Analysis of risk factors for amputation in patients with diabetic foot ulcers: a cohort study from a tertiary center

Denizhan Demirkol*, Şamil Aktaş, Tuncay Özcan, Xavier Tannier, Çiğdem Selçukcan Erol

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11 Atıf (Scopus)

Özet

Objective: This study aimed to analyze risk factors for amputation (overall, minor and major) in patients with diabetic foot ulcers (DFUs). Methods: 407 patients with DFUs (286 male, 121 female; mean age = 60, age range = 32-92) who were managed in a tertiary care centre from 2009 to 2019 were retrospectively identified and included in the study. DFUs were categorized based on the Meggit-Wagner, PEDIS, S(AD)SAD, and University of Texas (UT) classification systems. To identify amputation risk-related factors, results of patients with DFUs who underwent amputations (minor or major) were compared to those who received other adjunctive treatments using Chi-Square, one-way analysis of variance (ANOVA) and Spearman correlation analysis. Results: The mean C-reactive protein (CRP) and White Blood Cell (WBC) values were significantly higher in patients with major or minor amputation than in those without amputation. The mean Neutrophil (PNL), Platelets (PLT), wound width, creatinine and sedimentation (ESR) values were significantly higher in patients with major amputation compared to other groups of patients. Elevated levels of High-density lipoprotein (HDL), Hemoglobin (HGB) and albumin were determined to be protective factors against the risk of amputation. Spearman correlation analysis revealed a positive-sided, strong-levelled, significant relation between Wagner grades and amputation status of patients. Conclusion: This study has identified specific factors for major and minor amputation risk of patients with DFUs. Especially infection markers such as CRP, WBC, ESR and PNL were higher in the amputation group. Most importantly, Meggit Wagner, one of the four different classification systems used in the DFUs, was determined to be highly associated with patients’ amputation risk. Level of Evidence: Level IV, Prognostic Study.

Orijinal dilİngilizce
Sayfa (başlangıç-bitiş)333-339
Sayfa sayısı7
DergiActa Orthopaedica et Traumatologica Turcica
Hacim56
Basın numarası5
DOI'lar
Yayın durumuYayınlandı - Eyl 2022

Bibliyografik not

Publisher Copyright:
© 2022, AVES. All rights reserved.

Finansman

Funding: This research is produced from the first author’s doctoral thesis, which has been entitled “Prediction of Amputation Risk of Patients with Diabetic Foot by Artificial Intelligence Techniques,” supervised by Assoc. Prof. Çiğdem EROL (Ph.D.) from İstanbul University, Institute of Science. This thesis research program is also funded by The Scientific and Technological Research Council of Turkey (TÜBİTAK) 2214-A-International Research Fellowship Programme for Ph.D. Students and French Government Research Fellowships in Turkey, organized by Campus France Paris. Thus, joint research activities carried out with Professor Xavier Tannnier from Sorbonne Université/INSERM/Laboratoire d’Informatique Médicale et d’Ingénierie des Connaissances en e-Santé (LIMICS). The LIMICS laboratory has allocated additional funding for the publication of this article. This research is produced from the first author’s doctoral thesis, which has been entitled “Prediction of Amputation Risk of Patients with Diabetic Foot by Artificial Intelligence Techniques,” supervised by Assoc. Prof. Çiğdem EROL (Ph.D.) from İstanbul University, Institute of Science. This thesis research program is also funded by The Scientific and Technological Research Council of Turkey (TÜBİTAK) 2214-A-International Research Fellowship Programme for Ph.D. Students and French Government Research Fellowships in Turkey, organized by Campus France Paris. Thus, joint research activities carried out with Professor Xavier Tannnier from Sorbonne Université/INSERM/Laboratoire d’Informatique Médicale et d’Ingénierie des Connaissances en e-Santé (LIMICS). The LIMICS laboratory has allocated additional funding for the publication of this article.

FinansörlerFinansör numarası
Artificial Intelligence Techniques
Campus France Paris
Laboratoire d’Informatique Médicale et d’Ingénierie des Connaissances en e-Santé
Institut national de la santé et de la recherche médicale
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu
Sorbonne Université

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