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Background <p>Glycemic variability (GV), assessed by the Mean Amplitude of Glycemic Excursions (MAGE), provides critical insights into glucose metabolism. While recognized as the gold standard for GV evaluation, MAGE’s prognostic value in critically ill stroke patients remains underexplored.</p> Methods <p>Using data from the Critical Care Medical Information Market IV database, patients were stratified by MAGE quartiles. The primary outcome was 30-day all-cause mortality (ACM), while secondary outcomes included 90-day and 180-day ACM. Plot Kaplan Meier curves to compare the results between groups. Cox proportional hazards regression and restricted cubic spline (RCS) were used to evaluate the relationship between MAGE and prognosis.</p> Results <p>The cohort (<i>n</i> = 2,677, mean age 69.4 ± 15.2 years, 49.1% female) demonstrated significant mortality associations. The Kaplan Meier curve shows that the higher the level of MAGE, the higher the risk of ACM at 30 days, 90 days, and 180 days (log rank <i>P</i> &lt; 0.0001). Cox regression analysis showed that patients with the highest quartile of MAGE had a significantly increased risk of death at these time points (<i>P</i> &lt; 0.05). RCS analysis showed a non-linear relationship (<i>P</i> &lt; 0.05) between MAGE and outcomes.</p> Conclusions <p>MAGE effectively predicts mortality in critically ill stroke patients. Systematic MAGE monitoring and maintaining glucose below threshold levels may improve survival outcomes. These findings emphasize the importance of tailoring GV management strategies in intensive care settings and support the use of MAGE as a standardized indicator for assessing GV in the acute phase of stroke to reduce preventable mortality in vulnerable populations.</p>

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Nonlinear relationship between mean amplitude of glycemic excursion and mortality in critically ill stroke patients

  • 期刊论文

  • 发表日期：

    2025年12月19日

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  • Yiqu Wei,
  • Wanqing Xu,
  • Shuo Yang,
  • Congfeng Zhang

摘要

Background

Glycemic variability (GV), assessed by the Mean Amplitude of Glycemic Excursions (MAGE), provides critical insights into glucose metabolism. While recognized as the gold standard for GV evaluation, MAGE’s prognostic value in critically ill stroke patients remains underexplored.

Methods

Using data from the Critical Care Medical Information Market IV database, patients were stratified by MAGE quartiles. The primary outcome was 30-day all-cause mortality (ACM), while secondary outcomes included 90-day and 180-day ACM. Plot Kaplan Meier curves to compare the results between groups. Cox proportional hazards regression and restricted cubic spline (RCS) were used to evaluate the relationship between MAGE and prognosis.

Results

The cohort (n = 2,677, mean age 69.4 ± 15.2 years, 49.1% female) demonstrated significant mortality associations. The Kaplan Meier curve shows that the higher the level of MAGE, the higher the risk of ACM at 30 days, 90 days, and 180 days (log rank P < 0.0001). Cox regression analysis showed that patients with the highest quartile of MAGE had a significantly increased risk of death at these time points (P < 0.05). RCS analysis showed a non-linear relationship (P < 0.05) between MAGE and outcomes.

Conclusions

MAGE effectively predicts mortality in critically ill stroke patients. Systematic MAGE monitoring and maintaining glucose below threshold levels may improve survival outcomes. These findings emphasize the importance of tailoring GV management strategies in intensive care settings and support the use of MAGE as a standardized indicator for assessing GV in the acute phase of stroke to reduce preventable mortality in vulnerable populations.