Evidence map›Paper›PMID 36614807›Full record

ReviewJournal of clinical medicine2022

Narrative Review of Classification Systems Describing Laryngeal Vascularity Using Advanced Endoscopic Imaging.

Peter Kántor, Lucia Staníková, Anna Švejdová, Karol Zeleník, Pavel Komínek

Open access · goldAbstract readReview
In one paragraph

Review in Journal of clinical medicine, 2022. 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
0.6field-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, 4 citations in OpenAlex.

  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

5 authors at 2 institutions in 1 country.

Peter KántorDepartment of Otorhinolaryngology and Head and Neck Surgery, University Hospital Ostrava, 708 52 Ostrava, Czech Republic.ORCID 0000-0003-0057-754X
Lucia StaníkováDepartment of Otorhinolaryngology and Head and Neck Surgery, University Hospital Ostrava, 708 52 Ostrava, Czech Republic.
Anna ŠvejdováDepartment of Otorhinolaryngology and Head and Neck Surgery, University Hospital Hradec Králove, Faculty of Medicine in Hradec Králove, Charles University, 500 03 Hradec Králové, Czech Republic.ORCID 0000-0002-9052-0549
Karol ZeleníkDepartment of Otorhinolaryngology and Head and Neck Surgery, University Hospital Ostrava, 708 52 Ostrava, Czech Republic.ORCID 0000-0003-1349-9958
Pavel KomínekDepartment of Otorhinolaryngology and Head and Neck Surgery, University Hospital Ostrava, 708 52 Ostrava, Czech Republic.
University of Ostrava · CZCharles University · CZ

Funding

University of Ostrava SGS08/LF/2022
6 · The paper itself

Abstract

Endoscopic methods are critical in the early diagnosis of mucosal lesions of the head and neck. In recent years, new examination methods and classification systems have been developed and introduced into clinical practice. All of these new techniques target the notion of optical biopsy, which tries to assess the nature of the lesion before histology examination. Many methods suffer from interpretation issues due to subjective interpretation of the findings. Therefore, multiple classification systems have been developed to assist the proper interpretation of mucosal findings and reduce the error rate. They provide various perspectives on the assessment and interpretation of mucosa changes. This article provides a comprehensive and critical view of the available classification systems as well as their advantages and disadvantages.

Indexed as

enhanced contact endoscopylaryngeal cancerlarynxleukoplakianarrow-band imagingStorz Professional Image Enhancement System

Identifiers

PMID36614807
PMCPMC9821525
OpenAlexW4311963186

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.