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Xu J, Wiemken A, Langham MC, Rao H, Nabbout M, Caporale AS, Schwab RJ, Detre JA, Wehrli FW. Sleep-stage-dependent alterations in cerebral oxygen metabolism quantified by magnetic resonance. J Neurosci Res 2024; 102:e25313. [PMID: 38415989 DOI: 10.1002/jnr.25313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 01/25/2024] [Accepted: 02/09/2024] [Indexed: 02/29/2024]
Abstract
A key function of sleep is to provide a regular period of reduced brain metabolism, which is critical for maintenance of healthy brain function. The purpose of this work was to quantify the sleep-stage-dependent changes in brain energetics in terms of cerebral metabolic rate of oxygen (CMRO2 ) as a function of sleep stage using quantitative magnetic resonance imaging (MRI) with concurrent electroencephalography (EEG) during sleep in the scanner. Twenty-two young and older subjects with regular sleep hygiene and Pittsburgh Sleep Quality Index (PSQI) in the normal range were recruited for the study. Cerebral blood flow (CBF) and venous oxygen saturation (SvO2 ) were obtained simultaneously at 3 Tesla field strength and 2.7-s temporal resolution during an 80-min time series using OxFlow, an in-house developed imaging sequence. The method yields whole-brain CMRO2 in absolute physiologic units via Fick's Principle. Nineteen subjects yielded evaluable data free of subject motion artifacts. Among these subjects, 10 achieved slow-wave (N3) sleep, 16 achieved N2 sleep, and 19 achieved N1 sleep while undergoing the MRI protocol during scanning. Mean CMRO2 was 98 ± 7(μmol min-1 )/100 g awake, declining progressively toward deepest sleep stage: 94 ± 10.8 (N1), 91 ± 11.4 (N2), and 76 ± 9.0 μmol min-1 /100 g (N3), with each level differing significantly from the wake state. The technology described is able to quantify cerebral oxygen metabolism in absolute physiologic units along with non-REM sleep stage, indicating brain oxygen consumption to be closely associated with depth of sleep, with deeper sleep stages exhibiting progressively lower CMRO2 levels.
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Affiliation(s)
- Jing Xu
- Laboratory for Structural, Physiological, and Functional Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Andrew Wiemken
- Division of Sleep Medicine, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Michael C Langham
- Laboratory for Structural, Physiological, and Functional Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Hengyi Rao
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Marianne Nabbout
- Laboratory for Structural, Physiological, and Functional Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Alessandra S Caporale
- Laboratory for Structural, Physiological, and Functional Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Neurosciences, Imaging and Clinical Sciences, 'G. d'Annunzio University' of Chieti-Pescara, Chieti, Italy
- Institute for Advanced Biomedical Technologies (ITAB), 'G. d'Annunzio University' of Chieti-Pescara, Chieti, Italy
| | - Richard J Schwab
- Division of Sleep Medicine, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - John A Detre
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Felix W Wehrli
- Laboratory for Structural, Physiological, and Functional Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Lee H, Xu J, Fernandez-Seara MA, Wehrli FW. Validation of a new 3D quantitative BOLD based cerebral oxygen extraction mapping. J Cereb Blood Flow Metab 2024:271678X231220332. [PMID: 38289876 DOI: 10.1177/0271678x231220332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Quantitative BOLD (qBOLD) MRI allows evaluation of oxidative metabolism of the brain based purely on an endogenous contrast mechanism. The method quantifies deoxygenated blood volume (DBV) and hemoglobin oxygen saturation level of venous blood (Yv), yielding oxygen extraction fraction (OEF), and along with a separate measurement of cerebral blood flow, cerebral metabolic rate of oxygen (CMRO2) maps. Here, we evaluated our recently reported 3D qBOLD method that rectifies a number of deficiencies in prior qBOLD approaches in terms of repeat reproducibility and sensitivity to hypercapnia on the metabolic parameters, and in comparison to dual-gas calibrated BOLD (cBOLD) MRI for determining resting-state oxygen metabolism. Results suggested no significant difference between test-retest qBOLD scans in either DBV and OEF. Exposure to hypercapnia yielded group averages of 38 and 28% for OEF and 151 and 146 µmol/min/100 g for CMRO2 in gray matter at baseline and hypercapnia, respectively. The decrease of OEF during hypercapnia was significant (p ≪ 0.01), whereas CMRO2 did not change significantly (p = 0.25). Finally, baseline OEF (37 vs. 39%) and CMRO2 (153 vs. 145 µmol/min/100 g) in gray matter using qBOLD and dual-gas cBOLD were found to be in good agreement with literature values, and were not significantly different from each other (p > 0.1).
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Affiliation(s)
- Hyunyeol Lee
- School of Electronic and Electrical Engineering, Kyungpook National University, Daegu, Republic of Korea
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Jing Xu
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Maria A Fernandez-Seara
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Radiology, Clinica Universidad de Navarra, Pamplona, Spain
| | - Felix W Wehrli
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Caporale AS, Barclay AM, Xu J, Rao H, Lee H, Langham MC, Detre JA, Wehrli FW. Superior sagittal sinus flow as a proxy for tracking global cerebral blood flow dynamics during wakefulness and sleep. J Cereb Blood Flow Metab 2023; 43:1340-1350. [PMID: 36927172 PMCID: PMC10369151 DOI: 10.1177/0271678x231164423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 01/18/2023] [Accepted: 02/10/2023] [Indexed: 03/18/2023]
Abstract
Sleep, a state of reduced consciousness, affects brain oxygen metabolism and lowers cerebral metabolic rate of oxygen (CMRO2). Previously, we quantified CMRO2 during sleep via Fick's Principle, with a single-band MRI sequence measuring both hemoglobin O2 saturation (SvO2) and superior sagittal sinus (SSS) blood flow, which was upscaled to obtain total cerebral blood flow (tCBF). The procedure involves a brief initial calibration scan to determine the upscaling factor (fc), assumed state-invariant. Here, we used a dual-band sequence to simultaneously provide SvO2 in SSS and tCBF in the neck every 16 seconds, allowing quantification of fc dynamically. Ten healthy subjects were scanned by MRI with simultaneous EEG for 80 minutes, yielding 300 temporal image frames per subject. Four volunteers achieved slow-wave sleep (SWS), as evidenced by increased δ-wave activity (per American Academy of Sleep Medicine criteria). SWS was maintained for 13.5 ± 7.0 minutes, with CMRO2 28.6 ± 5.5% lower than pre-sleep wakefulness. Importantly, there was negligible bias between tCBF obtained by upscaling SSS-blood flow, and tCBF measured directly in the inflowing arteries of the neck (intra-class correlation 0.95 ± 0.04, averaged across all subjects), showing that the single-band approach is a valid substitute for quantifying tCBF, simplifying image data collection and analysis without sacrificing accuracy.
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Affiliation(s)
- Alessandra S Caporale
- Laboratory for Structural, Physiological, and Functional Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Neuroscience, Imaging and Clinical Sciences, ‘G. d’Annunzio University’ of Chieti-Pescara, Chieti, Italy
- Institute for Advanced Biomedical Technologies (ITAB), ‘G. d’Annunzio University’ of Chieti-Pescara, Chieti, Italy
| | - Alexander M Barclay
- Laboratory for Structural, Physiological, and Functional Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Jing Xu
- Laboratory for Structural, Physiological, and Functional Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Hengyi Rao
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Division of Sleep and Chronobiology, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Hyunyeol Lee
- Laboratory for Structural, Physiological, and Functional Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- School of Electronics Engineering, Kyungpook National University, Daegu, South Korea
| | - Michael C Langham
- Laboratory for Structural, Physiological, and Functional Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - John A Detre
- Laboratory for Structural, Physiological, and Functional Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Felix W Wehrli
- Laboratory for Structural, Physiological, and Functional Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Abstract
This article provides an overview of MRI methods exploiting magnetic susceptibility properties of blood to assess cerebral oxygen metabolism, including the tissue oxygen extraction fraction (OEF) and the cerebral metabolic rate of oxygen (CMRO2). The first section is devoted to describing blood magnetic susceptibility and its effect on the MRI signal. Blood circulating in the vasculature can have diamagnetic (oxyhemoglobin) or paramagnetic properties (deoxyhemoglobin). The overall balance between oxygenated and deoxygenated hemoglobin determines the induced magnetic field which, in turn, modulates the transverse relaxation decay of the MRI signal via additional phase accumulation. The following sections of this review then illustrate the principles underpinning susceptibility-based techniques for quantifying OEF and CMRO2. Here, it is detailed whether these techniques provide global (OxFlow) or local (Quantitative Susceptibility Mapping - QSM, calibrated BOLD - cBOLD, quantitative BOLD - qBOLD, QSM+qBOLD) measurements of OEF or CMRO2, and what signal components (magnitude or phase) and tissue pools they consider (intravascular or extravascular). Validations studies and potential limitations of each method are also described. The latter include (but are not limited to) challenges in the experimental setup, the accuracy of signal modeling, and assumptions on the measured signal. The last section outlines the clinical uses of these techniques in healthy aging and neurodegenerative diseases and contextualizes these reports relative to results from gold-standard PET.
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Affiliation(s)
- Emma Biondetti
- Department of Neuroscience, Imaging and Clinical Sciences, "D'Annunzio University" of Chieti-Pescara, Chieti, Italy; Institute for Advanced Biomedical Technologies, "D'Annunzio University" of Chieti-Pescara, Chieti, Italy
| | - Junghun Cho
- Department of Biomedical Engineering, University at Buffalo, The State University of New York, New York, USA
| | - Hyunyeol Lee
- School of Electronic and Electrical Engineering, Kyungpook National University, Daegu, Republic of Korea; Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
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Wu PH, Rodríguez-Soto AE, Wiemken A, Englund EK, Rodgers ZB, Langham MC, Schwab RJ, Detre JA, Guo W, Wehrli FW. MRI evaluation of cerebral metabolic rate of oxygen (CMRO 2) in obstructive sleep apnea. J Cereb Blood Flow Metab 2022; 42:1049-1060. [PMID: 34994242 PMCID: PMC9125486 DOI: 10.1177/0271678x211071018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/07/2021] [Revised: 11/15/2021] [Accepted: 12/10/2021] [Indexed: 01/09/2023]
Abstract
Patients with obstructive sleep apnea (OSA) are at elevated risk of developing systemic vascular disease and cognitive dysfunction. Here, cerebral oxygen metabolism was assessed in patients with OSA by means of a magnetic resonance-based method involving simultaneous measurements of cerebral blood flow rate and venous oxygen saturation in the superior sagittal sinus for a period of 10 minutes at an effective temporal resolution of 1.3 seconds before, during, and after repeated 24-second breath-holds mimicking spontaneous apneas, yielding, along with pulse oximetry-derived arterial saturation, whole-brain CMRO2 via Fick's Principle. Enrolled subjects were classified based on their apnea-hypopnea indices into OSA (N = 31) and non-sleep apnea reference subjects (NSA = 21), and further compared with young healthy subjects (YH, N = 10). OSA and NSA subjects were matched for age and body mass index. CMRO2 was lower in OSA than in the YH group during normal breathing (105.6 ± 14.1 versus 123.7 ± 22.8 μmol O2/min/100g, P = 0.01). Further, the fractional change in CMRO2 in response to a breath-hold challenge was larger in OSA than in the YH group (15.2 ± 9.2 versus 8.5 ± 3.4%, P = 0.04). However, there was no significant difference in CMRO2 between OSA and NSA subjects. The data suggest altered brain oxygen metabolism in OSA and possibly in NSA as well.
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Affiliation(s)
- Pei-Hsin Wu
- Department of Radiology, University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA
- Department of Electrical Engineering, National Sun Yat-sen University, National Sun Yat-sen University, Kaohsiung, Taiwan
| | - Ana E Rodríguez-Soto
- Department of Radiology, University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA
| | - Andrew Wiemken
- Division of Sleep Medicine, Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Erin K Englund
- Department of Radiology, University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA
| | - Zachary B Rodgers
- Department of Radiology, University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA
| | - Michael C Langham
- Department of Radiology, University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA
| | - Richard J Schwab
- Division of Sleep Medicine, Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - John A Detre
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Wensheng Guo
- Department of Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA
| | - Felix W Wehrli
- Department of Radiology, University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA
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Jiang D, Lu H. Cerebral oxygen extraction fraction MRI: Techniques and applications. Magn Reson Med 2022; 88:575-600. [PMID: 35510696 PMCID: PMC9233013 DOI: 10.1002/mrm.29272] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 03/20/2022] [Accepted: 03/29/2022] [Indexed: 12/20/2022]
Abstract
The human brain constitutes 2% of the body's total mass but uses 20% of the oxygen. The rate of the brain's oxygen utilization can be derived from a knowledge of cerebral blood flow and the oxygen extraction fraction (OEF). Therefore, OEF is a key physiological parameter of the brain's function and metabolism. OEF has been suggested to be a useful biomarker in a number of brain diseases. With recent advances in MRI techniques, several MRI-based methods have been developed to measure OEF in the human brain. These MRI OEF techniques are based on the T2 of blood, the blood signal phase, the magnetic susceptibility of blood-containing voxels, the effect of deoxyhemoglobin on signal behavior in extravascular tissue, and the calibration of the BOLD signal using gas inhalation. Compared to 15 O PET, which is considered the "gold standard" for OEF measurement, MRI-based techniques are non-invasive, radiation-free, and are more widely available. This article provides a review of these emerging MRI-based OEF techniques. We first briefly introduce the role of OEF in brain oxygen homeostasis. We then review the methodological aspects of different categories of MRI OEF techniques, including their signal mechanisms, acquisition methods, and data analyses. The strengths and limitations of the techniques are discussed. Finally, we review key applications of these techniques in physiological and pathological conditions.
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Affiliation(s)
- Dengrong Jiang
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Hanzhang Lu
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA
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Lee H, Wehrli FW. Whole-brain 3D Mapping of Oxygen Metabolism Using Constrained Quantitative BOLD. Neuroimage 2022;:118952. [PMID: 35093519 DOI: 10.1016/j.neuroimage.2022.118952] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 12/24/2021] [Accepted: 01/25/2022] [Indexed: 12/02/2022] Open
Abstract
Quantitative BOLD (qBOLD) MRI permits noninvasive evaluation of hemodynamic and metabolic states of the brain by quantifying parametric maps of deoxygenated blood volume (DBV) and hemoglobin oxygen saturation level of venous blood (Yv), and along with a measurement of cerebral blood flow (CBF), the cerebral metabolic rate of oxygen (CMRO2). The method, thus should have potential to provide important information on many neurological disorders as well as normal cerebral physiology. One major challenge in qBOLD is to separate de-oxyhemoglobin’s contribution to R2′ from other sources modulating the voxel signal, for instance, R2, R2′ from non-heme iron (R′2,nh), and macroscopic magnetic field variations. Further, even with successful separation of the several confounders, it is still challenging to extract DBV and Yv from the heme-originated R2′ because of limited sensitivity of the qBOLD model. These issues, which have not been fully addressed in currently practiced qBOLD methods, have so far precluded 3D whole-brain implementation of qBOLD. Thus, the purpose of this work was to develop a new 3D MRI oximetry technique that enables robust qBOLD parameter mapping across the entire brain. To achieve this goal, we employed a rapid, R2′-sensitive, steady-state 3D pulse sequence (termed ‘AUSFIDE’) for data acquisition, and implemented a prior-constrained qBOLD processing pipeline that exploits a plurality of preliminary parameters obtained via AUSFIDE, along with additionally measured cerebral venous blood volume. Numerical simulations and in vivo studies at 3 T were performed to evaluate the performance of the proposed, constrained qBOLD mapping in comparison to the parent qBOLD method. Measured parameters (Yv, DBV, R′2,nh, nonblood magnetic susceptibility) in ten healthy subjects demonstrate the expected contrast across brain territories, while yielding group-averages of 64.0 ± 2.3 % and 62.2 ± 3.1 % for Yv and 2.8 ± 0.5 % and 1.8 ± 0.4 % for DBV in cortical gray and white matter, respectively. Given the Yv measurements, additionally quantified CBF in seven of the ten study subjects enabled whole-brain 3D CMRO2 mapping, yielding group averages of 134.2 ± 21.1 and 79.4 ± 12.6 µmol/100 g/min for cortical gray and white matter, in good agreement with literature values. The results suggest feasibility of the proposed method as a practical and reliable means for measuring neurometabolic parameters over an extended brain coverage.
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Turner AD, Sullivan T, Drury K, Hall TA, Williams CN, Guilliams KP, Murphy S, Iqbal O’Meara AM. Cognitive Dysfunction After Analgesia and Sedation: Out of the Operating Room and Into the Pediatric Intensive Care Unit. Front Behav Neurosci 2021; 15:713668. [PMID: 34483858 PMCID: PMC8415404 DOI: 10.3389/fnbeh.2021.713668] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2021] [Accepted: 07/26/2021] [Indexed: 11/13/2022] Open
Abstract
In the midst of concerns for potential neurodevelopmental effects after surgical anesthesia, there is a growing awareness that children who require sedation during critical illness are susceptible to neurologic dysfunctions collectively termed pediatric post-intensive care syndrome, or PICS-p. In contrast to healthy children undergoing elective surgery, critically ill children are subject to inordinate neurologic stress or injury and need to be considered separately. Despite recognition of PICS-p, inconsistency in techniques and timing of post-discharge assessments continues to be a significant barrier to understanding the specific role of sedation in later cognitive dysfunction. Nonetheless, available pediatric studies that account for analgesia and sedation consistently identify sedative and opioid analgesic exposures as risk factors for both in-hospital delirium and post-discharge neurologic sequelae. Clinical observations are supported by animal models showing neuroinflammation, increased neuronal death, dysmyelination, and altered synaptic plasticity and neurotransmission. Additionally, intensive care sedation also contributes to sleep disruption, an important and overlooked variable during acute illness and post-discharge recovery. Because analgesia and sedation are potentially modifiable, understanding the underlying mechanisms could transform sedation strategies to improve outcomes. To move the needle on this, prospective clinical studies would benefit from cohesion with regard to datasets and core outcome assessments, including sleep quality. Analyses should also account for the wide range of diagnoses, heterogeneity of this population, and the dynamic nature of neurodevelopment in age cohorts. Much of the related preclinical evidence has been studied in comparatively brief anesthetic exposures in healthy animals during infancy and is not generalizable to critically ill children. Thus, complementary animal models that more accurately "reverse translate" critical illness paradigms and the effect of analgesia and sedation on neuropathology and functional outcomes are needed. This review explores the interactive role of sedatives and the neurologic vulnerability of critically ill children as it pertains to survivorship and functional outcomes, which is the next frontier in pediatric intensive care.
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Affiliation(s)
- Ashley D. Turner
- Division of Pediatric Critical Care, Department of Pediatrics, Washington University in St. Louis, St. Louis, MO, United States
| | - Travis Sullivan
- Department of Surgery, Virginia Commonwealth University School of Medicine, Richmond, VA, United States
| | - Kurt Drury
- Department of Pediatrics, Division of Pediatric Critical Care, Doernbecher Children’s Hospital, Oregon Health & Science University, Portland, OR, United States
| | - Trevor A. Hall
- Department of Pediatrics, Division of Pediatric Psychology, Pediatric Critical Care and Neurotrauma Recovery Program, Doernbecher Children’s Hospital, Oregon Health & Science University, Portland, OR, United States
| | - Cydni N. Williams
- Department of Pediatrics, Division of Pediatric Critical Care, Doernbecher Children’s Hospital, Oregon Health & Science University, Portland, OR, United States
| | - Kristin P. Guilliams
- Division of Pediatric Critical Care, Department of Pediatrics, Washington University in St. Louis, St. Louis, MO, United States
- Division of Pediatric Neurology, Department of Neurology, Washington University in St. Louis, St. Louis, MO, United States
- Division of Neuroradiology, Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, United States
| | - Sarah Murphy
- Department of Pediatrics, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - A. M. Iqbal O’Meara
- Department of Pediatrics, Child Health Research Institute, Children’s Hospital of Richmond at Virginia Commonwealth University School of Medicine, Richmond, VA, United States
- Department of Pediatrics, Uniformed Services University of the Health Sciences, Bethesda, MD, United States
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Mamelak M. Sleep, Narcolepsy, and Sodium Oxybate. Curr Neuropharmacol 2021; 20:272-291. [PMID: 33827411 PMCID: PMC9413790 DOI: 10.2174/1570159x19666210407151227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2021] [Revised: 03/18/2021] [Accepted: 03/24/2021] [Indexed: 11/23/2022] Open
Abstract
Sodium oxybate (SO) has been in use for many decades to treat narcolepsy with cataplexy. It functions as a weak GABAB agonist but also as an energy source for the brain as a result of its metabolism to succinate and as a powerful antioxidant because of its capacity to induce the formation of NADPH. Its actions at thalamic GABAB receptors can induce slow-wave activity, while its actions at GABAB receptors on monoaminergic neurons can induce or delay REM sleep. By altering the balance between monoaminergic and cholinergic neuronal activity, SO uniquely can induce and prevent cataplexy. The formation of NADPH may enhance sleep’s restorative process by accelerating the removal of the reactive oxygen species (ROS), which accumulate during wakefulness. SO improves alertness in normal subjects and in patients with narcolepsy. SO may allay severe psychological stress - an inflammatory state triggered by increased levels of ROS and characterized by cholinergic supersensitivity and monoaminergic deficiency. SO may be able to eliminate the inflammatory state and correct the cholinergic/ monoaminergic imbalance.
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Affiliation(s)
- Mortimer Mamelak
- Department of Psychiatry, Baycrest Hospital, University of Toronto, Toronto, Ontario. Canada
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