A systematic review of predictive risk models for diabetes complications based on large scale clinical studies

J Diabetes Complications. 2013 Jul-Aug;27(4):407-13. doi: 10.1016/j.jdiacomp.2012.11.003. Epub 2012 Dec 27.


This work presents a systematic review of long-term risk assessment models for evaluating the probability of developing complications in diabetes patients. Diabetes mellitus can cause many complications if not adequately controlled; risk assessment models can help physicians and patients in identifying the complications most likely to arise and in taking the necessary countermeasures. We identified six large medical studies related to diabetes mellitus upon which current available risk assessment models are built on; all these studies had duration over 5 years and most of them included some common demographic and clinical data strongly related to diabetic complications. The most common predictions for long term diabetes complications are related to cardiovascular diseases and diabetic retinopathy. Our analysis of the literature led us to the conclusion that researchers and medical practitioners should take in account that some limitations undermine the applicability of risk assessment models; for example, it is hard to judge whether results obtained on a specific cohort can be effectively translated to other populations. Nevertheless, all these studies have significantly contributed to identify significant risk factors associated with the major diabetes complications.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review
  • Systematic Review

MeSH terms

  • Databases, Factual / statistics & numerical data
  • Diabetes Complications / diagnosis*
  • Diabetes Complications / etiology*
  • Diabetes Mellitus, Type 1 / complications
  • Diabetes Mellitus, Type 2 / complications
  • Humans
  • Models, Biological*
  • Multicenter Studies as Topic / statistics & numerical data
  • Risk Factors