Validation of the Pittsburgh Cardiac Arrest Category illness severity score

Temperature Control Parameters Are Important: Earlier Preinduction Is Associated With Improved Outcomes Following Out-of-Hospital Cardiac Arrest

STUDY OBJECTIVE

Temperature control trials in cardiac arrest patients have not reliably conferred neuroprotective benefit but have been limited by inconsistent treatment parameters. To evaluate the presence of a time dependent treatment effect, we assessed the association between preinduction time and clinical outcomes.

METHODS

In this retrospective, single academic center study between 2014 and 2022, consecutive out-of-hospital cardiac arrest (OHCA) patients treated with temperature control were identified. Preinduction was defined as the time from hospital arrival to initiation of a closed-loop temperature feedback device [door to temperature control initiation time], and early door to temperature control device time was defined a priori as <3 hours. We assessed the association between good neurologic outcome (cerebral performance category 1 to 2) and door to temperature control device time using logistic regression. The proportion of patients who survived to hospital discharge was evaluated as a secondary outcome. A sensitivity analysis using inverse probability treatment weighting, created using a propensity score, was performed to minimize measurable confounding.

RESULTS

Three hundred and forty-seven OHCA patients were included; the early door to temperature control device cohort included 75 (21.6%) patients with a median (interquartile range) door to temperature control device time of 2.50 (2.03 to 2.75) hours, whereas the late door to temperature control device cohort included 272 (78.4%) patients with a median (interquartile range) door to temperature control device time of 5.18 (4.19 to 6.41) hours. In the multivariable logistic regression model, early door to temperature control device time was associated with improved good neurologic outcome and survival before [adjusted odds ratio (OR) (95% confidence interval) 2.36 (1.16 to 4.81) and 3.02 (1.54 to 6.02)] and after [adjusted OR (95% confidence interval) 1.95 (1.19 to 3.79) and 2.14 (1.33 to 3.36)] inverse probability of treatment weighting, respectively.

CONCLUSION

In our study of OHCA patients, a shorter preinduction time for temperature control was associated with improved good neurologic outcome and survival. This finding may indicate that early initiation in the emergency department will confer benefit. Our findings are hypothesis generating and need to be validated in future prospective trials.

Emergent Management of Hypoxic-Ischemic Brain Injury

OBJECTIVE

This article outlines interventions used to improve outcomes for patients with hypoxic-ischemic brain injury after cardiac arrest.

LATEST DEVELOPMENTS

Emergent management of patients after cardiac arrest requires prevention and treatment of primary and secondary brain injury. Primary brain injury is minimized by excellent initial resuscitative efforts. Secondary brain injury prevention requires the detection and correction of many pathophysiologic processes that may develop in the hours to days after the initial arrest. Key physiologic parameters important to secondary brain injury prevention include optimization of mean arterial pressure, cerebral perfusion, oxygenation and ventilation, intracranial pressure, temperature, and cortical hyperexcitability. This article outlines recent data regarding the treatment and prevention of secondary brain injury. Different patients likely benefit from different treatment strategies, so an individualized approach to treatment and prevention of secondary brain injury is advisable. Clinicians must use multimodal sources of data to prognosticate outcomes after cardiac arrest while recognizing that all prognostic tools have shortcomings.

ESSENTIAL POINTS

Neurologists should be involved in the postarrest care of patients with hypoxic-ischemic brain injury to improve their outcomes. Postarrest care requires nuanced and patient-centered approaches to the prevention and treatment of primary and secondary brain injury and neuroprognostication.

A multicenter, randomized, doubleblind, placebo-controlled trial of amantadine to stimulate awakening in comatose patients resuscitated from cardiac arrest

OBJECTIVE

We hypothesized that the administration of amantadine would increase awakening of comatose patients resuscitated from cardiac arrest.

METHODS

We performed a prospective, randomized, controlled pilot trial, randomizing subjects to amantadine 100 mg twice daily or placebo for up to 7 days. The study drug was administered between 72 and 120 hours after resuscitation and patients with absent N20 cortical responses, early cerebral edema, or ongoing malignant electroencephalography patterns were excluded. Our primary outcome was awakening, defined as following two-step commands, within 28 days of cardiac arrest. Secondary outcomes included length of stay, awakening, time to awakening, and neurologic outcome measured by Cerebral Performance Category at hospital discharge. We compared the proportion of subjects awakening and hospital survival using Fisher exact tests and time to awakening and hospital length of stay using Wilcoxon rank sum tests.

RESULTS

After 2 years, we stopped the study due to slow enrollment and lapse of funding. We enrolled 14 subjects (12% of goal enrollment), seven in the amantadine group and seven in the placebo group. The proportion of patients who awakened within 28 days after cardiac arrest did not differ between amantadine (n=2, 28.6%) and placebo groups (n=3, 42.9%; P>0.99). There were no differences in secondary outcomes. Study medication was stopped in three subjects (21.4%). Adverse events included a recurrence of seizures (n=2; 14.3%), both of which occurred in the placebo group.

CONCLUSION

We could not determine the effect of amantadine on awakening in comatose survivors of cardiac arrest due to small sample size.

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.

Blood-brain barrier permeability for the first 24 hours in hypoxic-ischemic brain injury following cardiac arrest

BACKGROUND

This study aimed to explore the changes in blood-brain barrier (BBB) permeability and intracranial pressure (ICP) for the first 24 h after the return of spontaneous circulation (ROSC) and their association with injury severity of cardiac arrest.

METHODS

This prospective study analysed the BBB permeability assessed using the albumin quotient (Qa) and ICP every 2 h for the first 24 h after ROSC. The injury severity of cardiac arrest was assessed using Pittsburgh Cardiac Arrest Category (PCAC) scores. The primary outcome was the time course of changes in the BBB permeability and ICP for the first 24 h after ROSC and their association with injury severity (PCAC scores of 1-4).

RESULTS

Qa and ICP were measured 274 and 197 times, respectively, in 32 enrolled patients. Overall, the BBB permeability increased progressively over time after ROSC, and then it increased significantly at 18 h after ROSC compared with the baseline. In contrast, the ICP revealed non-significant changes for the first 24 h after ROSC. The Qa in the PCAC 2 group was < 0.01, indicating normal or mild BBB disruption at all time points, whereas the PCAC 3 and 4 groups showed a significant increase in BBB permeability at 14 and 22 h, and 12 and 14 h after ROSC, respectively.

CONCLUSION

BBB permeability increased progressively over time for the first 24 h after ROSC despite post-resuscitation care, whereas ICP did not change over time. BBB permeability has an individual pattern when stratified by injury severity.

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.

Prediction performance of scoring systems after out-of-hospital cardiac arrest: A systematic review and meta-analysis

INTRODUCTION

Ongoing changes in post resuscitation medicine and society create a range of ethical challenges for clinicians. Withdrawal of life-sustaining treatment is a very sensitive, complex decision to be made by the treatment team and the relatives together. According to the guidelines, prognostication after cardiopulmonary resuscitation should be based on a combination of clinical examination, biomarkers, imaging, and electrophysiological testing. Several prognostic scores exist to predict neurological and mortality outcome in post-cardiac arrest patients. We aimed to perform a meta-analysis and systematic review of current scoring systems used after out-of-hospital cardiac arrest (OHCA).

MATERIALS AND METHODS

Our systematic search was conducted in four databases: Medline, Embase, Central and Scopus on 24th April 2023. The patient population consisted of successfully resuscitated adult patients after OHCA. We included all prognostic scoring systems in our analysis suitable to estimate neurologic function as the primary outcome and mortality as the secondary outcome. For each score and outcome, we collected the AUC (area under curve) values and their CIs (confidence iterval) and performed a random-effects meta-analysis to obtain pooled AUC estimates with 95% CI. To visualize the trade-off between sensitivity and specificity achieved using different thresholds, we created the Summary Receiver Operating Characteristic (SROC) curves.

RESULTS

24,479 records were identified, 51 of which met the selection criteria and were included in the qualitative analysis. Of these, 24 studies were included in the quantitative synthesis. The performance of CAHP (Cardiac Arrest Hospital Prognosis) (0.876 [0.853-0.898]) and OHCA (0.840 [0.824-0.856]) was good to predict neurological outcome at hospital discharge, and TTM (Targeted Temperature Management) (0.880 [0.844-0.916]), CAHP (0.843 [0.771-0.915]) and OHCA (0.811 [0.759-0.863]) scores predicted good the 6-month neurological outcome. We were able to confirm the superiority of the CAHP score especially in the high specificity range based on our sensitivity and specificity analysis.

CONCLUSION

Based on our results CAHP is the most accurate scoring system for predicting the neurological outcome at hospital discharge and is a bit less accurate than TTM score for the 6-month outcome. We recommend the use of the CAHP scoring system in everyday clinical practice not only because of its accuracy and the best performance concerning specificity but also because of the rapid and easy availability of the necessary clinical data for the calculation.

Post Cardiac Arrest Care in the Cardiac Intensive Care Unit

PURPOSE OF REVIEW

Cardiac arrests constitute a leading cause of mortality in the adult population and cardiologists are often tasked with the management of patients following cardiac arrest either as a consultant or primary provider in the cardiac intensive care unit. Familiarity with evidence-based practice for post-cardiac arrest care is a requisite for optimizing outcomes in this highly morbid group. This review will highlight important concepts necessary to managing these patients.

RECENT FINDINGS

Emerging evidence has further elucidated optimal care of post-arrest patients including timing for routine coronary angiography, utility of therapeutic hypothermia, permissive hypercapnia, and empiric aspiration pneumonia treatment. The complicated state of multi-organ failure following cardiac arrest needs to be carefully optimized by the clinician to prevent further neurologic injury and promote systemic recovery. Future studies should be aimed at understanding if these findings extend to specific patient populations, especially those at the highest risk for poor outcomes.

Indications for Cardiac Catheterization and Percutaneous Coronary Intervention in Patients with Resuscitated Out-of-Hospital Cardiac Arrest

PURPOSE OF REVIEW

The role of emergent cardiac catheterization after resuscitated out-of-hospital cardiac arrest (OHCA) has evolved based on recent randomized evidence. This review aims to discuss the latest evidence and current indications for emergent coronary angiography (CAG) and mechanical circulatory support (MCS) use following OHCA.

RECENT FINDINGS

In contrast to previous observational data, recent RCTs evaluating early CAG in resuscitated OHCA patients without ST elevation have uniformly demonstrated a lack of benefit in terms of survival or neurological outcome. There is currently no randomized evidence supporting MCS use specifically in patients with resuscitated OHCA and cardiogenic shock. Urgent CAG should be considered in all patients with ST elevation, recurrent electrical or hemodynamic instability, those who are awake following resuscitated OHCA, and those receiving extracorporeal cardiopulmonary resuscitation (ECPR). Recent evidence suggests that CAG may be safely delayed in hemodynamically stable patients without ST-segment elevation following resuscitated OHCA.

Prospective comparison of prognostic scores for prediction of outcome after out-of-hospital cardiac arrest: results of the AfterROSC1 multicentric study

BACKGROUND

Out-of-hospital cardiac arrest (OHCA) is a heterogeneous entity with multiple origins and prognoses. An early, reliable assessment of the prognosis is useful to adapt therapeutic strategy, tailor intensity of care, and inform relatives. We aimed primarily to undertake a prospective multicentric study to evaluate predictive performance of the Cardiac Arrest Prognosis (CAHP) Score as compare to historical dataset systematically collected after OHCA (Utstein style criteria). Our secondary aim was to evaluate other dedicated scores for predicting outcome after OHCA and to compare them to Utstein style criteria.

METHODS

We prospectively collected data from 24 French and Belgium Intensive Care Units (ICUs) between August 2020 and June 2022. All cases of non-traumatic OHCA (cardiac and non-cardiac causes) patients with stable return of spontaneous circulation (ROSC) and comatose at ICU admission (defined by Glasgow coma score ≤ 8) on ICU admission were included. The primary outcome was the modified Rankin scale (mRS) at day 90 after cardiac arrest, assessed by phone interviews. A wide range of developed scores (CAHP, OHCA, CREST, C-Graph, TTM, CAST, NULL-PLEASE, and MIRACLE2) were included, and their accuracies in predicting poor outcome at 90 days after OHCA (defined as mRS ≥ 4) were determined using the area under the receiving operating characteristic curve (AUROC) and the calibration belt.

RESULTS

During the study period, 907 patients were screened, and 658 were included in the study. Patients were predominantly male (72%), with a mean age of 61 ± 15, most having collapsed from a supposed cardiac cause (64%). The mortality rate at day 90 was 63% and unfavorable neurological outcomes were observed in 66%. The performance (AUROC) of Utstein criteria for poor outcome prediction was moderate at 0.79 [0.76-0.83], whereas AUROCs from other scores varied from 0.79 [0.75-0.83] to 0.88 [0.86-0.91]. For each score, the proportion of patients for whom individual values could not be calculated varied from 1.4% to 17.4%.

CONCLUSIONS

In patients admitted to ICUs after a successfully resuscitated OHCA, most of the scores available for the evaluation of the subsequent prognosis are more efficient than the usual Utstein criteria but calibration is unacceptable for some of them. Our results show that some scores (CAHP, sCAHP, mCAHP, OHCA, rCAST) have superior performance, and that their ease and speed of determination should encourage their use. Trial registration https://clinicaltrials.gov/ct2/show/NCT04167891.

Diagnostic yield of computed tomography after non-traumatic out-of-hospital cardiac arrest

AIM

Determine the frequency with which computed tomography (CT) after out-of-hospital cardiac arrest (OHCA) identifies clinically important findings.

METHODS

We included non-traumatic OHCA patients treated at a single center from February 2019 to February 2021. Clinical practice was to obtain CT head in comatose patients. Additionally, CT of the cervical spine, chest, abdomen, and pelvis were obtained if clinically indicated. We identified CT imaging obtained within 24 hours of emergency department (ED) arrival and summarized radiology findings. We used descriptive statistics to summarize population characteristics and imaging results, report their frequencies and, post hoc, compared time from ED arrival to catheterization between patients who did and did not undergo CT.

RESULTS

We included 597 subjects, of which 491 (82.2%) had a CT obtained. Time to CT was 4.1 hours [2.8-5.7]. Most (n = 480, 80.4%) underwent CT head, of which 36 (7.5%) had intracranial hemorrhage and 161 (33.5%) had cerebral edema. Fewer subjects (230, 38.5%) underwent a cervical spine CT, and 4 (1.7%) had acute vertebral fractures. Most subjects (410, 68.7%) underwent a chest CT, and abdomen and pelvis CT (363, 60.8%). Chest CT abnormalities included rib or sternal fractures (227, 55.4%), pneumothorax (27, 6.6%), aspiration or pneumonia (309, 75.4%), mediastinal hematoma (18, 4.4%) and pulmonary embolism (6, 3.7%). Significant abdomen and pelvis findings were bowel ischemia (24, 6.6%) and solid organ laceration (7, 1.9%). Most subjects that had CT imaging deferred were awake and had shorter time to catheterization.

CONCLUSIONS

CT identifies clinically important pathology after OHCA.

Validation of the rCAST Score and Comparison to the PCAC and FOUR Scores for Prognostication after Out-of-Hospital Cardiac Arrest

AIM

Early, accurate outcome prediction after out-of-hospital cardiac arrest (OHCA) is critical for clinical decision-making and resource allocation. We sought to validate the revised post-Cardiac Arrest Syndrome for Therapeutic hypothermia (rCAST) score in a United States cohort and compare its prognostic performance to the Pittsburgh Cardiac Arrest Category (PCAC) and Full Outline of UnResponsiveness (FOUR) scores.

METHODS

This is a single-center, retrospective study of OHCA patients admitted between January 2014-August 2022. Area under the receiver operating curve (AUC) was computed for each score for predicting poor neurologic outcome at discharge and in-hospital mortality. We compared the scores' predictive abilities via Delong's test.

RESULTS

Of 505 OHCA patients with all scores available, the medians [IQR] for rCAST, PCAC, and FOUR scores were 9.5 [6.0, 11.5], 4 [3,4], and 2 [0, 5], respectively. The AUC [95% confidence interval] of the rCAST, PCAC, and FOUR scores for predicting poor neurologic outcome were 0.815 [0.763 - 0.867], 0.753 [0.697 - 0.809], and 0.841 [0.796 - 0.886], respectively. The AUC [95% confidence interval] of the rCAST, PCAC, and FOUR scores for predicting mortality were 0.799 [0.751 - 0.847], 0.723 [0.673 - 0.773], and 0.813 [0.770 - 0.855], respectively. The rCAST score was superior to the PCAC score for predicting mortality (p=0.017). The FOUR score was superior to the PCAC score for predicting poor neurological outcome (p<0.001) and mortality (p<0.001).

CONCLUSION

The rCAST score can reliably predict poor outcome in a United States cohort of OHCA patients regardless of TTM status and outperforms the PCAC score.

Duration of cardiopulmonary resuscitation and phenotype of post-cardiac arrest brain injury

BACKGROUND

Patients resuscitated from cardiac arrest have variable severity of primary hypoxic ischemic brain injury (HIBI). Signatures of primary HIBI on brain imaging and electroencephalography (EEG) include diffuse cerebral edema and burst suppression with identical bursts (BSIB). We hypothesize distinct phenotypes of primary HIBI are associated with increasing cardiopulmonary resuscitation (CPR) duration.

METHODS

We identified from our prospective registry of both in-and out-of-hospital CA patients treated between January 2010 to January 2020 for this cohort study. We abstracted CPR duration, neurological examination, initial brain computed tomography gray to white ratio (GWR), and initial EEG pattern. We considered four phenotypes on presentation: awake; comatose with neither BSIB nor cerebral edema (non-malignant coma); BSIB; and cerebral edema (GWR ≤ 1.20). BSIB and cerebral edema were considered as non-mutually exclusive outcomes. We generated predicted probabilities of brain injury phenotype using localized regression.

RESULTS

We included 2,440 patients, of whom 545 (23%) were awake, 1,065 (44%) had non-malignant coma, 548 (23%) had BSIB and 438 (18%) had cerebral edema. Only 92 (4%) had both BSIB and edema. Median CPR duration was 16 [IQR 8-28] minutes. Median CPR duration increased in a stepwise manner across groups: awake 6 [3-13] minutes; non-malignant coma 15 [8-25] minutes; BSIB 21 [13-31] minutes; cerebral edema 32 [22-46] minutes. Predicted probability of phenotype changes over time.

CONCLUSIONS

Brain injury phenotype is related to CPR duration, which is a surrogate for severity of HIBI. The sequence of most likely primary HIBI phenotype with progressively longer CPR duration is awake, coma without BSIB or edema, BSIB, and finally cerebral edema.

Time to Awakening and Self-Fulfilling Prophecies After Cardiac Arrest

OBJECTIVES

Withdrawal of life-sustaining therapies for perceived poor neurologic prognosis (WLST-N) is common after resuscitation from cardiac arrest and may bias outcome estimates from models trained using observational data. We compared several approaches to outcome prediction with the goal of identifying strategies to quantify and reduce this bias.

DESIGN

Retrospective observational cohort study.

SETTING

Two academic medical centers ("UPMC" and "University of Alabama Birmingham" [UAB]).

PATIENTS

Comatose adults resuscitated from cardiac arrest.

INTERVENTION

None.

MEASUREMENTS AND MAIN RESULTS

As potential predictors, we considered clinical, laboratory, imaging, and quantitative electroencephalography data available early after hospital arrival. We followed patients until death, discharge, or awakening from coma. We used penalized Cox regression with a least absolute shrinkage and selection operator penalty and five-fold cross-validation to predict time to awakening in UPMC patients and then externally validated the model in UAB patients. This model censored patients after WLST-N, considering subsequent potential for awakening to be unknown. Next, we developed a penalized logistic model predicting awakening, which treated failure to awaken after WLST-N as a true observed outcome, and a separate logistic model predicting WLST-N. We scaled and centered individual patients' Cox and logistic predictions for awakening to allow direct comparison and then explored the difference in predictions across probabilities of WLST-N. Overall, 1,254 patients were included, and 29% awakened. Cox models performed well (mean area under the curve was 0.93 in the UPMC test sets and 0.83 in external validation). Logistic predictions of awakening were systematically more pessimistic than Cox-based predictions for patients at higher risk of WLST-N, suggesting potential for self-fulfilling prophecies to arise when failure to awaken after WLST-N is considered as the ground truth outcome.

CONCLUSIONS

Compared with traditional binary outcome prediction, censoring outcomes after WLST-N may reduce potential for bias and self-fulfilling prophecies.

A novel cardiac arrest severity score for the early prediction of hypoxic-ischemic brain injury and in-hospital death

INTRODUCTION

Out-of-hospital cardiac arrest (OHCA) outcomes are unsatisfactory despite postcardiac arrest care. Early prediction of prognoses might help stratify patients and provide tailored therapy. In this study, we derived and validated a novel scoring system to predict hypoxic-ischemic brain injury (HIBI) and in-hospital death (IHD).

METHODS

We retrospectively analyzed Korean Hypothermia Network prospective registry data collected from in Korea between 2015 and 2018. Patients without neuroprognostication data were excluded, and the remaining patients were randomly divided into derivation and validation cohorts. HIBI was defined when at least one prognostication predicted a poor outcome. IHD meant all deaths regardless of cause. In the derivation cohort, stepwise multivariate logistic regression was conducted for the HIBI and IHD scores, and model performance was assessed. We then classified the patients into four categories and analyzed the associations between the categories and cerebral performance categories (CPCs) at hospital discharge. Finally, we validated our models in an internal validation cohort.

RESULTS

Among 1373 patients, 240 were excluded, and 1133 were randomized into the derivation (n = 754) and validation cohorts (n = 379). In the derivation cohort, 7 and 8 predictors were selected for HIBI (0-8) and IHD scores (0-11), respectively, and the area under the curves (AUC) were 0.85 (95% CI 0.82-0.87) and 0.80 (95% CI 0.77-0.82), respectively. Applying optimum cutoff values of ≥6 points for HIBI and ≥7 points for IHD, the patients were classified as follows: HIBI (-)/IHD (-), Category 1 (n = 424); HIBI (-)/IHD (+), Category 2 (n = 100); HIBI (+)/IHD (-), Category 3 (n = 21); and HIBI (+)/IHD (+), Category 4 (n = 209). The CPCs at discharge were significantly different in each category (p < 0.001). In the validation cohort, the model showed moderate discrimination (AUC 0.83, 95% CI 0.79-0.87 for HIBI and AUC 0.77, 95% CI 0.72-0.81 for IHD) with good calibration. Each category of the validation cohort showed a significant difference in discharge outcomes (p < 0.001) and a similar trend to the derivation cohort.

CONCLUSIONS

We presented a novel approach for assessing illness severity after OHCA. Although external prospective studies are warranted, risk stratification for HIBI and IHD could help provide OHCA patients with appropriate treatment.

Scoring Systems to Predict Survival or Neurological Recovery after Out-of-hospital Cardiac Arrest

Numerous prediction scores have been developed to better inform clinical decision-making following out-of-hospital cardiac arrest (OHCA), however, there is no consensus among clinicians over which score to use. The aim of this review was to identify and compare scoring systems to predict survival and neurological recovery in patients with OHCA. A structured literature search of the MEDLINE database was carried out from inception to December 2021. Studies developing or validating scoring systems to predict outcome following OHCA were selected. Relevant data were extracted and synthesised for narrative review. In total, 16 scoring systems were identified: one predicting the probability of return of spontaneous circulation, six predicting survival to hospital discharge and nine predicting neurological outcome. NULL-PLEASE and CAST are recommended as the best scores to predict mortality and neurological outcome, respectively, due to the extent of external validation, ease of use and high predictive value of the variables. Whether use of these scores can lead to more cost-effective service delivery remains unclear.

Differential Effect of Targeted Temperature Management Between 32 °C and 36 °C Following Cardiac Arrest According to Initial Severity of Illness: Insights From Two International Data Sets

BACKGROUND

Recent guidelines have emphasized actively avoiding fever to improve outcomes in patients who are comatose following resuscitation from cardiac arrest (ie, out-of-hospital cardiac arrest). However, whether targeted temperature management between 32 °C and 36 °C (TTM32-36) can improve neurologic outcome in some patients remains debated.

RESEARCH QUESTION

Is there an association between the use of TTM32-36 and outcome according to severity assessed at ICU admission using a previously derived risk score?

STUDY DESIGN AND METHODS

Data prospectively collected in the Sudden Death Expertise Center (SDEC) registry (France) between May 2011 and December 2017 and in the Resuscitation Outcomes Consortium Continuous Chest Compressions (ROC-CCC) trial (United States and Canada) between June 2011 and May 2015 were used for this study. Severity at ICU admission was assessed through a modified version of the Cardiac Arrest Hospital Prognosis (mCAHP) score, divided into tertiles of severity. The study explored associations between TTM32-36 and favorable neurologic status at hospital discharge by using multiple logistic regression as well as in tertiles of severity for each data set.

RESULTS

A total of 2,723 patients were analyzed in the SDEC data set and 4,202 patients in the ROC-CCC data set. A favorable neurologic status at hospital discharge occurred in 728 (27%) patients in the French data set and in 1,239 (29%) patients in the North American data set. Among the French data set, TTM32-36 was independently associated with better neurologic outcome in the tertile of patients with low (adjusted OR, 1.63; 95% CI, 1.15-2.30; P = .006) and high (adjusted OR, 1.94; 95% CI, 1.06-3.54; P = .030) severity according to mCAHP at ICU admission. Similar results were observed in the North American data set (adjusted ORs of 1.36 [95% CI, 1.05-1.75; P = .020] and 2.42 [95% CI, 1.38-4.24; P = .002], respectively). No association was observed between TTM32-36 and outcome in the moderate groups of the two data sets.

INTERPRETATION

TTM32-36 was significantly associated with a better outcome in patients with low and high severity at ICU admission assessed according to the mCAHP score. Further studies are needed to evaluate individualized temperature control following out-of-hospital cardiac arrest.

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.

Predicting neurological outcomes after in-hospital cardiac arrests for patients with Coronavirus Disease 2019

Background

Machine learning models are more accurate than standard tools for predicting neurological outcomes in patients resuscitated after cardiac arrest. However, their accuracy in patients with Coronavirus Disease 2019 (COVID-19) is unknown. Therefore, we compared their performance in a cohort of cardiac arrest patients with COVID-19.

Methods

We conducted a retrospective analysis of resuscitation survivors in the Get With The Guidelines®-Resuscitation (GWTG-R) COVID-19 registry between February 2020 and May 2021. The primary outcome was a favorable neurological outcome, indicated by a discharge Cerebral Performance Category score ≤ 2. Pre- and peri-arrest variables were used as predictors. We applied our published logistic regression, neural network, and gradient boosted machine models developed in patients without COVID-19 to the COVID-19 cohort. We also updated the neural network model using transfer learning. Performance was compared between models and the Cardiac Arrest Survival Post-Resuscitation In-Hospital (CASPRI) score.

Results

Among the 4,125 patients with COVID-19 included in the analysis, 484 (12 %) patients survived with favorable neurological outcomes. The gradient boosted machine, trained on non-COVID-19 patients was the best performing model for predicting neurological outcomes in COVID-19 patients, significantly better than the CASPRI score (c-statistic: 0.75 vs 0.67, P < 0.001). While calibration improved for the neural network with transfer learning, it did not surpass the gradient boosted machine in terms of discrimination.

Conclusion

Our gradient boosted machine model developed in non-COVID patients had high discrimination and adequate calibration in COVID-19 resuscitation survivors and may provide clinicians with important information for these patients.

ProPACC: Protocol for a Trial of Integrated Specialty Palliative Care for Critically Ill Older Adults

BACKGROUND

Each year, approximately one million older adults die in American intensive care units (ICUs) or survive with significant functional impairment. Inadequate symptom management, surrogates' psychological distress and inappropriate healthcare use are major concerns. Pioneering work by Dr. J. Randall Curtis paved the way for integrating palliative care (PC) specialists to address these needs, but convincing proof of efficacy has not yet been demonstrated.

DESIGN

We will conduct a multicenter patient-randomized efficacy trial of integrated specialty PC (SPC) vs. usual care for 500 high-risk ICU patients over age 60 and their surrogate decision-makers from five hospitals in Pennsylvania.

INTERVENTION

The intervention will follow recommended best practices for inpatient PC consultation. Patients will receive care from a multidisciplinary SPC team within 24 hours of enrollment that continues until hospital discharge or death. SPC clinicians will meet with patients, families, and the ICU team every weekday. SPC and ICU clinicians will jointly participate in proactive family meetings according to a predefined schedule. Patients in the control arm will receive routine ICU care.

OUTCOMES

Our primary outcome is patient-centeredness of care, measured using the modified Patient Perceived Patient-Centeredness of Care scale. Secondary outcomes include surrogates' psychological symptom burden and health resource utilization. Other outcomes include patient survival, as well as interprofessional collaboration. We will also conduct prespecified subgroup analyses using variables such as PC needs, measured by the Needs of Social Nature, Existential Concerns, Symptoms, and Therapeutic Interaction scale.

CONCLUSIONS

This trial will provide robust evidence about the impact of integrating SPC with critical care on patient, family, and health system outcomes.

In-hospital mode of death after out-of-hospital cardiac arrest

Introduction

Factors associated with in-hospital mortality after out-of-hospital cardiac arrest (OHCA), such as mode of death and withdrawal of life-sustaining treatment (WLST), are not well established. This study aimed to compare clinical characteristics, timing of WLST and death, and precipitating aetiology between modes of death for OHCAs treated at hospital within a local health network.

Methods

Retrospective cohort study of adult non-traumatic OHCAs included in a hospital based OHCA registry between 2011 and 2016 and deceased at hospital discharge, excluding cases retrieved to external hospitals. Mode of death was defined as (1) cardiovascular instability, (2) non-neurological WLST, (3) neurological WLST, and (4) formal brain death. Relevant data were extracted from the registry and stratified according to mode of death and timing of death as early (within the emergency department) or late (after admission).

Results

Mode of death data was available for 69 early and 144 late deaths. Cardiovascular instability was the primary mode for 75% of early deaths, while 72% of late deaths were attributed to neurological injury (47% neurological WLST and 24% brain death, combined). Cardiovascular instability was associated with cardiac aetiology, brain death was associated with younger age and highest rates of organ donation, and neurological WLST was associated with highest rates of targeted temperature management, and longest time from arrest to death (p < 0.05).

Conclusions

This is the first study to compare clinical characteristics of adult patients resuscitated from OHCA according to in-hospital mode of death. A consensus on the definition of mode of death with standardised classification is needed.

Deep learning of early brain imaging to predict post-arrest electroencephalography

INTRODUCTION

Guidelines recommend use of computerized tomography (CT) and electroencephalography (EEG) in post-arrest prognostication. Strong associations between CT and EEG might obviate the need to acquire both modalities. We quantified these associations via deep learning.

METHODS

We performed a single-center, retrospective study including comatose patients hospitalized after cardiac arrest. We extracted brain CT DICOMs, resized and registered each to a standard anatomical atlas, performed skull stripping and windowed images to optimize contrast of the gray-white junction. We classified initial EEG as generalized suppression, other highly pathological findings or benign activity. We extracted clinical information available on presentation from our prospective registry. We trained three machine learning (ML) models to predict EEG from clinical covariates. We used three state-of-the-art approaches to build multi-headed deep learning models using similar model architectures. Finally, we combined the best performing clinical and imaging models. We evaluated discrimination in test sets.

RESULTS

We included 500 patients, of whom 218 (44%) had benign EEG findings, 135 (27%) showed generalized suppression and 147 (29%) had other highly pathological findings that were most commonly (93%) burst suppression with identical bursts. Clinical ML models had moderate discrimination (test set AUCs 0.73-0.80). Image-based deep learning performed worse (test set AUCs 0.51-0.69), particularly discriminating benign from highly pathological findings. Adding image-based deep learning to clinical models improved prediction of generalized suppression due to accurate detection of severe cerebral edema.

DISCUSSION

CT and EEG provide complementary information about post-arrest brain injury. Our results do not support selective acquisition of only one of these modalities, except in the most severely injured patients.

Precision Care in Cardiac Arrest: ICECAP (PRECICECAP) Study Protocol and Informatics Approach

BACKGROUND

Most trials in critical care have been neutral, in part because between-patient heterogeneity means not all patients respond identically to the same treatment. The Precision Care in Cardiac Arrest: Influence of Cooling duration on Efficacy in Cardiac Arrest Patients (PRECICECAP) study will apply machine learning to high-resolution, multimodality data collected from patients resuscitated from out-of-hospital cardiac arrest. We aim to discover novel biomarker signatures to predict the optimal duration of therapeutic hypothermia and 90-day functional outcomes. In parallel, we are developing a freely available software platform for standardized curation of intensive care unit-acquired data for machine learning applications.

METHODS

The Influence of Cooling duration on Efficacy in Cardiac Arrest Patients (ICECAP) study is a response-adaptive, dose-finding trial testing different durations of therapeutic hypothermia. Twelve ICECAP sites will collect data for PRECICECAP from multiple modalities routinely used after out-of-hospital cardiac arrest, including ICECAP case report forms, detailed medication data, cardiopulmonary and electroencephalographic waveforms, and digital imaging and communications in medicine files (DICOMs). We partnered with Moberg Analytics to develop a freely available software platform to allow high-resolution critical care data to be used efficiently and effectively. We will use an autoencoder neural network to create low-dimensional representations of all raw waveforms and derivative features, censored at rewarming to ensure clinical usability to guide optimal duration of hypothermia. We will also consider simple features that are historically considered to be important. Finally, we will create a supervised deep learning neural network algorithm to directly predict 90-day functional outcome from large sets of novel features.

RESULTS

PRECICECAP is currently enrolling and will be completed in late 2025.

CONCLUSIONS

Cardiac arrest is a heterogeneous disease that causes substantial morbidity and mortality. PRECICECAP will advance the overarching goal of titrating personalized neurocritical care on the basis of robust measures of individual need and treatment responsiveness. The software platform we develop will be broadly applicable to hospital-based research after acute illness or injury.

Effects of targeted temperature management at 33°C vs. 36°C on comatose patients after cardiac arrest stratified by the severity of encephalopathy

OBJECTIVES

To assess neurological outcome after targeted temperature management (TTM) at 33°C vs. 36°C, stratified by the severity of encephalopathy based on EEG-patterns at 12 and 24h.

DESIGN

Post hoc analysis of prospective cohort study.

SETTING

Five Dutch Intensive Care units.

PATIENTS

479 adult comatose post-cardiac arrest patients.

INTERVENTIONS

TTM at 33°C (n=270) or 36°C (n=209) and continuous EEG monitoring.

MEASUREMENTS AND MAIN RESULTS

Outcome according to the cerebral performance category (CPC) score at 6 months post-cardiac arrest was similar after 33°C and 36°C. However, when stratified by the severity of encephalopathy based on EEG-patterns at 12 and 24h after cardiac arrest, the proportion of good outcome (CPC 1-2) in patients with moderate encephalopathy was significantly larger after TTM at 33°C (66% vs. 45%; Odds Ratios 2.38, 95% CI=1.32-4.30; p=0.004). In contrast, with mild encephalopathy, there was no statistically significant difference in the proportion of patients with good outcome between 33°C and 36°C (88% vs. 81%; OR 1.68, 95% CI=0.65-4.38; p=0.282). Ordinal regression analysis showed a shift towards higher CPC scores when treated with TTM 33°C as compared with 36°C in moderate encephalopathy (cOR 2.39; 95% CI=1.40-4.08; p=0.001), but not in mild encephalopathy (cOR 0.81 95% CI=0.41-1.59; p=0.537). Adjustment for initial cardiac rhythm and cause of arrest did not change this relationship.

CONCLUSIONS

Effects of TTM probably depend on the severity of encephalopathy in comatose patients after cardiac arrest. These results support inclusion of predefined subgroup analyses based on EEG measures of the severity of encephalopathy in future clinical trials.

Comparison of Machine Learning Methods for Predicting Outcomes After In-Hospital Cardiac Arrest

OBJECTIVES

Prognostication of neurologic status among survivors of in-hospital cardiac arrests remains a challenging task for physicians. Although models such as the Cardiac Arrest Survival Post-Resuscitation In-hospital score are useful for predicting neurologic outcomes, they were developed using traditional statistical techniques. In this study, we derive and compare the performance of several machine learning models with each other and with the Cardiac Arrest Survival Post-Resuscitation In-hospital score for predicting the likelihood of favorable neurologic outcomes among survivors of resuscitation.

DESIGN

Analysis of the Get With The Guidelines-Resuscitation registry.

SETTING

Seven-hundred fifty-five hospitals participating in Get With The Guidelines-Resuscitation from January 1, 2001, to January 28, 2017.

PATIENTS

Adult in-hospital cardiac arrest survivors.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Of 117,674 patients in our cohort, 28,409 (24%) had a favorable neurologic outcome, as defined as survival with a Cerebral Performance Category score of less than or equal to 2 at discharge. Using patient characteristics, pre-existing conditions, prearrest interventions, and periarrest variables, we constructed logistic regression, support vector machines, random forests, gradient boosted machines, and neural network machine learning models to predict favorable neurologic outcome. Events prior to October 20, 2009, were used for model derivation, and all subsequent events were used for validation. The gradient boosted machine predicted favorable neurologic status at discharge significantly better than the Cardiac Arrest Survival Post-Resuscitation In-hospital score (C-statistic: 0.81 vs 0.73; p < 0.001) and outperformed all other machine learning models in terms of discrimination, calibration, and accuracy measures. Variables that were consistently most important for prediction across all models were duration of arrest, initial cardiac arrest rhythm, admission Cerebral Performance Category score, and age.

CONCLUSIONS

The gradient boosted machine algorithm was the most accurate for predicting favorable neurologic outcomes in in-hospital cardiac arrest survivors. Our results highlight the utility of machine learning for predicting neurologic outcomes in resuscitated patients.

Long-term Outcomes of Post-Cardiac Arrest Patients with Severe Neurological and Functional Impairments at Hospital Discharge

BACKGROUND

Patients resuscitated from cardiac arrest who have severe neurological or functional disability at discharge require high-intensity long-term support. However, few data describe the long-term survival and health-care utilization for these patients.

METHODS

We identified a cohort of cardiac arrest survivors ≥ 18 years of age, treated at a single center in Western Pennsylvania from January 2010 to December 2019, with a modified Rankin scale (mRS) of 5 at hospital discharge. We recorded demographics, cardiac arrest characteristics, and neurological exam at hospital discharge. We characterized long term survival and mortality through December 31, 2020 through National Death Index query. We described survival time overall and in subgroups using Kaplan-Meier curves and compared using log-rank tests.We linked cases with administrative data to determine 30, 90 day, and one-year hospital readmission rate. For subjects unable to follow commands at discharge, we reviewed records from index hospitalization to the present to describe improvement in neurological status and return home.

RESULTS

We screened 2,687 patients of which 975 survived to discharge. We identified 190 subjects with mRS of 5 at hospital discharge who were sent to non-hospice settings. Of these, 43 (23%) did not follow commands at discharge. One-year mortality was 38% (n = 71) with a median survival time of 4.2 years (IQR 0.3-10.9). Duration of survival was shorter in older subjects but did not differ based on, sex, or ability to follow commands at hospital discharge. Within the first year of discharge, 58% (n = 111) of subjects had at least one hospitalization with a median length of stay of 8 days [IQR 3-19]. Of subjects who did not follow commands at hospital discharge, 5/43 (11%) followed commands and 9 (21%) were reportedly living at home on subsequent encounters.

CONCLUSIONS

Of survivors treated over a decade at our institution, 20% (n = 190) were discharged from the hospital with severe functional disability. One-year mortality was 38%, and hospital readmissions were frequent. Few patients discharged unable to follow commands regained the ability over the period of observation, but many did return to living at home. These data can help inform decision maker expectations for patient trajectory and life expectancy.

External Validation of Pittsburgh Cardiac Arrest Category Illness Severity Score

Early prognostication post-cardiac arrest can help determine appropriate medical management and help evaluate effectiveness of post-arrest interventions. The Pittsburgh Cardiac Arrest Category (PCAC) severity score is a 4-level illness severity score found to strongly predict patient outcomes in both in- (IHCA) and out-of-hospital cardiac arrests (OHCA). We aimed to validate the PCAC severity score in an external cohort of cardiac arrest patients.

METHODS

We retrospectively assigned PCAC scores to both IHCA and OHCA patients treated by our hypothermia team from July 1, 2009 to July 1 2016. Our primary outcome was survival to hospital discharge. Secondary outcomes were favorable functional status defined as favorable discharge disposition (home or acute rehabilitation), discharge Cerebral Performance Category (CPC); and discharge modified Rankin Scale (mRS). We tested the association of PCAC and outcomes using a multivariable adjusted logistic regression model.

RESULTS

We included 317 subjects in our model. PCAC was strongly associated with survival I Reference; II adjusted odds ratio (OR) 0.20 95% confidence interval (CI) 0.35-0.66, III (OR 0.14 CI 0.3-0.73, p<0.05); IV (OR 0.05 CI 0.01-0.24, p<0.01). PCAC was similarly associated with favorable functional outcomes: favorable discharge disposition II (OR 0.12 CI 0.02-0.68), III (OR 0.19 CI 0.05-0.74, p<0.05) IV (OR 0.05 CI 0.01-0.22, p<0.01); favorable CPC score II (OR 0.25 CI 0.06-1.03), III (OR 0.14 CI 0.03-0.57, p<0.01), IV (OR 0.05 CI 0.01-0.20, p<0.01) and favorable mRS (OR 0.47 CI (0.33-0.68)).

CONCLUSION

Early (<6hr post-arrest) PCAC severity scoring strongly predicts patient outcomes from cardiac arrest in both OHCA and IHCA.

One-year outcomes in individual domains of the cerebral performance category extended

Background

Physical and cognitive impairments are common after cardiac arrest, and recovery varies. This study assessed recovery of individual domains of the Cerebral Performance Category- Extended (CPC-E) 1-year after cardiac arrest. We hypothesized patients would have recovery in all CPC-E domains 1-year after the index cardiac arrest.

Methods

Prospective cohort study of cardiac arrest survivors evaluating outcome measures mRS, CPC, and CPC-E. Outcomes were assessed at discharge, 3-months, 6-months, and 1-year. We defined recovery of a CPC-E domain when >90% of patients had scores of 1-2 in that domain.

Results

Of 156 patients discharged, 57 completed the CPC-E at discharge, and were included in the analysis. 37 patients had follow-up at 3-months, and 23 patients had follow-up at 6 and 12 months. Only 16 patients had assessments at all four timepoints. Domains of alertness (N = 56, 98%) logical thinking (N = 56; 98%), and attention (N = 55; 96%) recovered by hospital discharge. BADL (N = 34; 92%) and motor skills (N = 36; 97%) recovered by 3-months. Most patients (N = 20; 87%) experienced slight-to-no disability or symptoms (mRS 0-2/CPC 1-2) at 1-year follow up. CPC-E domains of short term memory (78%), mood (87%), fatigue (22%), complex ADL (78%), and return to work (65%) did not recover by 1-year.

Conclusions

CPC-E domains of alertness, logical thinking, and attention recover rapidly, while domains of short term memory, mood, fatigue, complex ADL and return to work remain chronically impaired 1-year after cardiac arrest. These deficits are not detected by mRS and CPC. Interventions to improve recovery in these domains are needed.

Sex differences in post cardiac arrest discharge locations

Background

We explored sex-based differences in discharge location after resuscitation from cardiac arrest.

Methods

We performed a single-center retrospective cohort study including patients hospitalized after resuscitation from cardiac arrest from January 2010 to May 2020. We identified patients from a prospective registry, from which we extracted standard demographic and clinical variables. We explored favorable discharge location, defined as discharge to home or acute rehabilitation for survivors to hospital discharge. We tested the association of sex with the residuals of a multivariable logistic regression built using bidirectional selection to control for clinically relevant covariates.

Results

We included 2,278 patients. Mean age was 59 (SD 16), 40% were women, and 77% were admitted after out-of-hospital cardiac arrest. A total of 970 patients (43%) survived to discharge; of those, 607 (63% of survivors) had a favorable discharge location. Female sex showed a weak independent association with unfavorable discharge location (adjusted OR 0.94 (95%CI 0.89–0.99)).

Conclusions

Our results suggest a possible sex-based disparity in discharge location after cardiac arrest.

Differential Effectiveness of Hypothermic Targeted Temperature Management According to the Severity of Post-Cardiac Arrest Syndrome

International guidelines recommend targeted temperature management (TTM) to improve the neurological outcomes in adult patients with post-cardiac arrest syndrome (PCAS). However, it still remains unclear if the lower temperature setting (hypothermic TTM) or higher temperature setting (normothermic TTM) is superior for TTM. According to the most recent large randomized controlled trial (RCT), hypothermic TTM was not found to be associated with superior neurological outcomes than normothermic TTM in PCAS patients. Even though this represents high-quality evidence obtained from a well-designed large RCT, we believe that we still need to continue investigating the potential benefits of hypothermic TTM. In fact, several studies have indicated that the beneficial effect of hypothermic TTM differs according to the severity of PCAS, suggesting that there may be a subgroup of PCAS patients that is especially likely to benefit from hypothermic TTM. Herein, we summarize the results of major RCTs conducted to evaluate the beneficial effects of hypothermic TTM, review the recent literature suggesting the possibility that the therapeutic effect of hypothermic TTM differs according to the severity of PCAS, and discuss the potential of individualized TTM.

Neuroprognostication after Cardiac Arrest: Who Recovers? Who Progresses to Brain Death?

Approximately 15% of deaths in developed nations are due to sudden cardiac arrest, making it the most common cause of death worldwide. Though high-quality cardiopulmonary resuscitation has improved overall survival rates, the majority of survivors remain comatose after return of spontaneous circulation secondary to hypoxic ischemic injury. Since the advent of targeted temperature management, neurologic recovery has improved substantially, but the majority of patients are left with neurologic deficits ranging from minor cognitive impairment to persistent coma. Of those who survive cardiac arrest, but die during their hospitalization, some progress to brain death and others die after withdrawal of life-sustaining treatment due to anticipated poor neurologic prognosis. Here, we discuss considerations neurologists must make when asked, "Given their recent cardiac arrest, how much neurologic improvement do we expect for this patient?"

Ultra-early serum concentrations of neuronal and astroglial biomarkers predict poor neurological outcome after out-of-hospital cardiac arrest-a pilot neuroprognostic study

OBJECTIVES

To assess ultra-early neuroprognostic significance of GFAP, NF-L, UCH-L1, tau, and S100B concentrations, change trajectory, and combination profile after Out-of-Hospital Cardiac Arrest (OHCA).

METHODS

Prospective enrollment of 22 OHCA and 10 control patients at an academic tertiary care center between May 1, 2017 and January 28, 2020. Blood was collected within one hour of return of spontaneous circulation (ROSC) (H0), at hours 6 (H6), 12, 18, 24, and daily or until discharge or death. Biomarker concentrations, multifactor score, and trajectory change were assessed and compared to final neurologic status (good vs poor Cerebral Performance Category; CPC 1-2 vs CPC 3-5, respectively).

RESULTS

10 patients had good and 12 had poor neurologic outcomes. Poor outcome patients had higher biomarker concentrations and combined biomarker scores at early time points. The earliest significant difference between good and poor outcome patients' serum biomarkers were at H12 for GFAP (good median: 425 pg/mL [IQR:370-630] vs poor: 5954[1712-65,055] pg/mL; p < 0.001), H12 for NF-L (64[41-69] vs 898[348-1990] pg/mL; p < 0.001), H0 for Tau (31[8-51] vs 124[53-238] pg/mL; p = 0.025), H0 for UCH-L1 (898[375-1600] vs 2475[1898-4098] pg/mL; p = 0.008), and H6 for S100B (123[70-290] vs 895[360-1199] pg/mL; p = 0.002). Four biomarker composite scores differed by H12 (78.03[52.03-111.25] vs 749 [198.46-4870.63] pg/mL; p = 0.003). Machine-learning approach also identified that four-marker score trajectory group memberships are in concordance with patient outcome.

CONCLUSIONS

Ultra-early serial serum concentrations of neuronal and astroglial biomarkers may be of neuroprognostic significance following OHCA.

Simultaneous external validation of various cardiac arrest prognostic scores: a single-center retrospective study

Background

This study aimed to compare and validate the out-of-hospital cardiac arrest (OHCA); cardiac arrest hospital prognosis (CAHP); non-shockable rhythm, unwitnessed arrest, long no-flow or long low-flow period, blood pH < 7.2, lactate > 7.0 mmol/L, end-stage chronic kidney disease, age ≥ 85 years, still resuscitation, and extracardiac cause (NULL-PLEASE) clinical; post-cardiac arrest syndrome for therapeutic hypothermia (CAST); and revised CAST (rCAST) scores in OHCA patients treated with recent cardiopulmonary resuscitation strategies.

Methods

We retrospectively collected data on adult OHCA patients admitted to our emergency department between February 2015 and July 2018. OHCA, CAHP, NULL-PLEASE clinical, CAST, and rCAST scores were calculated based on the data collected. The predictive abilities of each score were tested using the area under the curve (AUC) of the receiver operating characteristic (ROC) curve.

Results

We identified 236 OHCA patients from computer-based medical records and analyzed 189 without missing data. In OHCA patients without bystander witnesses, CAHP and OHCA scores were not calculated. Although the predictive abilities of the scores were not significantly different, the NULL-PLEASE score had a large AUC of ROC curve in various OHCA patients. Furthermore, in patients with bystander-witnessed OHCA, the NULL-PLEASE score had large partial AUCs of ROC from sensitivity 0.8–1.0 and specificity 0.8–1.0.

Conclusions

The NULL-PLEASE score had a high, comprehensive predictive ability in various OHCA patients. Furthermore, the NULL-PLEASE score had a high predictive ability for good and poor neurological outcomes in patients with bystander-witnessed OHCA.

Precision Cardiac Arrest Resuscitation Based on Etiology

Cardiac arrest results from a broad range of etiologies that can be broadly grouped as sudden and asphyxial. Animal studies point to differences in injury pathways invoked in the heart and brain that drive injury and outcome after these different forms of cardiac arrest. Present guidelines largely ignore etiology in their management recommendations. Existing clinical data reveal significant heterogeneity in the utility of presently employed resuscitation and postresuscitation strategies based on etiology. The development of future neuroprotective and cardioprotective therapies should also take etiology into consideration to optimize the chances for successful translation.

Impact of benzodiazepines on time to awakening in post cardiac arrest patients

AIM

Although guidelines recommend use of short acting sedation after cardiac arrest, there is significant practice variation. We examined whether benzodiazepine use is associated with delayed awakening in this population.

METHODS

We performed a retrospective single center study including comatose patients treated after in- or out-of-hospital cardiac arrest from January 2010 to September 2019. We excluded patients who awakened within 6 h of arrest, those who arrested due to trauma or neurological event, those with nonsurvivable primary brain injury and those with refractory shock. Our primary exposure of interest was high-dose benzodiazepine (>10 mg of midazolam equivalents per day) administration in the first 72-h post arrest. Our primary outcome was time to awakening. We used Cox regression to test for an independent association between exposure and outcome after controlling for biologically plausible covariates.

RESULTS

Overall, 2778 patients presented during the study period, 621 met inclusion criteria and 209 (34%) awakened after a median of 4 [IQR 3-7] days. Patients who received high-dose benzodiazepines awakened later than those who did not (5 [IQR 3-11] vs. 3 [IQR 3-6] days, P = 0.004). In adjusted regression, high-dose benzodiazepine exposure was independently associated with delayed awakening (adjusted hazard ratio 0.63 (95% CI 0.43-0.92)). Length of stay, awakening to discharge, and duration of mechanical ventilation were similar across groups.

CONCLUSION

High-dose benzodiazepine exposure is independently associated with delayed awakening in comatose survivors of cardiac arrest.

Multimodal Long-Term Predictors of Outcome in Out of Hospital Cardiac Arrest Patients Treated with Targeted Temperature Management at 36 °C

Introduction: Early prediction of long-term outcomes in patients resuscitated after cardiac arrest (CA) is still challenging. Guidelines suggested a multimodal approach combining multiple predictors. We evaluated whether the combination of the electroencephalography (EEG) reactivity, somatosensory evoked potentials (SSEPs) cortical complex and Gray to White matter ratio (GWR) on brain computed tomography (CT) at different temperatures could predict survival and good outcome at hospital discharge and six months after the event. Methods: We performed a retrospective cohort study including consecutive adult, non-traumatic patients resuscitated from out-of-hospital CA who remained comatose on admission to our intensive care unit from 2013 to 2017. We acquired SSEPs and EEGs during the treatment at 36 °C and after rewarming at 37 °C, Gray to white matter ratio (GWR) was calculated on the brain computed tomography scan performed within six hours of the hospital admission. We primarily hypothesized that SSEP was associated with favor-able functional outcome at distance and secondarily that SSEP provides independent information from EEG and CT. Outcomes were evaluated using the Cerebral Performance Category (CPC) scale at six months from discharge. Results: Of 171 resuscitated patients, 75 were excluded due to missing data or uninterpretable neurophysiological findings. EEG reactivity at 37 °C has been shown the best single predictor of good out-come (AUC 0.803) while N20P25 was the best single predictor for survival at each time point. (AUC 0.775 at discharge and AUC 0.747 at six months follow up). The predictive value of a model including EEG reactivity, average GWR, and SSEP N20P25 amplitude was superior (AUC 0.841 for survival and 0.920 for good out-come) to any combination of two tests or any single test. Conclusions: Our study, in which life-sustaining treatments were never suspended, suggests SSEP cortical complex N20P25, after normothermia and off sedation, is a reliable predictor for survival at any time. When SSEP cortical complex N20P25 is added into a model with GWR average and EEG reactivity, the predictivity for good outcome and survival at distance is superior than each single test alone.

Goal-Directed Care Using Invasive Neuromonitoring Versus Standard of Care After Cardiac Arrest: A Matched Cohort Study

PURPOSE

Following return of spontaneous circulation after cardiac arrest, hypoxic ischemic brain injury is the primary cause of mortality and disability. Goal-directed care using invasive multimodal neuromonitoring has emerged as a possible resuscitation strategy. We evaluated whether goal-directed care was associated with improved neurologic outcome in hypoxic ischemic brain injury patients after cardiac arrest.

DESIGN

Retrospective, single-center, matched observational cohort study.

SETTING

Quaternary academic medical center.

PATIENTS

Adult patients admitted to the ICU following return of spontaneous circulation postcardiac arrest with clinical evidence of hypoxic ischemic brain injury defined as greater than or equal to 10 minutes of cardiac arrest with an unconfounded postresuscitation Glasgow Coma Scale of less than or equal to 8.

INTERVENTIONS

We compared patients who underwent goal-directed care using invasive neuromonitoring with those treated with standard of care (using both total and matched groups).

MEASUREMENTS AND MAIN RESULTS

Goal-directed care patients were matched 1:1 to standard of care patients using propensity scores and exact matching. The primary outcome was a 6-month favorable neurologic outcome (Cerebral Performance Category of 1 or 2). We included 65 patients, of whom 21 received goal-directed care and 44 patients received standard of care. The median age was 50 (interquartile range, 35-61), 48 (74%) were male, and seven (11%) had shockable rhythms. Favorable neurologic outcome at 6 months was significantly greater in the goal-directed care group (n = 9/21 [43%]) compared with the matched (n = 2/21 [10%], p = 0.016) and total (n = 8/44 [18%], p = 0.034) standard of care groups. Goal-directed care group patients had higher mean arterial pressure (p < 0.001 vs total; p = 0.0060 vs matched) and lower temperature (p = 0.007 vs total; p = 0.041 vs matched).

CONCLUSIONS

In this preliminary study of patients with hypoxic ischemic brain injury postcardiac arrest, goal-directed care guided by invasive neuromonitoring was associated with a 6-month favorable neurologic outcome (Cerebral Performance Category 1 or 2) versus standard of care. Significant work is required to confirm this finding in a prospectively designed study.

Beyond Extracorporeal Cardiopulmonary Resuscitation: Systems of Care Supporting Cardiac Arrest Patients

Introduction: Out-of-hospital cardiac arrest (OHCA) is a major cause of death and disability in the United States. Cardiac arrest centers (CAC) are necessary for the management of these critically ill and complex post arrest patients due to their specialized services and provider expertise. We report the case of a patient with OHCA and the systems of care involved in his resuscitation and recovery. Case Report: Emergency medical services attended a 39-year-old male with ongoing bystander cardiopulmonary resuscitation (CPR) after a witnessed collapse. Despite receiving appropriate advanced cardiac life support, including three defibrillations, he remained in refractory ventricular fibrillation. A prehospital physician identified him as an extracorporeal cardiopulmonary resuscitation (ECPR) candidate due to his age, witnessed arrest, refractory rhythm, and functional status. He was expedited to a CAC but no longer qualified for ECPR due to the time limit. He was resuscitated by the multiple teams activated prior to his arrival. He eventually had sustained return of circulation, was taken to the catheterization lab for emergent percutaneous coronary intervention, and recovered with a good neurologic outcome. Conclusion: Cardiac arrest centers may be capable of advanced interventions including ECPR. However, the systems of care offered by these centers is itself a lifesaving intervention. As this case highlights, despite not receiving the specified intervention (ECPR) the systems of care required to offer such a resource led to this favorable outcome.

Recovery from disorders of consciousness: mechanisms, prognosis and emerging therapies

Substantial progress has been made over the past two decades in detecting, predicting and promoting recovery of consciousness in patients with disorders of consciousness (DoC) caused by severe brain injuries. Advanced neuroimaging and electrophysiological techniques have revealed new insights into the biological mechanisms underlying recovery of consciousness and have enabled the identification of preserved brain networks in patients who seem unresponsive, thus raising hope for more accurate diagnosis and prognosis. Emerging evidence suggests that covert consciousness, or cognitive motor dissociation (CMD), is present in up to 15-20% of patients with DoC and that detection of CMD in the intensive care unit can predict functional recovery at 1 year post injury. Although fundamental questions remain about which patients with DoC have the potential for recovery, novel pharmacological and electrophysiological therapies have shown the potential to reactivate injured neural networks and promote re-emergence of consciousness. In this Review, we focus on mechanisms of recovery from DoC in the acute and subacute-to-chronic stages, and we discuss recent progress in detecting and predicting recovery of consciousness. We also describe the developments in pharmacological and electrophysiological therapies that are creating new opportunities to improve the lives of patients with DoC.

Recovery among post-arrest patients with mild-to-moderate cerebral edema

BACKGROUND

Cerebral edema after cardiac arrest may be a modifiable cause of secondary brain injury. We aimed to identify processes of care associated with recovery in a cohort of patients with mild to moderate edema.

METHODS

We conducted a retrospective cohort study of adults resuscitated from out-of-hospital arrest (OHCA) at a single center from 2010 to 2018. We included those with cerebral edema ranging from mild to moderate (gray to white matter attenuation ratio (GWR) 1.2 to 1.3 on initial brain computerized tomography (CT). We used Pittsburgh Cardiac Arrest Category (PCAC) to adjust for illness severity and considered the following values in the first 24 h of admission as additional predictors: GWR, lab values affecting serum osmolality (sodium, glucose, blood urea nitrogen (BUN)), total osmolality, change in osmolality from 0 to 24 h, cardiac etiology of arrest, targeted temperature to 33 °C (vs 36 °C), time-weighted mean arterial pressure (MAP), partial pressures of arterial oxygen and carbon dioxide and select medications. Our primary outcome was discharge with cerebral performance category 1-3. We used unadjusted and adjusted logistic regression for analysis.

RESULTS

We included 214 patients for whom CT was performed median 3.8 [IQR 2.4-5.2] hours after collapse. Median age was 57 [IQR 48-67] years, 82 (38%) were female, and 68 (32%) arrested from ventricular tachycardia or fibrillation. In adjusted models, modifiable processes of care were not associated with outcome.

CONCLUSIONS

Illness severity, but not modifiable processes of care, were associated with recovery among post-arrest patients with mild-to-moderate cerebral edema.

Neurologic complications of cardiac arrest

Cardiac arrest is a catastrophic event with high morbidity and mortality. Despite advances over time in cardiac arrest management and postresuscitation care, the neurologic consequences of cardiac arrest are frequently devastating to patients and their families. Targeted temperature management is an intervention aimed at limiting postanoxic injury and improving neurologic outcomes following cardiac arrest. Recovery of neurologic function governs long-term outcome after cardiac arrest and prognosticating on the potential for recovery is a heavy burden for physicians. An early and accurate estimate of the potential for recovery can establish realistic expectations and avoid futile care in those destined for a poor outcome. This chapter reviews the epidemiology, pathophysiology, therapeutic interventions, prognostication, and neurologic sequelae of cardiac arrest.

Early risk stratification after resuscitation from cardiac arrest

Emergency clinicians often resuscitate cardiac arrest patients, and after acute resuscitation, clinicians face multiple decisions regarding disposition. Recent evidence suggests that out-of-hospital cardiac arrest patients with return of spontaneous circulation have higher odds of survival to hospital discharge, long-term survival, and improved functional outcomes when treated at centers that can provide advanced multidisciplinary care. For community clinicians, a high volume cardiac arrest center may be hours away. While current guidelines recommend against neurological prognostication in the first hours or days after return of spontaneous circulation, there are early findings suggestive of irrecoverable brain injury in which the patient would receive no benefit from transfer. In this Concepts article, we describe a simplified approach to quickly evaluate neurological status in cardiac arrest patients and identify findings concerning for irrecoverable brain injury. Characteristics of the arrest and resuscitation, initial neurological assessment, and brain computed tomography together can identify patients with high likelihood of irrecoverable anoxic injury. Patients who may benefit from centers with access to continuous electroencephalography are discussed. This approach can be used to identify patients who may benefit from rapid transfer to cardiac arrest centers versus those who may benefit from care close to home. Risk stratification also can provide realistic expectations for recovery to families.

Etiology and Determinants of In-Hospital Survival in Patients Resuscitated After Out-of-Hospital Cardiac Arrest in an Urban Medical Center

Out-of-hospital cardiac arrest (OHCA) is a leading cause of mortality globally. The goals of this study were to describe common causes of OHCA in an urban US medical center, identify predictive factors for survival, and to assess whether neurological status upon return of spontaneous circulation might be predictive of outcomes: 124 consecutive patients aged 18 years and older with OHCA admitted at Advocate Illinois Masonic Medical Center were studied. All patients resuscitated in the field with return of spontaneous circulation then transferred to the emergency department were included. The Glasgow Coma Score (GCS) was evaluated immediately on hospital arrival. In the total group, 34% (42 of 124) were discharged alive. In patients with coronary artery disease (CAD), 51% (20 of 39) were discharged alive versus 26% (22 of 85) of non-CAD patients (p <0.01). Initial GCS ≥ 9 was highly predictive of survival: 94% (34 of 36) of patients with GCS ≥ 9 survived versus 9% (8 of 88) with GCS ≤ 8 (p <0.0001). Defibrillation in the field was predictive of survival (chi-square = 7.81, p = 0.005). In the CAD group, all 16 patients with GCS ≥ 9 on presentation to the Emergency Department survived whereas all 13 with GCS ≤ 5 died (both p <0.0001). In the non-CAD group, 18 of 20 patients with GCS ≥ 9 survived, whereas only 2 of 52 with GCS ≤ 5 survived (both p <0.0001). Multivariate analysis by logistic regression showed that the strongest predictor of survival in the non-CAD subgroup was GCS (OR 0.27, CI 0.19 to 0.55, p <0.001). In conclusion, the etiology of the OHCA, immediate neurologic status, and defibrillation in the field (suggesting presenting arrhythmia) were predictive of survival. Immediate neurological recovery (GCS ≥ 9) regardless of etiology was a strong predictor of survival to discharge. Additional predictive factors depend on the etiology of the OHCA event. These data suggest that these straightforward factors can be helpful in predicting outcome in patients resuscitated after OHCA.

Rate of intra-arrest epinephrine administration and early post-arrest organ failure after in-hospital cardiac arrest

INTRODUCTION

Data supporting epinephrine administration during resuscitation of in-hospital cardiac arrest (IHCA) are limited. We hypothesized that more frequent epinephrine administration would predict greater early end-organ dysfunction and worse outcomes after IHCA.

METHODS

We performed a retrospective cohort study including patients resuscitated from IHCA at one of 67 hospitals between 2010 and 2019 who were ultimately cared for at a single tertiary care hospital. Our primary exposure of interest was rate of intra-arrest epinephrine bolus administration (mg/min). We considered several outcomes, including severity of early cardiovascular failure (modeled using Sequential Organ Failure Assessment (SOFA) cardiovascular subscore), early neurological and early global illness severity injury (modeled as Pittsburgh Cardiac Arrest Category (PCAC)). We used generalized linear models to test for independent associations between rate of epinephrine administration and outcomes.

RESULTS

We included 695 eligible patients. Mean age was 62 ± 15 years, 416 (60%) were male and 172 (26%) had an initial shockable rhythm. Median arrest duration was 16 [IQR 9-25] min, and median rate of epinephrine administration was 0.2 [IQR 0.1-0.3] mg/min. Higher rate of epinephrine predicted worse PCAC, and lower survival in patients with initial shockable rhythms. There was no association between rate of epinephrine and other outcomes.

CONCLUSION

Higher rates of epinephrine administration during IHCA are associated with more severe early global illness severity.