Evidence map›Paper›PMID 38033853›Full record

ReviewFrontiers in cell and developmental biology2023

Current advances of photobiomodulation therapy in treating knee osteoarthritis.

Yanlei Zhang, Quanbo Ji

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in cell and developmental biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
2.3field-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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Review
  4. Article
  5. Article
  6. Article
  7. 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 2 institutions in 1 country.

Yanlei ZhangMedical School of Chinese PLA, Beijing, China.
Quanbo JiDepartment of Orthopedics, The General Hospital of Chinese PLA, Beijing, China.
Chinese PLA General Hospital · CNPLA Academy of Military Science · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Knee osteoarthritis (KOA) is manifested by low-grade joint inflammation, irreversible cartilage degeneration, subchondral bone remodeling and osteophyte formation. It is one of the most prevalent degenerative diseases in the elderly. KOA usually results in chronic joint pain, physical impairment even disability bringing a huge socioeconomic burden. Unfortunately, there is so far no effective interventions to delay the progression and development of KOA. There is a pressing need for explorations and developments of new effective interventions. Photobiomodulation therapy (PBMT), also known as low-level light therapy (LLLT), has attracted widespread attention in treating KOA because it is drug-free, non-invasive, safe and useful with rarely reported side effects. It provides the biological stimulatory effects primarily by enhancing the activity of mitochondrial cytochrome c oxidase. This stimulation, in turn, fosters cell proliferation and tissue regeneration. In addition to this, the paper provides a concise overview of the light parameters and the effectiveness of PBMT when applied in the treatment of KOA patients in clinical settings. It also delves into the experimental evidence supporting the modulatory effects of PBMT and its potential underlying mechanisms in addressing synovitis, cartilage degeneration, and pain resolution.

Indexed as

knee osteoarthritismacrophage polarizationpainphotobiomodulation therapysynovial inflammation

Identifiers

PMID38033853
PMCPMC10687633
OpenAlexW4388728424

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.