Results 191 to 200 of about 955,879 (306)
ABSTRACT Objective Intravenous thrombolysis (IVT) before thrombectomy for ischemic stroke may alter clot structure and procedural performance. We investigated how IVT relates to thrombectomy metrics across stroke etiologies. Methods We performed a time‐to‐event analysis of consecutive patients with anterior circulation large vessel occlusion (acLVO ...
Annahita Sedghi +8 more
wiley +1 more source
Cone-beam CT-based age-specific risk prediction model for maxillary anterior supernumerary teeth. [PDF]
Li M, Mao J, Huang Y, Liu H, Wang G.
europepmc +1 more source
SPG4 and Dementia: Expanding the Clinical Spectrum
ABSTRACT Objective Hereditary spastic paraplegia (HSP) is a group of disorders characterized by progressive spasticity and lower limb weakness, with mutations in SPG4/SPAST being the most common cause. Detailed studies and clinical and molecular comparisons across different populations are missing.
Emanuele Panza +19 more
wiley +1 more source
Predictive value of metabolic and inflammatory indices (TGI, TG/HDL-C, and PIV) for complications in type 2 diabetes mellitus: A retrospective cohort study. [PDF]
Urkmez Y, Karacali M, Kilinc EU.
europepmc +1 more source
Objective A leading cause of death among patients with scleroderma (SSc), interstitial lung disease (ILD) remains challenging to prognosticate. The discovery of biomarkers that accurately determine which patients would benefit from close monitoring and aggressive therapy would be an essential clinical tool.
Cristina M. Padilla +13 more
wiley +1 more source
Predicting complications and mortality in myocardial infarction patients using a graph neural network model. [PDF]
Guo D +5 more
europepmc +1 more source
Objective This study aims to develop hip morphology‐based radiographic hip osteoarthritis (RHOA) risk prediction models and investigates the added predictive value of hip morphology measurements and the generalizability to different populations. Methods We combined data from nine prospective cohort studies participating in the Worldwide Collaboration ...
Myrthe A. van den Berg +26 more
wiley +1 more source
An interpretable machine learning model with SHAP explanations predicts spontaneous bleeding in pediatric acute liver failure. [PDF]
Xiong Q, Wang R, Yang C, Zhang M.
europepmc +1 more source

