Algorithmic derivation of optimal CPP, MAP, and BIS targets from cerebrovascular reactivity indices: A systematic scoping review

Autoregulation-guided physiological targeting, using metrics such as optimal cerebral perfusion pressure (CPPopt), optimal mean arterial pressure (MAPopt), and optimal bispectral index (BISopt), has emerged as a promising strategy for improving patient outcomes in critical care and neuromonitoring. These targets, derived from the continuous assessment of cerebrovascular reactivity (CVR) indices, are increasingly being studied for their potential to individualize patient management. This review aimed to identify and characterize existing literature detailing the derivation algorithms of CPPopt, MAPopt, and BISopt, focusing on key computational parameters, methodological consistencies, and quantitative algorithm performance metrics. Following PRISMA-ScR guidelines, studies were included if they reported algorithmic details of CPPopt, MAPopt, or BISopt derivation and provided at least six of seven core technical parameters (raw data sampling frequency, CVR index preprocessing, binning, data window size for optimality curve fitting, curve fitting method, update frequency, and yield), which were extracted during data extraction. Additional data captured included patient cohort characteristics, study objective, and CVR assessment technology. 20 studies met inclusion criteria: 13 described CPPopt, 6 described MAPopt, and 2 described BISopt derivation algorithms. CPPopt algorithms predominantly used pressure reactivity index (PRx) as the CVR index, 5 mmHg binning, and second-order polynomial curve fitting, with frequent minute-by-minute updates and multi-window averaging. MAPopt algorithms primarily used near-infrared spectroscopy (NIRS)-derived indices such as hemoglobin volume index and cerebral oximetry index (COx), while BISopt studies combined electroencephalogram (EEG) monitoring with PRx or COx. Algorithmic yield ranged from 45.6% to 100%, depending on preprocessing strategy and curve-fitting quality. Based on the existing literature, we found CPPopt derivation remains the most mature and widely studied algorithm, while MAPopt and BISopt are emerging modalities with growing interest. Despite high feasibility across studies, significant methodological variability limits the comparability of found algorithms. Standardized algorithm reporting is needed to support widespread clinical adoption of autoregulation-guided physiological targets.