{"title":"脓毒性休克相关急性肾损伤预测模型的建立和验证:一项使用nomogram模型的多中心研究。","authors":"Zhizhao Jiang, Sibai Hong, Yongqiang Chen, Chunhong Du, Zhiwu Hong, Rongcheng Xie, Ranran Li, Jianjun Wu, Haibin Jiang, Jiangchuan Lin, Tianlai Lin, Jiangtao Yun, Minghui Xie, Huangang Guo, Lingyun Zhu, Shengfeng Zhang, Yuqiang Yang, Liang Xu, Junhui Yang, Qingjun Zeng, Guosheng Gu, Chen Li, Peng Wang, Jianshe Shi, Xuri Sun, Yuqi Liu","doi":"10.1097/SHK.0000000000002631","DOIUrl":null,"url":null,"abstract":"<p><strong>Abstract: </strong>Background: Septic shock-associated acute kidney injury (SS-AKI) is a severe complication with high mortality. This study aimed to investigate the risk factors associated with AKI in patients with septic shock and establish a nomogram to predict its occurrence. Methods: Patients with septic shock were categorized based on the development of AKI. A binary logistic regression was used to identify significant risk factors, which were then incorporated into a nomogram. The performance of the nomogram was evaluated using receiver operating characteristic curve analysis, calibration curve, and decision curve analysis. A validation set was used to assess the model's generalizability. Results: Of the 507 septic shock patients enrolled in this study, 174 (34.3%) developed AKI. The dataset was randomly partitioned into a training set (n = 355) and a validation set (n = 152) at a ratio of 7:3. The predictive factors incorporated into the nomogram included chronic kidney disease, diuretic administration, deresuscitation during vasopressor administration, mechanical ventilation, source control failure, restrictive fluid resuscitation, and Sequential Organ Failure Assessment scores. The developed nomogram demonstrated excellent performance in predicting the risk of AKI in patients with septic shock. The model achieved an area under the receiver operating characteristic curve of 0.788 (95% confidence interval, 0.737-0.839) in the training set and 0.770 (95% confidence interval, 0.693-0.846) in the validation set, indicating strong discriminatory ability. The calibration curve analysis, using the Hosmer-Lemeshow test, indicated good agreement between the predicted and observed probabilities of AKI in both the training set ( P = 0.468) and the validation set ( P = 0.396). The decision curve analysis further indicated that the nomogram demonstrated substantial clinical utility in both the training set (0.09-0.87) and the validation set (0.11-0.64). Conclusions: The nomogram serves as an invaluable tool for clinicians to assess the risk of AKI in patients experiencing septic shock and facilitates timely intervention.</p>","PeriodicalId":21667,"journal":{"name":"SHOCK","volume":" ","pages":"311-321"},"PeriodicalIF":2.9000,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"DEVELOPMENT AND VALIDATION OF A PREDICTION MODEL FOR SEPTIC SHOCK-ASSOCIATED ACUTE KIDNEY INJURY: A MULTICENTER STUDY USING NOMOGRAM MODELING.\",\"authors\":\"Zhizhao Jiang, Sibai Hong, Yongqiang Chen, Chunhong Du, Zhiwu Hong, Rongcheng Xie, Ranran Li, Jianjun Wu, Haibin Jiang, Jiangchuan Lin, Tianlai Lin, Jiangtao Yun, Minghui Xie, Huangang Guo, Lingyun Zhu, Shengfeng Zhang, Yuqiang Yang, Liang Xu, Junhui Yang, Qingjun Zeng, Guosheng Gu, Chen Li, Peng Wang, Jianshe Shi, Xuri Sun, Yuqi Liu\",\"doi\":\"10.1097/SHK.0000000000002631\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Abstract: </strong>Background: Septic shock-associated acute kidney injury (SS-AKI) is a severe complication with high mortality. This study aimed to investigate the risk factors associated with AKI in patients with septic shock and establish a nomogram to predict its occurrence. Methods: Patients with septic shock were categorized based on the development of AKI. A binary logistic regression was used to identify significant risk factors, which were then incorporated into a nomogram. The performance of the nomogram was evaluated using receiver operating characteristic curve analysis, calibration curve, and decision curve analysis. A validation set was used to assess the model's generalizability. Results: Of the 507 septic shock patients enrolled in this study, 174 (34.3%) developed AKI. The dataset was randomly partitioned into a training set (n = 355) and a validation set (n = 152) at a ratio of 7:3. The predictive factors incorporated into the nomogram included chronic kidney disease, diuretic administration, deresuscitation during vasopressor administration, mechanical ventilation, source control failure, restrictive fluid resuscitation, and Sequential Organ Failure Assessment scores. The developed nomogram demonstrated excellent performance in predicting the risk of AKI in patients with septic shock. The model achieved an area under the receiver operating characteristic curve of 0.788 (95% confidence interval, 0.737-0.839) in the training set and 0.770 (95% confidence interval, 0.693-0.846) in the validation set, indicating strong discriminatory ability. The calibration curve analysis, using the Hosmer-Lemeshow test, indicated good agreement between the predicted and observed probabilities of AKI in both the training set ( P = 0.468) and the validation set ( P = 0.396). The decision curve analysis further indicated that the nomogram demonstrated substantial clinical utility in both the training set (0.09-0.87) and the validation set (0.11-0.64). Conclusions: The nomogram serves as an invaluable tool for clinicians to assess the risk of AKI in patients experiencing septic shock and facilitates timely intervention.</p>\",\"PeriodicalId\":21667,\"journal\":{\"name\":\"SHOCK\",\"volume\":\" \",\"pages\":\"311-321\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2025-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SHOCK\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1097/SHK.0000000000002631\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/5/13 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"CRITICAL CARE MEDICINE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SHOCK","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/SHK.0000000000002631","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/5/13 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"CRITICAL CARE MEDICINE","Score":null,"Total":0}
DEVELOPMENT AND VALIDATION OF A PREDICTION MODEL FOR SEPTIC SHOCK-ASSOCIATED ACUTE KIDNEY INJURY: A MULTICENTER STUDY USING NOMOGRAM MODELING.
Abstract: Background: Septic shock-associated acute kidney injury (SS-AKI) is a severe complication with high mortality. This study aimed to investigate the risk factors associated with AKI in patients with septic shock and establish a nomogram to predict its occurrence. Methods: Patients with septic shock were categorized based on the development of AKI. A binary logistic regression was used to identify significant risk factors, which were then incorporated into a nomogram. The performance of the nomogram was evaluated using receiver operating characteristic curve analysis, calibration curve, and decision curve analysis. A validation set was used to assess the model's generalizability. Results: Of the 507 septic shock patients enrolled in this study, 174 (34.3%) developed AKI. The dataset was randomly partitioned into a training set (n = 355) and a validation set (n = 152) at a ratio of 7:3. The predictive factors incorporated into the nomogram included chronic kidney disease, diuretic administration, deresuscitation during vasopressor administration, mechanical ventilation, source control failure, restrictive fluid resuscitation, and Sequential Organ Failure Assessment scores. The developed nomogram demonstrated excellent performance in predicting the risk of AKI in patients with septic shock. The model achieved an area under the receiver operating characteristic curve of 0.788 (95% confidence interval, 0.737-0.839) in the training set and 0.770 (95% confidence interval, 0.693-0.846) in the validation set, indicating strong discriminatory ability. The calibration curve analysis, using the Hosmer-Lemeshow test, indicated good agreement between the predicted and observed probabilities of AKI in both the training set ( P = 0.468) and the validation set ( P = 0.396). The decision curve analysis further indicated that the nomogram demonstrated substantial clinical utility in both the training set (0.09-0.87) and the validation set (0.11-0.64). Conclusions: The nomogram serves as an invaluable tool for clinicians to assess the risk of AKI in patients experiencing septic shock and facilitates timely intervention.
期刊介绍:
SHOCK®: Injury, Inflammation, and Sepsis: Laboratory and Clinical Approaches includes studies of novel therapeutic approaches, such as immunomodulation, gene therapy, nutrition, and others. The mission of the Journal is to foster and promote multidisciplinary studies, both experimental and clinical in nature, that critically examine the etiology, mechanisms and novel therapeutics of shock-related pathophysiological conditions. Its purpose is to excel as a vehicle for timely publication in the areas of basic and clinical studies of shock, trauma, sepsis, inflammation, ischemia, and related pathobiological states, with particular emphasis on the biologic mechanisms that determine the response to such injury. Making such information available will ultimately facilitate improved care of the traumatized or septic individual.