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Elevated Fasting Blood Glucose Is Predictive of Poor Outcome in Non-Diabetic Stroke Patients: A Sub-Group Analysis of SMART.

ABSTRACT: Although increasing evidence suggests that hyperglycemia following acute stroke adversely affects clinical outcome, whether the association between glycaemia and functional outcome varies between stroke patients with\without pre-diagnosed diabetes remains controversial. We aimed to investigate the relationship between the fasting blood glucose (FBG) and the 6-month functional outcome in a subgroup of SMART cohort and further to assess whether this association varied based on the status of pre-diagnosed diabetes.Data of 2862 patients with acute ischemic stroke (629 with pre-diagnosed diabetics) enrolled from SMART cohort were analyzed. Functional outcome at 6-month post-stroke was measured by modified Rankin Scale (mRS) and categorized as favorable (mRS:0-2) or poor (mRS:3-5). Binary logistic regression model, adjusting for age, gender, educational level, history of hypertension and stroke, baseline NIHSS and treatment group, was used in the whole cohort to evaluate the association between admission FBG and functional outcome. Stratified logistic regression analyses were further performed based on the presence/absence of pre-diabetes history.In the whole cohort, multivariable logistical regression showed that poor functional outcome was associated with elevated FBG (OR1.21 (95%CI 1.07-1.37), p = 0.002), older age (OR1.64 (95% CI1.38-1.94), p<0.001), higher NIHSS (OR2.90 (95%CI 2.52-3.33), p<0.001) and hypertension (OR1.42 (95%CI 1.13-1.98), p = 0.04). Stratified logistical regression analysis showed that the association between FBG and functional outcome remained significant only in patients without pre-diagnosed diabetes (OR1.26 (95%CI 1.03-1.55), p = 0.023), but not in those with premorbid diagnosis of diabetes (p = 0.885).The present results demonstrate a significant association between elevated FBG after stroke and poor functional outcome in patients without pre-diagnosed diabetes, but not in diabetics. This finding confirms the importance of glycemic control during acute phase of ischemic stroke especially in patients without pre-diagnosed diabetes. Further investigation for developing optimal strategies to control blood glucose level in hyperglycemic setting is therefore of great importance.ClinicalTrials.gov NCT00664846.

SUBMITTER: Yao M

PROVIDER: S-EPMC4975495 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Elevated Fasting Blood Glucose Is Predictive of Poor Outcome in Non-Diabetic Stroke Patients: A Sub-Group Analysis of SMART.

Yao Ming M Ni Jun J Zhou Lixin L Peng Bin B Zhu Yicheng Y Cui Liying L

PloS one 20160805 8

<h4>Background</h4>Although increasing evidence suggests that hyperglycemia following acute stroke adversely affects clinical outcome, whether the association between glycaemia and functional outcome varies between stroke patients with\without pre-diagnosed diabetes remains controversial. We aimed to investigate the relationship between the fasting blood glucose (FBG) and the 6-month functional outcome in a subgroup of SMART cohort and further to assess whether this association varied based on t ...[more]

PMID: 27494527

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Project description:BackgroundHyperglycemia is a known predictor of negative outcomes in stroke. Several glycemic measures, including admission random glucose, fasting glucose, and glycated hemoglobin (HbA1c), have been associated with bad neurological outcomes in acute ischemic stroke, particularly in nondiabetic patients. However, the predictive power of these glycemic measures is yet to be investigated.MethodsThis retrospective study enrolled 484 patients with acute ischemic stroke from January 2009 to March 2013, and complete records of initial stroke severity, neurological outcomes at three months, and glycemic measures were evaluated. We examined the predictive power of admission random glucose, fasting glucose, and HbA1c for neurological outcomes in acute ischemic stroke. Furthermore, subgroup analyses of nondiabetic patients and patients with diabetes were performed separately.ResultsReceiver operating characteristic (ROC) analysis revealed that admission random glucose and fasting glucose were significant predictors of poor neurological outcomes, whereas HbA1c was not (areas under the ROC curve (AUCs): admission random glucose = 0.564, p = 0.026; fasting glucose = 0.598, p = 0.001; HbA1c = 0.510, p = 0.742). Subgroup analyses of nondiabetic patients and those with diabetes revealed that only fasting glucose predicts neurological outcomes in patients with diabetes, and the AUCs of these three glycemic measures did not differ between the two groups. A multivariate logistic regression analysis of the study patients indicated that only age, initial stroke severity, and fasting glucose were independent predictors of poor neurological outcomes, whereas admission random glucose and HbA1c were not (adjusted odds ratio: admission random glucose = 1.002, p = 0.228; fasting glucose = 1.005, p = 0.039; HbA1c = 1.160, p = 0.076). Furthermore, subgroup multivariate logistic regression analyses of nondiabetic patients and those with diabetes indicated that none of the three glycemic measures were associated with poor neurological outcomes.DiscussionFasting glucose is an independent predictor of poor neurological outcomes in patients with acute ischemic stroke and had greater predictive power than that of admission random glucose and HbA1c. The predictive power of glycemic measures for poor neurological outcomes did not differ significantly between the nondiabetic patients and those with diabetes.

Project description:BackgroundLactate dehydrogenase (LDH) is associated with the prognosis of many diseases, but the relationship between LDH and the poor prognosis (recurrence and death) of acute ischemic stroke (AIS) has not been fully clarified. This study aimed to investigate the association between admission LDH level and poor prognosis in patients with AIS.MethodsThis retrospective study enrolled AIS patients treated in Taizhou Hospital of Zhejiang Province from July 2019 to December 2019. Poor prognosis included AIS recurrence and all-cause death at 3, 6, and 18 months. The correction between LDH and poor prognosis or all-cause death was assessed. Lasso Cox expression and multivariate Cox expression analyses were used to evaluate the association of LDH with the risk of poor prognosis and all-cause death, respectively. A nomogram was constructed to evaluate the predictive Values of LDH for the poor prognosis and all-cause death of AIS.Results732 patients were included in the study. Multivariate analysis shows that admission LDH levels were significantly correlated with poor prognosis [odds ratio (OR),1.003; 95% confidence interval (95% CI), 1.001-1.005; P = 0.001] and all-cause death (OR, 1.005; 95% CI, 1.000-1.009; P = 0.031). The correlation analysis showed that admission LDH level was positively correlated with National Institutes of Health Stroke Scale (NIHSS) score and modified Rankin Scale (mRS) score. Time-dependent receiver operating characteristic (td-ROC) curves analysis showed that the AUC values of admission LDH level for predicting prognosis of AIS patients in 3-month, 6-month, 12-month and 18-month were 0.706 (95% CI, 0.604-0.810), 0.653 (95% CI, 0.583-0.723), 0.616 (95% CI, 0.556-60676) and 0.610 (95% CI, 0.552-0.680), respectively. And td-ROC also showed that the AUC values of admission LDH level for predicting all-cause death of AIS patients in 3-month, 6-month,12-month and 18-month were 0.861 (95% CI, 0.764-0.958), 0.824 (95% CI, 0.753-0.890), 0.726 (95% CI, 0.633-0.819) and 0.715 (95% CI, 0.622-0.807), respectively. The nomograms were constructed to create the predictive models of the poor prognosis and all-cause death of AIS.ConclusionHigher LDH levels are independently associated with poor prognosis and all-cause death of AIS.

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Elevated Fasting Blood Glucose Is Predictive of Poor Outcome in Non-Diabetic Stroke Patients: A Sub-Group Analysis of SMART.

Publications

Elevated Fasting Blood Glucose Is Predictive of Poor Outcome in Non-Diabetic Stroke Patients: A Sub-Group Analysis of SMART.

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