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Estimating extra length of stay and risk factors of mortality attributable to healthcare-associated infection at a Chinese university hospital: a multi-state model

BACKGROUND: The current evidence of extra length of stay (LOS) attributable to healthcare-associated infection (HCAI) scarcely takes time-dependent bias into consideration. Plus, limited evidences were from developing countries. We aim to estimate the extra LOS and risk factors of mortality attribut...

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Autores principales: Zhou, Qian, Fan, Lili, Lai, Xiaoquan, Tan, Li, Zhang, Xinping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6864951/
https://www.ncbi.nlm.nih.gov/pubmed/31747887
http://dx.doi.org/10.1186/s12879-019-4474-5
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author Zhou, Qian
Fan, Lili
Lai, Xiaoquan
Tan, Li
Zhang, Xinping
author_facet Zhou, Qian
Fan, Lili
Lai, Xiaoquan
Tan, Li
Zhang, Xinping
author_sort Zhou, Qian
collection PubMed
description BACKGROUND: The current evidence of extra length of stay (LOS) attributable to healthcare-associated infection (HCAI) scarcely takes time-dependent bias into consideration. Plus, limited evidences were from developing countries. We aim to estimate the extra LOS and risk factors of mortality attributable to HCAI for inpatients. METHODS: Multi-state model (MSM) was adopted to estimate the extra LOS attributable to HCAI of each type and subgroup. COX regression model was used to examine the risk of mortality. RESULTS: A total of 51,691 inpatients were included and 1709 (3.31%) among them developed HCAI. Lower respiratory tract infection and Acinetobacter baumannii were the most prevalent HCAI and causative pathogen in surveyed institute. Generally, the expected extra LOS attributable to HCAI was 2.56 days (95% confidence interval: 2.54–2.61). Patients below 65 had extra LOS attributable to HCAI longer about 2 days than those above. The extra LOS attributable to HCAI of male patients was 1.33 days longer than female. Meanwhile, age above 65 years old and HCAI were the risk factors of mortality for inpatients. CONCLUSIONS: HCAI contributes to an increase in extra LOS of inpatients in China. The effect of HCAI on extra LOS is different among subgroups, with the age below 65, male and medicine department more sensitive.
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spelling pubmed-68649512019-12-12 Estimating extra length of stay and risk factors of mortality attributable to healthcare-associated infection at a Chinese university hospital: a multi-state model Zhou, Qian Fan, Lili Lai, Xiaoquan Tan, Li Zhang, Xinping BMC Infect Dis Research Article BACKGROUND: The current evidence of extra length of stay (LOS) attributable to healthcare-associated infection (HCAI) scarcely takes time-dependent bias into consideration. Plus, limited evidences were from developing countries. We aim to estimate the extra LOS and risk factors of mortality attributable to HCAI for inpatients. METHODS: Multi-state model (MSM) was adopted to estimate the extra LOS attributable to HCAI of each type and subgroup. COX regression model was used to examine the risk of mortality. RESULTS: A total of 51,691 inpatients were included and 1709 (3.31%) among them developed HCAI. Lower respiratory tract infection and Acinetobacter baumannii were the most prevalent HCAI and causative pathogen in surveyed institute. Generally, the expected extra LOS attributable to HCAI was 2.56 days (95% confidence interval: 2.54–2.61). Patients below 65 had extra LOS attributable to HCAI longer about 2 days than those above. The extra LOS attributable to HCAI of male patients was 1.33 days longer than female. Meanwhile, age above 65 years old and HCAI were the risk factors of mortality for inpatients. CONCLUSIONS: HCAI contributes to an increase in extra LOS of inpatients in China. The effect of HCAI on extra LOS is different among subgroups, with the age below 65, male and medicine department more sensitive. BioMed Central 2019-11-20 /pmc/articles/PMC6864951/ /pubmed/31747887 http://dx.doi.org/10.1186/s12879-019-4474-5 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Zhou, Qian
Fan, Lili
Lai, Xiaoquan
Tan, Li
Zhang, Xinping
Estimating extra length of stay and risk factors of mortality attributable to healthcare-associated infection at a Chinese university hospital: a multi-state model
title Estimating extra length of stay and risk factors of mortality attributable to healthcare-associated infection at a Chinese university hospital: a multi-state model
title_full Estimating extra length of stay and risk factors of mortality attributable to healthcare-associated infection at a Chinese university hospital: a multi-state model
title_fullStr Estimating extra length of stay and risk factors of mortality attributable to healthcare-associated infection at a Chinese university hospital: a multi-state model
title_full_unstemmed Estimating extra length of stay and risk factors of mortality attributable to healthcare-associated infection at a Chinese university hospital: a multi-state model
title_short Estimating extra length of stay and risk factors of mortality attributable to healthcare-associated infection at a Chinese university hospital: a multi-state model
title_sort estimating extra length of stay and risk factors of mortality attributable to healthcare-associated infection at a chinese university hospital: a multi-state model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6864951/
https://www.ncbi.nlm.nih.gov/pubmed/31747887
http://dx.doi.org/10.1186/s12879-019-4474-5
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