These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


PUBMED FOR HANDHELDS

Search MEDLINE/PubMed


  • Title: QT interval abnormalities are often present at diagnosis in diabetes and are better predictors of cardiac death than ankle brachial pressure index and autonomic function tests.
    Author: Rana BS, Lim PO, Naas AA, Ogston SA, Newton RW, Jung RT, Morris AD, Struthers AD.
    Journal: Heart; 2005 Jan; 91(1):44-50. PubMed ID: 15604334.
    Abstract:
    OBJECTIVES: To study serial measures of maximum QT interval corrected for heart rate (QTc) and QT dispersion (QTD) and their association with cardiac mortality patients with non-insulin dependent diabetes and to compare QT abnormalities with other mortality predictors (ankle brachial pressure index (ABPI) and autonomic function tests) in their ability to predict cardiac death. SETTING: Teaching hospital. METHODS AND PATIENTS: QT interval analysis, heart rate (RR) variation in response to deep breathing and standing, and ABPI were analysed in 192 patients with non-insulin dependent diabetes. Cardiac death was the primary end point. RESULTS: Mean (SD) follow up was 12.7 (3.2) years (range 1.2-17.1 years). There were 48 deaths, of which 26 were cardiac. QTc and QTD were individually significant predictors of cardiac mortality throughout the follow up period (p < 0.001). The predictability of QT parameters was superior to the predictability of ABPI and RR interval analysis. Temporal changes in QT parameters showed that the mean absolute QT parameter was a significant predictor of cardiac death (p < 0.001), whereas an intraindividual change in QT parameter over time was not predictive. CONCLUSION: QT abnormalities seem to exist at the point of diagnosis of diabetes and do not appear to change between then and the subsequent cardiac death. Furthermore, the analysis of QT interval is superior to ABPI and the RR interval in identifying diabetic patients at high risk of cardiac death.
    [Abstract] [Full Text] [Related] [New Search]