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Metabolic Profile as a Predictor of Ischaemic Stroke: The Experience of a Rural Hospital in Nigeria


Orebowale Olugbemide
Idowu Bankole
Adewumi Alabi
Mercy Dic-Ijiewere
Aihanuwa Eregie
Olufemi Fasanmade

Abstract

BACKGROUND
The metabolic profile which includes glycated haemoglobin, insulin resistance, pancreatic beta cell function and lipid profile is frequently deranged in acute ischaemic stroke. Stroke is a leading cause of death worldwide and an emerging cause of long-term disability and mortality in Africa. Our study aimed to determine the correlation between the metabolic profile and acute ischaemic stroke in a rural Hospital in Southern Nigeria.
METHODOLOGY
This was a prospective cross-sectional study. Fifty consecutive first-ever ischaemic stroke patients presenting within 72 hours of stroke were matched for age and sex with 3 control groups (49 persons with type 2 diabetes and hypertension, 49 persons with hypertension only and 57 apparently healthy individuals). Blood samples were obtained from all participants to determine glycated haemoglobin, fasting lipid profile, fasting plasma glucose, fasting insulin and C-peptide and random plasma glucose (in stroke cases at presentation). Insulin resistance and pancreatic beta-cell function were determined using the Homeostatic Model Assessment (HOMA). Data were analysed by multivariate and univariate statistics.
RESULTS
One hundred and two (49.8%) males and 103 (50.2%) females participated in the study. The overall mean age of the study participants was 61.6 ± 10.1 years. Compared with the control groups, predictors of acute ischaemic stroke were Fasting insulin (hyperinsulinaemia) [OR (95%CI) = 1.108 (1.043-1.178), p= 0.001], HOMA-β% [OR (95%CI) = 0.994 (0.990-1.001) p=0.006] and total cholesterol [OR (95%CI)= 0.009 (0.001-0.012) p=0.022].
CONCLUSION
In this study, hyperinsulinaemia, impaired beta-cell secretory function (HOMA-β) and elevated total cholesterol were found to be significant risk factors of ischaemic stroke. Hence, the need for regular screening to detect abnormal metabolic profiles and prompt treatment.


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