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Development and Evaluation of a Bayesian Risk Stratification Method for Major Amputations in Patients with Diabetic Foot Ulcers

  • The diabetic foot ulcer, which 2% – 6% of diabetes patients experience, is a severe health threat. It is closely linked to the risk of lower extremity amputation (LEA). When a DFU is present, the chief imperative is to initiate tertiary preventive actions to avoid amputation. In this light, clinical decision support systems (CDSS) can guide clinicians to identify DFU patients early. In this study, the PEDIS classification and a Bayesian logistic regression model are utilised to develop and evaluate a decision method for patient stratification. Therefore, we conducted a Bayesian cutpoint analysis. The CDSS revealed an optimal cutpoint for the amputation risk of 0.28. Sensitivity and specificity were 0.83 and 0.66. These results show that although the specificity is low, the decision method includes most actual patients at risk, which is a desirable feature in monitoring patients at risk for major amputation. This study shows that the PEDIS classification promises to provide a valid basis for a DFU risk stratification in CDSS.

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Metadaten
Author:Jens HüsersORCiD, Guido Hafer, Jan Heggemann, Stefan Wiemeyer, Swen Malte JohnORCiD, Ursula Hertha HübnerORCiD
Title (German):Development and Evaluation of a Bayesian Risk Stratification Method for Major Amputations in Patients with Diabetic Foot Ulcers
URN:urn:nbn:de:bsz:959-opus-36135
DOI:https://doi.org/10.3233/SHTI210897
ISBN:978-1-64368-250-1
ISBN:978-1-64368-251-8
Parent Title (German):Informatics and Technology in Clinical Care and Public Health
Publisher:IOS Press
Place of publication:Amsterdam, Berlin, Washington (DC)
Document Type:Conference Proceeding
Language:German
Year of Completion:2022
Release Date:2022/08/18
First Page:212
Last Page:215
Note:
International Conference on Informatics, Management, and Technology in Healthcare (ICIMTH), 16.10. - 17.10.2021, Athens (Greece)
Faculties:Fakultät WiSo
DDC classes:600 Technik, Medizin, angewandte Wissenschaften / 610 Medizin, Gesundheit
Review Status:Veröffentlichte Fassung/Verlagsversion
Licence (German):License LogoCreative Commons - CC BY-NC - Namensnennung - Nicht kommerziell 4.0 International