{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,21]],"date-time":"2026-07-21T20:22:01Z","timestamp":1784665321099,"version":"3.55.0"},"reference-count":42,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T00:00:00Z","timestamp":1770854400000},"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. Endocrinol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>This study aimed to develop and evaluate a nomogram model based on Traditional Chinese Medicine (TCM) pulse mapping parameters to predict the risk of diabetic foot (DF) in patients with type 2 diabetes mellitus (T2DM).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      A retrospective analysis was performed on clinical data and pulse mapping parameters from 485 T2DM patients hospitalized in the Departments of Vascular Diseases and Endocrinology at Shanghai TCM-Integrated Hospital between July 26, 2023, and April 9, 2025. Patients were divided into a DF group (\n                      <jats:italic>n<\/jats:italic>\n                      = 242) and a T2DM-only group (\n                      <jats:italic>n<\/jats:italic>\n                      = 243) according to the presence of DF. Pulse mapping parameters and clinical indicators were compared between the two groups. Least Absolute Shrinkage and Selection Operator (LASSO) regression and multivariate logistic regression analyses were conducted to identify risk factors associated with DF development in T2DM. The risk prediction nomogram was constructed using R Studio. Model performance was evaluated using the Receiver Operating Characteristic (ROC) curve and its Area Under the Curve (AUC). Accuracy, Precision, Recall, and F1-score were calculated. Calibration curves were plotted to assess the agreement between predicted probabilities and actual outcomes, and decision curve analysis (DCA) was used to evaluate the model\u2019s clinical utility.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Gender (OR = 0.501,\n                      <jats:italic>p<\/jats:italic>\n                      = 0.002), BMI (OR = 0.919,\n                      <jats:italic>p<\/jats:italic>\n                      = 0.003), hypertension (OR = 2.482,\n                      <jats:italic>p<\/jats:italic>\n                      &amp;lt; 0.001), systolic blood pressure (OR = 0.972,\n                      <jats:italic>p<\/jats:italic>\n                      &amp;lt; 0.001), blood urea nitrogen (BUN) (OR = 1.099,\n                      <jats:italic>p<\/jats:italic>\n                      = 0.011), and the pulse mapping parameter H5\/H1 (OR = 0.002,\n                      <jats:italic>p<\/jats:italic>\n                      &amp;lt; 0.001) were identified as independent risk factors for DF in T2DM. The nomogram model based on these factors achieved an AUC of 0.786 (95% CI: 0.694\u20130.877) in the test set, with an Accuracy of 0.7113, Precision of 0.6481, Recall of 0.7955, and F1-score of 0.7143. The Hosmer\u2013Lemeshow test demonstrated good calibration (\u03c7\u00b2 = 6.1672,\n                      <jats:italic>p<\/jats:italic>\n                      = 0.6285), showing close agreement between predicted and observed outcomes. The DCA confirmed favorable clinical applicability.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>This nomogram model provides an individualized and visualized tool for predicting DF risk in T2DM patients, offering TCM-based reference indicators for early DF risk assessment.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fendo.2026.1758234","type":"journal-article","created":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T05:27:12Z","timestamp":1770874032000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Development and validation of a nomogram model integrating noninvasive detection of radial pulse wave for predicting diabetic foot risk in type 2 diabetes 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China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cheng","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Vascular Disease, Shanghai Traditional Chinese Medicine (TCM)- Integrated Hospital, Shanghai University of Traditional Chinese Medicine (TCM)","place":["Shanghai, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haixia","family":"Yan","sequence":"additional","affiliation":[{"name":"School of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine (TCM)","place":["Shanghai, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,2,12]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"107843","DOI":"10.1016\/j.diabres.2019.107843","article-title":"Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes 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