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Development and Validation of a Prognostic Model for Multi-Drug-Resistant Non-Hospital-Acquired Bloodstream Infection
Bloodstream infections (BSI) are an increasing cause of admissions to hospitals. Non-hospital-acquired BSI are defined by blood cultures that are positive less than 48 hours after admission, but a relevant difference exists between community-acquired and healthcare-associated (HCA) BSI in terms of r...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10295786/ https://www.ncbi.nlm.nih.gov/pubmed/37370274 http://dx.doi.org/10.3390/antibiotics12060955 |
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author | Pivetta, Emanuele Corcione, Silvia Peasso, Paolo Cara, Irene Capodanno, Alberto Brussino, Andrea Petitti, Paolo Galli, Eleonora Galmozzi, Maddalena Ghisetti, Valeria Cavallo, Rossana Aprà, Franco Lupia, Enrico De Rosa, Francesco Giuseppe Montrucchio, Giuseppe |
author_facet | Pivetta, Emanuele Corcione, Silvia Peasso, Paolo Cara, Irene Capodanno, Alberto Brussino, Andrea Petitti, Paolo Galli, Eleonora Galmozzi, Maddalena Ghisetti, Valeria Cavallo, Rossana Aprà, Franco Lupia, Enrico De Rosa, Francesco Giuseppe Montrucchio, Giuseppe |
author_sort | Pivetta, Emanuele |
collection | PubMed |
description | Bloodstream infections (BSI) are an increasing cause of admissions to hospitals. Non-hospital-acquired BSI are defined by blood cultures that are positive less than 48 hours after admission, but a relevant difference exists between community-acquired and healthcare-associated (HCA) BSI in terms of risk of multidrug resistance (MDR). We planned a retrospective study in three different cohorts in order to develop and to temporally and spatially validate an easy and rapid prognostic model for identifying MDR non-hospital-acquired (non-HA) BSI. The pathogens most involved in BSI are Staphylococcus spp. and Escherichia coli, responsible for about 75% of all MDR isolated. The model includes age, gender, long-term care facility admission, immunocompromise, any recent invasive procedures and central line placement, recent intravenous treatment and antibiotic treatment. It shows an acceptable performance, especially for intermediate probabilities of MDR infection, with a C-index of 70%. The model was proposed in a nomogram that could allow better targeting of antibiotic therapy for non-HA BSI admitted in hospital. However, it should be further validated to determine its applicability in other populations. |
format | Online Article Text |
id | pubmed-10295786 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-102957862023-06-28 Development and Validation of a Prognostic Model for Multi-Drug-Resistant Non-Hospital-Acquired Bloodstream Infection Pivetta, Emanuele Corcione, Silvia Peasso, Paolo Cara, Irene Capodanno, Alberto Brussino, Andrea Petitti, Paolo Galli, Eleonora Galmozzi, Maddalena Ghisetti, Valeria Cavallo, Rossana Aprà, Franco Lupia, Enrico De Rosa, Francesco Giuseppe Montrucchio, Giuseppe Antibiotics (Basel) Article Bloodstream infections (BSI) are an increasing cause of admissions to hospitals. Non-hospital-acquired BSI are defined by blood cultures that are positive less than 48 hours after admission, but a relevant difference exists between community-acquired and healthcare-associated (HCA) BSI in terms of risk of multidrug resistance (MDR). We planned a retrospective study in three different cohorts in order to develop and to temporally and spatially validate an easy and rapid prognostic model for identifying MDR non-hospital-acquired (non-HA) BSI. The pathogens most involved in BSI are Staphylococcus spp. and Escherichia coli, responsible for about 75% of all MDR isolated. The model includes age, gender, long-term care facility admission, immunocompromise, any recent invasive procedures and central line placement, recent intravenous treatment and antibiotic treatment. It shows an acceptable performance, especially for intermediate probabilities of MDR infection, with a C-index of 70%. The model was proposed in a nomogram that could allow better targeting of antibiotic therapy for non-HA BSI admitted in hospital. However, it should be further validated to determine its applicability in other populations. MDPI 2023-05-24 /pmc/articles/PMC10295786/ /pubmed/37370274 http://dx.doi.org/10.3390/antibiotics12060955 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Pivetta, Emanuele Corcione, Silvia Peasso, Paolo Cara, Irene Capodanno, Alberto Brussino, Andrea Petitti, Paolo Galli, Eleonora Galmozzi, Maddalena Ghisetti, Valeria Cavallo, Rossana Aprà, Franco Lupia, Enrico De Rosa, Francesco Giuseppe Montrucchio, Giuseppe Development and Validation of a Prognostic Model for Multi-Drug-Resistant Non-Hospital-Acquired Bloodstream Infection |
title | Development and Validation of a Prognostic Model for Multi-Drug-Resistant Non-Hospital-Acquired Bloodstream Infection |
title_full | Development and Validation of a Prognostic Model for Multi-Drug-Resistant Non-Hospital-Acquired Bloodstream Infection |
title_fullStr | Development and Validation of a Prognostic Model for Multi-Drug-Resistant Non-Hospital-Acquired Bloodstream Infection |
title_full_unstemmed | Development and Validation of a Prognostic Model for Multi-Drug-Resistant Non-Hospital-Acquired Bloodstream Infection |
title_short | Development and Validation of a Prognostic Model for Multi-Drug-Resistant Non-Hospital-Acquired Bloodstream Infection |
title_sort | development and validation of a prognostic model for multi-drug-resistant non-hospital-acquired bloodstream infection |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10295786/ https://www.ncbi.nlm.nih.gov/pubmed/37370274 http://dx.doi.org/10.3390/antibiotics12060955 |
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