Cargando…

Cell cycle arrest biomarkers for predicting renal recovery from acute kidney injury: a prospective validation study

BACKGROUND: Acute kidney injury (AKI) is a common disease in the intensive care unit (ICU). AKI patients with nonrecovery of renal function have a markedly increased risk of death compared with patients with recovery. The current study aimed to explore and validate the utility of urinary cell cycle...

Descripción completa

Detalles Bibliográficos
Autores principales: Jia, Hui-Miao, Cheng, Li, Weng, Yi-Bing, Wang, Jing-Yi, Zheng, Xi, Jiang, Yi-Jia, Xin, Xin, Guo, Shu-Yan, Chen, Chao-Dong, Guo, Fang-Xing, Han, Yu-Zhen, Zhang, Tian-En, Li, Wen-Xiong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8840946/
https://www.ncbi.nlm.nih.gov/pubmed/35150348
http://dx.doi.org/10.1186/s13613-022-00989-8
_version_ 1784650738537857024
author Jia, Hui-Miao
Cheng, Li
Weng, Yi-Bing
Wang, Jing-Yi
Zheng, Xi
Jiang, Yi-Jia
Xin, Xin
Guo, Shu-Yan
Chen, Chao-Dong
Guo, Fang-Xing
Han, Yu-Zhen
Zhang, Tian-En
Li, Wen-Xiong
author_facet Jia, Hui-Miao
Cheng, Li
Weng, Yi-Bing
Wang, Jing-Yi
Zheng, Xi
Jiang, Yi-Jia
Xin, Xin
Guo, Shu-Yan
Chen, Chao-Dong
Guo, Fang-Xing
Han, Yu-Zhen
Zhang, Tian-En
Li, Wen-Xiong
author_sort Jia, Hui-Miao
collection PubMed
description BACKGROUND: Acute kidney injury (AKI) is a common disease in the intensive care unit (ICU). AKI patients with nonrecovery of renal function have a markedly increased risk of death compared with patients with recovery. The current study aimed to explore and validate the utility of urinary cell cycle arrest biomarkers for predicting nonrecovery in patients who developed AKI after ICU admission. METHODS: We prospectively and consecutively enrolled 379 critically ill patients who developed AKI after admission to the ICU, which were divided into a derivation cohort (194 AKI patients) and a validation cohort (185 AKI patients). The biomarkers of urinary tissue inhibitor of metalloproteinase-2 (TIMP-2) and insulin-like growth factor-binding protein 7 (IGFBP7) were detected at inclusion immediately after AKI diagnosis (day 0) and 24 h later (day 1). The optimal cut-off values of these biomarkers for predicting nonrecovery were estimated in the derivation cohort, and their predictive accuracy was assessed in the validation cohort. The primary endpoint was nonrecovery from AKI (within 7 days). RESULTS: Of 379 patients, 159 (41.9%) patients failed to recover from AKI onset, with 79 in the derivation cohort and 80 in the validation cohort. Urinary [TIMP-2]*[IGFBP7] on day 0 showed a better prediction ability for nonrecovery than TIMP-2 and IGFBP7 alone, with an area under the reciever operating characteristic curve (AUC) of 0.751 [95% confidence interval (CI) 0.701–0.852, p < 0.001] and an optimal cut-off value of 1.05 ((ng/mL)(2)/1000). When [TIMP-2]*[IGFBP7] was combined with the clinical factors of AKI diagnosed by the urine output (UO) criteria, AKI stage 2–3 and nonrenal SOFA score for predicting nonrecovery, the AUC was significantly improved to 0.852 (95% CI 0.750–0.891, p < 0.001), which achieved a sensitivity and specificity of 88.8% (72.9, 98.7) and 92.6% (80.8, 100.0), respectively. However, urine [TIMP-2]*[IGFBP7], TIMP-2 alone, and IGFBP7 alone on day 1 performed poorly for predicting AKI recovery. CONCLUSION: Urinary [TIMP-2]*[IGFBP7] on day 0 showed a fair performance for predicting nonrecovery from AKI. The predictive accuracy can be improved when urinary [TIMP-2]*[IGFBP7] is combined with the clinical factors of AKI diagnosed by the UO criteria, AKI stage 2–3 and nonrenal SOFA score. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13613-022-00989-8.
format Online
Article
Text
id pubmed-8840946
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Springer International Publishing
record_format MEDLINE/PubMed
spelling pubmed-88409462022-02-23 Cell cycle arrest biomarkers for predicting renal recovery from acute kidney injury: a prospective validation study Jia, Hui-Miao Cheng, Li Weng, Yi-Bing Wang, Jing-Yi Zheng, Xi Jiang, Yi-Jia Xin, Xin Guo, Shu-Yan Chen, Chao-Dong Guo, Fang-Xing Han, Yu-Zhen Zhang, Tian-En Li, Wen-Xiong Ann Intensive Care Research BACKGROUND: Acute kidney injury (AKI) is a common disease in the intensive care unit (ICU). AKI patients with nonrecovery of renal function have a markedly increased risk of death compared with patients with recovery. The current study aimed to explore and validate the utility of urinary cell cycle arrest biomarkers for predicting nonrecovery in patients who developed AKI after ICU admission. METHODS: We prospectively and consecutively enrolled 379 critically ill patients who developed AKI after admission to the ICU, which were divided into a derivation cohort (194 AKI patients) and a validation cohort (185 AKI patients). The biomarkers of urinary tissue inhibitor of metalloproteinase-2 (TIMP-2) and insulin-like growth factor-binding protein 7 (IGFBP7) were detected at inclusion immediately after AKI diagnosis (day 0) and 24 h later (day 1). The optimal cut-off values of these biomarkers for predicting nonrecovery were estimated in the derivation cohort, and their predictive accuracy was assessed in the validation cohort. The primary endpoint was nonrecovery from AKI (within 7 days). RESULTS: Of 379 patients, 159 (41.9%) patients failed to recover from AKI onset, with 79 in the derivation cohort and 80 in the validation cohort. Urinary [TIMP-2]*[IGFBP7] on day 0 showed a better prediction ability for nonrecovery than TIMP-2 and IGFBP7 alone, with an area under the reciever operating characteristic curve (AUC) of 0.751 [95% confidence interval (CI) 0.701–0.852, p < 0.001] and an optimal cut-off value of 1.05 ((ng/mL)(2)/1000). When [TIMP-2]*[IGFBP7] was combined with the clinical factors of AKI diagnosed by the urine output (UO) criteria, AKI stage 2–3 and nonrenal SOFA score for predicting nonrecovery, the AUC was significantly improved to 0.852 (95% CI 0.750–0.891, p < 0.001), which achieved a sensitivity and specificity of 88.8% (72.9, 98.7) and 92.6% (80.8, 100.0), respectively. However, urine [TIMP-2]*[IGFBP7], TIMP-2 alone, and IGFBP7 alone on day 1 performed poorly for predicting AKI recovery. CONCLUSION: Urinary [TIMP-2]*[IGFBP7] on day 0 showed a fair performance for predicting nonrecovery from AKI. The predictive accuracy can be improved when urinary [TIMP-2]*[IGFBP7] is combined with the clinical factors of AKI diagnosed by the UO criteria, AKI stage 2–3 and nonrenal SOFA score. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13613-022-00989-8. Springer International Publishing 2022-02-12 /pmc/articles/PMC8840946/ /pubmed/35150348 http://dx.doi.org/10.1186/s13613-022-00989-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research
Jia, Hui-Miao
Cheng, Li
Weng, Yi-Bing
Wang, Jing-Yi
Zheng, Xi
Jiang, Yi-Jia
Xin, Xin
Guo, Shu-Yan
Chen, Chao-Dong
Guo, Fang-Xing
Han, Yu-Zhen
Zhang, Tian-En
Li, Wen-Xiong
Cell cycle arrest biomarkers for predicting renal recovery from acute kidney injury: a prospective validation study
title Cell cycle arrest biomarkers for predicting renal recovery from acute kidney injury: a prospective validation study
title_full Cell cycle arrest biomarkers for predicting renal recovery from acute kidney injury: a prospective validation study
title_fullStr Cell cycle arrest biomarkers for predicting renal recovery from acute kidney injury: a prospective validation study
title_full_unstemmed Cell cycle arrest biomarkers for predicting renal recovery from acute kidney injury: a prospective validation study
title_short Cell cycle arrest biomarkers for predicting renal recovery from acute kidney injury: a prospective validation study
title_sort cell cycle arrest biomarkers for predicting renal recovery from acute kidney injury: a prospective validation study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8840946/
https://www.ncbi.nlm.nih.gov/pubmed/35150348
http://dx.doi.org/10.1186/s13613-022-00989-8
work_keys_str_mv AT jiahuimiao cellcyclearrestbiomarkersforpredictingrenalrecoveryfromacutekidneyinjuryaprospectivevalidationstudy
AT chengli cellcyclearrestbiomarkersforpredictingrenalrecoveryfromacutekidneyinjuryaprospectivevalidationstudy
AT wengyibing cellcyclearrestbiomarkersforpredictingrenalrecoveryfromacutekidneyinjuryaprospectivevalidationstudy
AT wangjingyi cellcyclearrestbiomarkersforpredictingrenalrecoveryfromacutekidneyinjuryaprospectivevalidationstudy
AT zhengxi cellcyclearrestbiomarkersforpredictingrenalrecoveryfromacutekidneyinjuryaprospectivevalidationstudy
AT jiangyijia cellcyclearrestbiomarkersforpredictingrenalrecoveryfromacutekidneyinjuryaprospectivevalidationstudy
AT xinxin cellcyclearrestbiomarkersforpredictingrenalrecoveryfromacutekidneyinjuryaprospectivevalidationstudy
AT guoshuyan cellcyclearrestbiomarkersforpredictingrenalrecoveryfromacutekidneyinjuryaprospectivevalidationstudy
AT chenchaodong cellcyclearrestbiomarkersforpredictingrenalrecoveryfromacutekidneyinjuryaprospectivevalidationstudy
AT guofangxing cellcyclearrestbiomarkersforpredictingrenalrecoveryfromacutekidneyinjuryaprospectivevalidationstudy
AT hanyuzhen cellcyclearrestbiomarkersforpredictingrenalrecoveryfromacutekidneyinjuryaprospectivevalidationstudy
AT zhangtianen cellcyclearrestbiomarkersforpredictingrenalrecoveryfromacutekidneyinjuryaprospectivevalidationstudy
AT liwenxiong cellcyclearrestbiomarkersforpredictingrenalrecoveryfromacutekidneyinjuryaprospectivevalidationstudy