Identification of Candidate Characteristics that Predicted a Successful Anesthesiology Residency Program Match in 2024: An Anonymous, Prospective Survey.

Background: The primary aim of our study was to identify candidate characteristics that predicted a successful outcome for applicants to anesthesiology residency programs in the 2024 Main Residency Match. The secondary aim of our study was to assess the impact of gold and silver signals on the application process.

Methods: The Baylor Scott & White Research Institute institutional review board approved this study.

Bidirectional locomotion induces unilateral limb adaptations.

Humans can acquire and maintain motor skills throughout their lives through motor learning. Motor learning and skill acquisition are essential for rehabilitation following neurological disease or injury. Adaptation, the initial stage of motor learning, involves short-term changes in motor performance in response to a new demand in the person's environment.

The impact of hindsight bias on the diagnosis of perioperative events by anesthesia providers: A multicenter randomized crossover study.

Study Objective: Hindsight bias is the tendency to overestimate the predictability of an event after it has already occurred. We aimed to evaluate whether hindsight bias influences the retrospective interpretation of clinical scenarios in the field of anesthesiology, which relies on clinicians making rapid decisions in the setting of perioperative adverse events.

Design: Two clinical scenarios were developed (intraoperative hypotension and intraoperative hypoxia) with 3 potential diagnoses for each.

Identification, Characterization, and Ranking of Candidate Metrics for Selection to Anesthesiology Residency: An Iterative Survey of Program Directors.

Background: The primary aim of this study was to identify and stratify candidate metrics used by anesthesiology residency program directors (PDs) to develop their residency rank lists through the National Resident Matching Program.

Methods: Sixteen PDs comprised the participants, selected for diversity in geography and program size. We used a 3-round iterative survey to identify and stratify candidate metrics.

Comparison of artificial intelligence large language model chatbots in answering frequently asked questions in anaesthesia.

Background: Patients are increasingly using artificial intelligence (AI) chatbots to seek answers to medical queries.

Methods: Ten frequently asked questions in anaesthesia were posed to three AI chatbots: ChatGPT4 (OpenAI), Bard (Google), and Bing Chat (Microsoft). Each chatbot's answers were evaluated in a randomised, blinded order by five residency programme directors from 15 medical institutions in the USA.