Combination of urinary biomarkers can predict cardiac surgery-associated acute kidney injury: a systematic review and meta-analysis
Abstract Introduction Acute kidney injury (AKI) develops in 20–50% of patients undergoing cardiac surgery (CS). We aimed to assess the predictive value of urinary biomarkers (UBs) for predicting CS-associated AKI. We also aimed to investigate the accuracy of the combination of UB measurements and th...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-03-01
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| Series: | Annals of Intensive Care |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13613-025-01459-7 |
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| Summary: | Abstract Introduction Acute kidney injury (AKI) develops in 20–50% of patients undergoing cardiac surgery (CS). We aimed to assess the predictive value of urinary biomarkers (UBs) for predicting CS-associated AKI. We also aimed to investigate the accuracy of the combination of UB measurements and their incorporation in predictive models to guide physicians in identifying patients developing CS-associated AKI. Methods All clinical studies reporting on the diagnostic accuracy of individual or combined UBs were eligible for inclusion. We searched three databases (MEDLINE, EMBASE, and CENTRAL) without any filters or restrictions on the 11th of November, 2022 and reperformed our search on the 3rd of November 2024. Random and mixed effects models were used for meta-analysis. The main effect measure was the area under the Receiver Operating Characteristics curve (AUC). Our primary outcome was the predictive values of each individual UB at different time point measurements to identify patients developing acute kidney injury (KDIGO). As a secondary outcome, we calculated the performance of combinations of UBs and clinical models enhanced by UBs. Results We screened 13,908 records and included 95 articles (both randomised and non-randomised studies) in the analysis. The predictive value of UBs measured in the intraoperative and early postoperative period was at maximum acceptable, with the highest AUCs of 0.74 [95% CI 0.68, 0.81], 0.73 [0.65, 0.82] and 0.74 [0.72, 0.77] for predicting severe CS-AKI, respectively. To predict all stages of CS-AKI, UBs measured in the intraoperative and early postoperative period yielded AUCs of 0.75 [0.67, 0.82] and 0.73 [0.54, 0.92]. To identify all and severe cases of acute kidney injury, combinations of UB measurements had AUCs of 0.82 [0.75, 0.88] and 0.85 [0.79, 0.91], respectively. Conclusion The combination of urinary biomarkers measurements leads to good accuracy. |
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| ISSN: | 2110-5820 |