Background: Targeting a cerebral perfusion pressure optimal for cerebral autoregulation (CPPopt) has been gaining more attention to prevent secondary damage after acute neurological injury. Brain tissue oxygenation (PbtO ₂ ) can identify insufficient cerebral blood flow and secondary brain injury. Defining the relationship between CPPopt and PbtO ₂ after aneurysmal subarachnoid hemorrhage may result in (1) mechanistic insights into whether and how CPPopt-based strategies might be beneficial and (2) establishing support for the use of PbtO ₂ as an adjunctive monitor for adequate or optimal local perfusion. Methods: We performed a retrospective analysis of a prospectively collected 2-center dataset of patients with aneurysmal subarachnoid hemorrhage with or without later diagnosis of delayed cerebral ischemia (DCI). CPPopt was calculated as the cerebral perfusion pressure (CPP) value corresponding to the lowest pressure reactivity index (moving correlation coefficient of mean arterial and intracranial pressure). The relationship of (hourly) deltaCPP (CPP−CPPopt) and PbtO ₂ was investigated using natural spline regression analysis. Data after DCI diagnosis were excluded. Brain tissue hypoxia was defined as PbtO ₂ <20 mmHg. Results: One hundred thirty-one patients were included with a median of 44.0 (interquartile range, 20.8–78.3) hourly CPPopt/PbtO2 datapoints. The regression plot revealed a nonlinear relationship between PbtO ₂ and deltaCPP ( P <0.001) with PbtO ₂ decrease with deltaCPP <0 mmHg and stable PbtO ₂ with deltaCPP ≥0mmHg, although there was substantial individual variation. Brain tissue hypoxia (34.6% of all measurements) was more frequent with deltaCPP <0 mmHg. These dynamics were similar in patients with or without DCI. Conclusions: We found a nonlinear relationship between PbtO ₂ and deviation of patients’ CPP from CPPopt in aneurysmal subarachnoid hemorrhage patients in the pre-DCI period. CPP values below calculated CPPopt were associated with lower PbtO ₂ . Nevertheless, the nature of PbtO ₂ measurements is complex, and the variability is high. Combined multimodality monitoring with CPP/CPPopt and PbtO ₂ should be recommended to redefine individual pressure targets (CPP/CPPopt) and retain the option to detect local perfusion deficits during DCI (PbtO ₂ ), which cannot be fulfilled by both measurements interchangeably.

Background and Purpose: Delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage negatively impacts long-term recovery but is often detected too late to prevent damage. We aim to develop hourly risk scores using routinely collected clinical data to detect DCI. Methods: A DCI classification model was trained using vital sign measurements (heart rate, blood pressure, respiratory rate, and oxygen saturation) and demographics routinely collected for clinical care. Twenty-two time-varying physiological measures were computed including mean, SD, and cross-correlation of heart rate time series with each of the other vitals. Classification was achieved using an ensemble approach with L2-regularized logistic regression, random forest, and support vector machines models. Classifier performance was determined by area under the receiver operating characteristic curves and confusion matrices. Hourly DCI risk scores were generated as the posterior probability at time t using the Ensemble classifier on cohorts recruited at 2 external institutions (n=38 and 40). Results: Three hundred ten patients were included in the training model (median, 54 years old [interquartile range, 45–65]; 80.2% women, 28.4% Hunt and Hess scale 4–5, 38.7% Modified Fisher Scale 3–4); 101 (33%) developed DCI with a median onset day 6 (interquartile range, 5–8). Classification accuracy before DCI onset was 0.83 (interquartile range, 0.76–0.83) area under the receiver operating characteristic curve. Risk scores applied to external institution datasets correctly predicted 64% and 91% of DCI events as early as 12 hours before clinical detection, with 2.7 and 1.6 true alerts for every false alert. Conclusions: An hourly risk score for DCI derived from routine vital signs may have the potential to alert clinicians to DCI, which could reduce neurological injury.