{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T12:07:27Z","timestamp":1777637247813,"version":"3.51.4"},"reference-count":32,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T00:00:00Z","timestamp":1777420800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Neurol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Restless legs syndrome (RLS) is a common and debilitating complication in end-stage renal disease (ESRD) patients undergoing dialysis, significantly impairing sleep quality and quality of life. Screening of prevalent cases remains challenging. This study aimed to develop and validate an interpretable machine learning-based classification model for identifying RLS status in ESRD patients.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      A total of 396 ESRD patients (173 hemodialysis, 223 peritoneal dialysis) were enrolled from April to October 2024. Patients were randomly divided into training (70%,\n                      <jats:italic>n<\/jats:italic>\n                      \u202f=\u202f287) and testing (30%,\n                      <jats:italic>n<\/jats:italic>\n                      \u202f=\u202f109) sets. Feature selection was performed using LASSO regression with five-fold cross-validation, followed by Akaike Information Criterion (AIC) refinement. Nine machine learning algorithms were developed: Logistic Regression (LR), Random Forest (RF), Support Vector Machine (SVM), Gradient Boosting Machine (GBM), K-Nearest Neighbors (KNN), Decision Tree (DT), Artificial Neural Network (ANN), Multivariate Adaptive Regression Splines (MARS), and Quadratic Discriminant Analysis (QDA). Model performance was evaluated using discrimination (AUC-ROC), calibration (Brier score, calibration curves), and clinical utility (Decision Curve Analysis, DCA). SHapley Additive exPlanations (SHAP) was employed to enhance model interpretability.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Five variables were selected: \u03b22-microglobulin, hemoglobin, diabetes mellitus, coronary heart disease, and alcohol consumption. SVM demonstrated optimal performance with AUC of 0.791 (95% CI: 0.702\u20130.879) in the testing set, outperforming other models. SVM achieved accuracy of 0.761, sensitivity of 0.711, specificity of 0.797, F1-score of 0.711, and Brier score of 0.183. Calibration curves showed good agreement between estimated and observed probabilities. DCA confirmed favorable net clinical benefit across threshold probabilities. SHAP analysis identified \u03b22-microglobulin (mean |SHAP|\u202f=\u202f0.131) and anemia as the most influential variables with diabetes, coronary heart disease, and alcohol consumption contributing moderately. SHAP dependence plots revealed interactions between \u03b22-microglobulin and hemoglobin, as well as diabetes modifying the protective effect of higher hemoglobin.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>We developed and validated an interpretable SVM-based classification model for identifying RLS in ESRD patients using readily available clinical variables. This model demonstrates promising performance and requires prospective external validation in multi-center cohorts before clinical implementation. This tool may facilitate screening of prevalent RLS cases and inform clinical decision-making.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fneur.2026.1836086","type":"journal-article","created":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T06:05:09Z","timestamp":1777442709000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Machine learning for identification of restless legs syndrome-associated factors and classification model development in end-stage renal disease patients"],"prefix":"10.3389","volume":"17","author":[{"given":"Tao","family":"Yuan","sequence":"first","affiliation":[{"name":"Department of Nephrology, Tianjin First Central Hospital","place":["Tianjin, China"]},{"name":"Tianjin Medical University","place":["Tianjin, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Na","family":"Sun","sequence":"additional","affiliation":[{"name":"Department of Nephrology, Tianjin First Central Hospital","place":["Tianjin, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lanbo","family":"Teng","sequence":"additional","affiliation":[{"name":"Department of Nephrology, Tianjin First Central Hospital","place":["Tianjin, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chuhan","family":"Xu","sequence":"additional","affiliation":[{"name":"National Clinical Research Center for Chinese Medicine, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine","place":["Tianjin, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunyan","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Nephrology, Tianjin First Central Hospital","place":["Tianjin, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenyu","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Nephrology, Tianjin First Central Hospital","place":["Tianjin, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenxiu","family":"Chang","sequence":"additional","affiliation":[{"name":"Department of Nephrology, Tianjin First Central Hospital","place":["Tianjin, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2026,4,29]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"860","DOI":"10.1016\/j.sleep.2014.03.025","article-title":"Restless legs syndrome\/Willis-Ekbom disease diagnostic criteria: updated international restless legs syndrome study group (IRLSSG) consensus criteria--history, rationale, description, and significance","volume":"15","author":"Allen","year":"2014","journal-title":"Sleep Med"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"1336","DOI":"10.1212\/WNL.0000000000002542","article-title":"Restless legs syndrome associated with major diseases: a systematic review and new concept","volume":"86","author":"Trenkwalder","year":"2016","journal-title":"Neurology"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"1275","DOI":"10.1038\/ki.2013.394","article-title":"Epidemiology, impact, and treatment options of restless legs syndrome in end-stage renal disease patients: an evidence-based review","volume":"85","author":"Giannaki","year":"2014","journal-title":"Kidney Int"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1186\/s12883-019-1265-y","article-title":"Restless legs syndrome in end stage renal disease patients undergoing hemodialysis","volume":"19","author":"Lin","year":"2019","journal-title":"BMC Neurol"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1080\/00207454.2021.1910256","article-title":"Restless leg syndrome in patients with chronic kidney disease: a hospital-based study from upper Egypt","volume":"133","author":"Hamed","year":"2023","journal-title":"Int J Neurosci"},{"key":"ref6","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1017\/S109285291600064X","article-title":"Clinical management of restless legs syndrome in end-stage renal disease patients","volume":"22","author":"Sahli","year":"2017","journal-title":"CNS Spectr"},{"key":"ref7","doi-asserted-by":"publisher","first-page":"1148","DOI":"10.1002\/mds.30125","article-title":"Evidence of involvement of the calcitonin gene-related peptide in restless legs syndrome","volume":"40","author":"Mogavero","year":"2025","journal-title":"Mov Disord"},{"key":"ref8","doi-asserted-by":"publisher","first-page":"295","DOI":"10.1016\/j.sleep.2008.01.002","article-title":"Assessing health-related quality of life in patients with restless legs syndrome","volume":"10","author":"Happe","year":"2009","journal-title":"Sleep Med"},{"key":"ref9","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1093\/aje\/kws016","article-title":"Prospective study of restless legs syndrome and risk of depression in women","volume":"176","author":"Li","year":"2012","journal-title":"Am J Epidemiol"},{"key":"ref10","doi-asserted-by":"publisher","first-page":"287","DOI":"10.1093\/sleep\/33.3.287","article-title":"Evidence continues to mount on the relationship of restless legs syndrome\/ periodic limb movements in sleep to hypertension, cardiovascular disease, and stroke","volume":"33","author":"Walters","year":"2010","journal-title":"Sleep"},{"key":"ref11","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1016\/j.sleep.2017.11.1126","article-title":"International restless legs syndrome study group (IRLSSG). Evidence-based and consensus clinical practice guidelines for the iron treatment of restless legs syndrome\/Willis-Ekbom disease in adults and children: an IRLSSG task force report","volume":"41","author":"Allen","year":"2018","journal-title":"Sleep Med"},{"key":"ref12","doi-asserted-by":"publisher","first-page":"1446","DOI":"10.1111\/ene.13449","article-title":"Gabapentin enacarbil, pregabalin and rotigotine are equally effective in restless legs syndrome: a comparative meta-analysis","volume":"24","author":"Iftikhar","year":"2017","journal-title":"Eur J Neurol"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/s11239-026-03272-w","article-title":"Establishment and validation of a machine learning-based prediction model for sepsis-induced coagulopathy","author":"Li","year":"2026","journal-title":"J Thromb Thrombolysis"},{"key":"ref14","doi-asserted-by":"publisher","first-page":"1734379","DOI":"10.3389\/fonc.2026.1734379","article-title":"Exploring the recurrence and metastasis of breast invasive ductal carcinoma based on machine learning and survival analysis","volume":"16","author":"Xu","year":"2026","journal-title":"Front Oncol"},{"key":"ref15","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1016\/j.jad.2025.04.139","article-title":"Development and validation of a predictive model for depression in patients with advanced stage of cardiovascular-kidney-metabolic syndrome","volume":"383","author":"Zha","year":"2025","journal-title":"J Affect Disord"},{"key":"ref16","doi-asserted-by":"publisher","first-page":"116","DOI":"10.1038\/s41586-019-1390-1","article-title":"A clinically applicable approach to continuous prediction of future acute kidney injury","volume":"572","author":"Toma\u0161ev","year":"2019","journal-title":"Nature"},{"key":"ref17","doi-asserted-by":"publisher","first-page":"71","DOI":"10.1038\/s41581-019-0243-3","article-title":"Artificial intelligence approaches to improve kidney care","volume":"16","author":"Rashidi","year":"2020","journal-title":"Nat Rev Nephrol"},{"key":"ref18","doi-asserted-by":"publisher","first-page":"1381","DOI":"10.1016\/j.sleep.2013.05.022","article-title":"Restless legs syndrome in hemodialysis patients: an epidemiologic survey in Greece","volume":"14","author":"Stefanidis","year":"2013","journal-title":"Sleep Med"},{"key":"ref19","doi-asserted-by":"publisher","first-page":"1025","DOI":"10.1111\/ene.12095","article-title":"Restless legs syndrome in end-stage renal disease: a multicenter study in Taiwan","volume":"20","author":"Lin","year":"2013","journal-title":"Eur J Neurol"},{"key":"ref20","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1038\/s42256-019-0138-9","article-title":"From local explanations to global understanding with explainable AI for trees","volume":"2","author":"Lundberg","year":"2020","journal-title":"Nat Mach Intell"},{"key":"ref21","doi-asserted-by":"publisher","first-page":"e70089","DOI":"10.1002\/bimj.70089","article-title":"Interpretable machine learning for survival analysis","volume":"67","author":"Langbein","year":"2025","journal-title":"Biom J"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.3791\/69440","article-title":"Explainable AI for visual inspection: a comparative analysis and review","volume":"224","author":"Albydhany","year":"2025","journal-title":"J Vis Exp"},{"key":"ref23","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1016\/S1389-9457(02)00258-7","article-title":"International restless legs syndrome study group. Validation of the international restless legs syndrome study group rating scale for restless legs syndrome","volume":"4","author":"Walters","year":"2003","journal-title":"Sleep Med"},{"key":"ref24","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1016\/0165-1781(89)90047-4","article-title":"The Pittsburgh sleep quality index: a new instrument for psychiatric practice and research","volume":"28","author":"Buysse","year":"1989","journal-title":"Psychiatry Res"},{"key":"ref25","doi-asserted-by":"publisher","first-page":"837","DOI":"10.2307\/2531595","article-title":"Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach","volume":"44","author":"DeLong","year":"1988","journal-title":"Biometrics"},{"key":"ref26","doi-asserted-by":"publisher","first-page":"565","DOI":"10.1177\/0272989X06295361","article-title":"Decision curve analysis: a novel method for evaluating prediction models","volume":"26","author":"Vickers","year":"2006","journal-title":"Med Decis Mak"},{"key":"ref27","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1016\/j.neunet.2022.02.007","article-title":"Possibilistic classification by support vector networks","volume":"149","author":"Hao","year":"2022","journal-title":"Neural Netw"},{"key":"ref28","doi-asserted-by":"publisher","first-page":"378","DOI":"10.1111\/j.1525-139X.2009.00584.x","article-title":"Beta2-microglobulin","volume":"22","author":"Dr\u00fceke","year":"2009","journal-title":"Semin Dial"},{"key":"ref29","doi-asserted-by":"publisher","first-page":"2423","DOI":"10.1111\/ene.14840","article-title":"Association between restless legs syndrome and peripheral neuropathy: a systematic review and meta-analysis","volume":"28","author":"Jim\u00e9nez-Jim\u00e9nez","year":"2021","journal-title":"Eur J Neurol"},{"key":"ref30","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1111\/j.1529-8027.2007.00116.x","article-title":"Restless legs syndrome in diabetic neuropathy: a frequent manifestation of small fiber neuropathy","volume":"12","author":"Gemignani","year":"2007","journal-title":"J Peripher Nerv Syst"},{"key":"ref31","doi-asserted-by":"publisher","first-page":"71","DOI":"10.1186\/s12872-017-0502-9","article-title":"High levels of serum \u03b22-microglobulin predict severity of coronary artery disease","volume":"17","author":"You","year":"2017","journal-title":"BMC Cardiovasc Disord"},{"key":"ref32","doi-asserted-by":"publisher","first-page":"1813","DOI":"10.1001\/jama.2025.0452","article-title":"Iron deficiency in adults: a review","volume":"333","author":"Auerbach","year":"2025","journal-title":"JAMA"}],"container-title":["Frontiers in Neurology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fneur.2026.1836086\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T06:05:13Z","timestamp":1777442713000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fneur.2026.1836086\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,29]]},"references-count":32,"alternative-id":["10.3389\/fneur.2026.1836086"],"URL":"https:\/\/doi.org\/10.3389\/fneur.2026.1836086","relation":{},"ISSN":["1664-2295"],"issn-type":[{"value":"1664-2295","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4,29]]},"article-number":"1836086"}}