Towards clinical translation of urinary vitronectin for non-invasive detection and monitoring of renal fibrosis in kidney transplant patients.

Background: Interstitial fibrosis and tubular atrophy (IFTA) is a critical factor in the prognosis of kidney health. Currently, IFTA quantitation in kidney biopsy samples is crucial for diagnosis and assessing disease severity, but the available non-invasive biomarkers are not satisfactory. Proteomic studies identified urinary vitronectin (VTN) as a potential biomarker for kidney fibrosis.

Stent Retriever AssIsted Lysis Technique with Tirofiban: A Potential Bailout Alternative to Angioplasty and Stenting.

Background And Purpose: Angioplasty and stent placement have been described as a bailout technique in individuals with failed thrombectomy. We aimed to investigate Stent retriever AssIsted Lysis (SAIL) with tirofiban before angioplasty and stent placement.

Materials And Methods: Patients from 2 comprehensive stroke centers were reviewed (2020-2023).

Intracranial thrombus composition is associated with occlusion location and endovascular treatment outcomes: results from ITACAT multicenter study.

Background: The impact of thrombolytics directed towards different thrombus components regarding site of occlusion in combination with mechanical thrombectomy (MT) to achieve endovascular complete recanalization is unclear.

Methods: Retrospective analysis of a prospective database in two stroke centers. Intracranial thrombi retrieved by MT were analyzed using hematoxylin-eosin staining for fibrin and red blood cell proportions, and CD61 immunostaining for platelets proportion in thrombus (PLTPT) assessment.

Electrical impedance measurements can identify red blood cell-rich content in acute ischemic stroke clots associated with first-pass successful recanalization.

Background: Electrochemical impedance spectroscopy can determine characteristics such as cell density, size, and shape. The development of an electrical impedance-based medical device to estimate acute ischemic stroke (AIS) clot characteristics could improve stroke patient outcomes by informing clinical decision making.

Objectives: To assess how well electrical impedance combined with machine learning identified red blood cell (RBC)-rich composition of AIS clots , which is associated with a successfully modified first-pass effect.

PRERISK: A Personalized, Artificial Intelligence-Based and Statistically-Based Stroke Recurrence Predictor for Recurrent Stroke.

Background: Predicting stroke recurrence for individual patients is difficult, but individualized prediction may improve stroke survivors' engagement in self-care. We developed PRERISK: a statistical and machine learning classifier to predict individual risk of stroke recurrence.

Methods: We analyzed clinical and socioeconomic data from a prospectively collected public health care-based data set of 41 975 patients admitted with stroke diagnosis in 88 public health centers over 6 years (2014-2020) in Catalonia-Spain.