Smartphone-Based Prediction Model for Postoperative Cardiac Surgery Outcomes Using Preoperative Gait and Posture...

Area of Science:

• Gerontology
• Biomedical Engineering
• Cardiology

Background:

• Gait speed assessment is crucial for predicting mortality and morbidity in elderly patients post-cardiac surgery.
• Current clinical assessments may not fully capture the nuances of frailty and its impact on surgical outcomes.

Purpose of the Study:

• To identify relationships between preoperative gait and postural stability using a mobile phone device and postoperative outcomes in older adults undergoing cardiac surgery.
• To enhance clinical prediction of mortality and morbidity in this patient population.

Main Methods:

• Prospective study of 16 ambulatory patients over 70 years old with cardiovascular disease undergoing non-emergent cardiac surgery.
• Preoperative assessment using a mobile phone app ('Lockhart Monitor') to measure gait speed (5-m walk) and postural stability (30-s stand still).
• Patients classified as frail (gait speed ≤0.833 m/s) or non-frail based on Society of Thoracic Surgeons guidelines; physicians and patients blinded to results.

Main Results:

• A subset of smartphone-derived gait and posture measures effectively differentiated between frail and non-frail patients.
• A regression model utilizing these smartphone measures demonstrated predictive capability for adverse postoperative outcomes in cardiovascular disease patients.

Conclusions:

• Mobile technology offers a feasible and noninvasive method for assessing gait and stability in clinical settings.
• The proposed regression model, based on smartphone data, can predict adverse postoperative outcomes, aiding in risk stratification for older adults undergoing cardiac surgery.