Improving Outcomes After Post-Cardiac Arrest Brain Injury: A Scientific Statement From the International Liaison Committee on Resuscitation.

This scientific statement presents a conceptual framework for the pathophysiology of post-cardiac arrest brain injury, explores reasons for previous failure to translate preclinical data to clinical practice, and outlines potential paths forward. Post-cardiac arrest brain injury is characterized by 4 distinct but overlapping phases: ischemic depolarization, reperfusion repolarization, dysregulation, and recovery and repair. Previous research has been challenging because of the limitations of laboratory models; heterogeneity in the patient populations enrolled; overoptimistic estimation of treatment effects leading to suboptimal sample sizes; timing and route of intervention delivery; limited or absent evidence that the intervention has engaged the mechanistic target; and heterogeneity in postresuscitation care, prognostication, and withdrawal of life-sustaining treatments. Future trials must tailor their interventions to the subset of patients most likely to benefit and deliver this intervention at the appropriate time, through the appropriate route, and at the appropriate dose. The complexity of post-cardiac arrest brain injury suggests that monotherapies are unlikely to be as successful as multimodal neuroprotective therapies. Biomarkers should be developed to identify patients with the targeted mechanism of injury, to quantify its severity, and to measure the response to therapy. Studies need to be adequately powered to detect effect sizes that are realistic and meaningful to patients, their families, and clinicians. Study designs should be optimized to accelerate the evaluation of the most promising interventions. Multidisciplinary and international collaboration will be essential to realize the goal of developing effective therapies for post-cardiac arrest brain injury.

Critical Care Management of Patients After Cardiac Arrest: A Scientific Statement From the American Heart Association and Neurocritical Care Society.

The critical care management of patients after cardiac arrest is burdened by a lack of high-quality clinical studies and the resultant lack of high-certainty evidence. This results in limited practice guideline recommendations, which may lead to uncertainty and variability in management. Critical care management is crucial in patients after cardiac arrest and affects outcome. Although guidelines address some relevant topics (including temperature control and neurological prognostication of comatose survivors, 2 topics for which there are more robust clinical studies), many important subject areas have limited or nonexistent clinical studies, leading to the absence of guidelines or low-certainty evidence. The American Heart Association Emergency Cardiovascular Care Committee and the Neurocritical Care Society collaborated to address this gap by organizing an expert consensus panel and conference. Twenty-four experienced practitioners (including physicians, nurses, pharmacists, and a respiratory therapist) from multiple medical specialties, levels, institutions, and countries made up the panel. Topics were identified and prioritized by the panel and arranged by organ system to facilitate discussion, debate, and consensus building. Statements related to postarrest management were generated, and 80% agreement was required to approve a statement. Voting was anonymous and web based. Topics addressed include neurological, cardiac, pulmonary, hematological, infectious, gastrointestinal, endocrine, and general critical care management. Areas of uncertainty, areas for which no consensus was reached, and future research directions are also included. Until high-quality studies that inform practice guidelines in these areas are available, the expert panel consensus statements that are provided can advise clinicians on the critical care management of patients after cardiac arrest.

Bag-Valve-Mask Ventilation and Survival From Out-of-Hospital Cardiac Arrest: A Multicenter Study.

BACKGROUND: Few studies have measured ventilation during early cardiopulmonary resuscitation (CPR) before advanced airway placement. Resuscitation guidelines recommend pauses after every 30 chest compressions to deliver ventilations. The effectiveness of bag-valve-mask ventilation delivered during the pause in chest compressions is unknown. We sought to determine: (1) the incidence of lung inflation with bag-valve-mask ventilation during 30:2 CPR; and (2) the association of ventilation with outcomes after out-of-hospital cardiac arrest. METHODS: We studied patients with out-of-hospital cardiac arrest from 6 sites of the Resuscitation Outcomes Consortium CCC study (Trial of Continuous Compressions versus Standard CPR in Patients with Out-of-Hospital Cardiac Arrest). We analyzed patients assigned to the 30:2 CPR arm with ≥2 minutes of thoracic bioimpedance signal recorded with a cardiac defibrillator/monitor. Detectable ventilation waveforms were defined as having a bioimpedance amplitude ≥0.5 Ω (corresponding to ≥250 mL VT) and a duration ≥1 s. We defined a chest compression pause as a 3- to 15-s break in chest compressions. We compared the incidence of ventilation and outcomes in 2 groups: patients with ventilation waveforms in <50% of pauses (group 1) versus those with waveforms in ≥50% of pauses (group 2). RESULTS: Among 1976 patients, the mean age was 65 years; 66% were male. From the start of chest compressions until advanced airway placement, mean±SD duration of 30:2 CPR was 9.8±4.9 minutes. During this period, we identified 26 861 pauses in chest compressions; 60% of patients had ventilation waveforms in <50% of pauses (group 1, n=1177), and 40% had waveforms in ≥50% of pauses (group 2, n=799). Group 1 had a median of 12 pauses and 2 ventilations per patient versus group 2, which had 12 pauses and 12 ventilations per patient. Group 2 had higher rates of prehospital return of spontaneous circulation (40.7% versus 25.2%; P<0.0001), survival to hospital discharge (13.5% versus 4.1%; P<0.0001), and survival with favorable neurological outcome (10.6% versus 2.4%; P<0.0001). These associations persisted after adjustment for confounders. CONCLUSIONS: In this study, lung inflation occurred infrequently with bag-valve-mask ventilation during 30:2 CPR. Lung inflation in ≥50% of pauses was associated with improved return of spontaneous circulation, survival, and survival with favorable neurological outcome.

Early Convalescent Plasma for High-Risk Outpatients with Covid-19.

BACKGROUND: Early administration of convalescent plasma obtained from blood donors who have recovered from coronavirus disease 2019 (Covid-19) may prevent disease progression in acutely ill, high-risk patients with Covid-19. METHODS: In this randomized, multicenter, single-blind trial, we assigned patients who were being treated in an emergency department for Covid-19 symptoms to receive either one unit of convalescent plasma with a high titer of antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or placebo. All the patients were either 50 years of age or older or had one or more risk factors for disease progression. In addition, all the patients presented to the emergency department within 7 days after symptom onset and were in stable condition for outpatient management. The primary outcome was disease progression within 15 days after randomization, which was a composite of hospital admission for any reason, seeking emergency or urgent care, or death without hospitalization. Secondary outcomes included the worst severity of illness on an 8-category ordinal scale, hospital-free days within 30 days after randomization, and death from any cause. RESULTS: A total of 511 patients were enrolled in the trial (257 in the convalescent-plasma group and 254 in the placebo group). The median age of the patients was 54 years; the median symptom duration was 4 days. In the donor plasma samples, the median titer of SARS-CoV-2 neutralizing antibodies was 1:641. Disease progression occurred in 77 patients (30.0%) in the convalescent-plasma group and in 81 patients (31.9%) in the placebo group (risk difference, 1.9 percentage points; 95% credible interval, -6.0 to 9.8; posterior probability of superiority of convalescent plasma, 0.68). Five patients in the plasma group and 1 patient in the placebo group died. Outcomes regarding worst illness severity and hospital-free days were similar in the two groups. CONCLUSIONS: The administration of Covid-19 convalescent plasma to high-risk outpatients within 1 week after the onset of symptoms of Covid-19 did not prevent disease progression. (SIREN-C3PO ClinicalTrials.gov number, NCT04355767.).

Hypothermia versus Normothermia after Out-of-Hospital Cardiac Arrest.

BACKGROUND: Targeted temperature management is recommended for patients after cardiac arrest, but the supporting evidence is of low certainty. METHODS: In an open-label trial with blinded assessment of outcomes, we randomly assigned 1900 adults with coma who had had an out-of-hospital cardiac arrest of presumed cardiac or unknown cause to undergo targeted hypothermia at 33°C, followed by controlled rewarming, or targeted normothermia with early treatment of fever (body temperature, ≥37.8°C). The primary outcome was death from any cause at 6 months. Secondary outcomes included functional outcome at 6 months as assessed with the modified Rankin scale. Prespecified subgroups were defined according to sex, age, initial cardiac rhythm, time to return of spontaneous circulation, and presence or absence of shock on admission. Prespecified adverse events were pneumonia, sepsis, bleeding, arrhythmia resulting in hemodynamic compromise, and skin complications related to the temperature management device. RESULTS: A total of 1850 patients were evaluated for the primary outcome. At 6 months, 465 of 925 patients (50%) in the hypothermia group had died, as compared with 446 of 925 (48%) in the normothermia group (relative risk with hypothermia, 1.04; 95% confidence interval [CI], 0.94 to 1.14; P = 0.37). Of the 1747 patients in whom the functional outcome was assessed, 488 of 881 (55%) in the hypothermia group had moderately severe disability or worse (modified Rankin scale score ≥4), as compared with 479 of 866 (55%) in the normothermia group (relative risk with hypothermia, 1.00; 95% CI, 0.92 to 1.09). Outcomes were consistent in the prespecified subgroups. Arrhythmia resulting in hemodynamic compromise was more common in the hypothermia group than in the normothermia group (24% vs. 17%, P<0.001). The incidence of other adverse events did not differ significantly between the two groups. CONCLUSIONS: In patients with coma after out-of-hospital cardiac arrest, targeted hypothermia did not lead to a lower incidence of death by 6 months than targeted normothermia. (Funded by the Swedish Research Council and others; TTM2 ClinicalTrials.gov number, NCT02908308.).

Cardiac Arrest and Neurologic Recovery: Insights from the Case of Mr. Damar Hamlin.

The association between brain injury after cardiac arrest and poor survival outcomes has led to longstanding pessimism. However, the publicly witnessed cardiac arrest, resuscitation, and acute management of Mr. Damar Hamlin and his favorable neurologic recovery provides some optimism. Mr. Hamlin's case highlights the neurologic advances of the last 2 decades and presents the opportunity to improve outcomes for all cardiac arrest patients in key areas: (1) effectively implementing the American Heart Association "Chain of Survival" to prevent initial brain injury and promote neuroprotection; (2) revisiting the process of neurologic prognostication and re-defining the brain recovery during the early periods, and (3) incorporating neurorehabilitation into existing cardiac rehabilitation models to support holistic recovery. ANN NEUROL 2023;93:871-876.

Prehospital Electroencephalography to Detect Traumatic Brain Injury during Helicopter Transport: A Pilot Observational Cohort Study.

OBJECTIVE: Early recognition of traumatic brain injury (TBI) is important to facilitate time-sensitive care. Electroencephalography (EEG) can identify TBI, but feasibility of EEG has not been evaluated in prehospital settings. We tested the feasibility of obtaining single-channel EEG during air medical transport after trauma. We measured association between quantitative EEG features, early blood biomarkers, and abnormalities on head computerized tomography (CT). METHODS: We performed a pilot prospective, observational study enrolling consecutive patients transported by critical care air ambulance from the scene of trauma to a Level I trauma center. During transport, prehospital clinicians placed a sensor on the patient's forehead to record EEG. We reviewed EEG waveforms and selected 90 seconds of recording for quantitative analysis. EEG data processing included fast Fourier transform to summarize component frequency power in the delta (0-4 Hz), theta (4-8 Hz), and alpha (8-13 Hz) ranges. We collected blood samples on day 1 and day 3 post-injury and measured plasma levels of two brain injury biomarkers (ubiquitin C-terminal hydrolase L1 [UCH-L1] and glial fibrillary acidic protein [GFAP]). We compared predictors between individuals with and without CT-positive TBI findings. RESULTS: Forty subjects were enrolled, with EEG recordings successfully obtained in 34 (85%). Reasons for failure included uncharged battery (n = 5) and user error (n = 1). Data were lost in three cases. Of 31 subjects with data, interpretable EEG signal was recorded in 26 (84%). Mean age was 48 (SD 16) years, 79% were male, and 50% suffered motor vehicle crashes. Eight subjects (24%) had CT-positive TBI. Subjects with and without CT-positive TBI had similar median delta power, alpha power, and theta power. UCH-L1 and GFAP plasma levels did not differ across groups. Delta power inversely correlated with UCH-L1 day 1 plasma concentration (r = -0.60, p = 0.03). CONCLUSIONS: Prehospital EEG acquisition is feasible during air transport after trauma.

External evaluation of Brain Injury Guideline (BIG) low risk criteria for traumatic brain injury.

BACKGROUND: Fewer than 20 % of traumatic brain injury (TBI) cases with traumatic intracranial hemorrhage (ICH) result in clinical deterioration. The Brain Injury Guideline (BIG) criteria were published in 2014 and categorize patients with TBI into three risk groups (BIG 1, 2, and 3) based on CT scan findings, neurological examination, anti-coagulant/platelet medications, and intoxication. Early data is promising, suggesting no instances of neurosurgical intervention or death in the low-risk BIG1 category within 30 days. We sought to externally validate the BIG criteria and identify patients with TBI at low risk of clinical deterioration. We hypothesized that patients meeting the BIG1 low risk criteria have less than a 1 % risk of death or neurosurgical intervention. METHODS: We performed a retrospective cohort study of a level 1 trauma center's trauma registry records from 2011 to 2022 to identify patients with head trauma. We abstracted demographics, injury characteristics, clinical course, CT imaging results, and outcomes, and we categorized patients according to the BIG criteria. The Clopper-Pearson Exact method was used to estimate outcome frequency with confidence intervals. The primary outcome was death or neurosurgical intervention within 30 days. Secondary outcomes included progression on repeat head CT (RHCT), ICU admission with neurocritical care intervention, and TBI-related hospital readmission within 30 days. RESULTS: A total of 1714 patients with TBI with ICH were identified from the trauma registry. 325 patients were excluded due to missing data, pregnancy, incarceration, polytrauma, or GCS < 13, leaving 1389 for analysis. 193 patients (13.9 %) were classified as BIG1. No patients classified as BIG1 experienced the primary outcome measures of death or neurosurgical intervention (95 % confidence interval [CI]: 0 %-1.9 %). The number of patients who experienced the secondary outcome measures of progression on RHCT, ICU admission with neurocritical care intervention, or TBI-related hospital readmission within 30 days were 9 (4.7 %, 95 % CI: 2.2 %-8.7 %), 1 (0.5 %, 95 % CI: 0 %-2.9 %), and 4 (2.1 %, 95 % CI: 0.6 %-5.2 %), respectively. CONCLUSION: BIG1 criteria identified a low-risk subset of patients with TBI with ICH. However, an upper 95 % CI of 1.9 % does not exclude the risk of neurologic deterioration being <1 %. Validation of these criteria in larger cohorts is warranted.

Clinical usability of deep learning-based saliency maps for occlusion myocardial infarction identification from the prehospital 12-Lead electrocardiogram.

INTRODUCTION: Deep learning (DL) models offer improved performance in electrocardiogram (ECG)-based classification over rule-based methods. However, for widespread adoption by clinicians, explainability methods, like saliency maps, are essential. METHODS: On a subset of 100 ECGs from patients with chest pain, we generated saliency maps using a previously validated convolutional neural network for occlusion myocardial infarction (OMI) classification. Three clinicians reviewed ECG-saliency map dyads, first assessing the likelihood of OMI from standard ECGs and then evaluating clinical relevance and helpfulness of the saliency maps, as well as their confidence in the model's predictions. Questions were answered on a Likert scale ranging from +3 (most useful/relevant) to -3 (least useful/relevant). RESULTS: The adjudicated accuracy of the three clinicians matched the DL model when considering area under the receiver operating characteristics curve (AUC) and F1 score (AUC 0.855 vs. 0.872, F1 score = 0.789 vs. 0.747). On average, clinicians found saliency maps slightly clinically relevant (0.96 ± 0.92) and slightly helpful (0.66 ± 0.98) in identifying or ruling out OMI but had higher confidence in the model's predictions (1.71 ± 0.56). Clinicians noted that leads I and aVL were often emphasized, even when obvious ST changes were present in other leads. CONCLUSION: In this clinical usability study, clinicians deemed saliency maps somewhat helpful in enhancing explainability of DL-based ECG models. The spatial convolutional layers across the 12 leads in these models appear to contribute to the discrepancy between ECG segments considered most relevant by clinicians and segments that drove DL model predictions.

Critical Care Management of Patients After Cardiac Arrest: A Scientific Statement from the American Heart Association and Neurocritical Care Society.

The critical care management of patients after cardiac arrest is burdened by a lack of high-quality clinical studies and the resultant lack of high-certainty evidence. This results in limited practice guideline recommendations, which may lead to uncertainty and variability in management. Critical care management is crucial in patients after cardiac arrest and affects outcome. Although guidelines address some relevant topics (including temperature control and neurological prognostication of comatose survivors, 2 topics for which there are more robust clinical studies), many important subject areas have limited or nonexistent clinical studies, leading to the absence of guidelines or low-certainty evidence. The American Heart Association Emergency Cardiovascular Care Committee and the Neurocritical Care Society collaborated to address this gap by organizing an expert consensus panel and conference. Twenty-four experienced practitioners (including physicians, nurses, pharmacists, and a respiratory therapist) from multiple medical specialties, levels, institutions, and countries made up the panel. Topics were identified and prioritized by the panel and arranged by organ system to facilitate discussion, debate, and consensus building. Statements related to postarrest management were generated, and 80% agreement was required to approve a statement. Voting was anonymous and web based. Topics addressed include neurological, cardiac, pulmonary, hematological, infectious, gastrointestinal, endocrine, and general critical care management. Areas of uncertainty, areas for which no consensus was reached, and future research directions are also included. Until high-quality studies that inform practice guidelines in these areas are available, the expert panel consensus statements that are provided can advise clinicians on the critical care management of patients after cardiac arrest.

2022 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations: Summary From the Basic Life Support; Advanced Life Support; Pediatric Life Support; Neonatal Life Support; Education, Implementation, and Teams; and First Aid Task Forces.

This is the sixth annual summary of the International Liaison Committee on Resuscitation International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations. This summary addresses the most recently published resuscitation evidence reviewed by International Liaison Committee on Resuscitation Task Force science experts. Topics covered by systematic reviews include cardiopulmonary resuscitation during transport; approach to resuscitation after drowning; passive ventilation; minimizing pauses during cardiopulmonary resuscitation; temperature management after cardiac arrest; use of diagnostic point-of-care ultrasound during cardiac arrest; use of vasopressin and corticosteroids during cardiac arrest; coronary angiography after cardiac arrest; public-access defibrillation devices for children; pediatric early warning systems; maintaining normal temperature immediately after birth; suctioning of amniotic fluid at birth; tactile stimulation for resuscitation immediately after birth; use of continuous positive airway pressure for respiratory distress at term birth; respiratory and heart rate monitoring in the delivery room; supraglottic airway use in neonates; prearrest prediction of in-hospital cardiac arrest mortality; basic life support training for likely rescuers of high-risk populations; effect of resuscitation team training; blended learning for life support training; training and recertification for resuscitation instructors; and recovery position for maintenance of breathing and prevention of cardiac arrest. Members from 6 task forces have assessed, discussed, and debated the quality of the evidence using Grading of Recommendations Assessment, Development, and Evaluation criteria and generated consensus treatment recommendations. Insights into the deliberations of the task forces are provided in the Justification and Evidence-to-Decision Framework Highlights sections, and priority knowledge gaps for future research are listed.

Coronavirus Disease 2019 Convalescent Plasma Outpatient Therapy to Prevent Outpatient Hospitalization: A Meta-Analysis of Individual Participant Data From 5 Randomized Trials.

BACKGROUND: Outpatient monoclonal antibodies are no longer effective and antiviral treatments for coronavirus disease 2019 (COVID-19) disease remain largely unavailable in many countries worldwide. Although treatment with COVID-19 convalescent plasma (CCP) is promising, clinical trials among outpatients have shown mixed results. METHODS: We conducted an individual participant data meta-analysis from outpatient trials to assess the overall risk reduction for all-cause hospitalizations by day 28 in transfused participants. Relevant trials were identified by searching Medline, Embase, medRxiv, World Health Organization COVID-19 Research Database, Cochrane Library, and Web of Science from January 2020 to September 2022. RESULTS: Five included studies from 4 countries enrolled and transfused 2620 adult patients. Comorbidities were present in 1795 (69%). The virus neutralizing antibody dilutional titer levels ranged from 8 to 14 580 in diverse assays. One hundred sixty of 1315 (12.2%) control patients were hospitalized, versus 111 of 1305 (8.5%) CCP-treated patients, yielding a 3.7% (95% confidence interval [CI], 1.3%-6.0%; P = .001) absolute risk reduction and 30.1% relative risk reduction for all-cause hospitalization. The hospitalization reduction was greatest in those with both early transfusion and high titer with a 7.6% absolute risk reduction (95% CI, 4.0%-11.1%; P = .0001) accompanied by at 51.4% relative risk reduction. No significant reduction in hospitalization was seen with treatment >5 days after symptom onset or in those receiving CCP with antibody titers below the median titer. CONCLUSIONS: Among outpatients with COVID-19, treatment with CCP reduced the rate of all-cause hospitalization and may be most effective when given within 5 days of symptom onset and when antibody titer is higher.

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.

Incorporation of Serial 12-Lead Electrocardiogram With Machine Learning to Augment the Out-of-Hospital Diagnosis of Non-ST Elevation Acute Coronary Syndrome.

STUDY OBJECTIVE: Ischemic electrocardiogram (ECG) changes are subtle and transient in patients with suspected non-ST-segment elevation (NSTE)-acute coronary syndrome. However, the out-of-hospital ECG is not routinely used during subsequent evaluation at the emergency department. Therefore, we sought to compare the diagnostic performance of out-of-hospital and ED ECG and evaluate the incremental gain of artificial intelligence-augmented ECG analysis. METHODS: This prospective observational cohort study recruited patients with out-of-hospital chest pain. We retrieved out-of-hospital-ECG obtained by paramedics in the field and the first ED ECG obtained by nurses during inhospital evaluation. Two independent and blinded reviewers interpreted ECG dyads in mixed order per practice recommendations. Using 179 morphological ECG features, we trained, cross-validated, and tested a random forest classifier to augment non ST-elevation acute coronary syndrome (NSTE-ACS) diagnosis. RESULTS: Our sample included 2,122 patients (age 59 [16]; 53% women; 44% Black, 13.5% confirmed acute coronary syndrome). The rate of diagnostic ST elevation and ST depression were 5.9% and 16.2% on out-of-hospital-ECG and 6.1% and 12.4% on ED ECG, with ∼40% of changes seen on out-of-hospital-ECG persisting and ∼60% resolving. Using expert interpretation of out-of-hospital-ECG alone gave poor baseline performance with area under the receiver operating characteristic (AUC), sensitivity, and negative predictive values of 0.69, 0.50, and 0.92. Using expert interpretation of serial ECG changes enhanced this performance (AUC 0.80, sensitivity 0.61, and specificity 0.93). Interestingly, augmenting the out-of-hospital-ECG alone with artificial intelligence algorithms boosted its performance (AUC 0.83, sensitivity 0.75, and specificity 0.95), yielding a net reclassification improvement of 29.5% against expert ECG interpretation. CONCLUSION: In this study, 60% of diagnostic ST changes resolved prior to hospital arrival, making the ED ECG suboptimal for the inhospital evaluation of NSTE-ACS. Using serial ECG changes or incorporating artificial intelligence-augmented analyses would allow correctly reclassifying one in 4 patients with suspected NSTE-ACS.

Impact of Preexisting Depression and Anxiety on Hospital Readmission and Long-Term Survival After Cardiac Arrest.

BACKGROUND: While sudden cardiac arrest (CA) survivors are at risk for developing psychiatric disorders, little is known about the impact of preexisting mental health conditions on long-term survival or postacute healthcare utilization. We examined the prevalence of preexisting psychiatric conditions in CA patients who survived hospital discharge, characterized incidence and reason for inpatient psychiatry consultation during these patients' acute hospitalizations, and determined the association of pre-CA depression and anxiety with hospital readmission rates and long-term survival. We hypothesized that prior depression or anxiety would be associated with higher hospital readmission rates and lower long-term survival. METHODS: We conducted a retrospective cohort study including patients resuscitated from in- and out-of-hospital CA who survived both admission and discharge from a single hospital between January 1, 2010, and December 31, 2017. We identified patients from our prospective registry, then performed a structured chart review to abstract past psychiatric history, prescription medications for psychiatric conditions, and identify inpatient psychiatric consultations. We used administrative data to identify readmissions within 1 year and vital status through December 31, 2020. We used multivariable Cox regressions controlling for patient demographics, medical comorbidities, discharge Cerebral Performance Category and disposition, depression, and anxiety history to predict long-term survival and hospital readmission. RESULTS: We included 684 subjects. Past depression or anxiety was noted in 24% (n = 162) and 19% (n = 129) of subjects. A minority of subjects (n = 139, 20%) received a psychiatry consultation during the index hospitalization. Overall, 262 (39%) subjects had at least 1 readmission within 1 year. Past depression was associated with an increased hazard of hospital readmission (hazard ratio 1.50, 95% CI 1.11-2.04), while past anxiety was not associated with readmission. Neither depression nor anxiety were independently associated with long-term survival. CONCLUSIONS: Depression is an independent risk factor for hospital readmission in CA survivors.

Home oxygen therapy from the emergency department for COVID-19 an observational study.

STUDY OBJECTIVE: During the COVID-19 pandemic, prescribing supplemental oxygen was a common reason for hospitalization of patients. We evaluated outcomes of COVID-19 patients discharged from the Emergency Department (ED) with home oxygen as part of a program to decrease hospital admissions. METHODS: We retrospectively observed COVID-19 patients with an ED visit resulting in direct discharge or observation from April 2020 to January 2022 at 14 hospitals in a single healthcare system. The cohort included those discharged with new oxygen supplementation, a pulse oximeter, and return instructions. Our primary outcome was subsequent hospitalization or death outside the hospital within 30 days of ED or observation discharge. RESULTS: Among 28,960 patients visiting the ED for COVID-19, providers admitted 11,508 (39.7%) to the hospital, placed 907 (3.1%) in observation status, and discharged 16,545 (57.1%) to home. A total of 614 COVID-19 patients (535 discharge to home and 97 observation unit) went home on new oxygen therapy. We observed the primary outcome in 151 (24.6%, CI 21.3-28.1%) patients. There were 148 (24.1%) patients subsequently hospitalized and 3 (0.5%) patients who died outside the hospital. The subsequent hospitalized mortality rate was 29.7% with 44 of the 148 patients admitted to the hospital dying. Mortality all cause at 30 days in the entire cohort was 7.7%. CONCLUSIONS: Most patients discharged to home with new oxygen for COVID-19 safely avoid later hospitalization and few patients die within 30 days. This suggests the feasibility of the approach and offers support for ongoing research and implementation efforts.

Association of substance use with outcomes in mildly ill COVID-19 outpatients.

BACKGROUND: Smoking, alcohol use, and non-prescription drug use are associated with worsened COVID-19 outcomes in hospitalized patients. Whether there is an association between substance use and outcomes in patients with COVID-19 who visited the Emergency Department (ED) but did not require hospitalization has not been well established. We investigated whether smoking, alcohol, and non-prescription drug use were associated with worsened COVID-19 outcomes among such patients presenting to the ED. METHODS: We conducted a secondary analysis of a clinical trial which sought to determine the effect of early convalescent plasma administration in patients presenting to the ED within 7 days of onset of mild COVID-19 symptoms. The study recruited 511 participants who were aged 50 years or older or had one or more risk factors for severe COVID-19. The primary outcome was disease progression within 15 days after randomization, which was defined as a composite of hospital admission for any reason, seeking emergency or urgent care, or death without hospitalization. Secondary outcomes included: no hospitalization within 30 days post-randomization, symptom worsening on the 5-category COVID-19 outpatient ordinal scale within 15 days post-randomization, and all-cause mortality. Substance use was categorized into either use or never use based on participant self-report. Logistic regression models were used to determine the association between substance use and outcomes. RESULTS: The mean age of the 511 patients enrolled was 52 years and the majority were females (274, 54%). Approximately 213 (42%) were non-Hispanic Whites, 156 (30%) Hispanics, 100 (20%) non-Hispanic Blacks, 18 (4%) non-Hispanic Asian, 8 (1%) American Indian Alaskan, and 16 (3%) unknown race. Tobacco 152 (30%) was the most common substance use reported. Alcohol use 36 (7%) and non-prescription drug use 33 (6%) were less common. Tobacco use and non-prescription drug use were associated with an increased risk for meeting the primary outcome ((tobacco: adjusted odds ratio [aOR] =2.08; 95% confidence interval [CI]: 1.37-3.15) and (drug: aOR =2.41; 95%CI: 1.17-5.00)) and increased risk for symptom worsening on the 5-category COVID-19 outpatient scale ((tobacco: aOR = 1.62; 95%CI: 1.09-2.42) and (drug: aOR = 2.32 95% CI: 1.10-4.87)) compared to non-use after adjusting for age, sex, plasma administration, and comorbidity. CONCLUSION: Tobacco and non-prescription drug use but not alcohol use were associated with worsened COVID-19 outcomes in patients who did not require hospitalization on their initial presentation. Future studies should determine the quantity, duration, and type of drug/tobacco use that may worsen COVID-19.

Increased Fellow Scholarly Publication Rate After Implementation of a Comprehensive Research Curriculum and Milestone-Based Research Timeline for Pediatric Emergency Medicine Fellows.

OBJECTIVE: Pediatric subspecialty fellows are required to complete a scholarly product during training; however, many do not bring the work to publication. To amplify our fellows' publication success, our pediatric emergency medicine fellowship program implemented a comprehensive research curriculum and established a milestone-based research timeline for each component of a project. Our objective was to assess whether these interventions increased the publication rate and enhanced the graduated fellows' perceived ability to perform independent research. METHODS: Our study was conducted at a tertiary children's hospital affiliated with an academic university, enrolling 3 fellows each year in its pediatric emergency medicine program. A comprehensive research curriculum and a milestone-based research timeline were implemented in 2011. We analyzed the publication rate of our graduating fellows before (2004-2011) and after (2012-2016) our intervention. In addition, in 2017 we surveyed our previous fellows who graduated from 2004 to 2016 and analyzed factors favoring manuscript publication and confidence with various research skills. RESULTS: During the study period, 38 trainees completed the fellowship program. Publication rate increased from 26% ± 17% to 87% ± 30 % ( P < 0.05). When scoring the importance of various factors, fellows most valued mentorship (5 ± 0 vs 4.3 ± 1.0, P < 0.05, postintervention vs preintervention) for the completion of the fellowship study and manuscript. Fellows after the intervention reported greater confidence in performing an analysis of variance (89% vs 36%, odds ratio, 6.3; 95% confidence interval, 1.4-150.1). CONCLUSIONS: Implementation of a comprehensive research curriculum and a milestone-based research timeline was associated with an increase in the publication rate within 3 years of graduation of our pediatric emergency medicine fellows. After implementation, fellows reported an increased importance of mentorship and greater confidence in performing an analysis of variance. We provide a comprehensive curriculum and a research timeline that may serve as a model for other fellowship programs.

Heart Disease and Stroke Statistics-2021 Update: A Report From the American Heart Association.

BACKGROUND: The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS: The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2021 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors related to cardiovascular disease. RESULTS: Each of the 27 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS: The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Brain injury after cardiac arrest.

As more people are surviving cardiac arrest, focus needs to shift towards improving neurological outcomes and quality of life in survivors. Brain injury after resuscitation, a common sequela following cardiac arrest, ranges in severity from mild impairment to devastating brain injury and brainstem death. Effective strategies to minimise brain injury after resuscitation include early intervention with cardiopulmonary resuscitation and defibrillation, restoration of normal physiology, and targeted temperature management. It is important to identify people who might have a poor outcome, to enable informed choices about continuation or withdrawal of life-sustaining treatments. Multimodal prediction guidelines seek to avoid premature withdrawal in those who might survive with a good neurological outcome, or prolonging treatment that might result in survival with severe disability. Approximately one in three admitted to intensive care will survive, many of whom will need intensive, tailored rehabilitation after discharge to have the best outcomes.