Non-diabetic nephropathy in diabetic patients: incidence, HbA1c variability and other predictive factors, and implications

Purpose Diabetes mellitus (DM) is the leading cause of chronic kidney disease (CKD) in the population. In patients with diabetes mellitus, the incidence of non-diabetic nephropathy (NDNP) has been estimated to range from 3% to 69.5%. Personal judgment is frequently employed while deciding whether or...

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Veröffentlicht in:International urology and nephrology 2024-09, Vol.56 (9), p.3091-3100
Hauptverfasser: Demirelli, Bülent, Boztepe, Burcu, Şenol, Elif Gülcan, Boynueğri, Başak, Bildacı, Yelda Deligöz, Gümrükçü, Gülistan, Canbakan, Mustafa, Öğütmen, Melike Betül
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container_end_page 3100
container_issue 9
container_start_page 3091
container_title International urology and nephrology
container_volume 56
creator Demirelli, Bülent
Boztepe, Burcu
Şenol, Elif Gülcan
Boynueğri, Başak
Bildacı, Yelda Deligöz
Gümrükçü, Gülistan
Canbakan, Mustafa
Öğütmen, Melike Betül
description Purpose Diabetes mellitus (DM) is the leading cause of chronic kidney disease (CKD) in the population. In patients with diabetes mellitus, the incidence of non-diabetic nephropathy (NDNP) has been estimated to range from 3% to 69.5%. Personal judgment is frequently employed while deciding whether or not to do a kidney biopsy (KB) on diabetic patients. NDNP alters the prognosis and course of treatment for people with DM. In our study, we examined the incidence of NDNP concurrent with the progression of diabetes mellitus, as well as the laboratory and clinical indicators that could be utilized to forecast it. Methods A retrospective analysis of 76 diabetic patients who underwent KB was conducted. Based on the pathological diagnoses of these patients, they were categorized as DNP (diabetic nephropathy) or NDNP. The definition of HbA1c variability was determined by calculating the mean HbA1c and the average value of the HbA1c measurements, as well as the standard deviation (SD) for each participant. Results NDNP was detected in 50% of 76 patients. Among patients with NDNP, 36.8% had focal segmental glomerulosclerosis (FSGS), 23.6% had membranous glomerulonephritis, and 7.8% had IgA nephritis. The NDNP group exhibited significantly higher rates of female gender, absence of diabetic retinopathy, shorter time to diagnosis of diabetes mellitus, chronic kidney disease, and proteinuria, less intensive medication for diabetes mellitus, presence of hematuria and leukociduria, immunological serological marker positivity, and non-HbA1C variability. Risk factors for predicting non-diabetic nephropathy, as determined by multivariate analysis, included female gender, the absence of diabetic retinopathy, non-HbA1c variability and a positive immunological serological test. Conclusion In this study, a significant number of diabetic patients with chronic kidney disease were diagnosed with NDNP. Identifying these patients allows for treatment of the specific underlying disease. Factors such as the absence of DR, non-HbA1c variability, female gender, and immunological serological test positivity can predict NDNP and guide the clinician’s decision on kidney biopsy. Further prospective studies are warranted to validate the efficacy of potential predictive factors like HbA1c variability.
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In patients with diabetes mellitus, the incidence of non-diabetic nephropathy (NDNP) has been estimated to range from 3% to 69.5%. Personal judgment is frequently employed while deciding whether or not to do a kidney biopsy (KB) on diabetic patients. NDNP alters the prognosis and course of treatment for people with DM. In our study, we examined the incidence of NDNP concurrent with the progression of diabetes mellitus, as well as the laboratory and clinical indicators that could be utilized to forecast it. Methods A retrospective analysis of 76 diabetic patients who underwent KB was conducted. Based on the pathological diagnoses of these patients, they were categorized as DNP (diabetic nephropathy) or NDNP. The definition of HbA1c variability was determined by calculating the mean HbA1c and the average value of the HbA1c measurements, as well as the standard deviation (SD) for each participant. Results NDNP was detected in 50% of 76 patients. Among patients with NDNP, 36.8% had focal segmental glomerulosclerosis (FSGS), 23.6% had membranous glomerulonephritis, and 7.8% had IgA nephritis. The NDNP group exhibited significantly higher rates of female gender, absence of diabetic retinopathy, shorter time to diagnosis of diabetes mellitus, chronic kidney disease, and proteinuria, less intensive medication for diabetes mellitus, presence of hematuria and leukociduria, immunological serological marker positivity, and non-HbA1C variability. Risk factors for predicting non-diabetic nephropathy, as determined by multivariate analysis, included female gender, the absence of diabetic retinopathy, non-HbA1c variability and a positive immunological serological test. Conclusion In this study, a significant number of diabetic patients with chronic kidney disease were diagnosed with NDNP. Identifying these patients allows for treatment of the specific underlying disease. Factors such as the absence of DR, non-HbA1c variability, female gender, and immunological serological test positivity can predict NDNP and guide the clinician’s decision on kidney biopsy. 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The Author(s), under exclusive licence to Springer Nature B.V.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c326t-70be82f47e3740ed1d8a8d86aad6563110e632031173ad1e64eb08afe8ed3b913</cites><orcidid>0000-0002-6623-9669 ; 0000-0001-9888-995X ; 0000-0002-3479-4801 ; 0000-0003-4054-2069 ; 0000-0002-5704-6160 ; 0000-0001-9110-868X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11255-024-04066-w$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11255-024-04066-w$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38662267$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Demirelli, Bülent</creatorcontrib><creatorcontrib>Boztepe, Burcu</creatorcontrib><creatorcontrib>Şenol, Elif Gülcan</creatorcontrib><creatorcontrib>Boynueğri, Başak</creatorcontrib><creatorcontrib>Bildacı, Yelda Deligöz</creatorcontrib><creatorcontrib>Gümrükçü, Gülistan</creatorcontrib><creatorcontrib>Canbakan, Mustafa</creatorcontrib><creatorcontrib>Öğütmen, Melike Betül</creatorcontrib><title>Non-diabetic nephropathy in diabetic patients: incidence, HbA1c variability and other predictive factors, and implications</title><title>International urology and nephrology</title><addtitle>Int Urol Nephrol</addtitle><addtitle>Int Urol Nephrol</addtitle><description>Purpose Diabetes mellitus (DM) is the leading cause of chronic kidney disease (CKD) in the population. In patients with diabetes mellitus, the incidence of non-diabetic nephropathy (NDNP) has been estimated to range from 3% to 69.5%. Personal judgment is frequently employed while deciding whether or not to do a kidney biopsy (KB) on diabetic patients. NDNP alters the prognosis and course of treatment for people with DM. In our study, we examined the incidence of NDNP concurrent with the progression of diabetes mellitus, as well as the laboratory and clinical indicators that could be utilized to forecast it. Methods A retrospective analysis of 76 diabetic patients who underwent KB was conducted. Based on the pathological diagnoses of these patients, they were categorized as DNP (diabetic nephropathy) or NDNP. The definition of HbA1c variability was determined by calculating the mean HbA1c and the average value of the HbA1c measurements, as well as the standard deviation (SD) for each participant. Results NDNP was detected in 50% of 76 patients. Among patients with NDNP, 36.8% had focal segmental glomerulosclerosis (FSGS), 23.6% had membranous glomerulonephritis, and 7.8% had IgA nephritis. The NDNP group exhibited significantly higher rates of female gender, absence of diabetic retinopathy, shorter time to diagnosis of diabetes mellitus, chronic kidney disease, and proteinuria, less intensive medication for diabetes mellitus, presence of hematuria and leukociduria, immunological serological marker positivity, and non-HbA1C variability. Risk factors for predicting non-diabetic nephropathy, as determined by multivariate analysis, included female gender, the absence of diabetic retinopathy, non-HbA1c variability and a positive immunological serological test. Conclusion In this study, a significant number of diabetic patients with chronic kidney disease were diagnosed with NDNP. Identifying these patients allows for treatment of the specific underlying disease. Factors such as the absence of DR, non-HbA1c variability, female gender, and immunological serological test positivity can predict NDNP and guide the clinician’s decision on kidney biopsy. Further prospective studies are warranted to validate the efficacy of potential predictive factors like HbA1c variability.</description><subject>Adult</subject><subject>Aged</subject><subject>Biopsy</subject><subject>Diabetes</subject><subject>Diabetes mellitus</subject><subject>Diabetic Nephropathies - blood</subject><subject>Diabetic Nephropathies - epidemiology</subject><subject>Diabetic nephropathy</subject><subject>Diabetic retinopathy</subject><subject>Disease Progression</subject><subject>Female</subject><subject>Females</subject><subject>Gender</subject><subject>Glomerulonephritis</subject><subject>Glomerulonephritis, IGA - blood</subject><subject>Glomerulonephritis, IGA - complications</subject><subject>Glomerulonephritis, IGA - epidemiology</subject><subject>Glomerulonephritis, Membranous - blood</subject><subject>Glomerulonephritis, Membranous - complications</subject><subject>Glomerulonephritis, Membranous - epidemiology</subject><subject>Glomerulosclerosis, Focal Segmental - blood</subject><subject>Glomerulosclerosis, Focal Segmental - complications</subject><subject>Glycated Hemoglobin - analysis</subject><subject>Hematuria</subject><subject>Humans</subject><subject>Immunoglobulin A</subject><subject>Immunology</subject><subject>Incidence</subject><subject>Kidney diseases</subject><subject>Male</subject><subject>Medicine</subject><subject>Medicine &amp; Public Health</subject><subject>Membranous glomerulonephritis</subject><subject>Middle Aged</subject><subject>Multivariate analysis</subject><subject>Nephrology</subject><subject>Nephrology – Original Paper</subject><subject>Nephropathy</subject><subject>Patients</subject><subject>Proteinuria</subject><subject>Retinopathy</subject><subject>Retrospective Studies</subject><subject>Risk factors</subject><subject>Serology</subject><subject>Sex Factors</subject><subject>Urology</subject><subject>Variability</subject><issn>1573-2584</issn><issn>0301-1623</issn><issn>1573-2584</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kcFPFTEQxhsjEUT_AQ-miRcOLE7b3W7XGyEqJAQuem667ayvZF-7tn2Q519P4SEaD55m8s1vvpnkI-QdgxMG0H_MjPGua4C3DbQgZXP3ghywrhcN71T78q9-n7zO-QYABgXwiuwLJSXnsj8gv65iaJw3IxZvacBlleJiympLfaDPelU8hpI_VdV6h8HiMT0fT5mltyZVys--bKkJjsaywkSXhM7b4m-RTsaWmPLx49Svl9nb6hZDfkP2JjNnfPtUD8n3L5-_nZ03l9dfL85OLxsruCxNDyMqPrU9ir4FdMwpo5ySxjjZScEYoBQcatML4xjKFkdQZkKFTowDE4fkaOe7pPhzg7notc8W59kEjJusBbSyY3KQD-iHf9CbuEmhflepgbcD66CvFN9RNsWcE056SX5t0lYz0A_J6F0yuiajH5PRd3Xp_ZP1Zlyje175HUUFxA7IdRR-YPpz-z-298HKmm4</recordid><startdate>20240901</startdate><enddate>20240901</enddate><creator>Demirelli, Bülent</creator><creator>Boztepe, Burcu</creator><creator>Şenol, Elif Gülcan</creator><creator>Boynueğri, Başak</creator><creator>Bildacı, Yelda Deligöz</creator><creator>Gümrükçü, Gülistan</creator><creator>Canbakan, Mustafa</creator><creator>Öğütmen, Melike Betül</creator><general>Springer Netherlands</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QP</scope><scope>K9.</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-6623-9669</orcidid><orcidid>https://orcid.org/0000-0001-9888-995X</orcidid><orcidid>https://orcid.org/0000-0002-3479-4801</orcidid><orcidid>https://orcid.org/0000-0003-4054-2069</orcidid><orcidid>https://orcid.org/0000-0002-5704-6160</orcidid><orcidid>https://orcid.org/0000-0001-9110-868X</orcidid></search><sort><creationdate>20240901</creationdate><title>Non-diabetic nephropathy in diabetic patients: incidence, HbA1c variability and other predictive factors, and implications</title><author>Demirelli, Bülent ; Boztepe, Burcu ; Şenol, Elif Gülcan ; Boynueğri, Başak ; Bildacı, Yelda Deligöz ; Gümrükçü, Gülistan ; Canbakan, Mustafa ; Öğütmen, Melike Betül</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c326t-70be82f47e3740ed1d8a8d86aad6563110e632031173ad1e64eb08afe8ed3b913</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Adult</topic><topic>Aged</topic><topic>Biopsy</topic><topic>Diabetes</topic><topic>Diabetes mellitus</topic><topic>Diabetic Nephropathies - blood</topic><topic>Diabetic Nephropathies - epidemiology</topic><topic>Diabetic nephropathy</topic><topic>Diabetic retinopathy</topic><topic>Disease Progression</topic><topic>Female</topic><topic>Females</topic><topic>Gender</topic><topic>Glomerulonephritis</topic><topic>Glomerulonephritis, IGA - blood</topic><topic>Glomerulonephritis, IGA - complications</topic><topic>Glomerulonephritis, IGA - epidemiology</topic><topic>Glomerulonephritis, Membranous - blood</topic><topic>Glomerulonephritis, Membranous - complications</topic><topic>Glomerulonephritis, Membranous - epidemiology</topic><topic>Glomerulosclerosis, Focal Segmental - blood</topic><topic>Glomerulosclerosis, Focal Segmental - complications</topic><topic>Glycated Hemoglobin - analysis</topic><topic>Hematuria</topic><topic>Humans</topic><topic>Immunoglobulin A</topic><topic>Immunology</topic><topic>Incidence</topic><topic>Kidney diseases</topic><topic>Male</topic><topic>Medicine</topic><topic>Medicine &amp; 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In patients with diabetes mellitus, the incidence of non-diabetic nephropathy (NDNP) has been estimated to range from 3% to 69.5%. Personal judgment is frequently employed while deciding whether or not to do a kidney biopsy (KB) on diabetic patients. NDNP alters the prognosis and course of treatment for people with DM. In our study, we examined the incidence of NDNP concurrent with the progression of diabetes mellitus, as well as the laboratory and clinical indicators that could be utilized to forecast it. Methods A retrospective analysis of 76 diabetic patients who underwent KB was conducted. Based on the pathological diagnoses of these patients, they were categorized as DNP (diabetic nephropathy) or NDNP. The definition of HbA1c variability was determined by calculating the mean HbA1c and the average value of the HbA1c measurements, as well as the standard deviation (SD) for each participant. Results NDNP was detected in 50% of 76 patients. Among patients with NDNP, 36.8% had focal segmental glomerulosclerosis (FSGS), 23.6% had membranous glomerulonephritis, and 7.8% had IgA nephritis. The NDNP group exhibited significantly higher rates of female gender, absence of diabetic retinopathy, shorter time to diagnosis of diabetes mellitus, chronic kidney disease, and proteinuria, less intensive medication for diabetes mellitus, presence of hematuria and leukociduria, immunological serological marker positivity, and non-HbA1C variability. Risk factors for predicting non-diabetic nephropathy, as determined by multivariate analysis, included female gender, the absence of diabetic retinopathy, non-HbA1c variability and a positive immunological serological test. Conclusion In this study, a significant number of diabetic patients with chronic kidney disease were diagnosed with NDNP. Identifying these patients allows for treatment of the specific underlying disease. Factors such as the absence of DR, non-HbA1c variability, female gender, and immunological serological test positivity can predict NDNP and guide the clinician’s decision on kidney biopsy. Further prospective studies are warranted to validate the efficacy of potential predictive factors like HbA1c variability.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><pmid>38662267</pmid><doi>10.1007/s11255-024-04066-w</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0002-6623-9669</orcidid><orcidid>https://orcid.org/0000-0001-9888-995X</orcidid><orcidid>https://orcid.org/0000-0002-3479-4801</orcidid><orcidid>https://orcid.org/0000-0003-4054-2069</orcidid><orcidid>https://orcid.org/0000-0002-5704-6160</orcidid><orcidid>https://orcid.org/0000-0001-9110-868X</orcidid></addata></record>
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subjects Adult
Aged
Biopsy
Diabetes
Diabetes mellitus
Diabetic Nephropathies - blood
Diabetic Nephropathies - epidemiology
Diabetic nephropathy
Diabetic retinopathy
Disease Progression
Female
Females
Gender
Glomerulonephritis
Glomerulonephritis, IGA - blood
Glomerulonephritis, IGA - complications
Glomerulonephritis, IGA - epidemiology
Glomerulonephritis, Membranous - blood
Glomerulonephritis, Membranous - complications
Glomerulonephritis, Membranous - epidemiology
Glomerulosclerosis, Focal Segmental - blood
Glomerulosclerosis, Focal Segmental - complications
Glycated Hemoglobin - analysis
Hematuria
Humans
Immunoglobulin A
Immunology
Incidence
Kidney diseases
Male
Medicine
Medicine & Public Health
Membranous glomerulonephritis
Middle Aged
Multivariate analysis
Nephrology
Nephrology – Original Paper
Nephropathy
Patients
Proteinuria
Retinopathy
Retrospective Studies
Risk factors
Serology
Sex Factors
Urology
Variability
title Non-diabetic nephropathy in diabetic patients: incidence, HbA1c variability and other predictive factors, and implications
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