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.
Author: | Jens HüsersORCiD, Guido Hafer, Jan Heggemann, Stefan Wiemeyer, Swen Malte JohnORCiD, Ursula Hertha HübnerORCiD |
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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): | Creative Commons - CC BY-NC - Namensnennung - Nicht kommerziell 4.0 International |