Background/purpose: Blood type has become an increasingly recognized risk factor for coagulopathy. We explored the association between blood type and hematoma expansion (HE) after intracerebral hemorrhage (ICH).
Methods: Spontaneous ICH patients prospectively enrolled in an ongoing ICH cohort study at Columbia University Irving Medical Center from 2009 to 2016 were evaluated. Primary ICH patients with admission blood type testing were evaluated for HE differences, defined as > 33% relative HE. The association of blood type with radiographic HE outcomes was assessed using multivariable logistic regression models. The association of blood type and poor clinical outcomes using modified Rankin Scale (mRS 4-6) was additionally explored.
Results: Of 272 ICH patients with blood type data and neuroimaging available to determine HE, there were 146 (54%) type-O, 82 (30%) type-A, 34 (13%) type-B, and 10 (3%) type-AB patients. No significant baseline demographic, clinical, or radiographic differences were noted between blood types. Type-B blood was associated with more HE compared to other blood types (OR 2.82; 95% CI 1.23-6.45) after adjusting for known covariates of HE (anticoagulant use, time to admission computed tomography scan, and baseline hematoma volume). No associations with blood type and poor 3 month mRS were identified, but these analyses were limited secondary to our smaller cohort.
Conclusions: There may be differences in HE after ICH in patients with different blood types. Further work is required to replicate these findings and identify the pathophysiologic mechanisms behind coagulopathy between blood types after ICH.
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http://dx.doi.org/10.1007/s12028-018-0655-0 | DOI Listing |
J Infect Dev Ctries
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Department of Emergency Medicine, Faculty of Medicine, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.
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Cell Commun Signal
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Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA.
One hallmark of cancer is the upregulation and dependency on glucose metabolism to fuel macromolecule biosynthesis and rapid proliferation. Despite significant pre-clinical effort to exploit this pathway, additional mechanistic insights are necessary to prioritize the diversity of metabolic adaptations upon acute loss of glucose metabolism. Here, we investigated a potent small molecule inhibitor to Class I glucose transporters, KL-11743, using glycolytic leukemia cell lines and patient-based model systems.
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January 2025
Department of Cardiology, West China Hospital, Sichuan University West China School of Medicine, 37 Guoxue Road, Chengdu, Sichuan, 610041, China.
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January 2025
Department of Life Technologies, Division of Biotechnology, University of Turku, Medisiina D, 5th floor, Kiinamyllynkatu 10, 20520, Turku, Finland.
Glycosylation changes of circulating proteins carrying the CA19-9 antigen may offer new targets for detection methods to be explored for the diagnosis of epithelial ovarian cancer (EOC). Search for assay designs for targets initially captured by a CA19-9 antigen reactive antibody from human body fluids by probing with fluorescent nanoparticles coated with lectins or antibodies to known EOC associated proteins. CA19-9 antigens were immobilized from ascites fluids, ovarian cyst fluids or serum samples using monoclonal antibody C192 followed by probing of carrier proteins using anti-MUC16, anti-MUC1 and, anti STn antibodies and seven lectins, all separately coated on nanoparticles.
View Article and Find Full Text PDFSci Data
January 2025
School of Medicine, Anhui University of Science and Technology, Huainan, 232001, China.
Ultrasound is a primary diagnostic tool commonly used to evaluate internal body structures, including organs, blood vessels, the musculoskeletal system, and fetal development. Due to challenges such as operator dependence, noise, limited field of view, difficulty in imaging through bone and air, and variability across different systems, diagnosing abnormalities in ultrasound images is particularly challenging for less experienced clinicians. The development of artificial intelligence (AI) technology could assist in the diagnosis of ultrasound images.
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