TY - JOUR
T1 - Measurement of Dynamical Resilience Indicators Improves the Prediction of Recovery Following Hospitalization in Older Adults
AU - Gijzel, Sanne M.W.
AU - Rector, Jerrald
AU - van Meulen, Fokke B.
AU - van der Loeff, Rolinka Schim
AU - van de Leemput, Ingrid A.
AU - Scheffer, Marten
AU - Olde Rikkert, Marcel G.M.
AU - Melis, René J.F.
PY - 2020/4
Y1 - 2020/4
N2 - Objectives: Acute illnesses and subsequent hospital admissions present large health stressors to older adults, after which their recovery is variable. The concept of physical resilience offers opportunities to develop dynamical tools to predict an individual's recovery potential. This study aimed to investigate if dynamical resilience indicators based on repeated physical and mental measurements in acutely hospitalized geriatric patients have added value over single baseline measurements in predicting favorable recovery. Design: Intensive longitudinal study. Setting and Participants: 121 patients (aged 84.3 ± 6.2 years, 60% female) admitted to the geriatric ward for acute illness. Measurements: In addition to preadmission characteristics (frailty, multimorbidity), in-hospital heart rate and physical activity were continuously monitored with a wearable sensor. Momentary well-being (life satisfaction, anxiety, discomfort) was measured by experience sampling 4 times per day. The added value of dynamical indicators of resilience was investigated for predicting recovery at hospital discharge and 3 months later. Results: 31% of participants satisfied the criteria of good recovery at hospital discharge and 50% after 3 months. A combination of a frailty index, multimorbidity, Clinical Frailty Scale, and or gait speed predicted good recovery reasonably well on the short term [area under the receiver operating characteristic curve (AUC) = 0.79], but only moderately after 3 months (AUC = 0.70). On addition of dynamical resilience indicators, the AUC for predicting good 3-month recovery increased to 0.79 (P = .03). Variability in life satisfaction and anxiety during the hospital stay were independent predictors of good 3-month recovery [odds ratio (OR) = 0.24, P = .01, and OR = 0.54, P = .04, respectively]. Conclusions and Implications: These results highlight that measurements capturing the dynamic functioning of multiple physiological systems have added value in assessing physical resilience in clinical practice, especially those monitoring mental responses. Improved monitoring and prediction of physical resilience could help target intensive treatment options and subsequent geriatric rehabilitation to patients who will most likely benefit from them.
AB - Objectives: Acute illnesses and subsequent hospital admissions present large health stressors to older adults, after which their recovery is variable. The concept of physical resilience offers opportunities to develop dynamical tools to predict an individual's recovery potential. This study aimed to investigate if dynamical resilience indicators based on repeated physical and mental measurements in acutely hospitalized geriatric patients have added value over single baseline measurements in predicting favorable recovery. Design: Intensive longitudinal study. Setting and Participants: 121 patients (aged 84.3 ± 6.2 years, 60% female) admitted to the geriatric ward for acute illness. Measurements: In addition to preadmission characteristics (frailty, multimorbidity), in-hospital heart rate and physical activity were continuously monitored with a wearable sensor. Momentary well-being (life satisfaction, anxiety, discomfort) was measured by experience sampling 4 times per day. The added value of dynamical indicators of resilience was investigated for predicting recovery at hospital discharge and 3 months later. Results: 31% of participants satisfied the criteria of good recovery at hospital discharge and 50% after 3 months. A combination of a frailty index, multimorbidity, Clinical Frailty Scale, and or gait speed predicted good recovery reasonably well on the short term [area under the receiver operating characteristic curve (AUC) = 0.79], but only moderately after 3 months (AUC = 0.70). On addition of dynamical resilience indicators, the AUC for predicting good 3-month recovery increased to 0.79 (P = .03). Variability in life satisfaction and anxiety during the hospital stay were independent predictors of good 3-month recovery [odds ratio (OR) = 0.24, P = .01, and OR = 0.54, P = .04, respectively]. Conclusions and Implications: These results highlight that measurements capturing the dynamic functioning of multiple physiological systems have added value in assessing physical resilience in clinical practice, especially those monitoring mental responses. Improved monitoring and prediction of physical resilience could help target intensive treatment options and subsequent geriatric rehabilitation to patients who will most likely benefit from them.
KW - Adaptive capacity
KW - personalized medicine
KW - resistance
KW - time series analysis
KW - wearable sensor
U2 - 10.1016/j.jamda.2019.10.011
DO - 10.1016/j.jamda.2019.10.011
M3 - Article
C2 - 31836428
AN - SCOPUS:85076489297
SN - 1525-8610
VL - 21
SP - 525–530.e4
JO - Journal of the American Medical Directors Association
JF - Journal of the American Medical Directors Association
IS - 4
ER -
