Identifying Drugs Implicated in Drug-Induced Immune Thrombocytopenia Using Levels of Evidence Applied to Laboratory Tests,
Notice bibliographique
Résumé
Abstract Abstract 3304 Introduction: Many drugs can cause platelet counts to decrease. However, only relatively few cause severe drug-induced immune thrombocytopenia (DITP), a hemorrhagic syndrome characterized by drug-dependent, platelet-reactive antibodies. Laboratory testing for DITP is important to confirm the diagnosis, however test methods have evolved over the years and results are often difficult to interpret. We applied hierarchical grading methodology to published reports of DITP test methods to evaluate their validity and reliability. Using this grading system, we identified drugs that were implicated in DITP reactions with the highest level of evidence. Methods: All drugs implicated in DITP reactions based on clinical criteria were compiled from a previous systematic review (Swisher KK, Drug Safety 2009). Primary publications and additional reports associated with each drug were retrieved by searching MEDLINE and EMBASE to identify those drugs for which in vitro DITP testing had been performed. In duplicate and independently, the validity of DITP test methods was assessed based on whether or not they demonstrated: 1) drug or drug metabolite-dependence; 2) platelet specificity; and 3) IgG-binding. Reliability of test methods was assessed based on whether or not DITP test results were confirmed by more than one laboratory. Discrepancies were adjudicated by a third party. Assessors were experienced in DITP test methods. Results: We identified 149 drugs that were associated with DITP reactions by clinical criteria alone. Of those, 92 were excluded because testing was either not performed or was negative, or primary reports were irretrievable. Publications associated with the remaining 57 drugs were reviewed in duplicate. Of those, 27 were excluded because testing did not confirm drug-dependence (N= 15), platelet specificity (N=1) or IgG binding (N=11); 19 were included; and 11 were sent for adjudication. In the end, 22 drugs (abciximab, acetaminophen, cephamandole, diazepam, diphenylhydantoin, eptifibatide, gold, ibuprofen, mirtazapine, naproxen, oxaliplatin, penicillin, quinidine, quinine, rifampin, rosiglitazole, roxifiban, sulfisoxazole, tirofiban, tranilast, trimethoprim/sulfamethoxazole and vancomycin) met all validity criteria. Only 6 (gold, quinine, quinidine, tirofiban, rifampin and vancomycin) were confirmed positive by more than one laboratory. Conclusion: Based on assessments of validity and reproducibility of laboratory test methods, we identified 6 drugs – gold, quinine, quinidine, tirofiban, rifampin and vancomycin – that have been implicated in DITP reactions with a high level of evidence. This type of methodological approach can improve the likelihood of DITP diagnosis with a given drug. Disclosures: Warkentin: Sanofi-Aventis: Speakers Bureau; Pfizer Canada: Speakers Bureau; GlaxoSmithKline: Consultancy, Research Funding; GTI Diagnostics: Consultancy, Research Funding; Canyon Pharma: Consultancy, Speakers Bureau; Informa: Patents & Royalties.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,024 | 0,131 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,005 | 0,007 |
| Bibliométrie | 0,039 | 0,023 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».