Evidence map›Paper›PMID 33553380›Full record

ReviewAnnals of translational medicine2021

Preoperative planning for intraoperative navigation guidance.

Shahbaaz A Sabri, Philip J York

Abstract readReview
In one paragraph

Review in Annals of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Review
  2. [Research on surgical instrument segmentation algorithm based on frequency-domain adaptive feature decomposition and visual Mamba].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2026
    Article
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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

2 authors.

Shahbaaz A SabriDepartment of Orthopedic Surgery, University of Colorado School of Medicine, Aurora, CO, USA.
Philip J YorkDepartment of Orthopedic Surgery, University of Colorado School of Medicine, Aurora, CO, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Intraoperative navigation for spinal procedures has continued to gain popularity. Numerous platforms are currently on the market and offer a spectrum of features. Preoperative considerations when utilizing this technology begin with understanding the fundamental concepts and methods of navigation. Several key factors including patient positioning, reference array placement, and sequence of instrumentation can help improve intraoperative navigation workflow when planned appropriately. The authors review current literature to help guide surgeon decision making when utilizing navigation. Additionally, tips and techniques for use of navigation are detailed to help avoid common surgeon pitfalls. In general, navigation platforms are classified based on image acquisition and degree of surgeon motion restriction during instrumentation. Imageless platforms often require preoperative images to be uploaded into the navigation system. Image-based systems rely on intraoperative imaging to ensure accuracy of its referencing software. The system then creates a three-dimensional model that allows for visualization of the navigated instrument within the surgical field. Active and passive navigation describe the degree of surgeon free-motion restriction when utilizing navigated instruments. Active navigation platforms, such as most robotic systems, prevent the deviation of the surgeon's instrument from a predetermined trajectory. Passive navigation does not restrict surgeon motion and the projected trajectory of the instrumented can be displayed on a three-dimensional model.

Indexed as

intraoperative navigationmobile CTNavigationO-arm

Identifiers

PMID33553380
PMCPMC7859791

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.