View clinical trials related to Spleen Injury.
Filter by:Spleen laceration is a lethal abdominal trauma and usually be diagnosed by medical images such as computed tomography. Deep learning had been proved its usage in detect abnormalities in medical images. In this trial, we used de-identified registry databank to develop a novel deep-learning based algorithm to detect the spleen trauma and to identify the injury locations.
OBJECTIVE: To determine the quality of life (QOL) and clinical outcome after conservative therapy, embolization (proximal versus distal) or surgery in patients with traumatic splenic injury. Secondary aims: (I) to examine therapy-related complications, (II) to establish the necessity of additional therapies, (III) the assessment of splenic function related to splenic morphology (MR imaging) after embolization and (IV) to find the prognostic factors for failure of non-operative management (NOM) in patients with splenic injuries. Finally, with the acquired data from this study a patient-oriented protocol will be provided for the management of traumatic splenic injury. HYPOTHESIS: The investigators expect that NOM is superior to surgery with regard to QOL, clinical outcome and splenic function. Embolization will need more additional therapies. Splenic morphology is related to splenic immune function. Expected prognostic factors are age above 40, ISS >25 and a splenic injury grade of 3 or higher. STUDY DESIGN: A combination of a retrospective and a prospective multicentre cohort study. This protocol involves the prospective part of the study. STUDY POPULATION/DATASET: Patients who enter the participating hospitals between March 2017 and December 2018 with splenic injury will be asked to participate. The follow-up period will be one year with regard to QOL, clinical symptoms and imaging. INTERVENTION: All patients will complete a number of questionnaires at different time points. The patients who were treated with splenic artery embolization (SAE) will undergo an MRI one month and one year after treatment. OUTCOME MEASURES: Primary outcome is QOL. Secondary outcomes are clinical symptoms and imaging. SAMPLE SIZE: Approximately 100 patients will be included per year during the inclusion phase. DATA ANALYSIS: With regard to the prospective data linear modelling will be performed. COLLABORATION/CONNECTION: Tilburg University, Erasmus Medical Center Rotterdam, Maasstad Hospital Rotterdam, Albert Schweitzer Hospital Dordrecht, Amphia hospital Breda, Leiden University Medical Center, VU University Medical Center Amsterdam, Medical Spectrum Twente, Radboud University Nijmegen, Isala Zwolle. TIME SCHEDULE: Year 1: literature search and conducting the retrospective study and analyses. Years 1-3: inclusion prospective study and follow-up of patients. Year 4: finishing follow-up data collection and analysing.