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Record W2416036256

Antiendothelial cell antibodies in inflammatory myopathies: distribution among clinical and serologic groups and association with interstitial lung disease.

2000· article· en· W2416036256 on OpenAlexaff
David D’Cruz, Gökhan Keser, M A Khamashta, Haner Di̇reskeneli̇, Ira N. Targoff, Frederick W. Miller, G R Hughes

Bibliographic record

VenuePubMed · 2000
Typearticle
Languageen
FieldMedicine
TopicInflammatory Myopathies and Dermatomyositis
Canadian institutionsWomen's Health Research Institute
Fundersnot available
KeywordsMedicineAutoantibodyInterstitial lung diseaseSerologyMyositisAntisynthetase syndromeDermatomyositisConnective tissue diseaseSystemic diseaseImmunopathologyAntibodyImmunologyInternal medicinePathologyLungGastroenterologyAutoimmune disease
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine the prevalence and associations of antiendothelial cell antibodies (AECA) in a well characterized cohort of patients with idiopathic inflammatory myopathies (IIM). METHODS: Clinical characteristics, AECA, and myositis-specific autoantibodies were assessed by standard methods in 56 subjects with IIM. RESULTS: AECA were found in 20/56 patients with IIM, were seen in all the major clinical and serologic IIM groups, and were found in 10/15 patients with interstitial lung disease (ILD) (chi squared 6.5, p<0.01 with Yates' correction, relative risk 2.7, specificity 86% and sensitivity 50%). Antisynthetase antibodies, also associated with ILD as described (chi squared = 26.5, p<0.001 with Yates' correction, relative risk 8.7, specificity 95%, sensitivity 77%), did not correlate with the presence of AECA. CONCLUSION: AECA appear to be present in all forms of IIM and are markers for ILD that are independent of anti-synthetase autoantibodies. AECA may be a useful serologic marker for ILD in IIM.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.596

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.212
Teacher spread0.206 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations28
Published2000
Admission routes1
Has abstractyes

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