Qing Xu, Zhifeng Zhou, Lu Jin, Chen Liu, Peiyun Li, Fang Wang, Ling Zhang, Ping Fu
{"title":"预测急性肾损伤肾替代治疗成功释放的新生物标志物:系统综述","authors":"Qing Xu, Zhifeng Zhou, Lu Jin, Chen Liu, Peiyun Li, Fang Wang, Ling Zhang, Ping Fu","doi":"10.1186/s13054-025-05451-2","DOIUrl":null,"url":null,"abstract":"Renal replacement therapy (RRT) is commonly used in critically ill patients with acute kidney injury (AKI). However, optimal timing of RRT liberation remains controversy. This meta-analysis evaluates novel biomarkers to predict successful RRT liberation in critically ill AKI patients. The systematic review reported following PRISMA guidelines, PubMed, Embase, and Scopus were searched up to May 2, 2025, and were screened using predefined criteria. Methodological quality was assessed using the Newcastle–Ottawa scale. Pooled ROC-AUCs with 95% CIs were calculated; heterogeneity was evaluated using I2 statistics. Sixteen studies (3020 patients) involving 23 biomarkers were included. Urinary neutrophil gelatinase-associated lipocalin (uNGAL) demonstrated fair predictive performance with 4 studies (AUC 0.766, I2 = 39.8%). When excluding a study focused on long-term outcomes, the result showed a better predictive ability with low heterogeneity (AUC 0.801, I2 = 0%). Plasma proenkephalin A (PENK) and serum NGAL also showed potential, but quantitative synthesis was limited by study number and heterogeneity. The cut-off value also varied widely, complicating clinical translation. In addition, multivariable models combining novel biomarkers with clinical indicators have also demonstrated promising predictive potential. However, due to the limited number of studies and inconsistent conclusions, further exploration is needed. uNGAL moderately predicts short-term RRT liberation, while other biomarkers (e.g., PENK) require further validation. Standardizing definitions of successful liberation and integrating dynamic biomarker changed with clinical indicators (e.g., urine output) may enhance predictive accuracy. Further large-scale, prospective, and multicenter studies are needed to validate these findings.","PeriodicalId":10811,"journal":{"name":"Critical Care","volume":"24 1","pages":""},"PeriodicalIF":8.8000,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Novel biomarkers for predicting successful liberation of renal replacement therapy for acute kidney injury: a systematic review\",\"authors\":\"Qing Xu, Zhifeng Zhou, Lu Jin, Chen Liu, Peiyun Li, Fang Wang, Ling Zhang, Ping Fu\",\"doi\":\"10.1186/s13054-025-05451-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Renal replacement therapy (RRT) is commonly used in critically ill patients with acute kidney injury (AKI). However, optimal timing of RRT liberation remains controversy. This meta-analysis evaluates novel biomarkers to predict successful RRT liberation in critically ill AKI patients. The systematic review reported following PRISMA guidelines, PubMed, Embase, and Scopus were searched up to May 2, 2025, and were screened using predefined criteria. Methodological quality was assessed using the Newcastle–Ottawa scale. Pooled ROC-AUCs with 95% CIs were calculated; heterogeneity was evaluated using I2 statistics. Sixteen studies (3020 patients) involving 23 biomarkers were included. Urinary neutrophil gelatinase-associated lipocalin (uNGAL) demonstrated fair predictive performance with 4 studies (AUC 0.766, I2 = 39.8%). When excluding a study focused on long-term outcomes, the result showed a better predictive ability with low heterogeneity (AUC 0.801, I2 = 0%). Plasma proenkephalin A (PENK) and serum NGAL also showed potential, but quantitative synthesis was limited by study number and heterogeneity. The cut-off value also varied widely, complicating clinical translation. In addition, multivariable models combining novel biomarkers with clinical indicators have also demonstrated promising predictive potential. However, due to the limited number of studies and inconsistent conclusions, further exploration is needed. uNGAL moderately predicts short-term RRT liberation, while other biomarkers (e.g., PENK) require further validation. Standardizing definitions of successful liberation and integrating dynamic biomarker changed with clinical indicators (e.g., urine output) may enhance predictive accuracy. 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Novel biomarkers for predicting successful liberation of renal replacement therapy for acute kidney injury: a systematic review
Renal replacement therapy (RRT) is commonly used in critically ill patients with acute kidney injury (AKI). However, optimal timing of RRT liberation remains controversy. This meta-analysis evaluates novel biomarkers to predict successful RRT liberation in critically ill AKI patients. The systematic review reported following PRISMA guidelines, PubMed, Embase, and Scopus were searched up to May 2, 2025, and were screened using predefined criteria. Methodological quality was assessed using the Newcastle–Ottawa scale. Pooled ROC-AUCs with 95% CIs were calculated; heterogeneity was evaluated using I2 statistics. Sixteen studies (3020 patients) involving 23 biomarkers were included. Urinary neutrophil gelatinase-associated lipocalin (uNGAL) demonstrated fair predictive performance with 4 studies (AUC 0.766, I2 = 39.8%). When excluding a study focused on long-term outcomes, the result showed a better predictive ability with low heterogeneity (AUC 0.801, I2 = 0%). Plasma proenkephalin A (PENK) and serum NGAL also showed potential, but quantitative synthesis was limited by study number and heterogeneity. The cut-off value also varied widely, complicating clinical translation. In addition, multivariable models combining novel biomarkers with clinical indicators have also demonstrated promising predictive potential. However, due to the limited number of studies and inconsistent conclusions, further exploration is needed. uNGAL moderately predicts short-term RRT liberation, while other biomarkers (e.g., PENK) require further validation. Standardizing definitions of successful liberation and integrating dynamic biomarker changed with clinical indicators (e.g., urine output) may enhance predictive accuracy. Further large-scale, prospective, and multicenter studies are needed to validate these findings.
期刊介绍:
Critical Care is an esteemed international medical journal that undergoes a rigorous peer-review process to maintain its high quality standards. Its primary objective is to enhance the healthcare services offered to critically ill patients. To achieve this, the journal focuses on gathering, exchanging, disseminating, and endorsing evidence-based information that is highly relevant to intensivists. By doing so, Critical Care seeks to provide a thorough and inclusive examination of the intensive care field.