Eastern Institute of Technology
Are clinical characteristics predictive of non-traumatic lower extremity amputation in a diabetic population?
Abstract
dc:description.abstractOBJECTIVE The objective of this project was to evaluate if data collected at an interdisciplinary Diabetes Ulcer Clinic, will predict lower extremity amputation (LEA), identify factors or characteristics that predict non traumatic major or minor LEA in the Hawke’s Bay diabetic population, investigate if these characteristics can be ranked in order of importance, and explain which combinations of factors are most predictive of LEA. RESEARCH DESIGN AND METHODS Data collected over a six year period stratified 150 diabetic adults (and 291 limbs) with lower extremity wounds, attending a Diabetes Ulcer Clinic, into two groups. The case group had a LEA and the control group did not have a LEA during the data collection period. Clinical variables and demographic data included: previous amputation, gender, diabetes type, peripheral neuropathy symptoms, peripheral perception to monofilament, biothesiometry results, rest pain, intermittent claudication, ankle brachial index, glycaemic control, hypertension, evidence of pressure load on foot, and wound aetiology. The data were analysed using a Cox proportional hazards regression model in addition to collation of data from Microsoft Excel. RESULTS Over the study period there were 41 amputations in 291 limbs from 150 people. The only variable predictive of LEA using Cox multivariate proportional hazards regression analysis was previous amputation (p = 0.028). Sample size was too small to demonstrate significance for any other variable. Some associations between clinical variables were found with LEA, rest pain, biothesiometry results, ankle brachial index, hyperglycaemia, hypertension and wound aetiology, but these were found not to be statistically significant. CONCLUSION Previous amputation was the only significant predictor of LEA in this sample. A larger population than currently exists in Hawke’s Bay is required to identify predictors of LEA. This project has shown this methodology is feasible and suggests approach could be expanded into a multi-centred study.
Degree
thesis:*- Name thesis:degree_name
- Master of Nursing
- Level thesis:degree_level
- Masters
- Grantor
- Eastern Institute of Technology
- Year dc:date.issued
- 2007
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Rutherford, Pip
Subjects
dc:subject × 7Rights
dc:rights- Statement dc:rights
-
- All rights reserved
- Language dc:language.iso
- en
Identifiers
dc:identifier.*- Handle dc:identifier.uri
- https://hdl.handle.net/10652/6609
- OAI identifier oai:identifier
- oai:null:10652/6609