Dataset Information

Paradoxical effect of obesity on hemorrhagic transformation after acute ischemic stroke.

ABSTRACT:

Background

Among the patients with established coronary artery diseases, obese patients tend to have a more favorable prognosis, which is called as obesity paradox. Interestingly, mildly obese patients who underwent coronary revascularization had a lower risk of bleeding. In this context, we have investigated the association between obesity and hemorrhagic transformation (HTf) after acute ischemic stroke.

Methods

A total of 365 patients with first-ever acute ischemic stroke were included in this study. Demographic, clinical and radiological information was collected and HTf was evaluated through follow-up T2*-weighted gradient-recalled echo MRI performed usually within 1 week after occurrence of stroke. Body mass index was calculated, and obesity was defined using the World Health Organization Western Pacific Regional Office criteria.

Results

The HTf was identified in 59 patients (16.2%). As the severity of obesity increased, the occurrence of HTf decreased. Compared with the normal weight group and after controlling possible confounders including acute and previous treatment, stroke severity and subtype, the risk of HTf decreased significantly in the obese group (odds ratio, 0.39; 95% confidence interval, 0.17-0.87).

Conclusions

The better outcome for HTf seen in obese patients suggests the existence of a "bleeding-obesity paradox" in acute ischemic stroke.

SUBMITTER: Kim CK

PROVIDER: S-EPMC3848776 | biostudies-literature | 2013 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Paradoxical effect of obesity on hemorrhagic transformation after acute ischemic stroke.

Kim Chi Kyung CK Ryu Wi-Sun WS Kim Beom Joon BJ Lee Seung-Hoon SH

BMC neurology 20130923

<h4>Background</h4>Among the patients with established coronary artery diseases, obese patients tend to have a more favorable prognosis, which is called as obesity paradox. Interestingly, mildly obese patients who underwent coronary revascularization had a lower risk of bleeding. In this context, we have investigated the association between obesity and hemorrhagic transformation (HTf) after acute ischemic stroke.<h4>Methods</h4>A total of 365 patients with first-ever acute ischemic stroke were i ...[more]

PMID: 24053109

Similar Datasets

Project description:ObjectiveTo develop and validate a model based on the radiomics features of the infarct areas on non-contrast-enhanced CT to predict hemorrhagic transformation (HT) in acute ischemic stroke.Materials and methodsA total of 118 patients diagnosed with acute ischemic stroke in two centers from January 2019 to February 2022 were included. The radiomics features of infarcted areas on non-contrast-enhanced CT were extracted using 3D-Slicer. A univariate analysis and the least absolute shrinkage and selection operator (LASSO) were used to select features, and the radiomics score (Rad-score) was then constructed. The predictive model of HT was constructed by analyzing the Rad-score and clinical and imaging features in the training cohort, and it was verified in the validation cohort. The model was evaluated with the receiver operating characteristic curve, calibration curve and decision curve, and the prediction performance of the model in different scenarios was further discussed hierarchically.ResultsOf the 118 patients, 52 developed HT, including 21 cases of hemorrhagic infarct (HI) and 31 cases of parenchymal hematoma (PH). The Rad-score was constructed from five radiomics features and was the only independent predictor for HT. The predictive model was constructed from the Rad-score. The area under the curve (AUCs) of the model for predicting HT in the training and validation cohorts were 0.845 and 0.750, respectively. Calibration curve and decision curve analyses showed that the model performed well. Further analysis found that the model predicted HT for different infarct sizes or treatment methods in the training and validation cohorts with 78.3 and 71.4% accuracy, respectively. For all samples, the model predicted an AUC of 0.754 for HT in patients within 4.5 h since stroke onset, and predicted an AUC of 0.648 for PH.ConclusionThis model, which was based on CT radiomics features, could help to predict HT in the setting of acute ischemic stroke for any infarct size and provide guiding suggestions for clinical treatment and prognosis evaluation.

Dataset Information

Paradoxical effect of obesity on hemorrhagic transformation after acute ischemic stroke.

Background

Methods

Results

Conclusions

Publications

Paradoxical effect of obesity on hemorrhagic transformation after acute ischemic stroke.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets