Morning surge in blood pressure using a random-effects multiple-component cosinor model.

Area of Science:

• Cardiovascular Physiology
• Biostatistics
• Chronobiology

Background:

• Blood pressure (BP) exhibits daily fluctuations, a key circadian rhythm.
• The morning BP surge is linked to cardiovascular events, but accurate quantification is challenging.

Purpose of the Study:

• To develop and validate a novel method for quantifying the morning BP surge.
• To extend the single cosinor approach to a multiple-component cosinor random-effects model for BP analysis.

Main Methods:

• Utilized a 2-component cosinor random-effects model to analyze 24-hour ambulatory BP data.
• Calculated morning BP surge by deriving the model fit.
• Compared the model's performance against functional principal component analysis (FPCA) using b-splines.

Main Results:

• The 2-component model significantly improved fit over a single model and showed comparable fit to a b-spline FPCA model.
• The average maximum slope (a measure of surge) was estimated at 2.857 mmHg/30 min.
• Quantified the between-individual standard deviation in maximum slopes as 1.02 mmHg/30 min.

Conclusions:

• A novel cosinor-based approach effectively quantifies morning BP surge and inter-individual variability.
• This method provides a valuable tool for assessing cardiovascular risk associated with BP patterns.