Evidence map›Paper›PMID 42223737›Full record

ArticleJournal of robotic surgery2026

Robotic-assisted pedicle screw placement achieves high accuracy and narrows the experience gap: a preclinical evaluation.

Anna T Reza, Matthias Walper, Mitchell K Ng, Paul G Mastrokostas, Andrew S Lee, Rafael G de Oliveira, Kornelis A Poelstra, John K Ratliff, Rajiv K Sethi, Michael A Mont

Abstract read
In one paragraph

Article in Journal of robotic surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Anna T RezaStryker (United States), Kalamazoo, USA.
Matthias WalperStryker (United States), Kalamazoo, USA.
Mitchell K NgRothman Orthopaedic Institute, Thomas Jefferson University Hospital, Philadelphia, USA. mitchng77@gmail.com.
Paul G MastrokostasDepartment of Orthopaedic Surgery, Maimonides Medical Center, Brooklyn, USA.
Andrew S LeeThe Robotic Spine Institute of Las Vegas, Allegiant Spine Institute, Las Vegas, USA.
Rafael G de OliveiraThe Robotic Spine Institute of Las Vegas, Allegiant Spine Institute, Las Vegas, USA.
Kornelis A PoelstraThe Robotic Spine Institute of Las Vegas, Allegiant Spine Institute, Las Vegas, USA.
John K RatliffStanford University, Stanford, USA.
Rajiv K SethiVirginia Mason Medical Center, Seattle, USA.
Michael A MontDepartment of Orthopaedic Surgery, Rubin Institute for Advanced Orthopedics, Baltimore, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To assess a robotic-assisted system versus open manual techniques to: (1) compare pedicle screw accuracy between fellows and attendings with and without robotic assistance, and (2) evaluate executed versus planned trajectory fidelity relative to prior reports. Robotic-assisted spine systems aim to improve the accuracy, reproducibility, and safety of pedicle screw placement. Limited evidence compares outcomes across differing surgeon experience levels. A total of 255 thoracolumbar pedicle screws were placed in synthetic torsos simulating adult degenerative anatomy. Four surgeons (two fellows, two attendings) each placed half their screws using open fluoroscopy-guided techniques and half using a minimally invasive percutaneous approach with the Mako Spine system and intraoperative CT-based planning. Postoperative CT and the Gertzbein-Robbins classification were used to assess accuracy. Optimal placement (Grade A), breach rates, and positional/angular deviation from planned trajectories were recorded. The robotic cohort achieved a higher rate of clinically acceptable screw placement compared with the manual cohort, although this difference was not statistically significant (124/127, 97.6% vs. 120/128, 93.8%; P = 0.223). Fellows and attendings both achieved high clinically acceptable screw placement rates using robotics (63/64, 98.4% vs. 61/63, 96.8%). Among fellows, robotic assistance increased optimal screw placement compared with the manual technique (53/64, 82.8% vs. 41/64, 64.1%; P < 0.05). Robotic screws demonstrated low mean deviations from planned trajectories (1.4 ± 0.9 mm positional, 1.7 ± 1.1° angular). The Mako Spine system enabled precise screw placement and narrowed performance gaps for less experienced surgeons. It shows promise as both training tool and means to standardize outcomes.

Indexed as

Clinical CompetencePedicle ScrewsRobotic Surgical ProceduresFluoroscopyHumansLumbar VertebraeMinimally Invasive Surgical ProceduresReproducibility of ResultsTomography, X-Ray ComputedAccuracyGertzbein-Robbins classificationPedicle screw placementRobot-assisted spine surgerySurgical training

Identifiers

PMID42223737
PMCPMC13226373

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Registered trials

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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.