ReviewCureus2025
Rise of Big Data in Spine Surgery Research: A Bibliometric Analysis, 1993-2024.
Review in Cureus, 2025. 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
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Spine surgery represents a dynamic and innovative specialty with a steady increase in annual publications since 1900. The introduction of large databases and registries marked a paradigm shift in research. Despite their quantitative superiority, databases are inherently limited in a number of ways. Spine surgery remains a somewhat controversial specialty with significant cost, population health, and outcomes implications, and has, not surprisingly, become more frequently associated with large-scale registry studies. The objective of this study was to descriptively characterize trends in large-database usage in spine surgery research over time, including publication volume, topic distribution, and geographic output. A database search in the Clarivate Analytics Web of Science (WoS) database with keywords ("big data" OR "large database" OR "registry" OR "national database") AND "spine surgery" was conducted on July 7, 2025, and original and review articles published between 1993 and 2024 were included. Retrieved articles were categorized into seven areas based on primary research objectives, and data underwent descriptive quantitative analysis. Descriptive analyses were performed in Microsoft Excel (Microsoft® Corp., Redmond, WA, USA), and keyword co-occurrence network and overlay visualizations were generated using VOSviewer (Version 1.6.20, Centre for Science and Technology Studies, Leiden University, The Netherlands). A total of 633 articles were analyzed, revealing a more than 10-fold increase in publications from 2012 to 2024. The degenerative category was most common (189 articles), followed by public health (179) and infection (75). The United States dominated the research output (62.29%). Raw annual citation counts also significantly increased, from 146 in 2012 to 2,132 in 2024. The utilization of large databases in spine surgery research has substantially grown, reflecting a shift toward big data usage. Publications on spinal infections and public health outcomes have notably increased, while degenerative conditions consistently prevail. Geographic distribution remains skewed towards western countries, especially the United States. These trends suggest an expanding recognition of database studies as a critical tool for evidence-based research in spine surgery.
Indexed as
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What OpenQuestion holds
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.