Affiliations 

  • 1 Department of Orthopaedics, Hospital Tengku Ampuan Afzan (HTAA), Kuantan, Malaysia
  • 2 Department of Radiology, Hospital Tengku Ampuan Afzan, Kuantan, Malaysia
  • 3 Department of Orthopaedic, Hospital Kuala Lipis, Kuala Lipis, Malaysia
Malays Orthop J, 2019 Nov;13(3):45-52.
PMID: 31890110 DOI: 10.5704/MOJ.1911.008

Abstract

Introduction: Diabetic foot infection, a complication which can lead to lower limb amputation, is a major source of morbidity and mortality in Malaysia. The objective of this study was to determine the predictive factors of major lower limb amputation among patients with diabetes mellitus in a cluster of three district hospitals in Pahang, Malaysia. Materials and Methods: This cross-sectional study involved 170 patients who had undergone surgical interventions for diabetic foot infections at three district hospitals from 1st of September 2014 to 31st December 2015. The predictors for major amputation of lower limb were determined using simple logistic regression (LR) and forward LR multiple logistic regression. Results: A total of 21 patients had undergone major amputations of lower limb (15 transtibial and 6 transfemoral). The following factors were associated with major amputation of lower limb; longer duration of disease, age ≥ 60 years, patients from Bentong Hospital, presence of hypertension, presence of fever, history of multiple limb-salvaging surgeries, monomicrobial culture, necrotising fasciitis, anemia and leukocytosis. Upon forward LR multiple logistic regression, only duration of disease, history of more than three previous limb-salvaging surgeries and total white blood cell count ≥15X109/L were found to be significant as predictive factors of major amputation of lower limb. Conclusion: Among the factors analysed in this study, a longer duration of disease, raised total white blood cell count and history of more than three limb-salvaging surgeries were identified as predictors for major amputation of lower limb in diabetic foot infections using stepwise logistic regression analysis.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.