Cargando…
1545. Development of a Linear Mixed-Effect Pharmacodynamic Model to Quantify the Effects of Frequently Prescribed Antimicrobials on QT Interval Prolongation in Hospitalized Patients
BACKGROUND: Torsades de pointes is a life-threatening ventricular tachycardia associated with prolongation of the QT interval. Many diseases and medications have been implicated as potentially prolonging the QT interval, but little data exists regarding the means of quantifying this risk. The aim of...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6808832/ http://dx.doi.org/10.1093/ofid/ofz360.1409 |
_version_ | 1783461832664547328 |
---|---|
author | Farkas, Andras Woods, Krystina L Ciummo, Francesco Shah, Ami Sassine, Joseph Olivo Freites, Christian Daroczi, Gergely Yassin, Arsheena |
author_facet | Farkas, Andras Woods, Krystina L Ciummo, Francesco Shah, Ami Sassine, Joseph Olivo Freites, Christian Daroczi, Gergely Yassin, Arsheena |
author_sort | Farkas, Andras |
collection | PubMed |
description | BACKGROUND: Torsades de pointes is a life-threatening ventricular tachycardia associated with prolongation of the QT interval. Many diseases and medications have been implicated as potentially prolonging the QT interval, but little data exists regarding the means of quantifying this risk. The aim of this study was to describe the impact of commonly used antimicrobials on the QT interval in hospitalized patients. METHODS: Demographic, diseases, laboratory, medication administration history and ECG recording data were collected from the electronic records of adult patients admitted, from July 2018 to December 2018, to two urban hospitals. A model for the QT interval comprised of four sub-models: gender, heart rate, circadian rhythm, and the drug and disease effects. Fixed and random effects with between occasion variability were estimated for the parameters. A Bayesian approach using the NUTS in STAN was used via the brms package in the R® software. RESULTS: Data from 1,353 patients were used with baseline characteristics shown in Table 1. Observed vs. predicted plots based on the training (Figure 1A) and validation data set (Figure 1B) showed a great fit. The parameters for QT(c0), α, gender, and circadian rhythm were accurately identified (Table 2). Similarly, the model correctly described the expected impact of acute or chronic diseases on the QT interval. Uncertainty interval estimates (Figure 2) show that patients treated with fluconazole and levofloxacin are likely to present with a QT interval [mean (95% CI) of 6.84 (0.22,21.45) and 5.05 (0.15, 16.70), respectively], that is > 5 ms longer vs. no treatment, the minimum cutoff that should evoke further risk assessment of QT interval prolongation. CONCLUSION: The model developed correctly describes the impact baseline risk factors have on the QT interval. Point estimates of QT interval prolongation show that patients treated with fluconazole and levofloxacin may be at considerable risk; while those treated with azithromycin or ciprofloxacin are more likely to be at an insignificant risk for QT interval prolongation during hospital admission. Further workup to quantify the impact of concomitant treatment with these and other at-risk medications is underway. [Image: see text] [Image: see text] [Image: see text] [Image: see text] DISCLOSURES: All authors: No reported disclosures. |
format | Online Article Text |
id | pubmed-6808832 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-68088322019-10-28 1545. Development of a Linear Mixed-Effect Pharmacodynamic Model to Quantify the Effects of Frequently Prescribed Antimicrobials on QT Interval Prolongation in Hospitalized Patients Farkas, Andras Woods, Krystina L Ciummo, Francesco Shah, Ami Sassine, Joseph Olivo Freites, Christian Daroczi, Gergely Yassin, Arsheena Open Forum Infect Dis Abstracts BACKGROUND: Torsades de pointes is a life-threatening ventricular tachycardia associated with prolongation of the QT interval. Many diseases and medications have been implicated as potentially prolonging the QT interval, but little data exists regarding the means of quantifying this risk. The aim of this study was to describe the impact of commonly used antimicrobials on the QT interval in hospitalized patients. METHODS: Demographic, diseases, laboratory, medication administration history and ECG recording data were collected from the electronic records of adult patients admitted, from July 2018 to December 2018, to two urban hospitals. A model for the QT interval comprised of four sub-models: gender, heart rate, circadian rhythm, and the drug and disease effects. Fixed and random effects with between occasion variability were estimated for the parameters. A Bayesian approach using the NUTS in STAN was used via the brms package in the R® software. RESULTS: Data from 1,353 patients were used with baseline characteristics shown in Table 1. Observed vs. predicted plots based on the training (Figure 1A) and validation data set (Figure 1B) showed a great fit. The parameters for QT(c0), α, gender, and circadian rhythm were accurately identified (Table 2). Similarly, the model correctly described the expected impact of acute or chronic diseases on the QT interval. Uncertainty interval estimates (Figure 2) show that patients treated with fluconazole and levofloxacin are likely to present with a QT interval [mean (95% CI) of 6.84 (0.22,21.45) and 5.05 (0.15, 16.70), respectively], that is > 5 ms longer vs. no treatment, the minimum cutoff that should evoke further risk assessment of QT interval prolongation. CONCLUSION: The model developed correctly describes the impact baseline risk factors have on the QT interval. Point estimates of QT interval prolongation show that patients treated with fluconazole and levofloxacin may be at considerable risk; while those treated with azithromycin or ciprofloxacin are more likely to be at an insignificant risk for QT interval prolongation during hospital admission. Further workup to quantify the impact of concomitant treatment with these and other at-risk medications is underway. [Image: see text] [Image: see text] [Image: see text] [Image: see text] DISCLOSURES: All authors: No reported disclosures. Oxford University Press 2019-10-23 /pmc/articles/PMC6808832/ http://dx.doi.org/10.1093/ofid/ofz360.1409 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of Infectious Diseases Society of America. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Abstracts Farkas, Andras Woods, Krystina L Ciummo, Francesco Shah, Ami Sassine, Joseph Olivo Freites, Christian Daroczi, Gergely Yassin, Arsheena 1545. Development of a Linear Mixed-Effect Pharmacodynamic Model to Quantify the Effects of Frequently Prescribed Antimicrobials on QT Interval Prolongation in Hospitalized Patients |
title | 1545. Development of a Linear Mixed-Effect Pharmacodynamic Model to Quantify the Effects of Frequently Prescribed Antimicrobials on QT Interval Prolongation in Hospitalized Patients |
title_full | 1545. Development of a Linear Mixed-Effect Pharmacodynamic Model to Quantify the Effects of Frequently Prescribed Antimicrobials on QT Interval Prolongation in Hospitalized Patients |
title_fullStr | 1545. Development of a Linear Mixed-Effect Pharmacodynamic Model to Quantify the Effects of Frequently Prescribed Antimicrobials on QT Interval Prolongation in Hospitalized Patients |
title_full_unstemmed | 1545. Development of a Linear Mixed-Effect Pharmacodynamic Model to Quantify the Effects of Frequently Prescribed Antimicrobials on QT Interval Prolongation in Hospitalized Patients |
title_short | 1545. Development of a Linear Mixed-Effect Pharmacodynamic Model to Quantify the Effects of Frequently Prescribed Antimicrobials on QT Interval Prolongation in Hospitalized Patients |
title_sort | 1545. development of a linear mixed-effect pharmacodynamic model to quantify the effects of frequently prescribed antimicrobials on qt interval prolongation in hospitalized patients |
topic | Abstracts |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6808832/ http://dx.doi.org/10.1093/ofid/ofz360.1409 |
work_keys_str_mv | AT farkasandras 1545developmentofalinearmixedeffectpharmacodynamicmodeltoquantifytheeffectsoffrequentlyprescribedantimicrobialsonqtintervalprolongationinhospitalizedpatients AT woodskrystinal 1545developmentofalinearmixedeffectpharmacodynamicmodeltoquantifytheeffectsoffrequentlyprescribedantimicrobialsonqtintervalprolongationinhospitalizedpatients AT ciummofrancesco 1545developmentofalinearmixedeffectpharmacodynamicmodeltoquantifytheeffectsoffrequentlyprescribedantimicrobialsonqtintervalprolongationinhospitalizedpatients AT shahami 1545developmentofalinearmixedeffectpharmacodynamicmodeltoquantifytheeffectsoffrequentlyprescribedantimicrobialsonqtintervalprolongationinhospitalizedpatients AT sassinejoseph 1545developmentofalinearmixedeffectpharmacodynamicmodeltoquantifytheeffectsoffrequentlyprescribedantimicrobialsonqtintervalprolongationinhospitalizedpatients AT olivofreiteschristian 1545developmentofalinearmixedeffectpharmacodynamicmodeltoquantifytheeffectsoffrequentlyprescribedantimicrobialsonqtintervalprolongationinhospitalizedpatients AT daroczigergely 1545developmentofalinearmixedeffectpharmacodynamicmodeltoquantifytheeffectsoffrequentlyprescribedantimicrobialsonqtintervalprolongationinhospitalizedpatients AT yassinarsheena 1545developmentofalinearmixedeffectpharmacodynamicmodeltoquantifytheeffectsoffrequentlyprescribedantimicrobialsonqtintervalprolongationinhospitalizedpatients |