Evidence map›Paper›PMID 35382520›Full record

ReviewJournal of scleroderma and related disorders2020

Big data in systemic sclerosis: Great potential for the future.

Mislav Radic, Tracy M Frech

Abstract readReview
In one paragraph

Review in Journal of scleroderma and related disorders, 2020. 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
–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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Novel therapies and innovation for systemic sclerosis skin ulceration.Best practice & research. Clinical rheumatology · 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.

Mislav RadicDepartment of Rheumatology, University of Utah, Salt Lake City, UT, USA.ORCID https://orcid.org/0000-0003-0350-6800
Tracy M FrechDepartment of Rheumatology, University of Utah, Salt Lake City, UT, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since it was first used in 1997, the term "big data" has been popularized; however, the concept of big data is relatively new to medicine. Big data refers to a method and technique to systematically retrieve, collect, manage, and analyze very large and complex sets of structured and unstructured data that cannot be sufficiently processed using traditional methods of processing data. Integrating big data in rare diseases with low prevalence and incidence, like systemic sclerosis is of particular importance. We conducted a literature review of use of big data in systemic sclerosis. The volume of data on systemic sclerosis has grown steadily in the recent years; however, big data methods have not been readily used. This inexhaustible source of data needs to be used more to unleash its full potential.

Indexed as

big datamethodologyrare diseasesregistriesSystemic sclerosis

Identifiers

PMID35382520
PMCPMC8922620

What OpenQuestion holds

Textmetadata
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.