Cristian A Angeramo1,2, Patricio Méndez3, Eduardo P Eyheremendy3, Francisco Schlottmann4. 1. Department of Surgery, Hospital Alemán of Buenos Aires, Av. Pueyrredon 1640, C1118AAT, Buenos Aires, Argentina. angeramoagustin@gmail.com. 2. Department of Radiology, Interventional Radiology Service, Hospital Alemán of Buenos Aires, Buenos Aires, Argentina. angeramoagustin@gmail.com. 3. Department of Radiology, Interventional Radiology Service, Hospital Alemán of Buenos Aires, Buenos Aires, Argentina. 4. Department of Surgery, Hospital Alemán of Buenos Aires, Av. Pueyrredon 1640, C1118AAT, Buenos Aires, Argentina.
Abstract
PURPOSE: Rectum sheath hematoma (RSH) is a rare and often misdiagnosed disease. We aimed to determine outcomes of patients affected by RSH and identify variables associated with the need of prompt intervention. METHODS: Patients diagnosed with RSH during the period 2012-2020 were retrospectively identified. Demographics, diagnostic, and therapeutic variables were evaluated. RSH was classified with computed tomography (CT) according to the Berna system. An artificial neural network (ANN) model including 12 variables was used to identify patients that might require a prompt endovascular or surgical treatment. RESULTS: A total of 20 patients were included for analysis; mean age was 69 (35-98) years and 14 (70%) were females. Iatrogenic injury and forceful contraction of the abdominal wall were the leading causes of RSH. Eleven (55%) patients were anticoagulated or antiaggregated. There were 3 (15%) grade 1, 5 (25%) grade 2, and 12 (60%) grade 3 RSH; 6 (30%) were treated conservatively, 10 (50%) with artery embolization, and 4 (20%) with surgery. Overall morbidity was 45% and there was no mortality in the series. According to the ANN, patients at high risk of requiring an invasive treatment were those with active extravasation on CT angiography, Berna grade III, age ≥ 65 years, hemodynamic instability, chronic use of corticosteroids, hematoma volume ≥ 1000 mL, and/or transfusion of ≥ 4 units of red blood cells. CONCLUSION: Conservative treatment might be effective in selected patients with RSH. Our artificial neural network analysis might help selecting patients who require endovascular or surgical treatment.
PURPOSE: Rectum sheath hematoma (RSH) is a rare and often misdiagnosed disease. We aimed to determine outcomes of patients affected by RSH and identify variables associated with the need of prompt intervention. METHODS: Patients diagnosed with RSH during the period 2012-2020 were retrospectively identified. Demographics, diagnostic, and therapeutic variables were evaluated. RSH was classified with computed tomography (CT) according to the Berna system. An artificial neural network (ANN) model including 12 variables was used to identify patients that might require a prompt endovascular or surgical treatment. RESULTS: A total of 20 patients were included for analysis; mean age was 69 (35-98) years and 14 (70%) were females. Iatrogenic injury and forceful contraction of the abdominal wall were the leading causes of RSH. Eleven (55%) patients were anticoagulated or antiaggregated. There were 3 (15%) grade 1, 5 (25%) grade 2, and 12 (60%) grade 3 RSH; 6 (30%) were treated conservatively, 10 (50%) with artery embolization, and 4 (20%) with surgery. Overall morbidity was 45% and there was no mortality in the series. According to the ANN, patients at high risk of requiring an invasive treatment were those with active extravasation on CT angiography, Berna grade III, age ≥ 65 years, hemodynamic instability, chronic use of corticosteroids, hematoma volume ≥ 1000 mL, and/or transfusion of ≥ 4 units of red blood cells. CONCLUSION: Conservative treatment might be effective in selected patients with RSH. Our artificial neural network analysis might help selecting patients who require endovascular or surgical treatment.
Authors: A Moreno Gallego; J L Aguayo; B Flores; T Soria; Q Hernández; S Ortiz; R González-Costea; P Parrilla Journal: Br J Surg Date: 1997-09 Impact factor: 6.939
Authors: Benjamin N Contrella; Auh Whan Park; Luke R Wilkins; Daniel Sheeran; Taryn E Hassinger; J Fritz Angle Journal: J Vasc Interv Radiol Date: 2019-11-14 Impact factor: 3.464
Authors: Ebubekir Gündeş; Durmuş Ali Çetin; Ulaş Aday; Hüseyin Çiyiltepe; Kamuran Cumhur Değer; Orhan Uzun; Aziz Serkan Senger; Erdal Polat; Mustafa Duman Journal: Ulus Travma Acil Cerrahi Derg Date: 2017-11