Clinical and Histopathological Spectrum of Childhood Onset Nephrotic Syndrome- Prospective Study

Introduction: Nephrotic Syndrome is one of the most common forms of renal disease in the pediatric population. Nephrotic Syndrome is a clinical manifestation of different histopathologic subtypes of several glomerular diseases. Present study is aimed to evaluate the clinical profile and histopathological spectrum of glomerular diseases in childhood onset nephrotic syndrome and their outcomes. Materials and methods: This study has been conducted in the Department of Nephrology, Andhra Medical College/King George Hospital in Visakhapatnam, Andhra Pradesh. This is a prospective, observational study conducted between April 2018 to November 2019. All children, birth to 16 years, presenting with clinical or laboratory features suggestive of Nephrotic Syndrome were included in the study. Results: A total of 48 children who fulfilled the inclusion criteria were enrolled for study and followed up for 6 months duration. Out of 48 patients, majority (62.5 %) were male patients with mean age of presentation being 6.95±3.71 years. Out of 48 patients, 4 patients who had atypical presentation were biopsied at presentation. Of the remaining 44 patients, 88.6 % had Steroid sensitive nephrotic syndrome, 11.4 % had Steroid resistant nephrotic syndrome. No relapse was seen in 38.5 % patients, infrequent relapses were seen in 25.6 %of patients, frequent relapses were seen in 20.5 % of patients and 10.3 % had Steroid dependent nephrotic syndrome.5.1 % of patients were late non responders. URTI was the commonest trigger, it was associated with 50.0 % of relapses. Minimal change disease was the commonest diagnosis on renal biopsy, found in 4 (36.36 %) patients, followed by FSGS in 3 (27.27 %), APSGN/ APIGN in 2 (18.18 %) cases, LN was found in 1 case (9 %), IgA was observed in one case. Conclusion: Nephrotic syndrome is the commonest presentation of glomerular disease in children. A large majority of cases are idiopathic nephrotic syndrome. Time to respond to steroids is a strong predictor