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Hospital-induced Delirium among Medical Older Adults: Evaluating the Veracity of Prognostic Models

Several prognostic models have been developed and validated for delirium prediction among older adults. However, model development and validation studies need to be evaluated for risk of bias to establish the veracity of the prognostic models. This is a critical step before they can be implemented i...

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Autores principales: Snigurska, Urszula, Bjarnadottir, Ragnhildur, Lucero, Robert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8682124/
http://dx.doi.org/10.1093/geroni/igab046.3613
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author Snigurska, Urszula
Bjarnadottir, Ragnhildur
Lucero, Robert
author_facet Snigurska, Urszula
Bjarnadottir, Ragnhildur
Lucero, Robert
author_sort Snigurska, Urszula
collection PubMed
description Several prognostic models have been developed and validated for delirium prediction among older adults. However, model development and validation studies need to be evaluated for risk of bias to establish the veracity of the prognostic models. This is a critical step before they can be implemented in clinical practice. Multiple systematic reviews have evaluated prognostic models of hospital-induced delirium. However, none of the existing systematic reviews evaluated the validity of models for non-surgical, medical hospitalized older adults. We conducted a scoping review to evaluate the validity of existing prognostic models of hospital-induced delirium in medical older adults. CINAHL, PsycINFO, PubMed, and Web of Science were searched for original studies. The database search yielded 4,312 records. Five studies were included in the qualitative synthesis. All the studies claimed to have developed valid prognostic models. However, the risk of bias assessment revealed that existing prognostic models of hospital-induced delirium in medical older adults are at a high risk of bias. Collectively, the statistical analysis was the greatest source of bias. Notably, while we have seen a proliferation of prognostic models for use in the surgical older adult population, efforts at developing prognostic models in the medical older adult population seem to have declined since the early 1990s. Newer methods of data collection, such as data mining of electronic health records, and statistical analysis, such as machine learning, have shown promise in accurate prediction of hospital-induced delirium while overcoming many challenges associated with manual data collection and traditional statistical analyses.
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spelling pubmed-86821242021-12-20 Hospital-induced Delirium among Medical Older Adults: Evaluating the Veracity of Prognostic Models Snigurska, Urszula Bjarnadottir, Ragnhildur Lucero, Robert Innov Aging Abstracts Several prognostic models have been developed and validated for delirium prediction among older adults. However, model development and validation studies need to be evaluated for risk of bias to establish the veracity of the prognostic models. This is a critical step before they can be implemented in clinical practice. Multiple systematic reviews have evaluated prognostic models of hospital-induced delirium. However, none of the existing systematic reviews evaluated the validity of models for non-surgical, medical hospitalized older adults. We conducted a scoping review to evaluate the validity of existing prognostic models of hospital-induced delirium in medical older adults. CINAHL, PsycINFO, PubMed, and Web of Science were searched for original studies. The database search yielded 4,312 records. Five studies were included in the qualitative synthesis. All the studies claimed to have developed valid prognostic models. However, the risk of bias assessment revealed that existing prognostic models of hospital-induced delirium in medical older adults are at a high risk of bias. Collectively, the statistical analysis was the greatest source of bias. Notably, while we have seen a proliferation of prognostic models for use in the surgical older adult population, efforts at developing prognostic models in the medical older adult population seem to have declined since the early 1990s. Newer methods of data collection, such as data mining of electronic health records, and statistical analysis, such as machine learning, have shown promise in accurate prediction of hospital-induced delirium while overcoming many challenges associated with manual data collection and traditional statistical analyses. Oxford University Press 2021-12-17 /pmc/articles/PMC8682124/ http://dx.doi.org/10.1093/geroni/igab046.3613 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of The Gerontological Society of America. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Abstracts
Snigurska, Urszula
Bjarnadottir, Ragnhildur
Lucero, Robert
Hospital-induced Delirium among Medical Older Adults: Evaluating the Veracity of Prognostic Models
title Hospital-induced Delirium among Medical Older Adults: Evaluating the Veracity of Prognostic Models
title_full Hospital-induced Delirium among Medical Older Adults: Evaluating the Veracity of Prognostic Models
title_fullStr Hospital-induced Delirium among Medical Older Adults: Evaluating the Veracity of Prognostic Models
title_full_unstemmed Hospital-induced Delirium among Medical Older Adults: Evaluating the Veracity of Prognostic Models
title_short Hospital-induced Delirium among Medical Older Adults: Evaluating the Veracity of Prognostic Models
title_sort hospital-induced delirium among medical older adults: evaluating the veracity of prognostic models
topic Abstracts
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8682124/
http://dx.doi.org/10.1093/geroni/igab046.3613
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