Evidence map›Paper›PMID 35387888›Full record

ArticleInternational journal of spine surgery2022

Management of Thoracic Disc Pathology via the Lateral Approach: Advances Using the Minimally Invasive Approach and Navigation.

Saman Shabani, Praveen V Mummaneni, Andrew Chan, Jeremy Huang, Nitin Agarwal, Vedat Deviran, Dean Chou

Open access · diamondAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of spine surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
0.7field-weighted citation impact, top 31% of its field
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 synthesis or guideline pooled it, 5 citations in OpenAlex.

  1. Pooled it
  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

7 authors at 2 institutions in 1 country.

Saman ShabaniDepartment of Neurological Surgery, University of California, San Francisco, CA, USA saman.shabani@protonmail.com.
Praveen V MummaneniDepartment of Neurological Surgery, University of California, San Francisco, CA, USA.
Andrew ChanDepartment of Neurological Surgery, University of California, San Francisco, CA, USA.
Jeremy HuangDepartment of Neurological Surgery, University of California, San Francisco, CA, USA.
Nitin AgarwalDepartment of Neurological Surgery, University of California, San Francisco, CA, USA.
Vedat DeviranDepartment of Orthopedic Surgery, University of California, San Francisco, CA, USA.
Dean ChouDepartment of Neurological Surgery, University of California, San Francisco, CA, USA.
University of California, San Francisco · USUniversity of California System · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Historically, thoracic disc pathology has been treated via open thoracotomy or open posterior costotransversectomy or lateral extracavitary approaches. However, these approaches are associated with approach-related morbidity. With advancement in such minimally invasive approaches as the lateral interbody fusion coupled with navigation, the morbidity of approaching anterior thoracic spinal pathology may be reduced. There are subtleties and nuances in the thoracic approaches that are different from the lateral lumbar interbody approaches. We discuss our technique of the minimally invasive approach to the thoracic spine, management of the rib and pleura, and incorporation of navigation into the procedure.

Indexed as

laterallateral surgerylateral thoracic discectomyminimally invasive surgeryretropleural approachthoracic discthoracic fusion

Identifiers

PMID35387888
PMCPMC9983567
OpenAlexW4224302667

What OpenQuestion holds

Textmetadata
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.