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Developing and validating a risk prediction model for acute care based on frailty syndromes

OBJECTIVES: Population ageing may result in increased comorbidity, functional dependence and poor quality of life. Mechanisms and pathophysiology underlying frailty have not been fully elucidated, thus absolute consensus on an operational definition for frailty is lacking. Frailty scores in the acut...

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Autores principales: Soong, J, Poots, A J, Scott, S, Donald, K, Bell, D
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4621379/
https://www.ncbi.nlm.nih.gov/pubmed/26490098
http://dx.doi.org/10.1136/bmjopen-2015-008457
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author Soong, J
Poots, A J
Scott, S
Donald, K
Bell, D
author_facet Soong, J
Poots, A J
Scott, S
Donald, K
Bell, D
author_sort Soong, J
collection PubMed
description OBJECTIVES: Population ageing may result in increased comorbidity, functional dependence and poor quality of life. Mechanisms and pathophysiology underlying frailty have not been fully elucidated, thus absolute consensus on an operational definition for frailty is lacking. Frailty scores in the acute medical care setting have poor predictive power for clinically relevant outcomes. We explore the utility of frailty syndromes (as recommended by national guidelines) as a risk prediction model for the elderly in the acute care setting. SETTING: English Secondary Care emergency admissions to National Health Service (NHS) acute providers. PARTICIPANTS: There were N=2 099 252 patients over 65 years with emergency admission to NHS acute providers from 01/01/2012 to 31/12/2012 included in the analysis. PRIMARY AND SECONDARY OUTCOME MEASURES: Outcomes investigated include inpatient mortality, 30-day emergency readmission and institutionalisation. We used pseudorandom numbers to split patients into train (60%) and test (40%). Receiver operator characteristic (ROC) curves and ordering the patients by deciles of predicted risk was used to assess model performance. Using English Hospital Episode Statistics (HES) data, we built multivariable logistic regression models with independent variables based on frailty syndromes (10th revision International Statistical Classification of Diseases, Injuries and Causes of Death (ICD-10) coding), demographics and previous hospital utilisation. Patients included were those >65 years with emergency admission to acute provider in England (2012). RESULTS: Frailty syndrome models exhibited ROC scores of 0.624–0.659 for inpatient mortality, 0.63–0.654 for institutionalisation and 0.57–0.63 for 30-day emergency readmission. CONCLUSIONS: Frailty syndromes are a valid predictor of outcomes relevant to acute care. The models predictive power is in keeping with other scores in the literature, but is a simple, clinically relevant and potentially more acceptable measurement for use in the acute care setting. Predictive powers of the score are not sufficient for clinical use.
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spelling pubmed-46213792015-11-02 Developing and validating a risk prediction model for acute care based on frailty syndromes Soong, J Poots, A J Scott, S Donald, K Bell, D BMJ Open Geriatric Medicine OBJECTIVES: Population ageing may result in increased comorbidity, functional dependence and poor quality of life. Mechanisms and pathophysiology underlying frailty have not been fully elucidated, thus absolute consensus on an operational definition for frailty is lacking. Frailty scores in the acute medical care setting have poor predictive power for clinically relevant outcomes. We explore the utility of frailty syndromes (as recommended by national guidelines) as a risk prediction model for the elderly in the acute care setting. SETTING: English Secondary Care emergency admissions to National Health Service (NHS) acute providers. PARTICIPANTS: There were N=2 099 252 patients over 65 years with emergency admission to NHS acute providers from 01/01/2012 to 31/12/2012 included in the analysis. PRIMARY AND SECONDARY OUTCOME MEASURES: Outcomes investigated include inpatient mortality, 30-day emergency readmission and institutionalisation. We used pseudorandom numbers to split patients into train (60%) and test (40%). Receiver operator characteristic (ROC) curves and ordering the patients by deciles of predicted risk was used to assess model performance. Using English Hospital Episode Statistics (HES) data, we built multivariable logistic regression models with independent variables based on frailty syndromes (10th revision International Statistical Classification of Diseases, Injuries and Causes of Death (ICD-10) coding), demographics and previous hospital utilisation. Patients included were those >65 years with emergency admission to acute provider in England (2012). RESULTS: Frailty syndrome models exhibited ROC scores of 0.624–0.659 for inpatient mortality, 0.63–0.654 for institutionalisation and 0.57–0.63 for 30-day emergency readmission. CONCLUSIONS: Frailty syndromes are a valid predictor of outcomes relevant to acute care. The models predictive power is in keeping with other scores in the literature, but is a simple, clinically relevant and potentially more acceptable measurement for use in the acute care setting. Predictive powers of the score are not sufficient for clinical use. BMJ Publishing Group 2015-10-21 /pmc/articles/PMC4621379/ /pubmed/26490098 http://dx.doi.org/10.1136/bmjopen-2015-008457 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/
spellingShingle Geriatric Medicine
Soong, J
Poots, A J
Scott, S
Donald, K
Bell, D
Developing and validating a risk prediction model for acute care based on frailty syndromes
title Developing and validating a risk prediction model for acute care based on frailty syndromes
title_full Developing and validating a risk prediction model for acute care based on frailty syndromes
title_fullStr Developing and validating a risk prediction model for acute care based on frailty syndromes
title_full_unstemmed Developing and validating a risk prediction model for acute care based on frailty syndromes
title_short Developing and validating a risk prediction model for acute care based on frailty syndromes
title_sort developing and validating a risk prediction model for acute care based on frailty syndromes
topic Geriatric Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4621379/
https://www.ncbi.nlm.nih.gov/pubmed/26490098
http://dx.doi.org/10.1136/bmjopen-2015-008457
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