Evidence map›Paper›PMID 41253301›Full record

ArticleAsian spine journal2026

Recent advances in robotic-assisted laminectomy in spine surgery: a narrative review.

Tarun Mattikalli, Konstantinos Margetis, James D Lin, Jeremy Steinberger

Abstract read
In one paragraph

Article in Asian spine journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Tarun MattikalliDepartment of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Konstantinos MargetisDepartment of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
James D LinDepartment of Orthopaedic Surgery, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Jeremy SteinbergerDepartment of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Robotic-assisted laminectomy (RAL) is an emerging technique in spine surgery that can potentially improve precision, safety, and efficiency. While robotic-assisted pedicle screw placement is well established, RAL remains in early stages with varied methodologies and primarily pre-clinical validation. This narrative review evaluates current evidence on RAL, focusing on bone cutting tools, resection strategies, state recognition techniques for real-time identification of bone type and surgical endpoints, and clinical applications to inform future advancements. A comprehensive literature search was conducted using PubMed, Embase, and Cochrane databases with relevant keywords and operators to maximize sensitivity. Twenty-seven studies met predefined inclusion and exclusion criteria. Evaluated cutting tools included burrs, drills, and ultrasonic osteotomes. Burrs and drills provided superior state recognition feedback, while ultrasonic devices offered better force control and reduced thermal damage. Cyclic dorsal-ventral drilling was found to be superior to layer-by-layer resection for ultrasonic cutting. The only clinical study of RAL in a human patient is a case report demonstrating robotic-guided, surgeon-operated laminar bone removal. While RAL shows promise in improving surgical accuracy, the lack of in vivo data and standardized methodology remains a key barrier to clinical adoption. Future research should prioritize comparative evaluation of cutting modalities, clinical validation in human subjects, and long-term outcome studies to support the broader integration of RAL into spine surgery.

Indexed as

LaminectomyRobotic surgical procedureSpinal stenosisSpine

Identifiers

PMID41253301
PMCPMC13153968

What OpenQuestion holds

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LicenceCC BY-NC
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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.