Durojaiye, O., Kritsotakis, E. orcid.org/0000-0002-9526-3852, Johnston, P. et al. (3 more authors) (2019) Developing a risk prediction model for 30-Day unplanned hospitalisation in patients receiving outpatient parenteral antimicrobial therapy. Clinical Microbiology and Infection, 25 (7). 905.e1-905.e7. ISSN 1198-743X
Abstract
Objectives Outpatient parenteral antimicrobial therapy (OPAT) is increasingly used to treat a wide range of infections. However, there is risk of hospital readmissions. The study aim was to develop a prediction model for the risk of 30-day unplanned hospitalisation in patients receiving OPAT.
Methods Using a retrospective cohort design, we retrieved data on 1073 patients who received OPAT over two years (01/2015 - 01/2017) at a large teaching hospital in Sheffield, UK. We developed a multivariable logistic regression model for 30-day unplanned hospitalisation and assessed its discrimination and calibration abilities, and internally validated using bootstrap resampling.
Results The 30-day unplanned hospitalisation rate was 11% (123/1073). The main indication for hospitalisation was worsening or non-response of infection (42%; 52/123). The final regression model consisted of age (adjusted odds ratio [aOR], 1.18 per decade; 95% confidence interval [CI], 1.04-1.34), Charlson comorbidity score (aOR, 1.11 per unit increase; 95%CI, 1.00-1.23), prior hospitalisations in past 12 months (aOR, 1.30 per admission; 95%CI, 1.17-1.45), concurrent intravenous antimicrobial therapy (aOR, 1.89; 95%CI, 1.03-3.47), and endovascular infection (aOR, 3.51; 95%CI, 1.49-8.28). Mode of OPAT treatment was retained in the model as a confounder. The model had adequate concordance (c-statistic 0.72; 95%CI 0.67-0.77) and calibration (Hosmer-Lemeshow P=0.546; calibration slope 0.99; 95%CI 0.78-1.21) and low degree of optimism (bootstrap optimism corrected c-statistic, 0.70).
Conclusions We identified a set of six important predictors of unplanned hospitalisation based on readily available data. The prediction model may help improve OPAT outcomes through better identification of high-risk patients and provision of tailored care.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © 2018 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. This is an author produced version of a paper subsequently published in Clinical Microbiology and Infection. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
Keywords: | Readmission; hospitalisation risk factors; predictive model; outpatient parenteral antimicrobial therapy |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Health and Related Research (Sheffield) > ScHARR - Sheffield Centre for Health and Related Research |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 03 Dec 2018 15:42 |
Last Modified: | 02 Nov 2021 14:48 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.cmi.2018.11.009 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:139435 |
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Filename: PIIS1198743X18307365 (cmi accepted v).pdf
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