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Published on: July 24, 2013
Inertial Sensor-Based Variables Are Indicators of Frailty and Adverse Post-Operative Outcomes in Cardiovascular
Rahul Soangra1, Thurmon E Lockhart2
1Department of Physical Therapy, Crean College of Health and Behavioral Sciences, Chapman University, Orange, CA 92866, USA. soangra@chapman.edu.
Insights
Gait speed and movement variability measured by smartphone inertial sensors can identify frail cardiovascular disease (CVD) patients at risk for adverse post-operative outcomes. This objective assessment aids in predicting surgical risks for elderly patients.
Area of Science:
- Biomedical Engineering
- Geriatrics
- Cardiology
Background:
- Cardiovascular disease (CVD) patients are at increased risk of frailty, morbidity, and mortality post-surgery.
- The Society of Thoracic Surgeons (STS) suggests gait speed as a predictor of post-operative outcomes in elderly CVD patients, though this requires further validation.
- Frailty in CVD patients is linked to an increased risk of falls and adverse surgical outcomes.
Purpose of the Study:
- To investigate the utility of inertial sensor-based movement variability characteristics in identifying CVD patients prone to adverse post-operative outcomes.
- To establish relationships between gait, postural predictors, and post-operative adverse outcomes in elderly CVD patients.
- To explore the potential of smartphone-embedded inertial sensors for objective patient assessment in clinical settings.
Main Methods:
- Recruited sixteen elderly CVD patients scheduled for cardiac surgery.
- Classified patients into frail (gait speed ≤ 0.833 m/s) and non-frail (gait speed > 0.833 m/s) groups based on STS guidelines.
- Utilized smartphone inertial sensors to measure walking velocity, Center of Pressure (COP) parameters, and nonlinear variability measures (sample entropy).
Main Results:
- Frail patients exhibited significantly lower walking velocity compared to non-frail patients (p < 0.01).
- Frail patients showed significantly higher COP radius (p < 0.01), COP Area (p < 0.01), COP path length (p < 0.05), and mean COP velocity (p < 0.05).
- Nonlinear variability measures, such as sample entropy, were significantly lower in frail participants in anterior-posterior and resultant sway directions (p < 0.01).
Conclusions:
- Inertial sensor-based gait and postural variability parameters can effectively identify frail CVD patients at risk for adverse post-operative outcomes.
- Smartphone-based assessments offer a quick, objective method for evaluating elderly CVD patients in perioperative care.
- These findings support the development of smartphone-based clinical decision support systems for perioperative risk assessment.
Abstract:
Cardiovascular disease (CVD) patients with intrinsic cardiac cause for falling have been found to be frail and submissive to morbidity and mortality as post-operative outcomes. In these older CVD patients, gait speed is conjectured by the Society of Thoracic Surgeons (STS) as an independent predictor of post-operative morbidity and mortality. However, this guideline by STS has not been studied adequately with a large sample size; rather it is based largely on expert opinions of cardiac surgeons and researchers. Although one's gait speed is not completely associated with one's risk of falls, gait speed is a quick robust measure to classify frail/non-frail CVD patients and undoubtedly frail individuals are more prone to falls. Thus, this study examines the effects of inertial sensor-based quick movement variability characteristics in identifying CVD patients likely to have an adverse post-operative outcome. This study establishes a relationship with gait and postural predictor variables with patient's post-operative adverse outcomes. Accordingly, inertial sensors embedded inside smartphones are indispensable for the assessment of elderly patients in clinical environments and may be necessary for quick objective assessment. Sixteen elderly CVD patients (Age 76.1 ± 3.6 years) who were scheduled for cardiac surgery the next day were recruited for this study. Based on STS recommendation guidelines, eight of the CVD patients were classified as frail (prone to adverse outcomes with gait speed ≤ 0.833 m/s) and the other eight patients as non-frail (gait speed > 0.833 m/s). Smartphone-derived walking velocity was found to be significantly lower in frail patients than that in non-frail patients (p < 0.01). Mean Center of Pressure (COP) radius (p < 0.01), COP Area (p < 0.01), COP path length (p < 0.05) and mean COP velocity (p < 0.05) were found to be significantly higher in frail patients than that in the non-frail patient group. Nonlinear variability measures such as sample entropy were significantly lower in frail participants in anterior-posterior (p < 0.01) and resultant sway direction (p < 0.01) than in the non-frail group. This study identified numerous postural and movement variability parameters that offer insights into predictive inertial sensor-based variables and post-operative adverse outcomes among CVD patients. In future, smartphone-based clinical measurement systems could serve as a clinical decision support system for assessing patients quickly in the perioperative period.
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