Cargando…
A “resistance calculator”: Simple stewardship intervention for refining empiric practices of antimicrobials in acute-care hospitals
OBJECTIVE: In the era of widespread resistance, there are 2 time points at which most empiric prescription errors occur among hospitalized adults: (1) upon admission (UA) when treating patients at risk of multidrug-resistant organisms (MDROs) and (2) during hospitalization, when treating patients at...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8459314/ https://www.ncbi.nlm.nih.gov/pubmed/33736724 http://dx.doi.org/10.1017/ice.2020.1372 |
_version_ | 1784571495953989632 |
---|---|
author | Zilberman-Itskovich, Shani Strul, Nathan Chedid, Khalil Martin, Emily T. Shorbaje, Akram Vitkon-Barkay, Itzhak Marcus, Gil Michaeli, Leah Broide, Mor Yekutiel, Matar Zohar, Yarden Razin, Hadas Low, Amitai Strulovici, Ariela Israeli, Boaz Geva, Gal Katz, David E. Ben-Chetrit, Eli Dodin, Mutaz Dhar, Sorabh Parsons, Leo Milton Ramos-Mercado, Abdiel Kaye, Keith S. Marchaim, Dror |
author_facet | Zilberman-Itskovich, Shani Strul, Nathan Chedid, Khalil Martin, Emily T. Shorbaje, Akram Vitkon-Barkay, Itzhak Marcus, Gil Michaeli, Leah Broide, Mor Yekutiel, Matar Zohar, Yarden Razin, Hadas Low, Amitai Strulovici, Ariela Israeli, Boaz Geva, Gal Katz, David E. Ben-Chetrit, Eli Dodin, Mutaz Dhar, Sorabh Parsons, Leo Milton Ramos-Mercado, Abdiel Kaye, Keith S. Marchaim, Dror |
author_sort | Zilberman-Itskovich, Shani |
collection | PubMed |
description | OBJECTIVE: In the era of widespread resistance, there are 2 time points at which most empiric prescription errors occur among hospitalized adults: (1) upon admission (UA) when treating patients at risk of multidrug-resistant organisms (MDROs) and (2) during hospitalization, when treating patients at risk of extensively drug-resistant organisms (XDROs). These errors adversely influence patient outcomes and the hospital’s ecology. DESIGN AND SETTING: Retrospective cohort study, Shamir Medical Center, Israel, 2016. PATIENTS: Adult patients (aged >18 years) hospitalized with sepsis. METHODS: Logistic regressions were used to develop predictive models for (1) MDRO UA and (2) nosocomial XDRO. Their performances on the derivation data sets, and on 7 other validation data sets, were assessed using the area under the receiver operating characteristic curve (ROC AUC). RESULTS: In total, 4,114 patients were included: 2,472 patients with sepsis UA and 1,642 with nosocomial sepsis. The MDRO UA score included 10 parameters, and with a cutoff of ≥22 points, it had an ROC AUC of 0.85. The nosocomial XDRO score included 7 parameters, and with a cutoff of ≥36 points, it had an ROC AUC of 0.87. The range of ROC AUCs for the validation data sets was 0.7–0.88 for the MDRO UA score and was 0.66–0.75 for nosocomial XDRO score. We created a free web calculator (https://assafharofe.azurewebsites.net). CONCLUSIONS: A simple electronic calculator could aid with empiric prescription during an encounter with a septic patient. Future implementation studies are needed to evaluate its utility in improving patient outcomes and in reducing overall resistances. |
format | Online Article Text |
id | pubmed-8459314 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-84593142021-10-01 A “resistance calculator”: Simple stewardship intervention for refining empiric practices of antimicrobials in acute-care hospitals Zilberman-Itskovich, Shani Strul, Nathan Chedid, Khalil Martin, Emily T. Shorbaje, Akram Vitkon-Barkay, Itzhak Marcus, Gil Michaeli, Leah Broide, Mor Yekutiel, Matar Zohar, Yarden Razin, Hadas Low, Amitai Strulovici, Ariela Israeli, Boaz Geva, Gal Katz, David E. Ben-Chetrit, Eli Dodin, Mutaz Dhar, Sorabh Parsons, Leo Milton Ramos-Mercado, Abdiel Kaye, Keith S. Marchaim, Dror Infect Control Hosp Epidemiol Original Article OBJECTIVE: In the era of widespread resistance, there are 2 time points at which most empiric prescription errors occur among hospitalized adults: (1) upon admission (UA) when treating patients at risk of multidrug-resistant organisms (MDROs) and (2) during hospitalization, when treating patients at risk of extensively drug-resistant organisms (XDROs). These errors adversely influence patient outcomes and the hospital’s ecology. DESIGN AND SETTING: Retrospective cohort study, Shamir Medical Center, Israel, 2016. PATIENTS: Adult patients (aged >18 years) hospitalized with sepsis. METHODS: Logistic regressions were used to develop predictive models for (1) MDRO UA and (2) nosocomial XDRO. Their performances on the derivation data sets, and on 7 other validation data sets, were assessed using the area under the receiver operating characteristic curve (ROC AUC). RESULTS: In total, 4,114 patients were included: 2,472 patients with sepsis UA and 1,642 with nosocomial sepsis. The MDRO UA score included 10 parameters, and with a cutoff of ≥22 points, it had an ROC AUC of 0.85. The nosocomial XDRO score included 7 parameters, and with a cutoff of ≥36 points, it had an ROC AUC of 0.87. The range of ROC AUCs for the validation data sets was 0.7–0.88 for the MDRO UA score and was 0.66–0.75 for nosocomial XDRO score. We created a free web calculator (https://assafharofe.azurewebsites.net). CONCLUSIONS: A simple electronic calculator could aid with empiric prescription during an encounter with a septic patient. Future implementation studies are needed to evaluate its utility in improving patient outcomes and in reducing overall resistances. Cambridge University Press 2021-09 2021-03-19 /pmc/articles/PMC8459314/ /pubmed/33736724 http://dx.doi.org/10.1017/ice.2020.1372 Text en © The Society for Healthcare Epidemiology of America 2021 https://creativecommons.org/licenses/by/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Zilberman-Itskovich, Shani Strul, Nathan Chedid, Khalil Martin, Emily T. Shorbaje, Akram Vitkon-Barkay, Itzhak Marcus, Gil Michaeli, Leah Broide, Mor Yekutiel, Matar Zohar, Yarden Razin, Hadas Low, Amitai Strulovici, Ariela Israeli, Boaz Geva, Gal Katz, David E. Ben-Chetrit, Eli Dodin, Mutaz Dhar, Sorabh Parsons, Leo Milton Ramos-Mercado, Abdiel Kaye, Keith S. Marchaim, Dror A “resistance calculator”: Simple stewardship intervention for refining empiric practices of antimicrobials in acute-care hospitals |
title | A “resistance calculator”: Simple stewardship intervention for refining empiric practices of antimicrobials in acute-care hospitals |
title_full | A “resistance calculator”: Simple stewardship intervention for refining empiric practices of antimicrobials in acute-care hospitals |
title_fullStr | A “resistance calculator”: Simple stewardship intervention for refining empiric practices of antimicrobials in acute-care hospitals |
title_full_unstemmed | A “resistance calculator”: Simple stewardship intervention for refining empiric practices of antimicrobials in acute-care hospitals |
title_short | A “resistance calculator”: Simple stewardship intervention for refining empiric practices of antimicrobials in acute-care hospitals |
title_sort | “resistance calculator”: simple stewardship intervention for refining empiric practices of antimicrobials in acute-care hospitals |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8459314/ https://www.ncbi.nlm.nih.gov/pubmed/33736724 http://dx.doi.org/10.1017/ice.2020.1372 |
work_keys_str_mv | AT zilbermanitskovichshani aresistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT strulnathan aresistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT chedidkhalil aresistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT martinemilyt aresistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT shorbajeakram aresistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT vitkonbarkayitzhak aresistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT marcusgil aresistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT michaelileah aresistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT broidemor aresistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT yekutielmatar aresistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT zoharyarden aresistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT razinhadas aresistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT lowamitai aresistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT struloviciariela aresistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT israeliboaz aresistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT gevagal aresistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT katzdavide aresistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT benchetriteli aresistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT dodinmutaz aresistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT dharsorabh aresistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT parsonsleomilton aresistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT ramosmercadoabdiel aresistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT kayekeiths aresistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT marchaimdror aresistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT zilbermanitskovichshani resistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT strulnathan resistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT chedidkhalil resistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT martinemilyt resistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT shorbajeakram resistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT vitkonbarkayitzhak resistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT marcusgil resistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT michaelileah resistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT broidemor resistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT yekutielmatar resistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT zoharyarden resistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT razinhadas resistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT lowamitai resistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT struloviciariela resistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT israeliboaz resistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT gevagal resistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT katzdavide resistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT benchetriteli resistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT dodinmutaz resistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT dharsorabh resistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT parsonsleomilton resistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT ramosmercadoabdiel resistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT kayekeiths resistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals AT marchaimdror resistancecalculatorsimplestewardshipinterventionforrefiningempiricpracticesofantimicrobialsinacutecarehospitals |