Background: Neuroimaging plays a vital role in the diagnosis of intracerebral hemorrhage (ICH) and in identifying the underlying etiology for appropriate therapeutic approach. This study aims to determine the significance and potential advantages of using early magnetic resonance imaging (MRI) as a diagnostic tool for ICH.
Methods: This retrospective study included 359 patients with ICH treated at the Department of Neurology, Mannheim University Hospital between January 2017 and December 2021. Patient characteristics, stroke severity and imaging procedures were descriptively analyzed. Factors associated with the choice of imaging modalities were evaluated. The etiology of hemorrhage was retrospectively analyzed using the existing data. We recorded the reassignment of ICH etiology by comparing the assessment after first sole review of CT scan and then subsequent MRI review. The overall rate of reassignments and the reassignments per CT-based initial etiology were analyzed.
Results: In the sample of 359 patients with ICH (mean age 73.1 years, 55.4% male), patients receiving an additional MRI were significantly younger (p < .001) and were less severely affected by stroke (median NIHSS score 5 vs. 15, p < .001). MRI was performed significantly less frequently in patients who died during hospitalization (11.7% vs. 63.9%, p < .001). MRI led to a reassignment of ICH etiology in 48.2% of cases (80/166), uncovering unknown underlying causes in 69% of cases (49/71). Reassignment occurred most frequently in patients with a CT-based diagnosis of hypertensive ICH (18/50). The most frequent reassigned etiologies after MR imaging were cerebral amyloid angiopathy (CAA; 36 patients) and secondary hemorrhage of an ischemic stroke (30 patients).
Conclusions: Early MR imaging in patients with ICH improves the determination of underlying etiology and the conception of an appropriate treatment approach, potentially contributing to better patient outcomes.
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http://dx.doi.org/10.1186/s12883-024-03992-7 | DOI Listing |
Front Pediatr
December 2024
Department of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.
Background: Premature births has imposed substantial burdens on medical resources. Consequently, a specialized team was established and a model focused on early intervention, namely the Delivery Room Intensive Care Unit (DICU) emphasizing "care, support, and treatment" was introduced and its impact on the morbidity and mortality outcomes of newborns was assessed. Additionally, we aimed to develop a nomogram model for predicting the risk of intraventricular hemorrhage (IVH) in preterm infants.
View Article and Find Full Text PDFNeurocrit Care
January 2025
Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No.119 South 4th Ring West Road, Fengtai District, Beijing, China.
Background: Microcirculatory dysfunction is one of the most important pathophysiology mechanisms of global cerebral edema (GCE) after aneurysmal subarachnoid hemorrhage (aSAH). Data regarding the impact of microcirculatory dysfunction on persistent GCE following aSAH are currently lacking. The aim of our study was to investigate whether microcirculatory dysfunction is correlated with persistent GCE in patients with aSAH across different age groups.
View Article and Find Full Text PDFNeurosurg Rev
January 2025
Department of Neurosurgery and Spine Surgery, University Hospital Essen, University of Duisburg-Essen, Essen, Germany.
Poor-grade aneurysmal subarachnoid hemorrhage (PGASAH) is associated with high mortality and morbidity despite advanced treatments. Accurate prediction of prognosis remains a clinical challenge. This study aimed to identify independent risk factors and develop a predictive nomogram for unfavorable outcomes in PGASAH patients.
View Article and Find Full Text PDFNeurosurg Rev
January 2025
Department of Medicine, Surgery, and Pharmacy University of Sassari, Sassari, SD, Italy.
It is feasible to predict delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage (aSAH) using Artificial intelligence (AI) algorithms, which may offer significant improvements in early diagnosis and patient management. This systematic review and meta-analysis evaluate the efficacy of machine learning (ML) in predicting DCI, aiming to integrate complex clinical data to enhance diagnostic accuracy. We searched PubMed, Scopus, Web of science, and Embase databases without restrictions until June 2024, applying PRISMA guidelines.
View Article and Find Full Text PDFAm J Case Rep
January 2025
Department of Neurosurgery, Denver Health Hospital Authority, Denver, CO, USA.
BACKGROUND Decompressive craniectomy is a common life-saving intervention in the setting of elevated intracranial pressure. Cranioplasty restores the calvarium and intracranial physiology once swelling recedes. Cranioplasty is often thought of as a low-risk intervention.
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