Identification of Factors that May Predict Career Trajectory Among Neuro-Ophthalmology Fellows

Background: There is modest literature regarding fellowship applicant factors that may predict future career achievement. We aim to characterize neuro-ophthalmology fellows and identify and analyze characteristics that may predict future career trajectory. Methods: Data, including demographic information, academic background, scholarly activities, and practice information, were collected using publicly available sources, on individuals who completed neuro-ophthalmology fellowships from 2015 to 2021. Summary statistics describing the cohort were calculated. Prefellowship characteristics were compared with postfellowship characteristics to evaluate which prefellowship characteristics may predict postfellowship academic productivity and career achievement. Results: Data were collected on 174 individuals (41.6% men, 58.4% women). Sixty-five percent were residency-trained in ophthalmology, 31% neurology, 1.7% both, and 1.7% pediatric neurology. Fifty-eight percent completed residency in the US, 8% in Canada, 32% internationally, and 2% in multiple locations. Among those practicing in the US/Canada, 63.8% practice at academic centers, 35.3% private practice, and 0.9% at both. Thirty-one percent completed additional subspecialty training and 17.8% additional graduate degrees. Completion of additional fellowship training or graduate degrees, and publication of more papers before fellowship, correlated with later academic productivity. There were no significant correlations between completion of an additional fellowship or graduate degree with current practice environment or attainment of leadership roles. There were no significant correlations between total publishing productivity prefellowship and practice environment or leadership roles postfellowship. Conclusions: Additional graduate degrees/subspecialty training, and prefellowship academic productivity, correlated with later academic productivity among neuro-ophthalmologists, suggesting that these metrics may be helpful in predicting future academic performance among fellowship applicants.