National Evaluation of the Arms Race Control Score in US Neurosurgery Residents

Research productivity has become a critical factor in the neurosurgery residency match process. The Arms Race Control Score (ARCS) was recently proposed by Bowers et al. to standardize the evaluation of research output for quality and effort. This study is the first to evaluate ARCS among all current US neurosurgery residents.

We collected bibliometric data for neurosurgery residents completing training between 2025 and 2031 in the US (n = 1,574) and computed and ARCS values. We stratified residents by median ARCS and compared demographic, academic, and institutional factors. Temporal trends in ARCS and its subcomponents were analyzed using linear regression. We also correlated ARCS with existing research metrics and used multivariate modeling to assess its predictivity.

Residents with above-median ARCS were more likely to hold advanced degrees (23.4% vs 12.0%), graduate from NIH Top 40 schools (44.3% vs 26.4%), and match into Doximity Top 25 residencies (44.4% vs 20.8%) (p<0.0001), but were less likely to be female (24.2% vs 30.0%, p = 0.0107). ARCS increased over time (R²=0.7221, p=0.0155), alongside publication counts (R2= 0.8622, p=0.0025), and the proportion of minimal-effort publications (R2=0.9598, p=0.0001). Of existing metrics, ARCS was most correlated with number of publications (ρ=0.9295, p<0.0001). Adding ARCS to a multivariate model did not change predictive performance (AUC=0.77).

With the recent rise in minimal-effort publications, ARCS may be a valuable tool in residency evaluation. However, it presently appears to be more influenced by publication quantity rather than quality and may offer minimal incremental utility.