Evidence map›Paper›PMID 40191588›Full record

ReviewBrain & spine2025

Advancing spine surgery: Evaluating the potential for full robotic automation.

Nicolás Samprón, Jesus Lafuente, Jorge Presa-Alonso, Marcel Ivanov, Roger Hartl, Florian Ringel

Abstract readReview
In one paragraph

Review in Brain & spine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Management of Severe Rigid Scoliosis: Best practices and controversies.Journal of clinical orthopaedics and trauma · 2025
    Article
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

6 authors.

Nicolás SamprónDepartment of Neurosurgery, Hospital Universitario Donostia, San Sebastian, Spain.
Jesus LafuenteDepartment of Neurosurgery, Hospital del Mar, Barcelona, Spain.
Jorge Presa-AlonsoCyber Surgery, San Sebastián, Spain.
Marcel IvanovDepartment of Neurosurgery, Royal Hallamshire Hospital, Sheffield, UK.
Roger HartlDepartment of Neurological Surgery, Och Spine at New York Presbyterian Hospital, Weill Cornell Medicine, New York, USA.
Florian RingelDepartment of Neurosurgery, University Medical Center, Mainz, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The use of robotic systems in spine surgery is expanding, with growing interest in the potential for full automation. This review explores current robotic technologies, their limitations, and future automation possibilities, focusing on technical and practical aspects. Research question: What are the current capabilities and limitations of robotic systems in spine surgery, and how might advancements in tracking technologies facilitate a transition toward greater automation? Material and methods: A narrative review of literature on robotic spine surgery systems was conducted, analyzing benefits, accuracy, limitations, and innovations necessary for full automation. Focus was placed on trajectory-guiding technologies, such as optical tracking and alternative tracking methods. Results: Current robotic systems (e.g., Cirq®, Mazor X™, ExcelsiusGPS™) assist in trajectory guidance but lack autonomy. Optical tracking systems present challenges, such as obstruction vulnerability and inaccuracies in complex constructs. Conversely, encoder-based tracking demonstrated superior accuracy, offering a promising pathway toward increased automation. The potential advantages of robotics over conventional navigation, including their nature and clinical relevance, remain a topic of active discussion. However, the inherent complexity of spine surgery and the critical role of human decision-making remain substantial barriers. Discussion and conclusion: While full automation in robotic spine surgery is not yet attainable, advancements in tracking technologies point to a future of enhanced robot-surgeon collaboration, which could optimize clinical outcomes and improve procedural safety.

Indexed as

AutomationCollaborative robotsEncoder-based systemsRobotic Spine surgeryTracking technologies

Identifiers

PMID40191588
PMCPMC11968298

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.