<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>16</volume><submitter>Deng Z</submitter><pubmed_abstract>&lt;h4>Introduction&lt;/h4>This study aimed to identify independent risk factors for DKD in T2DM patients and develop a risk prediction model with internal validation.&lt;h4>Methods&lt;/h4>We retrospectively collected data from 1,049 T2DM patients undergoing community health checks in Longhua District (2024). Patients were divided into DKD and non-DKD groups, then randomly divided into training (n=735) and validation (n=314) sets in 7:3 ratio.&lt;h4>Results&lt;/h4>The results of the binary logistic regression analysis showed that the duration of diabetes (OR 1.037, 95% CI: 1.005-1.07, P = 0.024), BMI (OR 0.869, 95% CI: 0.762-0.992, P = 0.037), Scr (OR 1.019, 95% CI: 1.010-1.028, P = 0.000), WBC (OR 1.141, 95% CI: 1.019-1.279, P = 0.023), and TyG-BMI (OR 1.019, 95% CI: 1.1007-1.030, P = 0.002) were independe</pubmed_abstract><journal>Frontiers in endocrinology</journal><pagination>1708419</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12834776</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Development and validation of a model that predicts the risk of diabetic kidney disease in type 2 diabetes mellitus patients: a retrospective study.</pubmed_title><pmcid>PMC12834776</pmcid><pubmed_authors>Yang J</pubmed_authors><pubmed_authors>Deng Z</pubmed_authors><pubmed_authors>Zhou H</pubmed_authors></additional><is_claimable>false</is_claimable><name>Development and validation of a model that predicts the risk of diabetic kidney disease in type 2 diabetes mellitus patients: a retrospective study.</name><description>&lt;h4>Introduction&lt;/h4>This study aimed to identify independent risk factors for DKD in T2DM patients and develop a risk prediction model with internal validation.&lt;h4>Methods&lt;/h4>We retrospectively collected data from 1,049 T2DM patients undergoing community health checks in Longhua District (2024). Patients were divided into DKD and non-DKD groups, then randomly divided into training (n=735) and validation (n=314) sets in 7:3 ratio.&lt;h4>Results&lt;/h4>The results of the binary logistic regression analysis showed that the duration of diabetes (OR 1.037, 95% CI: 1.005-1.07, P = 0.024), BMI (OR 0.869, 95% CI: 0.762-0.992, P = 0.037), Scr (OR 1.019, 95% CI: 1.010-1.028, P = 0.000), WBC (OR 1.141, 95% CI: 1.019-1.279, P = 0.023), and TyG-BMI (OR 1.019, 95% CI: 1.1007-1.030, P = 0.002) were independe</description><dates><release>2025-01-01T00:00:00Z</release><publication>2025</publication><modification>2026-06-13T05:26:07.243Z</modification><creation>2026-06-13T03:08:58.162Z</creation></dates><accession>S-EPMC12834776</accession><cross_references><pubmed>41607464</pubmed><doi>10.3389/fendo.2025.1708419</doi></cross_references></HashMap>