Single-center outcomes of artificial intelligence in management of pulmonary embolism and pulmonary embolism response team activation.

Multidisciplinary pulmonary embolism response teams (PERTs) have shown that timely triage expedites treatment. The use of artificial intelligence (AI) may help improve pulmonary embolism (PE) management with early CT pulmonary angiogram (CTPA) screening and accelerate PERT coordination. This study aimed to test the clinical validity of an FDA-approved PE AI algorithm.

COVID-19 Time of Intubation Mortality Evaluation (C-TIME): A system for predicting mortality of patients with COVID-19 pneumonia at the time they require mechanical ventilation.

Background: An accurate system to predict mortality in patients requiring intubation for COVID-19 could help to inform consent, frame family expectations and assist end-of-life decisions.

Research Objective: To develop and validate a mortality prediction system called C-TIME (COVID-19 Time of Intubation Mortality Evaluation) using variables available before intubation, determine its discriminant accuracy, and compare it to acute physiology and chronic health evaluation (APACHE IVa) and sequential organ failure assessment (SOFA).

Methods: A retrospective cohort was set in 18 medical-surgical ICUs, enrolling consecutive adults, positive by SARS-CoV 2 RNA by reverse transcriptase polymerase chain reaction or positive rapid antigen test, and undergoing endotracheal intubation.

Lessons learned from a delayed diagnosis of atrioesophageal fistula: A multidisciplinary approach.

Atrioesophageal fistulas are a rare complication of radiofrequency ablation (RFA) that requires rapid identification and emergent surgical repair to prevent morbidity and mortality. We report a case of a 32-year-old man with atrial fibrillation presenting with chest pain followed by rapidly progressive sepsis and embolic cerebrovascular accident 23 days after RFA. Subtle initially overlooked findings on multiple computed tomography caused a delay in diagnosis.