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Objective: Complications after Endovascular Aneurysm Repair (EVAR) can be fatal. Patient follow-up for surveillance imaging is becoming more challenging as fewer patients are seen, particularly after the first year. The aim of this study was to develop an artificial intelligence model to predict the complication probability of individual patients to better identify those needing more intensive post-operative surveillance. Methods: Pre-operative CTA 3D reconstruction images of AAA from 273 patients who underwent EVAR from 2011-2020 were collected. Of these, 48 patients had post-operative complications including endoleak, AAA rupture, graft limb occlusion, renal artery occlusion, and neck dilation. A deep convolutional neural network model (VascAI©) was developed which utilized pre-operative 3D CT images to predict risk of complications after EVAR. The model was built with TensorFlow software and run on the Google Colab Platform. An initial training subset of 40 randomly selected patients with complications and 189 without were used to train the AI model while the remaining 8 positive and 36 negative cases tested its performance and prediction accuracy. Data down-sampling was used to alleviate data imbalance and data augmentation methodology to further boost model performance. Results: Successful training was completed on the 229 cases in the training set and then applied to predict the complication probability of each individual in the held-out performance testing cases. The model provided a complication sensitivity of 100% and identified all the patients who later developed complications after EVAR. Of 36 patients without complications, 16 (44%) were falsely predicted to develop complications. The results therefore demonstrated excellent sensitivity for identifying patients who would benefit from more stringent surveillance and decrease the frequency of surveillance in 56% of patients unlike to develop complications. Conclusion: AI models can be developed to predict the risk of post-operative complications with high accuracy. Compared to existing methods, the model developed in this study did not require any expert-annotated data but only the AAA CTA images as inputs. This model can play an assistive role in identifying patients at high risk for post-EVAR complications and the need for greater compliance in surveillance.

Trichobezoar is a rare condition, almost exclusively seen in young females with certain psychiatric disorders. Trichobezoars are usually confined within the stomach and the complications include ulceration, perforation, intussusception and obstruction for which surgery is usually required. Most of the reported cases of giant gastric trichobezoar extraction underwent an exploratory laparotomy with only a few reported cases that underwent a successful laparoscopic approach. This case report details the surgical management of the first case of a giant obstructing gastric trichobezoar extraction using robotic-assisted surgery.

REVISTA MÉDICA HJCA RESUMEN INTRODUCCIÓN:La embolización de cuerpos extraños intravasculares es una complicación poco frecuente; sin embargo, está asociada a alteraciones cardíacas y pulmonares en más del 50% de los casos. Actualmente se prefiere realizar el manejo utilizando técnicas de extracción por cateterismo cardíaco, esto debido a la naturaleza menos invasiva del procedimiento y a las menores tasas de mortalidad y complicaciones asociadas. A continuación se presenta un reporte de caso donde se realizó la extracción un catéter intracardiaco mediante vía percutánea.CASO CLÍNICO: Lactante de sexo masculino, de 51 días de vida, con antecedentes de prematuridad extrema y peso adecuado para edad gestacional, ingresado en el servicio de neonatología; a quien como acceso vascular central se le colocó un catéter percutáneo femoral. Tras el retiro del mismo se apreció rotura y embolización de los dos tercios distales; la evaluación radiológica evidenció catéter a nivel de cavidades cardíacas derechas.EVOLUCIÓN: Se inició antibioticoterapia por el riesgo de infección asociado. De forma exitosa se realizó la extracción del cuerpo extraño por intervencionismo percutáneo; el paciente evolucionó favorablemente, no presentó ninguna complicación. CONCLUSIÓN:La rotura y embolización del catéter es un evento poco frecuente que incrementa la morbimortalidad de los pacientes ingresados en neonatología. La extracción percutánea debe ser la primera opción por la eficacia y seguridad del procedimiento.

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