Evidence map›Paper›PMID 38892808›Full record

ReviewJournal of clinical medicine2024

Diagnosis and Treatment of Uveitis in Children: A Summary of the Latest Data from a 5-Year Literature Review (2018-2023).

Monika Modrzejewska, Oliwia Zdanowska

Abstract readReview
In one paragraph

Review in Journal of clinical medicine, 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. Review
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.

Monika ModrzejewskaSecond Chair and Department of Ophthalmology, Pomeranian Medical University in Szczecin in Poland, Al. Powstańców Wlkp. 72, 70-111 Szczecin, Poland.ORCID 0000-0002-9221-8909
Oliwia ZdanowskaK. Marcinkowski University Hospital in Zielona Góra, 65-046 Zielona Góra, Poland.ORCID 0009-0008-5432-3653

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pediatric uveitis has a low incidence. It is very diverse in its presentation and is often the first sign of a severe systemic disease. The pediatric population poses a special therapeutic and diagnostic challenge due to the potentially adverse effects of therapeutic agents on the young body and difficult cooperation with the patient during the examination, as well as the increased risk of complications that can lead to severe disability. The most commonly diagnosed type of uveitis is non-infectious, with first-line therapy consisting of systemic corticosteroids followed by disease-modifying drugs (methotrexate (MTX), mycophenolate mofetil (MMF), and cyclosporin A (CsA)). In severe, refractory cases, biologic therapy is used. The authors reviewed the current literature on the etiology, diagnostic tools, and treatment of uveitis in the pediatric population covering the years 2018-2023, presenting current methods of modern diagnosis and treatment. The reason for writing this article was the need to update the knowledge on uveitis, driven by the increasing prevalence of autoimmune uveitis in the pediatric population. This trend presents significant challenges in diagnosing and treating the disease, as well as managing its complications. Correctly identifying the pathogenetic factor of uveitis can facilitate the diagnosis of the systemic disease underlying the ocular infection and enable the timely implementation of systemic treatment. Furthermore, the emergence of new diagnostic methods necessitates a revision and update of ophthalmic knowledge, essential for both ophthalmologists and other specialists involved in the treatment of uveitis.

Indexed as

diagnosisoptical coherence tomographypediatric uveitisreviewtreatment

Identifiers

PMID38892808
PMCPMC11172654

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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.