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

Vincenzo Lagani, Lefteris Koumakis, Franco Chiarugi, Edin Lakasing, Ioannis Tsamardinos

Research output: Contribution to journalArticlepeer-review

46 Scopus citations

Abstract

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. © 2013 Elsevier Inc.
Original languageEnglish (US)
Pages (from-to)407-413
Number of pages7
JournalJournal of Diabetes and its Complications
Volume27
Issue number4
DOIs
StatePublished - Jul 1 2013
Externally publishedYes

ASJC Scopus subject areas

  • Internal Medicine
  • Endocrinology, Diabetes and Metabolism
  • Endocrinology

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