Diabetic foot care: full-lifecycle management driven by digital intelligent technologies_Chinese Journal of Reparative and Reconstructive Surgery

Authors：

CHEN Lihong ^1,2 ,  RAN Xingwu ^1,2

1. Department of Endocrinology and Metabolism, West China Hospital, Sichuan University, Chengdu Sichuan, 610041, P. R. China;
2. Innovation Research Center for Diabetic Foot, Diabetic Foot Care Center, West China Hospital, Sichuan University, Chengdu Sichuan, 610041, P. R. China;

Corresponding?author：

RAN Xingwu, Email: ranxingwu@163.com

Keywords：

Diabetic foot; diabetes-related foot disease; artificial intelligence; regenerative medicine; full-lifecycle management

DOI：

10.7507/1002-1892.202603041

Video：

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Objective To conduct a comprehensive review of the latest diagnostic and therapeutic advancements in early warning, regenerative medicine, and digital management for the diabetic foot (DF). Methods Through a systematic review of recent global literature, the paradigm shifts in diabetic foot definitions, artificial intelligence (AI)-driven clinical applications, regenerative strategies, and full-lifecycle management models were evaluated. Results The emergence of “diabetes-related foot disease” and the “remission” status has refocused the clinical attention on proactive prevention. AI has demonstrated high objectivity and consistency in risk stratification, early warning, automated wound quantification, and decision support. Meanwhile, regenerative therapies, particularly mRNA-based treatments and bio-active scaffolds, have emerged as a premier research frontier and a pivotal breakthrough in the repair of refractory wounds. The implementation of full-lifecycle management has effectively achieved a closed-loop continuum of care, spanning from early intervention to clinical remission. Conclusion The field of diabetic foot care is evolving into a new era characterized by the integration of digital intelligence and precision regeneration. Future initiatives should focus on the multidisciplinary-led clinical translation and standardization of emerging technologies to establish a comprehensive, precision management framework aimed at achieving “long-term remission”.

Citation： CHEN Lihong, RAN Xingwu. Diabetic foot care: full-lifecycle management driven by digital intelligent technologies. Chinese Journal of Reparative and Reconstructive Surgery, 2026, 40(6): 893-898. doi: 10.7507/1002-1892.202603041 Copy

1.	Armstrong DG, Swerdlow MA, Armstrong AA, et al. Five year mortality and direct costs of care for people with diabetic foot complications are comparable to cancer. J Foot Ankle Res, 2020, 13(1): 16. doi: 10.1186/s13047-020-00383-2.
2.	van Netten JJ, Bus SA, Apelqvist J, et al. Definitions and criteria for diabetes-related foot disease (IWGDF 2023 update). Diabetes Metab Res Rev, 2024, 40(3): e3654. doi: 10.1002/dmrr.3654.
3.	Xu J, Deng W, Xu Z, et al. Chinese experts’ perspectives on the definition of change from “diabetic foot” to “diabetes-related foot disease”. Chin Med J (Engl), 2025, 138(22): 3004-3006.
4.	Ganesan O, Morris MX, Guo L, et al. A review of artificial intelligence in wound care. Artif Intell Surg. 2024, 4(4): 364-375.
5.	王光婭, 王玉, 孟宇辰, 等. 人工智能在糖尿病足中應用的研究進展. 中華現代護理雜志, 2024, 30(5): 691-695.
6.	Nanda R, Nath A, Patel S, et al. Machine learning algorithm to evaluate risk factors of diabetic foot ulcers and its severity. Med Biol Eng Comput, 2022, 60(8): 2349-2357.
7.	Heck I, Lu W, Wang Z, et al. Soft, wireless pressure-sensor-integrated smart bandage for the management of diabetic foot ulcers. Adv Mater Technol, 2023, 8(3): 2200821. doi: 10.1002/admt.202200821.
8.	Jiménez DR, Casanova-lozano L, Grau-carrión S, et al. Artificial intelligence methods for diagnostic and decision-making assistance in chronic wounds: a systematic review. J Med Syst, 2025, 49(1): 29. doi: 10.1007/s10916-025-02153-8.
9.	Anisuzzaman DM, Patel Y, Niezgoda JA, et al. A mobile App for wound localization using deep learning. IEEE Access, 2022, 10: 61398-61409.
10.	Goyal M, Reeves ND, Rajbhandari S, et al. Robust methods for real-time diabetic foot ulcer detection and localization on mobile devices. IEEE J Biomed Health Inform, 2019, 23(4): 1730-1741.
11.	Ramachandram D, Ramirez-GarciaLuna JL, Fraser RDJ, et al. Fully automated wound tissue segmentation using deep learning on mobile devices: cohort study. JMIR Mhealth Uhealth, 2022, 10(4): e36977. doi: 10.2196/36977.
12.	Goyal M, Reeves ND, Davison AK, et al. DFUNet: Convolutional neural networks for diabetic foot ulcer classification. IEEE TETCI, 2020, 4(5): 728-739.
13.	Dhillon MS, Alappatt K, Nayar PS, et al. Artificial intelligence in the foot and ankle: the applications in 2025. J Foot Ankle Surg (Asia-Pacific), 2025, 12(4): 171-175.
14.	趙楠, 金莉萍, 方金贏, 等. 基于醫聯體的糖尿病足智能診療平臺的構建與實踐. 中華糖尿病雜志, 2021, 13(9): 901-905.
15.	Basiri R. Applications of generative AI in diabetic foot ulcer treatment//Raghav A. Diabetic foot-Advanced methods of management. London: IntechOpen, 2025.
16.	Malik AH, Rahman S. Toward precision wound healing: Integrating regenerative therapies and smart technologies. Int J Sci Res Arch, 2025, 16(3): 244-257.
17.	Metwaly A, Ismail S, Nagy YM, et al. Limb salvage: A review of stem cell and growth factor therapies for diabetic foot ulcers. Diabetes Res Clin Pract, 2026, 231: 113036. doi: 10.1016/j.diabres.2025.113036.
18.	Zhu Y, Bao S, Yin X, et al. Advancements in diabetic foot ulcer therapy: The role of exosomes and decellularised extracellular matrix scaffolds. Diabetes Res Clin Pract, 2025, 226: 112364. doi: 10.1016/j.diabres.2025.112364.
19.	Chen T, Ouyang L, Mi B, et al. MicroRNA-493-5p engineered exosomes delivered via piezoelectric microneedles for epigenetic modulation of macrophages in diabetic wound healing. Mater Today Bio, 2026, 37: 102931. doi: 10.1016/j.mtbio.2026.102931.
20.	?ak MM, Zangi L. Clinical development of therapeutic mRNA applications. Mol Ther, 2025, 33(6): 2583-2609.
21.	Guo K. Lipid nanoparticle-based mRNA therapy for diabetic wound healing: scavenging ROS and modulating inflammation. New York: Icahn School of Medicine at Mount Sinai, 2025.
22.	Wang J, Wang Y, Lu M, et al. Biomimetic triplet messenger RNA formulation in MXene hydrogel microneedles for wound healing. Aggregate, 2025, 6(2): e700. doi: 10.1002/agt2.700. doi: 10.1002/agt2.700.
23.	Zhang M, Pan X, Li J, et al. mRNA-based therapeutics in skin regeneration and rejuvenation: From optimization strategies to translational advances. Chinese Chem Lett, 2026. doi: 10.1016/j.cclet.2026.112358.
24.	Moldovan CA, Salagean AA, Slevin M. Multiplexing 3D natural scaffolds to optimize the repair and regeneration of chronic diabetic wounds. Gels, 2025, 11(6): 430. doi: 10.3390/gels11060430.
25.	Dhankhar S, Garg N, Chauhan S, et al. Harnessing bioprinting technologies for diabetic wound regeneration. Curr Pharm Biotechnol, 2025, 26(10): 1482-1498.
26.	Liao HJ, Liao TC, Wu YF. Integrating regenerative therapies and artificial intelligence for precision management of diabetic foot ulcers. Adv Wound Care (New Rochelle), 2026. doi: 10.1177/21621918261422388.
27.	Akhavan-Kharazian N, Izadi-Vasafi H, Tabashiri-Isfahani M, et al. A review on smart dressings with advanced features. Wound Repair Regen, 2025, 33(3): e70014. doi: 10.1111/wrr.70014.
28.	Yuan XM, Kong WC, Shao YJ, et al. AI-feedback bioelectronics promote infectious wound healing. Cell Biomater, 2026, 2(2): 100191. doi: 10.1016/j.celbio.2025.100191.
29.	Thanha KPK, Sana PA, Ajesh JS, et al. Advanced smart bioelectronics for wound healing: biosensing, drug delivery, and artificial intelligence. Int J Pharm, 2025, 684: 126098. doi: 10.1016/j.ijpharm.2025.126098.
30.	Armstrong DG, Boulton AJM, Bus SA. Diabetic foot ulcers and their recurrence. N Engl J Med, 2017, 376(24): 2367-2375.
31.	Petersen BJ, Rothenberg GM, Lakhani PJ, et al. Ulcer metastasis? Anatomical locations of recurrence for patients in diabetic foot remission. J Foot Ankle Res, 2020, 13: 1. doi: 10.1186/s13047-020-0369-3.
32.	Donaldson G, Hendry G, Barn R. Exploring patient and podiatrist perspectives of the ‘in-remission’ status in diabetes-related foot disease. J Foot Ankle Res, 2025, 18(2): e70045. doi: 10.1002/jfa2.70045.
33.	Shakir K, Sarlak H, Bus SA, et al. Advancing diabetic foot ulcer care: focus on the post-healing transition phase. J Diabetes, 2025, 17(12): e70173. doi: 10.1111/1753-0407.70173.

1. Armstrong DG, Swerdlow MA, Armstrong AA, et al. Five year mortality and direct costs of care for people with diabetic foot complications are comparable to cancer. J Foot Ankle Res, 2020, 13(1): 16. doi: 10.1186/s13047-020-00383-2.
2. van Netten JJ, Bus SA, Apelqvist J, et al. Definitions and criteria for diabetes-related foot disease (IWGDF 2023 update). Diabetes Metab Res Rev, 2024, 40(3): e3654. doi: 10.1002/dmrr.3654.
3. Xu J, Deng W, Xu Z, et al. Chinese experts’ perspectives on the definition of change from “diabetic foot” to “diabetes-related foot disease”. Chin Med J (Engl), 2025, 138(22): 3004-3006.
4. Ganesan O, Morris MX, Guo L, et al. A review of artificial intelligence in wound care. Artif Intell Surg. 2024, 4(4): 364-375.
5. 王光婭, 王玉, 孟宇辰, 等. 人工智能在糖尿病足中應用的研究進展. 中華現代護理雜志, 2024, 30(5): 691-695.
6. Nanda R, Nath A, Patel S, et al. Machine learning algorithm to evaluate risk factors of diabetic foot ulcers and its severity. Med Biol Eng Comput, 2022, 60(8): 2349-2357.
7. Heck I, Lu W, Wang Z, et al. Soft, wireless pressure-sensor-integrated smart bandage for the management of diabetic foot ulcers. Adv Mater Technol, 2023, 8(3): 2200821. doi: 10.1002/admt.202200821.
8. Jiménez DR, Casanova-lozano L, Grau-carrión S, et al. Artificial intelligence methods for diagnostic and decision-making assistance in chronic wounds: a systematic review. J Med Syst, 2025, 49(1): 29. doi: 10.1007/s10916-025-02153-8.
9. Anisuzzaman DM, Patel Y, Niezgoda JA, et al. A mobile App for wound localization using deep learning. IEEE Access, 2022, 10: 61398-61409.
10. Goyal M, Reeves ND, Rajbhandari S, et al. Robust methods for real-time diabetic foot ulcer detection and localization on mobile devices. IEEE J Biomed Health Inform, 2019, 23(4): 1730-1741.
11. Ramachandram D, Ramirez-GarciaLuna JL, Fraser RDJ, et al. Fully automated wound tissue segmentation using deep learning on mobile devices: cohort study. JMIR Mhealth Uhealth, 2022, 10(4): e36977. doi: 10.2196/36977.
12. Goyal M, Reeves ND, Davison AK, et al. DFUNet: Convolutional neural networks for diabetic foot ulcer classification. IEEE TETCI, 2020, 4(5): 728-739.
13. Dhillon MS, Alappatt K, Nayar PS, et al. Artificial intelligence in the foot and ankle: the applications in 2025. J Foot Ankle Surg (Asia-Pacific), 2025, 12(4): 171-175.
14. 趙楠, 金莉萍, 方金贏, 等. 基于醫聯體的糖尿病足智能診療平臺的構建與實踐. 中華糖尿病雜志, 2021, 13(9): 901-905.
15. Basiri R. Applications of generative AI in diabetic foot ulcer treatment//Raghav A. Diabetic foot-Advanced methods of management. London: IntechOpen, 2025.
16. Malik AH, Rahman S. Toward precision wound healing: Integrating regenerative therapies and smart technologies. Int J Sci Res Arch, 2025, 16(3): 244-257.
17. Metwaly A, Ismail S, Nagy YM, et al. Limb salvage: A review of stem cell and growth factor therapies for diabetic foot ulcers. Diabetes Res Clin Pract, 2026, 231: 113036. doi: 10.1016/j.diabres.2025.113036.
18. Zhu Y, Bao S, Yin X, et al. Advancements in diabetic foot ulcer therapy: The role of exosomes and decellularised extracellular matrix scaffolds. Diabetes Res Clin Pract, 2025, 226: 112364. doi: 10.1016/j.diabres.2025.112364.
19. Chen T, Ouyang L, Mi B, et al. MicroRNA-493-5p engineered exosomes delivered via piezoelectric microneedles for epigenetic modulation of macrophages in diabetic wound healing. Mater Today Bio, 2026, 37: 102931. doi: 10.1016/j.mtbio.2026.102931.
20. ?ak MM, Zangi L. Clinical development of therapeutic mRNA applications. Mol Ther, 2025, 33(6): 2583-2609.
21. Guo K. Lipid nanoparticle-based mRNA therapy for diabetic wound healing: scavenging ROS and modulating inflammation. New York: Icahn School of Medicine at Mount Sinai, 2025.
22. Wang J, Wang Y, Lu M, et al. Biomimetic triplet messenger RNA formulation in MXene hydrogel microneedles for wound healing. Aggregate, 2025, 6(2): e700. doi: 10.1002/agt2.700. doi: 10.1002/agt2.700.
23. Zhang M, Pan X, Li J, et al. mRNA-based therapeutics in skin regeneration and rejuvenation: From optimization strategies to translational advances. Chinese Chem Lett, 2026. doi: 10.1016/j.cclet.2026.112358.
24. Moldovan CA, Salagean AA, Slevin M. Multiplexing 3D natural scaffolds to optimize the repair and regeneration of chronic diabetic wounds. Gels, 2025, 11(6): 430. doi: 10.3390/gels11060430.
25. Dhankhar S, Garg N, Chauhan S, et al. Harnessing bioprinting technologies for diabetic wound regeneration. Curr Pharm Biotechnol, 2025, 26(10): 1482-1498.
26. Liao HJ, Liao TC, Wu YF. Integrating regenerative therapies and artificial intelligence for precision management of diabetic foot ulcers. Adv Wound Care (New Rochelle), 2026. doi: 10.1177/21621918261422388.
27. Akhavan-Kharazian N, Izadi-Vasafi H, Tabashiri-Isfahani M, et al. A review on smart dressings with advanced features. Wound Repair Regen, 2025, 33(3): e70014. doi: 10.1111/wrr.70014.
28. Yuan XM, Kong WC, Shao YJ, et al. AI-feedback bioelectronics promote infectious wound healing. Cell Biomater, 2026, 2(2): 100191. doi: 10.1016/j.celbio.2025.100191.
29. Thanha KPK, Sana PA, Ajesh JS, et al. Advanced smart bioelectronics for wound healing: biosensing, drug delivery, and artificial intelligence. Int J Pharm, 2025, 684: 126098. doi: 10.1016/j.ijpharm.2025.126098.
30. Armstrong DG, Boulton AJM, Bus SA. Diabetic foot ulcers and their recurrence. N Engl J Med, 2017, 376(24): 2367-2375.
31. Petersen BJ, Rothenberg GM, Lakhani PJ, et al. Ulcer metastasis? Anatomical locations of recurrence for patients in diabetic foot remission. J Foot Ankle Res, 2020, 13: 1. doi: 10.1186/s13047-020-0369-3.
32. Donaldson G, Hendry G, Barn R. Exploring patient and podiatrist perspectives of the ‘in-remission’ status in diabetes-related foot disease. J Foot Ankle Res, 2025, 18(2): e70045. doi: 10.1002/jfa2.70045.
33. Shakir K, Sarlak H, Bus SA, et al. Advancing diabetic foot ulcer care: focus on the post-healing transition phase. J Diabetes, 2025, 17(12): e70173. doi: 10.1111/1753-0407.70173.

Chinese Journal of Reparative and Reconstructive Surgery

Diabetic foot care: full-lifecycle management driven by digital intelligent technologies

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