MétaCan
Menu
Back to cohort
Record W4409172274 · doi:10.1177/09612033251332258

Thrombocytopenia and autoimmune hemolytic anemia in antiphospholipid antibody-positive patients: Descriptive analysis of the AntiPhospholipid syndrome alliance for clinical trials and InternatiOnal networking (APS ACTION) clinical database and repository (“Registry”)

2025· article· en· W4409172274 on OpenAlexaff
Zeynep Belce Erton, Rebecca Karp Leaf, Danieli Andrade, Ann E. Clarke, Maria G. Tektonidou, Vittorio Pengo, Savino Sciascia, José Pardos‐Gea, Nina Kello, D. Paredes, C. López-Pedrera, H. Michael Belmont, Paul R. Fortin, Guilherme Ramires de Jesús, Tatsuya Atsumi, Zhouli Zhang, Maria Efthymiou, D. Ware Branch, Giulia Pazzola, Laura Andréoli, Alí Duarte‐García, Esther Rodríguez-Almaraz, Michelle Petri, Ricard Cervera, Bahar Artım-Esen, Rosana Quintana, Hui Shi, Yu Zuo, Rohan Willis, Megan R W Barber, Leslie Skeith, Massimo Radin, Pier Luigi Meroni, María Laura Bertolaccini, Hannah Cohen, Robert Roubey, Doruk Erkan

Bibliographic record

VenueLupus · 2025
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsUniversité LavalUniversity of Calgary
FundersNational Center for Advancing Translational SciencesNational Institute of Arthritis and Musculoskeletal and Skin Diseases
KeywordsMedicineAntiphospholipid syndromeAutoimmune hemolytic anemiaInternal medicineLupus anticoagulantSerologyAnemiaRheumatologySystemic lupus erythematosusImmunologyGastroenterologyAntibodyDiseaseThrombosis

Abstract

fetched live from OpenAlex

Background/Purpose APS ACTION Registry was created to study the natural course of antiphospholipid syndrome (APS) over 10 years in persistently antiphospholipid antibody (aPL) positive patients with or without systemic autoimmune rheumatic diseases (SARDs). Our primary objective was to compare the characteristics of aPL-positive patients with or without thrombocytopenia (TP) and/or autoimmune hemolytic anemia (AIHA). Methods The registry inclusion criteria are positive aPL based on the Revised Sapporo APS Classification Criteria, tested at least twice within 1 year prior to enrollment. For the primary comparison of demographic, clinical, and serologic characteristics in this retrospective study, we divided patients into two groups: TP/AIHA ever and never. Thrombocytopenia was defined as a platelet count of <100,000 x 10 9 /L tested twice at least 12 weeks apart, and AIHA was defined as anemia with hemolysis and a positive direct antiglobulin test (DAT). For the secondary analysis, we compared patients with TP versus AIHA, and the immunosuppressive use stratified by systemic lupus erythematosus (SLE) classification. Results As of April 2022, of 1,039 patients (primary aPL/APS: 618 [59%]; SLE classification: 334 [31%]) included in the registry, 228 (22%) had baseline (historical or current) TP and/or AIHA (TP only: 176 [17%]; AIHA only: 35 [3%], and both: 17 [2%]). Thrombocytopenia and/or AIHA was significantly associated with Asian race, SLE classification, cardiac valve disease, catastrophic/microvascular APS, triple aPL (lupus anticoagulant, anticardiolipin antibody, and anti-β 2 -glycoprotein-I antibody) positivity, and SLE-related serologic and inflammatory markers. When 101/618 (16%) primary aPL/APS patients and 101/334 (34%) SLE patients with TP and/or AIHA were compared, azathioprine and mycophenolate mofetil were more commonly reported in lupus patients, however corticosteroid, intravenous immunoglobulin, and rituximab use were similar between groups. Conclusion In our large multi-center international cohort of persistently aPL-positive patients, approximately one-fifth had active or historical TP and/or AIHA at registry entry; half of these patients had additional SLE. Cardiac valve disease, catastrophic/microvascular APS, and triple aPL-positivity were aPL-related clinical and laboratory manifestations associated with TP and/or AIHA, suggesting a more severe APS clinical phenotype in aPL-patients with TP and/or AIHA.

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)0.004
metaresearch head score (Gemma)0.003
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 score0.013
Threshold uncertainty score0.790

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.117
GPT teacher head0.459
Teacher spread0.342 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueLupusSame topicSystemic Lupus Erythematosus ResearchFrench-language works237,207