[Renal transplantation in Maastricht II asystole: report of a first case in Mexico]. / Trasplante renal en asistolia Maastrich II. Reporte del primer caso en México.

On May 6, 2012, an 18-year-old patient was admitted to the emergency room with sever traumatic brain injury and cardiovascular arrest; resuscitation maneuvers were started with a compressor table AUTOPULSE®. After 30 minutes, death was pronounced. Later, compressions were restarted. After the family agreed with the donation, blood samples were obtained to do serology tests and to obtain blood group and Rh factor and a cardiopulmonary bypass was started by femoral approach. After 2 hours and 35 minutes, extraction of the kidneys was performed. This case represented the first organ procurement from a non-heart-beating Maastricht II donor in our country. After 60 days, both receptors remained free of dialysis.

CT Rendering and Radiomic Analysis in Post-Chemotherapy Retroperitoneal Lymph Node Dissection for Testicular Cancer to Anticipate Difficulties for Young Surgeons.

Post-chemotherapy retroperitoneal lymph node dissection (PC-RPLND) in non-seminomatous germ-cell tumor (NSTGCTs) is a complex procedure. We evaluated whether 3D computed tomography (CT) rendering and their radiomic analysis help predict resectability by junior surgeons. The ambispective analysis was performed between 2016-2021. A prospective group (A) of 30 patients undergoing CT was segmented using the 3D Slicer software while a retrospective group (B) of 30 patients was evaluated with conventional CT (without 3D reconstruction). CatFisher's exact test showed a p-value of 0.13 for group A and 1.0 for Group B. The difference between the proportion test showed a p-value of 0.009149 (IC 0.1-0.63). The proportion of the correct classification showed a p-value of 0.645 (IC 0.55-0.87) for A, and 0.275 (IC 0.11-0.43) for Group B. Furthermore, 13 shape features were extracted: elongation, flatness, volume, sphericity, and surface area, among others. Performing a logistic regression with the entire dataset, n = 60, the results were: Accuracy: 0.7 and Precision: 0.65. Using n = 30 randomly chosen, the best result obtained was Accuracy: 0.73 and Precision: 0.83, with a p-value: 0.025 for Fisher's exact test. In conclusion, the results showed a significant difference in the prediction of resectability with conventional CT versus 3D reconstruction by junior surgeons versus experienced surgeons. Radiomic features used to elaborate an artificial intelligence model improve the prediction of resectability. The proposed model could be of great support in a university hospital, allowing it to plan the surgery and to anticipate complications.