Development and external validation of a nomogram for the early prediction of acute kidney injury in septic patients: a multicenter retrospective clinical study
Methods In our study, we retrospectively constructed a development cohort comprising 733 septic patients admitted to eight Grade-A tertiary hospitals in Shanghai from January 2021 to October 2022. Additionally, we established an external validation cohort consisting of 336 septic patients admitted t...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-12-01
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| Series: | Renal Failure |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/0886022X.2024.2310081 |
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| author | Qin-Yue Su Wen-Jie Chen Yan-Jun Zheng Wen Shi Fang-Chen Gong Shun-Wei Huang Zhi-tao Yang Hong-Ping Qu En-Qiang Mao Rui-Lan Wang Du-Ming Zhu Gang Zhao Wei Chen Sheng Wang Qian Wang Chang-Qing Zhu Gao Yuan Er-Zhen Chen Ying Chen |
| author_facet | Qin-Yue Su Wen-Jie Chen Yan-Jun Zheng Wen Shi Fang-Chen Gong Shun-Wei Huang Zhi-tao Yang Hong-Ping Qu En-Qiang Mao Rui-Lan Wang Du-Ming Zhu Gang Zhao Wei Chen Sheng Wang Qian Wang Chang-Qing Zhu Gao Yuan Er-Zhen Chen Ying Chen |
| author_sort | Qin-Yue Su |
| collection | DOAJ |
| description | Methods In our study, we retrospectively constructed a development cohort comprising 733 septic patients admitted to eight Grade-A tertiary hospitals in Shanghai from January 2021 to October 2022. Additionally, we established an external validation cohort consisting of 336 septic patients admitted to our hospital from January 2017 to December 2019. Risk predictors were selected by LASSO regression, and a corresponding nomogram was constructed. We evaluated the model’s discrimination, precision and clinical benefit through receiver operating characteristic (ROC) curves, calibration plots, decision curve analysis (DCA) and clinical impact curves (CIC) in both internal and external validation.Results AKI incidence was 53.2% in the development cohort and 48.2% in the external validation cohort. The model included five independent indicators: chronic kidney disease stages 1 to 3, blood urea nitrogen, procalcitonin, D-dimer and creatine kinase isoenzyme. The AUC of the model in the development and validation cohorts was 0.914 (95% CI, 0.894–0.934) and 0.923 (95% CI, 0.895–0.952), respectively. The calibration plot, DCA, and CIC demonstrated the model’s favorable clinical applicability.Conclusion We developed and validated a robust nomogram model, which might identify patients at risk of SA-AKI and promising for clinical applications. |
| format | Article |
| id | doaj-art-192c3532875145bbbcb237c569f72c64 |
| institution | Kabale University |
| issn | 0886-022X 1525-6049 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Renal Failure |
| spelling | doaj-art-192c3532875145bbbcb237c569f72c642025-01-23T04:17:47ZengTaylor & Francis GroupRenal Failure0886-022X1525-60492024-12-0146110.1080/0886022X.2024.2310081Development and external validation of a nomogram for the early prediction of acute kidney injury in septic patients: a multicenter retrospective clinical studyQin-Yue Su0Wen-Jie Chen1Yan-Jun Zheng2Wen Shi3Fang-Chen Gong4Shun-Wei Huang5Zhi-tao Yang6Hong-Ping Qu7En-Qiang Mao8Rui-Lan Wang9Du-Ming Zhu10Gang Zhao11Wei Chen12Sheng Wang13Qian Wang14Chang-Qing Zhu15Gao Yuan16Er-Zhen Chen17Ying Chen18Department of Emergency Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaDepartment of Emergency Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaDepartment of Emergency Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaDepartment of Emergency Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaDepartment of Emergency Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaDepartment of Emergency Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaDepartment of Emergency Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaDepartment of Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaDepartment of Emergency Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaDepartment of Emergency Medicine, Shanghai First People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaDepartment of Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, ChinaDepartment of Emergency Medicine, Shanghai Sixth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaDepartment of Critical Care Medicine, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, ChinaDepartment of Critical Care Medicine, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, ChinaDepartment of Emergency Medicine, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, ChinaDepartment of Emergency Medicine, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaDepartment of Critical Care Medicine, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaDepartment of Emergency Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaDepartment of Emergency Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaMethods In our study, we retrospectively constructed a development cohort comprising 733 septic patients admitted to eight Grade-A tertiary hospitals in Shanghai from January 2021 to October 2022. Additionally, we established an external validation cohort consisting of 336 septic patients admitted to our hospital from January 2017 to December 2019. Risk predictors were selected by LASSO regression, and a corresponding nomogram was constructed. We evaluated the model’s discrimination, precision and clinical benefit through receiver operating characteristic (ROC) curves, calibration plots, decision curve analysis (DCA) and clinical impact curves (CIC) in both internal and external validation.Results AKI incidence was 53.2% in the development cohort and 48.2% in the external validation cohort. The model included five independent indicators: chronic kidney disease stages 1 to 3, blood urea nitrogen, procalcitonin, D-dimer and creatine kinase isoenzyme. The AUC of the model in the development and validation cohorts was 0.914 (95% CI, 0.894–0.934) and 0.923 (95% CI, 0.895–0.952), respectively. The calibration plot, DCA, and CIC demonstrated the model’s favorable clinical applicability.Conclusion We developed and validated a robust nomogram model, which might identify patients at risk of SA-AKI and promising for clinical applications.https://www.tandfonline.com/doi/10.1080/0886022X.2024.2310081Sepsisacute kidney injurypredictionnomogram |
| spellingShingle | Qin-Yue Su Wen-Jie Chen Yan-Jun Zheng Wen Shi Fang-Chen Gong Shun-Wei Huang Zhi-tao Yang Hong-Ping Qu En-Qiang Mao Rui-Lan Wang Du-Ming Zhu Gang Zhao Wei Chen Sheng Wang Qian Wang Chang-Qing Zhu Gao Yuan Er-Zhen Chen Ying Chen Development and external validation of a nomogram for the early prediction of acute kidney injury in septic patients: a multicenter retrospective clinical study Renal Failure Sepsis acute kidney injury prediction nomogram |
| title | Development and external validation of a nomogram for the early prediction of acute kidney injury in septic patients: a multicenter retrospective clinical study |
| title_full | Development and external validation of a nomogram for the early prediction of acute kidney injury in septic patients: a multicenter retrospective clinical study |
| title_fullStr | Development and external validation of a nomogram for the early prediction of acute kidney injury in septic patients: a multicenter retrospective clinical study |
| title_full_unstemmed | Development and external validation of a nomogram for the early prediction of acute kidney injury in septic patients: a multicenter retrospective clinical study |
| title_short | Development and external validation of a nomogram for the early prediction of acute kidney injury in septic patients: a multicenter retrospective clinical study |
| title_sort | development and external validation of a nomogram for the early prediction of acute kidney injury in septic patients a multicenter retrospective clinical study |
| topic | Sepsis acute kidney injury prediction nomogram |
| url | https://www.tandfonline.com/doi/10.1080/0886022X.2024.2310081 |
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