Literature DB >> 23591268

Assessing cardiovascular drug safety for clinical decision-making.

Raymond L Woosley1, Klaus Romero.   

Abstract

Optimal therapeutic decision-making requires integration of patient-specific and therapy-specific information at the point of care, particularly when treating patients with complex cardiovascular conditions. The formidable task for the prescriber is to synthesize information about all therapeutic options and match the best treatment with the characteristics of the individual patient. Computerized decision support systems have been developed with the goal of integrating such information and presenting the acceptable therapeutic options on the basis of their effectiveness, often with limited consideration of their safety for a specific patient. Assessing the safety of therapies relative to each patient is difficult, and sometimes impossible, because the evidence required to make such an assessment is either imperfect or does not exist. In addition, many of the alerts sent to prescribers by decision-support systems are not perceived as credible, and 'alert fatigue' causes warnings to be ignored putting patients at risk of harm. The CredibleMeds.org and BrugadaDrugs.org websites are prototypes for evidence-based sources of safety information that rank drugs for their risk of a specific form of drug toxicity-in these cases, drug-induced arrhythmias. Broad incorporation of this type of information in electronic prescribing algorithms and clinical decision support could speed the evolution of safe personalized medicine.

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Year:  2013        PMID: 23591268     DOI: 10.1038/nrcardio.2013.57

Source DB:  PubMed          Journal:  Nat Rev Cardiol        ISSN: 1759-5002            Impact factor:   32.419


  63 in total

1.  Causal association in pharmacovigilance and pharmacoepidemiology: thoughts on the application of the Austin Bradford-Hill criteria.

Authors:  Saad A W Shakir; Deborah Layton
Journal:  Drug Saf       Date:  2002       Impact factor: 5.606

2.  Randomized clinical trial of a customized electronic alert requiring an affirmative response compared to a control group receiving a commercial passive CPOE alert: NSAID--warfarin co-prescribing as a test case.

Authors:  Brian L Strom; Rita Schinnar; Warren Bilker; Sean Hennessy; Charles E Leonard; Eric Pifer
Journal:  J Am Med Inform Assoc       Date:  2010 Jul-Aug       Impact factor: 4.497

3.  Evaluation of warfarin drug interaction listings in US product information for warfarin and interacting drugs.

Authors:  Lisa E Hines; Diana Ceron-Cabrera; Klaus Romero; Marietta Anthony; Raymond L Woosley; Edward P Armstrong; Daniel C Malone
Journal:  Clin Ther       Date:  2011-01       Impact factor: 3.393

4.  Polypharmacy, adverse drug-related events, and potential adverse drug interactions in elderly patients presenting to an emergency department.

Authors:  C M Hohl; J Dankoff; A Colacone; M Afilalo
Journal:  Ann Emerg Med       Date:  2001-12       Impact factor: 5.721

5.  Drug-related morbidity and mortality: updating the cost-of-illness model.

Authors:  F R Ernst; A J Grizzle
Journal:  J Am Pharm Assoc (Wash)       Date:  2001 Mar-Apr

6.  Outcomes of emergency department patients presenting with adverse drug events.

Authors:  Corinne M Hohl; Bohdan Nosyk; Lisa Kuramoto; Peter J Zed; Jeffrey R Brubacher; Riyad B Abu-Laban; Samuel B Sheps; Boris Sobolev
Journal:  Ann Emerg Med       Date:  2011-02-26       Impact factor: 5.721

7.  Recommendations for generating, evaluating, and implementing drug-drug interaction evidence.

Authors:  Lisa E Hines; Daniel C Malone; John E Murphy
Journal:  Pharmacotherapy       Date:  2012-04       Impact factor: 4.705

Review 8.  Cellular basis of drug-induced torsades de pointes.

Authors:  D M Roden
Journal:  Br J Pharmacol       Date:  2008-06-16       Impact factor: 8.739

9.  Clinically relevant QTc prolongation due to overridden drug-drug interaction alerts: a retrospective cohort study.

Authors:  Heleen van der Sijs; Ravi Kowlesar; A Peter J Klootwijk; Stefan P Nelwan; Arnold G Vulto; Teun van Gelder
Journal:  Br J Clin Pharmacol       Date:  2008-12-10       Impact factor: 4.335

10.  How current are leading evidence-based medical textbooks? An analytic survey of four online textbooks.

Authors:  Rebecca Jeffery; Tamara Navarro; Cynthia Lokker; R Brian Haynes; Nancy L Wilczynski; George Farjou
Journal:  J Med Internet Res       Date:  2012-12-10       Impact factor: 5.428

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  13 in total

1.  Accuracy of an automated knowledge base for identifying drug adverse reactions.

Authors:  E A Voss; R D Boyce; P B Ryan; J van der Lei; P R Rijnbeek; M J Schuemie
Journal:  J Biomed Inform       Date:  2016-12-16       Impact factor: 6.317

2.  A smart algorithm for the prevention and risk management of QTc prolongation based on the optimized RISQ-PATH model.

Authors:  Eline Vandael; Bert Vandenberk; Joris Vandenberghe; Bart Van den Bosch; Rik Willems; Veerle Foulon
Journal:  Br J Clin Pharmacol       Date:  2018-10-06       Impact factor: 4.335

3.  Coupling Data Mining and Laboratory Experiments to Discover Drug Interactions Causing QT Prolongation.

Authors:  Tal Lorberbaum; Kevin J Sampson; Jeremy B Chang; Vivek Iyer; Raymond L Woosley; Robert S Kass; Nicholas P Tatonetti
Journal:  J Am Coll Cardiol       Date:  2016-10-18       Impact factor: 24.094

Review 4.  [Proarrhythmic adverse effects of nonarrhythmic drugs].

Authors:  C G Jungbauer; L S Maier
Journal:  Herzschrittmacherther Elektrophysiol       Date:  2019-08-23

5.  Drug utilization study of systemic antifungal agents in a Brazilian tertiary care hospital.

Authors:  Maria Clara Padovani de Souza; Andrezza Gouvêa Dos Santos; Adriano Max Moreira Reis
Journal:  Int J Clin Pharm       Date:  2016-10-06

6.  Use of antihistamines and risk of ventricular tachyarrhythmia: a nested case-control study in five European countries from the ARITMO project.

Authors:  Elisabetta Poluzzi; I Diemberger; M De Ridder; A Koci; M Clo; A Oteri; S Pecchioli; I Bezemer; T Schink; S Pilgaard Ulrichsen; G Boriani; M C J Sturkenboom; F De Ponti; G Trifirò
Journal:  Eur J Clin Pharmacol       Date:  2017-08-22       Impact factor: 2.953

7.  Application of the Bogossian formula for evaluation of the QT interval in pacemaker patients with stimulated left bundle branch block.

Authors:  K F Weipert; H Bogossian; P Conzen; G Frommeyer; C Gemein; I Helmig; R Chasan; L Eckardt; M Seyfarth; B Lemke; M Zarse; C W Hamm; J Schmitt; D Erkapic
Journal:  Clin Res Cardiol       Date:  2018-05-11       Impact factor: 5.460

Review 8.  Risk factors for QTc-prolongation: systematic review of the evidence.

Authors:  Eline Vandael; Bert Vandenberk; Joris Vandenberghe; Rik Willems; Veerle Foulon
Journal:  Int J Clin Pharm       Date:  2016-12-23

9.  A new experimentally validated formula to calculate the QT interval in the presence of left bundle branch block holds true in the clinical setting.

Authors:  Harilaos Bogossian; Gerrit Frommeyer; Ilias Ninios; Eleni Pechlivanidou; Fuad Hasan; Quy Suu Nguyen; Dejan Mijic; Axel Kloppe; Zana Karosiene; Artak Margkarian; Dirk Bandorski; Dominik Schultes; Damir Erkapic; Melchior Seyfarth; Bernd Lemke; Lars Eckardt; Markus Zarse
Journal:  Ann Noninvasive Electrocardiol       Date:  2016-08-26       Impact factor: 1.468

10.  An Integrative Data Science Pipeline to Identify Novel Drug Interactions that Prolong the QT Interval.

Authors:  Tal Lorberbaum; Kevin J Sampson; Raymond L Woosley; Robert S Kass; Nicholas P Tatonetti
Journal:  Drug Saf       Date:  2016-05       Impact factor: 5.606

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