Bibliometric Indices as Indicators of Research Output: Analyzing Anesthesiologists as a Paradigm for Surgical Disciplines

Abstract

Abstract Background Anesthesiology is one of the increasingly competitive surgical specialties with a growing emphasis on scholarly activity. A metric of productivity and citation influence, the Hirsch index (h-index) can help identify mentors capable of guiding postgraduate trainees towards successful academic achievements. This study sought to determine associations between h-indices or m-quotients and manuscript publication in anesthesiology. Methods Using the American Society of Anesthesiologists (ASA) website, accepted abstracts from the ASA Annual Meetings from 2019 to 2021 were screened (n = 2146). First author (FAHi) and senior author (SAHi) h-indices as well as first author (FAMq) and senior author (SAMq) m-quotients were collected for each abstract using the Scopus database. Whether an accepted abstract was subsequently published as a manuscript in a peer-reviewed journal was also noted along with the number of days between ASA presentation and publication date. Linear and logistic regression models were used for statistical analyses. Results In total, 348 (34.4%) of the 1012 eligible abstracts were published as manuscripts. Mean FAHi, SAHi, FAMq, and SAMq were significantly higher for accepted ASA abstracts that were later published in peer reviewed journals compared to accepted abstracts that were not published (p < 0.001). FAHi, SAHi, FAMq, and SAMq had significant positive associations with odds of publication (p = 0.002; p < 0.001; p = 0.006; p < 0.001, respectively). There was no statistical significance between FAHi, SAHi, FAMq, or SAMq and the number of days between ASA presentation and publication. Conclusion Our study uniquely demonstrates the positive, direct association between h-indices and m-quotients with the probability of publication in anesthesiology. We propose that bibliometric indices are adapted to provide a refined perspective of a physician-scientist's capabilities. Postgraduate trainees can utilize these indices to discern research mentors primed for fostering academic excellence.