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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.
Abstract:
Background: Glycemic variability and its management hold significant prognostic implications in clinical practice for patient outcomes. The aim of this study is to analyze the correlation between glycemic variability and the deterioration of neurological function in patients with intracerebral hemorrhage (ICH), to provide evidence-based support for the treatment and care of clinical ICH patients. Methods: Patients with ICH admitted to our hospital between January 2022 and August 2024 were subjected to the National Institutes of Health Stroke Scale (NIHSS) scoring upon admission and discharge. A comparative analysis of baseline characteristics and glycemic variability parameters was conducted. Results: A total of 156 patients with ICH were included. The incidence of neurological deterioration in ICH patients was 30.8%. Correlation analysis revealed significant associations between age (r = 0.602), mean glucose levels (r = 0.623), Time in Range (TIR) (r = 0.589), Mean Amplitude of Glycemic Excursions (MAGE) (r = 0.608), and Large Amplitude of Glycemic Excursions (LAGE) (r = 0.634) with the occurrence of neurological deterioration. Logistic regression analysis identified age (OR = 2.512, 95%CI: 1.924-3.006), mean glucose (OR = 2.743, 95%CI: 2.101-3.286), TIR (OR = 3.204, 95%CI: 2.985-3.607), MAGE (OR = 3.029, 95%CI: 2.601-3.748), and LAGE (OR = 2.768, 95%CI: 2.245-3.103) as significant predictors of neurological deterioration in ICH patients. Conclusion: This finding underscores the critical importance of considering both chronological age and glycemic control metrics in the prognostic evaluation of ICH patients. Integrating these factors into clinical assessments may enhance the accuracy of predicting patient outcomes and guide tailored therapeutic strategies.
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