PURPOSE: The objective of this study was to identify the most clinically relevant drug-drug interactions (DDIs) at risk of affecting acenocoumarol safety in our tertiary care university hospital, a 2,000 bed institution. METHODS: We identified DDIs occurring with acenocoumarol by combining two different sources of information: a 1-year retrospective analysis of acenocoumarol prescriptions and comedications from our Computerized Physician Order Entry (CPOE) system (n = 2,439 hospitalizations) and a retrospective study of clinical pharmacology consultations involving acenocoumarol over the past 14 years (1994-2007) (n = 407). We classified these DDIs using an original risk-analysis method. A criticality index was calculated for each associated drug by multiplying three scores based on mechanism of interaction, involvement in a supratherapeutic international normalized ratio (INR) (≥ 6) and involvement in a severe bleeding. RESULTS: One hundred and twenty-six DDIs were identified and weighted. Twenty-eight drugs had a criticality index ≥ 20 and were therefore considered at high risk for interacting with acenocoumarol by increasing its effect: 75% of these drugs involved a pharmacokinetic mechanism and 14 % a pharmacodynamic mechanism. An unknown mechanism of interaction was involved in 11 % of drugs. CONCLUSION: Twenty-eight specific drugs were identified as being at high risk for interacting with acenocoumarol in our hospital using an original risk-analysis method. Most analyzed drugs interact with acenocoumarol via a pharmacokinetic mechanism. Actions such as the implementation of alerts in our CPOE system should be specifically developed for these drugs.
PURPOSE: The objective of this study was to identify the most clinically relevant drug-drug interactions (DDIs) at risk of affecting acenocoumarol safety in our tertiary care university hospital, a 2,000 bed institution. METHODS: We identified DDIs occurring with acenocoumarol by combining two different sources of information: a 1-year retrospective analysis of acenocoumarol prescriptions and comedications from our Computerized Physician Order Entry (CPOE) system (n = 2,439 hospitalizations) and a retrospective study of clinical pharmacology consultations involving acenocoumarol over the past 14 years (1994-2007) (n = 407). We classified these DDIs using an original risk-analysis method. A criticality index was calculated for each associated drug by multiplying three scores based on mechanism of interaction, involvement in a supratherapeutic international normalized ratio (INR) (≥ 6) and involvement in a severe bleeding. RESULTS: One hundred and twenty-six DDIs were identified and weighted. Twenty-eight drugs had a criticality index ≥ 20 and were therefore considered at high risk for interacting with acenocoumarol by increasing its effect: 75% of these drugs involved a pharmacokinetic mechanism and 14 % a pharmacodynamic mechanism. An unknown mechanism of interaction was involved in 11 % of drugs. CONCLUSION: Twenty-eight specific drugs were identified as being at high risk for interacting with acenocoumarol in our hospital using an original risk-analysis method. Most analyzed drugs interact with acenocoumarol via a pharmacokinetic mechanism. Actions such as the implementation of alerts in our CPOE system should be specifically developed for these drugs.
Authors: Amy J Grizzle; Maysaa H Mahmood; Yu Ko; John E Murphy; Edward P Armstrong; Grant H Skrepnek; William N Jones; Gregory P Schepers; W Paul Nichol; Antoun Houranieh; Donna C Dare; Christopher T Hoey; Daniel C Malone Journal: Am J Manag Care Date: 2007-10 Impact factor: 2.229
Authors: Agnes I Vitry; Elizabeth E Roughead; Emmae N Ramsay; Adrian K Preiss; Philip Ryan; Andrew L Gilbert; Gillian E Caughey; Sepehr Shakib; Adrian Esterman; Ying Zhang; Robyn A McDermott Journal: Pharmacoepidemiol Drug Saf Date: 2011-10 Impact factor: 2.890
Authors: G Palareti; N Leali; S Coccheri; M Poggi; C Manotti; A D'Angelo; V Pengo; N Erba; M Moia; N Ciavarella; G Devoto; M Berrettini; S Musolesi Journal: Lancet Date: 1996-08-17 Impact factor: 79.321
Authors: Marilyn D Paterno; Saverio M Maviglia; Paul N Gorman; Diane L Seger; Eileen Yoshida; Andrew C Seger; David W Bates; Tejal K Gandhi Journal: J Am Med Inform Assoc Date: 2008-10-24 Impact factor: 4.497
Authors: Donna Jo McCloskey; Teodor T Postolache; Bernard J Vittone; Khanh L Nghiem; Jude L Monsale; Robert A Wesley; Margaret E Rick Journal: Transl Res Date: 2007-11-20 Impact factor: 7.012
Authors: M Rosa Dalmau Llorca; Carina Aguilar Martín; Noèlia Carrasco-Querol; Zojaina Hernández Rojas; Emma Forcadell Drago; Dolores Rodríguez Cumplido; Elisabet Castro Blanco; Alessandra Queiroga Gonçalves; José Fernández-Sáez Journal: Int J Environ Res Public Health Date: 2021-05-26 Impact factor: 3.390