Evidence map›Paper›PMID 33578686›Full record

ReviewJournal of personalized medicine2021

Personalized Medicine Using Neuroimmunological Biomarkers in Depressive Disorders.

Suhyuk Chi, Moon-Soo Lee

Open access · goldAbstract readReview
In one paragraph

Review in Journal of personalized medicine, 2021. 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
0.4field-weighted citation impact, top 51% 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

4 citing papers in PubMed, 32 citations in OpenAlex.

  1. Review
  2. Molecular Biomarkers for Pediatric Depressive Disorders: A Narrative Review.International journal of molecular sciences · 2021
    Review
  3. Exploring the therapeutic potential of omega-3 fatty acids in depression.Environmental science and pollution research international · 2021
    Review
  4. Neuroimmunology and (Epi)Genetics in Depressive Disorders.Journal of personalized medicine · 2021
    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

2 authors at 1 institution in 1 country.

Suhyuk ChiDepartment of Psychiatry, Korea University Guro Hospital, Seoul 08308, Korea.ORCID 0000-0002-4977-6200
Moon-Soo LeeDepartment of Psychiatry, Korea University Guro Hospital, Seoul 08308, Korea.ORCID 0000-0003-0729-6943
Korea University Medical Center · KR

Funding

National Research Foundation of Korea NRF-2017R1D1A1B03028672
6 · The paper itself

Abstract

Major depressive disorder (MDD) is associated with increased suicidal risk and reduced productivity at work. Neuroimmunology, the study of the immune system and nervous system, provides further insight into the pathogenesis and outcome of MDD. Cytokines are the main modulators of neuroimmunology, and their levels are somewhat entangled in depressive disorders as they affect depressive symptoms and are affected by antidepressant treatment. The use of cytokine-derived medication as a treatment option for MDD is currently a topic of interest. Although not very promising, cytokines are also considered as possible prognostic or diagnostic markers for depression. The machine learning approach is a powerful tool for pattern recognition and has been used in psychiatry for finding useful patterns in data that have translational meaning and can be incorporated in daily clinical practice. This review focuses on the current knowledge of neuroimmunology and depression and the possible use of machine learning to widen our understanding of the topic.

Indexed as

cytokinesdepressionmachine learningneuroimmunology

Identifiers

PMID33578686
PMCPMC7916349
OpenAlexW3128940621

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.