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.

Time to specialty care and mortality after cardiac arrest.

INTRODUCTION: Out of hospital cardiac arrest (OHCA) patients are often transported to the closest emergency department (ED) or cardiac center for initial stabilization and may be transferred for further care. We investigated the effects of delay to transfer on in hospital mortality at a receiving facility. METHODS: We included OHCA patients transported from the ED by a single critical care transport service to a quaternary care facility between 2010 and 2018. We calculated dwell time as time from arrest to critical care transport team contact. We abstracted demographics, arrest characteristics, and interventions started prior to transport arrival. For the primary analysis, we used logistic regression to determine the association of dwell time and in-hospital mortality. As secondary outcomes we investigated for associations of dwell time and mortality within 24 h of arrival, proximate cause of death among decedents, arterial pH and lactate on arrival, sum of worst SOFA subscales within 24 h of arrival, and rearrest during interfacility transport. RESULTS: We included 572 OHCA patients transported from an outside ED to our facility. Median dwell time was 113 (IQR = 85-159) minutes. Measured in 30 min epochs, increasing dwell time was not associated with in-hospital mortality, 24-h mortality, cause of death and initial pH, but was associated with lower 24-h SOFA score (p = 0.01) and lower initial lactate (p = 0.03). Rearrest during transport was rare (n = 29, 5%). Dwell time was associated with lower probability of rearrest during transport (OR = 0.847, (95% CI 0.68-1.01), p = 0.07). CONCLUSIONS: Dwell time was not associated with in-hospital mortality. Rapid transport may be associated with risk of rearrest. Prospective data are needed to clarify optimal patient stabilization and transport strategies.

Effect of Fatigue Training on Safety, Fatigue, and Sleep in Emergency Medical Services Personnel and Other Shift Workers: A Systematic Review and Meta-Analysis.

BACKGROUND: Fatigue training may be an effective way to mitigate fatigue-related risk. We aimed to critically review and synthesize existing literature on the impact of fatigue training on fatigue-related outcomes for Emergency Medical Services (EMS) personnel and similar shift worker groups. METHODS: We performed a systematic literature review for studies that tested the impact of fatigue training of EMS personnel or similar shift workers. Outcomes of interest included personnel safety, patient safety, personnel performance, acute fatigue, indicators of sleep duration and quality, indicators of long-term health (e.g., cardiovascular disease), and burnout/stress. A meta-analysis was performed to determine the impact of fatigue training on sleep quality. RESULTS: Of the 3,817 records initially identified for review, 18 studies were relevant and examined fatigue training in shift workers using an experimental or quasi-experimental design. Fatigue training improved patient safety, personal safety, and ratings of acute fatigue and reduced stress and burnout. A meta-analysis of five studies showed improvement in sleep quality (Fixed Effects SMD -0.87; 95% CI -1.05 to -0.69; p < 0.00001; Random Effects SMD -0.80; 95% CI -1.72, 0.12; p < 0.00001). CONCLUSIONS: Reviewed literature indicated that fatigue training improved safety and health outcomes in shift workers. Further research is required to identify the optimal components of fatigue training programs to maximize the beneficial outcomes.

Effect of Task Load Interventions on Fatigue in Emergency Medical Services Personnel and Other Shift Workers: A Systematic Review.

BACKGROUND: Modifying the task load of Emergency Medical Services (EMS) personnel may mitigate fatigue, sleep quality and fatigue related risks. A review of the literature addressing task load interventions may benefit EMS administrators as they craft policies related to mitigating fatigue. We conducted a systematic review of the peer-reviewed literature to address the following question: "In EMS personnel, do task load interventions mitigate fatigue, mitigate fatigue-related risks, and/or improve sleep?" (PROSPERO 2016:CRD42016040114). METHODS: We performed a systematic review of the literature that described use of randomized controlled trials, quasi-experimental studies, and observational study designs. We retained and reviewed research that involved EMS personnel or similar shift worker groups 18 years of age and older. Studies of 'healthy volunteers' and non-shift worker populations were excluded. Studies were included where the methodology of the study implied a theoretical framework of task load (or workload) affecting fatigue, and then fatigue related outcomes. Outcomes of interest included personnel safety, patient safety, personnel performance, acute fatigue, and cost to system. We used the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) methodology to summarize findings and assess quality of evidence from very low to high quality. RESULTS: The search strategy yielded 3,394 unique records resulting in 58 records included as potentially eligible. An additional 69 studies were reviewed in full following searches of bibliographies. We detected wide variation in the description and measurement of task load in the retained and excluded research. Among 127 potentially relevant studies reviewed in full, five were judged eligible. None of the retained studies reported findings germane to personnel safety, patient safety, or cost to system. We judged most studies to have serious or very serious risk of bias. CONCLUSIONS: The effect of task load interventions on fatigue, fatigue-related risks, and/or sleep quality was not estimable and the overall quality of evidence was judged low or very low. There was considerable heterogeneity in how task load was defined and measured.

Effects of Napping During Shift Work on Sleepiness and Performance in Emergency Medical Services Personnel and Similar Shift Workers: A Systematic Review and Meta-Analysis.

BACKGROUND: Scheduled napping during work shifts may be an effective way to mitigate fatigue-related risk. This study aimed to critically review and synthesize existing literature on the impact of scheduled naps on fatigue-related outcomes for EMS personnel and similar shift worker groups. METHODS: A systematic literature review was performed of the impact of a scheduled nap during shift work on EMS personnel or similar shift workers. The primary (critical) outcome of interest was EMS personnel safety. Secondary (important) outcomes were patient safety; personnel performance; acute states of fatigue, alertness, and sleepiness; indicators of sleep duration and/or quality; employee retention/turnover; indicators of long-term health; and cost to the system. Meta-analyses were performed to evaluate the impact of napping on a measure of personnel performance (the psychomotor vigilance test [PVT]) and measures of acute fatigue. RESULTS: Of 4,660 unique records identified, 13 experimental studies were determined relevant and summarized. The effect of napping on reaction time measured at the end of shift was small and non-significant (SMD 0.12, 95% CI -0.13 to 0.36; p = 0.34). Napping during work did not change reaction time from the beginning to the end of the shift (SMD -0.01, 95% CI -25.0 to 0.24; p = 0.96). Naps had a moderate, significant effect on sleepiness measured at the end of shift (SMD 0.40, 95% CI 0.09 to 0.72; p = 0.01). The difference in sleepiness from the start to the end of shift was moderate and statistically significant (SMD 0.41, 95% CI 0.09 to 0.72; p = 0.01). CONCLUSIONS: Reviewed literature indicated that scheduled naps at work improved performance and decreased fatigue in shift workers. Further research is required to identify the optimal timing and duration of scheduled naps to maximize the beneficial outcomes.

Shorter Versus Longer Shift Durations to Mitigate Fatigue and Fatigue-Related Risks in Emergency Medical Services Personnel and Related Shift Workers: A Systematic Review.

BACKGROUND: This study comprehensively reviewed the literature on the impact of shorter versus longer shifts on critical and important outcomes for Emergency Medical Services (EMS) personnel and related shift worker groups. METHODS: Six databases (e.g., PubMed/MEDLINE) were searched, including one website. This search was guided by a research question developed by an expert panel a priori and registered with the PROSPERO database of systematic reviews (2016:CRD42016040099). The critical outcomes of interest were patient safety and personnel safety. The important outcomes of interest were personnel performance, acute fatigue, sleep and sleep quality, retention/turnover, long-term health, burnout/stress, and cost to system. Screeners worked independently and full-text articles were assessed for relevance. Data abstracted from the retained literature were categorized as favorable, unfavorable, mixed/inconclusive, or no impact toward the shorter shift duration. This research characterized the evidence as very low, low, moderate, or high quality according to the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) methodology. RESULTS: The searched yielded n = 21,674 records. Of the 480 full-text articles reviewed, 100 reported comparisons of outcomes of interest by shift duration. We identified 24 different shift duration comparisons, most commonly 8 hours versus 12 hours. No one study reported findings for all 9 outcomes. Two studies reported findings linked to both critical outcomes of patient and personnel safety, 34 reported findings for one of two critical outcomes, and 64 did not report findings for critical outcomes. Fifteen studies were grouped to compare shifts <24 hours versus shifts ≥24 hours. None of the findings for the critical outcomes of patient and personnel safety were categorized as unfavorable toward shorter duration shifts (<24 hours). Nine studies were favorable toward shifts <24 hours for at least one of the 7 important outcomes, while findings from one study were categorized as unfavorable. Evidence quality was low or very low. CONCLUSIONS: The quality of existing evidence on the impact of shift duration on fatigue and fatigue-related risks is low or very low. Despite these limitations, this systematic review suggests that for outcomes considered critical or important to EMS personnel, shifts <24 hours in duration are more favorable than shifts ≥24 hours.

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.

Emotional distress, social support, and functional dependence predict readiness for hospital discharge in a prospective sample of cognitively intact cardiac arrest survivors.

AIM: To inform screening, referral and treatment initiatives, we tested the hypothesis that emotional distress, social support, functional dependence, and cognitive impairment within 72 hours prior to discharge predict readiness for discharge in awake and alert cardiac arrest (CA) survivors. METHODS: This was a secondary analysis of a prospective single-center cohort of CA survivors enrolled between 4/2021 and 9/2022. We quantified emotional distress using the Posttraumatic Stress Disorder Checklist-5 and PROMIS Emotional Distress - Anxiety and Depression Short Forms 4a; perceived social support using the ENRICHD Social Support Inventory; functional dependence using the modified Rankin Scale; and cognitive impairment using the Telephone Interview for Cognitive Status. Our primary outcome was readiness for discharge, measured using the Readiness for Hospital Discharge Scale. We used multivariable linear regression to test the independent association of each survivorship factor and readiness for discharge. RESULTS: We included 110 patients (64% male, 88% white, mean age 59 [standard deviation ± 13.1 years]). Emotional distress, functional dependence, and social support were independently associated with readiness for discharge (adjusted ß's [absolute value]: 0.25-0.30, all p < 0.05). CONCLUSIONS: Hospital systems should consider implementing routine in-hospital screening for emotional distress, social support, and functional dependence for CA survivors who are awake, alert and approaching hospital discharge, and prioritize brief in hospital treatment or post-discharge referrals.

Metabolic Manipulation and Therapeutic Hypothermia.

Hypothermia has multiple physiological effects, including decreasing metabolic rate and oxygen consumption (VO2). There are few human data about the magnitude of change in VO2 with decreases in core temperature. We aimed to quantify to magnitude of reduction in resting VO2 as we reduced core temperature in lightly sedated healthy individuals. After informed consent and physical screening, we cooled participants by rapidly infusing 20 mL/kg of cold (4°C) saline intravenously and placing surface cooling pads on the torso. We attempted to suppress shivering using a 1 mcg/kg intravenous bolus of dexmedetomidine followed by titrated infusion at 1.0 to 1.5 µg/(kg·h). We measured resting metabolic rate VO2 through indirect calorimetry at baseline (37°C) and at 36°C, 35°C, 34°C, and 33°C. Nine participants had mean age 30 (standard deviation 10) years and 7 (78%) were male. Baseline VO2 was 3.36 mL/(kg·min) (interquartile range 2.98-3.76) mL/(kg·min). VO2 was associated with core temperature and declined with each degree decrease in core temperature, unless shivering occurred. Over the entire range from 37°C to 33°C, median VO2 declined 0.7 mL/(kg·min) (20.8%) in the absence of shivering. The largest average decrease in VO2 per degree Celsius was by 0.46 mL/(kg·min) (13.7%) and occurred between 37°C and 36°C in the absence of shivering. After a participant developed shivering, core body temperature did not decrease further, and VO2 increased. In lightly sedated humans, metabolic rate decreases around 5.2% for each 1°C decrease in core temperature from 37°C to 33°C. Because the largest decrease in metabolic rate occurs between 37°C and 36°C, subclinical shivering or other homeostatic reflexes may be present at lower temperatures.

A multi-center, randomized, double blinded, placebo-controlled trial of amantadine to stimulate awakening in comatose patients resuscitated from cardiac arrest.

Objectives: 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 100mg twice daily or placebo for up to 7 days. The study drug was administered between 72-120 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 (CPC) at hospital discharge. We compared the proportion of subjects awakening and hospital survival using Fisher's 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), 7 in the amantadine arm and 7 in the placebo arm. The proportion of patients who awakened within 28 days after cardiac arrest did not differ between amantadine (n=2, 28.57%) and placebo groups (n=3, 42.86%) (p = 1.00). There were no differences in secondary outcomes. Study medication was stopped in three (21%) subjects. Adverse events included a recurrence of seizures (n=2; 14%), both of which occurred in the placebo arm. Conclusion: We could not determine the effect of amantadine on awakening in comatose survivors of cardiac arrest due to small sample size.

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.

Protective positive psychology factors and emotional distress after cardiac arrest.

BACKGROUND: There is a critical need to identify factors that can prevent emotional distress post-cardiac arrest (CA). CA survivors have previously described benefitting from utilizing positive psychology constructs (mindfulness, existential well-being, resilient coping, social support) to cope with distress. Here, we explored associations between positive psychology factors and emotional distress post-CA. METHODS: We recruited CA survivors treated from 4/2021-9/2022 at a single academic medical center. We assessed positive psychology factors (mindfulness [Cognitive and Affective Mindfulness Scale-Revised], existential well-being [Meaning in Life Questionnaire Presence of Meaning subscale], resilient coping [Brief Resilient Coping Scale], perceived social support [ENRICHD Social Support Inventory]) and emotional distress (posttraumatic stress [Posttraumatic Stress Checklist-5], anxiety and depression symptoms [PROMIS Emotional Distress - Anxiety and Depression Short Forms 4a]) just before discharge from the index hospitalization. We selected covariates for inclusion in our multivariable models based on an association with any emotional distress factor (p < 0.10). For our final, multivariable regression models, we individually tested the independent association of each positive psychology factor and emotional distress factor. RESULTS: We included 110 survivors (mean age 59 years, 64% male, 88% non-Hispanic White, 48% low income); 36.4% of survivors scored above the cut-off for at least one measure of emotional distress. In separate adjusted models, each positive psychology factor was independently associated with emotional distress (ß: -0.20 to -0.42, all p < 0.05). CONCLUSIONS: Higher levels of mindfulness, existential well-being, resilient coping, and perceived social support were each associated with less emotional distress. Future intervention development studies should consider these factors as potential treatment targets.

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.

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.

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.

Evaluating novel methods of outcome assessment following cardiac arrest.

INTRODUCTION: We compared novel methods of long-term follow-up after resuscitation from cardiac arrest to a query of the National Death Index (NDI). We hypothesized use of the electronic health record (EHR), and internet-based sources would have high sensitivity for identifying decedents identified by the NDI. METHODS: We performed a retrospective study including patients treated after cardiac arrest at a single academic center from 2010 to 2018. We evaluated two novel methods to ascertain long-term survival and modified Rankin Scale (mRS): 1) a structured chart review of our health system's EHR; and 2) an internet-based search of: a) local newspapers, b) Ancestry.com, c) Facebook, d) Twitter, e) Instagram, and f) Google. If a patient was not reported deceased by any source, we considered them to be alive. We compared results of these novel methods to the NDI to calculate sensitivity. We queried the NDI for 200 in-hospital decedents to evaluate sensitivity against a true criterion standard. RESULTS: We included 1,097 patients, 897 (82%) alive at discharge and 200 known decedents (18%). NDI identified 197/200 (99%) of known decedents. The EHR and local newspapers had highest sensitivity compared to the NDI (87% and 86% sensitivity, respectively). Online sources identified 10 likely decedents not identified by the NDI. Functional status estimated from EHR, and internet sources at follow up agreed in 38% of alive patients. CONCLUSIONS: Novel methods of outcome assessment are an alternative to NDI for determining patients' vital status. These methods are less reliable for estimating functional status.

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.

Glycopyrrolate does not ameliorate hypothermia associated bradycardia in healthy individuals: A randomized crossover trial.

BACKGROUND: Hypothermia improves outcomes following ischemia-reperfusion injury. Shivering is common and can be mediated by agents such as dexmedetomidine. The combination of dexmedetomidine and hypothermia results in bradycardia. We hypothesized that glycopyrrolate would prevent bradycardia during dexmedetomidine-mediated hypothermia. METHODS: We randomly assigned eight healthy subjects to premedication with a single 0.4 mg glycopyrrolate intravenous (IV) bolus, titrated glycopyrrolate (0.01 mg IV every 3 min as needed for heart rate <50), or no glycopyrrolate during three separate sessions of 3 h cooling. Following 1 mg/kg IV dexmedetomidine bolus, subjects received 20 ml/kg IV 4 °C saline and surface cooling (EM COOLS, Weinerdorf, Austria). We titrated dexmedetomidine infusion to suppress shivering but permit arousal to verbal stimuli. After 3 h of cooling, we allowed subjects to passively rewarm. We compared heart rate, core temperature, mean arterial blood pressure, perceived comfort and thermal sensation between groups using Kruskal-Wallis test and ANOVA. RESULTS: Mean age was 27 (SD 6) years and most (N = 6, 75%) were male. Neither heart rate nor core temperature differed between the groups during maintenance of hypothermia (p > 0.05). Mean arterial blood pressure was higher in the glycopyrrolate bolus condition (p < 0.048). Thermal sensation was higher in the control condition than the glycopyrrolate bolus condition (p = 0.01). Bolus glycopyrrolate resulted in less discomfort than titrated glycopyrrolate (p = 0.04). CONCLUSIONS: Glycopyrrolate did not prevent the bradycardic response to hypothermia and dexmedetomidine. Mean arterial blood pressure was higher in subjects receiving a bolus of glycopyrrolate before induction of hypothermia. Bolus glycopyrrolate was associated with less intense thermal sensation and less discomfort during cooling.

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 ±â€¯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.

Cardiac arrest survivors lost to follow-up after 3-Months, 6-Months and 1-Year.

BACKGROUND: Long-term assessment of global functional outcomes in cardiac arrest (CA) survivors allows for evaluation of acute care practices and referral to rehabilitation services. Given that many post-CA patients are lost to follow-up (LTFU), we explored whether these patients are systematically different from those who complete follow-up based on demographic, resuscitation and outcome characteristics. METHODS: We conducted a prospective cohort study of 168 English-speaking CA survivors between 9/25/2016 and 5/31/2018. We measured demographic data and global functional outcomes using Modified Rankin Scale (mRS), and Cerebral Performance Category (CPC) in-person at hospital discharge, and via telephone at 3-, 6-months, and 1-year. We compared patients LTFU (e.g., failure to contact or refused to follow-up) with those contacted. Patients who were hospitalized, in a rehabilitation facility, missed by the research team, or dead were considered not eligible for follow-up. RESULTS: Of the 116 patients eligible for follow-up at 3-months, the majority completed follow-up (n = 69; 59.5%) and 47 (40.5%) were LTFU. Conversely, at 6-months and 1-year, fewer subjects were assessed (42% and 47%) compared to those who were LTFU (58% and 53%), respectively. At 3-months, LTFU patients were younger, unmarried, and had longer ICU stay. At 6-months and 1-year, LTFU patients were primarily male, had a non-shockable primary rhythm, and non-cardiac arrest etiologies. CONCLUSIONS: Over one-third of patients are LTFU during the first year after CA, and differences emerged for demographics and characteristics of the event. Future research should account for the informative, non-random distribution of patients LTFU.