Associations of longitudinal height and weight with clinical outcomes in pediatric kidney replacement therapy: results from the ESPN/ERA Registry

Nutritional profile and infection-related hospital admissions in children with chronic kidney disease

BACKGROUND

Protein energy wasting (PEW) and undernutrition are highly prevalent in children with chronic kidney disease (CKD), but their impact on clinical outcomes is not well described. This prospective longitudinal study in children with CKD assessed the association of nutritional parameters with infection-related hospital admissions (IRHA).

METHODS

Children with CKD2-5D aged 2-18 years and infection-free for 1 month were recruited over 5 years. Evaluation for undernutrition by subjective global nutritional assessment and for PEW using paediatric criteria was undertaken and categorized as mild (>2 criteria), standard (>3 criteria) and modified PEW (>3 criteria with short stature). The IRHA (severe viral, bacterial or fungal infections) were recorded.

RESULTS

Among 137 children (45 on dialysis; age 123 ± 46 months; 70% males), undernutrition was seen in 60% and PEW in 52%. In over 38 ± 21 months follow-up, 107 (78%) required hospital admissions (67% IRHA). The incidence rate of IRHA in days per patient-year was higher in those with undernutrition compared to well-nourished children [1.74 (1.27, 2.31) vs. 0.65 (0.44, 0.92) p < 0.0001] and higher in those with PEW compared to no PEW [1.74 (1.30, 2.28) vs. 0.56 (0.36, 0.82) p < 0.0001] respectively. On adjusted analysis, independent risk factors for IRHA were undernutrition, low BMI, hypoalbuminemia and dialysis status with modified PEW [OR 5.34 (2.16, 13.1) p < 0.001] and raised CRP [OR 4.66 (1.56, 13.9) p = 0.006] having the highest risk. Additionally, modified PEW and BMI were noted to have a twofold risk for recurrent infections.

CONCLUSION

In children with CKD2-5D, incidence rate of IRHA was significantly higher in those with undernutrition and PEW. While dialysis, poor nutritional status and inflammation were risk factors for IRHA, modified PEW and BMI were associated with recurrent infections.

Predicting wait time for pediatric kidney transplant: a novel index

BACKGROUND

Over one thousand pediatric kidney transplant candidates are added to the waitlist annually, yet the prospective time spent waiting is unknown for many. Our study fills this gap by identifying variables that impact waitlist time and by creating an index to predict the likelihood of a pediatric candidate receiving a transplant within 1 year of listing. This index could be used to guide patient management by giving clinicians a potential timeline for each candidate's listing based on a unique combination of risk factors.

METHODS

A retrospective analysis of 3757 pediatric kidney transplant candidates from the 2014 to 2020 OPTN/UNOS database was performed. The data was randomly divided into a training set, comprising two-thirds of the data, and a testing set, comprising one-third of the data. From the training set, univariable and multivariable logistic regressions were used to identify significant predictive factors affecting wait times. A predictive index was created using variables significant in the multivariable analysis. The index's ability to predict likelihood of transplantation within 1 year of listing was validated using ROC analysis on the training set. Validation of the index using ROC analysis was repeated on the testing set.

RESULTS

A total of 10 variables were found to be significant. The five most significant variables include the following: blood group, B (OR 0.65); dialysis status (OR 3.67); kidney disease etiology, SLE (OR 0.38); and OPTN region, 5 (OR 0.54) and 6 (OR 0.46). ROC analysis of the index on the training set yielded a c-statistic of 0.71. ROC analysis of the index on the testing set yielded a c-statistic of 0.68.

CONCLUSIONS

This index is a modest prognostic model to assess time to pediatric kidney transplantation. It is intended as a supplementary tool to guide patient management by providing clinicians with an individualized prospective timeline for each candidate. Early identification of candidates with potential for prolonged waiting times may help encourage more living donation including paired donation chains.