Evidence map›Paper›PMID 35794905›Full record

ReviewTherapeutic advances in musculoskeletal disease2022

Big data analyses and individual health profiling in the arena of rheumatic and musculoskeletal diseases (RMDs).

Diederik De Cock, Elena Myasoedova, Daniel Aletaha, Paul Studenic

Open access · goldAbstract readReview
In one paragraph

Review in Therapeutic advances in musculoskeletal disease, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.4field-weighted citation impact, top 11% 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

6 citing papers in PubMed, 15 citations in OpenAlex.

  1. Observational
  2. Review
  3. Article
  4. Review
  5. Article
  6. 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 4 institutions in 4 countries.

Diederik De CockClinical and Experimental Endocrinology, Department of Chronic Diseases and Metabolism, KU Leuven, Leuven, Belgium.
Elena MyasoedovaDivision of Rheumatology, Department of Internal Medicine and Division of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
Daniel AletahaDivision of Rheumatology, Department of Internal Medicine 3, Medical University Vienna, Vienna, Austria.
Paul StudenicDivision of Rheumatology, Department of Internal Medicine 3, Medical University Vienna, Waehringer Guertel 18-20, 1090 Vienna, Austria.ORCID https://orcid.org/0000-0002-8895-6941
Karolinska Institutet · SEKU Leuven · BEMayo Clinic · USMedical University of Vienna · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Health care processes are under constant development and will need to embrace advances in technology and health science aiming to provide optimal care. Considering the perspective of increasing treatment options for people with rheumatic and musculoskeletal diseases, but in many cases not reaching all treatment targets that matter to patients, care systems bare potential to improve on a holistic level. This review provides an overview of systems and technologies under evaluation over the past years that show potential to impact diagnosis and treatment of rheumatic diseases in about 10 years from now. We summarize initiatives and studies from the field of electronic health records, biobanking, remote monitoring, and artificial intelligence. The combination and implementation of these opportunities in daily clinical care will be key for a new era in care of our patients. This aims to inform rheumatologists and healthcare providers concerned with chronic inflammatory musculoskeletal conditions about current important and promising developments in science that might substantially impact the management processes of rheumatic diseases in the 2030s.

Indexed as

e-healthelectronic health recordshealth care servicespersonalized medicineprecision medicineprecision medicine diagnostic testsremote monitoringrheumatic and musculoskeletal disease

Identifiers

PMID35794905
PMCPMC9251966
OpenAlexW4285184547

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.