Evidence map›Paper›PMID 37564913›Full record

ArticleNorth American Spine Society journal2023

The use of robot-assisted surgery for the unstable traumatic spine: A retrospective cohort study.

Luis Daniel Diaz-Aguilar, Nolan J Brown, Nicholas Bui, Bejan Alvandi, Zach Pennington, Julian Gendreau, Sunil P Jeswani, Martin H Pham, David R Santiago-Dieppa, Andrew D Nguyen

Abstract read
In one paragraph

Article in North American Spine Society journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
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  3. 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

10 authors.

Luis Daniel Diaz-AguilarDepartment of Neurosurgery, University of California San Diego, La Jolla, CA, 92093 USA.
Nolan J BrownDepartment of Neurosurgery, University of California Irvine, Orange, CA, 92868 USA.
Nicholas BuiDepartment of Neurosurgery, University of California Irvine, Orange, CA, 92868 USA.
Bejan AlvandiDepartment of Orthopaedic Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611 USA.
Zach PenningtonDepartment of Neurologic Surgery, Mayo Clinic, Rochester, MN, 55905 USA.
Julian GendreauJohns Hopkins Whiting School of Engineering, Baltimore, MD, 21205 USA.
Sunil P JeswaniDepartment of Neurosurgery, University of California San Diego, La Jolla, CA, 92093 USA.
Martin H PhamDepartment of Neurosurgery, University of California San Diego, La Jolla, CA, 92093 USA.
David R Santiago-DieppaDepartment of Neurosurgery, University of California San Diego, La Jolla, CA, 92093 USA.
Andrew D NguyenDepartment of Neurosurgery, University of California San Diego, La Jolla, CA, 92093 USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Robotic assistance has been shown to increase instrumentation placement accuracy in open and minimally invasive spinal fusion. These gains have been achieved without increases in operative times, blood loss, or hospitalization duration. However, most work has been done in the degenerative population and little is known of the utility of robotic assistance when applied to spinal trauma. This is largely due to the uncertainty stemming from the disruption of normal anatomy by the traumatic injury. Since the robot depends upon registration for instrumentation guidance according to the fiducials it uses, trauma can introduce unique challenges. The present study sought to evaluate the safety and efficacy of robotic assistance in a consecutive cohort of spine trauma patients. Methods: All patients with Thoracolumbar Injury Classification and Severity Scale (TLICS) >4 who underwent robot-assisted spinal fusion using the Globus ExcelsiusGPS at a single tertiary care center for trauma between 2020 and 2022 were identified. Demographic, clinical, and surgical data were collected and analyzed; the primary endpoints were operative time, fluoroscopy time, estimated blood loss, postoperative complications, admission time, and 90-day readmission rate. The paired t-test was used to compare differences between mean values when looking at the number of surgical levels. Results: Forty-two patients undergoing robot-assisted spinal surgery were included (mean age 61.3±17.1 year; 47% female. Patients were stratified by the number of operative levels, 2 (n = 10), 3-4 (n = 11), 5 to 6 (n = 13), or >6 (n = 8). There appeared to be a positive correlation between number of levels instrumented and odds of postoperative complications, admission duration, fluoroscopy time, and estimated blood loss. There were no instances of screw malposition or breach. Conclusions: This initial experience suggests robotic assistance can be safely employed in the spine trauma population. Additional experiences in larger patient populations are necessary to delineate those traumatic pathologies most amenable to robotic assistance.

Indexed as

ImagingRadiographRegistrationRoboticsSpineTrauma

Identifiers

PMID37564913
PMCPMC10410240

What OpenQuestion holds

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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.