Evidence map›Paper›PMID 40176860›Full record

ArticleBioMedicine2025

Robotic spine surgery - Surgical technique and nuances for improving safety.

Mun Chun Lai, Pirateb Paramasivam Meenakshi Sundaram, Arun-Kumar Kaliya-Perumal, Jacob Yoong-Leong Oh

Abstract read
In one paragraph

Article in BioMedicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

4 authors.

Mun Chun LaiDivision of Spine, Department of Orthopaedic Surgery, Tan Tock Seng Hospital, Singapore.ORCID https://orcid.org/0000-0001-6603-4236
Pirateb Paramasivam Meenakshi SundaramDivision of Spine, Department of Orthopaedic Surgery, Tan Tock Seng Hospital, Singapore.
Arun-Kumar Kaliya-PerumalRehabilitation Research Institute of Singapore, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore.ORCID https://orcid.org/0000-0002-2747-4500
Jacob Yoong-Leong OhDivision of Spine, Department of Orthopaedic Surgery, Tan Tock Seng Hospital, Singapore.ORCID https://orcid.org/0000-0002-2832-8433

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The integration of robotic technology into spinal surgery has led to a remarkable transformation, offering improved precision and safety. The "CT-Fluoro merge" and "Scan-and-Plan" methods for pedicle screw application promise numerous advantages, minimizing risks associated with traditional approaches. Our early series of patients who underwent robot-assisted pedicle screw placements for various indications, predominantly lumbar spondylosis, revealed no complications related to screws, neurological deficits, or unplanned returns to the operating theatre, thus emphasizing the safety and effectiveness of the robot. Studies have consistently demonstrated the superiority of robot-assisted pedicle screw placement in terms of accuracy, with decreasing rates of technical issues indicating improvements in reliability and precision. Our experiences align with these findings, signalling the emergence of robotic spine surgery as the forthcoming standard of care in the field. This short communication explores the steps involved in robotic pedicle screw placement, discusses nuances for improving safety, and emphasizes its benefits and implications for the future of spinal care.

Indexed as

Computer-assisted surgeriesImage guided surgeryPatient safetyRoboticsSpinal spondylosis

Identifiers

PMID40176860
PMCPMC11959973

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.