Lack of association between hyperglycaemia at arrival and clinical outcomes in acute stroke patients treated with tissue plasminogen activator

The Impact of Diabetes Mellitus and Admission Hyperglycemia on Clinical Outcomes after Recanalization Therapies for Acute Ischemic Stroke: STAY ALIVE National Prospective Registry

It was previously reported that diabetes mellitus (DM) and admission hyperglycemia (aHG) were associated with poor clinical outcomes in patients with acute ischemic stroke (AIS) who were treated with intravenous thrombolysis (IVT) or mechanical thrombectomy (MT). Our study aimed to assess the prognostic effect of DM and aHG (≥7.8 mmol/L) on clinical outcomes in patients treated with recanalization therapies (IVT and MT). Our multicentric study was based on data from the prospective STAY ALIVE stroke registry between November 2017 and January 2020. We compared the demographic data, clinical parameters and time metrics between recanalized DM and non-DM groups, and we analyzed the impact of DM and aHG on 90-day functional outcome, 90-day mortality, symptomatic intracranial hemorrhage (sICH), and successful recanalization. Statistical analyses were also performed in two subgroups: (1) patients treated with IVT alone and (2) patients treated with MT. Altogether, we included 695 patients from the three participating stroke centers in Hungary. Regarding the overall population, patients with diabetes were older (72 vs. 67 years, p < 0.001) and comorbidities were more frequent. There were significant differences in the 90-day good functional outcome (48.9% vs. 66.7%, p < 0.001), 90-day mortality (21.9% vs. 11.6%, p < 0.001) and the rate of symptomatic intracranial hemorrhaging (sICH) (7.8% vs. 2.2%, p < 0.001) between the groups. Diabetes and aHG were independently associated with a poor clinical outcome (OR 2.02, 95% CI 1.31−3.11, p = 0.001; OR 2.09, 95% CI 1.39−3.14, p < 0.001) and mortality at 3 months (OR 2.45, 95% CI 1.35−4.47, p = 0.003; OR 2.42, 95% CI 1.37−4.28, p = 0.002) and sICH (OR 4.32, 95% CI 1.54−12.09, p = 0.005; OR 4.61, 95% CI 1.58−13.39, p = 0.005) in the overall population. However, the presence of DM and aHG was not correlated with successful reperfusion (OR 0.39, 95% CI 0.09−1.67, p = 0.205; OR 0.42, 95% CI 0.09−1.97, p = 0.274) after MT. Our study revealed that diabetes and hyperglycemia on admission were correlated with poor clinical outcomes at 3 months in patients with acute stroke regardless of the recanalization method. In addition, the variables were also associated with sICH after recanalization therapies. However, successful recanalization was not associated with DM and aHG in patients who underwent MT.

Prevalence of diabetes and its effects on stroke outcomes: A meta-analysis and literature review

AIMS/INTRODUCTION

Diabetes mellitus is an established risk factor for stroke and maybe associated with poorer outcomes after stroke. The aims of the present literature review were to determine: (i) the prevalence of diabetes in acute stroke patients through a meta-analysis; (ii) the association between diabetes and outcomes after ischemic and hemorrhagic stroke; and (iii) to review the value of glycated hemoglobin and admission glucose-based tests in predicting stroke outcomes.

MATERIALS AND METHODS

Ovid MEDLINE and EMBASE searches were carried out to find studies relating to diabetes and inpatient stroke populations published between January 2004 and April 2017. A meta-analysis of the prevalence of diabetes from included studies was undertaken. A narrative review on the associations of diabetes and different diagnostic methods on stroke outcomes was carried out.

RESULTS

A total of 66 eligible articles met inclusion criteria. A meta-analysis of 39 studies (n = 359,783) estimated the prevalence of diabetes to be 28% (95% confidence interval 26-31). The rate was higher in ischemic (33%, 95% confidence interval 28-38) compared with hemorrhagic stroke (26%, 95% confidence interval 19-33) inpatients. Most, but not all, studies found that acute hyperglycemia and diabetes were associated with poorer outcomes after ischemic or hemorrhagic strokes: including higher mortality, poorer neurological and functional outcomes, longer hospital stay, higher readmission rates, and stroke recurrence. Diagnostic methods for establishing diagnosis were heterogeneous between the reviewed studies.

CONCLUSIONS

Approximately one-third of all stroke patients have diabetes. Uniform methods to screen for diabetes after stroke are required to identify individuals with diabetes to design interventions aimed at reducing poor outcomes in this high-risk population.

C-R Relationship between Fasting Plasma Glucose and Unfavorable Outcomes in Patients of Ischemic Stroke withoutDiabetes

BACKGROUND

Limited data are available on the impact of fasting plasma glucose (FPG) on outcomes in nondiabetic acute ischemic stroke patients.

METHODS

The prospective, multi-center, and observational study was performed at 8 hospitals in the Liaoning Province between 2015-2016, sought to elucidate the relationship between FPG and the 6-month functional outcomes in nondiabetic acute ischemic stroke patients. The primary effect measure was the adjusted odds ratio for a shift in the direction of unfavorable outcome on the modified Rankin Scale (mRS) score at 6 months, estimated with an ordinal logistic regression, and adjusted for common prognostic factors. Finally, we employed a restricted cubic spline function of linear model to characterize concentration-response (C-R) relationships between FPG and outcomes.

RESULTS

A total of 1260 consecutive patients were enrolled, 48.9% of patients had FPG levels >6.1mmol/L. A total of 282 (22.4%) patients achieved an unfavorable neurologic outcome. Patients achieving an unfavorable neurologic outcome had significantly higher levels of FPG than those achieving a favorable neurologic outcome (6.47mmol/L versus 7.02 mmol/L). FPG was significantly related to an unfavorable neurologic outcome in nondiabetic acute ischemic stroke patients. The C-R curve showed a nonlinear relation between FPG and 6-month mRS with the nadir at 5.9mmol/L. Moreover, the likelihood of unfavorable outcome increased by 8.5% for each 1mmol/L increase in FPG.

CONCLUSIONS

Early identification and prompt hyperglycemia management should be considered to improve the functional outcomes during the early poststroke stage.

Long-term outcomes in older patients with hyperglycemia on admission for ischemic stroke

AIMS

Evaluate the association between admission blood glucose (ABG) and mortality in older patients with or without diabetes mellitus (DM) hospitalized for acute ischemic stroke (AIS).

METHODS

Observational data of patients ≥65years, admitted for AIS between January 2011 and December 2013. ABG levels were classified to categories: ≤70 (low), 70-110 (normal), 111-140 (mildly elevated), 141-180mg/dl (moderately elevated) and >180mg/dl (markedly elevated). Main outcome was all-cause mortality at the end-of-follow-up.

RESULTS

Cohort included 854 patients, 347 with (mean±SD age 80±8, 44% male), and 507 without DM (mean±SD age 78±8, 53% male). There was a significant interaction between DM, ABG and mortality at end-of-follow-up (p≤0.05). In patients without DM there was a dose-dependent association between ABG category and mortality: adjusted hazard ratios (95% CI) compared to normal ABG were 1.8 (1.2-2.8), 2.9 (1.6-5.2) and 4.5 (2.1-9.7), respectively, for mildly, moderately and markedly elevated ABG. In patients with DM there was no association between ABG and mortality. There was no interaction between DM, ABG and in-hospital mortality or length of stay (LOS). Irrespective of DM status, compared to normal ABG levels, increased ABG category was associated with increased in-hospital mortality: adjusted odds ratios were 3.9 (1.1-13.4), 7.0 (1.8-28.1), and 20.3 (4.6-89.6) with mildly, moderately and markedly elevated ABG, respectively. Mean LOS was 6±5, 7±8, 8±7, and 8±8days, respectively.

CONCLUSION

In older patients without DM hospitalized for AIS, elevated ABG is associated with increased long-term mortality. Irrespective of DM status, elevated ABG was associated with increased in-hospital mortality and LOS.

Higher fasting glucose next day after intravenous thrombolysis is independently associated with poor outcome in acute ischemic stroke

BACKGROUND

We aimed to test the outcome-predictive power of routine fasting glucose (FG) obtained at second day after onset in intravenous thrombolysis (IVT) acute ischemic stroke (AIS) patients.

METHODS

We identified AIS patients presenting to our institution between December 2011 and July 2013 within 4.5 hours of onset, who received admission glucose (AG) before IVT, FG, and glycated hemoglobin (HbA1c) the second day after admission, from our prospectively recorded stroke database. Multivariate logistic regression was used to assess the association of FG and 90-day modified Rankin Scale (mRS).

RESULTS

Between December 2011 and July 2013, a total of 166 AIS patients received intravenous plasminogen activator. Of those, 119 patients who have AG before IVT, FG, and HbA1c the second day were included in the study. FG independently predicted 90-day clinical unfavorable outcome (mRS, 3-6 with an odds ratio of 1.576; 95% confidence interval [CI], 1.053-2.358; P = .027). This association was not significant in AG (P = .714), HbA1c (P = .655), and history of diabetes (P = .547). In receiver operating characteristic analysis, increased FG was associated with 90-day mRS (3-6) with an area under curve of .72, (95% CI, .65-.9; P = .001).

CONCLUSIONS

FG is a powerful predictor associated with the outcome in IVT-treated AIS patients independent of AG and HbA1c.

Diabetes Mellitus, Admission Glucose, and Outcomes After Stroke Thrombolysis

Background and Purpose—

The potential detrimental effect of diabetes mellitus and admission glucose level (AGL) on outcomes after stroke thrombolysis is unclear. We evaluated outcomes of patients treated by intravenous and/or intra-arterial therapy, according to diabetes mellitus and AGL.

Methods—

We analyzed data from a patient registry (n=704) and conducted a systematic review of previous observational studies. The primary study outcome was the percentage of patients who achieved a favorable outcome (modified Rankin score ≤2 at 3 months).

Results—

We identified 54 previous reports that evaluated the effect of diabetes mellitus or AGL on outcomes after thrombolysis. In an unadjusted meta-analysis that included our registry data and previous available observational data, diabetes mellitus was associated with less favorable outcome (odds ratio [OR], 0.76; 95% confidence interval [CI], 0.73–0.79) and more symptomatic intracranial hemorrhage (OR, 1.38; 95% CI, 1.21–1.56). However, in multivariable analysis, diabetes mellitus remained associated with less favorable outcome (OR, 0.77; 95% CI, 0.69–0.87) but not with symptomatic intracranial hemorrhage (OR, 1.11; 95% CI, 0.83–1.48). In unadjusted and in adjusted meta-analysis, higher AGL was associated with less favorable outcome and more symptomatic intracranial hemorrhage; the adjusted OR (95% CI) per 1 mmol/L increase in AGL was 0.92 (0.90–0.94) for favorable outcome, and 1.09 (1.04–1.14) for symptomatic intracranial hemorrhage.

Conclusions—

These results confirm that AGL and history of diabetes mellitus are associated with poor clinical outcome after thrombolysis. AGL may be a surrogate marker of brain infarction severity rather than a causal factor. However, randomized controlled evidences are needed to address the significance of a tight glucose control during thrombolysis on clinical outcome.

Prediction of intracerebral hemorrhage following thrombolytic therapy for acute ischemic stroke using multiple artificial neural networks

OBJECTIVES

Artificial neural networks (ANNs) have been increasingly used in diagnosis and the prediction of outcome, mortality, and risk factors in ischemic stroke. Each model may have different accuracy, sensitivity, and specificity in processing the same clinical information. Thus, using only one model of ANNs may mislead the prediction. The present study aimed to predict symptomatic intracerebral hemorrhage (SICH) following thrombolysis in acute ischemic stroke based on clinical, laboratory, and imaging data using multiple ANN models.

METHODS

Models for radial basis function (RBF), multilayer perceptron (MLP), probabilistic neural network (PNN), and support vector machine (SVM) were generated to analyze 194 datasets with 29 predictive variables. The relative importance of each predictor variable was calculated using sensitivity analysis.

RESULTS

Comparison among the models based on the areas under the receiver operating characteristic curves (AUC) showed no significantly statistical difference in predictive performance among RBF, MLP, and PNN. PNN showed significantly better performance than SVM. With a minimum importance score of 50 together with an AUC value ≥0·50, three models identified stroke subtype as an important predictive variable for SICH. Other potential predictors were stroke location, prothrombin time, low-density-lipoprotein cholesterol, diastolic blood pressure, International Normalized Ratio, and brain computed tomography findings.

DISCUSSION

Although ANN models showed similar performance, the classification results were not totally alike, suggesting an advantage of using multiple classification models over a single model. The predictive results are supported by previous statistical studies on different datasets, suggesting generalizability of the utility of ANN analyses.