Early head CT in post-cardiac arrest patients: A helpful tool or contributor to self-fulfilling prophecy?

High risk and low incidence diseases: Aneurysmal subarachnoid hemorrhage

INTRODUCTION

Aneurysmal subarachnoid hemorrhage (aSAH) is a serious condition that carries a high rate of morbidity.

OBJECTIVE

This review highlights the pearls and pitfalls of aSAH, including presentation, diagnosis, and management in the emergency department based on current evidence.

DISCUSSION

aSAH is a type of hemorrhagic stroke, most commonly from rupture of a saccular aneurysm, which results in leakage of blood into the subarachnoid space. It presents acutely and has many mimics, making the diagnosis difficult. Patients who present with either sentinel or acute presentation of a headache that is described as sudden or severe, has associated neck stiffness, cranial nerve deficits, syncope, seizure, and/or coma should raise suspicion for the diagnosis. Non-contrast head computed tomography is the imaging modality of choice for evaluation and diagnosis of the disease in patients who present acutely. Further diagnostic testing with lumbar puncture or advanced neuroimaging may be required in patients who present >6 h after symptom onset. Patients with aSAH require critical, multidisciplinary care, with particular attention to management of airway, breathing, and circulation; expeditious referral for neurosurgical intervention; coagulopathy reversal; and prophylaxis against downstream complications.

CONCLUSION

An understanding of aSAH can assist emergency clinicians in diagnosing and managing this disease.

Time-dependent association of grey-white ratio on early brain CT predicting outcomes after cardiac arrest at hospital discharge

BACKGROUND

Cerebral edema after cardiac arrest can be quantified by the ratio of grey matter to white matter radiodensity (GWR) on computed tomography (CT). Severe edema predicts worse outcomes. We hypothesized the sensitivity and false positive rate of GWR predicting outcomes change over the first 24 hours post-arrest.

METHODS

We performed a single-center retrospective cohort study including patients resuscitated from cardiac arrest between January 2010 and December 2023 who were unresponsive to verbal commands. We excluded patients who arrested from a primary traumatic or neurological etiology and those without brain imaging within 24 hours of arrest. We divided patients into groups based on time from arrest to CT, then quantified the performance of GWR dichotomized at <1.10 and <1.20, predicting in-hospital mortality and death by neurologic criteria (DNC).

RESULTS

We included 2,204 patients with mean age 59 (SD 16) years. Overall, 1651 (75%) died in the hospital, of whom 248 (11%) progressed to DNC. Sensitivity of GWR <1.10 and GWR <1.20 for predicting in-hospital mortality increased over the first four hours post-arrest, reaching a maximum of 25% after five hours, while false positive rates remained <5% at all time points. Similar temporal trends were observed with DNC, although absolute values of sensitivity and false positive rate (FPR) varied.

CONCLUSION

The sensitivity and FPR of early GWR predicting in-hospital mortality and DNC after resuscitation from cardiac arrest varies over the initial post-arrest period. Reduced GWR on brain CTs is most sensitive for in-hospital mortality when obtained more than four hours post-arrest and for DNC when obtained between four and five hours. However, FPR remained execellent throughout, making early reductions in GWR a specific marker of poor outcome regardless of timing. While brain CTs obtained within the first 24 hours post-arrest may be indicated to evaluate for neurologic etiologies of arrest, they may be less informative as an independent marker of prognosis.

Association Between Neurological Status and Outcomes in Cardiac Arrest Patients Undergoing PCI in Contemporary Practice: Insights From BMC2

BACKGROUND

Coronary artery disease remains the largest contributor to cardiac arrests worldwide; yet, long-term outcomes are often driven by neurological status after resuscitation. We examined the association between pre-percutaneous coronary intervention (PCI) level of consciousness (LOC) and outcomes among patients with cardiac arrest who underwent PCI.

METHODS

The study cohort included patients undergoing PCI after cardiac arrest between April 2018 and March 2022 at 48 hospitals in the state of Michigan. Pre-PCI LOC was categorized as mentally alert, partially responsive, unresponsive, and unable to assess. In-hospital outcomes included mortality, bleeding, and acute kidney injury.

RESULTS

Among 3021 patients who underwent PCI after cardiac arrest, 1394 (49%) were mentally alert, 132 (5%) were partially responsive, 698 (24%) were unresponsive, and 631 (22%) were unable to assess. The mentally alert cohort had lower mortality (4.59%) compared with the partially responsive (17.42%), unresponsive (50.14%), and unable to assess cohorts (38.03%; P<0.001). After adjusting for baseline differences, compared with mentally alert patients, the odds of mortality were markedly elevated in patients who were partially responsive (adjusted odds ratio, 4.63 [95% CI, 2.67-8.04]; P<0.001), unable to assess (adjusted odds ratio, 13.95 [95% CI, 9.97-19.51]; P<0.001), and unresponsive (adjusted odds ratio, 24.36 [17.34-34.23]; P<0.001). After adjustment, patients with impaired LOC also had higher risks of acute kidney injury and bleeding compared with mentally alert patients.

CONCLUSIONS

Pre-PCI LOC is a strong predictor of in-hospital outcomes after PCI among cardiac arrest patients. A patient's pre-PCI LOC should be considered an important factor when weighing treatment options, designing clinical trials, and counseling patients and their families regarding prognosis after PCI.

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.

Regional Brain Net Water Uptake in Computed Tomography after Cardiac Arrest - A Novel Biomarker for Neuroprognostication

BACKGROUND

Selective water uptake by neurons and glial cells and subsequent brain tissue oedema are key pathophysiological processes of hypoxic-ischemic encephalopathy (HIE) after cardiac arrest (CA). Although brain computed tomography (CT) is widely used to assess the severity of HIE, changes of brain radiodensity over time have not been investigated. These could be used to quantify regional brain net water uptake (NWU), a potential prognostic biomarker.

METHODS

We conducted an observational prognostic accuracy study including a derivation (single center cardiac arrest registry) and a validation (international multicenter TTM2 trial) cohort. Early (<6 h) and follow-up (>24 h) head CTs of CA patients were used to determine regional NWU for grey and white matter regions after co-registration with a brain atlas. Neurological outcome was dichotomized as good versus poor using the Cerebral Performance Category Scale (CPC) in the derivation cohort and Modified Rankin Scale (mRS) in the validation cohort.

RESULTS

We included 115 patients (81 derivation, 34 validation) with out-of-hospital (OHCA) and in-hospital cardiac arrest (IHCA). Regional brain water content remained unchanged in patients with good outcome. In patients with poor neurological outcome, we found considerable regional water uptake with the strongest effect in the basal ganglia. NWU >8% in the putamen and caudate nucleus predicted poor outcome with 100% specificity (95%-CI: 86-100%) and 43% (moderate) sensitivity (95%-CI: 31-56%).

CONCLUSION

This pilot study indicates that NWU derived from serial head CTs is a promising novel biomarker for outcome prediction after CA. NWU >8% in basal ganglia grey matter regions predicted poor outcome while absence of NWU indicated good outcome. NWU and follow-up CTs should be investigated in larger, prospective trials with standardized CT acquisition protocols.

Standardised and automated assessment of head computed tomography reliably predicts poor functional outcome after cardiac arrest: a prospective multicentre study

PURPOSE

Application of standardised and automated assessments of head computed tomography (CT) for neuroprognostication after out-of-hospital cardiac arrest.

METHODS

Prospective, international, multicentre, observational study within the Targeted Hypothermia versus Targeted Normothermia after out-of-hospital cardiac arrest (TTM2) trial. Routine CTs from adult unconscious patients obtained > 48 h ≤ 7 days post-arrest were assessed qualitatively and quantitatively by seven international raters blinded to clinical information using a pre-published protocol. Grey-white-matter ratio (GWR) was calculated from four (GWR-4) and eight (GWR-8) regions of interest manually placed at the basal ganglia level. Additionally, GWR was obtained using an automated atlas-based approach. Prognostic accuracies for prediction of poor functional outcome (modified Rankin Scale 4-6) for the qualitative assessment and for the pre-defined GWR cutoff < 1.10 were calculated.

RESULTS

140 unconscious patients were included; median age was 68 years (interquartile range [IQR] 59-76), 76% were male, and 75% had poor outcome. Standardised qualitative assessment and all GWR models predicted poor outcome with 100% specificity (95% confidence interval [CI] 90-100). Sensitivity in median was 37% for the standardised qualitative assessment, 39% for GWR-8, 30% for GWR-4 and 41% for automated GWR. GWR-8 was superior to GWR-4 regarding prognostic accuracies, intra- and interrater agreement. Overall prognostic accuracy for automated GWR (area under the curve [AUC] 0.84, 95% CI 0.77-0.91) did not significantly differ from manually obtained GWR.

CONCLUSION

Standardised qualitative and quantitative assessments of CT are reliable and feasible methods to predict poor functional outcome after cardiac arrest. Automated GWR has the potential to make CT quantification for neuroprognostication accessible to all centres treating cardiac arrest patients.

Brain computed tomography after resuscitation from in-hospital cardiac arrest

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.

Association between quantitative analysis of cerebral edema using CT imaging and neurological outcomes in cardiac arrest survivors

BACKGROUND

To determine if the density distribution proportion of Hounsfield unit (HUdp) in head computed tomography (HCT) images can be used to quantitatively measure cerebral edema in survivors of out-of-hospital cardiac arrest (OHCA).

METHODS

This retrospective observational study included adult comatose OHCA survivors who underwent HCT within 6 h (first) and 72-96 h (second), all performed using the same CT scanner. Semi-automated quantitative analysis was used to identify differences in HUdp at specific HU ranges across the intracranial component based on neurological outcome. Cerebral edema was defined as the increased displacement of the sum of HUdp values (ΔHUdp) at a specific range between two HCT scans. Poor neurological outcome was defined as cerebral performance categories 3-5 at 6 months after OHCA.

RESULTS

Twenty-three (42%) out of 55 patients had poor neurological outcome. Significant HUdp differences were observed between good and poor neurological outcomes in the second HCT scan at HU = 1-14, 23-35, and 39-56 (all P < 0.05). Only the ΔHUdp = 23-35 range showed a significant increase and correlation in the poor neurological outcome group (4.90 vs. -0.72, P < 0.001) with the sum of decreases in the other two ranges (r = 0.97, P < 0.001). Multivariate logistic regression analysis demonstrated a significant association between ΔHUdp = 23-35 range and poor neurological outcomes (adjusted OR, 1.12; 95% CI: 1.02-1.24; P = 0.02).

CONCLUSION

In this cohort study, the increased displacement in ΔHUdp = 23-35 range is independently associated with poor neurological outcome and provides a quantitative assessment of cerebral edema formation in OHCA survivors.

Coma Prognostication After Acute Brain Injury: A Review

Importance

Among the most impactful neurologic assessments is that of neuroprognostication, defined here as the prediction of neurologic recovery from disorders of consciousness caused by severe, acute brain injury. Across a range of brain injury etiologies, these determinations often dictate whether life-sustaining treatment is continued or withdrawn; thus, they have major implications for morbidity, mortality, and health care costs. Neuroprognostication relies on a diverse array of tests, including behavioral, radiologic, physiological, and serologic markers, that evaluate the brain's functional and structural integrity.

Observations

Prognostic markers, such as the neurologic examination, electroencephalography, and conventional computed tomography and magnetic resonance imaging (MRI), have been foundational in assessing a patient's current level of consciousness and capacity for recovery. Emerging techniques, such as functional MRI, diffusion MRI, and advanced forms of electroencephalography, provide new ways of evaluating the brain, leading to evolving schemes for characterizing neurologic function and novel methods for predicting recovery.

Conclusions and Relevance

Neuroprognostic markers are rapidly evolving as new ways of assessing the brain's structural and functional integrity after brain injury are discovered. Many of these techniques remain in development, and further research is needed to optimize their prognostic utility. However, even as such efforts are underway, a series of promising findings coupled with the imperfect predictive value of conventional prognostic markers and the high stakes of these assessments have prompted clinical guidelines to endorse emerging techniques for neuroprognostication. Thus, clinicians have been thrust into an uncertain predicament in which emerging techniques are not yet perfected but too promising to ignore. This review illustrates the current, and likely future, landscapes of prognostic markers. No matter how much prognostic markers evolve and improve, these assessments must be approached with humility and individualized to reflect each patient's values.

Simple approach to quantify hypoxic-ischemic brain injury severity from computed tomography imaging files after cardiac arrest

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.

Outcome prediction in comatose cardiac arrest patients with initial shockable and non-shockable rhythms

BACKGROUND

Prognosis after out-of-hospital cardiac arrest (OHCA) is presumed poorer in patients with non-shockable than shockable rhythms, frequently leading to treatment withdrawal. Multimodal outcome prediction is recommended 72 h post-arrest in still comatose patients, not considering initial rhythms. We investigated accuracy of outcome predictors in all comatose OHCA survivors, with a particular focus on shockable vs. non-shockable rhythms.

METHODS

In this observational NORCAST sub-study, patients still comatose 72 h post-arrest were stratified by shockable vs. non-shockable rhythms for outcome prediction analyzes. Good outcome was defined as cerebral performance category 1-2 within 6 months. False positive rate (FPR) was used for poor and sensitivity for good outcome prediction accuracy.

RESULTS

Overall, 72/128 (56%) patients with shockable and 12/50 (24%) with non-shockable rhythms had good outcome (p < .001). For poor outcome prediction, absent pupillary light reflexes (PLR) and corneal reflexes (clinical predictors) 72 h after sedation withdrawal, PLR 96 h post-arrest, and somatosensory evoked potentials (SSEP), all had FPR <0.1% in both groups. Unreactive EEG and neuron-specific enolase (NSE) >60 μg/L 24-72 h post-arrest had better precision in shockable patients. For good outcome, the clinical predictors, SSEP and CT, had 86%-100% sensitivity in both groups. For NSE, sensitivity varied from 22% to 69% 24-72 h post-arrest. The outcome predictors indicated severe brain injury proportionally more often in patients with non-shockable than with shockable rhythms. For all patients, clinical predictors, CT, and SSEP, predicted poor and good outcome with high accuracy.

CONCLUSION

Outcome prediction accuracy was comparable for shockable and non-shockable rhythms. PLR and corneal reflexes had best precision 72 h after sedation withdrawal and 96 h post-arrest.

Development and validation of a novel score to predict brain death after out-of-hospital cardiac arrest

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.

Associations between clinical characteristics of cardiac arrest and early CT head findings of hypoxic ischaemic brain injury following out-of-hospital cardiac arrest

BACKGROUND/OBJECTIVE

Post-cardiac arrest patients are vulnerable to hypoxic-ischaemic brain injury (HIBI), but HIBI may not be identified until computed tomography (CT) scan of the brain is obtained post-resuscitation and stabilization. We aimed to evaluate the association of clinical arrest characteristics with early CT findings of HIBI to identify those at the highest risk for HIBI.

METHODS

This is a retrospective analysis of out-of-hospital cardiac arrest (OHCA) patients who underwent whole-body imaging. Head CT reports were analyzed with an emphasis on findings suggestive of HIBI; HIBI was present if any of the following were noted on the neuroradiologist read: global cerebral oedema, sulcal effacement, blurred grey-white junction, and ventricular compression. The primary exposure was duration of cardiac arrest. Secondary exposures included age, cardiac vs noncardiac etiology, and witnessed vs unwitnessed arrest. The primary outcome was CT findings of HIBI.

RESULTS

A total of 180 patients (average age 54 years, 32% female, 71% White, 53% witnessed arrest, 32% cardiac etiology of arrest, mean CPR duration of 15 ± 10 minutes) were included in this analysis. CT findings of HIBI were seen in 47 (48.3%) patients. Multivariate logistic regression demonstrated a significant association between CPR duration and HIBI (adjusted OR = 1.1, 95% CI 1.01-1.11, p < 0.01).

CONCLUSION

Signs of HIBI are commonly seen on CT head within 6 hours of OHCA, occurring in approximately half of patients, and are associated with CPR duration. Determining risk factors for abnormal CT findings can help clinically identify patients at higher risk for HIBI and target interventions appropriately.

Critically ill metastatic cancer patients returning home after unplanned ICU stay: an observational, multicentre retrospective study

BACKGROUND

Data about critically ill metastatic cancer patients functional outcome after unplanned admission to the ICU are scarce. The aim of this study was to assess factors associated with 90-day return home and 1-year survival in this population.

STUDY DESIGN AND METHODS

A multicenter retrospective study included all consecutive metastatic cancer patients admitted to the ICU for unplanned reason between 2017 and 2020.

RESULTS

Among 253 included metastatic cancer patients, mainly with lung cancer, 94 patients (37.2%) could return home on day 90. One-year survival rate was 28.5%. Performance status 0 or 1 (OR, 2.18; 95% CI 1.21-3.93; P = 0.010), no malnutrition (OR, 2.90; 95% CI 1.61-5.24; P < 0.001), female gender (OR, 2.39; 95% CI 1.33-4.29; P = 0.004), recent chemotherapy (OR, 2.62; 95% CI 1.40-4.90; P = 0.003), SOFA score ≤ 5 on admission (OR, 2.62; 95% CI 1.41-4.90; P = 0.002) were significantly predictive for 90-day return home. Malnutrition (HR, 1.66; 95% CI 1.18-2.22; P = 0.003), acute respiratory failure (ARF) as reason for admission (HR, 1.40; 95% CI 1.10-1.95; P = 0.043), SAPS II on admission (HR, 1.03; 95% CI 1.02-1.05; P < 0.001) and decisions to forgo life-sustaining therapies (DFLST) (HR, 2.80; 95% CI 2.04-3.84; P < 0.001) were independently associated with 1-year mortality.

CONCLUSIONS

More than one out of three metastatic cancer patients could return home within 3 months after an unplanned admission to the ICU. Previous performance and nutritional status, ongoing specific treatment and low severity of the acute illness were found to be predictive for return home. Such encouraging findings should help change the dismal perception of critically ill metastatic cancer patients.

Neurologic Complications of Critical Medical Illness

OBJECTIVE

This article reviews the neurologic complications encountered in patients admitted to non-neurologic intensive care units, outlines various scenarios in which a neurologic consultation can add to the diagnosis or management of a critically ill patient, and provides advice on the best diagnostic approach in the evaluation of these patients.

LATEST DEVELOPMENTS

Increasing recognition of neurologic complications and their adverse impact on long-term outcomes has led to increased neurology involvement in non-neurologic intensive care units. The COVID-19 pandemic has highlighted the importance of having a structured clinical approach to neurologic complications of critical illness as well as the critical care management of patients with chronic neurologic disabilities.

ESSENTIAL POINTS

Critical illness is often accompanied by neurologic complications. Neurologists need to be aware of the unique needs of critically ill patients, especially the nuances of the neurologic examination, challenges in diagnostic testing, and neuropharmacologic aspects of commonly used medications.

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.

Inter-rater agreement between humans and computer in quantitative assessment of computed tomography after cardiac arrest

Background

Head computed tomography (CT) is used to predict neurological outcome after cardiac arrest (CA). The current reference standard includes quantitative image analysis by a neuroradiologist to determine the Gray-White-Matter Ratio (GWR) which is calculated via the manual measurement of radiodensity in different brain regions. Recently, automated analysis methods have been introduced. There is limited data on the Inter-rater agreement of both methods.

Methods

Three blinded human raters (neuroradiologist, neurologist, student) with different levels of clinical experience retrospectively assessed the Gray-White-Matter Ratio (GWR) in head CTs of 95 CA patients. GWR was also quantified by a recently published computer algorithm that uses coregistration with standardized brain spaces to identify regions of interest (ROIs). We calculated intraclass correlation (ICC) for inter-rater agreement between human and computer raters as well as area under the curve (AUC) and sensitivity/specificity for poor outcome prognostication.

Results

Inter-rater agreement on GWR was very good (ICC 0.82–0.84) between all three human raters across different levels of expertise and between the computer algorithm and neuroradiologist (ICC 0.83; 95% CI 0.78–0.88). Despite high overall agreement, we observed considerable, clinically relevant deviations of GWR measurements (up to 0.24) in individual patients. In our cohort, at a GWR threshold of 1.10, this did not lead to any false poor neurological outcome prediction.

Conclusion

Human and computer raters demonstrated high overall agreement in GWR determination in head CTs after CA. The clinically relevant deviations of GWR measurement in individual patients underscore the necessity of additional qualitative evaluation and integration of head CT findings into a multimodal approach to prognostication of neurological outcome after CA.

Prognostic accuracy of head computed tomography for prediction of functional outcome after out-of-hospital cardiac arrest: Rationale and design of the prospective TTM2-CT-substudy

Background

Head computed tomography (CT) is a guideline recommended method to predict functional outcome after cardiac arrest (CA), but standardized criteria for evaluation are lacking. To date, no prospective trial has systematically validated methods for diagnosing hypoxic-ischaemic encephalopathy (HIE) on CT after CA. We present a protocol for validation of pre-specified radiological criteria for assessment of HIE on CT for neuroprognostication after CA.

Methods/design

This is a prospective observational international multicentre substudy of the Targeted Hypothermia versus Targeted Normothermia after out-of-hospital cardiac arrest (TTM2) trial. Patients still unconscious 48 hours post-arrest at 13 participating hospitals were routinely examined with CT. Original images will be evaluated by examiners blinded to clinical data using a standardized protocol. Qualitative assessment will include evaluation of absence/presence of "severe HIE". Radiodensities will be quantified in pre-specified regions of interest for calculation of grey-white matter ratios (GWR) at the basal ganglia level. Functional outcome will be dichotomized into good (modified Rankin Scale 0-3) and poor (modified Rankin Scale 4-6) at six months post-arrest. Prognostic accuracies for good and poor outcome will be presented as sensitivities and specificities with 95% confidence intervals (using pre-specified cut-offs for quantitative analysis), descriptive statistics (Area Under the Receiver Operating Characteristics Curve), inter- and intra-rater reliabilities according to STARD guidelines.

Conclusions

The results from this prospective trial will validate a standardized approach to radiological evaluations of HIE on CT for prediction of functional outcome in comatose CA patients.The TTM2 trial and the TTM2 CT substudy are registered at ClinicalTrials.gov NCT02908308 and NCT03913065.

Early risk stratification for progression to death by neurological criteria following out-of-hospital cardiac arrest

BACKGROUND

Some patients resuscitated from out-of-hospital cardiac arrest (OHCA) progress to death by neurological criteria (DNC). We hypothesized that initial brain imaging, electroencephalography (EEG), and arrest characteristics predict progression to DNC.

METHODS

We identified comatose OHCA patients from January 2010 to February 2020 treated at a single quaternary care facility in Western Pennsylvania. We abstracted demographics and arrest characteristics; Pittsburgh Cardiac Arrest Category, initial motor exam and pupillary light reflex; initial brain computed tomography (CT) grey-to-white ratio (GWR), sulcal or basal cistern effacement; initial EEG background and suppression ratio. We used two modeling approaches: fast and frugal tree (FFT) analysis to create an interpretable clinical risk stratification tool and ridge regression for comparison. We used bootstrapping to randomly partition cases into 80% training and 20% test sets and evaluated test set sensitivity and specificity.

RESULTS

We included 1,569 patients, of whom 147 (9%) had diagnosed DNC. Across bootstrap samples, >99% of FFTs included three predictors: sulcal effacement, and in cases without sulcal effacement, the combination of EEG background suppression and GWR ≤ 1.23. This tree had mean sensitivity and specificity of 87% and 81%. Ridge regression with all available predictors had mean sensitivity 91 % and mean specificity 83%. Subjects falsely predicted as likely to progress to DNC generally died of rearrest or withdrawal of life sustaining therapies due to poor neurological prognosis. Two of these cases awakened from coma during the index hospitalization.

CONCLUSIONS

Sulcal effacement on presenting brain CT or EEG suppression with GWR ≤ 1.23 predict progression to DNC after OHCA.

Das ist neu in der Neurointensiv- und Notfallmedizin: die wichtigsten Studien des Jahres im Rück- und Überblick

Die vorliegende Übersichtsarbeit fasst wichtige klinische Studien der neurologischen Notfall- und Intensivmedizin zwischen 2020 und 2021 zusammen zu den Themen: rekanalisierende Therapie beim ischämischen Schlaganfall, Anwendbarkeit und Auswirkung eines zerebralen Sauerstoffgewebemonitorings bei Subarachnoidalblutung, Wirksamkeit induzierter Hypothermie bei Patienten mit „cardiac arrest“ (CA), Wertigkeit früher kranialer Bildgebung nach CA, Relevanz eines schnellen Managements und medikamentöser Therapie beim Status epilepticus sowie Inzidenz von Critical-illness-Polyneuropathie-Myopathie bei intensivpflichtigen COVID-Patienten.

Resuscitation highlights in 2021

BACKGROUND

This review is the latest in a series of regular annual reviews undertaken by the editors and aims to highlight some of the key papers published in Resuscitation during 2021.

METHODS

Hand-searching by the editors of all papers published in Resuscitation during 2021. Papers were selected based on then general interest and novelty and were categorised into themes.

RESULTS

98 papers were selected for brief mention.

CONCLUSIONS

Resuscitation science continues to evolve and incorporates all links in the chain of survival.

Delayed head CT in out-of-hospital cardiac arrest survivors: Does this improve predictive performance of neurological outcome?

BACKGROUND

We compared the ability of head computed tomography (HCT) and MRI, respectively, obtained before or after target temperature management to predict neurologic outcomes in out-of-hospital cardiac arrest (OHCA) survivors.

METHODS

This retrospective study included adult comatose OHCA survivors who underwent neuroimaging scans within 6 h (first HCT) or 72-96 h (second HCT and MRI) after the return of spontaneous circulation (ROSC). We calculated the gray-white matter ratio (GWR), hypoxic-ischemic brain injury presence (loss of boundary at the basal ganglia level [LOB at BG], sulcal effacement at the centrum semiovale [SE at CS], and pseudo-SAH sign), and the overall score based on MRI findings (a total score of 21 brain regions individually scored according to the degree of signal abnormality).

RESULTS

Overall, 78 patients were included in this analysis, of whom 45 (58%) showed poor outcomes. The second HCT scan showed greater prognostic performance than the first HCT scan for GWR (area under curve 0.92 vs. 0.70), LOB at BG (0.93 vs. 0.65), SE at CS (0.89 vs. 0.64), and pseudo-SAH sign (0.75 vs. 0.51). The overall score on MRI (0.99) showed the highest prognostic performance. However, on the second HCT scan, the combination of GWR and LOB at BG showed prognostic performance (0.96) comparable to the overall score on MRI (P=0.12); the corresponding sensitivity and specificity values were 85.7% and 100%.

CONCLUSIONS

Overall score on MRI and the combination of GWR and LOB at BG findings on second HCT scans may help predict poor outcomes in OHCA survivors.