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Prediction model of renal function recovery for primary membranous nephropathy with acute kidney injury

BACKGROUND AND OBJECTIVES: 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 in...

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Autores principales: Chen, Tianxin, Zhou, Ying, Zhu, Jianfen, Chen, Xinxin, Pan, Jingye
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9281044/
https://www.ncbi.nlm.nih.gov/pubmed/35831820
http://dx.doi.org/10.1186/s12882-022-02882-9
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author Chen, Tianxin
Zhou, Ying
Zhu, Jianfen
Chen, Xinxin
Pan, Jingye
author_facet Chen, Tianxin
Zhou, Ying
Zhu, Jianfen
Chen, Xinxin
Pan, Jingye
author_sort Chen, Tianxin
collection PubMed
description BACKGROUND AND OBJECTIVES: 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. METHODS: 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. RESULT: 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. CONCLUSION: The predictive nomogram model provides useful prognostic tool for renal function recovery in PMN patients with AKI. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12882-022-02882-9.
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spelling pubmed-92810442022-07-15 Prediction model of renal function recovery for primary membranous nephropathy with acute kidney injury Chen, Tianxin Zhou, Ying Zhu, Jianfen Chen, Xinxin Pan, Jingye BMC Nephrol Research BACKGROUND AND OBJECTIVES: 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. METHODS: 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. RESULT: 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. CONCLUSION: The predictive nomogram model provides useful prognostic tool for renal function recovery in PMN patients with AKI. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12882-022-02882-9. BioMed Central 2022-07-13 /pmc/articles/PMC9281044/ /pubmed/35831820 http://dx.doi.org/10.1186/s12882-022-02882-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Chen, Tianxin
Zhou, Ying
Zhu, Jianfen
Chen, Xinxin
Pan, Jingye
Prediction model of renal function recovery for primary membranous nephropathy with acute kidney injury
title Prediction model of renal function recovery for primary membranous nephropathy with acute kidney injury
title_full Prediction model of renal function recovery for primary membranous nephropathy with acute kidney injury
title_fullStr Prediction model of renal function recovery for primary membranous nephropathy with acute kidney injury
title_full_unstemmed Prediction model of renal function recovery for primary membranous nephropathy with acute kidney injury
title_short Prediction model of renal function recovery for primary membranous nephropathy with acute kidney injury
title_sort prediction model of renal function recovery for primary membranous nephropathy with acute kidney injury
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9281044/
https://www.ncbi.nlm.nih.gov/pubmed/35831820
http://dx.doi.org/10.1186/s12882-022-02882-9
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