Objective

This study aimed to determine the post-matriculation perceptions of interns and faculty who participated in the 2020-2021 virtual interview process and how their expectations of the program and the applicants, respectively, aligned with reality.

Design, setting, and participants

Published surveys on virtual interviewing were reviewed and modified to design two surveys, for interns and for faculty who interviewed. Interns and faculty members from the Departments of Surgery and Medicine at one institution who participated in the 2020-2021 virtual interview process completed the surveys four to six months after the start of the academic year. Following survey completion, surgical interns from the same application cycle participated in one in-person focus group nine months after the start of the academic year to clarify points raised in the surveys.

Results

Forty-six interns and faculty members responded to the survey (subgroup response rates ranging from 13-30%) and ten interns participated in the focus group (participation rate 100%). Most faculty and intern participants found that expectations formed during virtual interviews were accurate. However, our respondents noted limitations to virtual interviews that reduced their usefulness, including challenges with unnatural social interactions, understanding city fit, and getting a sense of resident and program culture. Participants provided possible solutions to address these challenges.

Conclusions

Overall, this mixed-methods study at a single institution found that perceptions from virtual interviews were generally accurate but with some limitations. We describe several opportunities to improve the virtual interview process and optimize the application experience.

Objective

The study aim was to develop and validate models to predict clinically significant post-hepatectomy liver failure (PHLF) and serious complications (a Comprehensive Complication Index® [CCI®]>40) using preoperative and intraoperative variables.

Summary background data

PHLF is a serious complication after major hepatectomy but does not comprehensively capture a patient's postoperative course. Adding the CCI® as an additional metric can account for complications unrelated to liver function.

Methods

The cohort included adult patients who underwent major hepatectomies at twelve international centers (2010-2020). After splitting the data into training and validation sets (70:30), models for PHLF and a CCI®>40 were fit using logistic regression with a lasso penalty on the training cohort. The models were then evaluated on the validation dataset.

Results

Among 2,192 patients, 185 (8.4%) had clinically significant PHLF and 160 (7.3%) had a CCI®>40. The PHLF model had an area under the curve (AUC) of 0.80, calibration slope of 0.95, and calibration-in-the-large of -0.09, while the CCI® model had an AUC of 0.76, calibration slope of 0.88, and calibration-in-the-large of 0.02. When the models were provided only preoperative variables to predict PHLF and a CCI®>40, this resulted in similar AUCs of 0.78 and 0.71, respectively. Both models were used to build two risk calculators with the option to include or exclude intraoperative variables (PHLF Risk Calculator; CCI®>40 Risk Calculator).

Conclusions

Using an international cohort of major hepatectomy patients, we used preoperative and intraoperative variables to develop and internally validate multivariable models to predict clinically significant PHLF and a CCI®>40 with good discrimination and calibration.