Evidence map›Paper›PMID 33506017›Full record

ArticleBioMed research international2021

Rong Yu, Lv Liu, Ya-Li Li, Liang-Liang Fan

Open access · hybridAbstract readCase Reports
In one paragraph

Article in BioMed research international, 2021. 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
0.3field-weighted citation impact, top 45% 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

4 authors at 2 institutions in 1 country.

Rong YuDepartment of Anesthesiology, The Second Xiangya Hospital, Central South University, Changsha 410011, China.ORCID https://orcid.org/0000-0001-5777-0629
Lv LiuDepartment of Respiratory Medicine, Diagnosis and Treatment Center of Respiratory Disease, Diagnosis and Treatment Center of Respiratory Disease, The Second Xiangya Hospital of Central South University, Changsha 410011, China.ORCID https://orcid.org/0000-0001-9719-9930
Ya-Li LiDepartment of Reproductive Genetics, HeBei General Hospital, Shijiazhuang 050051, China.ORCID https://orcid.org/0000-0002-6889-5539
Liang-Liang FanDepartment of Reproductive Genetics, HeBei General Hospital, Shijiazhuang 050051, China.ORCID https://orcid.org/0000-0001-7431-1838
Central South University · CNHebei General Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Waardenburg syndrome (WS) is a group of rare genetic disorders characterized by hearing loss, changes in coloring of hair, skin, and eyes, and alterations in the shape of the face. Tietz syndrome is another rare disorder which presented similar phenotypes to WS. Patients with Tietz/Waardenburg syndrome often present with pale blue eyes, albino skin, and distinctive hair coloring, such as a patch of white hair or hair that prematurely turns gray. At present, more than six candidate genes are responsible for four types of Waardenburg syndrome and Tietz syndrome. This study is aimed at identifying the pathogenic gene variants in a three-generation Han Chinese family with hearing loss, blue-gray iris, albino skin, and white hair. In order to discover the molecular genetic lesion underlying the disease phenotype, whole exome sequencing in the proband, with Tietz/Waardenburg syndrome phenotypes, of a Han Chinese family from HeBei, China, was conducted. A novel heterozygous c.650G>C/p.Arg217Thr variant in

Indexed as

Albinism, OculocutaneousDeafnessWaardenburg SyndromeAdultAsian PeopleChinaEye ColorFemaleHumansMaleMiddle AgedPedigreePolymorphism, GeneticTranscription FactorsTranscription Factors

Identifiers

PMID33506017
PMCPMC7815406
OpenAlexW3120933513

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.