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Record W4389132875 · doi:10.1136/bmjresp-2023-002076

Association of anti-Ro52 autoantibody with interstitial lung disease in autoimmune diseases: a systematic review and meta-analysis

2023· review· en· W4389132875 on OpenAlexaboutno aff
Sepehr Nayebirad, Aida Mohamadi, Hannaneh Yousefi‐Koma, Minoo Javadi, Kimia Farahmand, Reza Atef‐Yekta, Zahra Tamartash, Mana Jameie, Amir Mohammad Mohammadzadegan, Hoda Kavosi

Bibliographic record

VenueBMJ Open Respiratory Research · 2023
Typereview
Languageen
FieldMedicine
TopicInflammatory Myopathies and Dermatomyositis
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInterstitial lung diseaseAutoantibodyMeta-analysisInternal medicinePopulationCochrane LibraryObservational studyAutoimmune diseaseDiseaseImmunologyAntibodyLungEnvironmental health

Abstract

fetched live from OpenAlex

Objectives Interstitial lung disease (ILD) is an important manifestation of autoimmune diseases that can lead to morbidity and mortality. Although several autoantibodies have been linked with ILD presentation and adverse outcomes, the association of anti-Ro52 antibody with ILD is less studied. Hence, we investigated this association in various autoimmune diseases in the current study. Design We designed a systematic review and meta-analysis and did a comprehensive search from inception until 2 January 2023. Data sources A systematic search was conducted in four electronic databases: PubMed, Web of Science, Scopus and Embase. Eligibility criteria Observational studies that reported ILD diagnosis (outcome) and anti-Ro antibody (exposure) status in any autoimmune conditions (population) were included. The association between rapidly progressive ILD (RP-ILD) and anti-Ro52 was studied in idiopathic inflammatory myopathies (IIM). Data extraction and synthesis Collected data included study characteristics and ORs with 95% CIs. Quality assessment was performed using a modified version of the Newcastle-Ottawa Scale for cross-sectional studies. Random effects meta-analysis was used to pool the effect estimates. Results A total of 2353 studies were identified, from which 59 articles met the eligibility criteria. Anti-Ro52/SSA positivity was associated with ILD in all autoimmune disease subgroups: IIM (OR=3.08; 95% CI: 2.18 to 4.35; p value<0.001; I 2 =49%), systemic lupus (OR=2.43; 95% CI: 1.02 to 5.79; p=0.046; I 2 =71%), Sjogren (OR=1.77; 95% CI: 1.09 to 2.87; p=0.021; I 2 =73%), systemic sclerosis (OR=1.71; 95% CI: 1.04 to 2.83; p=0.036; I 2 =43%), mixed connective tissue disease (OR=3.34; 95% CI: 1.82 to 6.13; p<0.001; I 2 =0%). Additionally, anti-Ro52-positive myopathy patients were more likely to have simultaneous RP-ILD (OR=2.69; 95% CI:1.50 to 4.83; p<0.001; I 2 =71%). Conclusion Anti-Ro52/SSA positivity is associated with a higher frequency of ILD diagnosis in various autoimmune diseases. Anti-Ro52/SSA is also linked with a more severe lung involvement (RP-ILD). Future studies can investigate the benefits of screening for anti-Ro52 and its association with ILD development. PROSPERO registration number CRD42022381447.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.022
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.034
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0220.041
Bibliometrics0.0090.011
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.235
GPT teacher head0.512
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations76
Published2023
Admission routes1
Has abstractyes

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