ArticlePlastic and reconstructive surgery. Global open2026
Validation of Orthopedic Surgery Residency Database for Use Within Plastic Surgery.
Article in Plastic and reconstructive surgery. Global open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Matched plastic surgery (PS) residency applicants report higher mean numbers of abstracts, presentations, and publications than unmatched peers. However, the National Resident Matching Program aggregates these metrics, limiting insight into program-specific trends. Building on an orthopedic surgery model that uses Python scripts interfaced with the Elsevier Scopus Application Programming Interface, this study aims to create a comprehensive database of PS resident research output and demographics. Methods: Eighty-eight active integrated PS residency programs were identified via the Accreditation Council for Graduate Medical Education. A total of 1170 residents (postgraduate years 1-6) were identified through official program websites and social media and validated with the National Resident Matching Program data. Resident demographics (degree type, sex, medical school) were verified using the Residency Explorer (RE) tool. A Python script was used to collect bibliometric data, including publication count, authorship role, journal name, impact factor, and citation count. Manual verification was followed to confirm authorship. Results: The script identified 38,226 publications, of which 14,385 were verified and attributed to 1055 residents. This methodology captured 90% of residents within multiple queries. Degree type data matched RE data in 80% of programs, and gender data matched RE data in 62% of programs. Conclusions: This study demonstrates the feasibility of using automated data mining and public sources to construct a robust, validated database of PS research output. The methodology offers scalability to other specialties and lays the groundwork for predictive tools to support applicants in selecting programs that align with their academic profiles, as well as guiding away-rotation and signaling decisions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.