Investigation of Orthopedic Research Trends through Published Papers within Q1 Journals through 2021 - 2022
Year: 2025
Type: article
Abstract: Objectives This study aimed to identify emerging “hot topics” in orthopedic surgery and analyze key factors shaping the future of the specialty, providing insights into evolving challenges and opportunities for practitioners and researchers. Methods In August-September 2024, we analyzed citation counts for articles published in 2021-2022 across 15 high-impact first-quartile (Q1) orthopedic journals. Articles were categorized by subspecialty and trauma relevance, and citation data were collected from Google Scholar. Two reviewers extracted the data, resolving discrepancies with a third reviewer. Citation indices were calculated to compare academic impact, and journals were ranked into quartiles (Q1-Q4) based on citation scores and impact factor. Results In 2021, the average citation index across orthopedic subspecialties ranged from 3.6 for Hand (min-max: 0-19.5) to 15 for General Orthopedics. The highest citation indices were seen in General (15), Knee/Leg (12.4), and Trauma (12.4). The average citation index in 2022 for the Hand topic was 3.6 (min-max: 0-11.2), the Wrist topic 6.7 (0-11.8), the Elbow/Forearm topic 4.3 (0-9.3), the Shoulder/Humerus topic 7.4 (0-12.2), the Hip/Pelvis/Femur 8.2 (4.9-10.6), the Knee/leg topic 10.1 (4.8-18.8), the Foot & Ankle topic 9.8 (4-33), the Spine topic 8.3 (0-15.5), the Clavicle topic 4.3 (0-14.5), the Basic Science topic 2.8 (0-8.7), General topic 9.4 (3.6-17.9), and the Trauma topic was 8.7 (3-16.3). The cumulative citation index for 2021-2022 showed General (24.4) and Knee/Leg (22.5) as the highest, followed by Trauma (21.1) and Shoulder/Humerus (21.6). Conclusion Analyzing citation trends in orthopedic subspecialties helps predict emerging discoveries and guides patient care, research, and education advancements. Staying informed on these trends ensures the field evolves with the most impactful developments.
Source: SurgiColl
DOI: 10.58616/001c.129178
Authors: Nissan Nazar, Aidan Cadiz, Farshid Daneshvar, Amir R. Kachooei
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4408726123