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


METHODS
English Secondary Care emergency admissions to National Health Service (NHS) acute providers.


METHODS
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.


METHODS
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.
NIHR CLAHRC Northwest London, Imperial College London, Chelsea and Westminster Campus, London, UK Royal College of Physicians, London, UK.
J
J
Soong
NIHR CLAHRC Northwest London, Imperial College London, Chelsea and Westminster Campus, London, UK.
A J
http://orcid.org/0000-0002-2331-0904
AJ
Poots
Oliver Wyman, London, UK.
S
S
Scott
Oliver Wyman, London, UK.
K
K
Donald
NIHR CLAHRC Northwest London, Imperial College London, Chelsea and Westminster Campus, London, UK.
D
http://orcid.org/0000-0002-9944-1097
D
Bell
D000368:Aged; D000369:Aged, 80 and over; D000375:Aging; D059019:Clinical Coding / Q000592:standards*; D015897:Comorbidity; D003422:Critical Care / Q000592:standards*; D016208:Databases, Factual; D004739:England / Q000453:epidemiology; D005260:Female; D016330:Frail Elderly / Q000706:statistics & numerical data*; D015577:Geriatric Assessment; D017052:Hospital Mortality / Q000639:trends*; D006801:Humans; D038801:International Classification of Diseases; D016015:Logistic Models; D008297:Male; D015999:Multivariate Analysis; D010359:Patient Readmission / Q000706:statistics & numerical data*; D011788:Quality of Life; D012372:ROC Curve; D012307:Risk Factors
Acute; Frailty Syndromes; Model; Outcomes; Risk Prediction