A systems approach towards remote health-monitoring in older adults: Introducing a zero-interaction digital exhaust

Insights into endometriosis symptom trajectories and assessment of surgical intervention outcomes using longitudinal actigraphy

Endometriosis is a common, chronic condition associated with debilitating pain, fatigue, and heterogeneous symptom presentation. In this exploratory study, 68 participants with confirmed endometriosis were monitored for up to three 4-6-week smartwatch cycles. We collected daily self-reports of pain and fatigue as well as retrospective questionnaires assessing quality of life, and we extracted daily measures of physical activity (PA), sleep, and diurnal rhythms from wrist-worn actigraphy data. We found that daily PA was strongly negatively correlated with self-reported fatigue (repeated measures correlations R < - 0.3 ) and that participants with more severe or variable symptom trajectories displayed lower levels of PA, greater sleep disturbance, and more disrupted sleep and activity rhythms (Spearman's |R| > 0.3 ). Lastly, we found evidence of sleep and PA changes following surgery for endometriosis that reflected change in self-reported symptoms. Collectively, our findings suggest that passive data collection using wrist-worn wearables in endometriosis could facilitate individualized objective insights into symptom trajectories.

Free-Living Sit-to-Stand Characteristics as Predictors of Lower Extremity Functional Decline among Older Adults

PURPOSE

Habitual strength and power-demanding activities of daily life may support the maintenance of adequate lower extremity functioning with aging, but this has been sparingly explored. Hence, we examined whether the characteristics of free-living sit-to-stand (STS) transitions predict a decline in lower extremity functioning over a 4-yr follow-up.

METHODS

A total of 340 community-dwelling older adults (60% women; age 75, 80, or 85 yr) participated in this prospective cohort study. At baseline, a thigh-worn accelerometer was used continuously (3-7 d) to monitor the number and intensity of free-living STS transitions. A decline in lower extremity functioning was defined as a drop of ≥2 points in the Short Physical Performance Battery (SPPB) from baseline to follow-up. Maximal isometric knee extension strength was measured in the laboratory.

RESULTS

Eighty-five participants (75% women) declined in SPPB over 4 yr. After adjusting for age, sex, and baseline SPPB points, higher free-living peak STS angular velocity (odds ratio (OR), 0.70; 95% confidence interval (CI), 0.52-0.92, per 20°·s -1 increase) protected against a future decline. When adjusting the model for maximal isometric knee extension strength, the statistical significance was attenuated (OR = 0.72; 95% CI = 0.54-0.96, per 20°·s -1 increase).

CONCLUSIONS

Performing STS transitions at higher velocities in the free-living environment can prevent a future decline in lower extremity function. This indicates that changes in daily STS behavior may be useful in the early identification of functional loss. Free-living peak STS angular velocity may be a factor underlying the longitudinal association of lower extremity strength and performance.

Evaluation of Ambient Sensor Systems for the Early Detection of Heart Failure Decompensation in Older Patients Living at Home Alone: Protocol for a Prospective Cohort Study

BACKGROUND

The results of telemedicine intervention studies in patients with heart failure (HF) to reduce rehospitalization rate and mortality by early detection of HF decompensation are encouraging. However, the benefits are lower than expected. A possible reason for this could be the fact that vital signs, including blood pressure, heart rate, heart rhythm, and weight changes, may not be ideal indicators of the early stages of HF decompensation but are more sensitive for acute events triggered by ischemic episodes or rhythm disturbances. Preliminary results indicate a potential role of ambient sensor-derived digital biomarkers in this setting.

OBJECTIVE

The aim of this study is to identify changes in ambient sensor system-derived digital biomarkers with a high potential for early detection of HF decompensation.

METHODS

This is a prospective interventional cohort study. A total of 24 consecutive patients with HF aged 70 years and older, living alone, and hospitalized for HF decompensation will be included. Physical activity in the apartment and toilet visits are quantified using a commercially available, passive, infrared motion sensing system (DomoHealth SA). Heart rate, respiration rate, and toss-and-turns in bed are recorded by using a commercially available Emfit QS device (Emfit Ltd), which is a contact-free piezoelectric sensor placed under the participant's mattress. Sensor data are visualized on a dedicated dashboard for easy monitoring by health professionals. Digital biomarkers are evaluated for predefined signs of HF decompensation, including particularly decreased physical activity; time spent in bed; increasing numbers of toilet visits at night; and increasing heart rate, respiration rate, and motion in bed at night. When predefined changes in digital biomarkers occur, patients will be called in for clinical evaluation, and N-terminal pro b-type natriuretic peptide measurement (an increase of >30% considered as significant) will be performed. The sensitivity and specificity of the different biomarkers and their combinations for the detection of HF decompensation will be calculated.

RESULTS

The study is in the data collection phase. Study recruitment started in February 2024. Data analysis is scheduled to start after all data are collected. As of manuscript submission, 5 patients have been recruited. Results are expected to be published by the end of 2025.

CONCLUSIONS

The results of this study will add to the current knowledge about opportunities for telemedicine to monitor older patients with HF living at home alone by evaluating the potential of ambient sensor systems for this purpose. Timely recognition of HF decompensation could enable proactive management, potentially reducing health care costs associated with preventable emergency presentations or hospitalizations.

TRIAL REGISTRATION

ClinicalTrials.gov NCT06126848; https://clinicaltrials.gov/study/NCT06126848.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/55953.

Patient and Staff Experience of Remote Patient Monitoring-What to Measure and How: Systematic Review

BACKGROUND

Patient and staff experience is a vital factor to consider in the evaluation of remote patient monitoring (RPM) interventions. However, no comprehensive overview of available RPM patient and staff experience-measuring methods and tools exists.

OBJECTIVE

This review aimed at obtaining a comprehensive set of experience constructs and corresponding measuring instruments used in contemporary RPM research and at proposing an initial set of guidelines for improving methodological standardization in this domain.

METHODS

Full-text papers reporting on instances of patient or staff experience measuring in RPM interventions, written in English, and published after January 1, 2011, were considered for eligibility. By "RPM interventions," we referred to interventions including sensor-based patient monitoring used for clinical decision-making; papers reporting on other kinds of interventions were therefore excluded. Papers describing primary care interventions, involving participants under 18 years of age, or focusing on attitudes or technologies rather than specific interventions were also excluded. We searched 2 electronic databases, Medline (PubMed) and EMBASE, on February 12, 2021.We explored and structured the obtained corpus of data through correspondence analysis, a multivariate statistical technique.

RESULTS

In total, 158 papers were included, covering RPM interventions in a variety of domains. From these studies, we reported 546 experience-measuring instances in RPM, covering the use of 160 unique experience-measuring instruments to measure 120 unique experience constructs. We found that the research landscape has seen a sizeable growth in the past decade, that it is affected by a relative lack of focus on the experience of staff, and that the overall corpus of collected experience measures can be organized in 4 main categories (service system related, care related, usage and adherence related, and health outcome related). In the light of the collected findings, we provided a set of 6 actionable recommendations to RPM patient and staff experience evaluators, in terms of both what to measure and how to measure it. Overall, we suggested that RPM researchers and practitioners include experience measuring as part of integrated, interdisciplinary data strategies for continuous RPM evaluation.

CONCLUSIONS

At present, there is a lack of consensus and standardization in the methods used to measure patient and staff experience in RPM, leading to a critical knowledge gap in our understanding of the impact of RPM interventions. This review offers targeted support for RPM experience evaluators by providing a structured, comprehensive overview of contemporary patient and staff experience measures and a set of practical guidelines for improving research quality and standardization in this domain.

Distinct eye movement patterns to complex scenes in Alzheimer's disease and Lewy body disease

Background

Alzheimer's disease (AD) and Lewy body disease (LBD), the two most common causes of neurodegenerative dementia with similar clinical manifestations, both show impaired visual attention and altered eye movements. However, prior studies have used structured tasks or restricted stimuli, limiting the insights into how eye movements alter and differ between AD and LBD in daily life.

Objective

We aimed to comprehensively characterize eye movements of AD and LBD patients on naturalistic complex scenes with broad categories of objects, which would provide a context closer to real-world free viewing, and to identify disease-specific patterns of altered eye movements.

Methods

We collected spontaneous viewing behaviors to 200 naturalistic complex scenes from patients with AD or LBD at the prodromal or dementia stage, as well as matched control participants. We then investigated eye movement patterns using a computational visual attention model with high-level image features of object properties and semantic information.

Results

Compared with matched controls, we identified two disease-specific altered patterns of eye movements: diminished visual exploration, which differentially correlates with cognitive impairment in AD and with motor impairment in LBD; and reduced gaze allocation to objects, attributed to a weaker attention bias toward high-level image features in AD and attributed to a greater image-center bias in LBD.

Conclusion

Our findings may help differentiate AD and LBD patients and comprehend their real-world visual behaviors to mitigate the widespread impact of impaired visual attention on daily activities.

Wearable-based accelerometer activity profile as digital biomarker of inflammation, biological age, and mortality using hierarchical clustering analysis in NHANES 2011-2014

Repeated disruptions in circadian rhythms are associated with implications for health outcomes and longevity. The utilization of wearable devices in quantifying circadian rhythm to elucidate its connection to longevity, through continuously collected data remains largely unstudied. In this work, we investigate a data-driven segmentation of the 24-h accelerometer activity profiles from wearables as a novel digital biomarker for longevity in 7,297 U.S. adults from the 2011-2014 National Health and Nutrition Examination Survey. Using hierarchical clustering, we identified five clusters and described them as follows: "High activity", "Low activity", "Mild circadian rhythm (CR) disruption", "Severe CR disruption", and "Very low activity". Young adults with extreme CR disturbance are seemingly healthy with few comorbid conditions, but in fact associated with higher white blood cell, neutrophils, and lymphocyte counts (0.05-0.07 log-unit, all p < 0.05) and accelerated biological aging (1.42 years, p < 0.001). Older adults with CR disruption are significantly associated with increased systemic inflammation indexes (0.09-0.12 log-unit, all p < 0.05), biological aging advance (1.28 years, p = 0.021), and all-cause mortality risk (HR = 1.58, p = 0.042). Our findings highlight the importance of circadian alignment on longevity across all ages and suggest that data from wearable accelerometers can help in identifying at-risk populations and personalize treatments for healthier aging.