
==== Front
J Neurosurg Anesthesiol
J Neurosurg Anesthesiol
ANA
Journal of Neurosurgical Anesthesiology
0898-4921
1537-1921
Lippincott Williams & Wilkins Hagerstown, MD

38011867
JNA-D-23-00029
10.1097/ANA.0000000000000944
00010
3
Clinical Investigations
Impact of Intraoperative Fluctuations of Cardiac Output on Cerebrovascular Autoregulation: An Integrative Secondary Analysis of Individual-level Data
Kahl Ursula MD *u.kahl@uke.de

Krause Linda PhD †l.krause@uke.de

Amin Sabrina MD *sabrina.amin@hotmail.com

Harler Ulrich MD, PhD u.harler@uke.de
*
Beck Stefanie MD *st.beck@uke.de

Dohrmann Thorsten MD *t.dohrmann@uke.de

Mewes Caspar MD *c.mewes@uke.de

Graefen Markus MD ‡graefen@uke.de

Haese Alexander MD ‡haese@uke.de

Zöllner Christian MD *c.zoellner@uke.de

Fischer Marlene MD, PhD *§mar.fischer@uke.de

* Departments of Anesthesiology
§ Intensive Care Medicine
† Institute of Medical Biometry and Epidemiology
‡ Martini-Klinik, Prostate Cancer Center, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
Address correspondence to: Marlene Fischer, MD, PhD. E-mail: mar.fischer@uke.de.
10 2024
27 11 2023
36 4 334340
18 2 2023
9 10 2023
Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc.
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0/

Background:

Intraoperative impairment of cerebral autoregulation (CA) has been associated with perioperative neurocognitive disorders. We investigated whether intraoperative fluctuations in cardiac index are associated with changes in CA.

Methods:

We conducted an integrative explorative secondary analysis of individual-level data from 2 prospective observational studies including patients scheduled for radical prostatectomy. We assessed cardiac index by pulse contour analysis and CA as the cerebral oxygenation index (COx) based on near-infrared spectroscopy. We analyzed (1) the cross-correlation between cardiac index and COx, (2) the correlation between the time-weighted average (TWA) of the cardiac index below 2.5 L min−1 m−2, and the TWA of COx above 0.3, and (3) the difference in areas between the cardiac index curve and the COx curve among various subgroups.

Results:

The final analysis included 155 patients. The median cardiac index was 3.16 [IQR: 2.65, 3.72] L min−1 m−2. Median COx was 0.23 [IQR: 0.12, 0.34]. (1) The median cross-correlation between cardiac index and COx was 0.230 [IQR: 0.186, 0.287]. (2) The correlation (Spearman ρ) between TWA of cardiac index below 2.5 L min−1 m−2 and TWA of COx above 0.3 was 0.095 (P=0.239). (3) Areas between the cardiac index curve and the COx curve did not differ significantly among subgroups (<65 vs. ≥65 y, P=0.903; 0 vs. ≥1 cardiovascular risk factors, P=0.518; arterial hypertension vs. none, P=0.822; open vs. robot-assisted radical prostatectomy, P=0.699).

Conclusions:

We found no meaningful association between intraoperative fluctuations in cardiac index and CA. However, it is possible that a potential association was masked by the influence of anesthesia on CA.

Key Words:

cerebrovascular autoregulation
cerebral blood flow
cardiac index
cardiac output
radical prostatectomy
noncardiac surgery
SDCT
OPEN-ACCESSTRUE
==== Body
pmcCerebral autoregulation (CA) enables the cerebral vasculature to adapt to hypoperfusion and hyperperfusion by dilation and constriction, allowing for constant cerebral blood flow (CBF) despite changes in systemic arterial blood pressure (ABP).1 This is important since the brain is highly dependent on continuous CBF to provide oxygen and nutrients owing to its proportionally high metabolic rate.2

Together with the total peripheral resistance, cardiac output is one of the main determinants of CBF.2 The interaction between cardiac output, CA, and CBF is complex. It has been hypothesized that there may be a direct relationship between cardiac output and CBF in healthy individuals, suggesting that cardiac output is distributed to the organs proportionally to the metabolic demand of the individual organ.3–5 This probably requires multiple regulating mechanisms, including CA. However, information on the relationship between cardiac index, which is defined as cardiac output related to the body surface area, and CA is scarce. Very few studies have investigated an association between changes in cardiac index and dynamic autoregulation.6,7 Importantly, no study has investigated an association between cardiac index and CA in patients during anesthesia and surgery.

The perioperative setting is particularly interesting, since the brain may be exposed to hypoperfusion or hyperperfusion during anesthesia and surgery. Cardiac index and ABP may be subject to substantial fluctuations caused by anesthetic medication, positioning, and surgical blood loss. At the same time, CA may be impaired due to the influence of anesthetic medication.8 Of note, impaired CA has been suggested to contribute to the development of perioperative neurocognitive disorders.9–11 It is thus of utmost importance to identify factors associated with impaired CA.

We aimed to investigate whether intraoperative fluctuations in cardiac index are associated with changes in CA, expressed by the cerebral oxygenation index (COx). In addition, we aimed to investigate whether there is an association between cardiac index below a predefined threshold and impaired CA. We hypothesized that changes in cardiac index would correlate with changes in the COx. In addition, we hypothesized that a cardiac index below a predefined threshold would be associated with impaired CA.

METHODS

Study Design, Setting, Participants, and Ethical Approval

We conducted a secondary analysis of individual-level data from 2 prospective observational studies. The initial studies were designed (1) to compare CA between patients in the steep head-down position, undergoing robot-assisted radical prostatectomy, and patients in the supine position, undergoing open retropubic surgery12; and (2) to examine the association between changes in oscillatory activity assessed with a 64-channel electroencephalogram and cognitive function before and after general anesthesia for radical prostatectomy.13 We enrolled patients between 2015 and 2017 in the Department of Anesthesiology, University Medical Center Hamburg-Eppendorf, Germany. We included adult male patients scheduled for elective robot-assisted or open radical prostatectomy and excluded patients with a history of any central nervous system disorder, including cerebrovascular or neurodegenerative disease, or an American Society of Anesthesiologists (ASA) physical status classification >IV. For this secondary analysis, we included all patients who had received continuous intraoperative measurements of cardiac index and CA.

On April 27, 2016, the ethics committee of the Hamburg State Chamber of Physicians approved the original studies (protocol number PV4782; September 2, 2014). The study protocols comply with the ethical standards of the 1964 Declaration of Helsinki and its later amendments. Patients gave written informed consent before any study-related procedures.

Monitoring of Cardiac Output

All patients received invasive arterial pressure monitoring with an arterial catheter in the left or right radial artery (Leader-Cath, VYGON GmbH & Co KG). In a convenience sample of patients, the arterial line was connected to the ProAQT Cardiac Index monitoring component of the PulsioFlex monitoring concept (ProAQT Cardiac Index monitoring, Getinge AB). The cardiac index was determined based on the patients’ body surface area and pulse contour analysis of the arterial pressure curve without calibration with a reference cardiac output. Cardiac index monitoring was limited by device availability in the operation room.

Monitoring of Cerebral Autoregulation

The intraoperative monitoring of CA has been described previously.10,12,14 We measured CA continuously based on the time-correlation method.1,15 The COx was calculated as a moving linear correlation of ABP and regional cerebral oxygenation (rSO2) values. It was computed based on a sliding 300-second window, updated every 10 seconds (ICM+, Cambridge Enterprise).

Cerebral oxygenation was measured noninvasively with near-infrared spectroscopy (INVOS 5100 Cerebral Oximeter, Medtronic plc, Minneapolis, MN, U.S.). We placed the near-infrared spectroscopy optode on the left side of the patient’s forehead. If the left side was not available, optodes were placed on the right side.

Anesthesiologic Management

All patients received general anesthesia with endotracheal intubation and mechanical ventilation. For anesthesia induction, we used opioid-based analgesia with sufentanil (0.3 to 1.0 μg/kg), followed by propofol (1.5 to 2.5 mg/kg) for sedation and rocuronium (0.5 to 0.6 mg/kg) for muscle relaxation. For anesthesia maintenance, we used the volatile anesthetic sevoflurane with a targeted age-adjusted minimal alveolar concentration of 1.0 and repeated bolus injections of sufentanil for intraoperative analgesia. Anesthesia depth was monitored targeting a bispectral index of 30 to 40. We administered continuous infusions of crystalloid fluids and norepinephrine to maintain mean arterial pressure above 65 mm Hg. The tidal volume was set at 6 to 8 mL/kg of the patient’s ideal bodyweight. The respiratory rate was adjusted to maintain the end-tidal carbon dioxide between 32 and 42 mm Hg.

Data Collection and Statistical Analysis

Information on medical history and pre-existing medication were obtained during preanesthesia visits. In addition, we retrieved data on perioperative medication, anesthesiologic, and surgical management from anesthesia protocols.

The 2 parameters, cardiac index and COx, were assessed using 2 different monitors with nonsynchronized time stamps. To ensure alignment between both time series, we analyzed the ABP measurements produced by each monitor using cross-correlation. We defined ABP values as artifacts, if systolic blood pressure was below 40 or above 300 mm Hg, or if diastolic blood pressure was below 30 or above 150 mm Hg.16 Values identified as artifacts and their corresponding cardiac index and COx values were imputed using linear interpolation for time-series data (package “imputeTS” version 3.2).17 We plotted all COx and cardiac index curves and visually screened them for plausibility. The relationship between synchronized, artifact-corrected cardiac index and COx was analyzed between the time of incision and the beginning of emergence from anesthesia. Impaired CA was defined as a positive correlation between rSO2 and mean arterial pressure, exceeding a COx of 0.3.18 For sensitivity analysis 1, impaired CA was defined as a COx exceeding 0.0. A cardiac index below 2.5 L min−1 m−2 was defined as pathologic.19 For sensitivity analysis 2, we used a cardiac index of 1.8 L/min/m2 as the lower threshold.

We used 3 different approaches to investigate the relationship between intraoperative cardiac index and CA.We calculated cross-correlations between the cardiac index and the COx. We investigated potential time lags of up to 400 minutes. Cross-correlation is an extension to “normal” standard correlation that takes into account a potential shift in time between the start of both time series. This potential shift is called a “time lag.” When a cross-correlation is computed, a range of time lags is used, a lag of 0—that is, no shift between the curves—represents one of the time lags used.

We analyzed the correlation between the time-weighted average (TWA) of cardiac index below the pathologic threshold and the TWA of COx above the pathologic threshold. The TWA was calculated by dividing the area under or above the predefined thresholds by the total time of interest (time of incision until the beginning of anesthesia emergence). The area under or above thresholds was approximated using the rectangular formula. Correlations were quantified using Spearman ρ statistic and corresponding CIs were calculated using 1000 bootstrap resamples (R package “RVAideMemoire” version 0.9-81-2).20

We compared the area between the synchronized cardiac index curve and the COx curve in different subgroups (patients aged <65 vs. ≥65 y, patients undergoing open radical prostatectomy vs. robot-assisted radical prostatectomy, patients without cardiovascular risk factors vs. at least 1 cardiovascular risk factor, and patients with normotensive blood pressure vs. a history of arterial hypertension) using Wilcoxon rank sum tests, Kruskal-Wallis rank sum tests or χ2 tests. To calculate the area between the curves, both curves were first centered around zero per individual by subtracting the mean value of that individual for the respective index.

We used R version 4.2.1 and SPSS Statistics 24 (IBM Deutschland GmbH) for statistical analyses and creation of figures. Since this is an exploratory study, P values are only provided as descriptive summary measures and should not be interpreted as the results of confirmatory hypothesis testing. This manuscript adheres to the STROBE reporting guidelines for observational studies.

RESULTS

Study Population

Cardiac index and CA were assessed in 159 patients during surgery and 155 patients were included in the final analysis (Fig. 1). Baseline characteristics and variables related to surgery and anesthesia are listed in Table 1.

FIGURE 1 Flow of participants throughout the study. aBeck et al12; bLendner et al.13 n indicates number.

TABLE 1 Patient Characteristics, Perioperative Management, Intraoperative Monitoring of Cardiac Index, and Cerebral Autoregulation

Age	
 All patients (y)	63 [59, 67]	
  <65	84 (54)	
  ≥65	71 (46)	
ASA physical status score	
 ASA I	32 (21)	
 ASA II	99 (64)	
 ASA III	24 (15)	
Body mass index (kg/m2)	26.3 [24.3, 29.4]	
Obesity	38 (25)	
Cardiovascular risk factors	
 Arterial hypertension	78 (50)	
 Dyslipoproteinemia	41 (26)	
 Smoker	20 (13)	
 Diabetes mellitus	8 (5)	
Type of surgery	
 Robot-assisted RP	82 (53)	
 Open RP	73 (47)	
Duration of surgery (min)	180 [155, 210]	
Estimated Blood loss (mL)	500 [250, 800]	
Sufentanil (µg)	95 [85, 110]	
Crystalloid fluids (mL)	2500 [2000, 3000]	
Colloid fluids (mL)	0 [0, 500]	
Duration of measurement (min)	88 [44, 134]	
Cardiac index monitoring	
 Cardiac index (L/min/m2)	3.16 [2.65, 3.72]	
 Time with cardiac index below 2.5 (%)	2.06 [0.59, 14.20]	
 Time-weighted average of cardiac index below 2.5	0.02 [0.00, 0.17]	
 Time with cardiac index below 1.8 (%)	0.70 [0.26, 1.94]	
 Time-weighted average of cardiac index below 1.8	0.00 [0.00, 0.01]	
CA monitoring	
 COx	0.23 [0.12, 0.34]	
 Time with COx above 0.3 (%)	43.78 [35.30, 53.19]	
 Time with COx above 0.0 (%)	67.68 [58.92, 75.14]	
 Time-weighted average of COx above 0.3	0.12 [0.09, 0.17]	
 Time-weighted average of COx above 0.0	0.29 [0.24, 0.36]	
Data are shown as number (%) or median [interquartile range].

ASA indicates American Society of Anesthesiologists, CA, cerebral autoregulation; COx, cerebral oxygenation index; RP, radical prostatectomy.

Cardiac Index and Cerebrovascular Autoregulation

The results of the intraoperative monitoring of cardiac index and CA are displayed in Table 1. Bins of cardiac index across different levels of the COx are presented in Fig. 2.We found no clinically relevant cross-correlation between the cardiac index and the COx (median cross correlation=0.230 [IQR: 0.186, 0.287]; Fig. 3).

There was no clinically relevant correlation between the TWA of cardiac index below the pathologic threshold of 2.5 L/min/m2 and the TWA of COx above the pathologic threshold of 0.3 (Spearman ρ=0.095 [95% CI: −0.063 to 0.266], P=0.239; Fig. 4). Sensitivity analysis 1 using a threshold of 0.0 for the COx confirmed this finding (Spearman ρ=0.082 [95% CI: −0.098 to 0.234], P=0.308). Sensitivity analysis 2 revealed a very weak positive correlation between the TWA of cardiac index below 1.8 L min−1 m−2 and the TWA of COx above the pathologic threshold of 0.3 (Spearman ρ=0.158 [95% CI: −0.004 to 0.311], P=0.049; Supplementary Figure 1, Supplemental Digital Content 1, http://links.lww.com/JNA/A667).

There were no clinically relevant differences between the area between the cardiac index curve and the COx curve when comparing patients aged <65 versus ≥65 years (P=0.903; Supplementary Figure 2, Supplemental Digital Content 2, http://links.lww.com/JNA/A668), patients undergoing open radical prostatectomy versus robot-assisted radical prostatectomy (P=0.699), patients without cardiovascular risk factors versus at least 1 cardiovascular risk factor (P=0.518; Supplementary Figure 2, Supplemental Digital Content 2, http://links.lww.com/JNA/A668), and patients with normal ABP versus history of arterial hypertension (P=0.822).

FIGURE 2 Bins of CI (in L/min/m2) across the COx. CI indicates cardiac index; COx, cerebral oxygenation index.

FIGURE 3 Cross-correlation between the CI and cerebral autoregulation, expressed as COx. CI indicates cardiac index; COx, cerebral oxygenation index.

FIGURE 4 Correlation between the time-weighted average of CI below 2.5 L/min/m2 and the time-weighted average of the COx above 0.3. CI indicates cardiac index; COx, cerebral oxygenation index.

DISCUSSION

We aimed to investigate whether intraoperative changes in cardiac index are associated with changes in CA expressed by the COx. In addition, we aimed to investigate whether there is an association between cardiac index below the pathologic threshold and impaired CA. Contrary to our hypothesis, we did not find a clinically relevant association between cardiac index and CA.

Intact CA function is confined to the autoregulatory plateau, which describes the range of cerebral perfusion pressure between the lower and upper limits of autoregulation. Cardiac output is one of the main determinants of ABP.2 It is thus plausible that disturbances of cardiac output affect CA through changes in ABP.2 A decrease in cardiac output may lead to a decrease in ABP below the lower limit of autoregulation, where cerebral vessels are maximally dilated, resulting in compromised CA.2 In healthy nonanesthetized individuals, a moderate reduction or increase of cardiac output will be met with an increase or decrease of peripheral vascular resistance, to prevent changes in ABP, keeping the cerebral perfusion pressure within the autoregulatory range.2,4 In anesthetized patients, this mechanism may be impaired. Fluctuations of cardiac output, caused by surgical blood loss and anesthetic medication, may entail periods of cerebral perfusion pressure outside the autoregulatory range, resulting in impaired CA.21 This is all the more important during surgery and anesthesia since previous studies have shown that the autoregulatory range is shortened under sevoflurane anesthesia.22

To the best of our knowledge, only 2 studies have investigated the association between cardiac index and CA.6,7 Contrary to our study, these two assessed dynamic CA by inducing transient hypotension in healthy subjects. The authors found no association between changes in stroke volume or cardiac index and CBF after thigh cuff deflation and concluded that cardiac output does not play an important role in CA.6,7 We investigated dynamic CA in surgical patients during general anesthesia by assessing changes in rSO2 during spontaneously occurring changes in ABP. Our results corroborate the above-mentioned findings. Neither did we find a correlation between changes in the cardiac index and the COx. Nor did we find an association between cardiac index below a pathologic threshold and impaired CA. This is reassuring, given that intact CA is crucial for the prevention of critical disturbances of CBF and to ensure neuroprotection.1 In addition, this is in line with the theory of Meng et al4 that changes in cardiac output may lead to an upward or downward shift of the autoregulatory plateau, while the mechanism of autoregulation itself remains intact.

Interestingly, the second sensitivity analysis, which was based on extremely low cutoffs of the cardiac index, revealed a very weak positive correlation between cardiac index and COx. Although barely significant, this finding suggests that extreme changes in cardiac output may indeed have a negative impact on CA. However, one must be careful when interpreting the results of the second sensitivity analysis. Our patients were meticulously monitored by the attending anesthesiologists, who immediately treated any hypotensive or low-output episodes with vasopressors or crystalloid fluids according to the suspected underlying mechanism. Thus, episodes with a cardiac index below the pathologic threshold were extremely scarce. Only 3 patients had a mean CI below 1.8 L/min/m2. Therefore, this interesting finding urgently needs to be re-examined in a population with prolonged and more pronounced episodes of hypotension or low cardiac output, such as surgeries with a higher risk for hemodynamic instability including major vascular surgery.

Taken together, our findings suggest that within a wide range of cardiac index alterations, arterial pressure fluctuations, rather than changes in cardiac output, may determine the regulation of CBF.

Importantly, the perioperative setting of our study may have influenced our findings. We analyzed data from patients receiving inhalational anesthesia with sevoflurane. The anesthetic medication, particularly sevoflurane, has a dose-dependent effect on CA.8,23,24 High doses of sevoflurane have been linked with impaired CA,23,25 which is attributable to its strong vasodilatory properties.8,22,26 However, at doses below a minimal alveolar concentration of 1.5, sevoflurane does not seem to impair CA.27,28 While the anesthesiologic management for this study included narrow target ranges for end-tidal sevoflurane, aiming at a minimal alveolar concentration of 1.0, we did not collect data on these variables, and we did not include them as confounding variables. This remains a source of potential bias. It is thus plausible that the effect of anesthetic medication on CA may have masked a correlation between changes in cardiac index and CA. Therefore, we cannot draw conclusions about nonanesthetized patients.

Other than an actual lack of association between cardiac output and CA, there may be alternative explanations for the negative findings of our study: (1) Hemodilution and surgical blood loss may induce concomitant alterations in cardiac output and CBF that may not necessarily translate into changes in ABP.29 (2) Owing to its high metabolic demand, the brain receives a high proportion of blood volume, which may be even higher during periods of reduced cardiac output.30 Therefore, a relatively higher proportion of CBF during episodes of low cardiac output may explain the lack of association observed in our study. Meng and colleagues suggest varying autoregulatory plateaus depending on different levels of cardiac output, where CBF reduction is less pronounced during low cardiac output compared with the perfusion of other organs. (3) In contrast to periods of low cardiac output, increases in cardiac output above the physiological threshold do not seem to translate into higher cerebral perfusion.29

Eventually, it is important to acknowledge the complex interplay of different autoregulatory systems that take part in regulating CBF.4 While this study focused primarily on the concept of pressure autoregulation, other mechanisms include neurovascular coupling, cerebrovascular reactivity to carbon dioxide and oxygen, and possibly even a direct connection between cardiac output and CBF.4,29 Each of these mechanisms may influence CBF, while also influencing one another.4 We did not investigate any of these additional autoregulatory systems, nor did we measure CBF directly. Therefore, we realize that the results of our study represent only a small fraction of a complex system. Nevertheless, we hope that the results of this study will aid in the understanding of the specific interaction of cardiac output and CA and encourage further research, exploring the interaction with other autoregulatory mechanisms.

Our study has several limitations. Importantly, our results are of exploratory nature, since they reflect findings from a secondary analysis of individual-level data from 2 different studies. We only included relatively healthy male patients without preoperative central nervous system disease or neurocognitive disorders, undergoing general anesthesia for elective noncardiac surgery. All surgeries were performed in the 30 to 40 degrees head-down position with capnoperitoneum. Of note, one of the primary studies that this secondary analysis is based on specifically investigated the influence of the head-down position with capnoperitoneum on CA. The findings of this study indicate that the head-down position with capnoperitoneum does not affect CA.12 Therefore, we may assume that positioning and the capnoperitoneum have not influenced our findings. However, neither can we exclude an effect on cardiac output, nor an influence of sex on both CA and cardiac output. Thus, our results cannot be generalized to female patients, to critically ill patients, to surgical settings other than prostatectomy, to nonanesthetized individuals, or patients with neurological disease. Future studies should include a more diverse study population.

CONCLUSIONS

Over a wide range of cardiac indices, we did not find a clinically relevant association between intraoperative fluctuations in cardiac index and intraoperative CA. This is reassuring, given that intact CA is of utmost importance to ensure adequate cerebral perfusion. However, extreme changes in cardiac output may indeed have a negative impact on CA. In addition, it is possible that an association between cardiac index and CA was masked by the influence of anesthesia on CA. Therefore, we cannot draw conclusions about nonanesthetized patients.

Supplementary Material

SUPPLEMENTARY MATERIAL

U.K. and L.K. contributed equally to this work.

This research was partially supported by the Else Kröner-Fresenius-Stiftung (2015_A33).

M.F. and U.K. receive financial research support from the External Research Program, Medtronic, Minneapolis, MN, USA. Medtronic was not involved in the design or conduct of the study, nor the collection, analysis, or interpretation of data. The remaining authors have no conflicts of interest to declare.

Supplemental Digital Content is available for this article. Direct URL citations are provided in the HTML and PDF versions of this article on the journal's website, www.jnsa.com.
==== Refs
REFERENCES

1 Xiong L Liu X Shang T . Impaired cerebral autoregulation: measurement and application to stroke. J Neurol Neurosurg Psychiatry. 2017;88 :520. 10.1136/jnnp-2016-314385 28536207
2 Donnelly J Budohoski KP Smielewski P . Regulation of the cerebral circulation: bedside assessment and clinical implications. Crit Care. 2016;20 :129. 10.1186/s13054-016-1293-6 27145751
3 Henriksen OM Jensen LT Krabbe K . Relationship between cardiac function and resting cerebral blood flow: MRI measurements in healthy elderly subjects. Clin Physiol Funct Imaging. 2014;34 :471–477. 10.1111/cpf.12119 24314236
4 Meng L Hou W Chui J . Cardiac output and cerebral blood flow. Anesthesiology. 2015;123 :1198–1208. 10.1097/aln.0000000000000872 26402848
5 Williams LR Leggett RW . Reference values for resting blood flow to organs of man. Clin Phys Physiol Meas. 1989;10 :187–217. 10.1088/0143-0815/10/3/001 2697487
6 Deegan BM Devine ER Geraghty MC . The relationship between cardiac output and dynamic cerebral autoregulation in humans. J Appl Physiol. 2010;109 :1424–1431. 10.1152/japplphysiol.01262.2009 20689094
7 Deegan BM Geraghty MC Hodgeman RM , . Assessment of techniques used to evaluate the effect of posture and cardiac output on cerebral autoregulation. 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society; 2008, 1992–1995. 10.1109/iembs.2008.4649580
8 Slupe AM Kirsch JR . Effects of anesthesia on cerebral blood flow, metabolism, and neuroprotection. J Cereb Blood Flow Metab. 2018;38 :2192–2208. 10.1177/0271678x18789273 30009645
9 Chan B Aneman A . A prospective, observational study of cerebrovascular autoregulation and its association with delirium following cardiac surgery. Anaesthesia. 2019;74 :33–44. doi:10.1111/anae.14457 30338515
10 Kahl U Rademacher C Harler U . Intraoperative impaired cerebrovascular autoregulation and delayed neurocognitive recovery after major oncologic surgery: a secondary analysis of pooled data. J Clin Monit Comput. 2021;36 :765–773. 10.1007/s10877-021-00706-z 33860406
11 Kumpaitiene B Svagzdiene M Sirvinskas E . Cerebrovascular autoregulation impairments during cardiac surgery with cardiopulmonary bypass are related to postoperative cognitive deterioration: prospective observational study. Minerva Anestesiol. 2019;85 :594–603. 10.23736/s0375-9393.18.12358-3 29756691
12 Beck S Ragab H Hoop D . Comparing the effect of positioning on cerebral autoregulation during radical prostatectomy: a prospective observational study. J Clin Monit Comput. 2020;35 :891–901. 10.1007/s10877-020-00549-0 32564173
13 Lendner JD Harler U Daume J . Oscillatory and aperiodic neuronal activity in working memory following anesthesia. Clin Neurophysiol. 2023;150 :79–88. doi:10.1016/j.clinph.2023.03.005 37028144
14 Kahl U Yu Y Nierhaus A . Cerebrovascular autoregulation and arterial carbon dioxide in patients with acute respiratory distress syndrome: a prospective observational cohort study. Ann Intensive Care. 2020;11 :47. 10.1186/s13613-021-00831-7
15 Zweifel C Dias C Smielewski P . Continuous time-domain monitoring of cerebral autoregulation in neurocritical care. Med Eng Phys. 2014;36 :638–645. 10.1016/j.medengphy.2014.03.002 24703503
16 Hirsch J DePalma G Tsai TT . Impact of intraoperative hypotension and blood pressure fluctuations on early postoperative delirium after non-cardiac surgery. Br J Anaesth. 2015;115 :418–426. doi:10.1093/bja/aeu458 25616677
17 Moritz S Bartz-Beielstein T . imputeTS: time series missing value imputation in R. R J. 2017;9 :207. 10.32614/rj-2017-009
18 Brady KM Lee JK Kibler KK . Continuous time-domain analysis of cerebrovascular autoregulation using near-infrared spectroscopy. Stroke. 2007;38 :2818–2825. 10.1161/strokeaha.107.485706 17761921
19 Patel HN Miyoshi T Addetia K . Normal values of cardiac output and stroke volume according to measurement technique, age, sex, and ethnicity: results of the World Alliance of Societies of Echocardiography Study. J Am Soc Echocardiogr. 2021;34 :1077–1085.e1. 10.1016/j.echo.2021.05.012 34044105
20 Hervé M . RVAideMemoire: Testing and Plotting Procedures for Biostatistics. n.d. Accessed February 18, 2023. https://CRAN.R-project.org/package=RVAideMemoire
21 Whitwam JG Galletly DC Ma D . The effects of propofol on heart rate, arterial pressure and Aδ and C somatosympathetic reflexes in anaesthetized dogs.. Eur J Anaesthesiol. 2000;17 :57–63. 10.1046/j.1365-2346.2000.00605.x 10758446
22 Goettel N Patet C Rossi A . Monitoring of cerebral blood flow autoregulation in adults undergoing sevoflurane anesthesia: a prospective cohort study of two age groups. J Clin Monit Comput. 2016;30 :255–264. 10.1007/s10877-015-9754-z 26285741
23 Conti A Iacopino DG Fodale V . Cerebral haemodynamic changes during propofol-remifentanil or sevoflurane anaesthesia: transcranial Doppler study under bispectral index monitoring. Br J Anaesth. 2006;97 :333–339. doi:10.1093/bja/ael169 16829673
24 Dagal A Lam AM . Cerebral autoregulation and anesthesia. Curr Opin Anaesthesiol. 2009;22 :547–552. 10.1097/aco.0b013e32833020be 19620861
25 Reinsfelt B Westerlind A Ricksten S‐E . The effects of sevoflurane on cerebral blood flow autoregulation and flow‐metabolism coupling during cardiopulmonary bypass. Acta Anaesthesiol Scand. 2011;55 :118–123. 10.1111/j.1399-6576.2010.02324.x 21039354
26 Patel P , & Drummond JC . Cerebral Physiology and the Effects of Anesthetic Drugs. 2010. https://api.semanticscholar.org/CorpusID:78313645
27 Gupta S Heath K Matta BF . Effect of incremental doses of sevoflurane on cerebral pressure autoregulation in humans. Br J Anaesth. 1997;79 :469–472. 10.1093/bja/79.4.469 9389265
28 Juhász M Molnár L Fülesdi B . Effect of sevoflurane on systemic and cerebral circulation, cerebral autoregulation and CO2 reactivity. BMC Anesthesiol. 2019;19 :109. 10.1186/s12871-019-0784-9 31215448
29 Castle-Kirszbaum M Parkin WG Goldschlager T . Cardiac output and cerebral blood flow: a systematic review of cardio-cerebral coupling. J Neurosurg Anesthesiol. 2022;34 :352–363. 10.1097/ana.0000000000000768 33782372
30 Lie SL Hisdal J Høiseth LØ . Cerebral blood flow velocity during simultaneous changes in mean arterial pressure and cardiac output in healthy volunteers. Eur J Appl Physiol. 2021;121 :2207–2217. 10.1007/s00421-021-04693-6 33890157
