Evidence map›Paper›PMID 31766590›Full record

ArticleJournal of clinical medicine2019

A Nomogram to Predict the Outcome of Fine Needle Aspiration Cytology in Head and Neck Masses.

Ulana Kotowski, Faris F Brkic, Oskar Koperek, Eleonore Pablik, Stefan Grasl, Matthaeus Ch Grasl, Boban M Erovic

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical medicine, 2019. 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
0.4field-weighted citation impact, top 32% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. 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

7 authors at 1 institution in 1 country.

Ulana KotowskiDepartment of Otorhinolaryngology and Head and Neck Surgery, Medical University of Vienna, 1090 Vienna, Austria.ORCID 0000-0002-8771-3104
Faris F BrkicDepartment of Otorhinolaryngology and Head and Neck Surgery, Medical University of Vienna, 1090 Vienna, Austria.
Oskar KoperekDepartment of Pathology, Medical University of Vienna, 1090 Vienna, Austria.ORCID 0000-0002-0191-8126
Eleonore PablikCeMSIIS, Section for Medical Statistics, Medical University Vienna, 1090 Vienna, Austria.
Stefan GraslDepartment of Otorhinolaryngology and Head and Neck Surgery, Medical University of Vienna, 1090 Vienna, Austria.
Matthaeus Ch GraslDepartment of Otorhinolaryngology and Head and Neck Surgery, Medical University of Vienna, 1090 Vienna, Austria.
Boban M ErovicInstitute of Head and Neck Diseases, Evangelical Hospital Vienna, 1180 Vienna, Austria.
Medical University of Vienna · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fine needle aspiration cytology (FNAC) is an important diagnostic tool for tumors of the head and neck. However, non-diagnostic or inconclusive results may occur and lead to delay in treatment. The aim of this study was to evaluate the factors that predict a successful FNAC. A retrospective search was performed to identify all patients who received an FNAC at the Department of Otorhinolaryngology, Head and Neck Surgery, Medical University of Vienna. The variables were patients' age and sex, localization and size of the punctured structure, previous radiotherapy, experience of the head and neck surgeon, experience of the pathologist and the FNAC result. Based on these parameters, a nomogram was subsequently created to predict the probability of accurate diagnosis. After performing 1221 FNACs, the size of the punctured lesion (

Indexed as

cancerfine needle aspiration cytologyneck lumpsnomogramsalivary gland

Identifiers

PMID31766590
PMCPMC6947452
OpenAlexW2990133036

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.