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Application of a practice-based approach in variable selection for a prediction model development study of hospital-induced delirium

BACKGROUND: Prognostic models of hospital-induced delirium, that include potential predisposing and precipitating factors, may be used to identify vulnerable patients and inform the implementation of tailored preventive interventions. It is recommended that, in prediction model development studies,...

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Autores principales: Snigurska, Urszula A., Ser, Sarah E., Solberg, Laurence M., Prosperi, Mattia, Magoc, Tanja, Chen, Zhaoyi, Bian, Jiang, Bjarnadottir, Ragnhildur I., Lucero, Robert J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10500854/
https://www.ncbi.nlm.nih.gov/pubmed/37704994
http://dx.doi.org/10.1186/s12911-023-02278-1
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author Snigurska, Urszula A.
Ser, Sarah E.
Solberg, Laurence M.
Prosperi, Mattia
Magoc, Tanja
Chen, Zhaoyi
Bian, Jiang
Bjarnadottir, Ragnhildur I.
Lucero, Robert J.
author_facet Snigurska, Urszula A.
Ser, Sarah E.
Solberg, Laurence M.
Prosperi, Mattia
Magoc, Tanja
Chen, Zhaoyi
Bian, Jiang
Bjarnadottir, Ragnhildur I.
Lucero, Robert J.
author_sort Snigurska, Urszula A.
collection PubMed
description BACKGROUND: Prognostic models of hospital-induced delirium, that include potential predisposing and precipitating factors, may be used to identify vulnerable patients and inform the implementation of tailored preventive interventions. It is recommended that, in prediction model development studies, candidate predictors are selected on the basis of existing knowledge, including knowledge from clinical practice. The purpose of this article is to describe the process of identifying and operationalizing candidate predictors of hospital-induced delirium for application in a prediction model development study using a practice-based approach. METHODS: This study is part of a larger, retrospective cohort study that is developing prognostic models of hospital-induced delirium for medical-surgical older adult patients using structured data from administrative and electronic health records. First, we conducted a review of the literature to identify clinical concepts that had been used as candidate predictors in prognostic model development-and-validation studies of hospital-induced delirium. Then, we consulted a multidisciplinary task force of nine members who independently judged whether each clinical concept was associated with hospital-induced delirium. Finally, we mapped the clinical concepts to the administrative and electronic health records and operationalized our candidate predictors. RESULTS: In the review of 34 studies, we identified 504 unique clinical concepts. Two-thirds of the clinical concepts (337/504) were used as candidate predictors only once. The most common clinical concepts included age (31/34), sex (29/34), and alcohol use (22/34). 96% of the clinical concepts (484/504) were judged to be associated with the development of hospital-induced delirium by at least two members of the task force. All of the task force members agreed that 47 or 9% of the 504 clinical concepts were associated with hospital-induced delirium. CONCLUSIONS: Heterogeneity among candidate predictors of hospital-induced delirium in the literature suggests a still evolving list of factors that contribute to the development of this complex phenomenon. We demonstrated a practice-based approach to variable selection for our model development study of hospital-induced delirium. Expert judgement of variables enabled us to categorize the variables based on the amount of agreement among the experts and plan for the development of different models, including an expert-model and data-driven model. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12911-023-02278-1.
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spelling pubmed-105008542023-09-15 Application of a practice-based approach in variable selection for a prediction model development study of hospital-induced delirium Snigurska, Urszula A. Ser, Sarah E. Solberg, Laurence M. Prosperi, Mattia Magoc, Tanja Chen, Zhaoyi Bian, Jiang Bjarnadottir, Ragnhildur I. Lucero, Robert J. BMC Med Inform Decis Mak Research BACKGROUND: Prognostic models of hospital-induced delirium, that include potential predisposing and precipitating factors, may be used to identify vulnerable patients and inform the implementation of tailored preventive interventions. It is recommended that, in prediction model development studies, candidate predictors are selected on the basis of existing knowledge, including knowledge from clinical practice. The purpose of this article is to describe the process of identifying and operationalizing candidate predictors of hospital-induced delirium for application in a prediction model development study using a practice-based approach. METHODS: This study is part of a larger, retrospective cohort study that is developing prognostic models of hospital-induced delirium for medical-surgical older adult patients using structured data from administrative and electronic health records. First, we conducted a review of the literature to identify clinical concepts that had been used as candidate predictors in prognostic model development-and-validation studies of hospital-induced delirium. Then, we consulted a multidisciplinary task force of nine members who independently judged whether each clinical concept was associated with hospital-induced delirium. Finally, we mapped the clinical concepts to the administrative and electronic health records and operationalized our candidate predictors. RESULTS: In the review of 34 studies, we identified 504 unique clinical concepts. Two-thirds of the clinical concepts (337/504) were used as candidate predictors only once. The most common clinical concepts included age (31/34), sex (29/34), and alcohol use (22/34). 96% of the clinical concepts (484/504) were judged to be associated with the development of hospital-induced delirium by at least two members of the task force. All of the task force members agreed that 47 or 9% of the 504 clinical concepts were associated with hospital-induced delirium. CONCLUSIONS: Heterogeneity among candidate predictors of hospital-induced delirium in the literature suggests a still evolving list of factors that contribute to the development of this complex phenomenon. We demonstrated a practice-based approach to variable selection for our model development study of hospital-induced delirium. Expert judgement of variables enabled us to categorize the variables based on the amount of agreement among the experts and plan for the development of different models, including an expert-model and data-driven model. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12911-023-02278-1. BioMed Central 2023-09-13 /pmc/articles/PMC10500854/ /pubmed/37704994 http://dx.doi.org/10.1186/s12911-023-02278-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Snigurska, Urszula A.
Ser, Sarah E.
Solberg, Laurence M.
Prosperi, Mattia
Magoc, Tanja
Chen, Zhaoyi
Bian, Jiang
Bjarnadottir, Ragnhildur I.
Lucero, Robert J.
Application of a practice-based approach in variable selection for a prediction model development study of hospital-induced delirium
title Application of a practice-based approach in variable selection for a prediction model development study of hospital-induced delirium
title_full Application of a practice-based approach in variable selection for a prediction model development study of hospital-induced delirium
title_fullStr Application of a practice-based approach in variable selection for a prediction model development study of hospital-induced delirium
title_full_unstemmed Application of a practice-based approach in variable selection for a prediction model development study of hospital-induced delirium
title_short Application of a practice-based approach in variable selection for a prediction model development study of hospital-induced delirium
title_sort application of a practice-based approach in variable selection for a prediction model development study of hospital-induced delirium
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10500854/
https://www.ncbi.nlm.nih.gov/pubmed/37704994
http://dx.doi.org/10.1186/s12911-023-02278-1
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