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Development of a Clinical Prediction Rule for Adverse Events in Multimorbid Patients in Emergency and Hospitalisation
(1) Background: There is currently a global consensus that the quality of comprehensive care for acutely hospitalised elderly people should include addressing functionality and mobility, cognitive status, prevention of pressure ulcers, urinary incontinence, falls and delirium, as well as pain contro...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9324433/ https://www.ncbi.nlm.nih.gov/pubmed/35886434 http://dx.doi.org/10.3390/ijerph19148581 |
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author | Morales-Puerto, Marta Ruiz-Díaz, María Aranda-Gallardo, Marta Morales-Asencio, José Miguel Alcalá-Gutiérrez, Purificación Rodríguez-Montalvo, José Antonio León-Campos, Álvaro García-Mayor, Silvia Canca-Sánchez, José Carlos |
author_facet | Morales-Puerto, Marta Ruiz-Díaz, María Aranda-Gallardo, Marta Morales-Asencio, José Miguel Alcalá-Gutiérrez, Purificación Rodríguez-Montalvo, José Antonio León-Campos, Álvaro García-Mayor, Silvia Canca-Sánchez, José Carlos |
author_sort | Morales-Puerto, Marta |
collection | PubMed |
description | (1) Background: There is currently a global consensus that the quality of comprehensive care for acutely hospitalised elderly people should include addressing functionality and mobility, cognitive status, prevention of pressure ulcers, urinary incontinence, falls and delirium, as well as pain control and medication-related problems. The aim of this study is to develop and validate a clinical prediction rule for multimorbid patients admitted to an acute care hospital unit for any of the five adverse events included in our vulnerability pentad: falls, pressure ulcers, urinary incontinence, pain and delirium. (2) Methods: Longitudinal analytical clinimetric study, with two cohorts. The study population will consist of multimorbid patients hospitalised for acute care, referred from the Emergency Room. A clinical prediction rule will be proposed, incorporating predictive factors of these five adverse outcomes described. This study has received funding, awarded in November 2020 (PI-0107-2020), and was approved in October 2019 by the Research Ethics Committee ″Costa del Sol″. (3) Conclusions: Preventing adverse events in hospitalised patients is particularly important for those with multimorbidity. By applying a clinical prediction rule to detect specific risks, an estimate can be obtained of their probability of occurrence. |
format | Online Article Text |
id | pubmed-9324433 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93244332022-07-27 Development of a Clinical Prediction Rule for Adverse Events in Multimorbid Patients in Emergency and Hospitalisation Morales-Puerto, Marta Ruiz-Díaz, María Aranda-Gallardo, Marta Morales-Asencio, José Miguel Alcalá-Gutiérrez, Purificación Rodríguez-Montalvo, José Antonio León-Campos, Álvaro García-Mayor, Silvia Canca-Sánchez, José Carlos Int J Environ Res Public Health Study Protocol (1) Background: There is currently a global consensus that the quality of comprehensive care for acutely hospitalised elderly people should include addressing functionality and mobility, cognitive status, prevention of pressure ulcers, urinary incontinence, falls and delirium, as well as pain control and medication-related problems. The aim of this study is to develop and validate a clinical prediction rule for multimorbid patients admitted to an acute care hospital unit for any of the five adverse events included in our vulnerability pentad: falls, pressure ulcers, urinary incontinence, pain and delirium. (2) Methods: Longitudinal analytical clinimetric study, with two cohorts. The study population will consist of multimorbid patients hospitalised for acute care, referred from the Emergency Room. A clinical prediction rule will be proposed, incorporating predictive factors of these five adverse outcomes described. This study has received funding, awarded in November 2020 (PI-0107-2020), and was approved in October 2019 by the Research Ethics Committee ″Costa del Sol″. (3) Conclusions: Preventing adverse events in hospitalised patients is particularly important for those with multimorbidity. By applying a clinical prediction rule to detect specific risks, an estimate can be obtained of their probability of occurrence. MDPI 2022-07-14 /pmc/articles/PMC9324433/ /pubmed/35886434 http://dx.doi.org/10.3390/ijerph19148581 Text en © 2022 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 | Study Protocol Morales-Puerto, Marta Ruiz-Díaz, María Aranda-Gallardo, Marta Morales-Asencio, José Miguel Alcalá-Gutiérrez, Purificación Rodríguez-Montalvo, José Antonio León-Campos, Álvaro García-Mayor, Silvia Canca-Sánchez, José Carlos Development of a Clinical Prediction Rule for Adverse Events in Multimorbid Patients in Emergency and Hospitalisation |
title | Development of a Clinical Prediction Rule for Adverse Events in Multimorbid Patients in Emergency and Hospitalisation |
title_full | Development of a Clinical Prediction Rule for Adverse Events in Multimorbid Patients in Emergency and Hospitalisation |
title_fullStr | Development of a Clinical Prediction Rule for Adverse Events in Multimorbid Patients in Emergency and Hospitalisation |
title_full_unstemmed | Development of a Clinical Prediction Rule for Adverse Events in Multimorbid Patients in Emergency and Hospitalisation |
title_short | Development of a Clinical Prediction Rule for Adverse Events in Multimorbid Patients in Emergency and Hospitalisation |
title_sort | development of a clinical prediction rule for adverse events in multimorbid patients in emergency and hospitalisation |
topic | Study Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9324433/ https://www.ncbi.nlm.nih.gov/pubmed/35886434 http://dx.doi.org/10.3390/ijerph19148581 |
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