Comprehensive Factors for Predicting the Complications of Diabetes Mellitus: A Systematic Review
- 作者: Erandathi M.1, Wang W.Y.1, Mayo M.1, Lee C.2
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隶属关系:
- University of Waikato, Hamilton, New Zealand
- National Chen Kung University Hospital, Tainan, Taiwan
- 期: 卷 20, 编号 9 (2024)
- 栏目: Medicine
- URL: https://snv63.ru/1573-3998/article/view/643042
- DOI: https://doi.org/10.2174/0115733998271863231116062601
- ID: 643042
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详细
Background::This article focuses on extracting a standard feature set for predicting the complications of diabetes mellitus by systematically reviewing the literature. It is conducted and reported by following the guidelines of PRISMA, a well-known systematic review and meta-analysis method. The research articles included in this study are extracted using the search engine \"Web of Science\" over eight years. The most common complications of diabetes, diabetic neuropathy, retinopathy, nephropathy, and cardiovascular diseases are considered in the study.
Method::The features used to predict the complications are identified and categorised by scrutinising the standards of electronic health records.
Result::Overall, 102 research articles have been reviewed, resulting in 59 frequent features being identified. Nineteen attributes are recognised as a standard in all four considered complications, which are age, gender, ethnicity, weight, height, BMI, smoking history, HbA1c, SBP, eGFR, DBP, HDL, LDL, total cholesterol, triglyceride, use of insulin, duration of diabetes, family history of CVD, and diabetes. The existence of a well-accepted and updated feature set for health analytics models to predict the complications of diabetes mellitus is a vital and contemporary requirement. A widely accepted feature set is beneficial for benchmarking the risk factors of complications of diabetes.
Conclusion::This study is a thorough literature review to provide a clear state of the art for academicians, clinicians, and other stakeholders regarding the risk factors and their importance.
作者简介
Madurapperumage Erandathi
University of Waikato, Hamilton, New Zealand
Email: info@benthamscience.net
William Wang
University of Waikato, Hamilton, New Zealand
编辑信件的主要联系方式.
Email: info@benthamscience.net
Michael Mayo
University of Waikato, Hamilton, New Zealand
Email: info@benthamscience.net
Ching-Chi Lee
National Chen Kung University Hospital, Tainan, Taiwan
Email: info@benthamscience.net
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