The Outcomes of the Initial Misclassification of Undifferentiated Hypotension in the Emergency Department: A Prospective Observational Study.

Background: Managing shock, a life-threatening emergency, is challenging. The influence of the initial misclassification of undifferentiated hypotension (UH) in the emergency department (ED) on patients' outcomes remains uninvestigated. The aim of this study was to investigate whether the initial misclassification of UH in the ED affects patients' clinical outcomes. Materials and Methods: This prospective observational study enrolled 270 non-traumatic adult patients with UH who had visited the ED of National Taiwan University Hospital between July 2020 and January 2022. The patients were divided into same-diagnosis and different-diagnosis groups, depending on the consistency between the initial and final classifications of shock. The outcome was survival to discharge. The clinical variables, management, and outcomes were compared between the groups. Results: A total of 39 of 270 patients (14.4%) were in the different-diagnosis group. Most misclassified patients were initially diagnosed as having hypovolemic shock (HS, n = 29) but finally diagnosed as having distributive shock (DS, n = 28) or cardiogenic shock (n = 1). When compared with the same-diagnosis group, the different-diagnosis group had higher hospitalization (94.9% vs. 81.4%, p = 0.023) but lower ED discharge (5.1% vs. 16.5%, p = 0.046) rates. Logistic regression analysis showed that the HS initially diagnosed was associated with an increased risk of misclassification (odds ratio [OR] = 14.731, 95% confidence interval [CI] = 3.572-60.749, p < 0.001). However, the survival to discharge did not differ between the two groups. DS, when finally diagnosed instead of the initial misclassification, was associated with in-hospital mortality (OR = 0.317, 95%CI = 0.124-0.810, p = 0.016). Conclusions: The misclassification of UH in the ED is not rare, particularly in patients with DS, who are likely to be initially misdiagnosed with HS. Although misclassification may increase hospitalization and decrease ED discharge, it does not affect survival to discharge.

The compliance with TTM protocol may benefit outcomes in cardiac arrest survivors: A retrospective cohort study.

BACKGROUND: Established protocols for implementing high-quality targeted temperature management (TTM) provide guidance concerning the cooling rate, duration of maintenance, and rewarming speed. However, whether compliant to TTM protocols results in improved survival and better neurological recovery has not been examined. METHODS: A retrospective cohort study enrolled 1141 survivors of non-traumatic adult cardiac arrest with a pre-arrest cerebral performance category (CPC) score of 1-2 from 2015 to 2020 at a tertiary medical center. Of the survivors, 330 patients who underwent TTM were further included. Patients with spontaneous hypothermia (<35 °C) (n = 107) and expired during the TTM (n = 21) were excluded. A total of 202 patients were thus enrolled. One hundred and ten patients underwent TTM that completely complied with the protocol (protocol-complaint group), but 92 patients deviated in some manner from the protocol (protocol non-compliant group). RESULTS: Fifty patients (50%) and 46 patients (50%) in the protocol-compliant and non-compliant groups, respectively, did not survive to hospital discharge. In the protocol-compliant group, 42 patients (38.2%) had favorable neurological recovery, compared with 32 patients (34.8%) in the protocol non-compliant group. After adjusting for age, initial shockable rhythm, witnessed collapse, and cardiopulmonary resuscitation duration, protocol non-compliant was associated with the poor neurological outcomes (aOR 2.44, 95% CI = 1.13-5.25), but not with in-hospital mortality (aOR 1.31, 95% CI = 0.70-2.47). The most common reason for noncompliance was a prolonged duration reaching the target temperature (n = 33, 58.7%). The number of phases of non-compliant was not significantly associated with in-hospital mortality or poor neurological recovery. CONCLUSION: Among cardiac arrest survivors undergoing TTM, those who did not receive TTM that in compliance with the protocol were more likely to experience poor neurological recovery than those whose TTM fully complied with the protocols. The most frequently identified deviation was a prolonged duration to reaching the target temperature.

Application of Phosphorylated Tau for Predicting Outcomes Among Sudden Cardiac Arrest Survivors.

BACKGROUND: Phosphorylated Tau (p-Tau), an early biomarker of neuronal damage, has emerged as a promising candidate for predicting neurological outcomes in cardiac arrest (CA) survivors. Despite its potential, the correlation of p-Tau with other clinical indicators remains underexplored. This study assesses the predictive capability of p-Tau and its effectiveness when used in conjunction with other predictors. METHODS: In this single-center retrospective study, 230 CA survivors had plasma and brain computed tomography scans collected within 24 h after the return of spontaneous circulation (ROSC) from January 2016 to June 2023. The patients with prearrest Cerebral Performance Category scores ≥ 3 were excluded (n = 33). The neurological outcomes at discharge with Cerebral Performance Category scores 1-2 indicated favorable outcomes. Plasma p-Tau levels were measured using an enzyme-linked immunosorbent assay, diastolic blood pressure (DBP) was recorded after ROSC, and the gray-to-white matter ratio (GWR) was calculated from brain computed tomography scans within 24 h after ROSC. RESULTS: Of 197 patients enrolled in the study, 54 (27.4%) had favorable outcomes. Regression analysis showed that higher p-Tau levels correlated with unfavorable neurological outcomes. The levels of p-Tau were significantly correlated with DBP and GWR. For p-Tau to differentiate between neurological outcomes, an optimal cutoff of 456 pg/mL yielded an area under the receiver operating characteristic curve of 0.71. Combining p-Tau, GWR, and DBP improved predictive accuracy (area under the receiver operating characteristic curve = 0.80 vs. 0.71, p = 0.008). CONCLUSIONS: Plasma p-Tau levels measured within 24 h following ROSC, particularly when combined with GWR and DBP, may serve as a promising biomarker of neurological outcomes in CA survivors, with higher levels predicting unfavorable outcomes.

Impact of Postarrest Vasoactive-Inotropic Score on Acute Kidney Injury in Cardiac Arrest Survivors: A Retrospective Cohort Study.

Background: Postarrest acute kidney injury (AKI) is a major health burden because it is associated with prolonged hospitalization, increased dialysis requirement, high mortality, and unfavorable neurological outcomes. Managing hemodynamic instability during the early postarrest period is critical; however, the role of quantified vasopressor dependence in AKI development in relation to illness severity remains unclear. Methods: A retrospective, observational cohort study that enrolled 411 non-traumatic adult cardiac arrest survivors without pre-arrest end-stage kidney disease between January 2017 and December 2019, grouped according to their baseline kidney function. The criteria for kidney injury were based on the Kidney Disease: Improving Global Outcomes definition and AKI staging system. The degree of vasopressor dependence within the first 24 h following return of spontaneous circulation (ROSC) was presented using the maximum vasoactive-inotropic score ( VIS max ). Results: Of the 411 patients, 181 (44%) had early AKI after ROSC. Patients with AKI showed an increased risk of in-hospital mortality (adjusted OR [aOR] 5.40, 95% CI 3.36-8.69, p < 0.001) and unfavorable neurological outcome (aOR 5.70, 95% CI 3.45-9.43, p < 0.001) compared to patients without AKI. The risk of adverse outcomes increased with illness severity. Patients with vasopressor support had an increased risk of early AKI. A low VIS max was associated with AKI stage 1-2 (aOR 2.51, 95% CI 1.20-5.24), whereas a high VIS max was associated with an increased risk for AKI stage 3 (aOR 2.46, 95% CI 1.28-4.75). Conclusions: Early AKI is associated with an increased risk of in-hospital mortality and unfavorable neurologic recovery in cardiac arrest survivors. Postarrest VIS max is an independent predictor of the development and severity of AKI following ROSC, regardless of baseline kidney function.

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.

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.

Outcome prediction of cardiac arrest with automatically computed gray-white matter ratio on computed tomography images.

BACKGROUND: This study aimed to develop an automated method to measure the gray-white matter ratio (GWR) from brain computed tomography (CT) scans of patients with out-of-hospital cardiac arrest (OHCA) and assess its significance in predicting early-stage neurological outcomes. METHODS: Patients with OHCA who underwent brain CT imaging within 12 h of return of spontaneous circulation were enrolled in this retrospective study. The primary outcome endpoint measure was a favorable neurological outcome, defined as cerebral performance category 1 or 2 at hospital discharge. We proposed an automated method comprising image registration, K-means segmentation, segmentation refinement, and GWR calculation to measure the GWR for each CT scan. The K-means segmentation and segmentation refinement was employed to refine the segmentations within regions of interest (ROIs), consequently enhancing GWR calculation accuracy through more precise segmentations. RESULTS: Overall, 443 patients were divided into derivation N=265, 60% and validation N=178, 40% sets, based on age and sex. The ROI Hounsfield unit values derived from the automated method showed a strong correlation with those obtained from the manual method. Regarding outcome prediction, the automated method significantly outperformed the manual method in GWR calculation (AUC 0.79 vs. 0.70) across the entire dataset. The automated method also demonstrated superior performance across sensitivity, specificity, and positive and negative predictive values using the cutoff value determined from the derivation set. Moreover, GWR was an independent predictor of outcomes in logistic regression analysis. Incorporating the GWR with other clinical and resuscitation variables significantly enhanced the performance of prediction models compared to those without the GWR. CONCLUSIONS: Automated measurement of the GWR from non-contrast brain CT images offers valuable insights for predicting neurological outcomes during the early post-cardiac arrest period.

Prognostic value of arterial carbon dioxide tension during cardiopulmonary resuscitation in out-of-hospital cardiac arrest patients receiving extracorporeal resuscitation.

BACKGROUND: Current guidelines on extracorporeal cardiopulmonary resuscitation (ECPR) recommend careful patient selection, but precise criteria are lacking. Arterial carbon dioxide tension (PaCO2) has prognostic value in out-of-hospital cardiac arrest (OHCA) patients but has been less studied in patients receiving ECPR. We studied the relationship between PaCO2 during cardiopulmonary resuscitation (CPR) and neurological outcomes of OHCA patients receiving ECPR and tested whether PaCO2 could help ECPR selection. METHODS: This single-centre retrospective study enrolled 152 OHCA patients who received ECPR between January 2012 and December 2020. Favorable neurological outcome (FO) at discharge was the primary outcome. We used multivariable logistic regression to determine the independent variables for FO and generalised additive model (GAM) to determine the relationship between PaCO2 and FO. Subgroup analyses were performed to test discriminative ability of PaCO2 in subgroups of OHCA patients. RESULTS: Multivariable logistic regression showed that PaCO2 was independently associated with FO after adjusting for other favorable resuscitation characteristics (Odds ratio [OR] 0.23, 95% Confidence Interval [CI] 0.08-0.66, p-value = 0.006). GAM showed a near-linear reverse relationship between PaCO2 and FO. PaCO2 < 70 mmHg was the cutoff point for predicting FO. PaCO2 also had prognostic value in patients with less favorable characteristics, including non-shockable rhythm (OR, 3.78) or low flow time > 60 min (OR, 4.66). CONCLUSION: PaCO2 before ECMO implementation had prognostic value for neurological outcomes in OHCA patients. Patients with PaCO2 < 70 mmHg had higher possibility of FO, even in those with non-shockable rhythm or longer low-flow duration. PaCO2 could serve as an ECPR selection criterion.

Prognostic implication of heart failure stage and left ventricular ejection fraction for patients with in-hospital cardiac arrest: a 16-year retrospective cohort study.

BACKGROUND: The 2022 AHA/ACC/HFSA guidelines for the management of heart failure (HF) makes therapeutic recommendations based on HF status. We investigated whether the prognosis of in-hospital cardiac arrest (IHCA) could be stratified by HF stage and left ventricular ejection fraction (LVEF). METHODS: This single-center retrospective study analyzed the data of patients who experienced IHCA between 2005 and 2020. Based on admission diagnosis, past medical records, and pre-arrest echocardiography, patients were classified into general IHCA, at-risk for HF, pre-HF, HF with preserved ejection fraction (HFpEF), and HF with mildly reduced ejection fraction or HF with reduced ejection fraction (HFmrEF-or-HFrEF) groups. RESULTS: This study included 2,466 patients, including 485 (19.7%), 546 (22.1%), 863 (35.0%), 342 (13.9%), and 230 (9.3%) patients with general IHCA, at-risk for HF, pre-HF, HFpEF, and HFmrEF-or-HFrEF, respectively. A total of 405 (16.4%) patients survived to hospital discharge, with 228 (9.2%) patients achieving favorable neurological recovery. Multivariable logistic regression analysis indicated that pre-HF and HFpEF were associated with better neurological (pre-HF, OR: 2.11, 95% confidence interval [CI]: 1.23-3.61, p = 0.006; HFpEF, OR: 1.90, 95% CI: 1.00-3.61, p = 0.05) and survival outcomes (pre-HF, OR: 2.00, 95% CI: 1.34-2.97, p < 0.001; HFpEF, OR: 1.91, 95% CI: 1.20-3.05, p = 0.007), compared with general IHCA. CONCLUSION: HF stage and LVEF could stratify patients with IHCA into different prognoses. Pre-HF and HFpEF were significantly associated with favorable neurological and survival outcomes after IHCA. Further studies are warranted to investigate whether HF status-directed management could improve IHCA outcomes.

Point-of-care testing for adult out-of-hospital cardiac arrest resuscitated at the ED to predict ROSC: Development and external validation of POC-ED-ROSC model.

BACKGROUND AND IMPORTANCE: Most prediction models, like return of spontaneous circulation (ROSC) after cardiac arrest (RACA) or Utstein-based (UB)-ROSC score, were developed for prehospital settings to predict the probability of ROSC in patients with out-of-hospital cardiac arrest (OHCA). A prediction model has been lacking for the probability of ROSC in patients with OHCA at emergency departments (EDs). OBJECTIVE: In the present study, a point-of-care (POC) testing-based model, POC-ED-ROSC, was developed and validated for predicting ROSC of OHCA at EDs. DESIGN, SETTINGS AND PARTICIPANTS: Prospectively collected data for adult OHCA patients between 2015 and 2020 were analysed. POC blood gas analysis obtained within 5 min of ED arrival was used. OUTCOMES MEASURE AND ANALYSIS: The primary outcome was ROSC. In the derivation cohort, multivariable logistic regression was used to develop the POC-ED-ROSC model. In the temporally split validation cohort, the discriminative performance of the POC-ED-ROSC model was assessed using the area under the receiver operating characteristic (ROC) curve (AUC) and compared with RACA or UB-ROSC score using DeLong test. MAIN RESULTS: The study included 606 and 270 patients in the derivation and validation cohorts, respectively. In the total cohort, 471 patients achieved ROSC. Age, initial cardiac rhythm at ED, pre-hospital resuscitation duration, and POC testing-measured blood levels of lactate, potassium and glucose were significant predictors included in the POC-ED-ROSC model. The model was validated with fair discriminative performance (AUC: 0.75, 95% confidence interval [CI]: 0.69-0.81) with no significant differences from RACA (AUC: 0.68, 95% CI: 0.62-0.74) or UB-ROSC score (AUC: 0.74, 95% CI: 0.68-0.79). CONCLUSION: Using only six easily accessible variables, the POC-ED-ROSC model can predict ROSC for OHCA resuscitated at ED with fair accuracy.

Comparison of outcomes between cardiogenic and non-cardiogenic cardiac arrest patients receiving targeted temperature management: The nationwide TIMECARD multicenter registry.

BACKGROUND AND PURPOSE: Targeted temperature management (TTM) has been recommended for post-resuscitation care of cardiac arrest (CA) patients who remain comatose. However, the differences between cardiogenic and non-cardiogenic causes need further investigation. Thus, this study aimed to investigate the difference in outcomes between cardiogenic and non-cardiogenic CA patients receiving TTM. METHODS: The TIMECARD registry established the study cohort and database for patients receiving TTM between January 2013 and September 2019. A total of 543 patients were enrolled, with 305 and 238 patients in the cardiogenic and non-cardiogenic groups, respectively. RESULTS: Compared with the non-cardiogenic group, the cardiogenic group had higher proportion of initial shockable rhythm, better survival (cardiogenic: 45.9%; non-cardiogenic: 30.7%, P = 0.0017), and better neurologic performance at discharge. In the cardiogenic group, witnessed collapse (OR = 0.31, 95% CI: 0.13-0.72), and coronary intervention (OR = 0.45, 95% CI: 0.24-0.84) were positive predictors for overall outcome. Mean arterial pressure <65 mmHg led to poor outcome regardless in the cardiogenic (OR = 3.31, 95% CI: 1.46-7.52) or non-cardiogenic group (OR = 2.39, 95% CI: 1.06-5.39). CONCLUSION: Patients with cardiogenic CA post TTM had better survival and neurologic performance at discharge than those without cardiogenic CA. Cardiogenic etiology was a potential predictor of better cardiac arrest survival, but it was not an independent risk factor for overall outcome after adjusting for potential covariates. In the cardiogenic group, better outcomes were reported in patients with witnessed collapse, bystander cardiopulmonary resuscitation, as well as those receiving coronary intervention.

TIMECARD score: An easily operated prediction model of unfavorable neurological outcomes in out-of-hospital cardiac arrest patients with targeted temperature management.

BACKGROUND: Targeted temperature management (TTM) is recommended for comatose out-of-hospital cardiac arrest (OHCA) survivors. Several prediction models have been proposed; however, most of these tools require data conversion and complex calculations. Early and easy predictive model of neurological prognosis in OHCA survivors with TTM warrant investigation. MATERIALS AND METHODS: This multicenter retrospective cohort study enrolled 408 non-traumatic adult OHCA survivors with TTM from the TaIwan network of targeted temperature ManagEment for CARDiac arrest (TIMECARD) registry during January 2014 to June 2019. The primary outcome was unfavorable neurological outcome at discharge. The clinical variables associated with unfavorable neurological outcomes were identified and a risk prediction score-TIMECARD score was developed. The model was validated with data from National Taiwan University Hospital. RESULTS: There were 319 (78.2%) patients presented unfavorable neurological outcomes at hospital discharge. Eight independent variables, including malignancy, no bystander cardiopulmonary resuscitation (CPR), non-shockable rhythm, call-to-start CPR duration >5 min, CPR duration >20 min, sodium bicarbonate use during resuscitation, Glasgow Coma Scale motor score of 1 at return of spontaneous circulation, and no emergent coronary angiography, revealed a significant correlation with unfavorable neurological prognosis in TTM-treated OHCA survivors. The TIMECARD score was established and demonstrated good discriminatory performance in the development cohort (area under the receiver operating characteristic curve [AUC] = 0.855) and validation cohorts (AUC = 0.918 and 0.877, respectively). CONCLUSION: In emergency settings, the TIMECARD score is a practical and simple-to-calculate tool for predicting neurological prognosis in OHCA survivors, and may help determine whether to initiate TTM in indicated patients.

Clinical Validation of Explainable Deep Learning Model for Predicting the Mortality of In-Hospital Cardiac Arrest Using Diagnosis Codes of Electronic Health Records.

Background: Using deep learning for disease outcome prediction is an approach that has made large advances in recent years. Notwithstanding its excellent performance, clinicians are also interested in learning how input affects prediction. Clinical validation of explainable deep learning models is also as yet unexplored. This study aims to evaluate the performance of Deep SHapley Additive exPlanations (D-SHAP) model in accurately identifying the diagnosis code associated with the highest mortality risk. Methods: Incidences of at least one in-hospital cardiac arrest (IHCA) for 168,693 patients as well as 1,569,478 clinical records were extracted from Taiwan's National Health Insurance Research Database. We propose a D-SHAP model to provide insights into deep learning model predictions. We trained a deep learning model to predict the 30-day mortality likelihoods of IHCA patients and used D-SHAP to see how the diagnosis codes affected the model's predictions. Physicians were asked to annotate a cardiac arrest dataset and provide expert opinions, which we used to validate our proposed method. A 1-to-4-point annotation of each record (current decision) along with four previous records (historical decision) was used to validate the current and historical D-SHAP values. Results: A subset consisting of 402 patients with at least one cardiac arrest record was randomly selected from the IHCA cohort. The median age was 72 years, with mean and standard deviation of 69 ± 17 years. Results indicated that D-SHAP can identify the cause of mortality based on the diagnosis codes. The top five most important diagnosis codes, namely respiratory failure, sepsis, pneumonia, shock, and acute kidney injury were consistent with the physician's opinion. Some diagnoses, such as urinary tract infection, showed a discrepancy between D-SHAP and clinical judgment due to the lower frequency of the disease and its occurrence in combination with other comorbidities. Conclusions: The D-SHAP framework was found to be an effective tool to explain deep neural networks and identify most of the important diagnoses for predicting patients' 30-day mortality. However, physicians should always carefully consider the structure of the original database and underlying pathophysiology.

Combination of Cerebral Computed Tomography and Simplified Cardiac Arrest Hospital Prognosis (sCAHP) Score for Predicting Neurological Recovery in Cardiac Arrest Survivors.

Background: Cerebral computed tomography (CT) and various severity scoring systems have been developed for the early prediction of the neurological outcomes of cardiac arrest survivors. However, few studies have combined these approaches. Therefore, we evaluated the value of the combination of cerebral CT and severity score for neuroprognostication. Methods: This single-center, retrospective observational study included consecutive patients surviving nontraumatic cardiac arrest (January 2016 and December 2020). Gray-to-white ratio (GWR), third and fourth ventricle characteristics, and medial temporal lobe atrophy scores were evaluated on noncontrast cerebral CT. Simplified cardiac arrest hospital prognosis (sCAHP) score was calculated for severity assessment. The associations between the CT characteristics, sCAHP score and neurological outcomes were analyzed. Results: This study enrolled 559 patients. Of them, 194 (34.7%) were discharged with favorable neurological outcomes. Patients with favorable neurological outcome had a higher GWR (1.37 vs 1.25, p < 0.001), area of fourth ventricle (461 vs 413 mm 2 , p < 0.001), anteroposterior diameter of fourth ventricle (0.95 vs 0.86 cm , p < 0.001) and a lower sCAHP score (146 vs 190, p < 0.001) than those with poor recovery. Patients with higher sCAHP score had lower GWR (p trend < 0.001), area of fourth ventricle (p trend = 0.019) and anteroposterior diameter of fourth ventricle (p trend = 0.014). The predictive ability by using area under receiver operating characteristic curve (AUC) for the combination of sCAHP score and GWR was significantly higher than that calculated for sCAHP (0.86 vs 0.76, p < 0.001) or GWR (0.86 vs 0.81, p = 0.001) alone. Conclusions: The combination of GWR and sCAHP score can be used to effectively predict the neurological outcomes of cardiac arrest survivors and thus ensure timely intervention for those at high risk of poor recovery.

Optimal inhaled oxygen and carbon dioxide concentrations for post-cardiac arrest cerebral reoxygenation and neurological recovery.

Prolonged cerebral hypoperfusion after the return of spontaneous circulation (ROSC) from cardiac arrest (CA) may lead to poor neurological recovery. In a 7-min asphyxia-induced CA rat model, four combinations of inhaled oxygen (iO2) and carbon dioxide (iCO2) were administered for 150 min post-ROSC and compared in a randomized animal trial. At the end of administration, the partial pressure of brain tissue oxygenation (PbtO2) monitored in the hippocampal CA1 region returned to the baseline for the 88% iO2 [ΔPbtO2, median: -0.39 (interquartile range: 5.6) mmHg] and 50% iO2 [ΔpbtO2, -2.25 (10.9) mmHg] groups; in contrast, PbtO2 increased substantially in the 88% iO2+12% iCO2 [ΔpbtO2, 35.05 (16.0) mmHg] and 50% iO2+12% iCO2 [ΔpbtO2, 42.03 (31.7) mmHg] groups. Pairwise comparisons (post hoc Dunn's test) indicated the significant role of 12% iCO2 in augmenting PbtO2 during the intervention and improving neurological recovery at 24 h post-ROSC. Facilitating brain reoxygenation may improve post-CA neurological outcomes.

Inhaled Carbon Dioxide Improves Neurological Outcomes by Downregulating Hippocampal Autophagy and Apoptosis in an Asphyxia-Induced Cardiac Arrest and Resuscitation Rat Model.

Background Protracted cerebral hypoperfusion following cardiac arrest (CA) may cause poor neurological recovery. We hypothesized that inhaled carbon dioxide (CO2) could augment cerebral blood flow (CBF) and improve post-CA neurological outcomes. Methods and Results After 6-minute asphyxia-induced CA and resuscitation, Wistar rats were randomly allocated to 4 groups (n=25/group) and administered with different inhaled CO2 concentrations, including control (0% CO2), 4% CO2, 8% CO2, and 12% CO2. Invasive monitoring was maintained for 120 minutes, and neurological outcomes were evaluated with neurological function score at 24 hours post-CA. After the 120-minute experiment, CBF was 242.3% (median; interquartile range, 221.1%-267.4%) of baseline in the 12% CO2 group while CBF fell to 45.8% (interquartile range, 41.2%-58.1%) of baseline in the control group (P<0.001). CBF increased along with increasing inhaled CO2 concentrations with significant linear trends (P<0.001). At 24 hours post-CA, compared with the control group (neurological function score, 9 [interquartile range, 8-9]), neurological recovery was significantly better in the 12% CO2 group (neurological function score, 10 [interquartile range, 9.8-10]) (P<0.001) while no survival difference was observed. Brain tissue malondialdehyde (P=0.02) and serum neuron-specific enolase (P=0.002) and S100ß levels (P=0.002) were significantly lower in the 12% CO2 group. TUNEL (terminal deoxynucleotidyl transferase-mediated biotin-deoxyuridine triphosphate nick-end labeling)-positive cell densities in hippocampal CA1 (P<0.001) and CA3 (P<0.001) regions were also significantly reduced in the 12% CO2 group. Western blotting showed that beclin-1 (P=0.02), p62 (P=0.02), and LAMP2 (lysosome-associated membrane protein 2) (P=0.01) expression levels, and the LC3B-II:LC3B-I ratio (P=0.02) were significantly lower in the 12% CO2 group. Conclusions Administering inhaled CO2 augmented post-CA CBF, mitigated oxidative brain injuries, ameliorated neuronal injury, and downregulated apoptosis and autophagy, thereby improving neurological outcomes.

Using a telemedicine-assisted airway model to improve the communication and teamwork of tracheal intubation during the coronavirus disease 2019 pandemic.

INTRODUCTION: Isolated spaces impair communication and teamwork during tracheal intubation (TI) in suspected coronavirus disease 2019 patients. We thus aimed to evaluate the telemedicine-assisted airway model (TAM) to improve communication and teamwork during the pandemic. METHODS: This two-stage prospective study included adult patients intubated in the emergency department of the National Taiwan University Hospital between 1 August 2020 and 31 July 2021. First, we randomised patients receiving TI in the standard setting into the conventional group (Con-G) and the isolation area into the isolation group (Iso-G). We evaluated the obstacles to communication and teamwork in an isolation scenario. Second, we developed the TAM to facilitate communication and teamwork between staff in separate spaces during TI and assigned patients to the TAM group (TAM-G). Communication and teamwork were evaluated using the Team Emergency Assessment Measure (TEAM). Subjective evaluations were conducted using a questionnaire administered to medical staff. RESULTS: Eighty-nine patients were enrolled: 17, 34, and 38 in the Con-G, Iso-G, and TAM-G, respectively. The communication frequency (CF) of the Con-G and Iso-G was the highest and lowest, respectively. The CF of the TAM-G increased and approached that of the Con-G. The overall TEAM score was the highest in the Con-G and the lowest in the Iso-G, while the overall score in the TAM-G was comparable to that of the Con-G. DISCUSSION: The TAM may improve communication and teamwork for TIs without compromising efficacy during the pandemic. This study was registered at ClinicalTrials.gov; registration numbers: NCT04479332 and NCT04591873.

Post-resuscitation diastolic blood pressure is a prognostic factor for outcomes of cardiac arrest patients: a multicenter retrospective registry-based analysis.

BACKGROUND: Post-resuscitation hemodynamic level is associated with outcomes. This study was conducted to investigate if post-resuscitation diastolic blood pressure (DBP) is a favorable prognostic factor. METHODS: Using TaIwan Network of Targeted Temperature ManagEment for CARDiac Arrest (TIMECARD) registry, we recruited adult patients who received targeted temperature management in nine medical centers between January 2014 and September 2019. After excluding patients with extracorporeal circulation support, 448 patients were analyzed. The first measured, single-point blood pressure after resuscitation was used for analysis. Study endpoints were survival to discharge and discharge with favorable neurologic outcomes (CPC 1-2). Multivariate analysis, area under the receiver operating characteristic curve (AUC), and generalized additive model (GAM) were used for analysis. RESULTS: Among the 448 patients, 182 (40.7%) patients survived, and 89 (19.9%) patients had CPC 1-2. In the multivariate analysis, DBP > 70 mmHg was an independent factor for survival (adjusted odds ratio [aOR] 2.16, 95% confidence interval [CI, 1.41-3.31]) and > 80 mmHg was an independent factor for CPC 1-2 (aOR 2.04, 95% CI [1.14-3.66]). GAM confirmed that DBP > 80 mmHg was associated with a higher likelihood of CPC 1-2. In the exploratory analysis, patients with DBP > 80 mmHg had a significantly higher prevalence of cardiogenic cardiac arrest (p = 0.015) and initial shockable rhythm (p = 0.045). CONCLUSION: We found that DBP after resuscitation can predict outcomes, as a higher DBP level correlated with cardiogenic cardiac arrest.