We studied the correlations between the pattern of weakness, stroke type, topography, and etiology in 255 patients whose first stroke was manifested by isolated hemiparesis. They represented 14% of consecutively admitted stroke patients. The weakness distributions were as follows: face, upper limb, and lower limb (FUL) (50%); face and upper limb (FU) (29%); upper limb (U) (10%); and upper and lower limb (UL) (9%). Twenty-nine percent of the patients had dysarthria, which was of no localizing value. Less than one half of the patients had a deep infarct, and one third had a potential embolic source from the heart or large arteries. Logistic regression analysis showed that history of hypertension and type of weakness distribution were the main factors accounting for lesion localization: patients with FUL distribution and hypertension had a 90% probability of deep infarct; patients either with FUL distribution but no hypertension or with UL distribution and hypertension each had 70% probability of deep infarct. Pure motor monoparesis was almost never caused by a deep infarct. We suggest that the assumption of a lacunar etiology to a pure motor stroke should be applied only to patients with FUL involvement.
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http://dx.doi.org/10.1212/wnl.42.4.789 | DOI Listing |
Cardiovasc Drugs Ther
December 2024
Vascular Surgery Department, General Surgery Center, First Hospital of Jilin University, Changchun City, Jilin Province, P.R. China.
Purpose: This meta-analysis aimed to conduct a systematic evaluation of the comparative efficacy and safety of new oral anticoagulants (NOACs) versus warfarin for the treatment of deep venous thrombosis (DVT).
Methods: A systematic computerized search of databases including PubMed, Medline, Web of Science, Embase, Cochrane Library, and www.
Clinicaltrials: gov .
J Neuropathol Exp Neurol
December 2024
Department of Pathology and Laboratory Medicine, University of California Davis, Sacramento, CA, United States.
Microinfarcts and microhemorrhages are characteristic lesions of cerebrovascular disease. Although multiple studies have been published, there is no one universal standard criteria for the neuropathological assessment of cerebrovascular disease. In this study, we propose a novel application of machine learning in the automated screening of microinfarcts and microhemorrhages.
View Article and Find Full Text PDFThromb Res
December 2024
Department of Oncology Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China. Electronic address:
Background: Immune checkpoint inhibitors (ICIs), which offer previously unknown therapeutic advantages, have revolutionized cancer treatment. However, the risk of thromboembolic events (TEEs) associated with ICIs remains unclear. The aim of this network meta-analysis (NMA) was to evaluate the incidence of TEEs in cancer patients receiving different treatment regimens.
View Article and Find Full Text PDFOrphanet J Rare Dis
December 2024
Department of Pathology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Zhongshan Road 321#, Nanjing, 210008, Jiangsu, China.
Background And Objectives: Mitochondrial encephalomyopathy with lactic acidosis and stroke-like episodes (MELAS) syndrome is a maternally inherited mitochondrial disorder that mostly affects the central nervous system and skeletal muscle. This study provides a comprehensive summary of the clinical symptoms, multisystemic pathogenesis, and genetic characteristics of MELAS syndrome. The aim was to improve comprehension of clinical practice and gain a deeper understanding of the latest pathophysiological theories.
View Article and Find Full Text PDFmedRxiv
December 2024
Department of Bioengineering, University of Washington, Seattle, WA, USA.
Background: Carotid atherosclerosis is a major etiology of stroke. Although intraplaque hemorrhage (IPH) is known to increase stroke risk and plaque burden, its long-term effects on plaque dynamics remain unclear.
Objectives: This study aimed to evaluate the long-term impact of IPH on carotid plaque burden progression using deep learning-based segmentation on multi-contrast vessel wall imaging (VWI).
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