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Analysis of Neurology Residency Match Outcomes Using the Texas Seeking Transparency in Application to Residency (STAR) Database

Year: 2025
Type: article
Study design: Observational Study
Abstract: Background Historically, United States Medical Licensing Examination (USMLE) Step 1 scores played a crucial role in residency selection. However, recent trends have shifted toward a more holistic review process that emphasizes factors such as extracurricular activities and program location in addition to exam performance. Objective This study aims to identify predictors of successful matches into US-based neurology residency programs following the transition of USMLE Step 1 to pass/fail scoring. Design/methods This retrospective study analyzed neurology residency applicant data from the Texas Seeking Transparency in Application to Residency (STAR) database from 2019 to 2024. Following the IRB exemption, variables such as research output, leadership roles, Step 2 scores, clerkship honors, and program signaling were evaluated for their association with successful matches. ANOVA and t-tests were used to determine statistically significant predictors of match success. Results Among 1,017 matched neurology applicants, the mean number of abstracts presented increased from 2018 (4.65) to 2024 (5.63, p < 0.05). Volunteer experiences decreased significantly from 6.17 to 4.11 (p < 0.01). Clerkship honors predicted match success (p = 0.02) and peaked in 2024 (mean = 3.51). Among 2024 applicants who signaled a program, 47.1% matched to a signaled program. No significant changes were observed in research publications, leadership roles, Step 2 scores, or demographic factors. Conclusions Following the transition to pass/fail Step 1 scoring, research productivity and extracurricular activities remained important, while clerkship honors emerged as the strongest predictor of match success.
Source: Cureus
Authors: Adam Y Ali, Samuel Salib, Niloufar S Tehrani, Gurkiranjeet Gakhal, Ryan Chowdhury, Ubaid Ansari, Layla Ali, Maaz Asim, Angela Mihalic, Michael S Wong
Language: English
Field: Medicine
Open Access status: diamond
OpenAlex ID: W4416156604
FWCI:
Cites: 8
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