Evidence map›Paper›PMID 36149471›Full record

ReviewBundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz2022

[Rare-disease data standards].

Peter N Robinson, Holm Graessner

Abstract readEnglish AbstractReview
In one paragraph

Review in Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Identification of metabolite-disease associations based on knowledge graph.Metabolomics : Official journal of the Metabolomic Society · 2025
    Article
  3. Article
  4. [Healthcare networks for people with rare diseases: integrating data and expertise].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2022
    Review
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

2 authors.

Peter N RobinsonThe Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, 06032, Farmington, CT, USA. peter.robinson@jax.org.
Holm GraessnerInstitut für Medizinische Genetik und Angewandte Genomik, Zentrum für Seltene Erkrankungen, Universitätsklinikum Tübingen, Tübingen, Deutschland.

Funding

The Human Phenotype Ontology: Accelerating Computational Integration of Clinical Data for GenomicsU24HG011449 · NHGRI · JACKSON LABORATORY · PI Peter Nicholas Robinson · 2021 to 2026
$6.7M
NHGRI NIH HHS U24 HG011449
6 · The paper itself

Abstract

The use of standardized data formats (data standards) in healthcare supports four main goals: (1) exchange of data, (2) integration of computer systems and tools, (3) data storage and archiving, and (4) support of federated databases. Standards are especially important for rare-disease research and clinical care.In this review, we introduce healthcare standards and present a selection of standards that are commonly used in the field of rare diseases. The Human Phenotype Ontology (HPO) is the most commonly used standard for annotating phenotypic abnormalities and supporting phenotype-driven analysis of diagnostic exome and genome sequencing. Numerous standards for diseases are available that support a range of needs. Online Mendelian Inheritance in Man (OMIM) and the Orphanet Rare Disease Ontology (ORDO) are the most important standards developed specifically for rare diseases. The Mondo Disease Ontology (Mondo) is a new disease ontology that aims to integrate data from a comprehensive range of current nosologies. New standards and schemas such as the Medical Action Ontology (MAxO) and the Global Alliance for Genomics and Health (GA4GH) phenopacket are being introduced to extend the scope of standards that support rare disease research.In order to provide optimal care for patients with SE in different healthcare settings, it will be necessary to better integrate standards for rare disease with electronic healthcare resources such as the Fast Healthcare Interoperability Resources (FHIR) standard for healthcare data exchange.

Indexed as

Databases, GeneticRare DiseasesElectronic Health RecordsGermanyHumansInformation Storage and RetrievalPhenotypeNosologyOntologyRare diseasesStandards for healthcare dataTerminology

Identifiers

PMID36149471
PMCPMC9636095

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.