4.6 Article

Development and validation of a nomogram for the risk prediction of malignant cerebral edema after acute large hemispheric infarction involving the anterior circulation

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FRONTIERS IN NEUROLOGY
卷 14, 期 -, 页码 -

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FRONTIERS MEDIA SA
DOI: 10.3389/fneur.2023.1221879

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stroke; nomogram; malignant cerebral edema; large hemisphere infarction; ischemic stroke

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In this study, a nomogram was developed and validated for the early prediction of malignant cerebral edema (MCE) risk in patients with large hemisphere infarction (LHI). The nomogram, based on LASSO-logistic regression, demonstrated accuracy and usefulness in predicting MCE. It can serve as a practical tool for guiding clinical decision-making and treatment approaches in patients with LHI.
Background: Malignant cerebral edema (MCE) is a life-threatening complication of large hemisphere infarction (LHI). Therefore, a fast, accurate, and convenient tool for predicting MCE can guide triage services and facilitate shared decision-making. In this study, we aimed to develop and validate a nomogram for the early prediction of MCE risk in acute LHI involving the anterior circulation and to understand the potential mechanism of MCE. Methods: This retrospective study included 312 consecutive patients with LHI from 1 January 2019 to 28 February 2023. The patients were divided into MCE and non-MCE groups. MCE was defined as an obvious mass effect with >= 5 mm midline shift or basal cistern effacement. Least absolute shrinkage and selection operator (LASSO) and logistic regression were performed to explore the MCE-associated factors, including medical records, laboratory data, computed tomography (CT) scans, and independent clinic risk factors. The independent factors were further incorporated to construct a nomogram for MCE prediction. Results: Among the 312 patients with LHI, 120 developed MCE. The following eight factors were independently associated with MCE: Glasgow Coma Scale score (p = 0.007), baseline National Institutes of Health Stroke Scale score (p = 0.006), Alberta Stroke Program Early CT Score (p < 0.001), admission monocyte count (p = 0.004), white blood cell count (p = 0.002), HbA1c level (p < 0.001), history of hypertension (p = 0.027), and history of atrial fibrillation (p = 0.114). These characteristics were further used to establish a nomogram for predicting prognosis. The nomogram achieved an AUC-ROC of 0.89 (95% CI, 0.82-0.96). Conclusion: Our nomogram based on LASSO-logistic regression is accurate and useful for the early prediction of MCE after LHI. This model can serve as a precise and practical tool for clinical decision-making in patients with LHI who may require aggressive therapeutic approaches.

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