Initial arterial pH as a predictor of neurologic outcome after out-of-hospital cardiac arrest: A propensity-adjusted analysis

The early change in pH values after out-of-hospital cardiac arrest is not associated with neurological outcome at hospital discharge

Background

The association between pH values and outcome for patients after out-of-hospital cardiac arrest (OHCA) was not fully elucidated; besides, the relationship of change in pH values and neurological outcome was unknown. The aim was to explore the association of pH values as well as change in pH values and neurological outcome for OHCA cardiac patients.

Methods

The adult patients with non-traumatic out-of-hospital cardiac arrest, shock-refractory ventricular fibrillation or pulseless ventricular tachycardia, and at least two arterial blood gases analysis recorded after admission were included. The change in pH values is calculated as the difference between the second and first pH value, and divided by time interval got the rate of change in pH values. The primary outcome was modified Rankin Score (mRS), dichotomized to good (mRS 0-3) and poor (mRS 4-6) outcomes at hospital discharge. The independent relationship of the first pH value, second pH value, and changes in pH values with neurological outcome was investigated with multivariable logistic regression models, respectively.

Results

A total of 1388 adult patients were included for analysis, of which 514 (37%) had good neurological outcome. The median first pH value and second pH value after admission were 7.21 (interquartile range [IQR] 7.09-7.29) and 7.28 (IQR 7.20-7.36), respectively. The median absolute, relative change, and rate of changes in pH values were 0.08 (IQR 0.01-0.16), 1.10% (IQR 0.11-2.22%), and 0.02 (IQR 0-0.06) per hour, respectively. After adjusting for confounders, the higher first pH value (odds ratio [OR] 3.81, confidence interval [CI] 1.60-9.24, P = 0.003) and higher second pH value (OR 9.54, CI 3.45-26.87, P < 0.001) after admission were associated with good neurological outcome, respectively. The absolute (OR 1.58, CI 0.58-4.30, P = 0.368) and relative (OR 1.03, CI 0.96-1.11, P = 0.399) change as well as the rate of change (OR 0.98, CI 0.33-2.71, P = 974) in pH values were not associated with neurological outcome.

Conclusions

For OHCA patients, abnormality in pH values was very common, with a more acidic pH value indicating poor neurological outcome. However, the change in pH values was not associated with outcomes.

The relationship between the initial pH and neurological outcome in patients with out-of-hospital cardiac arrest is affected by the status of recovery of spontaneous circulation on hospital arrival

The early prediction of neurological outcomes is useful for out-of-hospital cardiac arrest (OHCA). The initial pH was associated with neurological outcomes, but the values varied among the studies. Patients admitted to our division with OHCA of cardiac origin between January 2015 and December 2022 were retrospectively examined (N = 199). A good neurological outcome was defined as a Glasgow-Pittsburgh cerebral performance category (CPC) of 1-2 at discharge. Patients were divided according to the achievement of recovery of spontaneous circulation (ROSC) on hospital arrival, and the efficacy of pH in predicting good neurological outcomes was compared. In patients with ROSC on hospital arrival (N = 100), the initial pH values for good and poor neurological outcomes were 7.26 ± 0.14 and 7.09 ± 0.18, respectively (p < 0.001). In patients without ROSC on hospital arrival (N = 99), the initial pH values for good and poor neurological outcomes were 7.06 ± 0.23 and 6.92 ± 0.15, respectively (p = 0.007). The pH associated with good neurological outcome was much lower in patients without ROSC than in those with ROSC on hospital arrival (P = 0.003). A higher initial pH is associated with good neurological outcomes in patients with OHCA. However, the pH for a good or poor neurological outcome depends on the ROSC status on hospital arrival.

Arterial Blood Gas Analysis for Survival Prediction in Pediatric Patients with Out-of-Hospital Cardiac Arrest

Arterial blood gas analysis (ABGA) is one of the few tests performed during cardiopulmonary resuscitation (CPR). There have been some studies on the prediction of survival outcomes in adult out-of-hospital cardiac arrest (OHCA) patients during CPR using ABGA results. However, in pediatric OHCA patients, the prognosis of survival outcome based on ABGA results during CPR remains unclear. We retrospectively analyzed prospectively collected data from the Korean Cardiac Arrest Resuscitation Consortium (KoCARC) registry, a multicenter OHCA registry of Republic of Korea. We analyzed 108 pediatric (age < 19 years) OHCA patients between October 2015 and June 2022. Using multivariable logistic regression, an adjusted odds ratio (aOR) was obtained to validate the ABGA results of survival to hospital admission and survival to discharge. The variables associated with survival to hospital admission were non-comorbidities (aOR 3.03, 95% confidence interval (CI) 1.22-7.53, p = 0.017) and PaO₂ > 45.750 mmHg (aOR 2.69, 95% CI 1.13-6.42, p = 0.026). There was no variable that was statistically significant association with survival to discharge. PaO₂ > 47.750 mmHg and non-comorbidities may serve as an independent prognostic factor for survival to hospital admission in pediatric OHCA patients. However, the number of cases analyzed in our study was relatively small, and there have been few studies investigating the association between ABGA results during CPR and the survival outcome of pediatric OHCA patients. Therefore, further large-scale studies are needed.

Clinical Validation of Cardiac Arrest Hospital Prognosis (CAHP) Score and MIRACLE2 Score to Predict Neurologic Outcomes after Out-of-Hospital Cardiac Arrest

Background. Out-of-hospital cardiac arrest (OHCA) remains a challenge for emergency physicians, given the poor prognosis. In 2020, MIRACLE2, a new and easier to apply score, was established to predict the neurological outcome of OHCA. Objective. The aim of this study is to compare the discrimination of MIRACLE2 score with cardiac arrest hospital prognosis (CAHP) score for OHCA neurologic outcomes. Methods. This retrospective cohort study was conducted between January 2015 and December 2019. Adult patients (>17 years) with cardiac arrest who were brought to the hospital by an emergency medical service crew were included. Deaths due to trauma, burn, drowning, resuscitation not initiated due to pre-ordered “do not resuscitate” orders, and patients who did not achieve return of spontaneous circulation were excluded. Receiver operating characteristic curve analysis with Youden Index was performed to calculate optimal cut-off values for both scores. Results. Overall, 200 adult OHCA cases were analyzed. The threshold of the MIRACLE2 score for favorable neurologic outcomes was 5.5, with an area under the curve (AUC) value of 0.70 (0.61−0.80, p < 0.001); the threshold of the CAHP score was 223.4, with an AUC of 0.77 (0.68−0.86, p < 0.001). On setting the MIRACLE2 score cut-off value, we documented 64.7% sensitivity (95% confidence interval [CI], 56.9−71.9%), 66.7.0% specificity (95% CI, 48.2−82.0%), 90.8% positive predictive value (PPV; 95% CI, 85.6−94.2%), and 27.2% negative predictive value (NPV; 95% CI, 21.4−33.9%). On establishing a CAHP cut-off value, we observed 68.2% sensitivity (95% CI, 60.2−75.5%), 80.6% specificity (95% CI, 62.5−92.6%), 94.6% PPV (95% CI, 88.6%−98.0%), and 33.8% NPV (95% CI, 23.2−45.7%) for unfavorable neurologic outcomes. Conclusions. The CAHP score demonstrated better discrimination than the MIRACLE2 score, affording superior sensitivity, specificity, PPV, and NPV; however, the CAHP score remains relatively difficult to apply. Further studies are warranted to establish scores with better discrimination and ease of application.

Dynamic changes in arterial blood gas during cardiopulmonary resuscitation in out-of-hospital cardiac arrest

We aimed to investigate the prognostic value of dynamic changes in arterial blood gas analysis (ABGA) measured after the start of cardiopulmonary resuscitation (CPR) for return of spontaneous circulation (ROSC) in patients with out-of-hospital cardiac arrest (OHCA). This prospective observational study was conducted at the emergency department of a university hospital from February 2018 to February 2020. All blood samples for gas analysis were collected from a radial or femoral arterial line, which was inserted during CPR. Changes in ABGA parameters were expressed as delta (Δ), defined as the values of the second ABGA minus the values of the initial ABGA. The primary outcome was sustained ROSC. Out of the 80 patients included in the analysis, 13 achieved sustained ROSC after in-hospital resuscitation. Multivariable logistic analysis revealed that ΔpaO₂ (odds ratio [OR] = 1.023; 95% confidence interval [CI] = 1.004–1.043, p = 0.020) along with prehospital shockable rhythm (OR = 84.680; 95% CI = 2.561–2799.939, p = 0.013) and total resuscitation duration (OR = 0.881; 95% CI = 0.805–0.964, p = 0.006) were significant predictors for sustained ROSC. Our study suggests a possible association between ΔpaO₂ in ABGA during CPR and an increased rate of sustained ROSC in the late phase of OHCA.

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

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

Prediction of Neurological Outcomes in Out-of-hospital Cardiac Arrest Survivors Immediately after Return of Spontaneous Circulation: Ensemble Technique with Four Machine Learning Models

BACKGROUND

We performed this study to establish a prediction model for 1-year neurological outcomes in out-of-hospital cardiac arrest (OHCA) patients who achieved return of spontaneous circulation (ROSC) immediately after ROSC using machine learning methods.

METHODS

We performed a retrospective analysis of an OHCA survivor registry. Patients aged ≥ 18 years were included. Study participants who had registered between March 31, 2013 and December 31, 2018 were divided into a develop dataset (80% of total) and an internal validation dataset (20% of total), and those who had registered between January 1, 2019 and December 31, 2019 were assigned to an external validation dataset. Four machine learning methods, including random forest, support vector machine, ElasticNet and extreme gradient boost, were implemented to establish prediction models with the develop dataset, and the ensemble technique was used to build the final prediction model. The prediction performance of the model in the internal validation and the external validation dataset was described with accuracy, area under the receiver-operating characteristic curve, area under the precision-recall curve, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Futhermore, we established multivariable logistic regression models with the develop set and compared prediction performance with the ensemble models. The primary outcome was an unfavorable 1-year neurological outcome.

RESULTS

A total of 1,207 patients were included in the study. Among them, 631, 139, and 153 were assigned to the develop, the internal validation and the external validation datasets, respectively. Prediction performance metrics for the ensemble prediction model in the internal validation dataset were as follows: accuracy, 0.9620 (95% confidence interval [CI], 0.9352-0.9889); area under receiver-operator characteristics curve, 0.9800 (95% CI, 0.9612-0.9988); area under precision-recall curve, 0.9950 (95% CI, 0.9860-1.0000); sensitivity, 0.9594 (95% CI, 0.9245-0.9943); specificity, 0.9714 (95% CI, 0.9162-1.0000); PPV, 0.9916 (95% CI, 0.9752-1.0000); NPV, 0.8718 (95% CI, 0.7669-0.9767). Prediction performance metrics for the model in the external validation dataset were as follows: accuracy, 0.8509 (95% CI, 0.7825-0.9192); area under receiver-operator characteristics curve, 0.9301 (95% CI, 0.8845-0.9756); area under precision-recall curve, 0.9476 (95% CI, 0.9087-0.9867); sensitivity, 0.9595 (95% CI, 0.9145-1.0000); specificity, 0.6500 (95% CI, 0.5022-0.7978); PPV, 0.8353 (95% CI, 0.7564-0.9142); NPV, 0.8966 (95% CI, 0.7857-1.0000). All the prediction metrics were higher in the ensemble models, except NPVs in both the internal and the external validation datasets.

CONCLUSION

We established an ensemble prediction model for prediction of unfavorable 1-year neurological outcomes in OHCA survivors using four machine learning methods. The prediction performance of the ensemble model was higher than the multivariable logistic regression model, while its performance was slightly decreased in the external validation dataset.

Associations between initial serum pH value and outcomes of pediatric out-of-hospital cardiac arrest

INTRODUCTION

Pediatric out-of-hospital cardiac arrest (OHCA) is one of the most critical conditions seen in the emergency department (ED). Although initial serum pH value is reported to be associated with outcome in adult OHCA patients, the association is unclear in pediatric OHCA patients. Thus, we aimed to identify the association between initial pH value and outcome among pediatric OHCA patients.

METHODS

This study was a retrospective analysis of a multicenter prospective cohort registry (Japanese Association for Acute Medicine out-of-hospital cardiac arrest registry) from 87 hospitals in Japan. We included pediatric OHCA patients younger than 16 years of age who were registered in this registry between June 2014 and December 2017. Of the 34,754 patients in the database, 458 patients were ultimately included in the analysis. We equally divided the patients into four groups, based on their initial pH value, and conducted a multivariate logistic regression analysis to calculate the adjusted odds ratios of the initial pH value on hospital arrival with their 95% confidence intervals for the primary outcome.

RESULTS

The median (interquartile range) age was 1 (0-6) year, and 77.9% (357/458) of the first monitored rhythm was asystole. The primary outcome was 1-month survival. The overall 1-month survival was 13.3% (61/458), and a 1-month favorable neurologic outcome was seen in 5.2% (24/458) of cases. The adjusted odds ratios and 95% confidence intervals for the pH 6.81-6.64, pH 6.63-6.47, pH <6.47, and pH unknown groups compared with the pH ≥6.82 group for 1-month survival were 0.39 (0.16-0.97), 0.13 (0.04-0.44), 0.03 (0.00-0.24), and 0.07 (0.02-0.21), respectively.

CONCLUSIONS

This study demonstrated the association between the initial pH value on hospital arrival and 1-month survival among pediatric OHCA patients.

Development and Validation of a Clinical Score to Predict Neurological Outcomes in Patients With Out-of-Hospital Cardiac Arrest Treated With Extracorporeal Cardiopulmonary Resuscitation

IMPORTANCE

Extracorporeal cardiopulmonary resuscitation (ECPR) is expected to improve the neurological outcomes of patients with refractory cardiac arrest; however, it is invasive, expensive, and requires substantial human resources. The ability to predict neurological outcomes would assist in patient selection for ECPR.

OBJECTIVE

To develop and validate a prediction model for neurological outcomes of patients with out-of-hospital cardiac arrest with shockable rhythm treated with ECPR.

DESIGN, SETTING, AND PARTICIPANTS

This prognostic study analyzed data from the Japanese Association for Acute Medicine Out-of-Hospital Cardiac Arrest registry, a multi-institutional nationwide cohort study that included 87 emergency departments in Japan. All adult patients with out-of-hospital cardiac arrest and shockable rhythm who were treated with ECPR between June 2014 and December 2017 were included. Patients were randomly assigned to the development and validation cohorts based on the institutions. The analysis was conducted between November 2019 and August 2020.

EXPOSURES

Age (<65 years), time from call to hospital arrival (≤25 minutes), initial cardiac rhythm on hospital arrival (shockable), and initial pH value (≥7.0).

MAIN OUTCOMES AND MEASURES

The primary outcome was 1-month survival with favorable neurological outcome, defined by Cerebral Performance Category 1 or 2. In the development cohort, a simple scoring system was developed to predict this outcome using a logistic regression model. The diagnostic ability and calibration of the scoring system were assessed in the validation cohort.

RESULTS

A total of 916 patients were included, 458 in the development cohort (median [interquartile range {IQR}] age, 61 [47-69] years, 377 [82.3%] men) and 458 in the validation cohort (median [IQR] age, 60 [49-68] years; 393 [85.8%] men). The cohorts had the same proportion of favorable neurological outcome (57 patients [12.4%]). The prediction scoring system was developed, attributing a score of 1 for each clinical predictor. Patients were divided into 4 groups, corresponding to their scores on the prediction model, as follows: very low probability (score 0), low probability (score 1), middle probability (score 2), and high probability (score 3-4) of good neurological outcome. The mean predicted probabilities in the groups stratified by score were as follows: very low, 1.6% (95% CI, 1.6%-1.6%); low, 4.4% (95% CI, 4.2%-4.6%); middle, 12.5% (95% CI, 12.1%-12.8%); and high, 30.8% (95% CI, 29.1%-32.5%). In the validation cohort, the C statistic of the scoring system was 0.724 (95% CI, 0.652-0.786). The predicted probability was evaluated as well calibrated to the observed favorable outcome in both cohorts by visual assessment of the calibration plot.

CONCLUSIONS AND RELEVANCE

In this study, the scoring system had good discrimination and calibration performance to predict favorable neurological outcomes of patients with out-of-hospital cardiac arrest and shockable rhythm who were treated with ECPR.

Neurologic prognostication after resuscitation from cardiac arrest

Out-of-hospital cardiac arrest remains a leading cause of mortality in the United States, and the majority of patients who die after achieving return of spontaneous circulation die from withdrawal of care due to a perceived poor neurologic prognosis. Unfortunately, withdrawal of care often occurs during the first day of admission and research suggests this early withdrawal of care may be premature and result in unnecessary deaths for patients who would have made a full neurologic recovery. In this review, we explore the evidence for neurologic prognostication in the emergency department for patients who achieve return of spontaneous circulation after an out-of-hospital cardiac arrest.

Acidemia Detected on Venous Blood Gas After Out-of-Hospital Cardiac Arrest Predicts Likelihood to Survive to Hospital Discharge

BACKGROUND

Sudden cardiac arrest is the most common cause of death worldwide, and prognostication after survival remains challenging. Decisions regarding prognosis can be fraught with error in the immediate postarrest period, with guidelines recommending the use of various tests, including blood gas pH, to determine which interventions to perform. Despite these recommendations, the prognostic utility of blood gas pH remains unclear.

OBJECTIVES

In this retrospective cohort study, we aimed to demonstrate the prognostic utility of emergency department blood gas pH after return of spontaneous circulation (ROSC) in out-of-hospital cardiac arrest.

METHODS

A retrospective cohort study was performed, including all adult survivors of out-of-hospital cardiac arrest (n = 79). Primary disease-oriented outcome was venous blood pH after ROSC and survival to hospital discharge.

RESULTS

In patients with out-of-hospital cardiac arrest, pH < 7.2 was associated with decreased likelihood of survival to hospital discharge (odds ratio 0.06), with every 0.1-unit increase in pH being associated with an increased likelihood of survival (1.98). Based on the area under the receiver curve, the pH that optimizes sensitivity and specificity for predicting survival was 7.04.

CONCLUSION

Both presence and degree of acidemia on initial blood gas after ROSC was associated with a decreased likelihood of survival to hospital discharge. The optimal cutoff for prediction in this cohort of patients was 7.04. Using a higher pH cutoff would result in fewer patients receiving intervention that would otherwise have survived.