Evidence map›Paper›PMID 38803169›Full record

ReviewCurrent rheumatology reviews2025

A Review of Connecting Bioinformatic Techniques to Rheumatoid Arthritis and its Associated Comorbidities.

Yeswanth Ranganathan, Pritam Ramesh Kumar, Sudhakar Gandhi Paramasivam, Ravi Shankar Krishnan

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current rheumatology reviews, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Yeswanth RanganathanDepartment of Biotechnology, University College of Engineering, BIT Campus, Anna University, Tiruchirappalli, 620024, India.ORCID 0009-0004-8085-0167
Pritam Ramesh KumarDepartment of Biotechnology, University College of Engineering, BIT Campus, Anna University, Tiruchirappalli, 620024, India.
Sudhakar Gandhi ParamasivamDepartment of Biotechnology, University College of Engineering, BIT Campus, Anna University, Tiruchirappalli, 620024, India.
Ravi Shankar KrishnanDepartment of Biotechnology, University College of Engineering, BIT Campus, Anna University, Tiruchirappalli, 620024, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rheumatoid Arthritis (RA) is a progressive autoimmune condition inflicting serious threats to people's life and health by causing severe pain and joint destruction. It affects not only bones and joints but also causes comorbid conditions and shortens the lifetime. The interactions and synergistic effects of comorbid disease with RA are not yet well studied. Hence, understanding how these conditions will collectively affect the progression and outcome of RA is the current area of research. Identification of RA and comorbidities associated with target genes may uncover diagnosis and treatment methodologies. This review is to provide an overview of the interlinking approach of Rheumatoid Arthritis with its comorbid conditions and its systemic complications using bioinformatic techniques which would be useful to identify the genes and pathways that are in common for both RA and comorbid diseases. It would also emphasize the significance of bioinformatics in comparing the pathological features of RA and comorbid diseases. With the help of bioinformatics, valuable insights into the mechanism underlying Rheumatoid arthritis and comorbid diseases would be better understood.

Indexed as

Arthritis, RheumatoidComputational BiologyComorbidityHumansautoimmune.bioinformatic techniquescomorbid diseasesgenespathwaysRheumatoid arthritis

Identifiers

PMID38803169

What Socratic 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 Socratic graph.