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Record W4315927645 · doi:10.1080/09537104.2022.2157807

Management of immune thrombotic thrombocytopenic purpura with caplacizumab: a Canadian, single-centre, real-world experience

2023· article· en· W4315927645 on OpenAlexaffabout
Brandon Tse, Megan Buchholz, Katerina Pavenski

Bibliographic record

VenuePlatelets · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicComplement system in diseases
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicinePlateletThrombotic thrombocytopenic purpuraThrombocytopenic purpuraImmune thrombocytopeniaInternal medicine

Abstract

fetched live from OpenAlex

When combined with therapeutic plasma exchange (TPE) and immunosuppression, upfront universal administration of caplacizumab was shown to be effective in the management of immune thrombotic thrombocytopenic purpura (iTTP). However, access to this drug remains challenging in many jurisdictions. We retrospectively review results of a single-institution experience with caplacizumab over a 3-year period. During the study period, we treated 48 patients with iTTP, of which 11 (23%) received caplacizumab. Eight of these 11 patients (73%) were female; the median age was 45 years (IQR 37.0-58.5). All received TPE within 24 h of admission (median 9 exchanges, IQR 7.0-12.5), and high-dose steroids. Caplacizumab was initiated for a median of 6 days after admission (IQR 2.5-8.0) and continued for a median of 26 days (IQR 14.0-33.0). Five patients (45%) had refractory disease at caplacizumab initiation. Ten patients (91%) survived, reaching clinical remission. Platelet normalization was reached with a median of 4 days following caplacizumab initiation (IQR 1.5-4.0). Complications included minor bleeding (n = 1) and local allergic reaction (n = 1). No patients experienced TTP exacerbation; relapse occurred in two patients (18%) over 1-5 years of follow-up. Caplacizumab appeared to be effective and safe, despite delayed initiation and in the setting of refractory disease.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.608
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.031
GPT teacher head0.261
Teacher spread0.231 · 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; both teacher heads agree on what is shown here.

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

Citations10
Published2023
Admission routes2
Has abstractyes

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