Fangfang Sun1, Huijing Wang2,3,4, Danting Zhang1, Fei Han2,3,4, Shuang Ye1. 1. Department of Rheumatology, Ren Ji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai. 2. Kidney Disease Center, First Affiliated Hospital, Zhejiang University School of Medicine. 3. Institute of Nephrology, Zhejiang University. 4. Key Laboratory of Kidney Disease Prevention and Control Technology, Hangzhou, China.
Abstract
OBJECTIVE: To develop a short-term renal outcome prediction model for acute kidney injury (AKI) in patients with LN. METHODS: Two lupus AKI cohorts from two independent centres during 2013-2019 were included: a derivation cohort from a rheumatology centre and a validation cohort from a nephrology centre. Clinical characteristics and renal histologic features were obtained. The outcome measurement was the recovery of kidney function within 12 months. Lasso regression was used for feature selection. Prediction models with or without pathology were built and a nomogram was plotted. Model evaluation including calibration curve and decision curve analysis was performed. RESULTS: A total of 130 patients were included in the derivation cohort and 96 patients in the validation cohort, of which 82 and 73 patients received a renal biopsy, respectively. The prognostic nomogram model without pathology included determinants of SLE duration, days from AKI onset to treatment and baseline creatinine level [C-index 0.85 (95% CI 0.78, 0.91) and 0.79 (95% CI 0.70, 0.88) for the two cohorts]. A combination of histologic tubulointerstitial (TI) fibrosis in the nomogram gave an incremental predictive performance (C-index 0.93 vs 0.85; P = 0.039) in the derivation cohort but failed to improve the performance in the validation cohort (C-index 0.81 vs 0.79; P = 0.78). Decision curve analysis suggested clinical benefit of the prediction models. CONCLUSION: The predictive nomogram models might facilitate more accurate management for lupus patients with AKI.
OBJECTIVE: To develop a short-term renal outcome prediction model for acute kidney injury (AKI) in patients with LN. METHODS: Two lupus AKI cohorts from two independent centres during 2013-2019 were included: a derivation cohort from a rheumatology centre and a validation cohort from a nephrology centre. Clinical characteristics and renal histologic features were obtained. The outcome measurement was the recovery of kidney function within 12 months. Lasso regression was used for feature selection. Prediction models with or without pathology were built and a nomogram was plotted. Model evaluation including calibration curve and decision curve analysis was performed. RESULTS: A total of 130 patients were included in the derivation cohort and 96 patients in the validation cohort, of which 82 and 73 patients received a renal biopsy, respectively. The prognostic nomogram model without pathology included determinants of SLE duration, days from AKI onset to treatment and baseline creatinine level [C-index 0.85 (95% CI 0.78, 0.91) and 0.79 (95% CI 0.70, 0.88) for the two cohorts]. A combination of histologic tubulointerstitial (TI) fibrosis in the nomogram gave an incremental predictive performance (C-index 0.93 vs 0.85; P = 0.039) in the derivation cohort but failed to improve the performance in the validation cohort (C-index 0.81 vs 0.79; P = 0.78). Decision curve analysis suggested clinical benefit of the prediction models. CONCLUSION: The predictive nomogram models might facilitate more accurate management for lupus patients with AKI.
Authors: Brian R Stotter; Ellen Cody; Hongjie Gu; Ankana Daga; Larry A Greenbaum; Minh Dien Duong; Alexandra Mazo; Beatrice Goilav; Alexis Boneparth; Mahmoud Kallash; Ahmed Zeid; Wacharee Seeherunvong; Rebecca R Scobell; Issa Alhamoud; Caitlin E Carter; Siddharth Shah; Caroline E Straatmann; Bradley P Dixon; Jennifer C Cooper; Raoul D Nelson; Deborah M Levy; Hermine I Brunner; Priya S Verghese; Scott E Wenderfer Journal: Pediatr Nephrol Date: 2022-10-17 Impact factor: 3.651