Analyzing Vital Sign Variability in Remote Monitoring as a Predictor of 31-Day Heart Failure Readmission: A...

Area of Science:

• Cardiology
• Medical Informatics
• Digital Health

Background:

• Heart failure (HF) is a leading cause of hospital readmissions.
• Remote patient monitoring (RPM) is used for post-discharge care, but its effectiveness and the role of vital sign variability are not fully understood.
• Early identification of patients at high risk for readmission is crucial.

Purpose of the Study:

• To evaluate the association between physiologic variability and patient engagement during RPM and 31-day heart failure readmissions.
• To determine the prognostic value of day-to-day vital sign variability in patients with HF post-discharge.

Main Methods:

• A retrospective cohort study of 213 patients with HF undergoing post-discharge RPM.
• Daily recording of weight, blood pressure, and heart rate for up to 31 days.
• Calculation of vital sign variability metrics and analysis using adjusted logistic regression models.

Main Results:

• Pulse variability was significantly associated with 31-day HF readmission (OR 9.91).
• Total vital sign variability also predicted readmission (OR 6.93).
• Higher escalation outreach rates (OR 15.46) and brain natriuretic peptide levels were associated with readmission.

Conclusions:

• Variability in physiologic measures, particularly pulse variability, captured via RPM can indicate early decompensation.
• Dynamic RPM patterns offer potential value in assessing post-discharge risk for heart failure patients.
• RPM data, focusing on variability, may enhance prediction of early hospital readmissions.