{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,10]],"date-time":"2026-11-10T01:22:39Z","timestamp":1794273759574,"version":"4.9.0"},"reference-count":36,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T00:00:00Z","timestamp":1784505600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,11,10]],"date-time":"2026-11-10T00:00:00Z","timestamp":1794268800000},"content-version":"vor","delay-in-days":113,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"name":"the Scientific Research Project of National Key Clinical Specialty Construction Project","award":["No. 2022YBL-JB-10"],"award-info":[{"award-number":["No. 2022YBL-JB-10"]}]},{"name":"the Scientific Research Project of National Key Clinical Specialty Construction Project","award":["No. 2022YBL-ZD-04"],"award-info":[{"award-number":["No. 2022YBL-ZD-04"]}]},{"name":"the Hainan Provincial Department of Science and Technology, Hainan Provincial Joint Project for Health Science and Technology Innovation","award":["No. WSJK2024MS148"],"award-info":[{"award-number":["No. WSJK2024MS148"]}],"id":[{"id":"https:\/\/ror.org\/03rbw2w25","id-type":"ROR","asserted-by":"crossref"}]},{"name":"the Natural Science Foundation of Fujian Province","award":["No. 2023J01583"],"award-info":[{"award-number":["No. 2023J01583"]}]},{"name":"the Fujian Province Medical and Health Middle-aged and Young Talents Overseas (Abroad) Study and Further Education Program."}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["npj Digit. Med."],"DOI":"10.1038\/s41746-026-03035-0","type":"journal-article","created":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T03:56:01Z","timestamp":1784519761000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Generating guideline-concordant and safe recommendations for diabetic kidney disease management via a hierarchical retrieval-augmented large language model"],"prefix":"10.1038","volume":"9","author":[{"given":"Xuan","family":"Tao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lan","family":"Tian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chenhao","family":"Fang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jin-hao","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jia-qi","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiao-jie","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin-ying","family":"Song","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zi-hang","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi-nan","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan-hong","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ze-yang","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Min-xia","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wan-xuan","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian-ya","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hong","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,20]]},"reference":[{"key":"3035_CR1","doi-asserted-by":"publisher","first-page":"2532","DOI":"10.1001\/jama.2011.861","volume":"305","author":"IH de Boer","year":"2011","unstructured":"de Boer, I. H. et al. Temporal trends in the prevalence of diabetic kidney disease in the United States. Jama 305, 2532\u20132539 (2011).","journal-title":"Jama"},{"key":"3035_CR2","doi-asserted-by":"publisher","first-page":"110945","DOI":"10.1016\/j.diabres.2023.110945","volume":"204","author":"H Sun","year":"2022","unstructured":"Sun, H. et al. IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045. Diab. Res. Clin. Pract. 204, 110945 (2022).","journal-title":"Diab. Res. Clin. Pract."},{"key":"3035_CR3","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1038\/ki.2014.98","volume":"86","author":"RJ MacIsaac","year":"2014","unstructured":"MacIsaac, R. J., Ekinci, E. I. & Jerums, G. Progressive diabetic nephropathy. How useful is microalbuminuria? Contra\u2019. Kidney Int. 86, 50\u201357 (2014).","journal-title":"Kidney Int."},{"key":"3035_CR4","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1016\/j.jare.2022.04.013","volume":"44","author":"P Houeiss","year":"2023","unstructured":"Houeiss, P. et al. Urinary 20-HETE: A prospective Non-Invasive prognostic and diagnostic marker for diabetic kidney disease. J. Adv. Res. 44, 109\u2013117 (2023).","journal-title":"J. Adv. Res."},{"key":"3035_CR5","doi-asserted-by":"publisher","first-page":"2587","DOI":"10.1007\/s11427-022-2348-0","volume":"66","author":"S Du","year":"2023","unstructured":"Du, S. et al. In-depth urinary and exosome proteome profiling analysis identifies novel biomarkers for diabetic kidney disease. Sci. China Life Sci. 66, 2587\u20132603 (2023).","journal-title":"Sci. China Life Sci."},{"key":"3035_CR6","doi-asserted-by":"crossref","unstructured":"Chronic Kidney Disease and Risk Management: Standards of Care in Diabetes-2025. Diabetes Care 48, S239-s251 (2025).","DOI":"10.2337\/dc25-S011"},{"key":"3035_CR7","doi-asserted-by":"crossref","unstructured":"KDIGO 2022 Clinical Practice Guideline for Diabetes Management in Chronic Kidney Disease. Kidney Int. 102, S1-s127 (2022).","DOI":"10.1016\/j.kint.2022.06.008"},{"key":"3035_CR8","doi-asserted-by":"crossref","unstructured":"KDIGO 2024 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease. Kidney Int. 105, S117-s314 (2024).","DOI":"10.1016\/j.kint.2023.10.018"},{"key":"3035_CR9","doi-asserted-by":"publisher","first-page":"3075","DOI":"10.2337\/dci22-0027","volume":"45","author":"IH de Boer","year":"2022","unstructured":"de Boer, I. H. et al. Diabetes Management in Chronic Kidney Disease: A Consensus Report by the American Diabetes Association (ADA) and Kidney Disease: Improving Global Outcomes (KDIGO). Diab. Care 45, 3075\u20133090 (2022).","journal-title":"Diab. Care"},{"key":"3035_CR10","doi-asserted-by":"crossref","unstructured":"Facilitating positive health behaviors and well-being to improve health outcomes: standards of care in diabetes-2025. Diabetes Care 48, S86-S127 (2025).","DOI":"10.2337\/dc25-S005"},{"key":"3035_CR11","doi-asserted-by":"publisher","first-page":"e48568","DOI":"10.2196\/48568","volume":"25","author":"J Liu","year":"2023","unstructured":"Liu, J., Wang, C. & Liu, S. Utility of ChatGPT in clinical practice. J. Med. Internet Res. 25, e48568 (2023).","journal-title":"J. Med. Internet Res."},{"key":"3035_CR12","doi-asserted-by":"publisher","first-page":"1941","DOI":"10.1097\/JS9.0000000000001066","volume":"110","author":"L Deng","year":"2024","unstructured":"Deng, L. et al. Evaluation of large language models in breast cancer clinical scenarios: a comparative analysis based on ChatGPT-3.5, ChatGPT-4.0, and Claude2. Int. J. Surg. 110, 1941\u20131950 (2024).","journal-title":"Int. J. Surg."},{"key":"3035_CR13","doi-asserted-by":"publisher","first-page":"451","DOI":"10.1038\/s41586-025-08869-4","volume":"642","author":"D McDuff","year":"2025","unstructured":"McDuff, D. et al. Towards accurate differential diagnosis with large language models. Nature 642, 451\u2013457 (2025).","journal-title":"Nature"},{"key":"3035_CR14","doi-asserted-by":"crossref","unstructured":"Miao, J., Thongprayoon, C., Suppadungsuk, S., Garcia Valencia, O. A. & Cheungpasitporn, W. Integrating retrieval-augmented generation with large language models in nephrology: advancing practical applications. Medicina 60, 445 (2024).","DOI":"10.3390\/medicina60030445"},{"key":"3035_CR15","doi-asserted-by":"publisher","first-page":"1119","DOI":"10.1007\/s10439-023-03329-4","volume":"52","author":"J Ferdush","year":"2024","unstructured":"Ferdush, J., Begum, M. & Hossain, S. T. ChatGPT and clinical decision support: scope, application, and limitations. Ann. Biomed. Eng. 52, 1119\u20131124 (2024).","journal-title":"Ann. Biomed. Eng."},{"key":"3035_CR16","unstructured":"Gan, A. et al. Retrieval augmented generation evaluation in the era of large language models: a comprehensive survey. arXiv [cs.CL] (2025)."},{"key":"3035_CR17","doi-asserted-by":"crossref","unstructured":"Fan, W. et al. A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models. arXiv:2405.06211 [cs.CL] (2025).","DOI":"10.1145\/3637528.3671470"},{"key":"3035_CR18","doi-asserted-by":"crossref","unstructured":"Guti\u00e9rrez, B. J., Shu, Y., Gu, Y., Yasunaga, M., & Su, Y. HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models. arXiv:2405.14831 [cs.CL] (2024).","DOI":"10.52202\/079017-1902"},{"key":"3035_CR19","doi-asserted-by":"crossref","unstructured":"Ge, J. et al. Development of a liver disease-specific large language model chat interface using retrieval-augmented generation. Hepatology 80, 1158\u20131168 (2024).","DOI":"10.1097\/HEP.0000000000000834"},{"key":"3035_CR20","doi-asserted-by":"publisher","first-page":"e78625","DOI":"10.2196\/78625","volume":"27","author":"V Parameswaran","year":"2025","unstructured":"Parameswaran, V. et al. Evaluating large language models and retrieval-augmented generation enhancement for delivering guideline-adherent nutrition information for cardiovascular disease prevention: cross-sectional study. J. Med. Internet Res. 27, e78625 (2025).","journal-title":"J. Med. Internet Res."},{"key":"3035_CR21","first-page":"273","volume":"8","author":"IP Nweke","year":"2025","unstructured":"Nweke, I. P., Ogadah, C. O., Koshechkin, K. & Oluwasegun, P. M. Multi-agent AI systems in healthcare: a systematic review enhancing clinical decision-making. Asian J. Med. Princ. Clin. Pract. 8, 273\u2013285 (2025).","journal-title":"Asian J. Med. Princ. Clin. Pract."},{"key":"3035_CR22","doi-asserted-by":"publisher","unstructured":"Zakka, C. et al. Almanac \u2014 Retrieval-Augmented Language Models for Clinical Medicine. NEJM AI 1. https:\/\/doi.org\/10.1056\/aioa2300068 (2024).","DOI":"10.1056\/aioa2300068"},{"key":"3035_CR23","doi-asserted-by":"publisher","first-page":"687","DOI":"10.3390\/bioengineering12070687","volume":"12","author":"B Pingua","year":"2025","unstructured":"Pingua, B. et al. Medical LLMs: Fine-Tuning vs. Retrieval-Augmented Generation. Bioengineering 12, 687 (2025).","journal-title":"Bioengineering"},{"key":"3035_CR24","unstructured":"Wang, X. et al. Self-Consistency Improves Chain of Thought Reasoning in Language Models. arXiv:2203.11171 [cs.CL] (2023)."},{"key":"3035_CR25","unstructured":"Xia, Y. et al. Reimagining Urban Science: Scaling Causal Inference with Large Language Models. arXiv:2504.12345 [cs.CL] (2025)."},{"key":"3035_CR26","doi-asserted-by":"publisher","first-page":"1930","DOI":"10.1038\/s41591-023-02448-8","volume":"29","author":"AJ Thirunavukarasu","year":"2023","unstructured":"Thirunavukarasu, A. J. et al. Large language models in medicine. Nat. Med. 29, 1930\u20131940 (2023).","journal-title":"Nat. Med."},{"key":"3035_CR27","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1038\/s41591-018-0300-7","volume":"25","author":"EJ Topol","year":"2019","unstructured":"Topol, E. J. High-performance medicine: the convergence of human and artificial intelligence. Nat. Med. 25, 44\u201356 (2019).","journal-title":"Nat. Med."},{"key":"3035_CR28","doi-asserted-by":"publisher","first-page":"259","DOI":"10.1038\/s41586-023-05881-4","volume":"616","author":"M Moor","year":"2023","unstructured":"Moor, M. et al. Foundation models for generalist medical artificial intelligence. Nature 616, 259\u2013265 (2023).","journal-title":"Nature"},{"key":"3035_CR29","unstructured":"Xi, Z. et al. The Rise and Potential of Large Language Model Based Agents: A Survey. arXiv:2309.07864 [cs.AI] (2023)."},{"key":"3035_CR30","unstructured":"DeepSeek-AI. et al. DeepSeek-V3 Technical Report. arXiv:2412.19437 [cs.CL] (2024)."},{"key":"3035_CR31","unstructured":"Nori, H., King, N., McKinney, S. M., Carignan, D., & Horvitz, E. Capabilities of GPT-4 on Medical Challenge Problems. arXiv:2303.13375 [cs.CL] (2023)."},{"key":"3035_CR32","unstructured":"Lewis, P. et al. Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks. arXiv:2005.11401 [cs.CL] (2020)."},{"key":"3035_CR33","doi-asserted-by":"crossref","unstructured":"Wei, J. et al. Chain of Thought Prompting Elicits Reasoning in Large Language Models. arXiv:2201.11903 [cs.CL] (2022).","DOI":"10.52202\/068431-1800"},{"key":"3035_CR34","doi-asserted-by":"publisher","first-page":"684","DOI":"10.1016\/j.kint.2023.10.016","volume":"105","author":"A Levin","year":"2024","unstructured":"Levin, A. et al. Executive summary of the KDIGO 2024 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease: known knowns and known unknowns. Kidney Int. 105, 684\u2013701 (2024).","journal-title":"Kidney Int."},{"key":"3035_CR35","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1038\/s41586-023-06291-2","volume":"620","author":"K Singhal","year":"2023","unstructured":"Singhal, K. et al. Large language models encode clinical knowledge. Nature 620, 172\u2013180 (2023).","journal-title":"Nature"},{"key":"3035_CR36","doi-asserted-by":"crossref","unstructured":"Chen, J., Lin, H., Han, X. & Sun, L. Benchmarking Large Language Models in Retrieval-Augmented Generation. in Proceedings of the AAAI Conference on Artificial Intelligence, (2023). arXiv:2309.01431 [cs.CL].","DOI":"10.1609\/aaai.v38i16.29728"}],"container-title":["npj Digital Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41746-026-03035-0","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41746-026-03035-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41746-026-03035-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,11,10]],"date-time":"2026-11-10T00:32:35Z","timestamp":1794270755000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41746-026-03035-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,20]]},"references-count":36,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["3035"],"URL":"https:\/\/doi.org\/10.1038\/s41746-026-03035-0","relation":{},"ISSN":["2398-6352"],"issn-type":[{"value":"2398-6352","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,20]]},"assertion":[{"value":"9 February 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 July 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 July 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Ethics"}}],"article-number":"877"}}