Machine Learning-Based Etiologic Subtyping of Ischemic Stroke Using Circulating Exosomal microRNAs.

Ischemic stroke is a major cause of mortality worldwide. Proper etiological subtyping of ischemic stroke is crucial for tailoring treatment strategies. This study explored the utility of circulating microRNAs encapsulated in extracellular vesicles (EV-miRNAs) to distinguish the following ischemic stroke subtypes: large artery atherosclerosis (LAA), cardioembolic stroke (CES), and small artery occlusion (SAO). Using next-generation sequencing (NGS) and machine-learning techniques, we identified differentially expressed miRNAs (DEMs) associated with each subtype. Through patient selection and diagnostic evaluation, a cohort of 70 patients with acute ischemic stroke was classified: 24 in the LAA group, 24 in the SAO group, and 22 in the CES group. Our findings revealed distinct EV-miRNA profiles among the groups, suggesting their potential as diagnostic markers. Machine-learning models, particularly logistic regression models, exhibited a high diagnostic accuracy of 92% for subtype discrimination. The collective influence of multiple miRNAs was more crucial than that of individual miRNAs. Additionally, bioinformatics analyses have elucidated the functional implications of DEMs in stroke pathophysiology, offering insights into the underlying mechanisms. Despite limitations like sample size constraints and retrospective design, our study underscores the promise of EV-miRNAs coupled with machine learning for ischemic stroke subtype classification. Further investigations are warranted to validate the clinical utility of the identified EV-miRNA biomarkers in stroke patients.

Comparative Cadaveric Analysis for Surgical Corridor and Maneuverability: Far-Lateral Approach and Its Transcondylar Extension.

OBJECTIVE: The necessity of partial occipital condyle (OC) resection for lesions in the ventral craniocervical junction is debatable. This study's purpose was to compare the surgical exposure of the classic far-lateral approach (FLA) and transcondylar FLA. METHODS: The classic FLA and transcondylar FLA were performed in 12 human cadaveric heads (24 sides). The surgical corridor of 3 levels (a: vagus nerve, b: from the midpoint of proximal ends of the vagus and hypoglossal nerves to the midpoint of the distal ends of each nerve, c: hypoglossal nerve) and the maneuverability (the area between neurovascular structures that limits instrumental maneuvers) were measured after each approach. RESULTS: The surgical corridors were significantly greater in transcondylar FLA than in classic FLA (a: 14.4 ± 3.4 mm vs. 17.1 ± 4.4 mm, P < 0.001; b: 8.6 ± 2.9 mm vs. 11.2 ± 4.1 mm, P < 0.001; c: 5.5 ± 2.2 mm vs. 7.7 ± 2.8 mm, P < 0.001). Transcondylar FLA also provided greater maneuverability than classic FLA (73.2 ± 23.9 mm2 vs. 94.9 ± 32.2 mm2, P < 0.001). The increased length of the surgical corridor was greatest in a (a: 2.7 ± 2.3 mm, b: 2.6 ± 2.0 mm, c: 2.2 ± 1.4 mm). However, the rate of increase was greatest in c (a: 18.9 ± 16.4%, b: 30.4 ± 26.2%, c: 44.8 ± 27.2%). The area of increased maneuverability was 21.7 ± 20.3 mm2 (31.1 ± 27.8%) after partial OC resection. CONCLUSIONS: Transcondylar FLA can significantly increase surgical exposure compared with the classic FLA, although also increasing surgical complications. Therefore, the surgical approach should be individualized according to each lesion and patient. The results of our study may assist in surgical decision-making regarding the need for OC resection.

Factors Predicting Ventricle Volume Increase After Aneurysmal Clipping in Patients with Subarachnoid Hemorrhage.

OBJECTIVE: Although many studies have evaluated risk factors associated with hydrocephalus after aneurysmal subarachnoid hemorrhage, specific ventricle volume changes after subarachnoid hemorrhage have not been evaluated. We sought to evaluate factors predicting ventricle volume enlargement in patients with aneurysmal subarachnoid hemorrhage by measuring ventricle volume with a validated, semiautomated tool. METHODS: Uni- and multivariable linear regression analyses were conducted with the follow-up ventricle volume as the dependent variable and the duration between subarachnoid hemorrhage occurrence and follow-up imaging as the independent variable, classified by the use of various predictive factors. A logistic regression model was used to calculate the odds ratio for the greater ventricle volume group compared with the lower ventricle volume group based on predictive factors. RESULTS: We included 173 participants with a mean age of 55.5 years. Overall, an approximate increase in ventricle volume of 1.1 mL was observed daily within 60 days of clipping due to subarachnoid hemorrhage. In the multivariate logistic regression analysis, patients in the first and second tertile groups for body mass index showed approximately a 5.9- and 4.1-fold increased risk of greater follow-up ventricle volume, respectively, compared with the third tertile group for body mass index within 60 days of subarachnoid hemorrhage. CONCLUSIONS: We found that greater body mass index independently predicted suppression of ventricle volume growth, owing to maintenance of subarachnoid trabeculae structures after subarachnoid hemorrhage. Further studies are needed to confirm our findings.