Evidence map›Paper›PMID 36468920›Full record

ArticleArchives of endocrinology and metabolism2023

Development and validation of the clinical report form for nodular thyroid pathologies.

Vanessa Neto, Sara Esteves-Ferreira, Isabel Inácio, Márcia Alves, Rosa Dantas, Teresa Azevedo, Joana Guimarães, Maria Teresa Herdeiro, Alexandra Nunes

Abstract read
In one paragraph

Article in Archives of endocrinology and metabolism, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Vanessa NetoInstituto de Biomedicina (iBiMED), Departamento de Ciências Médicas, Universidade de Aveiro, Aveiro, Portugal.
Sara Esteves-FerreiraCentro Hospitalar do Baixo Vouga (CHBV), Aveiro, Portugal.
Isabel InácioCentro Hospitalar do Baixo Vouga (CHBV), Aveiro, Portugal.
Márcia AlvesCentro Hospitalar do Baixo Vouga (CHBV), Aveiro, Portugal.
Rosa DantasCentro Hospitalar do Baixo Vouga (CHBV), Aveiro, Portugal.
Teresa AzevedoCentro Hospitalar do Baixo Vouga (CHBV), Aveiro, Portugal.
Joana GuimarãesInstituto de Biomedicina (iBiMED), Departamento de Ciências Médicas, Universidade de Aveiro, Aveiro, Portugal.
Maria Teresa HerdeiroInstituto de Biomedicina (iBiMED), Departamento de Ciências Médicas, Universidade de Aveiro, Aveiro, Portugal.
Alexandra NunesInstituto de Biomedicina (iBiMED), Departamento de Ciências Médicas, Universidade de Aveiro, Aveiro, Portugal, alexandranunes@ua.pt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The aim of this study is to develop and validate a novel clinical report form in the format of a structured interview to enable the characterization of the Portuguese population of the Baixo Vouga region with different subtypes of nodular thyroid pathologies (NTyPs). Materials and methods: A structured interview was developed and to the best of our knowledge, this is the first structured interview built and validated for that purpose in Portugal. Results: This structured interview enables the identification of possible correlations between each subtype of nodular lesions and sociodemographic data, consumption habits and lifestyle, endocrine history, and family predisposition. Conclusion: The novel structured interview will simultaneously, enable a detailed characterization of the group of patients with nodular thyroid lesions and will support future metabolomic studies.

Indexed as

Goiter, NodularThyroid GlandHumansPortugalclinical report formcohort characterizationNodular thyroid pathologiesstructured interview

Identifiers

PMID36468920
PMCPMC9983788

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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.