Prediction model of renal function recovery for primary membranous nephropathy with acute kidney injury.
Prediction model of renal function recovery for primary membranous nephropathy with acute kidney injury.
复制标题
原发性膜性肾病合并急性肾损伤肾功能恢复预测模型
DOI:
10.1186/s12882-022-02882-9
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发表时间:
2022-07-13
期刊:
影响因子:
2.3
通讯作者:
中科院分区:
文献类型:
--
作者:
The clinical and pathological impact factors for renal function recovery in acute kidney injury (AKI) on the progression of renal function in primary membranous nephropathy (PMN) with AKI patients have not yet been reported, we sought to investigate the factors that may influence renal function recovery and develop a nomogram model for predicting renal function recovery in PMN with AKI patients. Two PMN with AKI cohorts from the Nephrology Department, the First Affiliated Hospital of Wenzhou Medical University during 2012–2018 and 2019–2020 were included, i.e., a derivation cohort during 2012–2018 and a validation cohort during 2019–2020. Clinical characteristics and renal pathological features were obtained. The outcome measurement was the recovery of renal function within 12 months. Lasso regression was used for clinical and pathological features selection. Prediction model was built and nomogram was plotted. Model evaluations including calibration curves were performed. Renal function recovery was found in 72 of 124 (58.1%) patients and 41 of 72 (56.9%) patients in the derivation and validation cohorts, respectively. The prognostic nomogram model included determinants of sex, age, the comorbidity of hypertensive nephropathy, the stage of glomerular basement membrane and diuretic treatment with a reasonable concordance index of 0.773 (95%CI,0.716–0.830) in the derivation cohort and 0.773 (95%CI, 0.693–0.853) in the validation cohort. Diuretic use was a significant impact factor with decrease of renal function recovery in PMN with AKI patients. The predictive nomogram model provides useful prognostic tool for renal function recovery in PMN patients with AKI. The online version contains supplementary material available at 10.1186/s12882-022-02882-9.
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影响因子:
3
作者:
Chen T;Zhou Y;Chen X;Chen B;Pan J
通讯作者:
Pan J
影响因子:
13.2
作者:
Chen, CL;Fang, HC;Wang, JS
通讯作者:
Wang, JS
DOI:
10.2215/cjn.03531006
发表时间:
2007-05-01
影响因子:
9.8
作者:
Waldman, Meryl;Crew, R. John;Appel, Gerald
通讯作者:
Appel, Gerald
影响因子:
6
作者:
Costantino VV;Gil Lorenzo AF;Bocanegra V;Vallés PG
通讯作者:
Vallés PG
影响因子:
4.3
作者:
Abraham S;Rameshkumar R;Chidambaram M;Soundravally R;Subramani S;Bhowmick R;Sheriff A;Maulik K;Mahadevan S
通讯作者:
Mahadevan S