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Management of Vasculitis-associated Alveolar Hemorrhage: A Bayesian Reanalysis of PEXIVAS

2025· article· en· W4410274077 on OpenAlexaff
Omri Avraham Arbiv, L. Fidler, A.S. Gershon, K. Liu

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicHeparin-Induced Thrombocytopenia and Thrombosis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineVasculitisDiffuse alveolar hemorrhageBayesian probabilityIntensive care medicinePathologyArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract RATIONALE: Diffuse alveolar hemorrhage (DAH) is a rare and life-threatening manifestation of antineutrophil-cytoplasmic antibody (ANCA)-associated vasculitis (AAV). PEXIVAS was a randomized-controlled trial that showed that plasma exchange (PLEX) did not improve outcomes in patients with AAV, and that a reduced-dose glucocorticoid taper was non-inferior to standard-dose taper. However, a minority of patients in PEXIVAS had DAH, which may limit the generalizability of these findings. We used a Bayesian approach to reanalyze PEXIVAS to evaluate the effect of these interventions on patients with DAH. METHODS: PEXIVAS enrolled adults with granulomatosis and polyangiitis or microscopic polyangiitis with either DAH or reduced kidney function. Individuals were randomized in 2x2 design to PLEX or no PLEX and standard-dose or reduced-dose glucocorticoid taper, the latter of which was designed as a non-inferiority trial. Our primary outcome was the hazard ratio (HR) of overall survival. Published means and standard deviations of HR were used in the Bayesian framework as the likelihood, modelled as a log-normal distribution using a non-informative prior (i.e., implying no prior belief). We obtained the posterior mean HR and 95% credible interval (CrI), as well as the probability that PLEX reduced mortality (HR <1) or that reduced-dose glucocorticoids led to greater mortality (HR >1) by calculating the area under the curve (AUC) of the posterior distribution beyond each threshold. RESULTS: 704 individuals were recruited in PEXIVAS, of which 191 had DAH. Using a non-informative prior, we found that mean HR with PLEX was 0.45 (95% CrI 0.14-1.42) for those with DAH and 0.86 (95% CrI 0.43-1.71) without DAH. By evaluating AUC, we found that PLEX led to a 67% probability of increased survival (HR <1) in those without DAH, but a 93% probability of increased survival in those with DAH. With a reduced-dose glucocorticoid taper, individuals without DAH had a mean HR 0.46 (95% CrI 0.22-0.95), whereas those with DAH had a mean HR 1.33 (95% CrI 0.57-3.11). Reduced-dose glucocorticoid taper corresponded to a 2% probability of increased mortality (HR >1) in individuals without DAH, but a 74% probability of increased mortality in those with DAH. CONCLUSION: Using a Bayesian approach, we show that individuals with AAV with DAH may benefit from PLEX, although appear to derive greater harm from a reduced-dose glucocorticoid taper. These results suggest the need for further review of treatment strategies in this subpopulation.

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)0.030
metaresearch head score (Gemma)0.091
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.030
Threshold uncertainty score0.157

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.091
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.017
GPT teacher head0.330
Teacher spread0.313 · 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 designSimulation or modeling
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
Published2025
Admission routes1
Has abstractyes

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