Correlation Between Glycemic Variability in Patients With Intracerebral Hemorrhage and Neurological Deterioration

Lichun Lu1, Xiangyi Yin1, Chen Wang1

  • 1Suzhou Research Center of Medical School, Suzhou Hospital, Affiliated Hospital of Medical School, Nanjing University, Suzhou, China.

Insights

High glycemic variability and older age predict neurological decline in intracerebral hemorrhage (ICH) patients. Monitoring blood sugar metrics like Time in Range (TIR), Mean Amplitude of Glycemic Excursions (MAGE), and Large Amplitude of Glycemic Excursions (LAGE) is crucial for better outcomes.

Area of Science:

  • Neurology
  • Endocrinology
  • Clinical Medicine

Background:

  • Glycemic variability significantly impacts patient prognosis in clinical practice.
  • Effective management of blood glucose levels is essential for patient outcomes.
  • Understanding the link between glycemic variability and neurological function is critical for intracerebral hemorrhage (ICH) care.

Purpose of the Study:

  • To investigate the correlation between glycemic variability and neurological function deterioration in ICH patients.
  • To provide evidence-based support for the clinical treatment and care of ICH patients.
  • To identify key predictors of neurological deterioration in ICH.

Main Methods:

  • 156 ICH patients were analyzed retrospectively.
  • National Institutes of Health Stroke Scale (NIHSS) scores were used to assess neurological function at admission and discharge.
  • Correlation and logistic regression analyses were performed on baseline characteristics and glycemic variability parameters.

Main Results:

  • Neurological deterioration occurred in 30.8% of ICH patients.
  • Significant associations were found between age, mean glucose, Time in Range (TIR), Mean Amplitude of Glycemic Excursions (MAGE), and Large Amplitude of Glycemic Excursions (LAGE) with neurological deterioration.
  • Age, mean glucose, TIR, MAGE, and LAGE were identified as significant predictors of neurological deterioration.

Conclusions:

  • Chronological age and glycemic control metrics are critical for prognostic evaluation in ICH patients.
  • Integrating these factors into clinical assessments can improve outcome prediction accuracy.
  • Tailored therapeutic strategies can be guided by considering age and glycemic control in ICH management.