Can information on functional and cognitive status improve short-term mortality risk prediction among community-dwelling older people? A cohort study using a UK primary care database
Received 4 July 2017
Accepted for publication 11 October 2017
Published 19 December 2017 Volume 2018:10 Pages 31—39
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Professor Henrik Toft Sørensen
Janet Sultana,1,2 Andrea Fontana,3 Francesco Giorgianni,1 Giorgio Basile,1 Elisabetta Patorno,4 Alberto Pilotto,5 Mariam Molokhia,6 Robert Stewart,7 Miriam Sturkenboom,2 Gianluca Trifirò1,2
1Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, Italy; 2Department of Medical Informatics, Erasmus University Medical Centre, Rotterdam, the Netherlands; 3Unit of Biostatistics, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy; 4Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, USA; 5Geriatrics Unit, Department of Geriatric Care, Ortho Geriatrics and Rehabilitation, Frailty Area, E.O. Galliera Hospital, Genova, Italy; 6Department of Primary Care and Public Health Sciences, King’s College, London, UK; 7Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience King’s College London, UK
Background: Functional and cognitive domains have rarely been evaluated for their prognostic value in general practice databases. The aim of this study was to identify functional and cognitive domains in The Health Improvement Network (THIN) and to evaluate their additional value for the prediction of 1-month and 1-year mortality in elderly people.
Materials and methods: A cohort study was conducted using a UK nationwide general practitioner database. A total of 1,193,268 patients aged 65 years or older, of whom 15,300 had dementia, were identified from 2000 to 2012. Information on mobility, dressing and accommodation was recorded frequently enough to be analyzed further in THIN. Cognition data could not be used due to very poor recording of data in THIN. One-year and 1-month mortality was predicted using logistic models containing variables such as age, sex, disease score and functionality status.
Results: A significant but moderate improvement in 1-year and 1-month mortality prediction in elderly people was observed by adding accommodation to the variables age, sex and disease score, as the c-statistic (95% confidence interval [CI]) increased from 0.71 (0.70–0.72) to 0.76 (0.75–0.77) and 0.73 (0.71–0.75) to 0.79 (0.77–0.80), respectively. A less notable improvement in the prediction of 1-year and 1-month mortality was observed in people with dementia.
Conclusion: Functional domains moderately improved the accuracy of a model including age, sex and comorbidities in predicting 1-year and 1-month mortality risk among community-dwelling older people, but they were much less able to predict mortality in people with dementia. Cognition could not be explored as a predictor of mortality due to insufficient data being recorded.
Keywords: elderly, frailty, database, mortality
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