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Published on: February 12, 2016
DIFFERENTIAL METABOLIC AND INFLAMMATORY RESPONSES TO ACUTE HYPERGLYCAEMIA IN ISCHAEMIC STROKE: IMPLICATIONS FOR
K Alali1, O Albitar1,2, S F Ismail3
1Discipline of Clinical Pharmacy, School of Pharmaceutical Sciences, Universiti Sains Malaysia, Penang, Malaysia.
Background:
Hyperglycaemia during acute ischaemic stroke (AIS) has been associated with poorer outcomes yet attempts to normalise glucose have not demonstrated clinical benefit. One proposed explanation is that the participants are not routinely stratified by the pre-stroke glycaemic status (diabetic hyperglycaemia [DHG], non-diabetic hyperglycaemia [NDHG]), which may contribute to heterogeneity in metabolic responses and dilute treatment effects. We compared early endocrine and inflammatory responses (insulin, C-peptide, cortisol, and cytokines) between DHG and NDHG and examined exploratory associations with stroke severity and 90-day functional outcomes.
Methods:
In this prospective multicentre cohort, 80 patients with AIS and hyperglycaemia (DHG or NDHG) were enrolled within 72 hours of admission. Biomarkers were measured on admission. Group comparisons were performed by diabetes status and stroke severity. Exploratory associations with 90-day functional outcome were assessed with LASSO regression.
Results:
Compared with DHG, NDHG was associated with higher insulin (142 vs 75 pmol/L;p<0.05), C-peptide (1.15 vs 0.87 nmol/L;p<0.05), IL-8 (23 vs 13 pg/mL;p<0.01), and IL-6 (8 vs 3 pg/mL;p=0.094). Cortisol was numerically higher in DHG than NDHG (352 vs 271 nmol/L;p=0.32). Within NDHG, endocrine and inflammatory measures varied by stroke severity, while remaining generally higher than DHG.
Conclusion:
Diabetes status was associated with differences in early endocrine and inflammatory profiles during AIS-associated hyperglycaemia. Given the observational design, single-time-point sampling, and modest sample size, these findings should be interpreted as hypothesis-generating. Future adequately powered studies with standardised sampling and detailed diabetes phenotyping are needed to determine whether diabetes-stratified approaches to hyperglycaemia management and prognostic modelling improve clinical utility.
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