ArticleExpert review of clinical immunology2015
Inflammatory myopathy: diagnosis and clinical course, specific clinical scenarios and new complementary tools.
Article in Expert review of clinical immunology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed, 16 citations in OpenAlex.
- [Atypical arthritis of the hands : Collagenosis-part 1].Der Radiologe · 2021Review
- Reflex testing of speckled cytoplasmic patterns observed in routine ANA HEp-2 indirect immunofluorescence with a multiplex anti-synthetase dot-blot assay: a multicentric pilot study.Immunologic research · 2018Article
- Quantitative 3D scintigraphy shows increased muscular uptake of pyrophosphate in idiopathic inflammatory myopathy.EJNMMI research · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
Idiopathic inflammatory myopathies are a heterogeneous group of rare autoimmune diseases characterized by symmetric proximal muscle weakness and inflammatory infiltrates on muscle biopsy. A meticulously collected combination of clinical, serological, and pathological data is essential to correctly diagnose and classify myositis patients, often a considerable challenge for clinicians. This article provides a comprehensive overview of the most useful tools for the diagnosis and follow-up of patients with myositis. Capillaroscopy, serological biomarkers (particularly the autoantibody profile) and imaging techniques, such as muscle magnetic resonance and chest ultrasound, are of great aid in diagnosing, classifying and managing these patients. Relevant clinical scenarios, such as interstitial lung disease, associated cancer and pregnancy are also addressed in this review. Myositis registries, identification of new autoantibodies, and genetic studies will enhance our understanding of the pathogenesis of these conditions and help to define new diagnostic and therapeutic approaches.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.