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A predictive model of progressive chronic kidney disease in idiopathic nephrotic syndrome
Ana Carmen Quaresma Mendonça1, Eduardo Araújo Oliveira1, Brunna Pinto Fróes1
1Pediatric Nephrology Unit, Federal University of Minas Gerais, Belo Horizonte, Brazil.
Insights
A new predictive model identifies children with idiopathic nephrotic syndrome (INS) at high risk for chronic kidney disease (CKD). This tool aids early detection and intervention for better renal outcomes in pediatric patients.
Area of Science:
- Pediatric Nephrology
- Chronic Kidney Disease Epidemiology
- Predictive Modeling in Medicine
Background:
- Limited data exists on chronic kidney disease (CKD) risk factors in children with idiopathic nephrotic syndrome (INS).
- Early identification of high-risk patients is crucial for timely intervention.
Purpose of the Study:
- To develop and validate a predictive model for CKD progression in pediatric patients with INS.
- To identify key risk factors associated with CKD development in this population.
Main Methods:
- Retrospective cohort study of 294 patients with INS (1970-2012).
- Cox proportional hazards model used to develop a predictive score based on initial age, hematuria, and steroid resistance.
- Prognostic score categorized patients into low, medium, and high-risk groups.
Main Results:
- The predictive model demonstrated high accuracy (c-statistic 0.92-0.95) at 2, 5, and 10 years.
- High-risk patients had a 40% probability of progressing to CKD stage 3+ within 10 years (P < 0.001).
- Low-risk and medium-risk groups showed excellent 10-year renal survival (100% and 95%, respectively).
Conclusions:
- The developed predictive model effectively identifies children with INS at high risk for renal dysfunction.
- This tool can facilitate early detection of at-risk individuals, enabling targeted management strategies.
Background:
There are limited data on the risk factors for chronic kidney disease (CKD) in children with idiopathic nephrotic syndrome (INS). This retrospective cohort study aimed to develop a predictive model for CKD progression in children with INS.
Methods:
Between 1970 and 2012, a total of 294 patients with INS were followed up. The primary outcome was progression to CKD stage 3 or higher. A predictive model was developed using a Cox proportional hazards model. A score was calculated using b-coefficients and summing up points assigned to each significant variable. Prognostic score was grouped into categories: low risk, medium risk, and high risk.
Results:
Median follow-up was 6.9 years. Median renal survival was 26.1 years and probability of CKD stage 3 or higher was 8% in 10 years. Multivariate analysis showed that the most accurate model included initial age, hematuria, and steroid resistance. Accuracy was high with a c-statistic of 0.95 (95% confidence interval [CI] 0.91-0.99), 0.92 (95% CI 0.88-0.96), and 0.92 (95% CI 0.87-0.97) at 2, 5, and 10 years of follow-up respectively. By survival analysis, 10-year renal survival was 100% for the low-risk and 95% for the medium-risk group, while 40% of high-risk patients would exhibit CKD stage 3 or higher (P < 0.001).
Conclusions:
Our predictive model of CKD may contribute to the early identification of a subgroup of INS patients at a high risk of renal dysfunction.
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