Cerebrovascular Autoregulation in Preterm Infants During and After Surgical Ligation of the Ductus Arteriosus, a Comparison Between Two Surgical Approaches

Objective: During ligation of the ductus arteriosus, cerebrovascular autoregulation (CAR) may deteriorate. It is unknown whether different surgical approaches affect changes in CAR differently. The objective of this study was to compare the potential change in CAR in preterm infants during and after ligation comparing two surgical approaches: sternotomy and posterolateral thoracotomy. Design: This was an observational cohort pilot study. Setting: Level III NICU. Patients: Preterm infants (GA < 32 weeks) requiring ductal ligation were eligible for inclusion. Interventions: Halfway the study period, our standard surgical approach changed from a posterolateral thoracotomy to sternotomy. We analyzed dynamic CAR, using an index of autoregulation (COx) correlating cerebral tissue oxygen saturation and invasive arterial blood pressure measurements, before, during, and after ligation, in relation to the two approaches. Measurements and Main Results: Of nine infants, four were approached by thoracotomy and five by sternotomy. Median GA was 26 (range: 24.9–27.9) weeks, median birth weight (BW) was 800 (640–960) grams, and median post-natal age (PNA) was 18 (15–30) days, without differences between groups. COx worsened significantly more during and after thoracotomy from baseline (Δρ from baseline: during surgery: Δ + 0.32, at 4 h: Δ + 0.36, at 8 h: Δ + 0.32, at 12 h: Δ + 0.31) as compared with sternotomy patients (Δρ from baseline: during surgery: Δ + 0.20, at 4 h: Δ + 0.05, at 8 h: Δ + 0.15, at 12 h: Δ + 0.11) (F = 6.50; p = 0.038). Conclusions: In preterm infants, CAR reduced significantly during and up to 12 h after ductal ligation in all infants, but more evident during and after posterolateral thoracotomy as compared with sternotomy. These results need to be confirmed in a larger population

Cerebral Autoregulation Assessment Using the Near Infrared Spectroscopy 'NIRS-Only' High Frequency Methodology in Critically Ill Patients:A Prospective Cross-Sectional Study

Impairments in cerebral autoregulation (CA) are related to poor clinical outcome. Near infrared spectroscopy (NIRS) is a non-invasive technique applied to estimate CA. Our general purpose was to study the clinical feasibility of a previously published 'NIRS-only' CA methodology in a critically ill intensive care unit (ICU) population and determine its relationship with clinical outcome. Bilateral NIRS measurements were performed for 1-2 h. Data segments of ten-minutes were used to calculate transfer function analyses (TFA) CA estimates between high frequency oxyhemoglobin (oxyHb) and deoxyhemoglobin (deoxyHb) signals. The phase shift was corrected for serial time shifts. Criteria were defined to select TFA phase plot segments (segments) with 'high-pass filter' characteristics. In 54 patients, 490 out of 729 segments were automatically selected (67%). In 34 primary neurology patients the median (q1-q3) low frequency (LF) phase shift was higher in 19 survivors compared to 15 non-survivors (13° (6.3-35) versus 0.83° (-2.8-13), p = 0.0167). CA estimation using the NIRS-only methodology seems feasible in an ICU population using segment selection for more robust and consistent CA estimations. The 'NIRS-only' methodology needs further validation, but has the advantage of being non-invasive without the need for arterial blood pressure monitoring

Feasibility of individualised severe traumatic brain injury management using an automated assessment of optimal cerebral perfusion pressure: the COGiTATE phase II study protocol.

INTRODUCTION: Individualising therapy is an important challenge for intensive care of patients with severe traumatic brain injury (TBI). Targeting a cerebral perfusion pressure (CPP) tailored to optimise cerebrovascular autoregulation has been suggested as an attractive strategy on the basis of a large body of retrospective observational data. The objective of this study is to prospectively assess the feasibility and safety of such a strategy compared with fixed thresholds which is the current standard of care from international consensus guidelines. METHODS AND ANALYSIS: CPPOpt Guided Therapy: Assessment of Target Effectiveness (COGiTATE) is a prospective, multicentre, non-blinded randomised, controlled trial coordinated from Maastricht University Medical Center, Maastricht (The Netherlands). The other original participating centres are Cambridge University NHS Foundation Trust, Cambridge (UK), and University Hospitals Leuven, Leuven (Belgium). Adult severe TBI patients requiring intracranial pressure monitoring are randomised within the first 24 hours of admission in neurocritical care unit. For the control arm, the CPP target is the Brain Trauma Foundation guidelines target (60-70 mm Hg); for the intervention group an automated CPP target is provided as the CPP at which the patient's cerebrovascular reactivity is best preserved (CPPopt). For a maximum of 5 days, attending clinicians review the CPP target 4-hourly. The main hypothesis of COGiTATE are: (1) in the intervention group the percentage of the monitored time with measured CPP within a range of 5 mm Hg above or below CPPopt will reach 36%; (2) the difference in between groups in daily therapy intensity level score will be lower or equal to 3. ETHICS AND DISSEMINATION: Ethical approval has been obtained for each participating centre. The results will be presented at international scientific conferences and in peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT02982122

Measuring cerebrovascular autoregulation in preterm infants using near-infrared spectroscopy:An overview of the literature

Introduction: The preterm born infant's ability to regulate its cerebral blood flow (CBF) is crucial in preventing secondary ischemic and hemorrhagic damage in the developing brain. The relationship between arterial blood pressure (ABP) and CBF estimates, such as regional cerebral oxygenation as measured by near-infrared spectroscopy (NIRS), is an attractive option for continuous non-invasive assessment of cerebrovascular autoregulation.Areas covered: The authors performed a literature search to provide an overview of the current literature on various current clinical practices and methods to measure cerebrovascular autoregulation in the preterm infant by NIRS. The authors focused on various aspects: Characteristics of patient cohorts, surrogate measures for cerebral perfusion pressure, NIRS devices and their accompanying parameters, definitions for impaired cerebrovascular autoregulation, methods of measurements and clinical implications.Expert commentary: Autoregulation research in preterm infants has reported many methods for measuring autoregulation using different mathematical models, signal processing and data requirements. At present, it remains unclear which NIRS signals and algorithms should be used that result in the most accurate and clinically relevant assessment of cerebrovascular autoregulation. Future studies should focus on optimizing strategies for cerebrovascular autoregulation assessment in preterm infants in order to develop autoregulation-based cerebral perfusion treatment strategies

Near-Infrared Spectroscopy-Derived Dynamic Cerebral Autoregulation in Experimental Human Endotoxemia-An Exploratory Study

Cerebral perfusion may be altered in sepsis patients. However, there are conflicting findings on cerebral autoregulation (CA) in healthy participants undergoing the experimental endotoxemia protocol, a proxy for systemic inflammation in sepsis. In the current study, a newly developed near-infrared spectroscopy (NIRS)-based CA index is investigated in an endotoxemia study population, together with an index of focal cerebral oxygenation. Methods: Continuous-wave NIRS data were obtained from 11 healthy participants receiving a continuous infusion of bacterial endotoxin for 3 h (ClinicalTrials.gov NCT02922673) under extensive physiological monitoring. Oxygenated–deoxygenated hemoglobin phase differences in the (very)low frequency (VLF/LF) bands and the Tissue Saturation Index (TSI) were calculated at baseline, during systemic inflammation, and at the end of the experiment 7 h after the initiation of endotoxin administration. Results: The median (inter-quartile range) LF phase difference was 16.2° (3.0–52.6°) at baseline and decreased to 3.9° (2.0–8.8°) at systemic inflammation (p = 0.03). The LF phase difference increased from systemic inflammation to 27.6° (12.7–67.5°) at the end of the experiment (p = 0.005). No significant changes in VLF phase difference were observed. The TSI (mean ± SD) increased from 63.7 ± 3.4% at baseline to 66.5 ± 2.8% during systemic inflammation (p = 0.03) and remained higher at the end of the experiment (67.1 ± 4.2%, p = 0.04). Further analysis did not reveal a major influence of changes in several covariates such as blood pressure, heart rate, PaCO(2), and temperature, although some degree of interaction could not be excluded. Discussion: A reversible decrease in NIRS-derived cerebral autoregulation phase difference was seen after endotoxin infusion, with a small, sustained increase in TSI. These findings suggest that endotoxin administration in healthy participants reversibly impairs CA, accompanied by sustained microvascular vasodilation

Enhanced Visualization of Optimal Cerebral Perfusion Pressure Over Time to Support Clinical Decision Making.

OBJECTIVE: Cerebrovascular reactivity can provide a continuously updated individualized target for management of cerebral perfusion pressure, termed optimal cerebral perfusion pressure. The objective of this project was to find a way of improving the optimal cerebral perfusion pressure methodology by introducing a new visualization method. DATA SOURCES: Four severe traumatic brain injury patients with intracranial pressure monitoring. DATA EXTRACTION: Data were collected and pre-processed using ICM+ software. DATA SYNTHESIS: Sequential optimal cerebral perfusion pressure curves were used to create a color-coded maps of autoregulation - cerebral perfusion pressure relationship evolution over time. CONCLUSIONS: The visualization method addresses some of the main drawbacks of the original methodology and might bring the potential for its clinical application closer.Marcel Aries received an unrestricted grant from the Dutch Society of Intensive Care. Joseph Donnelly is supported by a Woolf Fisher Trust Scholarship. The software for brain monitoring ICM+® (www.neurosurg.cam.ac.uk/imcplus) is licensed by the University of Cambridge (Cambridge Enterprise).This is the author accepted manuscript. It is currently embargoed pending publication by Wolters Kluwer

Improving Prediction of Favourable Outcome After 6 Months in Patients with Severe Traumatic Brain Injury Using Physiological Cerebral Parameters in a Multivariable Logistic Regression Model.

BACKGROUND/OBJECTIVE: Current severe traumatic brain injury (TBI) outcome prediction models calculate the chance of unfavourable outcome after 6 months based on parameters measured at admission. We aimed to improve current models with the addition of continuously measured neuromonitoring data within the first 24 h after intensive care unit neuromonitoring. METHODS: Forty-five severe TBI patients with intracranial pressure/cerebral perfusion pressure monitoring from two teaching hospitals covering the period May 2012 to January 2019 were analysed. Fourteen high-frequency physiological parameters were selected over multiple time periods after the start of neuromonitoring (0-6 h, 0-12 h, 0-18 h, 0-24 h). Besides systemic physiological parameters and extended Corticosteroid Randomisation after Significant Head Injury (CRASH) score, we added estimates of (dynamic) cerebral volume, cerebral compliance and cerebrovascular pressure reactivity indices to the model. A logistic regression model was trained for each time period on selected parameters to predict outcome after 6 months. The parameters were selected using forward feature selection. Each model was validated by leave-one-out cross-validation. RESULTS: A logistic regression model using CRASH as the sole parameter resulted in an area under the curve (AUC) of 0.76. For each time period, an increased AUC was found using up to 5 additional parameters. The highest AUC (0.90) was found for the 0-6 h period using 5 parameters that describe mean arterial blood pressure and physiological cerebral indices. CONCLUSIONS: Current TBI outcome prediction models can be improved by the addition of neuromonitoring bedside parameters measured continuously within the first 24 h after the start of neuromonitoring. As these factors might be modifiable by treatment during the admission, testing in a larger (multicenter) data set is warranted

Changes in cerebral oxygenation and cerebral blood flow during hemodialysis - A simultaneous near-infrared spectroscopy and positron emission tomography study

Near-infrared spectroscopy (NIRS) is used to monitor cerebral tissue oxygenation (rSO2) depending on cerebral blood flow (CBF), cerebral blood volume and blood oxygen content. We explored whether NIRS might be a more easy applicable proxy to [15O]H2O positron emission tomography (PET) for detecting CBF changes during hemodialysis. Furthermore, we compared potential determinants of rSO2 and CBF. In 12 patients aged ≥ 65 years, NIRS and PET were performed simultaneously: before (T1), early after start (T2), and at the end of hemodialysis (T3). Between T1 and T3, the relative change in frontal rSO2 (ΔrSO2) was -8 ± 9% ( P = 0.001) and -5 ± 11% ( P = 0.08), whereas the relative change in frontal gray matter CBF (ΔCBF) was -11 ± 18% ( P = 0.009) and -12 ± 16% ( P = 0.007) for the left and right hemisphere, respectively. ΔrSO2 and ΔCBF were weakly correlated for the left (ρ 0.31, P = 0.4), and moderately correlated for the right (ρ 0.69, P = 0.03) hemisphere. The Bland-Altman plot suggested underestimation of ΔCBF by NIRS. Divergent associations of pH, pCO2 and arterial oxygen content with rSO2 were found compared to corresponding associations with CBF. In conclusion, NIRS could be a proxy to PET to detect intradialytic CBF changes, although NIRS and PET capture different physiological parameters of the brain