PMID- 35346252 OWN - NLM STAT- MEDLINE DCOM- 20220405 LR - 20220518 IS - 1479-5876 (Electronic) IS - 1479-5876 (Linking) VI - 20 IP - 1 DP - 2022 Mar 26 TI - Prediction of 3-year risk of diabetic kidney disease using machine learning based on electronic medical records. PG - 143 LID - 10.1186/s12967-022-03339-1 [doi] LID - 143 AB - BACKGROUND: Established prediction models of Diabetic kidney disease (DKD) are limited to the analysis of clinical research data or general population data and do not consider hospital visits. Construct a 3-year diabetic kidney disease risk prediction model in patients with type 2 diabetes mellitus (T2DM) using machine learning, based on electronic medical records (EMR). METHODS: Data from 816 patients (585 males) with T2DM and 3 years of follow-up at the PLA General Hospital. 46 medical characteristics that are readily available from EMR were used to develop prediction models based on seven machine learning algorithms (light gradient boosting machine [LightGBM], eXtreme gradient boosting, adaptive boosting, artificial neural network, decision tree, support vector machine, logistic regression). Model performance was evaluated using the area under the receiver operating characteristic curve (AUC). Shapley additive explanation (SHAP) was used to interpret the results of the best performing model. RESULTS: The LightGBM model had the highest AUC (0.815, 95% CI 0.747-0.882). Recursive feature elimination with random forest and SHAP plot based on LightGBM showed that older patients with T2DM with high homocysteine (Hcy), poor glycemic control, low serum albumin (ALB), low estimated glomerular filtration rate (eGFR), and high bicarbonate had an increased risk of developing DKD over the next 3 years. CONCLUSIONS: This study constructed a 3-year DKD risk prediction model in patients with T2DM and normo-albuminuria using machine learning and EMR. The LightGBM model is a tool with potential to facilitate population management strategies for T2DM care in the EMR era. CI - (c) 2022. The Author(s). FAU - Dong, Zheyi AU - Dong Z AD - Department of Nephrology, First Medical Center of Chinese, PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, No. 28 Fuxing Road, Beijing, 100853, China. FAU - Wang, Qian AU - Wang Q AD - Department of Nephrology, First Medical Center of Chinese, PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, No. 28 Fuxing Road, Beijing, 100853, China. FAU - Ke, Yujing AU - Ke Y AD - Department of Nephrology, First Medical Center of Chinese, PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, No. 28 Fuxing Road, Beijing, 100853, China. FAU - Zhang, Weiguang AU - Zhang W AD - Department of Nephrology, First Medical Center of Chinese, PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, No. 28 Fuxing Road, Beijing, 100853, China. FAU - Hong, Quan AU - Hong Q AD - Department of Nephrology, First Medical Center of Chinese, PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, No. 28 Fuxing Road, Beijing, 100853, China. FAU - Liu, Chao AU - Liu C AD - Department of Nephrology, First Medical Center of Chinese, PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, No. 28 Fuxing Road, Beijing, 100853, China. FAU - Liu, Xiaomin AU - Liu X AD - Department of Nephrology, First Medical Center of Chinese, PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, No. 28 Fuxing Road, Beijing, 100853, China. FAU - Yang, Jian AU - Yang J AD - Department of Nephrology, First Medical Center of Chinese, PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, No. 28 Fuxing Road, Beijing, 100853, China. FAU - Xi, Yue AU - Xi Y AD - Department of Nephrology, First Medical Center of Chinese, PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, No. 28 Fuxing Road, Beijing, 100853, China. FAU - Shi, Jinlong AU - Shi J AD - Medical Big Data Research Center, Medical Innovation Research Division of Chinese People's Liberation, Army General Hospital, National Engineering Laboratory for Medical Big Data Application Technology, No. 28 Fuxing Road, Beijing, 100853, China. FAU - Zhang, Li AU - Zhang L AD - Department of Nephrology, First Medical Center of Chinese, PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, No. 28 Fuxing Road, Beijing, 100853, China. FAU - Zheng, Ying AU - Zheng Y AD - Department of Nephrology, First Medical Center of Chinese, PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, No. 28 Fuxing Road, Beijing, 100853, China. FAU - Lv, Qiang AU - Lv Q AD - Department of Nephrology, First Medical Center of Chinese, PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, No. 28 Fuxing Road, Beijing, 100853, China. FAU - Wang, Yong AU - Wang Y AD - Department of Nephrology, First Medical Center of Chinese, PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, No. 28 Fuxing Road, Beijing, 100853, China. FAU - Wu, Jie AU - Wu J AD - Department of Nephrology, First Medical Center of Chinese, PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, No. 28 Fuxing Road, Beijing, 100853, China. FAU - Sun, Xuefeng AU - Sun X AD - Department of Nephrology, First Medical Center of Chinese, PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, No. 28 Fuxing Road, Beijing, 100853, China. FAU - Cai, Guangyan AU - Cai G AD - Department of Nephrology, First Medical Center of Chinese, PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, No. 28 Fuxing Road, Beijing, 100853, China. FAU - Qiao, Shen AU - Qiao S AD - Medical Big Data Research Center, Medical Innovation Research Division of Chinese People's Liberation, Army General Hospital, National Engineering Laboratory for Medical Big Data Application Technology, No. 28 Fuxing Road, Beijing, 100853, China. FAU - Yin, Chengliang AU - Yin C AD - Medical Big Data Research Center, Medical Innovation Research Division of Chinese People's Liberation, Army General Hospital, National Engineering Laboratory for Medical Big Data Application Technology, No. 28 Fuxing Road, Beijing, 100853, China. FAU - Su, Shibin AU - Su S AD - Medical Big Data Research Center, Medical Innovation Research Division of Chinese People's Liberation, Army General Hospital, National Engineering Laboratory for Medical Big Data Application Technology, No. 28 Fuxing Road, Beijing, 100853, China. suarthas@163.com. FAU - Chen, Xiangmei AU - Chen X AD - Department of Nephrology, First Medical Center of Chinese, PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, No. 28 Fuxing Road, Beijing, 100853, China. xmchen301@126.com. LA - eng PT - Journal Article PT - Research Support, Non-U.S. Gov't DEP - 20220326 PL - England TA - J Transl Med JT - Journal of translational medicine JID - 101190741 SB - IM MH - *Diabetes Mellitus, Type 2/complications/epidemiology MH - *Diabetic Nephropathies/epidemiology MH - Electronic Health Records MH - Humans MH - Logistic Models MH - Machine Learning MH - Male PMC - PMC8959559 OTO - NOTNLM OT - Diabetic kidney disease OT - Electronic medical records OT - Light gradient boosting machine OT - Machine learning OT - Risk assessment OT - Type 2 diabetes COIS- The authors declare that they have no competing interests. EDAT- 2022/03/30 06:00 MHDA- 2022/04/05 06:00 PMCR- 2022/03/26 CRDT- 2022/03/29 05:39 PHST- 2021/11/02 00:00 [received] PHST- 2022/03/06 00:00 [accepted] PHST- 2022/03/29 05:39 [entrez] PHST- 2022/03/30 06:00 [pubmed] PHST- 2022/04/05 06:00 [medline] PHST- 2022/03/26 00:00 [pmc-release] AID - 10.1186/s12967-022-03339-1 [pii] AID - 3339 [pii] AID - 10.1186/s12967-022-03339-1 [doi] PST - epublish SO - J Transl Med. 2022 Mar 26;20(1):143. doi: 10.1186/s12967-022-03339-1.