Biomarkers of cell cycle arrest, microcirculation dysfunction, and inflammation in the prediction of SA-AKI
Abstract Sepsis-associated acute kidney injury (SA-AKI) is a severe complication in critically ill patients, with a complex pathogenesis involving in cell cycle arrest, microcirculatory dysfunction, and inflammation. Current diagnostic strategies remain suboptimal. Therefore, this study aimed to eva...
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Nature Portfolio
2025-03-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-92315-y |
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| author | Qian Zhang Boxin Yang Xiaodan Li Yang Zhao Shuo Yang Qingbian Ma Liyan Cui |
| author_facet | Qian Zhang Boxin Yang Xiaodan Li Yang Zhao Shuo Yang Qingbian Ma Liyan Cui |
| author_sort | Qian Zhang |
| collection | DOAJ |
| description | Abstract Sepsis-associated acute kidney injury (SA-AKI) is a severe complication in critically ill patients, with a complex pathogenesis involving in cell cycle arrest, microcirculatory dysfunction, and inflammation. Current diagnostic strategies remain suboptimal. Therefore, this study aimed to evaluate pathophysiology-based biomarkers and develop an improved predictive model for SA-AKI. The prospective observational study was conducted, enrolling 26 healthy individuals and 96 sepsis patients from Peking University Third Hospital. Clinical and laboratory data were collected, and patients were monitored for AKI development within 72 h. Further, sepsis patients were categorized into SA-noAKI (n = 46) and SA-AKI (n = 50) groups. Novel biomarkers, including tissue inhibitor of metalloproteinase-2 (TIMP-2), insulin-like growth factor-binding protein-7 (IGFBP-7), and angiopoietin-2 (Ang-2), were measured in all participants. Among these sepsis patients, the SA-AKI incidence was 52.08% (50/96). Compared to SA-noAKI, the SA-AKI group had significantly higher levels of TIMP-2 (93.55 [79.36, 119.56] ng/mL), IGFBP-7 (27.8 [21.44, 37.29] ng/mL), TIMP-2×IGFBP-7 (2.91 [1.90, 3.55] (ng/mL)²/1000), and Ang-2 (10.61 [5.79, 14.57] ng/mL) (P < 0.05). Accordingly, logistic regression identified TIMP-2×IGFBP-7 (OR = 2.71), Ang-2 (OR = 1.19), and PCT (OR = 1.05) as independent risk factors. The ROC curve of the predictive model demonstrated superior early-stage accuracy (AUC = 0.898), which remained stable during internal validation (AUC = 0.899). Meanwhile, the nomogram exhibited that this model was characterized with excellent discrimination, calibration, and clinical performance. In general, TIMP-2×IGFBP-7, Ang-2 and PCT were the independent risk factors for SA-AKI, and the novel model based on the three indicators provided a more accurate and sensitive strategy for the early prediction of SA-AKI. |
| format | Article |
| id | doaj-art-30dd377147ca42feba90ec28dca09295 |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-30dd377147ca42feba90ec28dca092952025-08-20T02:59:20ZengNature PortfolioScientific Reports2045-23222025-03-0115111110.1038/s41598-025-92315-yBiomarkers of cell cycle arrest, microcirculation dysfunction, and inflammation in the prediction of SA-AKIQian Zhang0Boxin Yang1Xiaodan Li2Yang Zhao3Shuo Yang4Qingbian Ma5Liyan Cui6Department of laboratory medicine, Peking University Third HospitalDepartment of laboratory medicine, Peking University Third HospitalDepartment of Emergency Medicine, Peking University Third HospitalDepartment of laboratory medicine, Peking University Third HospitalDepartment of laboratory medicine, Peking University Third HospitalDepartment of Emergency Medicine, Peking University Third HospitalDepartment of laboratory medicine, Peking University Third HospitalAbstract Sepsis-associated acute kidney injury (SA-AKI) is a severe complication in critically ill patients, with a complex pathogenesis involving in cell cycle arrest, microcirculatory dysfunction, and inflammation. Current diagnostic strategies remain suboptimal. Therefore, this study aimed to evaluate pathophysiology-based biomarkers and develop an improved predictive model for SA-AKI. The prospective observational study was conducted, enrolling 26 healthy individuals and 96 sepsis patients from Peking University Third Hospital. Clinical and laboratory data were collected, and patients were monitored for AKI development within 72 h. Further, sepsis patients were categorized into SA-noAKI (n = 46) and SA-AKI (n = 50) groups. Novel biomarkers, including tissue inhibitor of metalloproteinase-2 (TIMP-2), insulin-like growth factor-binding protein-7 (IGFBP-7), and angiopoietin-2 (Ang-2), were measured in all participants. Among these sepsis patients, the SA-AKI incidence was 52.08% (50/96). Compared to SA-noAKI, the SA-AKI group had significantly higher levels of TIMP-2 (93.55 [79.36, 119.56] ng/mL), IGFBP-7 (27.8 [21.44, 37.29] ng/mL), TIMP-2×IGFBP-7 (2.91 [1.90, 3.55] (ng/mL)²/1000), and Ang-2 (10.61 [5.79, 14.57] ng/mL) (P < 0.05). Accordingly, logistic regression identified TIMP-2×IGFBP-7 (OR = 2.71), Ang-2 (OR = 1.19), and PCT (OR = 1.05) as independent risk factors. The ROC curve of the predictive model demonstrated superior early-stage accuracy (AUC = 0.898), which remained stable during internal validation (AUC = 0.899). Meanwhile, the nomogram exhibited that this model was characterized with excellent discrimination, calibration, and clinical performance. In general, TIMP-2×IGFBP-7, Ang-2 and PCT were the independent risk factors for SA-AKI, and the novel model based on the three indicators provided a more accurate and sensitive strategy for the early prediction of SA-AKI.https://doi.org/10.1038/s41598-025-92315-ySepsis associated acute kidney injuryBiomarkersTissue inhibitor metalloproteinase-2Insulin-like growth factor-binding protein-7Angiopoeitin-2Procalcitonin |
| spellingShingle | Qian Zhang Boxin Yang Xiaodan Li Yang Zhao Shuo Yang Qingbian Ma Liyan Cui Biomarkers of cell cycle arrest, microcirculation dysfunction, and inflammation in the prediction of SA-AKI Scientific Reports Sepsis associated acute kidney injury Biomarkers Tissue inhibitor metalloproteinase-2 Insulin-like growth factor-binding protein-7 Angiopoeitin-2 Procalcitonin |
| title | Biomarkers of cell cycle arrest, microcirculation dysfunction, and inflammation in the prediction of SA-AKI |
| title_full | Biomarkers of cell cycle arrest, microcirculation dysfunction, and inflammation in the prediction of SA-AKI |
| title_fullStr | Biomarkers of cell cycle arrest, microcirculation dysfunction, and inflammation in the prediction of SA-AKI |
| title_full_unstemmed | Biomarkers of cell cycle arrest, microcirculation dysfunction, and inflammation in the prediction of SA-AKI |
| title_short | Biomarkers of cell cycle arrest, microcirculation dysfunction, and inflammation in the prediction of SA-AKI |
| title_sort | biomarkers of cell cycle arrest microcirculation dysfunction and inflammation in the prediction of sa aki |
| topic | Sepsis associated acute kidney injury Biomarkers Tissue inhibitor metalloproteinase-2 Insulin-like growth factor-binding protein-7 Angiopoeitin-2 Procalcitonin |
| url | https://doi.org/10.1038/s41598-025-92315-y |
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