Sheila Bermejo , Ester González , Katia López-Revuelta , Meritxell Ibernon , Diana López , Adoración Martín-Gómez , Rosa Garcia-Osuna , Tania Linares , Montserrat Díaz , Nàdia Martín , Xoana Barros , Helena Marco , Maruja Isabel Navarro , Noemí Esparza , Sandra Elias , Ana Coloma , Nicolás Roberto Robles , Irene Agraz , Esteban Poch , Lida Rodas , María José Soler
{"title":"糖尿病合并慢性肾病患者非糖尿病肾病的预测模型西班牙多中心研究","authors":"Sheila Bermejo , Ester González , Katia López-Revuelta , Meritxell Ibernon , Diana López , Adoración Martín-Gómez , Rosa Garcia-Osuna , Tania Linares , Montserrat Díaz , Nàdia Martín , Xoana Barros , Helena Marco , Maruja Isabel Navarro , Noemí Esparza , Sandra Elias , Ana Coloma , Nicolás Roberto Robles , Irene Agraz , Esteban Poch , Lida Rodas , María José Soler","doi":"10.1016/j.nefroe.2025.04.004","DOIUrl":null,"url":null,"abstract":"<div><h3>Aims</h3><div>Kidney biopsy is increasing in patients with diabetes and around 50–60% of patients with diabetes have non-diabetic kidney disease (NDKD). Identifying NDKD is crucial since these patients have a better renal prognosis and survival compared to patients with diabetic nephropathy (DN). The objective of this study is to provide a clinical practice tool for through a predictive model of NDKD.</div></div><div><h3>Material and methods</h3><div>Observational and multicenter Spanish study of the pathological results of kidney biopsies in patients with diabetes from 2002 to 2014. A logistic regression analysis and the probability of presenting NDKD was calculated using a punctuation score.</div></div><div><h3>Results</h3><div>A total of 832 patients with diabetes and renal biopsy were analyzed. An accurate risk-predictive model for NDKD was developed with five top-ranked non-invasive clinical variables (age, serum creatinine, presence of diabetic retinopathy, microhematuria and peripheral vascular disease) obtaining a score for each one allowing for a proper prediction of NDKD.</div></div><div><h3>Conclusions</h3><div>In our study, we developed a risk-stratification score to calculate the probability of NDKD. This could be in a next future a useful tool for the clinical indication of renal biopsy in patients with diabetes and kidney disease.</div></div>","PeriodicalId":31770,"journal":{"name":"Nefrologia English Edition","volume":"45 5","pages":"Pages 360-368"},"PeriodicalIF":0.0000,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A predictive model of non-diabetic kidney disease in patients with diabetes mellitus and chronic kidney disease. A Spanish multi-center study\",\"authors\":\"Sheila Bermejo , Ester González , Katia López-Revuelta , Meritxell Ibernon , Diana López , Adoración Martín-Gómez , Rosa Garcia-Osuna , Tania Linares , Montserrat Díaz , Nàdia Martín , Xoana Barros , Helena Marco , Maruja Isabel Navarro , Noemí Esparza , Sandra Elias , Ana Coloma , Nicolás Roberto Robles , Irene Agraz , Esteban Poch , Lida Rodas , María José Soler\",\"doi\":\"10.1016/j.nefroe.2025.04.004\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Aims</h3><div>Kidney biopsy is increasing in patients with diabetes and around 50–60% of patients with diabetes have non-diabetic kidney disease (NDKD). Identifying NDKD is crucial since these patients have a better renal prognosis and survival compared to patients with diabetic nephropathy (DN). The objective of this study is to provide a clinical practice tool for through a predictive model of NDKD.</div></div><div><h3>Material and methods</h3><div>Observational and multicenter Spanish study of the pathological results of kidney biopsies in patients with diabetes from 2002 to 2014. A logistic regression analysis and the probability of presenting NDKD was calculated using a punctuation score.</div></div><div><h3>Results</h3><div>A total of 832 patients with diabetes and renal biopsy were analyzed. An accurate risk-predictive model for NDKD was developed with five top-ranked non-invasive clinical variables (age, serum creatinine, presence of diabetic retinopathy, microhematuria and peripheral vascular disease) obtaining a score for each one allowing for a proper prediction of NDKD.</div></div><div><h3>Conclusions</h3><div>In our study, we developed a risk-stratification score to calculate the probability of NDKD. This could be in a next future a useful tool for the clinical indication of renal biopsy in patients with diabetes and kidney disease.</div></div>\",\"PeriodicalId\":31770,\"journal\":{\"name\":\"Nefrologia English Edition\",\"volume\":\"45 5\",\"pages\":\"Pages 360-368\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nefrologia English Edition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2013251425000549\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nefrologia English Edition","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2013251425000549","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Medicine","Score":null,"Total":0}
A predictive model of non-diabetic kidney disease in patients with diabetes mellitus and chronic kidney disease. A Spanish multi-center study
Aims
Kidney biopsy is increasing in patients with diabetes and around 50–60% of patients with diabetes have non-diabetic kidney disease (NDKD). Identifying NDKD is crucial since these patients have a better renal prognosis and survival compared to patients with diabetic nephropathy (DN). The objective of this study is to provide a clinical practice tool for through a predictive model of NDKD.
Material and methods
Observational and multicenter Spanish study of the pathological results of kidney biopsies in patients with diabetes from 2002 to 2014. A logistic regression analysis and the probability of presenting NDKD was calculated using a punctuation score.
Results
A total of 832 patients with diabetes and renal biopsy were analyzed. An accurate risk-predictive model for NDKD was developed with five top-ranked non-invasive clinical variables (age, serum creatinine, presence of diabetic retinopathy, microhematuria and peripheral vascular disease) obtaining a score for each one allowing for a proper prediction of NDKD.
Conclusions
In our study, we developed a risk-stratification score to calculate the probability of NDKD. This could be in a next future a useful tool for the clinical indication of renal biopsy in patients with diabetes and kidney disease.
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