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Record 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 on 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

Bibliographic record

VenueBlood · 2018
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsUniversity of VictoriaUniversity of British Columbia
Fundersnot available
KeywordsMedicineWarfarinApixabanRivaroxabanDabigatranAtrial fibrillationPropensity score matchingAspirinInternal medicineCohortEmergency medicineIntensive care medicine

Abstract

fetched live from 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.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.068
GPT teacher head0.321
Teacher spread0.253 · 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 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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