DEVELOPMENT AND INTERNAL VALIDATION OF A PREDICTION MODEL TO IDENTIFY OLDER ADULTS AT RISK OF LOW PHYSICAL ACTIVITY DURING HOSPITALISATION

H.C. van Dijk - Huisman^1,2, M.H.P. Welters³, W. Bijnens⁴, S.M.J. van Kuijk⁵, F.J.H. Magdelijns⁶, R.A. de Bie^2,7, A.F. Lenssen^3,2

¹Maastricht University Medical Center, Department of Physiotherapy, Maastricht, Netherlands, ²Maastricht University, CAPHRI School for Public Health and Primary Care, Maastricht, Netherlands, ³Maastricht University Medical Center, Physiotherapy, Maastricht, Netherlands, ⁴Maastricht University, Research Engineering (IDEE), Maastricht, Netherlands, ⁵Maastricht University Medical Center, Department of Clinical Epidemiology and Medical Technology Assessment, Maastricht, Netherlands, ⁶Maastricht University Medical Center, Department of Internal Medicine, Division of General Medicine and Clinical Geriatric Medicine, Maastricht, Netherlands, ⁷Maastricht University, Department of Epidemiology, Faculty of Health, Medicine and Life Sciences, School for Public Health and Primary Care, Maastricht, Netherlands

Background: Inactive behaviour is common in older adults during hospitalisation and associated with poor health outcomes. If patients at high risk of spending little time standing/walking could be identified early after admission, they could be given interventions aimed at increasing their time spent standing/walking, such as guidance from a physiotherapist. A prognostic tool that predicts a patient’s probability of spending little time standing/walking during hospitalisation does not exist yet. Because of the association between inactive behaviour and functional decline we expect that the Short Physical Performance Battery (SPPB) and the Activity Measure for Post-Acute Care Inpatient Basic Mobility short form (AM-PAC) could help to accurately predict the probability of spending little time standing/walking during hospitalisation.

Purpose: The purpose of this study is to develop and validate a prediction model that can be used early after admission to identify older adults at high risk of spending little time standing/walking during hospitalisation.

Methods: A prospective cohort study was conducted at the Maastricht University Medical Centre between October 2018 and March 2020. Older adults (≥70 years) admitted to the department of Internal Medicine for acute medical illness were recruited within 48 hours of admittance. Two prediction models were developed to predict the probability of low PA levels during hospitalisation. Time spent standing/walking per day was measured with an accelerometer until discharge (≤12 days). The average time standing/walking per day between inclusion and discharge was dichotomized into low/high PA levels by dividing the cohort at the median (50.0%) in model 1, and lowest tertile (33.3%) in model 2. Potential predictors - SPPB, AM-PAC, age, sex, walking aid use, and disabilities in activities of daily living - were selected based on literature and analysed using logistic regression analysis. Models were internally validated using bootstrapping. Model performance was quantified using measures of discrimination (area under the receiver operating characteristic curve (AUC)) and calibration (Hosmer and Lemeshow (H-L) goodness-of-fit test and calibration plots).

Results: A total of 165 patients were included. Model 1 predicts a probability of spending ≤64.4 minutes standing/walking and holds the predictors SPPB, AM-PAC and sex. Model 2 predicts a probability of spending ≤47.2 minutes standing/walking and holds the predictors SPPB, AM-PAC, age and walking aid use. AUCs of models 1 and 2 were .80 (95% confidence interval (CI) = .73 - .87) and .86 (95%CI = .79 - .92), respectively, indicating good discriminative ability. Both models demonstrate near perfect calibration of the predicted probabilities and good overall performance, with model 2 performing slightly better.

Conclusions: The developed and internally validated prediction models enable clinicians to identify older adults at high risk of low PA levels during hospitalisation. External validation and determining the clinical impact are needed before applying the models in clinical practise.

Implications: The models can be used in clinical practice by performing a screening early after admission, consisting of the SPPB, AM-PAC, age, sex and walking aid use. Patients at high risk can subsequently be given interventions aimed at increasing their PA behaviour.

Funding acknowledgements: This research received no funding.

Keywords:
Physical activity
Hospital
Older adults

Topics:
Health promotion & wellbeing/healthy ageing/physical activity
Disability & rehabilitation
Older people

Did this work require ethics approval? Yes

Institution: Maastricht University Medical Center

Committee: University Hospital Maastricht and Maastricht University (METC azM/UM)

Ethics number: METC18-103