1
|
Steinberg A. Emergent Management of Hypoxic-Ischemic Brain Injury. Continuum (Minneap Minn) 2024; 30:588-610. [PMID: 38830064 DOI: 10.1212/con.0000000000001426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/05/2024]
Abstract
OBJECTIVE This article outlines interventions used to improve outcomes for patients with hypoxic-ischemic brain injury after cardiac arrest. LATEST DEVELOPMENTS Emergent management of patients after cardiac arrest requires prevention and treatment of primary and secondary brain injury. Primary brain injury is minimized by excellent initial resuscitative efforts. Secondary brain injury prevention requires the detection and correction of many pathophysiologic processes that may develop in the hours to days after the initial arrest. Key physiologic parameters important to secondary brain injury prevention include optimization of mean arterial pressure, cerebral perfusion, oxygenation and ventilation, intracranial pressure, temperature, and cortical hyperexcitability. This article outlines recent data regarding the treatment and prevention of secondary brain injury. Different patients likely benefit from different treatment strategies, so an individualized approach to treatment and prevention of secondary brain injury is advisable. Clinicians must use multimodal sources of data to prognosticate outcomes after cardiac arrest while recognizing that all prognostic tools have shortcomings. ESSENTIAL POINTS Neurologists should be involved in the postarrest care of patients with hypoxic-ischemic brain injury to improve their outcomes. Postarrest care requires nuanced and patient-centered approaches to the prevention and treatment of primary and secondary brain injury and neuroprognostication.
Collapse
|
2
|
Ratay C, Elmer J, Callaway CW, Flickinger KL, Coppler PJ. Brain computed tomography after resuscitation from in-hospital cardiac arrest. Resuscitation 2024; 198:110181. [PMID: 38492716 DOI: 10.1016/j.resuscitation.2024.110181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 03/05/2024] [Accepted: 03/08/2024] [Indexed: 03/18/2024]
Abstract
BACKGROUND Few data characterize the role of brain computed tomography (CT) after resuscitation from in-hospital cardiac arrest (IHCA). We hypothesized that identifying a neurological etiology of arrest or cerebral edema on brain CT are less common after IHCA than after resuscitation from out-of-hospital cardiac arrest (OHCA). METHODS We included all patients comatose after resuscitation from IHCA or OHCA in this retrospective cohort analysis. We abstracted patient and arrest clinical characteristics, as well as pH and lactate, to estimate systemic illness severity. Brain CT characteristics included quantitative measurement of the grey-to-white ratio (GWR) at the level of the basal ganglia and qualitative assessment of sulcal and cisternal effacement. We compared GWR distribution by stratum (no edema ≥1.30, mild-to-moderate <1.30 and >1.20, severe ≤1.20) and newly identified neurological arrest etiology between IHCA and OHCA groups. RESULTS We included 2,306 subjects, of whom 420 (18.2%) suffered IHCA. Fewer IHCA subjects underwent post-arrest brain CT versus OHCA subjects (149 (35.5%) vs 1,555 (82.4%), p < 0.001). Cerebral edema for IHCA versus OHCA was more often absent (60.1% vs. 47.5%) or mild-to-moderate (34.3% vs. 27.9%) and less often severe (5.6% vs. 24.6%). A neurological etiology of arrest was identified on brain CT in 0.5% of IHCA versus 3.2% of OHCA. CONCLUSIONS Although severe edema was less frequent in IHCA relative to OHCA, mild-to-moderate or severe edema occurred in one in three patients after IHCA. Unsuspected neurological etiologies of arrest were rarely discovered by CT scan in IHCA patients.
Collapse
Affiliation(s)
- Cecelia Ratay
- Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
| | - Jonathan Elmer
- Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Clifton W Callaway
- Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Katharyn L Flickinger
- Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Patrick J Coppler
- Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| |
Collapse
|
3
|
Case NP, Callaway CW, Elmer J, Coppler PJ. Simple approach to quantify hypoxic-ischemic brain injury severity from computed tomography imaging files after cardiac arrest. Resuscitation 2024; 195:110050. [PMID: 37977348 PMCID: PMC10922650 DOI: 10.1016/j.resuscitation.2023.110050] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Revised: 11/08/2023] [Accepted: 11/09/2023] [Indexed: 11/19/2023]
Abstract
BACKGROUND Grey-white ratio (GWR) can estimate severity of cytotoxic cerebral edema secondary to hypoxic-ischemic brain injury after cardiac arrest and predict progression to death by neurologic criteria (DNC). Current approaches to calculating GWR are not standardized and have variable interrater reliability. We tested if measures of variance of brain density on early computed tomographic (CT) imaging after cardiac arrest could predict DNC. METHODS We performed a retrospective cohort study, identifying post-arrest patients treated between 2011 and 2020 at our single center. We extracted demographic data from our registry and Digital Imaging and Communication in Medicine (DICOM) files for each patient's first brain CT. We analyzed slices 15-20 of each DICOM, corresponding to the level of the basal ganglia while accommodating differences in patient anatomy. We extracted pixel arrays and converted the radiodensities to Hounsfield units (HU). To focus on brain tissue densities, we excluded HU > 60 and < 10. We calculated the variance of each patient's HU distribution and the difference between the means of a two-group Gaussian finite mixture model. We compared these novel metrics to existing measures of cerebral edema, then randomly divided our data into 80% training and 20% test sets and used logistic regression to predict DNC. RESULTS Of 1,133 included subjects, 457 (40%) were female, mean (standard deviation) age was 58 (16) years, and 115 (10%) progressed to DNC. CTs were obtained a median [interquartile range] of 4.2 [2.8-5.7] hours post-arrest. Our novel measures correlated weakly with GWR. HU variance, but not difference between mixture model means, differed significantly between subjects with and without sulcal or cistern effacement. GWR outperformed our novel measures in predicting progression to DNC with an area under the receiver operating characteristic curve (AUC) of 0.82, compared to HU variance (AUC = 0.73) and the difference between mixture model means (AUC = 0.56). CONCLUSION There are differences in the distribution of HU on post-arrest CT in patients with qualitative measures of cerebral edema. Current methods to quantify cerebral edema outperform simple measures of attenuation variance on early brain CT. Further analyses could investigate if these measures of variance, or other distributional characteristics of brain density, have improved predictive performance on brain CTs obtained later in the clinical course or derived from discrete regions of anatomical interest.
Collapse
Affiliation(s)
- Nicholas P Case
- Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Clifton W Callaway
- Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jonathan Elmer
- Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Patrick J Coppler
- Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
| |
Collapse
|
4
|
Kim J, Lee JH. Quantitative cistern effacement and reduced gray to white matter ratio for prognostication in early brain computed tomography of patients with cardiac arrest. Heliyon 2024; 10:e23741. [PMID: 38187337 PMCID: PMC10767505 DOI: 10.1016/j.heliyon.2023.e23741] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Revised: 10/15/2023] [Accepted: 12/12/2023] [Indexed: 01/09/2024] Open
Abstract
Background The impact of cerebral edema on brain cells and ventricles in cardiac arrest patients can manifest as effacement of cortical sulci, diminished ventricle size, altered gray matter to white matter ratio (GWR), and increased optic nerve sheath diameter (ONSD) in brain CT scans. However, a complete investigation of GWR in whole lobes, quantitative cistern size, and comprehensive comparison of various brain CT parameters has not been conducted. This study aimed to comprehensively compare various early brain CT parameters along with conventional significant variables in relation to poor neurological outcome and diffuse cortical necrosis. Methods This retrospective study included 86 adult patients with cardiac arrest who underwent brain CT/MRI. GWRs, the distance of the posterior ambient cistern, and ONSD in early brain CT and regions of interest (ROIs) in brain MRI were measured and analyzed along with clinical characteristics. Results ROIs in the putamen and parietal white matter showed significant differences (p = 0.05, p = 0.022, respectively). The distance of the posterior ambient cistern and the GWR of the putamen and parietal white matter were newly developed predictors that were not used previously and demonstrated a significant correlation with the presence of diffuse cortical necrosis (OR 0.4, p = 0.006, AUC 0.637; OR 0.478, p = 0.02, AUC 0.603, respectively) or poor neurological outcomes (AUC 0.637, AUC 0.603, respectively), but were not more significant than pupil reflex (OR 0.06, p < 0.001). ONSD was not significantly associated with the outcomes. Conclusions Quantitative cistern effacement and reduced GWR of the putamen and parietal white matter in early brain CT measurements of cardiac arrest patients were promising predictors in early brain CT for prognostication, but compared with clinical characteristics, the clinical significance of the CT predictors was not considerable. The relationship and clinical significance between the parameters in early brain CT and the outcomes might have to be separately considered.
Collapse
Affiliation(s)
- Jinsung Kim
- Department of Emergency Medicine, Dong-A University College of Medicine, Busan, South Korea
| | - Jae Hoon Lee
- Department of Emergency Medicine, Dong-A University College of Medicine, Busan, South Korea
| |
Collapse
|
5
|
Bevers MB. Refining the continuum of neurologic prognosis - Predicting brain death after cardiac arrest. Resuscitation 2023; 192:109990. [PMID: 37805059 DOI: 10.1016/j.resuscitation.2023.109990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 09/27/2023] [Indexed: 10/09/2023]
Affiliation(s)
- Matthew B Bevers
- Division of Neurocritical Care, Brigham and Women's Hospital, Boston, MA, United States
| |
Collapse
|
6
|
Kitlen E, Kim N, Rubenstein A, Keenan C, Garcia G, Khosla A, Johnson J, Miller PE, Wira C, Greer D, Gilmore EJ, Beekman R. Development and validation of a novel score to predict brain death after out-of-hospital cardiac arrest. Resuscitation 2023; 192:109955. [PMID: 37661012 DOI: 10.1016/j.resuscitation.2023.109955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 08/21/2023] [Accepted: 08/27/2023] [Indexed: 09/05/2023]
Abstract
BACKGROUND AND OBJECTIVES Brain death (BD) occurs in 9-24% of successfully resuscitated out-of-hospital cardiac arrests (OHCA). To predict BD after OHCA, we developed a novel brain death risk (BDR) score. METHODS We identified independent predictors of BD after OHCA in a retrospective, single academic center cohort between 2011 and 2021. The BDR score ranges from 0 to 7 points and includes: non-shockable rhythm (1 point), drug overdose as etiology of arrest (1 point), evidence of grey-white differentiation loss or sulcal effacement on head computed tomography (CT) radiology report within 24 hours of arrest (2 points), Full-Outline-Of-UnResponsiveness (FOUR) score of 0 (2 points), FOUR score 1-5 (1 point), and age <45 years (1 point). We internally validated the BDR score using k-fold cross validation (k = 8) and externally validated the score at an independent academic center. The main outcome was BD. RESULTS The development cohort included 362OHCA patients, of whom 18% (N = 58) experienced BD. Internal validation provided an area under the receiving operator characteristic curve (AUC) (95% CI) of 0.931 (0.905-0.957). In the validation cohort, 19.8% (N = 17) experienced BD. The AUC (95% CI) was 0.849 (0.765-0.933). In both cohorts, a BDR score >4 was the optimal cut off (sensitivity 0.903 and 0.882, specificity 0.830 and 0.652, in the development and validation cohorts respectively). DISCUSSION The BDR score identifies those at highest risk for BD after OHCA. Our data suggest that a BDR score >4 is the optimal cut off.
Collapse
Affiliation(s)
- Eva Kitlen
- Department of Neurology, Yale School of Medicine, New Haven, CT, United States
| | - Noah Kim
- Department of Neurology, Yale School of Medicine, New Haven, CT, United States
| | - Alexandra Rubenstein
- Department of Neurology, Boston University Medical Center, Boston, MA, United States
| | - Caitlyn Keenan
- Department of Neurology, Boston University Medical Center, Boston, MA, United States
| | - Gabriella Garcia
- Department of Neurology, University of Pennsylvania, PA, United States
| | - Akhil Khosla
- Department of Pulmonary Critical Care, Yale School of Medicine, New Haven, CT, United States
| | | | - P Elliott Miller
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, United States
| | - Charles Wira
- Department of Emergency Medicine, Yale School of Medicine, New Haven, CT, United States
| | - David Greer
- Department of Neurology, Boston University Medical Center, Boston, MA, United States
| | - Emily J Gilmore
- Department of Neurology, Yale School of Medicine, New Haven, CT, United States
| | - Rachel Beekman
- Department of Neurology, Yale School of Medicine, New Haven, CT, United States.
| |
Collapse
|
7
|
Busl KM, Maciel CB. When the heart comes back but the brain is lost-are we ready to predict brain death after cardiac arrest? Resuscitation 2022; 179:256-258. [PMID: 36089161 DOI: 10.1016/j.resuscitation.2022.09.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 09/02/2022] [Indexed: 10/14/2022]
Affiliation(s)
- Katharina M Busl
- Department of Neurology, Division of Neurocritical Care, University of Florida College of Medicine, Gainesville, FL 32611, USA.
| | - Carolina B Maciel
- Department of Neurology, Division of Neurocritical Care, University of Florida College of Medicine, Gainesville, FL 32611, USA; Department of Neurology, Yale University School of Medicine, New Haven, CT 06520, USA; Department of Neurology, University of Utah, Salt Lake City, UT 84132, USA.
| |
Collapse
|