MétaCan
Menu
← Back to cohort

Thrombosis in Immune Thrombocytopenia Patients with Antiphospholipid Antibodies: A Meta-Analysis

2015· article· en· W2979396655 on OpenAlexaboutno aff
Guillaume Moulis, Alexandra Audermard-Verger, Laurent Arnaud, Cécile Luxembourger, François Montastruc, Amelia Maria Găman, Elisabet Svenungsson, Marco Ruggeri, Matthieu Mahévas, Mathieu Gerfaud‐Valentin, Andrés Brainsky, Marc Michel, Bertrand Godeau, Laurent Guy, Maryse Mapeyre-mestre, L. Sailler

Bibliographic record

VenueBlood · 2015
Typearticle
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInternal medicineMeta-analysisLupus anticoagulantThrombosisOdds ratioPublication biasAntiphospholipid syndromeRheumatology

Abstract

fetched live from OpenAlex

Abstract Background: Thrombosis during immune thrombocytopenia (ITP) management is a critical issue. Among suspected risk factors for thrombosis in ITP patients, the role of antiphospholipid antibodies (aPL) is controversial. We performed a systematic review and a meta-analysis to investigate risk of thrombosis with lupus anticoagulant (LA), anticardiolipin (aCL) and anti-β2GP1 antibodies in primary ITP. Methods: Literature search was computed on Medline, Cochrane and ISI Web of Sciences by two independent investigators from January 1st 1980 to December 31st 2014. Unpublished studies were searched in meeting abstracts of the American Society of Hematology, the European Haematology Association, the American College of Rheumatology and the European League Against Rheumatism. Inclusion criteria were observational studies including primary ITP patients where presence of aPL was documented (LA, aCL or anti-β2GP1 antibodies). We assessed the occurrence of thrombotic events in these studies. Two investigators performed data extraction. All authors were contacted in order to confirm or provide complementary data if needed. Study quality was assessed using the NewCastle-Ottawa (NOS) scale. The main analysis assessed the risk of all thromboses (arterial or venous) associated with the presence of LA, aCL or anti-β2GP1 antibodies. Sensitivity analyses were performed, restricted to the best quality studies. We also also stratified the risk of arterial and venous thrombosis separately. Random effect (Der Simonian & Laird) models were used. Heterogeneity was assessed using the I2 index. Odds ratio (OR) and their 95% confidence intervals (95%CI) were computed. Publication bias was searched using Egger's test and funnel plot. Results: Searching in electronic databases retrieved 776 citations, completed by 12 additional studies from unpublished literature. Out of them, 44 studies were identified for a full-length text review. Eventually, 10 cohort studies totalizing 1010 patients were selected (9 with LA, 6 with aCL, 2 with anti-β2GP1 antibody dosages). Five studies were prospective and 5 retrospective. The median NOS score was 6 (range: 4-8). The pooled OR for the risk of all thromboses associated with LA positivity was 6.11, 95%CI [3.40-10.99] (I2 =0%, Egger's test: p=0.37). It was 2.13, 95%CI [1.11-4.12] with aCL (I2 =0%, Egger's test: p=0.14). Sensitivity analyses restricted to studies with quality score ≥6 led to similar results. The OR for arterial thrombosis was 5.52, 95%CI [2.40-12.70] with LA and 2.12, 95%CI [0.84-5.33] with aCL. The OR for venous thrombosis was 5.13, 95%CI [2.31-11.40] with LA and 2.00, 95%CI [0.83-4.81] with aCL. Only two studies assessed the risk of thrombosis associated with anti-β2GP1 antibody positivity, with high heterogeneity (I2 =81%). Consequently, no pooled OR was computed. Conclusions: This meta-analysis demonstrates that aPL positivity in ITP patients is a risk factor for thrombosis. The risk was three times higher with LA than with aCL. It was similar for arterial and venous thromboses. For practicing clinicians, our results imply that systematic aPL determinations should be performed in ITP, since aPL positivity and associated thrombosis risk should influence the choice of treatment. Disclosures Michel: Roche: Research Funding; GSK: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AMGEN: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees. Godeau:Roche: Research Funding; Amgen: Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau.

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)0.012
metaresearch head score (Gemma)0.022
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: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.022
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0160.049
Bibliometrics0.0050.006
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0030.002
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 head0.052
GPT teacher head0.288
Teacher spread0.237 · 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
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

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueBlood→Same topicPlatelet Disorders and Treatments→French-language works237,207→