Evidence map›Paper›PMID 33990898›Full record

ReviewFrontiers of medicine2021

Advances in tissue state recognition in spinal surgery: a review.

Hao Qu, Yu Zhao

Abstract readReview
PubMed Publisher
In one paragraph

Review in Frontiers of medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 21% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.

  1. Pooled it
  2. AI-driven tissue discrimination sensing methods for robot-assisted spine surgery: a state-of-the-art review.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026
    Review
  3. Recent Advances in the Treatment of Spinal Cord Injury.The archives of bone and joint surgery · 2024
    Review
  4. 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

2 authors at 2 institutions in 1 country.

Hao QuDepartment of Orthopaedics, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
Yu ZhaoDepartment of Orthopaedics, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China. zhaoyupumch@126.com.
Chinese Academy of Medical Sciences & Peking Union Medical College · CNPeking Union Medical College Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Spinal disease is an important cause of cervical discomfort, low back pain, radiating pain in the limbs, and neurogenic intermittent claudication, and its incidence is increasing annually. From the etiological viewpoint, these symptoms are directly caused by the compression of the spinal cord, nerve roots, and blood vessels and are most effectively treated with surgery. Spinal surgeries are primarily performed using two different techniques: spinal canal decompression and internal fixation. In the past, tactile sensation was the primary method used by surgeons to understand the state of the tissue within the operating area. However, this method has several disadvantages because of its subjectivity. Therefore, it has become the focus of spinal surgery research so as to strengthen the objectivity of tissue state recognition, improve the accuracy of safe area location, and avoid surgical injury to tissues. Aside from traditional imaging methods, surgical sensing techniques based on force, bioelectrical impedance, and other methods have been gradually developed and tested in the clinical setting. This article reviews the progress of different tissue state recognition methods in spinal surgery and summarizes their advantages and disadvantages.

Indexed as

Decompression, SurgicalHumansbioelectrical impedanceforce sensingimagespinal surgerytissue state recognition

Identifiers

PMID33990898
OpenAlexW3161551447

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.