Treatment of glucocorticoid- induced hyperglycemia in hospitalized patients - a systematic review and meta- analysis
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40842_2023_Article_158.pdf
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Author(s) • • • • • • • •
Struja, Tristan
Nitritz, Neele
Alexander, Islay
Kupferschmid, Kevin
Hafner, Jason F.
Spagnuolo, Carlos C.
Schuetz, Philipp
Mueller, Beat
Blum, Claudine A.
Date Issued
January 27, 2024
Publisher
BioMed Central
Citation
Clinical Diabetes and Endocrinology. 2024 Jan 27;10(1):8
Version
Final published version
Abstract
Purpose
Glucocorticoid (GC)-induced hyperglycemia is a frequent issue, however there are no specific guidelines for this diabetes subtype. Although treat-to-target insulin is recommended in general to correct hyperglycemia, it remains unclear which treatment strategy has a positive effect on outcomes. We performed a systematic review and meta-analysis of randomized controlled trials (RCTs) to assess whether treating GC-induced hyperglycemia improves clinical outcomes.
Methods
MEDLINE and EMBASE were systematically searched for RCTs on adults reporting treatment and outcomes of GC-induced hyperglycemia since the beginning of the data bases until October 21, 2023. Glucose-lowering strategies as compared to usual care were investigated.
Results
We found 17 RCTs with 808 patients and included seven trials in the quantitative analysis. Patients with an intensive glucose-lowering strategy had lower standardized mean glucose levels of – 0.29 mmol/l (95%CI -0.64 to -0.05) compared to usual care group patients. There was no increase in hypoglycemic events in the intensively treated groups (RR 0.91, 95%CI 0.70–1.17). Overall, we did not have enough trials reporting clinical outcomes for a quantitative analysis with only one trial reporting mortality.
Conclusion
In GC-induced hyperglycemia, tight glucose control has a moderate effect on mean glucose levels with no apparent harmful effect regarding hypoglycemia. There is insufficient data whether insulin treatment improves clinical outcomes, and data on non-insulin based treatment regimens are currently too sparse to draw any conclusions.
MIT Department
Massachusetts Institute of Technology. Institute for Medical Engineering & Science
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DOI of Published Version
https://doi.org/10.1186/s40842-023-00158-1