We tested the hypothesis that admission serum magnesium levels are associated with extent of hemorrhage in patients with aneurysmal subarachnoid hemorrhage.
Single-center prospective observational study.
Tertiary hospital neurologic ICU.
Patients with aneurysmal subarachnoid hemorrhage.
Clinically indicated CT scans and serum laboratory studies.
Demographic, clinical, laboratory, and radiographic data were analyzed. Extent of initial hemorrhage was graded semi-quantitatively on admission CT scans using the modified Fisher scale (grades: 0, no radiographic hemorrhage; 1, thin [< 1 mm in depth] subarachnoid hemorrhage; 2, thin subarachnoid hemorrhage with intraventricular hemorrhage; 3, thick [≥ 1 mm] subarachnoid hemorrhage; 4, thick subarachnoid hemorrhage with intraventricular hemorrhage). We used both ordinal (modified Fisher scale) and dichotomized (thick vs thin subarachnoid hemorrhage) univariate and adjusted logistic regression models to assess associations between serum magnesium and radiographic subarachnoid hemorrhage severity. Data from 354 patients (mean age 55 ± 14 yr, 28.5% male, median admission Glasgow Coma Scale 14 [10–15]) were analyzed. Mean magnesium was lower in patients with thick versus thin subarachnoid hemorrhage (1.92 vs 1.99 mg/dL; p = 0.022). A monotonic trend across categories of modified Fisher scale was found using analysis of variance and Spearman rank correlation (p = 0.015 and p = 0.008, respectively). In adjusted ordinal and binary regression models, lower magnesium levels were associated with higher modified Fisher scale (odds ratio 0.33 per 1 mg/dL increase; 95% CI, 0.14–0.77; p = 0.011) and with thick subarachnoid hemorrhage (odds ratio 0.29 per 1 mg/dL increase; 95% CI, 0.10–0.78; p = 0.015).
These data support the hypothesis that magnesium influences hemorrhage severity in patients with aneurysmal subarachnoid hemorrhage, potentially through a hemostatic mechanism.
1Department of Neurology, Northwestern University, Chicago, IL.
2Department of Neurology, University of Chicago, Chicago, IL.
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Dr. Liotta originated the idea for the study, designed and conceptualized the study, analyzed and interpreted the data, collected study data, and drafted and revised the article for important intellectual content. Drs. Karmarkar, Batra, and Kim revised the article for important intellectual content. Dr. Prabhakaran collected study data and revised the article for important intellectual content. Dr. Naidech designed and conceptualized the study, collected study data, and revised the article for important intellectual content. Dr. Maas designed and conceptualized the study, analyzed and interpreted the data, collected study data, and drafted and revised the article for important intellectual content. Statistical analyses were performed jointly by Drs. Liotta and Maas. Dr. Maas holds a masters of science in biostatistics from Northwestern University and Dr. Liotta has completed post-graduate coursework in biostatistics at Northwestern University.
Dr. Liotta’s institution received funding from the National Institutes of Health (NIH) National Center for Advancing Translational Sciences (NCATS) grant KL2TR001424 and NIH grants K23 NS092975, and he received funding from NIH medical school student loan repayment grant L30 NS098427. Drs. Liotta and Maas received support for article research from the NIH. Dr. Naidech’s institution received funding from the Agency for Healthcare Research and Quality grant K18 HS023437. Research reported in this publication was supported, in part, by the NIH NCATS grant UL1 TR000150. Dr. Maas’ institution received funding from the NIH grants K23 NS092975. The remaining authors have disclosed that they do not have any potential conflicts of interest.
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