ArticleEFORT open reviews2026
Robot-assisted pedicle screw placement in spinal surgery: an updated systematic umbrella review and meta-meta-analysis of comparisons against freehand and navigation-guided techniques.
Article in EFORT open reviews, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed.
- Robot-Assisted "Postage-Stamp" Vertebrotomy for Spinal Tumor Resection: Case Report.Journal of clinical medicine · 2026Article
- The global landscape of robot-assisted pedicle screws: a bibliometric and thematic evolution analysis.Journal of robotic surgery · 2026Review
- Global evolution of robot-assisted spine surgery: a bibliometric and knowledge-mapping study (1997-2026).Journal of robotic surgery · 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: The efficacy and safety of robot-assisted pedicle screw placement versus freehand and computer-assisted navigation techniques remain debatable. This umbrella review synthesizes meta-analytic evidence on the associated accuracy, safety, and clinical outcomes. Methods: A comprehensive search was performed in PubMed, Embase, Scopus, Web of Science, Ovid, and Cochrane databases, from inception to October 2025, with no language restrictions. Researchers independently assessed meta-analyses that compared robot-assisted with freehand and computer-assisted navigation techniques. Methodological quality was assessed using the AMSTAR-2 tool, and evidence was graded using the GRADE framework. The primary outcomes included accuracy metrics (acceptable and perfect screw placement) and safety indicators (intraoperative blood loss, radiation exposure, and hospital stay). The protocol was registered with PROSPERO (registration number: CRD42024556304). Results: A total of 38 meta-analyses comprising 414 primary studies were included. Convincing evidence (class I) supported robotic superiority for acceptable placement versus freehand (eOR = 2.74; 95% CI: 2.33-3.22) and versus navigation (eOR = 2.36; 95% CI: 1.73-3.22), and for perfect placement versus navigation (eOR = 2.47; 95% CI: 1.84-3.32). Highly suggestive evidence (class II) supported superior perfect placement (vs freehand) and shorter hospital stays. Suggestive evidence (class III) indicated reductions in intraoperative blood loss and radiation exposure. Conclusion: Robot-assisted pedicle screw placement demonstrates superior accuracy versus freehand and navigation-guided methods, supported by convincing (class I) evidence. Highly suggestive (class II) evidence also supports its superiority in perfect placement and shortening hospital stays, while suggestive (class III) evidence indicates reduced blood loss and radiation. These findings, supported by a robust evidence base, underscore the need for standardized clinical guidelines to maximize impact on patient outcomes.
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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.