Developing and validating a risk prediction model for acute care based on frailty syndromes
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TLDR
Frailty syndromes are a valid predictor of outcomes relevant to acute care and are a simple, clinically relevant and potentially more acceptable measurement for use in the acute care setting.Abstract:
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.read more
Citations
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Journal ArticleDOI
Development and validation of a hospital frailty risk score focusing on older people in acute care settings using electronic hospital records; an observational study
Thomas Gilbert,Jenny Neuburger,Joshua Kraindler,Eilís Keeble,Paul V. Smith,Cono Ariti,Sandeepa Arora,Andrew Street,Stuart G Parker,Helen C. Roberts,Martin Bardsley,Simon Conroy +11 more
TL;DR: The Hospital Frailty Risk Score provides hospitals and health systems with a low-cost, systematic way to screen for frailty and identify a group of patients who are at greater risk of adverse outcomes and for whom a frailty-attuned approach might be useful.
Journal ArticleDOI
Data Resource Profile: Hospital Episode Statistics Admitted Patient Care (HES APC).
Annie Herbert,Linda Wijlaars,Ania Zylbersztejn,Ania Zylbersztejn,David A Cromwell,Pia Hardelid,Pia Hardelid +6 more
TL;DR: In this article, the authors identified 264 relevant publications where the primary analysis involved the use of HES APC data, and a further 130 papers where HES data had been linked to cohorts created in other datasets.
Journal ArticleDOI
Measuring Frailty in Medicare Data: Development and Validation of a Claims-Based Frailty Index.
Dae Hyun Kim,Dae Hyun Kim,Sebastian Schneeweiss,Robert J. Glynn,Lewis A. Lipsitz,Lewis A. Lipsitz,Kenneth Rockwood,Jerry Avorn +7 more
TL;DR: A novel frailty index can measure the risk for adverse health outcomes that is not otherwise quantified using demographic characteristics and traditional comorbidity measures in Medicare data.
Journal ArticleDOI
Validation of a Claims-Based Frailty Index Against Physical Performance and Adverse Health Outcomes in the Health and Retirement Study.
Dae Hyun Kim,Robert J. Glynn,Jerry Avorn,Lewis A. Lipsitz,Kenneth Rockwood,Ajinkya Pawar,Sebastian Schneeweiss +6 more
TL;DR: The CFI is useful to identify individuals with poor physical function and at greater risks of adverse health outcomes in Medicare data and remained statistically significant after adjustment for age, sex, and a comorbidity index.
Journal ArticleDOI
Clinical frailty adds to acute illness severity in predicting mortality in hospitalized older adults: An observational study
TL;DR: It is found frailty and AIS independently associated with inpatient mortality after adjustment for confounders and hospitals may find it informative to undertake large scale assessment of frailty (vulnerability), as well as AIS (stressor), in older patients admitted to hospital as emergencies.
References
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Scikit-learn: Machine Learning in Python
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Frailty in Older Adults Evidence for a Phenotype
Linda P. Fried,Catherine M. Tangen,Jeremy D. Walston,Anne B. Newman,Calvin H. Hirsch,John S. Gottdiener,Teresa E. Seeman,Russell P. Tracy,Willem J. Kop,B Gregory Burke,Mary Ann McBurnie +10 more
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