Key result
Wearable digital biomarkers correlate moderately with KCCQ scores, enabling real-time functional status tracking.
Why the study?
Patient monitoring using patient-reported outcome measures is constrained by recall and non-response bias, respondent burden, and missing data.
Can wearable accelerometer-derived behavioural digital biomarkers predict patient-reported outcome measures in patients with an implantable cardioverter defibrillator?
Observational (n=303)
Yes
Can wearable accelerometer-derived behavioural digital biomarkers predict patient-reported outcome measures in patients with an implantable cardioverter defibrillator?
Effect estimate: CCC 0.49 (95% CI 0.38-0.59)
Wearable digital biomarkers can provide personalized, real-time estimation of patient-reported outcomes, potentially enabling proactive and tailored patient care.
May support real-time PRO monitoring in ICD patients; leaves open whether predictions improve outcomes in prospective trials.
AIMS: Patient-reported outcome measures (PROMs) serve multiple purposes, including shared decision-making and patient communication, treatment monitoring, and health technology assessment. Patient monitoring using PROMs is constrained by recall and non-response bias, respondent burden, and missing data. We evaluated the potential of behavioural digital biomarkers obtained from a wearable accelerometer to achieve personalized predictions of PROMs. METHODS AND RESULTS: Data from the multicentre, prospective SafeHeart study conducted at Amsterdam University Medical Center in the Netherlands and Copenhagen University Hospital, Rigshospitalet in Copenhagen, Denmark, were used. The study enrolled patients with an implantable cardioverter defibrillator between May 2021 and September 2022 who then wore wearable devices with raw acceleration output to capture digital biomarkers reflecting physical behaviour. To collect PROMs, patients received the Kansas City Cardiomyopathy Questionnaire (KCCQ) and EuroQoL 5-Dimensions 5-Level (EQ5D-5L) questionnaire at two instances: baseline and after six months. Multivariable Tobit regression models were used to explore associations between digital biomarkers and PROMs, specifically whether digital biomarkers could enable PROM prediction. The study population consisted of 303 patients (mean age 62.9 ± 10.9 years, 81.2% male). Digital biomarkers showed significant correlations to patient-reported physical and social limitations, severity and frequency of symptoms, and quality of life. Prospective validation of the Tobit models indicated moderate correlations between the observed and predicted scores for KCCQ [concordance correlation coefficient (CCC) = 0.49, mean difference: 1.07 points] and EQ5D-5L (CCC = 0.38, mean difference: 0.02 points). CONCLUSION: Wearable digital biomarkers correlate with PROMs, and may be leveraged for real-time prediction. These findings hold promise for monitoring of PROMs through wearable accelerometers.
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Kolk et al. (2023) conducted an observational in Implantable cardioverter defibrillator (ICD) carriers (n=303). Wearable accelerometer-derived behavioural digital biomarkers was evaluated on Prediction of KCCQ summary score (CCC 0.49, 95% CI 0.38-0.59). Wearable digital biomarkers showed moderate correlations with observed KCCQ scores (CCC 0.49) and EQ5D-5L scores (CCC 0.38), enabling real-time prediction of patient-reported outcomes.
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