Mean flow index (Mxa) algorithm option can influence cerebral autoregulation classification in critically ill septic...

Area of Science:

• Neuroscience
• Biomedical Engineering
• Critical Care Medicine

Background:

• Dynamic cerebral autoregulation (DCA) is crucial for maintaining stable cerebral blood flow.
• The Mean flow index (Mxa) is a common method for assessing DCA.
• Mxa calculation relies on specific signal processing parameters like block duration, overlap, and epoch length.

Purpose of the Study:

• To evaluate the reproducibility of Mxa calculations.
• To investigate the impact of varying signal processing parameters (block, overlap, epoch) on Mxa reproducibility.
• To assess Mxa calculation consistency in septic shock patients.

Main Methods:

• Retrospective analysis of 50 transcranial Doppler recordings from septic shock patients.
• Computation of Mxa using eight signal-processing strategies with varied block durations (5-10s), overlap percentages (20%, 50%, 80%), and epoch lengths (3-5min).
• Statistical comparison using repeated measures analyses, intraclass correlation coefficients (ICC), Bland-Altman plots, and polychoric correlation heatmaps.

Main Results:

• Median Mxa values ranged from 0.36 to 0.45, with no significant within-patient differences across configurations (p > 0.05).
• Excellent agreement (ICC > 0.90) was observed between Mxa calculations using the same epoch duration.
• Modest decline in agreement occurred when epoch lengths differed, but no single parameter significantly drove variability.

Conclusions:

• Mxa values demonstrate high reproducibility within patients, particularly when epoch length is consistent.
• The findings support the reliability of Mxa for assessing dynamic cerebral autoregulation.
• Flexibility in signal processing strategies is permissible, provided methodological consistency is maintained.