Impact of Holistic Application Scoring on Interview Offers.

Objective: We aimed to develop a holistic screening tool for surgical residency application processing to capture the diverse skills and attributes of the applicant, based on characteristics most commonly associated with success in our residency program.

Design: We developed an application-scoring rubric with 4 domains based on ACGME Holistic reviewing criteria: academic potential, experiences, personal attributes, and clinical competency. We scored academic potential based on a composite of Step 2 score, MSPE tier rank, surgery clerkship grade, college honors, publications, and presentations.

Bias Perpetuates Bias: ChatGPT Learns Gender Inequities in Academic Surgery Promotions.

Objective: Gender inequities persist in academic surgery with implicit bias impacting hiring and promotion at all levels. We hypothesized that creating letters of recommendation for both female and male candidates for academic promotion in surgery using an AI platform, ChatGPT, would elucidate the entrained gender biases already present in the promotion process.

Design: Using ChatGPT, we generated 6 letters of recommendation for "a phenomenal surgeon applying for job promotion to associate professor position", specifying "female" or "male" before surgeon in the prompt.

Evaluating variable selection methods for multivariable regression models: A simulation study protocol.

Researchers often perform data-driven variable selection when modeling the associations between an outcome and multiple independent variables in regression analysis. Variable selection may improve the interpretability, parsimony and/or predictive accuracy of a model. Yet variable selection can also have negative consequences, such as false exclusion of important variables or inclusion of noise variables, biased estimation of regression coefficients, underestimated standard errors and invalid confidence intervals, as well as model instability.

The clinical and biochemical spectrum of ectopic acromegaly.

Ectopic acromegaly is a rare condition caused by extrapituitary central or peripheral neuroendocrine tumours (NET) that hypersecrete GH or, more commonly, GHRH. It affects less than 1% of acromegaly patients and a misdiagnosis of classic acromegaly can lead to an inappropriate pituitary surgery. Four types of ectopic acromegaly have been described: 1) Central ectopic GH-secretion: Careful cross-sectional imaging is required to exclude ectopic pituitary adenomas.