Published in:
Open Access 01-12-2021 | Stroke | Research article
Persistent hyperglycemia is a useful glycemic pattern to predict stroke mortality: a systematic review and meta-analysis
Published in: BMC Neurology | Issue 1/2021
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Background
Glycemic patterns have been reported to be prognostic factors for stroke; however, this remains to be further evaluated. This meta-analysis aimed to evaluate the usefulness of glycemic patterns such as persistent hyperglycemia (PH) including short duration and long duration PH (SPH; LPH), admission hyperglycemia (AH), short-duration hyperglycemia (SH), and persistent normoglycemia (PN) in predicting stroke prognosis using published results.
Methods
Major scientific databases including but are not limited to PubMed, EMBASE, Web of Science, Ovid, CNKI (Chinese National Knowledge Infrastructure), and Clinicaltrials.gov were searched till 1st March 2021 for clinical trials on the correlation between glycemic patterns and stroke outcomes. The primary outcome was defined as short-term (1- or 3-month) post-stroke mortality, and the secondary outcome was post-stroke hemorrhage at 6 months.
Results
Ten studies involving 3584 individuals were included in the final analysis. In subgroup analyses, PH patients with no history of diabetes had increased post-stroke mortality (odds ratio [OR]: 4.80, 95% CI: 3.06–7.54) than patients with no PH; and patients with glucose levels > 140 mg/dl had greater mortality (OR: 5.12, 95% CI: 3.21–8.18) than those with glucose levels < 140 mg/dl; compared with AH patients, PH patients had increased short-term mortality (OR: 0.31, 95% CI: 0.16–0.60). In the prediction of stroke mortality among patients without diabetes, SPH (OR: 0.28, 95%CI: 0.12–0.69) seemed to be more related to increased mortality than LPH (OR: 0.35, 95% CI: 0.14–-0.90).
Conclusions
PH, especially SPH, could predict increased post-stroke mortality in non-diabetic patients. The rank of individual glycemic patterns in predicting stroke mortality in non-diabetic patients was SPH > LPH > AH > PN.