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Published on: February 2, 2021
Risk factors and predictive models for perioperative acute kidney injury in children: a narrative review
1Department of Operation Room, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Insights
Perioperative acute kidney injury (AKI) in children is a significant risk, especially after cardiac surgery. Early identification of risk factors and predictive models are crucial for preventing long-term kidney damage.
Area of Science:
- Pediatric Nephrology
- Critical Care Medicine
- Surgical Outcomes
Background:
- Perioperative acute kidney injury (AKI) affects 5-30% of pediatric surgical patients, rising to 40% in neonates undergoing cardiac surgery.
- AKI increases mortality and the risk of developing chronic kidney disease in children.
- This review focuses on identifying risk factors and predictive models for perioperative AKI in pediatric populations.
Purpose of the Study:
- To synthesize current evidence on risk factors for pediatric perioperative AKI.
- To review existing and emerging predictive models for early AKI detection in children.
- To inform strategies for early risk stratification and preventive care in pediatric surgical patients.
Main Methods:
- A comprehensive literature search was conducted across major databases (PubMed/MEDLINE, Embase, Web of Science, Cochrane Library) up to March 2024.
- Search terms included "acute kidney injury," "pediatrics," "perioperative," "risk factors," and "prediction models."
- Studies involving pediatric patients (age ≤18 years) were included in the narrative review.
Main Results:
- Key risk factors identified include young age, congenital heart disease, nephrotoxic medication exposure, and major surgeries (e.g., cardiopulmonary bypass).
- Various predictive models, from statistical methods to machine learning, are evaluated, incorporating novel biomarkers like NGAL and KIM-1.
- Promising biomarkers such as urinary L-FABP and TIMP-2×IGFBP7 show potential for earlier AKI detection.
Conclusions:
- Early identification of children at high risk for perioperative AKI is critical for improving outcomes.
- A need exists for pediatric-specific predictive models, with ongoing research focusing on validation and refinement.
- Implementing risk-stratified, evidence-based care and validating novel biomarkers can enhance long-term renal health in pediatric surgical patients.
Background And Objective:
Perioperative acute kidney injury (AKI) is a serious complication in children, with an incidence of 5-30% and up to 40% in neonates after cardiac surgery. It increases mortality and the risk of chronic kidney disease. This narrative review synthesizes current evidence on risk factors and predictive models for perioperative AKI in children, aiming to inform early risk stratification and preventive care.
Methods:
A literature search was conducted up to March 2024 using PubMed/MEDLINE, Embase, Web of Science, and Cochrane Library. The search combined terms related to AKI, pediatrics, the perioperative period, risk factors, and prediction models. Studies focusing on pediatric patients (≤18 years) were included.
Key Content And Findings:
Key risk factors include young age, congenital heart disease, exposure to nephrotoxic medications, and major surgeries like those using cardiopulmonary bypass. The review evaluates predictive models, from traditional statistical methods to machine learning models that incorporate novel biomarkers such as neutrophil gelatinase-associated lipocalin and kidney injury molecule-1 for earlier detection. Promising biomarkers like urinary L-FABP and TIMP-2×IGFBP7 are also highlighted. Integrating these tools into clinical workflows can guide proactive management.
Conclusions:
Early identification of high-risk children is crucial. While predictive modeling is advancing, a gap remains in models specifically validated for pediatric populations. Future research should focus on multicenter studies to refine pediatric-specific models, validate novel biomarkers, and develop personalized approaches. Implementing evidence-based, risk-stratified care has the potential to significantly improve outcomes and long-term renal health for children undergoing surgery.
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