ReviewNorth American Spine Society journal2026
Lateral lumbar interbody fusion versus single position prone transpsoas approach: A comprehensive bibliometric analysis.
Review in North American Spine Society journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Stand-alone prone lateral interbody fusion: a retrospective case series.Journal of spine surgery (Hong Kong) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Lateral lumbar interbody fusion (LLIF) and single position prone lateral (PTP) approaches represent significant advances in minimally invasive spine surgery, yet comprehensive comparative analysis of their research trajectories remains limited. Purpose: This bibliometric analysis aims to comprehensively compare the scientific landscapes surrounding LLIF and PTP approaches by examining publication trends, citation patterns, authorship networks, and thematic evolution. Methods: We systematically searched Scopus, PubMed and Google Scholar from inception through September 2025 for articles addressing LLIF and single position prone lateral approaches. Bibliometrix package in R was used to complete the bibliometric analysis. We included the following parameters: publication output, citation metrics, journal distribution, author productivity, international collaboration networks, keyword co-occurrence, and thematic mapping in the analysis. Results: We identified 823 LLIF publications and 107 single position prone lateral publications. LLIF accounted for 20,707 total citations with an h-index of 70 and a mean of 31.93 citations per document, whereas PTP accumulated 915 citations with an h-index of 17 and a mean of 8.44 citations per document. Although LLIF has a larger volume of publications, PTP has progressed more rapidly, showing annual growth rates of 44% compared with 30% for LLIF during comparable developmental periods. The United States contributed 45.6% of LLIF and 71.8% of PTP publications, with LLIF research spanning 42 countries and PTP 16 countries. Core research themes for both techniques evolved from technical descriptions to comparative effectiveness studies, and the substantial overlap in authors and institutions indicates complementary rather than competitive research trajectories. Conclusions: LLIF represents a mature surgical approach with a strong evidence base while PTP demonstrates accelerating research interest, with growth trajectories exceeding those of LLIF during comparable developmental stages. Based on current publication trends and thematic evolution, future research on PTP should prioritize rigorous comparative studies, long-term outcome evaluations, cost-effectiveness analyses, and patient-centered outcome research to strengthen the evidence base and guide clinical adoption.
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.