、尿量、SOFA评分和SAPS II， auc分别为0.780 （95% CI 0.769-0.790）和0.776 （95% CI 0.760-0.793）。校正曲线和决策曲线分析证实了该模型具有较高的预测精度和临床应用价值。结论：本研究中建立的nomogram对ICU老年患者AKI有很好的预测效果。
期刊介绍：
Renal Failure primarily concentrates on acute renal injury and its consequence, but also addresses advances in the fields of chronic renal failure, hypertension, and renal transplantation. Bringing together both clinical and experimental aspects of renal failure, this publication presents timely, practical information on pathology and pathophysiology of acute renal failure; nephrotoxicity of drugs and other substances; prevention, treatment, and therapy of renal failure; renal failure in association with transplantation, hypertension, and diabetes mellitus.
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