MétaCan
Menu
Back to cohort

Adjudicating Bleeding Outcomes in a Large Thromboprophylaxis Trial in Critical Illness.

2009· article· en· W2590044361 on OpenAlexaff
Donald M. Arnold, Christian Rabbat, François Lauzier, Nicole Zytaruk, Diane Heels‐Ansdell

Bibliographic record

VenueBlood · 2009
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsUniversité de SherbrookeSt. Joseph’s Healthcare HamiltonMcMaster UniversityCanadian Blood Services
Fundersnot available
KeywordsBleedMedicineMajor bleedingAdjudicationPsychological interventionKappaEmergency medicineIntensive care medicineInternal medicineSurgeryAtrial fibrillationPsychiatry

Abstract

fetched live from OpenAlex

Abstract Abstract 2471 Poster Board II-448 Background: Adjudication in clinical trials can confirm or refute eligibility, describe cointerventions, judge appropriateness of care, or assess the severity of morbidity outcomes. Objective: To refine the adjudication process, calibrate 4 adjudicators, and measure agreement on bleeding severity in an international trial of heparin thromboprophylaxis (PROTECT). Methods: Independently and blinded to each others' ratings and study drug, 4 adjudicators used web-based methods to examine 40 charts of patients assessed by local research coordinators to have either major (20 patients) or minor (20 patients) bleeding. We discussed reasons for disagreement after the first 20 charts to remediate and recalibrate. We calculated crude agreement, chance-corrected agreement (kappa), and chance-independent agreement (phi). Results: For 45 events in 40 patients, pair-wise crude agreement ranged from 86.7-93.3% (average 82.2%). Overall kappa was 0.81. Phi (which can only analyze pair-wise values) ranged from 0.75-0.87. We resolved all disagreements. During adjudication discussions, we 1) addressed methodological issues (e.g., handling recurrent bleeds), 2) added a category (e.g., no bleed), 3) expanded a category (e.g., a major bleed did not have to be overt if other criteria were fulfilled), and 4) divorced procedure-grounded definitions (such as the need for transfusion or therapeutic interventions) from bleeding severity criteria (e.g., the patient could still be classified as having no bleed or a minor bleed if 2 units of PRBCs were transfused for anemia). Conclusions: After independent quadruplicate review of 45 bleeding events, we documented satisfactory agreement for bleeding outcomes, refined the adjudication process, and calibrated adjudicators for the remainder of the trial. Henceforth, charts will be randomly allocated to pairs of adjudicators for blinded review. Disclosures: No relevant conflicts of interest to declare.

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)0.298
metaresearch head score (Gemma)0.330
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.298
Threshold uncertainty score0.866

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2980.330
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.360
GPT teacher head0.567
Teacher spread0.207 · 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.

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

Citations5
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueBloodSame topicPharmaceutical industry and healthcareFrench-language works237,207