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Direct oral anticoagulants and the risk of adverse clinical outcomes among patients with different body weight categories: a large hospital-based study.
Nwanosike, Ezekwesiri Michael; Merchant, Hamid A; Sunter, Wendy; Ansari, Muhammad Ayub; Conway, Barbara R; Hasan, Syed Shahzad.
Afiliação
  • Nwanosike EM; Department of Pharmacy, School of Applied Sciences, University of Huddersfield, Queensgate, Huddersfield, HD1 3DH, UK.
  • Merchant HA; Department for Bioscience, School of Health, Sport and Bioscience, the University of East London, London, E16 2RD, UK.
  • Sunter W; Calderdale and Huddersfield Pharmacy Services, Anticoagulation Services, Calderdale and Huddersfield NHS Foundation Trust Hospitals, Lindley, Huddersfield, HD3 3EA, UK.
  • Ansari MA; School of Computing and Engineering, University of Huddersfield, Queensgate, Huddersfield, HD1 3DH, UK.
  • Conway BR; Department of Pharmacy, School of Applied Sciences, University of Huddersfield, Queensgate, Huddersfield, HD1 3DH, UK.
  • Hasan SS; Department of Pharmacy, School of Applied Sciences, University of Huddersfield, Queensgate, Huddersfield, HD1 3DH, UK. s.hasan@hud.ac.uk.
Eur J Clin Pharmacol ; 80(1): 163-173, 2024 Jan.
Article em En | MEDLINE | ID: mdl-37978999
ABSTRACT

OBJECTIVE:

Through predictable pharmacokinetics-including a convenient fixed-dose regimen, direct oral anticoagulants (DOACs) are preferred over previous treatments in anticoagulation for various indications. However, the association between higher body weight and the risk of adverse consequences is not well studied among DOAC users. We aim to explore the association of body weight and adverse clinical outcomes in DOAC users.

METHODS:

A total of 97,413 anonymised DOAC users in a tertiary care setting were identified following structured queries on the electronic health records (EHRs) to extract the feature-rich anonymised dataset. The prepared dataset was analysed, and the features identified with machine learning (ML) informed the adjustments of covariates in the multivariate regression analysis to examine the association. Kaplan-Meier analysis was performed to evaluate the mortality benefits of DOACs.

RESULTS:

Among DOAC users, the odds of adverse clinical outcomes, such as clinically relevant non-major bleeding (CRNMB), ischaemic stroke, all-cause mortality, and prolonged hospital stay, were lower in patients with overweight, obesity, or morbid obesity than in patients with normal body weight. The odds of ischaemic stroke (OR 0.42, 95% CI 0.36-0.88, p = 0.001) and all-cause mortality (OR 0.87, 95% CI 0.81-0.95, p = 0.001) were lower in patients with morbid obesity than in patients with normal body weight. In the Kaplan-Meier analysis, apixaban was associated with a significantly lower rate of mortality overall and in obesity and overweight subgroups than other DOACs (p < 0.001). However, rivaroxaban performed better than apixaban in the morbid obesity subgroup (p < 0.001).

CONCLUSION:

This study shows the positive effects of DOAC therapy on clinical outcomes, particularly in patients with high body weight. However, this still needs validation by further studies particularly among patients with morbid obesity.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Fibrilação Atrial / Obesidade Mórbida / Isquemia Encefálica / Acidente Vascular Cerebral / AVC Isquêmico Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Fibrilação Atrial / Obesidade Mórbida / Isquemia Encefálica / Acidente Vascular Cerebral / AVC Isquêmico Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article