Measured Physical Activity and 30-Day Rehospitalization in Heart Failure Patients

Waring, Thomas; Gross, Katherine; Soucier, Richard; ZuWallack, Richard

doi:10.1097/hcr.0000000000000204

Cited by 28 publications

(23 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…28 Its significance for TM in the post-discharge period is demonstrated by the finding that physical inactivity measured by step count predicts hospital readmissions after hospitalization for decompensated HF. 29 While earlier-cited previous studies used medical devices for step counting, we are the first to demonstrate the usability of build-in pedometer technology of iOS devices to assess PA in HF patients Designing meaningful outcome parameters using mobile technology under real-life conditions. In addition, the CPMP collects both self-measured physiological data and patient-reported outcomes in everyday life conditions.…”

Section: Smart Devices Provide New Patient-reported Outcome Measuresmentioning

confidence: 88%

“…The MDSC differed significantly between patients with severely (LVEF < 30%) and moderately reduced ejection 15 in good (<26), moderate (26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40)(41)(42)(43)(44)(45), and poor QoL (>45)], the daily walking activity was higher as well ( Figure 3B).…”

Section: Device-related Measurement Of Stepsmentioning

confidence: 96%

“…With increasing health-related QoL measured in the MLHFQ [categorized according to Behlouli et al 15 in good (<26), moderate (26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40)(41)(42)(43)(44)(45), and poor QoL (>45)], the daily walking activity was higher as well ( Figure 3B). Study participants with poor exercise performance (walking distance ≤400 m in the conventional 6MWT; peak VO 2 ≤ 14 mL/kg/min in CPET) made significantly fewer steps per day than those with values above.…”

Section: Device-related Measurement Of Stepsmentioning

confidence: 99%

See 2 more Smart Citations

Designing meaningful outcome parameters using mobile technology: a new mobile application for telemonitoring of patients with heart failure

et al. 2019

View full text Add to dashboard Cite

Aims Health data captured by commercially available smart devices may represent meaningful patient‐reported outcome measures (PROMs) in heart failure (HF) patients. The purpose of this study was to test this hypothesis by evaluating the feasibility of a new telemonitoring concept for patients following initial HF hospitalization. Methods and results We designed a cardio patient monitoring platform (CPMP) that comprised mobile iOS‐based applications for patients' smartphone/smartwatch and the equivalent application on a physicians' tablet. It allowed for safe and continuous data transmission of self‐measured physiological parameters, activity data, and patient‐reported symptoms. In a prospective feasibility trial with 692 patient days from 10 patients hospitalized for newly diagnosed HF with reduced ejection fraction (mean left ventricular ejection fraction (LVEF) 26.5 ± 9.8%), we examined the CPMP during the first 2 months following discharge (69 ± 15 observation days per patient). The mean daily step count recorded by the mobile devices emerged as a promising new PROM. Its 14 day average increased over the study period (3612 ± 3311 steps/day at study inclusion and 7069 ± 5006 steps/day at end of study; P < 0.0001). It is unique for continuously reflecting real‐life activity and correlated significantly with traditional surrogate parameters of cardiac performance including LVEF ( r = 0.44; 95% CI 0.07–0.71; P = 0.0232), 6 min walk test ( r = 0.67; 95% CI 0.38–0.84; P = 0.0002), and scores in health‐related quality of life questionnaires. Conclusions We provide the first patient monitoring platform for HF patients that relies on commercially available iOS/watchOS‐based devices. Our study suggests it is ready for implementation as a tool for recording meaningful PROMs in future HF trials and telemonitoring.

show abstract

Section: Smart Devices Provide New Patient-reported Outcome Measuresmentioning

confidence: 88%

Section: Device-related Measurement Of Stepsmentioning

confidence: 96%

Section: Device-related Measurement Of Stepsmentioning

confidence: 99%

See 1 more Smart Citation

Designing meaningful outcome parameters using mobile technology: a new mobile application for telemonitoring of patients with heart failure

et al. 2019

View full text Add to dashboard Cite

show abstract

“…Three studies considered vector magnitudes and frequency per minute (41,47,51). If a predefined threshold was reached, this was considered an active minute.…”

Section: Vector Measurementsmentioning

confidence: 99%

“…A patient was considered "active" if pre-determined thresholds of both number and magnitude of accelerometer deflections were reached. Waring et al used a triaxial accelerometer, calculating the sum of vector magnitude units (VMUs) from three planes of movement per minute (47). This study defined the threshold for higher-intensity PA to be ≥3,000 VMUs and dichotomised their patients into more active (≥60 minutes of higher-intensity activity) and less active (<60 minutes) groups.…”

Section: Vector Measurementsmentioning

confidence: 99%

Can activity monitors predict outcomes in patients with heart failure? A systematic review

Tan

Wong

Bakrania

et al. 2018

European Heart Journal - Quality of Care and Clinical Outcomes

View full text Add to dashboard Cite

show abstract

Utility of single‐item questions to assess physical inactivity in patients with chronic heart failure

et al. 2020

View full text Add to dashboard Cite

Aim The purpose of this study was to explore the utility of two single-item self-report (SR) questions to assess physical inactivity in patients with heart failure (HF). Methods and results This is a cross-sectional study using data from 106 patients with HF equipped with accelerometers for 1 week each. Two SR items relating to physical activity were also collected. Correlations between accelerometer activity counts and the SR items were analysed. Patients were classified as physically active or inactive on the basis of accelerometer counts, and the SR items were used to try to predict that classification. Finally, patients were classified as having high self-reported physical activity or low self-reported physical activity, on the basis of the SR items, and the resulting groups were analysed for differences in actual physical activity. There were significant but weak correlations between the SR items and accelerometer counts: ρ = 0.24, P = 0.016 for SR1 and ρ = 0.21, P = 0.033 for SR2. Using SR items to predict whether a patient was physically active or inactive produced an area under the curve of 0.62 for SR1, with a specificity of 92% and a sensitivity of 30%. When dividing patients into groups on the basis of SR1, there was a significant difference of 1583 steps per day, or 49% more steps in the high self-reported physical activity group (P < 0.001). Conclusions There might be utility in the single SR question for high-specificity screening of large populations to identify physically inactive patients in order to assign therapeutic interventions efficiently where resources are limited.

show abstract

Measured Physical Activity and 30-Day Rehospitalization in Heart Failure Patients

Abstract: Physical inactivity is related to 30-day all-cause readmissions for heart failure. Further studies are necessary to assess causality and to determine whether treatments directed at increasing physical activity could reduce readmission rate.

Cited by 28 publications

References 19 publications

Designing meaningful outcome parameters using mobile technology: a new mobile application for telemonitoring of patients with heart failure

Designing meaningful outcome parameters using mobile technology: a new mobile application for telemonitoring of patients with heart failure

Can activity monitors predict outcomes in patients with heart failure? A systematic review

Utility of single‐item questions to assess physical inactivity in patients with chronic heart failure

Contact Info

Product

Resources

About