Left Ventricular Hypertrophy (LVH) is common in Type 2 Diabetes (T2DM) and despite optimal treatment of blood pressure can still persist. We know LVH is a cardiovascular (CV) risk factor in its own right and contributes to high CV event rates in patients with T2DM. Apart from hypertension, other factors contribute to the development of LVH in patients with T2DM, in particular oxidative stress (OS) has been implicated in LVH development. Allopurinol is a potent anti-oxidant, acting by blocking the enzyme Xanthine Oxidase, and has been previously shown to reduce vascular OS. Therefore the main aim of this thesis was to investigate whether allopurinol regresses LVH in patients with T2DM. The trial design was a randomised, double blind, placebo controlled study in 66 patients with T2DM with echocardiographic evidence of LVH. Allopurinol 600mg/day or placebo was given for nine months over the study period. The primary outcome was reduction in left ventricular mass (LVM) as calculated by cardiac magnetic resonance imaging (CMR) at baseline and at nine months follow-up. The secondary end-points were change in flow mediated dilatation (FMD) and augmentation index (AIx). Allopurinol significantly reduced absolute LVM (-2.65 ± 5.91g and placebo group +1.21 ± 5.10g (p=0.012)) and LVM indexed to body surface area (-1.32 ± 2.84g/m2 and placebo group +0.65 ± 3.07g/m2 (p=0.017)). When analysis was made of high and low baseline LVM then the effects of allopurinol were exaggerated in the high LVM mass group. No significant change was seen in either FMD or AIx. This thesis shows that allopurinol regresses LVM in patients with T2DM and LVH and controlled blood pressure. Regressing LVH has been shown previously to improve CV mortality and morbidity. Therefore allopurinol may become a useful therapy to reduce CV events in T2DM patients with LVH.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:600769 |
Date | January 2014 |
Creators | Szwejkowski, Benjamin |
Contributors | Struthers, Allan |
Publisher | University of Dundee |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | https://discovery.dundee.ac.uk/en/studentTheses/530c354b-f49b-4c84-af2f-59418aa11db6 |
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