Scholarlink

Purpose <p>To explore how diabetes influences the association between stress hyperglycemia (SH) and functional outcomes in acute ischemic stroke (AIS), and to develop a nomogram based on the stress hyperglycemia ratio (SHR) to predict the prognosis of AIS patients.</p> Methods <p>Patients were divided into diabetic mellitus (DM) and non-diabetic mellitus (non-DM) groups. SH was calculated using the ratio of fasting blood sugar (FBG) to glycosylated hemoglobin A1c (HbA1c). Poor functional outcomes were defined as a modified Rankin Scale (mRS) score &gt; 2 at a 3-month follow-up. Multivariable logistic regression analysis was used to identify the relationship between SHR and functional outcomes in diabetic and non-diabetic groups. Least Absolute Shrinkage Selection Operator (LASSO) regression analysis and logistic regression analysis were employed to build a nomogram.</p> Results <p>In the DM group, severe stress hyperglycemia showed no significant association with poor function outcomes at 3&#xa0;months. However, in the non-DM group, severe stress hyperglycemia was associated with poor function outcomes [odds ratio (OR) = 2.21, 95% confidence interval CI 1.61–3.02, p &lt; 0.001]. After adjusting for covariates, the differences remained statistically significant (adjusted OR = 1.62, 95% CI 1.09–2.42, p = 0.0181). Lasso regression identified 8 predictive factors, while logistic regression highlighted age, NIHSS, and SHR as independent predictors, forming a nomogram. The receiver operating characteristic curve assessed the discriminative ability of the nomogram, calibration, and clinical decision curves to evaluate model fitting and net benefit.</p> Conclusion <p>Severe stress hyperglycemia is linked to worse outcomes in non-diabetic patients but not significantly correlated in diabetic patients. A nomogram incorporating age, SHR, and NIHSS predicts poor outcomes in non-diabetic patients.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Stress hyperglycemia ratio predicts outcome in stroke patients without diabetes and builds a nomogram: a multi-center retrospective cohort study in a Chinese population

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年1月15日

查看全文
  • Manjuan Yao,
  • Shiyu Hu,
  • Shaoling Li,
  • Yuqi Liao,
  • Lijie Ren

摘要

Purpose

To explore how diabetes influences the association between stress hyperglycemia (SH) and functional outcomes in acute ischemic stroke (AIS), and to develop a nomogram based on the stress hyperglycemia ratio (SHR) to predict the prognosis of AIS patients.

Methods

Patients were divided into diabetic mellitus (DM) and non-diabetic mellitus (non-DM) groups. SH was calculated using the ratio of fasting blood sugar (FBG) to glycosylated hemoglobin A1c (HbA1c). Poor functional outcomes were defined as a modified Rankin Scale (mRS) score > 2 at a 3-month follow-up. Multivariable logistic regression analysis was used to identify the relationship between SHR and functional outcomes in diabetic and non-diabetic groups. Least Absolute Shrinkage Selection Operator (LASSO) regression analysis and logistic regression analysis were employed to build a nomogram.

Results

In the DM group, severe stress hyperglycemia showed no significant association with poor function outcomes at 3 months. However, in the non-DM group, severe stress hyperglycemia was associated with poor function outcomes [odds ratio (OR) = 2.21, 95% confidence interval CI 1.61–3.02, p < 0.001]. After adjusting for covariates, the differences remained statistically significant (adjusted OR = 1.62, 95% CI 1.09–2.42, p = 0.0181). Lasso regression identified 8 predictive factors, while logistic regression highlighted age, NIHSS, and SHR as independent predictors, forming a nomogram. The receiver operating characteristic curve assessed the discriminative ability of the nomogram, calibration, and clinical decision curves to evaluate model fitting and net benefit.

Conclusion

Severe stress hyperglycemia is linked to worse outcomes in non-diabetic patients but not significantly correlated in diabetic patients. A nomogram incorporating age, SHR, and NIHSS predicts poor outcomes in non-diabetic patients.