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1.  Atherogenic index of plasma in highly active antiretroviral therapy-naïve patients with human immunodeficiency virus infection in Southeast Nigeria 
Introduction:
Metabolic abnormalities are often common among human immunodeficiency virus (HIV) patients. The atherogenic index of plasma (AIP) is increasingly being used as a screening tool for dyslipidemia as it predicts the presence of small, dense, and highly atherogenic low density lipoprotein (LDL) and high density lipoprotein (HDL) particles. The aim of this study was to identify the pattern and predictors of an abnormal atherogenic index in highly active antiretroviral therapy (HAART)-naïve HIV patients.
Materials and Methods:
HAART-naïve patients with HIV infection were recruited for this cross-sectional study. Anthropometric indices, blood pressure, CD4 count, viral load, fasting blood glucose, and lipid profiles were determined. Total cholesterol (TCH)/HDL, triglyceride (TG)/HDL, and LDL/HDL ratios were calculated. The AIP was calculated as log (TG/HDL). The correlations between AIP and the other lipoprotein ratios and predictors of AIP were determined using stepwise multiple linear regression. P < 0.05 was considered as significant.
Results:
A total of 353 patients with a mean age of 37.3 (9.6) years were recruited for this study. Low HDL level was the most common abnormality in 222 (62.9%) patients while elevated TCH was seen in 54 (15.3%) patients. Those with medium risk (AIP 0.1-0.24) and high risk category (AIP > 0.24) constituted up to 226 (64%) of the patients. There were significant correlations between AIP and CD4 count, body mass index, LDL, TCH/HDL, and LDL/HDL. Predictors of AIP were CD4 count, TCH/HDL, and LDL/HDL.
Conclusion:
Abnormal AIP is frequent in HAART-naïve HIV patients and is inversely related to their level of immunity. We recommend that AIP estimation should be part of baseline assessment of HIV patients before the commencement of therapy.
doi:10.4103/2230-8210.139217
PMCID: PMC4171884  PMID: 25285278
Atherogenic index; dyslipidemia; human immunodeficiency virus; lipids; plasma
2.  Beta cell response to a mixed meal in nigerian patients with type 2 diabetes 
Background
The pathophysiology of type2 diabetes involves both insulin resistance and poor beta cell function. Studies have been done in several populations to assess the relative importance of these mechanisms in individual patients. In our environment studies to assess beta cell function have been done with glucagon stimulation or an oral glucose tolerance test. This study was done to assess the response of the beta cell to a standardized mixed meal and its relationship with glycaemic control in patients with type2 diabetes.
Methods
Ninety patients with type 2 diabetes were recruited into the study. Weight, height, body mass index and waist circumference were measured. Blood samples were analysed for fasting plasma glucose (FPG) and fasting C peptide (FCP) and glycated haemoglobin (HbA1c). Patients were given their usual drugs for management of their diabetes and then served with a standard meal calculated to contain 50 g of carbohydrate, made up of 53 % carbohydrate, 17 % of protein and 30 % of lipids, providing 500 kcal. Blood samples 2 hours after the start of the meal were analysed for postprandial glucose (PPG) and postprandial C peptide (PCP). Fasting (M0) and postprandial beta cell responsiveness (M1) were calculated.
Results
The mean FPG and PPG were 7.51+/− 3.39 mmol/l and 11.02+/−4.03 mmol/l respectively while the mean glycated haemoglobin (HbA1c) was 9.0+/−2.5 %. The mean fasting C peptide was 1.44+/−1.80ug/ml. Many of the patients (56.7 %) had low FCP levels. The mean postprandial C peptide was 4.0+/−2.8 ng/ml. There were significant correlations between M1, HbA1c and PPG (p = 0.015, 0.024, 0.001 respectively) and also between M0, HbA1c, PPG and FPG (p = 0.001, 0.002, 0.001). HbA1c decreased across increasing tertiles of M0 (p < 0.001) and also M1 (p = 0.002). In step-wise linear regression analysis, M0 and M1 significantly predicted HbA1c.
Conclusions
Many of the patients had low C peptide levels with poor beta cell response to the meal. The patients had poor glycaemic control and poor beta cell function. Both fasting and postprandial beta cell responsiveness were significant determinants of blood glucose and glycated haemoglobin levels. It is likely that putting these patients on insulin may have led to better glycaemic control in them.
doi:10.1186/1472-6823-12-11
PMCID: PMC3489861  PMID: 22738260
Beta cell; Type2 diabetes; Meal stimulation; Glycaemic control

Results 1-2 (2)