Evidence map›Paper›PMID 30457569›Full record

ArticleScientific data2018

A reference set of curated biomedical data and metadata from clinical case reports.

J Harry Caufield, Yijiang Zhou, Anders O Garlid, Shaun P Setty, David A Liem, Quan Cao, Jessica M Lee, Sanjana Murali, Sarah Spendlove, Wei Wang and 6 more

Abstract readDataset
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific data, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Review
  7. Review
  8. The h-ANN Model: Comprehensive Colonoscopy Concept Compilation Using Combined Contextual Embeddings.Biomedical engineering systems and technologies, international joint conference, BIOSTEC ... revised selected papers. BIOSTEC (Conference) · 2022
    Article
  9. Bacteriocins: Properties and potential use as antimicrobials.Journal of clinical laboratory analysis · 2022
    Review
  10. Article
  11. A Second Look at FAIR in Proteomic Investigations.Journal of proteome research · 2021
    Article
  12. Review
  13. Review
  14. 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

16 authors.

J Harry CaufieldThe NIH BD2K Center of Excellence in Biomedical Computing, University of California at Los Angeles, Los Angeles, CA 90095, USA.
Yijiang ZhouThe NIH BD2K Center of Excellence in Biomedical Computing, University of California at Los Angeles, Los Angeles, CA 90095, USA.
Anders O GarlidThe NIH BD2K Center of Excellence in Biomedical Computing, University of California at Los Angeles, Los Angeles, CA 90095, USA.
Shaun P SettyDepartment of Pediatric and Adult Congenital Cardiac Surgery, Miller Children's and Women's Hospital and Long Beach Memorial Hospital, Long Beach, CA 90806, USA.
David A LiemThe NIH BD2K Center of Excellence in Biomedical Computing, University of California at Los Angeles, Los Angeles, CA 90095, USA.
Quan CaoThe NIH BD2K Center of Excellence in Biomedical Computing, University of California at Los Angeles, Los Angeles, CA 90095, USA.ORCID 0000-0002-1566-8850
Jessica M LeeThe NIH BD2K Center of Excellence in Biomedical Computing, University of California at Los Angeles, Los Angeles, CA 90095, USA.
Sanjana MuraliThe NIH BD2K Center of Excellence in Biomedical Computing, University of California at Los Angeles, Los Angeles, CA 90095, USA.
Sarah SpendloveThe NIH BD2K Center of Excellence in Biomedical Computing, University of California at Los Angeles, Los Angeles, CA 90095, USA.ORCID 0000-0002-5439-0863
Wei WangThe NIH BD2K Center of Excellence in Biomedical Computing, University of California at Los Angeles, Los Angeles, CA 90095, USA.
Li ZhangDepartment of Cardiology, First Affiliated Hospital, Zhejiang University School of Medicine, 310003, Hangzhou, Zhejiang, P.R. China.
Yizhou SunThe NIH BD2K Center of Excellence in Biomedical Computing, University of California at Los Angeles, Los Angeles, CA 90095, USA.
Alex BuiThe NIH BD2K Center of Excellence in Biomedical Computing, University of California at Los Angeles, Los Angeles, CA 90095, USA.
Henning HermjakobThe NIH BD2K Center of Excellence in Biomedical Computing, University of California at Los Angeles, Los Angeles, CA 90095, USA.ORCID 0000-0001-8479-0262
Karol E WatsonThe NIH BD2K Center of Excellence in Biomedical Computing, University of California at Los Angeles, Los Angeles, CA 90095, USA.
Peipei PingThe NIH BD2K Center of Excellence in Biomedical Computing, University of California at Los Angeles, Los Angeles, CA 90095, USA.

Funding

TRAININGU54GM114833 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI LINDSEY, MERRY L., PING, PEIPEI · 2014 to 2017
$13.8M
Omics Phenotyping for Identifying Molecular Signatures of the Healthy and Failing Heart: An Integrated Data Science PlatformR35HL135772 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI PING, PEIPEI · 2017 to 2023
$6.4M
NHLBI NIH HHS R35 HL135772NIGMS NIH HHS U54 GM114833
6 · The paper itself

Abstract

Clinical case reports (CCRs) provide an important means of sharing clinical experiences about atypical disease phenotypes and new therapies. However, published case reports contain largely unstructured and heterogeneous clinical data, posing a challenge to mining relevant information. Current indexing approaches generally concern document-level features and have not been specifically designed for CCRs. To address this disparity, we developed a standardized metadata template and identified text corresponding to medical concepts within 3,100 curated CCRs spanning 15 disease groups and more than 750 reports of rare diseases. We also prepared a subset of metadata on reports on selected mitochondrial diseases and assigned ICD-10 diagnostic codes to each. The resulting resource, Metadata Acquired from Clinical Case Reports (MACCRs), contains text associated with high-level clinical concepts, including demographics, disease presentation, treatments, and outcomes for each report. Our template and MACCR set render CCRs more findable, accessible, interoperable, and reusable (FAIR) while serving as valuable resources for key user groups, including researchers, physician investigators, clinicians, data scientists, and those shaping government policies for clinical trials.

Indexed as

Clinical Studies as TopicData CurationMetadataComputational BiologyData AnalysisHumans

Identifiers

PMID30457569
PMCPMC6244181

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.