Evidence map›Paper›PMID 38711247›Full record

ReviewMedical science monitor : international medical journal of experimental and clinical research2024

Optimizing Behçet Uveitis Management: A Review of Personalized Immunosuppressive Strategies.

Biao Li, Kaiyao Chi, Haoran Li, Jing Wang, Yanlin Zheng

Abstract readReview
In one paragraph

Review in Medical science monitor : international medical journal of experimental and clinical research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Biao LiDepartment of Ophthalmology, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China (mainland).
Kaiyao ChiDepartment of Ophthalmology, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China (mainland).
Haoran LiDepartment of Ophthalmology, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China (mainland).
Jing WangDepartment of Ophthalmology, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China (mainland).
Yanlin ZhengDepartment of Ophthalmology, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China (mainland).

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Behçet uveitis poses significant management challenges, owing to its intricate pathogenesis and the severe prognosis it harbors, frequently culminating in irreversible visual impairment and an elevated risk of blindness. This review synthesizes contemporary insights into personalized immunosuppressive strategies for Behçet uveitis, emphasizing the necessity for a customized approach in recognition of the disease's heterogeneity and the variable responsiveness to treatment. This discourse elaborates on the application, efficacy, and safety profiles of traditional immunosuppressants, highlighting a paradigm shift toward integrative combination therapies aimed at diminishing reliance on glucocorticoids and mitigating their associated adverse effects. This thorough evaluation seeks to enlighten clinical practices and spearhead future investigations aimed at refining the management of Behçet uveitis, championing a personalized, multidisciplinary strategy to amplify therapeutic efficacy and enhance patient quality of life.

Indexed as

Behcet SyndromeImmunosuppressive AgentsUveitisHumansPrecision MedicineQuality of LifeImmunosuppressive Agents

Identifiers

PMID38711247
PMCPMC11088284

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.