Evidence map›Paper›PMID 42696239›Full record

ArticleJournal of robotic surgery2026

Robotically equipped 3D hybrid operating room in spine and trauma surgery - updated experience in 359 patients and 2080 screws.

Dominik M Haida, Peter Mohr, Thorsten Möhlig, Friedemann Meiswinkel, Mircea-Andrei Ungureanu, Thorsten Enk, Marc Hanschen, Stefan Huber-Wagner

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

8 authors.

Dominik M HaidaTechnical University of Munich, School of Medicine and Health, TUM Klinikum, Rechts der Isar, Department of Trauma Surgery, Ismaninger Straße 22, 81675, Munich, Germany.
Peter MohrDIAK Klinikum Landkreis Schwäbisch Hall, Radiation Protection, Diakoniestraße 10, 74523, Schwäbisch Hall, Germany.
Thorsten MöhligDIAK Klinikum Landkreis Schwäbisch Hall, Department of Trauma, Spine & Orthopaedic Surgery, Level-I Trauma Centre, Spine Centre (DWG), Diakoniestraße 10, 74523, Schwäbisch Hall, Germany.
Friedemann MeiswinkelDIAK Klinikum Landkreis Schwäbisch Hall, Department of Trauma, Spine & Orthopaedic Surgery, Level-I Trauma Centre, Spine Centre (DWG), Diakoniestraße 10, 74523, Schwäbisch Hall, Germany.
Mircea-Andrei UngureanuDIAK Klinikum Landkreis Schwäbisch Hall, Department of Trauma, Spine & Orthopaedic Surgery, Level-I Trauma Centre, Spine Centre (DWG), Diakoniestraße 10, 74523, Schwäbisch Hall, Germany.
Thorsten EnkDIAK Klinikum Landkreis Schwäbisch Hall, Department of Neurosurgery, Diakoniestraße 10, 74523, Schwäbisch Hall, Germany.
Marc HanschenTechnical University of Munich, School of Medicine and Health, TUM Klinikum, Rechts der Isar, Department of Trauma Surgery, Ismaninger Straße 22, 81675, Munich, Germany.
Stefan Huber-WagnerTechnical University of Munich, School of Medicine and Health, TUM Klinikum, Rechts der Isar, Department of Trauma Surgery, Ismaninger Straße 22, 81675, Munich, Germany. s.huber-wagner@tum.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Modern techniques, such as robotics and navigation, alongside cutting-edge imaging solutions like cone beam CT imaging, are playing an increasingly prominent role in spine and trauma surgery within so-called Hybrid ORs. This study aims to contribute to the ongoing scientific discussion surrounding accuracy rates and learning curves in the utilisation of a modern Hybrid OR. In a Level 1 trauma centre, a 3D Navigation-Hybrid OR was implemented, and a prospective data collection was launched (March 2022 - June 2025). Analysis was performed retrospectively. The Hybrid OR consists of a robotic cone beam CT "Loop-X", a robotic arm "Cirq Arm System", a navigation unit "Curve Navigation System", a wall-mounted monitor "BUZZ" and Elements Viewer 3D mixed reality glasses for planning (Brainlab, Munich, Germany). Intervention areas included the entire skeletal system, encompassing the spine, pelvis (pelvic ring and acetabulum), and extremities, with various indications, primarily trauma (fractures) and oncology (tumours). The focus of this study is to assess accuracy rates and learning curves. In n = 359 patients, 2080 screws were inserted. 1881 (90.4%) spinal screws were inserted with an accuracy rate (GR-A & GR-B) of 98.5% (CI95%: 97.9% - 99.0%). A total of 199 (9.6%) non-spinal screws were inserted with an accuracy rate of 99.0% (CI95%: 97.6% - 99.9%). The overall accuracy rate of screw placement was therefore 98.5% (CI95%: 98.0% - 99.0%). Minimally invasive techniques were used in 243 (67.7%) cases and the robotic arm was utilised in 271 (75.5%) cases. Subgroup analyses revealed a significant learning curve (p < 0.001) and a significant reduction in operation times over time (p = 0.008). Wound infection occurred in 10 (2.8%) cases, and 17 (4.7%) patients died during hospitalisation. This study demonstrates that a 3D-Navigation Hybrid OR can be successfully integrated into the clinical routine of a level 1 trauma centre. It shows promising results for interventions on the entire skeletal system, with consistently high accuracy rates and low complication rates. Furthermore, it highlights a significant learning curve and a significant reduction in operation times over time.

Indexed as

Bone ScrewsImaging, Three-DimensionalOperating RoomsRobotic Surgical ProceduresSpineAdultAgedCone-Beam Computed TomographyFemaleHumansLearning CurveMaleMiddle AgedRetrospective StudiesAcetabulumCone beam CT (CBCT)Hybrid ORLearning curveMixed-RealityNavigationNeurosurgeryPelvisRobotic armRobotics

Identifiers

PMID42696239
PMCPMC13545108

What OpenQuestion holds

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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.