Early brain computed tomography findings are associated with outcome in patients treated with therapeutic hypothermia after out-of-hospital cardiac arrest

Neurological prognosis prediction for cardiac arrest patients using quantitative imaging biomarkers from brain computed tomography

PURPOSE

We aimed to predict the neurological prognosis of cardiac arrest (CA) patients using quantitative imaging biomarkers extracted from brain computed tomography images.

METHODS

We retrospectively enrolled 86 CA patients (good prognosis, 32; poor prognosis, 54) who were treated at three hospitals between 2017 and 2019. We then extracted 1131 quantitative imaging biomarkers from whole-brain and local volumes of interest in the computed tomography images of the patients. The data were split into training and test sets containing 60 and 26 samples, respectively, and the training set was used to select representative quantitative imaging biomarkers for classification. In univariate analysis, the classification was evaluated using the p-value of the Brunner-Munzel test and area under the receiver operating characteristic curve (AUC) for the test set. In multivariate analysis, machine learning models reflecting nonlinear and complex relations were trained, and they were evaluated using the AUC on the test set.

RESULTS

The best performance provided p = 0.009 (<0.01) and an AUC of 0.775 (95% confidence interval, 0.590-0.960) for the univariate analysis and an AUCof0.813 (95% confidence interval, 0.640-0.985) for the multivariate analysis. Overall, the gray level with the maximum gradient in the histogram of the three-dimensionally low-pass-filtered image was an important feature for prediction across the analyses.

CONCLUSIONS

Quantitative imaging biomarkers can be used in neurological prognosis prediction for CA patients. Relevant biomarkers may contribute to protocolized computed tomography image acquisition to ensure proper decision support in acute care.

Prognostic Implication of Ventricular Volumetry in Early Brain Computed Tomography after Cardiac Arrest

Brain swelling after cardiac arrest may affect brain ventricular volume. This study aimed to investigate the prognostic implications of ventricular volume on early thin-slice brain computed tomography (CT) after cardiac arrest. We measured the gray-to-white matter ratio (GWR) and the characteristics and volumes of the lateral, third, and fourth ventricles. The primary outcome was a poor 6-month neurological outcome. Of the 166 patients, 115 had a poor outcome. The fourth ventricle was significantly smaller in the poor outcome group (0.58 cm3 [95% CI, 0.43-0.80]) than in the good outcome group (0.74 cm3 [95% CI, 0.68-0.99], p < 0.001). Ventricular characteristics and other ventricular volumes did not differ between outcome groups. The area under the curve for the fourth ventricular volume was 0.68, comparable to 0.69 for GWR. Lower GWR (<1.09) and lower fourth ventricular volume (<0.41 cm3) predicted poor outcomes with 100% specificity and sensitivities of 8.7% (95% CI, 4.2-15.4) and 20.9% (95% CI, 13.9-29.4), respectively. Combining these measures improved the sensitivity to 25.2% (95% CI, 17.6-34.2). After adjusting for covariates, the fourth ventricular volume was independently associated with neurologic outcome. A marked decrease in fourth ventricular volume, with concomitant hypoattenuation on CT scans, more accurately predicted outcomes.

Prognostic performance of gray-white matter ratio in adult out-of-hospital cardiac arrest patients after receiving extracorporeal cardiopulmonary resuscitation

BACKGROUND

Gray-to-white matter ratio (GWR), measured by computed tomography (CT), is commonly used to predict poor neurological outcomes after out-of-hospital cardiac arrest (OHCA). The prognostic performance of GWR in OHCA patients receiving extracorporeal cardiopulmonary resuscitation (ECPR) is not known.

METHODS

This study is a secondary analysis of data from the SAVE-J II registry, a retrospective, multicenter study. Participants were divided into four groups according to average GWR (aGWR) values ranging from 1.00 to 1.39, separated by 0.1 intervals. The aGWR values were calculated for bilateral basal ganglia, centrum semiovale, and high convexity obtained by head CT within 24 h after ECPR. Primary outcome was poor neurological outcomes at 30-day.

RESULTS

In total, 1,146 OHCA patients treated with ECPR were included in our analysis. Overall, participants with lower aGWR more likely had poor neurological outcomes, aGWR 1.00-1.09 (94.6%), aGWR 1.10-1-19 (87.8%), aGWR 1.20-1.29 (78.5%), and aGWR 1.30-1.39 (70.3%). Multivariable logistic regression showed that lower aGWR was associated with poor neurological outcome at 30-day, aGWR 1.30-1.39: reference, aGWR 1.00-1.09: adjusted odds ratio (aOR) 10.01 (95% confidence interval (CI) [3.58-27.99]), aGWR 1.10-1.19: aOR 4.83 (95% CI [2.31-10.12]), aGWR 1.20-1.29: aOR 2.16 (95% CI [1.02-4.55]). Receiver operating characteristic curve analysis revealed that the prognostic performance of aGWR had an area under the curve of 0.628, 95% CI [0.59-0.66]). The aGWR threshold of 1.005 for predicting poor neurological outcome reached 100% specificity with 0.1% sensitivity.

CONCLUSION

Early neuro-prognostication depending on GWR may not be sufficient after ECPR and requires a multimodal approach.

Prognostic Performance of Initial Clinical Examination in Predicting Good Neurological Outcome in Cardiac Arrest Patients Treated with Targeted Temperature Management

Prognostication studies of cardiac arrest patients have mainly focused on poor neurological outcomes. However, an optimistic prognosis for good outcome could provide both justification to maintain and escalate treatment and evidence-based support to persuade family members or legal surrogates after cardiac arrest. The aim of the study was to evaluate the utility of clinical examinations performed after return of spontaneous circulation (ROSC) in predicting good neurological outcomes in out-of-hospital cardiac arrest (OHCA) patients treated with targeted temperature management (TTM). This retrospective study included OHCA patients treated with TTM from 2009 to 2021. Initial clinical examination findings related to the Glasgow coma scale (GCS) motor score, pupillary light reflex, corneal reflex (CR) and breathing above the set ventilator rate were assessed immediately after ROSC and before the initiation of TTM. The primary outcome was good neurological outcome at 6 months after cardiac arrest. Of 350 patients included in the analysis, 119 (34%) experienced a good neurological outcome at 6 months after cardiac arrest. Among the parameters of the initial clinical examinations, specificity was the highest for the GCS motor score, and sensitivity was the highest for breathing above the set ventilator rate. A GCS motor score of >2 had a sensitivity of 42.0% (95% confidence interval [CI] = 33.0-51.4) and a specificity of 96.5% (95% CI = 93.3-98.5). Breathing above the set ventilator rate had a sensitivity of 84.0% (95% CI = 76.2-90.1) and a specificity of 69.7% (95% CI = 63.3-75.6). As the number of positive responses increased, the proportion of patients with good outcomes increased. Consequently, 87.0% of patients for whom all four examinations were positive experienced good outcomes. As a result, the initial clinical examinations predicted good neurological outcomes with a sensitivity of 42.0-84.0% and a specificity of 69.7-96.5%. When more examinations with positive results are achieved, a good neurological outcome can be expected.

Deep learning-enabled detection of hypoxic-ischemic encephalopathy after cardiac arrest in CT scans: a comparative study of 2D and 3D approaches

Objective

To establish a deep learning model for the detection of hypoxic-ischemic encephalopathy (HIE) features on CT scans and to compare various networks to determine the best input data format.

Methods

168 head CT scans of patients after cardiac arrest were retrospectively identified and classified into two categories: 88 (52.4%) with radiological evidence of severe HIE and 80 (47.6%) without signs of HIE. These images were randomly divided into a training and a test set, and five deep learning models based on based on Densely Connected Convolutional Networks (DenseNet121) were trained and validated using different image input formats (2D and 3D images).

Results

All optimized stacked 2D and 3D networks could detect signs of HIE. The networks based on the data as 2D image data stacks provided the best results (S100: AUC: 94%, ACC: 79%, S50: AUC: 93%, ACC: 79%). We provide visual explainability data for the decision making of our AI model using Gradient-weighted Class Activation Mapping.

Conclusion

Our proof-of-concept deep learning model can accurately identify signs of HIE on CT images. Comparing different 2D- and 3D-based approaches, most promising results were achieved by 2D image stack models. After further clinical validation, a deep learning model of HIE detection based on CT images could be implemented in clinical routine and thus aid clinicians in characterizing imaging data and predicting outcome.

Recovery and Survival of Patients After Out-of-Hospital Cardiac Arrest: A Literature Review Showcasing the Big Picture of Intensive Care Unit-Related Factors

As an important public health issue, out-of-hospital cardiac arrest (OHCA) requires several stages of high quality medical care, both on-field and after hospital admission. Post-cardiac arrest shock can lead to severe neurological injury, resulting in poor recovery outcome and increased risk of death. These characteristics make this condition one of the most important issues to deal with in post-OHCA patients hospitalized in intensive care units (ICUs). Also, the majority of initial post-resuscitation survivors have underlying coronary diseases making revascularization procedure another crucial step in early management of these patients. Besides keeping myocardial blood flow at a satisfactory level, other tissues must not be neglected as well, and maintaining mean arterial pressure within optimal range is also preferable. All these procedures can be simplified to a certain level along with using targeted temperature management methods in order to decrease metabolic demands in ICU-hospitalized post-OHCA patients. Additionally, withdrawal of life-sustaining therapy as a controversial ethical topic is under constant re-evaluation due to its possible influence on overall mortality rates in patients initially surviving OHCA. Focusing on all of these important points in process of managing ICU patients is an imperative towards better survival and complete recovery rates.

Head-to-pelvis CT imaging after sudden cardiac arrest: Current status and future directions

Causes for sudden circulatory arrest (SCA) can vary widely making early treatment and triage decisions challenging. Additionally, cardiopulmonary resuscitation (CPR), while a life-saving link in the chain of survival, can be associated with traumatic injuries. Computed tomography (CT) can identify many causes of SCA as well as its sequelae. However, the diagnostic and therapeutic impact of CT in survivors of SCA has not been reviewed to date. This general review outlines the rationale and potential applications of focused head, chest, and abdomen/pelvis CT as well as comprehensive head-to-pelvis CT imaging after SCA. CT has a diagnostic yield approaching 30% to identify causes of SCA while the addition of ECG-gated chest CT provides further information about coronary anatomy and cardiac function. Risks of CT include radiation exposure, contrast-induced kidney injury, and incidental findings. This review's findings suggest that routine head-to-pelvis CT can yield clinically actional findings with the potential to improve clinical outcome after SCA that merits further investigation.

Electrocardiogram monitoring as a predictor of neurological and survival outcomes in patients with out-of-hospital cardiac arrest: a single-center retrospective observational study

Introduction

This study hypothesized that monitoring electrocardiogram (ECG) waveforms in patients with out-of-hospital cardiac arrest (OHCA) could have predictive value for survival or neurological outcomes. We aimed to establish a new prognostication model based on the single variable of monitoring ECG waveforms in patients with OHCA using machine learning (ML) techniques.

Methods

This observational retrospective study included successfully resuscitated patients with OHCA aged ≥ 18 years admitted to an intensive care unit in Japan between April 2010 and April 2020. Waveforms from ECG monitoring for 1 h after admission were obtained from medical records and examined. Based on the open-access PTB-XL dataset, a large publicly available 12-lead ECG waveform dataset, we built an ML-supported premodel that transformed the II-lead waveforms of the monitoring ECG into diagnostic labels. The ECG diagnostic labels of the patients in this study were analyzed for prognosis using another model supported by ML. The endpoints were favorable neurological outcomes (cerebral performance category 1 or 2) and survival to hospital discharge.

Results

In total, 590 patients with OHCA were included in this study and randomly divided into 3 groups (training set, n = 283; validation set, n = 70; and test set, n = 237). In the test set, our ML model predicted neurological and survival outcomes, with the highest areas under the receiver operating characteristic curves of 0.688 (95% CI: 0.682-0.694) and 0.684 (95% CI: 0.680-0.689), respectively.

Conclusion

Our ML predictive model showed that monitoring ECG waveforms soon after resuscitation could predict neurological and survival outcomes in patients with OHCA.

Explainable artificial intelligence-based prediction of poor neurological outcome from head computed tomography in the immediate post-resuscitation phase

Predicting poor neurological outcomes after resuscitation is important for planning treatment strategies. We constructed an explainable artificial intelligence-based prognostic model using head computed tomography (CT) scans taken immediately within 3 h of resuscitation from cardiac arrest and compared its predictive accuracy with that of previous methods using gray-to-white matter ratio (GWR). We included 321 consecutive patients admitted to our institution after resuscitation for out-of-hospital cardiopulmonary arrest with circulation resumption over 6 years. A machine learning model using head CT images with transfer learning was used to predict the neurological outcomes at 1 month. These predictions were compared with the predictions of GWR for multiple regions of interest in head CT using receiver operating characteristic (ROC)-area under curve (AUC) and precision recall (PR)-AUC. The regions of focus were visualized using a heatmap. Both methods had similar ROC-AUCs, but the machine learning model had a higher PR-AUC (0.73 vs. 0.58). The machine learning-focused area of interest for classification was the boundary between gray and white matter, which overlapped with the area of focus when diagnosing hypoxic- ischemic brain injury. The machine learning model for predicting poor outcomes had superior accuracy to conventional methods and could help optimize treatment.

Is gray-white matter ratio in out-of-hospital cardiac arrest patients' really early predictor of neurological outcome?

OBJECTIVE

This study aimed to evaluate the association between neurological outcome and gray-white ratio (GWR) in brain computed tomography (CT) in patients with return of spontaneous circulation (ROSC) who were brought to the emergency department (ED) due to out-of-hospital cardiac arrest (OHCA).

METHODS

This study has a retrospective design. Patients with ROSC who were brought to the ED due to OHCA and who underwent brain CT in the first 24 h were included in the study. Demographic data, brain CT results (intensities of gray matter and white matter in Hounsfield units and calculated GWR), and hospital outcome were recorded. The cerebral Performance Categories (CPC) score was used as the outcome of the study.

RESULTS

A total of 160 patients were included in the study. 55% of the patients were male and the median age was 75.5. The median brain CT time of the patients was 120 min. 16.3% of the patients were in the good neurological outcome group. When attenuation values and GWRs of the patients were compared according to CPC of patients (good-poor), no statistically significant difference was detected in any parameter except MC2 attenuation (P > 0.05 for all values). The patients were separated into groups geriatric and nongeriatric and GWRs were compared. GWRs were lower in the geriatric groups (P < 0.05 for all values).

CONCLUSION

Although it is emphasized in the literature that detection of low GWR in brain CT can help the clinical decision process in patients surviving comatose arrest, we think that it is not valid for especially in geriatric patients and in patients who underwent early brain CT after ROSC.

Can Optic Nerve Sheath Images on a Thin-Slice Brain Computed Tomography Reconstruction Predict the Neurological Outcomes in Cardiac Arrest Survivors?

We analyzed the prognostic performance of optic nerve sheath diameter (ONSD) on thin-slice (0.6 mm) brain computed tomography (CT) reconstruction images as compared to routine-slice (4 mm) images. We conducted a retrospective analysis of brain CT images taken within 2 h after cardiac arrest. The maximal ONSD (mONSD) and optic nerve sheath area (ONSA) were measured on thin-slice images, and the routine ONSD (rONSD) and gray-to-white matter ratio (GWR) were measured on routine-slice images. We analyzed their area under the receiver operator characteristic curve (AUC) and the cutoff values for predicting a poor 6-month neurological outcome (a cerebral performance category score of 3–5). Of the 159 patients analyzed, 113 patients had a poor outcome. There was no significant difference in rONSD between the outcome groups (p = 0.116). Compared to rONSD, mONSD (AUC 0.62, 95% CI: 0.54–0.70) and the ONSA (AUC 0.63, 95% CI: 0.55–0.70) showed better prognostic performance and had higher sensitivities to determine a poor outcome (mONSD, 20.4% [95% CI, 13.4–29.0]; ONSA, 16.8% [95% CI, 10.4–25.0]; rONSD, 7.1% [95% CI, 3.1–13.5]), with specificity of 95.7% (95% CI, 85.2–99.5). A combined cutoff value obtained by both the mONSD and GWR improved the sensitivity (31.0% [95% CI, 22.6–40.4]) of determining a poor outcome, while maintaining a high specificity. In conclusion, rONSD was clinically irrelevant, but the mONSD had an increased sensitivity in cutoff having acceptable specificity. Combination of the mONSD and GWR had an improved prognostic performance in these patients.

Brain Death and Its Prediction in Out-of-Hospital Cardiac Arrest Patients Treated with Targeted Temperature Management

Evolution toward brain death (BD) in out-of-hospital cardiac arrest patients with targeted temperature management (TTM) provides opportunities for organ donation. However, knowledge regarding BD in these patients is limited. We retrospectively analyzed the TTM registry of one hospital where life-sustaining therapy was not withdrawn. In-hospital death patients were categorized into BD and non-BD groups. We explored the process of evolution toward BD and its predictors by comparing the serial measurements of clinical variables and the results of various prognostic tests between the two groups. Of the 121 patients who died before hospital discharge, 19 patients (15.7%) developed BD at a median of 6 (interquartile range, 5.0–7.0) days after cardiac arrest. Four patients with pupillary light reflexes at 48 h eventually developed BD. The area under the curves of the gray-to-white matter ratio (GWR) on early brain computed tomography images and the level of S100 calcium-binding protein B (S100B) at 72 h were 0.67 (95% CI, 0.55–0.77) and 0.70 (95% CI, 0.55–0.83), respectively. In conclusion, approximately one-sixth of all in-hospital deaths were diagnosed with BD at a median of 6 days after cardiac arrest. The use of GWR and serial S100B measurements may help to screen potential BD.

Gray-White Matter Ratio at the Level of the Basal Ganglia as a Predictor of Neurologic Outcomes in Cardiac Arrest Survivors: A Literature Review

Loss of gray-white matter discrimination is the primary early imaging finding within of cranial computed tomography in cardiac arrest survivors, and this has been also regarded as a novel predictor for evaluating neurologic outcome. As displayed clearly on computed tomography and based on sensitivity to hypoxia, the gray-white matter ratio at basal ganglia (GWR-BG) region was frequently detected to assess the neurologic outcome by several studies. The specificity of GWR-BG is 72.4 to 100%, while the sensitivity is significantly different. Herein we review the mechanisms mediating cerebral edema following cardiac arrest, demonstrate the determination procedures with respect to GWR-BG, summarize the related researches regarding GWR-BG in predicting neurologic outcomes within cardiac arrest survivors, and discuss factors associated with predicting the accuracy of this methodology. Finally, we describe the effective measurements to increase the sensitivity of GWR-BG in predicting neurologic outcome.

Prognostication of neurologic outcome using gray-white-matter-ratio in comatose patients after cardiac arrest

Background

This study aimed to assess the prognostic value regarding neurologic outcome of CT neuroimaging based Gray-White-Matter-Ratio measurement in patients after resuscitation from cardiac arrest.

Methods

We retrospectively evaluated CT neuroimaging studies of 91 comatose patients resuscitated from cardiac arrest and 46 non-comatose controls. We tested the diagnostic performance of Gray-White-Matter-Ratio compared with established morphologic signs of hypoxic-ischaemic brain injury, e. g. loss of distinction between gray and white matter, and laboratory parameters, i. e. neuron-specific enolase, for the prediction of poor neurologic outcomes after resuscitated cardiac arrest. Primary endpoint was neurologic function assessed with cerebral performance category score 30 days after the index event.

Results

Gray-White-Matter-Ratio showed encouraging interobserver variability (ICC 0.670 [95% CI: 0.592–0.741] compared to assessment of established morphologic signs of hypoxic-ischaemic brain injury (Fleiss kappa 0.389 [95% CI: 0.320–0.457]) in CT neuroimaging studies. It correlated with cerebral performance category score with lower Gray-White-Matter-Ratios associated with unfavourable neurologic outcomes. A cut-off of 1.17 derived from the control population predicted unfavourable neurologic outcomes in adult survivors of cardiac arrest with 100% specificity, 50.3% sensitivity, 100% positive predictive value, and 39.3% negative predictive value. Gray-White-Matter-Ratio prognostic power depended on the time interval between circulatory arrest and CT imaging, with increasing sensitivity the later the image acquisition was executed.

Conclusions

A reduced Gray-White-Matter-Ratio is a highly specific prognostic marker of poor neurologic outcomes early after resuscitation from cardiac arrest. Sensitivity seems to be dependent on the time interval between circulatory arrest and image acquisition, with limited value within the first 12 h.

Differences in the gray-to-white matter ratio according to different computed tomography scanners for outcome prediction in post-cardiac arrest patients receiving target temperature management

The gray-to-white matter ratio (GWR) has been used to identify brain damage in comatose patients after cardiac arrest. However, Hounsfield units (HUs), the measurement of brain density on computed tomography (CT) images, may vary depending on the machine type or parameter. Therefore, differences in CT scanners may affect the GWR in post-cardiac arrest patients. We performed a retrospective study on comatose post-cardiac arrest patients who visited the hospital from 2007 to 2017. Two CT, Lightspeed and SOMATOM, scanners were used. Two observers independently measured the HUs of the caudate nucleus, putamen, posterior internal capsule, and corpus callosum using regions of interest. We compared the GWR calculated from the HUs measured at different CT scanners. The analysis of different scanners showed statistically significant differences in the measured HUs and GWR. The HUs and GWR of Lightspeed were measured lower than SOMATOM. The difference between the two CT scanners was also evident in groups divided by neurological prognosis. The area under the curve of the receiver operating characteristic curve to predict poor outcomes of Lightspeed was 0.798, and the cut-off value for 100% specificity was 1.172. The SOMATOM was 0.855, and the cut-off value was 1.269. The difference in scanners affects measurements and performance characteristics of the GWR in post-cardiac arrest patients. Therefore, when applying the results of the GWR study to clinical practice, reference values for each device should be presented, and an integrated plan should be prepared.

Predictive values of early head computed tomography for survival outcome after cardiac arrest in childhood: a pilot study

Predicting outcomes of children after cardiac arrest (CA) remains challenging. To identify useful prognostic markers for pediatric CA, we retrospectively analyzed the early findings of head computed tomography (CT) of patients. Subjects were non-traumatic, out-of-hospital CA patients < 16 years of age who underwent the first head CT within 24 h in our institute from 2006 to 2018 (n = 70, median age: 4 months, range 0–163). Of the 24 patients with return of spontaneous circulation, 14 survived up to 30 days after CA. The degree of brain damage was quantitatively measured with modified methods of the Alberta Stroke Program Early CT Score (mASPECTS) and simplified gray-matter-attenuation-to-white-matter-attenuation ratio (sGWR). The 14 survivors showed higher mASPECTS values than the 56 non-survivors (p = 0.035). All 3 patients with mASPECTS scores ≥ 20 survived, while an sGWR ≥ 1.14 indicated a higher chance of survival than an sGWR < 1.14 (54.5% vs. 13.6%). Follow-up magnetic resonance imaging for survivors validated the correlation of the mASPECTS < 15 with severe brain damage. Thus, low mASPECTS scores were associated with unfavorable neurological outcomes on the Pediatric Cerebral Performance Category scale. A quantitative analysis of early head CT findings might provide clues for predicting survival of pediatric CA.

Prognostic value of brainstem auditory and visual evoked potentials in cardiac arrest patients with targeted temperature management

PURPOSE

We analysed the prognostic value of somatosensory, brainstem auditory and visual evoked potentials (SSEPs, BAEPs and VEPs, respectively) for outcome prediction in cardiac arrest patients with targeted temperature management (TTM) and assessed whether BAEP and VEP measurements conferred added value to SSEP measurements.

METHODS

Cases with SSEPs and VEPs or BAEPs were reviewed in a TTM registry. We focused on whether the following responses were clearly discernible: N20 for SSEPs, V for BAEPs, and P100 for VEPs. Each type of evoked potential was classified as absent, present or indeterminable. Neurological outcomes after 6 months were dichotomized as good (Cerebral Performance Category [CPC] 1-2) or poor (CPC 3-5).

RESULTS

From 185 patients, 185 SSEPs, 172 BAEPs and 178 VEPs were included. None of the patients with a good outcome had absent SSEP, BAEP or VEP responses. Absent SSEP, BAEP and VEP responses yielded sensitivities of 42.3% (95% confidence interval [CI], 33.7-51.3%), 9.4% (95% CI, 4.6-16.7%) and 54.4% (95% CI, 46.0-62.5%) for poor outcomes, respectively. For the overall cohort, the addition of VEP measurements improved the sensitivities of single SSEP measurements (65.8% [95% CI, 57.7-73.3%] versus 36.2% [95% CI, 28.6-44.4%] and multimodal prognostication using SSEPs, brainstem reflex and brain computed tomography (75.7% [95% CI, 68.0-82.3%] versus 60.5% [95% CI, 52.3-68.4%]).

CONCLUSIONS

The prognostic value of VEPs was comparable to that of SSEPs, but the use of BAEPs was limited due to their low sensitivity. Additional VEP measurements can reduce prognostic uncertainty.

Prognostic Values of the Gray-to-White Matter Ratio on Brain Computed Tomography Images for Neurological Outcomes after Cardiac Arrest: A Meta-Analysis

Materials and Methods

The PubMed, ScienceDirect, Web of Science, and China National Knowledge Infrastructure databases were searched for all relevant articles published before March 31, 2020, without any language restrictions. The pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated with a random-effects model using Stata 14.0 software.

Result

A total of 24 eligible studies with 2812 CA patients were recruited in the meta-analysis. The pooled result showed that decreased GWR was correlated with poor neurological outcomes after CA (OR = 11.28, 95% CI: 6.29–20.21, and P < 0.001) with moderate heterogeneity (I² = 71.5%, P < 0.001). The pooled sensitivity and specificity were 0.58 (95% CI: 0.47–0.68) and 0.95 (95% CI: 0.87–0.98), respectively. The area under the curve (AUC) of GWR was 0.84 (95% CI: 0.80–0.87). Compared with GWR (cerebrum) and GWR (average), GWR using the basal ganglion level of brain CT had the highest AUC of 0.87 (0.84–0.90). Subgroup analysis indicated that heterogeneity may be derived from the time of CT measurement, preset specificity, targeted temperature management, or proportion of cardiac etiology. Sensitivity analysis indicated that the result was stable, and Deeks' plot showed no possible publication bias (P = 0 .64).

Conclusion

Current research suggests that GWR, especially using the basal ganglion level of brain CT, is a useful parameter for determining neurological outcomes after CA.

Utility of brain parenchyma density measurement and computed tomography perfusion imaging in predicting brain death

Purpose

To assess the utility of brain parenchyma density measurement on unenhanced computed tomography (CT) in predicting brain death (BD), in order to evaluate the added value of CT perfusion (CTP).

Material and methods

A total of 77 patients who were clinically diagnosed as BD and had both CT angiography (CTA) and CTP imaging in the same session were retrospectively reviewed. On unenhanced phase of CTA, density measurement was performed from 23 regions of interests (ROIs) which were located in the following areas: level of basal ganglia (caudate nucleus, putamen, corpus callosum, posterior limb of internal capsule), level of brainstem, grey- white matters on levels of centrum semiovale (CS), high convexity (HC), and cerebellum. CTP images were evaluated qualitatively and independently. Grey matter (GM), white matter (WM), density, and GM/WM density ratio of BD patients were compared with control subjects.

Results

Comparing with the normal control group, the GM and WM density at each level and GM/WM density ratio of CS, HC, and cerebellum level were significantly lower in brain-dead patients (p = 0.019 for HC-WM, p < 0.001 for other areas). Using ROC analysis, the highest value of area under curve (AUC) for the GM/WM density ratio was found at the HC level (AUC = 0.907). The sensitivity of the GM/WM density ratio at the HC level was found to be 90% when the cut-off value of 1.25 was identified. Evaluating the GM/WM density ratio together with the CTP results increased the sensitivity further to 98%.

Conclusions

The GM/WM density ratio at the HC level on unenhanced CT may be a useful finding to predict BD. Also, the addition of CTP increases the sensitivity of this method.

Adult Advanced Life Support: 2020 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science with Treatment Recommendations

This 2020 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations for advanced life support includes updates on multiple advanced life support topics addressed with 3 different types of reviews. Topics were prioritized on the basis of both recent interest within the resuscitation community and the amount of new evidence available since any previous review. Systematic reviews addressed higher-priority topics, and included double-sequential defibrillation, intravenous versus intraosseous route for drug administration during cardiac arrest, point-of-care echocardiography for intra-arrest prognostication, cardiac arrest caused by pulmonary embolism, postresuscitation oxygenation and ventilation, prophylactic antibiotics after resuscitation, postresuscitation seizure prophylaxis and treatment, and neuroprognostication. New or updated treatment recommendations on these topics are presented. Scoping reviews were conducted for anticipatory charging and monitoring of physiological parameters during cardiopulmonary resuscitation. Topics for which systematic reviews and new Consensuses on Science With Treatment Recommendations were completed since 2015 are also summarized here. All remaining topics reviewed were addressed with evidence updates to identify any new evidence and to help determine which topics should be the highest priority for systematic reviews in the next 1 to 2 years.

Adult Advanced Life Support: 2020 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations

This 2020 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations for advanced life support includes updates on multiple advanced life support topics addressed with 3 different types of reviews. Topics were prioritized on the basis of both recent interest within the resuscitation community and the amount of new evidence available since any previous review. Systematic reviews addressed higher-priority topics, and included double-sequential defibrillation, intravenous versus intraosseous route for drug administration during cardiac arrest, point-of-care echocardiography for intra-arrest prognostication, cardiac arrest caused by pulmonary embolism, postresuscitation oxygenation and ventilation, prophylactic antibiotics after resuscitation, postresuscitation seizure prophylaxis and treatment, and neuroprognostication. New or updated treatment recommendations on these topics are presented. Scoping reviews were conducted for anticipatory charging and monitoring of physiological parameters during cardiopulmonary resuscitation. Topics for which systematic reviews and new Consensuses on Science With Treatment Recommendations were completed since 2015 are also summarized here. All remaining topics reviewed were addressed with evidence updates to identify any new evidence and to help determine which topics should be the highest priority for systematic reviews in the next 1 to 2 years.

Neurologic prognostication after resuscitation from cardiac arrest

Out-of-hospital cardiac arrest remains a leading cause of mortality in the United States, and the majority of patients who die after achieving return of spontaneous circulation die from withdrawal of care due to a perceived poor neurologic prognosis. Unfortunately, withdrawal of care often occurs during the first day of admission and research suggests this early withdrawal of care may be premature and result in unnecessary deaths for patients who would have made a full neurologic recovery. In this review, we explore the evidence for neurologic prognostication in the emergency department for patients who achieve return of spontaneous circulation after an out-of-hospital cardiac arrest.

Neuron-specific enolase and neuroimaging for prognostication after cardiac arrest treated with targeted temperature management

BACKGROUND

Prognostication after cardiac arrest (CA) needs a multimodal approach, but the optimal method is not known. We tested the hypothesis that the combination of neuron-specific enolase (NSE) and neuroimaging could improve outcome prediction after CA treated with targeted temperature management (TTM).

METHODS

A retrospective observational cohort study was performed on patients who underwent at least one NSE measurement between 48 and 72 hr; received both a brain computed tomography (CT) scan within 24 hr and diffusion-weighted magnetic resonance imaging (DW-MRI) within 7 days after return of spontaneous circulation (ROSC); and were treated with TTM after out-of-hospital CA between 2009 and 2017 at the Seoul St. Mary's Hospital in Korea. The primary outcome was a poor neurological outcome at 6 months after CA, defined as a cerebral performance category of 3-5.

RESULTS

A total of 109 subjects underwent all three tests and were ultimately included in this study. Thirty-four subjects (31.2%) experienced good neurological outcomes at 6 months after CA. The gray matter to white matter attenuation ratio (GWR) was weakly correlated with the mean apparent diffusion coefficient (ADC), PV400 and NSE (Spearman's rho: 0.359, -0.362 and -0.263, respectively). NSE was strongly correlated with the mean ADC and PV400 (Spearman's rho: -0.623 and 0.666, respectively). Serum NSE had the highest predictive value among the single parameters (area under the curve (AUC) 0.912, sensitivity 70.7% for maintaining 100% specificity). The combination of a DWI parameter (mean ADC or PV400) and NSE had better prognostic performance than the combination of the CT parameter (GWR) and NSE. The addition of the GWR to a DWI parameter and NSE did not improve the prediction of neurological outcomes.

CONCLUSION

The GWR (≤ 24 hr) is weakly correlated with the mean ADC (≤ 7 days) and NSE (highest between 48 and 72 hr). The combination of a DWI parameter and NSE has better prognostic performance than the combination of the GWR and NSE. The addition of the GWR to a DWI parameter and NSE does not improve the prediction of neurological outcomes after CA treatment with TTM.

Prediction of poor neurological outcome in comatose survivors of cardiac arrest: a systematic review

Purpose

To assess the ability of clinical examination, blood biomarkers, electrophysiology, or neuroimaging assessed within 7 days from return of spontaneous circulation (ROSC) to predict poor neurological outcome, defined as death, vegetative state, or severe disability (CPC 3–5) at hospital discharge/1 month or later, in comatose adult survivors from cardiac arrest (CA).

Methods

PubMed, EMBASE, Web of Science, and the Cochrane Database of Systematic Reviews (January 2013–April 2020) were searched. Sensitivity and false-positive rate (FPR) for each predictor were calculated. Due to heterogeneities in recording times, predictor thresholds, and definition of some predictors, meta-analysis was not performed.

Results

Ninety-four studies (30,200 patients) were included. Bilaterally absent pupillary or corneal reflexes after day 4 from ROSC, high blood values of neuron-specific enolase from 24 h after ROSC, absent N20 waves of short-latency somatosensory-evoked potentials (SSEPs) or unequivocal seizures on electroencephalogram (EEG) from the day of ROSC, EEG background suppression or burst-suppression from 24 h after ROSC, diffuse cerebral oedema on brain CT from 2 h after ROSC, or reduced diffusion on brain MRI at 2–5 days after ROSC had 0% FPR for poor outcome in most studies. Risk of bias assessed using the QUIPS tool was high for all predictors.

Conclusion

In comatose resuscitated patients, clinical, biochemical, neurophysiological, and radiological tests have a potential to predict poor neurological outcome with no false-positive predictions within the first week after CA. Guidelines should consider the methodological concerns and limited sensitivity for individual modalities. (PROSPERO CRD42019141169)

Electronic supplementary material

The online version of this article (10.1007/s00134-020-06198-w) contains supplementary material, which is available to authorized users.

Is jugular bulb oximetry monitoring associated with outcome in out of hospital cardiac arrest patients?

Cerebral protection against secondary hypoxic-ischemic brain injury is a key priority area in post-resuscitation intensive care management in survivors of cardiac arrest. Nevertheless, the current understanding of the incidence, diagnosis and its’ impact on neurological outcome remains undetermined. The aim of this study was to evaluate jugular bulb oximetry as a potential monitoring modality to detect the incidences of desaturation episodes during post-cardiac arrest intensive care management and to evaluate their subsequent impact on neurological outcome. We conducted a prospective, observational study in unconscious adult patients admitted to the intensive care unit who had successful resuscitation following out of hospital cardiac arrest of presumed cardiac causes. All the patients were treated as per European Resuscitation Council 2015 guidelines and they received jugular bulb catheter. Jugular bulb oximetry measurements were performed at six hourly intervals. The neurological outcomes were evaluated on 90th day after the cardiac arrest by cerebral performance categories scale. Forty patients met the eligibility criteria. Measurements of jugular venous oxygen saturation were performed for 438 times. Altogether, we found 2 incidences of jugular bulb oxygen saturation less than 50% (2/438; 0.46%), and 4 incidences when it was less than 55% (4/438; 0.91%). The study detected an association between SjVO₂ and CO₂ (r = 0.26), each 1 kPa increase in CO₂ led to an increase in SjvO₂ by 3.4% + / − 0.67 (p < 0.0001). There was no association between SjvO₂ and PaO₂ or SjvO₂ and MAP. We observed a statistically significant higher mean SjvO₂ (8.82% + / − 2.05, p < 0.0001) in unfavorable outcome group. The episodes of brain hypoxia detected by jugular bulb oxygen saturation were rare during post-resuscitation intensive care management in out of hospital cardiac arrest patients. Therefore, this modality of monitoring may not yield any additional information towards prevention of secondary hypoxic ischemic brain injury in post cardiac arrest survivors. Other factors contributing towards high jugular venous saturation needs to be considered.

Early outcome prediction with quantitative pupillary response parameters after out-of-hospital cardiac arrest: A multicenter prospective observational study​

We aimed to determine the characteristics of quantitative pupillary response parameters other than amplitude of pupillary light reflex (PLR) early after return of spontaneous circulation (ROSC) and their implications for predicting neurological outcomes early after cardiac arrest (CA). Fifty adults resuscitated after non-traumatic out-of-hospital CA from four emergency hospitals were enrolled. Pupil diameters, PLR, constriction velocity (CV), maximum CV (MCV), dilation velocity (DV), latency of constriction, and Neurological Pupil index (NPi) were quantitatively measured at 0, 6, 12, 24, 48, and 72 h post-ROSC using an automated pupillometer. Change over time of each parameter was compared between favorable (Cerebral Performance Category [CPC] 1 or 2) and unfavorable neurological outcome (CPC 3–5) groups. Prognostic values of 90-day favorable outcome by these parameters and when combined with clinical predictors (witness status, bystander cardiopulmonary resuscitation, initial shockable rhythm, implementation of target temperature management) were tested. Thirteen patients achieved favorable outcome. CV, MCV, DV (P < 0.001), and NPi (P = 0.005) were consistently greater in the favorable group than in the unfavorable outcome group. Change over time was not statistically different between the groups in all parameters. CV, MCV, DV (ρ = 0.96 to 0.97, P < 0.001, respectively), and NPi (ρ = 0.65, P < 0.001) positively correlated with PLR. The prognostic value of 0-hour CV (area under the curve, AUC [95% confidence interval]: 0.92 [0.80–1.00]), DV (0.84 [0.68–0.99]), and NPi (0.88 [0.74–1.00]) was equivalent to that of PLR (0.84 [0.69–0.98]). Prognostic values improved to AUC of 0.95–0.96 when 0-hour PLR, CV, DV, or NPi was combined with clinical predictors. The 0-hour CV, MCV, and NPi showed equivalent prognostic values to PLR alone/in combination with clinical predictors. Using PLR among several quantitative pupillary response parameters for early neurological prognostication of post-CA patients is a simple and effective strategy.

Prognosis Value of Gray-White-Matter Ratios in Comatose Survivors After In-Hospital Cardiac Arrest

BACKGROUND

The gray-white-matter ratio (GWR) measured on cerebral non-contrasted computed tomography (NCCT) has been reported to help the prognostication of mortality or comatose status of out-of-hospital cardiac arrest (OHCA) victims. Since the etiologies and resuscitative process differ significantly between patients with OHCA and in-hospital cardiac arrest (IHCA), the predictive ability of GWR in IHCA survivors remains unclear.

METHODS

This retrospective observational study conducted in a single tertiary medical center in Taiwan enrolled all the non-traumatic IHCA adults with sustained return of spontaneous circulation (ROSC) and had received cerebral NCCT examination within 24 hours following cardiac arrest. The GWR of survivor and non-survivor as well as good and poor neurological outcome were analyzed.

RESULTS

A total of 79 IHCA patients with 68.4% in male gender and mean age of 66-year-old were enrolled in the current study. 34 patients (43.0%) survived to hospital discharge and 20 patients (25.3%) were discharged with good neurological outcome. The median GWR of patients with good and poor outcomes in either aspect of survival or neurological function did not show significant difference. The area under the plotted receiver of characteristic curves of each GWR also did not show satisfactory predictive performance.

CONCLUSIONS

The use of GWR for outcome prognosis of patients in emergency department whom progressed to circulatory failure did not show promising result.

Imaging for Neuroprognostication After Cardiac Arrest: Systematic Review and Meta-analysis

BACKGROUND

Predicting neurological outcome in comatose survivors of cardiac arrest relies on clinical findings, radiological and neurophysiological test results. To evaluate the predictive accuracy of brain computed tomography (CT) and magnetic resonance imaging (MRI) for prognostication of neurological outcomes after cardiac arrest.

METHODS

We searched MEDLINE (database inception to August 2018) and included all observational cohort studies or randomized controlled trials including adult (16 years or older) survivors of cardiac arrest which evaluated the diagnostic accuracy of CT or MRI for predicting neurologic outcome or mortality. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. All review stages were conducted independently by 2 reviewers, and where possible data were pooled using bivariate meta-analysis. The main outcome was to evaluate the of accuracy of CT and MRI in neuroprognostication of patients after cardiac arrest.

RESULTS

We included 44 studies that examined brain CT (n = 24) or MRI (n = 21) in 4008 (n per study, 9-398) patients. Decreased grey to white matter ratio on CT (20 studies) was useful for predicting poor neurological outcome (sensitivity 0.44, 95% CI 0.29-0.60; specificity 0.97, 95% CI 0.93-0.99; positive likelihood ratio [LR+] 13.8, 95% CI 6.9-27.7). Similarly, diffusion-weighted imaging (DWI) on MRI (16 studies; sensitivity 0.77, 95% CI 0.65-0.85; specificity 0.92, 95% CI 0.85-0.96; LR+ 9.2, 95% CI 5.2-16.4) and DWI and fluid-attenuated inversion recovery (FLAIR) MRI (4 studies, sensitivity 0.70, 95% CI 0.43-0.88; specificity 0.95, 95% CI 0.79-0.99; LR+ 13.4, 95% CI 3.5-51.2) were useful for predicting poor neurological outcomes. We found marked heterogeneity in timing of radiological examinations and neurological assessments relative to the cardiac arrest.

CONCLUSION

Decreased grey to white matter ratio on CT and DWI or DWI and FLAIR on MRI are useful adjuncts for predicting poor early neurological outcome after cardiac arrest.

Potential impacts of a novel integrated extracorporeal-CPR workflow using an interventional radiology and immediate whole-body computed tomography system in the emergency department

Extracorporeal cardiopulmonary resuscitation (ECPR) can be associated with increased survival and neurologic benefits in selected patients with out-of-hospital cardiac arrest (OHCA). However, there remains insufficient evidence to recommend the routine use of ECPR for patients with OHCA. A novel integrated trauma workflow concept that utilizes a sliding computed tomography (CT) scanner and interventional radiology (IR) system, named a hybrid emergency room system (HERS), allowing emergency therapeutic interventions and CT examination without relocating trauma patients, has recently evolved in Japan. HERS can drastically shorten the ECPR implementation time and more quickly facilitate definitive interventions than the conventional advanced cardiovascular life support workflow. Herein, we discuss our novel workflow concept using HERS on ECPR for patients with OHCA.

Brain computed tomography angiography in postcardiac arrest patients and neurologic outcome

Objective

This study aimed to analyze intracranial vessels using brain computed tomography angiography (CTA) and scoring systems to diagnose brain death and predict poor neurologic outcomes of postcardiac arrest patients.

Methods

Initial brain CTA images of postcardiac arrest patients were analyzed using scoring systems to determine a lack of opacification and diagnose brain death. The primary outcome was poor neurologic outcome, which was defined as cerebral performance category score 3 to 5. The frequency, sensitivity, specificity, positive predictive value, negative predictive value, and area under receiver operating characteristic curve for the lack of opacification of each vessel and for each scoring system used to predict poor neurologic outcomes were determined.

Results

Patients with poor neurologic outcomes lacked opacification of the intracranial vessels, most commonly in the vein of Galen, both internal cerebral veins, and the mid cerebral artery (M4). The 7-score results (P=0.04) and 10-score results were significantly different (P=0.04) between outcome groups, with an area under receiver operating characteristic of 0.61 (range, 0.48 to 0.72). The lack of opacification of each intracranial vessel and all scoring systems exhibited high specificity (100%) and positive predictive values (100%) for predicting poor neurologic outcomes.

Conclusion

Lack of opacification of vessels on brain CTA exhibited high specificity for predicting poor neurologic outcomes of patients after cardiac arrest.

Prediction of poor outcome after hypoxic-ischemic brain injury by diffusion-weighted imaging: A systematic review and meta-analysis

Accurate prediction of the neurological outcome following hypoxic-ischemic brain injury (HIBI) remains difficult. Diffusion-weighted imaging (DWI) can detect acute and subacute brain abnormalities following global cerebral hypoxia. Therefore, DWI can be used to predict the outcomes of HIBI. To this end, we searched the PubMed, EMBASE, and Cochrane Library databases for studies that examine the diagnostic accuracy of DWI in predicting HIBI outcomes in adult patients between January1995 and September 2019. Next, we conducted a comprehensive meta-analysis using the Meta-DiSc and several complementary techniques. Following the application of inclusion and exclusion criteria, a total of 28 studies were included with 98 data subsets. The overall sensitivity and specificity, with 95% confidence interval, were 0.613(0.599-0.628) and 0.958(0.947-0.967), respectively, and the area under the curve was 0.9090. Significant heterogeneity among the included studies and a threshold effect were observed (p<0.001). Different positive indices were the major sources for the heterogeneity, followed by the anatomical region examined, both of which significantly affected the prognostic accuracy. In conclusion, we demonstrated that DWI can be an instrumental modality in predicting the outcome of HIBI with good prognostic accuracy. However, the lack of clear and generally accepted positive indices limits its clinical application. Therefore, using more reliable positive indices and combining DWI with other clinical predictors may improve the diagnostic accuracy of HIBI.

The Influence of Therapeutics on Prognostication After Cardiac Arrest

PURPOSE OF REVIEW

The goal of this review is to highlight the influence of therapeutic maneuvers on neuro-prognostication measures administered to comatose survivors of cardiac arrest. We focus on the effect of sedation regimens in the setting of targeted temperature management (TTM), one of the principle interventions known to improve neurological recovery after cardiac arrest. Further, we discuss the critical need for novel markers, as well as refinement of existing markers, among patients receiving extracorporeal membrane oxygenation (ECMO) in the setting of failed conventional resuscitation, known as extracorporeal cardiopulmonary resuscitation (ECPR).

RECENT FINDINGS

Automated pupillometry may have some advantage over standard pupillary examination for prognostication following TTM, sedation, or the use of ECMO after cardiac arrest. New serum biomarkers such as Neurofilament light chain have shown good predictive abilities and need further validation in these populations. There is a high-level uncertainty in brain death declaration protocols particularly related to apnea testing and appropriate ancillary tests in patients receiving ECMO. Both sedation and TTM alone and in combination have been shown to affect prognostic markers to varying degrees. The optimal approach to analog-sedation is unknown, and requires further study. Moreover, validation of known prognostic markers, as well as brain death declaration processes in patients receiving ECMO is warranted. Data on the effects of TTM, sedation, and ECMO on biomarkers (e.g., neuron-specific enolase) and electrophysiology measures (e.g., somatosensory-evoked potentials) is sparse. The best approach may be one customized to the individual patient, a precision-medicine approach.

Management of Out-of-Hospital Cardiac Arrest Complicating Acute Coronary Syndromes

PURPOSE OF THE REVIEW

Out-of-hospital cardiac arrest (OHCA) complicating acute coronary syndromes (ACS) continues to carry a high rate of morbidity and mortality despite significant advances in EMS and interventional cardiology services. In this review, we discuss an evidence-based approach to the initial care and management of patients with OHCA complicating ACS from the pre-hospital response and initial resuscitation strategy, to advanced therapies such as coronary angiography, targeted-temperature management, neuro-prognostication, and care of the post-arrest patient.

RECENT FINDINGS

Early recognition of cardiac arrest and prompt initiation of bystander CPR are the most important factors associated with improved survival. A comprehensive and coordinated approach to in-hospital management, including PCI, targeted temperature management, critical care, and hemodynamic support represents a significant critical link in the chain of survival. OHCA complicated by ACS continues to be one of the most challenging disease states facing healthcare practitioners and maintains a high mortality rate despite substantial advancements in healthcare delivery. A comprehensive approach to in-hospital management and further exploration of novel interventions, including ECMO, may yield opportunities to optimize care and improve outcomes for cardiac arrest patients.

Timing of brain computed tomography and accuracy of outcome prediction after cardiac arrest

AIM

Gray-white-matter ratio (GWR) calculated from head CT is a radiologic index of tissue changes associated with hypoxic-ischemic encephalopathy after cardiac arrest (CA). Evidence from previous studies indicates high specificity for poor outcome prediction at GWR thresholds of 1.10-1.20. We aimed to determine the relationship between accuracy of neurologic prognostication by GWR and timing of CT.

METHODS

We included 195 patients admitted to the ICU following CA. GWR was calculated from CT radiologic densities in 16 regions of interest. Outcome was determined upon intensive care unit discharge using the cerebral performance category (CPC). Accuracy of outcome prediction of GWR was compared for 3 epochs (<6, 6-24, and >24 h after CA).

RESULTS

125 (64%) patients had poor (CPC4-5) and 70 (36%) good outcome (CPC1-3). Irrespective of timing, specificity for poor outcome prediction was 100% at a GWR threshold of 1.10. Among 50 patients with both early and late CT, GWR decreased significantly over time (p = 0.002) in patients with poor outcome, sensitivity for poor outcome prediction was 12% (7-20%) with early CTs (<6 h) and 48% (38-58%) for late CTs (>24 h). Across all patients, sensitivity of early and late CT was 17% (9-28%) and 39% (28-51%), respectively.

CONCLUSION

A GWR below 1.10 predicts poor outcome (CPC4-5) in patients after CA with high specificity irrespective of time of acquisition of CT. Because GWR decreases over time in patients with severe HIE, sensitivity for prediction of poor outcome is higher for late CTs (>24 h after CA) as compared to early CTs (<6 h after CA).

Changes in the gray and white matter of patients with ischemic-edematous insults after traumatic brain injury

OBJECTIVE

Gray matter (GM) and white matter (WM) are vulnerable to ischemic-edematous insults after traumatic brain injury (TBI). The extent of secondary insult after brain injury is quantifiable using quantitative CT analysis. One conventional quantitative CT measure, the gray-white matter ratio (GWR), and a more recently proposed densitometric analysis are used to assess the extent of these insults. However, the prognostic capacity of the GWR in patients with TBI has not yet been validated. This study aims to test the prognostic value of the GWR and evaluate the alternative parameters derived from the densitometric analysis acquired during the acute phase of TBI. In addition, the prognostic ability of the conventional TBI prognostic models (i.e., IMPACT [International Mission for Prognosis and Analysis of Clinical Trials in TBI] and CRASH [Corticosteroid Randomisation After Significant Head Injury] models) were compared to that of the quantitative CT measures.

METHODS

Three hundred patients with TBI of varying ages (92 pediatric, 94 adult, and 114 geriatric patients) and admitted between 2008 and 2013 were included in this retrospective cohort study. The normality of the density of the deep GM and whole WM was evaluated as the proportion of CT pixels with Hounsfield unit values of 31-35 for GM and 26-30 for WM on CT images of the entire supratentorial brain. The outcome was evaluated using the Glasgow Outcome Scale (GOS) at discharge (GOS score ≤ 3, n = 100).

RESULTS

Lower proportions of normal densities in the deep GM and whole WM indicated worse outcomes. The proportion of normal WM exhibited a significant prognostic capacity (area under the curve [AUC] = 0.844). The association between the outcome and the normality of the WM density was significant in adult (AUC = 0.792), pediatric (AUC = 0.814), and geriatric (AUC = 0.885) patients. In pediatric patients, the normality of the overall density and the density of the GM were indicative of the outcome (AUC = 0.751). The average GWR was not associated with the outcome (AUC = 0.511). IMPACT and CRASH models showed adequate and reliable performance in the pediatric and geriatric groups but not in the adult group. The highest overall predictive performance was achieved by the densitometry-augmented IMPACT model (AUC = 0.881).

CONCLUSIONS

Both deep GM and WM are susceptible to ischemic-edematous insults during the early phase of TBI. The extent of the secondary injury was better evaluated by analyzing the normality of the deep GM and WM rather than by calculating the GWR.

Cerebral Edema After Cardiopulmonary Resuscitation: A Therapeutic Target Following Cardiac Arrest?

We sought to review the role that cerebral edema plays in neurologic outcome following cardiac arrest, to understand whether cerebral edema might be an appropriate therapeutic target for neuroprotection in patients who survive cardiopulmonary resuscitation. Articles indexed in PubMed and written in English. Following cardiac arrest, cerebral edema is a cardinal feature of brain injury and is a powerful prognosticator of neurologic outcome. Like other conditions characterized by cerebral ischemia/reperfusion, neuroprotection after cardiac arrest has proven to be difficult to achieve. Neuroprotection after cardiac arrest generally has focused on protecting neurons, not the microvascular endothelium or blood-brain barrier. Limited preclinical data suggest that strategies to reduce cerebral edema may improve neurologic outcome. Ongoing research will be necessary to determine whether targeting cerebral edema will improve patient outcomes after cardiac arrest.

Prognostication via early computed tomography head in patients treated with targeted temperature management after cardiac arrest

BACKGROUND

We evaluated computed tomography head (CTH) imaging obtained prior to targeted temperature management (TTM) in patients after cardiac arrest, and its role in prognostication.

METHODS

In this retrospective cohort study in a tertiary-care hospital, 341 adults presenting with out-of-hospital cardiac arrest received a CTH prior to TTM. Associations between outcomes and neuroimaging variables were evaluated with Chi-square analysis for significant associations that yielded a composite neuroimaging score-Tennessee Early Neuroimaging Score (TENS). Univariable and multivariable logistic regression analysis including TENS as an independent variable and the four outcome dependent variables were analyzed.

RESULTS

Four of the neuroimaging variables-sulcal effacement, partial gray-white matter effacement, total gray-white matter effacement, deep nuclei effacement-had significant associations with each of the four outcome variables and yielded TENS. In multivariable logistic regression models adjusted for potential confounders, TENS was associated with poor discharge CPC (OR 2.15, 95%CI 1.16-3.98, p = .015), poor disposition (OR 2.62, 95%CI 1.37-5.02, p = .004), in-hospital mortality (OR 1.99, 95%CI 1.09-3.62, p = .024), and ICU mortality (OR 1.89, 95%CI 1.12-3.20, p = .018).

CONCLUSION

Imaging prior to TTM may help identify post-cardiac arrest patients with severe anoxic brain injury and poor outcomes.

Standards for Studies of Neurological Prognostication in Comatose Survivors of Cardiac Arrest: A Scientific Statement From the American Heart Association

Significant improvements have been achieved in cardiac arrest resuscitation and postarrest resuscitation care, but mortality remains high. Most of the poor outcomes and deaths of cardiac arrest survivors have been attributed to widespread brain injury. This brain injury, commonly manifested as a comatose state, is a marker of poor outcome and a major basis for unfavorable neurological prognostication. Accurate prognostication is important to avoid pursuing futile treatments when poor outcome is inevitable but also to avoid an inappropriate withdrawal of life-sustaining treatment in patients who may otherwise have a chance of achieving meaningful neurological recovery. Inaccurate neurological prognostication leading to withdrawal of life-sustaining treatment and deaths may significantly bias clinical studies, leading to failure in detecting the true study outcomes. The American Heart Association Emergency Cardiovascular Care Science Subcommittee organized a writing group composed of adult and pediatric experts from neurology, cardiology, emergency medicine, intensive care medicine, and nursing to review existing neurological prognostication studies, the practice of neurological prognostication, and withdrawal of life-sustaining treatment. The writing group determined that the overall quality of existing neurological prognostication studies is low. As a consequence, the degree of confidence in the predictors and the subsequent outcomes is also low. Therefore, the writing group suggests that neurological prognostication parameters need to be approached as index tests based on relevant neurological functions that are directly related to the functional outcome and contribute to the quality of life of cardiac arrest survivors. Suggestions to improve the quality of adult and pediatric neurological prognostication studies are provided.

Management of Comatose Survivors of Cardiac Arrest

PURPOSE OF REVIEW

Because the whole-body ischemia-reperfusion insult associated with cardiac arrest often results in brain injury, neurologists perform an important role in postresuscitation cardiac arrest care. This article provides guidance for the assessment and management of brain injury following cardiac arrest.

RECENT FINDINGS

Neurologists have many roles in postresuscitation cardiac arrest care: (1) early assessment of brain injury severity to help inform triage for invasive circulatory support or revascularization; (2) advocacy for the maintenance of a neuroprotective thermal, hemodynamic, biochemical, and metabolic milieu; (3) detection and management of seizures; (4) development of an accurate, multimodal, and conservative approach to prognostication; (5) application of shared decision-making paradigms around the likely outcomes of therapy and the goals of care; and (6) facilitation of the neurocognitive assessment of survivors. Therefore, optimal management requires early neurologist involvement in patient care, a detailed knowledge of postresuscitation syndrome and its complex interactions with prognosis, expertise in bringing difficult cases to their optimal conclusions, and a support system for survivors with cognitive deficits.

SUMMARY

Neurologists have a critical role in postresuscitation cardiac arrest care and are key participants in the treatment team from the time of first restoration of a perfusing heart rhythm through the establishment of rehabilitation services for survivors.

Grey-white matter ratio measured using early unenhanced brain computed tomography shows no correlation with neurological outcomes in patients undergoing targeted temperature management after cardiac arrest

AIM

This study evaluated whether the grey-white matter ratio (GWR) assessed via early brain computed tomography (CT) within 2 h after the return of spontaneous circulation (ROSC) following cardiac arrest is associated with poor neurological outcomes after 6 months in post-cardiac arrest patients treated with targeted temperature management (TTM).

METHODS

This study used data from the Korean Hypothermia Network prospective registry obtained from November 2015 to October 2017 to assess patients with out-of-hospital cardiac arrest (OHCA) who underwent brain CT within 2 h following the ROSC. The primary endpoint was the neurological outcome 6 months post-cardiac arrest (cerebral performance category; CPC). The GWR was measured using early brain CT images. The subgroup analysis examined the difference in GWRs obtained from early and repeated brain CT.

RESULTS

Five-hundred-twelve patients were enrolled. Good (CPC 1-2) and poor (CPC 3-5) neurological outcomes were observed in 162 (31.6%) and 350 (68.4%) patients, respectively. The multivariate logistic regression analysis revealed that the GWR measured using early brain CT was a statistically nonsignificant predictor of poor neurologic outcomes (p = 0.727). In patients with poor outcomes, the mean GWR obtained from early and repeated CT images were 1.171 ± 0.058 and 1.091 ± 0.133, respectively (p < 0.001); there was no statistically significant difference between the GWRs in patients with good outcomes.

CONCLUSION

The GWR assessed via early brain CT alone is not an independent factor predictive of poor neurologic outcomes but could be useful when used with repeated CT data.