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Enregistrement W2906785804 · doi:10.1182/blood-2018-99-112631

Inpatient Mortality and Length of Stay Among Direct-Acting Oral Anticoagulant (DOAC) and Warfarin Users Presenting with Major Hemorrhage

2018· article· en· W2906785804 sur OpenAlexaff
Walter Bialkowski, Sylvia Tan, Alan E. Mast, Joseph E. Kiss, Daryl J. Kor, Jerome L. Gottschall, Yanyun Wu, Nareg H. Roubinian, Darrell J. Triulzi, Steven Kleinman, Young Choi, Donald Brambilla, Ann B. Zimrin, The NHLBI Recipient Epidemiology and Donor Evaluation Study-III

Notice bibliographique

RevueBlood · 2018
Typearticle
Langueen
DomaineMedicine
ThématiqueAtrial Fibrillation Management and Outcomes
Établissements canadiensUniversity of VictoriaUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésMedicineWarfarinApixabanRivaroxabanDabigatranAtrial fibrillationPropensity score matchingAspirinInternal medicineCohortEmergency medicineIntensive care medicine

Résumé

récupéré en direct d'OpenAlex

Abstract Background: Use of direct-acting oral anticoagulants (DOAC) is increasingly common among patients with atrial fibrillation and venous thromboembolic disease. Differences in the mechanisms of action as compared to warfarin could impact transfusion patterns and clinical outcomes in patients, especially for those presenting with major hemorrhage. The management of patients taking these newer medications and corresponding outcomes are relevant to optimizing clinical decision making in situations of major hemorrhage. Methods: We tested the hypothesis that inpatient all-cause mortality among patients presenting with major hemorrhage differs based on the home-administered anticoagulant medication class (DOAC versus warfarin). A cohort of patients presenting to twelve US hospitals from 2013 to 2016 was identified using the Recipient Epidemiology and Donor Evaluation Study (REDS)-III Recipient Database. Primary ICD diagnosis codes, issued blood products, laboratory data, and early mortality events were used in the application of the International Society on Thrombosis and Hemostasis definition of major hemorrhage. Exposure status was defined as a record of home-administered DOAC (apixaban, dabigatran, edoxaban, or rivaroxaban; exposed) or warfarin (non-exposed). Patients with multiple encounters and those transferred into or out of network were excluded from the analysis. Proportional hazards regression was used to compare all-cause mortality and hospital length of stay. We then repeated the analysis using a cohort matched on propensity scores to account for confounding by age, gender, concurrent aspirin and anti-platelet use, liver and renal dysfunction, cancer, CHA2DS2-VASc score, traumatic injury, and hospital. We then repeated the propensity score matched analysis stratified by anatomic location of bleed and traumatic injury. Results: More than 1.5 million hospitalizations were screened for eligibility. Exclusion of minors, outpatients, hospitalizations without a medication of interest, absence of major hemorrhage, multiple hospitalizations, and hospital transfers resulted in 3,731 patients available for the unadjusted analysis. Inpatient all-cause mortality was lower among DOAC users when the entire cohort was considered (HR = 0.60, 95%CI 0.45 - 0.80, p=0.0005). Implementation of propensity score matching to account for confounding abrogated this difference (HR=0.84, 95%CI 0.58 - 1.22, p=0.36). Time to hospital discharge was shorter for DOAC users (HR = 1.17, 95%CI 1.05 - 1.30, p=0.0034). Transfusion patterns were similar by medication, except for plasma transfusion occurring in 42% of warfarin encounters and 11% of DOAC encounters. Vitamin K was administered in 63% of warfarin encounters, whereas specific DOAC reversal agents were largely unavailable during the analysis period [used in 5 (1%) DOAC encounters]. There were no statistically significant differences in inpatient all-cause mortality in the stratified analysis (warfarin as reference): HR = 0.69 (95%CI 0.31 - 1.55) for traumatic head injuries; HR = 1.10 (95%CI 0.62 - 1.95) for non-traumatic head injuries; HR = 0.62 (95%CI 0.20 - 1.94) for traumatic, non-head injuries; and HR = 0.69 (95%CI 0.29 - 1.63) for non-traumatic, non-head injuries. Conclusions: Analysis of a population taking oral anticoagulation and presenting with major hemorrhage showed that transfusion of plasma was more commonly employed to treat major hemorrhage among warfarin users than DOAC users. Inpatient all-cause mortality was lower among DOAC users in the overall cohort; however, accounting for potential confounding factors using propensity score matching abrogated this difference. Hospital length of stay was shorter for DOAC users compared to warfarin users. Stratification by location of bleed and traumatic injury did not alter these findings. Less plasma use and a shorter length of hospitalization in this study, combined with no observable difference in inpatient all-cause mortality, suggests that outcomes following major hemorrhage are at least no different for DOAC users as compared to warfarin users. Disclosures Mast: Novo Nordisk: Research Funding. Kor:NIH: Consultancy; NIH: Research Funding; UpToDate: Patents & Royalties; CSL Behring: Honoraria.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,007
Score d'incertitude au seuil0,014

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0000,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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.

Tête enseignante Opus0,068
Tête enseignante GPT0,321
Écart entre enseignants0,253 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2018
Routes d'admission1
Résumé présentoui

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