V  DANWE-KOUKREO^{1, 2}, A-P KENGNE³, C NJUKENG⁴, D AROKE^1,2, S-P CHOUKEM^{1 ,2 ,5}

¹Faculty of Health Sciences, University of Buea

²Health and Human Development Research Group, Cameroon

³South African Medical Research Council, Cape-Town, South Africa

⁴Saint Albert the Great Reference Laboratory

⁵Diabetes and Endocrine Unit, Department of Internal Medicine, Douala General Hospital

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Background: Cardiovascular complications are an important cause of morbidity and mortality in people with diabetes. Various risk equations have been developed to assist cardiovascular disease (CVD) risk assessment. Their use however is still limited in various contexts.

Objectives: To assess and compare the risk of CVD in diabetic Cameroonians using 4 diabetic specific CVD risk equations: the ADVANCE, the Fremantle Diabetes Study (FDS), the New Zealand Diabetes Cohort Study (NZDCS) and the Swedish National Diabetes Registry (SNDR) risk equations. To assess the potential impact of an ideal control of the modifiable risk factors on the CVD risk.

Methods: Type 2 diabetic patients receiving regular care at the outpatient Diabetes/Endocrine Unit of the Douala General Hospital were examined between November 2014 and March 2015. Absolute CVD risk estimates were computed from the 4 selected equations.The agreement between equations was evaluated with the Spearman’s and the Kappa tests. The significance level was considered at p<0.05.

Results: We included 184 participants of whom 97(52.7%) were females. The mean age was 58.7 years (standard deviation [SD] 10.3) with 47.3% of the participants in the 40-59 age range. The median diabetes duration was 5 years (25^th-75^th percentile: 1.25-10). About 10.9% of the study population had a previous history of CVD (5.2% females, 17% males, p=0.009). The median 5-year predicted CVD risks were: 5.4% (4.1% for females, 6% for males) with the ADVANCE; 7.1% (6% for females, 8.8% for males) with the FDS; 24.5%(21% for females, 26.2% for males) with the NZDCS; and 10.8%(10.5% for females, 11.3% for males) with the SNDR. There was a significant correlation between the risk equations. There was a fair degree of agreement between the ADVANCE and the FDS, with a Kappa k coefficient of 0.397(CI 0.309-0.489), but no agreement between the rest. The modifiable risk factors had a significant impact on the risk reduction by reducing median risk by 3.88% in the ADVANCE, 3.7% in the FDS and 11.1% in the NZDCS.

Conclusion: The risk equation analysis greatly varied between the equations; there was a good correlation but a very poor degree of agreement between these equations; and the modifiable risk factors had a significant impact on CVD risk reduction. The fact that these risk equations do not fully agree in their risk estimations makes them difficult to be used in this context, particularly in term of choosing the appropriate one. Adequate control of modifiable risk factors will help mitigating the risk.