Early detection to prevent foot ulceration among type 2 diabetes mellitus patient: A multi-intervention review

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Dewa Ayu Rismayanti
Faculty of Nursing, Universitas Airlangga, Surabaya, East Java, Indonesia.
https://orcid.org/0000-0001-7133-5770

Nursalam Nursalam
Faculty of Nursing, Universitas Airlangga, Surabaya, East Java, Indonesia.

Virgianti Nur Farida
Faculty of Nursing, Universitas Airlangga, Surabaya, East Java, Indonesia.
https://orcid.org/0000-0001-7133-5770

Ni Wayan Suniya Dewi
Faculty of Nursing, Universitas Airlangga, Surabaya, East Java, Indonesia.

Resti Utami
Faculty of Nursing, Universitas Airlangga, Surabaya, East Java, Indonesia.

Arifal Aris
Faculty of Nursing, Universitas Airlangga, Surabaya, East Java, Indonesia.

Ni Luh Putu Inca Buntari Agustini
Faculty of Nursing, Universitas Airlangga, Surabaya, East Java, Indonesia.

ABSTRACT

Foot ulceration is one of the biggest complications experienced by type 2 diabetes patients. The severity and prevention of new wounds can be overcome through early detection interventions. This systematic review aims to explain and provide a comparison of various interventions that have been developed to prevent the occurrence of Diabetes Foot Ulcers (DFU). We searched Scopus, Science Direct, PubMed, CINAHL, SAGE, and ProQuest for English, experimental studies, published between 2016-2021 that tested early detection for preventing diabetic foot ulcers in diabetic patients.

The Joanna Briggs Institute guidelines were used to assess eligibility, and PRISMA quality and a checklist to guide this review. 25 studies were obtained that matched the specified inclusion criteria. The entire article has an experimental study design. Majority of respondents were type 2 diabetes patients who have not experienced ulceration. Based on the results of the review, there were 3 main types of interventions used in the early detection of DFU.

The types of intervention used are 1) conventional intervention/physical assessment, 2) 3D thermal camera assessment system, and 3) DFU screening instrument. The three types of interventions have advantages and disadvantages, so their use needs to be adjusted to the conditions and needs of the patient. the development of DFU risk early detection intervention needs to be developed. Integration with modern technology can also be done to increase the accuracy of the results and the ease of examination procedures.

 

REFERENCES

Shabibi P, Abedzadeh Zavareh MS, Sayehmiri K, et al. Effect of educational intervention based on the Health Belief Model on promoting self-care behaviors of type-2 diabetes patients. Electron Physician 2017;9:5960–8. DOI: https://doi.org/10.19082/5960

Schaper NC, van Netten JJ, Apelqvist J, et al. Practical guidelines on the prevention and management of diabetic foot disease (IWGDF 2019 update). Diabetes Metab Res Rev 2020;36:1-10. DOI: https://doi.org/10.1002/dmrr.3266

Banik PC, Barua L, Moniruzzaman M, et al. Risk of diabetic foot ulcer and its associated factors among Bangladeshi subjects: A multicentric cross-sectional study. BMJ Open 2020;10:e034058. DOI: https://doi.org/10.1136/bmjopen-2019-034058

Tolossa T, Mengist B, Mulisa D, et al. Prevalence and associated factors of foot ulcer among diabetic patients in Ethiopia: a systematic review and meta-analysis. BMC Public Health 2020;20:41. DOI: https://doi.org/10.1186/s12889-019-8133-y

Carbajal-Ramírez A, Hernández-Domínguez JA, Molina-Ayala MA, et al. Early identification of peripheral neuropathy based on sudomotor dysfunction in Mexican patients with type 2 diabetes. BMC Neurol 2019;19:1–6. DOI: https://doi.org/10.1186/s12883-019-1332-4

Hsieh YL, Lee FH, Chen CL, et al. Factors influencing intention to receive examination of diabetes complications. Asian Nurs Res 2016;10: 289–94. DOI: https://doi.org/10.1016/j.anr.2016.10.004

Ghobadi A, Sarbarzeh PA, Jalilian M, et al. Evaluation of factors affecting the severity of diabetic foot ulcer in patients with diabetes referred to a diabetes centre in Kermanshah. Diabetes Metab Syndr Obes Targets Ther 2020;13:693–703. DOI: https://doi.org/10.2147/DMSO.S242431

Damanhuri NS, Othman NA, Zaidi WFAW, Abdullah S. A development of plantar pressure sensor for foot ulcer detection in diabetic neuropathy individuals–A pilot study. J Phys Conf Ser 2020;1535:12019. DOI: https://doi.org/10.1088/1742-6596/1535/1/012019

Chantelau E-A. A novel diagnostic test for end-stage sensory failure associated with diabetic foot ulceration: Proof-of-principle study. J Diabetes Sci Technol 2021;15:622-9. DOI: https://doi.org/10.1177/1932296819900256

Azzopardi K, Gatt A, Chockalingam N, Formosa C. Hidden dangers revealed by misdiagnosed diabetic neuropathy: a comparison of simple clinical tests for the screening of vibration perception threshold at primary care level. Prim Care Diabetes 2018;12:111–5. DOI: https://doi.org/10.1016/j.pcd.2017.09.004

Zwaferink JBJ, Hijmans JM, Schrijver CM, et al. Mechanical noise improves the vibration perception threshold of the foot in people with diabetic neuropathy. J Diabetes Sci Technol 2018;14:16–21. DOI: https://doi.org/10.1177/1932296818804552

van Doremalen RFM, van Netten JJ, van Baal JG, et al. Infrared 3D thermography for inflammation detection in diabetic foot disease: A proof of concept. J Diabetes Sci Technol 2019;14:46–54. DOI: https://doi.org/10.1177/1932296819854062

Fraiwan L, AlKhodari M, Ninan J, et al. Diabetic foot ulcer mobile detection system using smart phone thermal camera: a feasibility study. Biomed Eng Online 2017;16:1-19. DOI: https://doi.org/10.1186/s12938-017-0408-x

Fraiwan L, Ninan J, Al-Khodari M. Mobile application for ulcer detection. Open Biomed Eng J 2018;12:16. DOI: https://doi.org/10.2174/1874120701812010016

Wang L, Pedersen PC, Strong DM, et al. An automatic assessment system of diabetic foot ulcers based on wound area determination, color segmentation, and healing score evaluation. J Diabetes Sci Technol 2016;10:421-8. DOI: https://doi.org/10.1177/1932296815599004

Cassidy B, Reeves ND, Pappachan JM, et al. The DFUC 2020 dataset: Analysis towards diabetic foot ulcer detection. touchREV Endocrinol 2021;17:5-11.

Goyal M, Reeves ND, Davison AK, et al. Dfunet: Convolutional neural networks for diabetic foot ulcer classification. IEEE Trans Emerg Top Comput Intell 2018;4:728-39. DOI: https://doi.org/10.1109/TETCI.2018.2866254

Zhou Q, Peng M, Zhou L, et al. Development and validation of a brief diabetic foot ulceration risk checklist among diabetic patients: A multicenter longitudinal study in China. Sci Rep 2018;8:1–9. DOI: https://doi.org/10.1038/s41598-018-19268-3

Baker N, Al-Muzaini A. A user’s guide to skin and nail conditions in diabetes. Diabet Foot 2018;4:31-9.

Akturan S, Kaya ÇA, Ünalan PC, Akman M. The effect of the BATHE interview technique on the empowerment of diabetic patients in primary care: a cluster randomised controlled study. Prim Care Diabetes 2017;11:154–61. DOI: https://doi.org/10.1016/j.pcd.2016.12.003

Babu KS, Sabut S, Nithya DK. Efficient detection and classification of diabetic foot ulcer tissue using PSO technique. Int J Eng Technol 2018;7:1006-10. DOI: https://doi.org/10.14419/ijet.v7i3.12.17622

Martínez-Alberto CE, Brito-Brito PR, Fernández-Gutiérrez DA, et al. Evaluation of the risk of diabetic peripheral neuropathy: Design and validation of the NeuDiaCan nursing screening procedure. Enfer Clin (English Ed) 2020;30:89-98. DOI: https://doi.org/10.1016/j.enfcle.2019.07.006

Binns‐Hall O, Selvarajah D, Sanger D, et al. One‐stop microvascular screening service: an effective model for the early detection of diabetic peripheral neuropathy and the high‐risk foot. Diabet Med 2018;35:887–94. DOI: https://doi.org/10.1111/dme.13630

Peterson M, Pingel R, Rolandsson O, Dahlin LB. Vibrotactile perception on the sole of the foot in an older group of people with normal glucose tolerance and type 2 diabetes. SAGE Open Med 2020;8:2050312120931640. DOI: https://doi.org/10.1177/2050312120931640

Santos TRM, Melo JV, Leite NC, Salles GF, Cardoso CRL. Usefulness of the vibration perception thresholds measurement as a diagnostic method for diabetic peripheral neuropathy: Results from the Rio de Janeiro type 2 diabetes cohort study. J Diabetes Complicat 2018;32:770–6. DOI: https://doi.org/10.1016/j.jdiacomp.2018.05.010

Goyal M, Reeves ND, Rajbhandari S, Yap MH. Robust methods for real-time diabetic foot ulcer detection and localization on mobile devices. IEEE J Biomed Health Inform 2018;23:1730–41. DOI: https://doi.org/10.1109/JBHI.2018.2868656

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