Clinical characteristics and prognostic analysis of primary IgA nephropathy with diffuse crescent formation
Objective To understand the clinical and pathological characteristics and prognosis of patients with diffuse crescentic IgA nephropathy(CIgAN).Methods Thirty-three patients diagnosed as CIgAN through kidney biopsy from July 2007 to July 2022 were selected.Their clinical and pathological data were analyzed.Twenty-two patients followed-up for more than 6 months were included in the follow-up cohort.Results In the 33 patients,there were 18 males(55%)and 15 females(45%).The age at the time of kidney biopsy was 36(21.551)years old and their serum creatinine(Scr)was 153(92271)μmol/L.Their percentage of crescents was 62.5%(54.2%66.7%),with cellular fibrocellular crescents accounting for 26.1±16.5%.Thirteen patients had an-tecedent upper respiratory tract infections.The average follow-up time was 25(872)months in the follow-up cohort.Of the 22 patients,10 patients(46%)progressed to composite renal outcomes,and 8(36%)developed end-stage kidney disease(ESKD).Multivariate Cox regression analysis showed that Scr at the time of kidney biopsy was an independent risk factor for composite renal out-comes,while the percentage of crescents was not associated with composite renal outcomes.The receiver operating characteristic curve(ROC)analysis indicated that even with immunosuppressive therapy,patients with diffuse crescentic IgA nephropathy and serum Scr concentration greater than 149 μmol/L at the time of kidney biopsy still had a high risk of poor prognosis.Conclusions CIgAN tends to progress rapidly and has a poor prognosis,especially in patients with Scr concentration greater than 149 μmol/L at the time of kidney biopsy.The predominant type of crescents is cellular fibrocellular crescents.Serum Scr concentration at the time of kidney biopsy is an independent risk factor for a decline in estimated glomerular filtration rate(eGFR)of≥50%or ESKD in patients with CIgAN.The percentage of crescents is not significantly correlated with patient prognosis.
NETL
NSTL
万方数据
