Does One Size Fit All? External Validation of the rCAST Score to Predict the Hospital Outcomes of Post-Cardiac Arrest Patients Receiving Targeted Temperature Management

Factors predicting mortality in the cardiac ICU during the early phase of targeted temperature management in the treatment of post-cardiac arrest syndrome - The RAPID score

Introduction

Survival rates after out-of-hospital cardiac arrest (OHCA) remain low, and early prognostication is challenging. While numerous intensive care unit scoring systems exist, their utility in the early hours following hospital admission, specifically in the targeted temperature management (TTM) population, is questionable. Our aim was to create a score system that may accurately estimate outcome within the first 12 h after admission in patients receiving TTM.

Methods

We analyzed data from 103 OHCA patients who subsequently underwent TTM between 2016 and 2022. Patient demographic data, prehospital characteristics, clinical and laboratory parameters were already available in the first 12 h after admission were collected. Following a bootstrap-based predictor selection, we constructed a nonlinear logistic regression model. Internal validation was performed using bootstrap resampling. Discrimination was described using the c-statistic, whereas calibration was characterized by the intercept and slope.

Results

According to the Akaike Information Criterion (AIC) heart rate (AIC = 9.24, p = 0.0013), age (AIC = 4.39, p = 0.0115), pH (AIC = 3.68, p = 0.0171), initial rhythm (AIC = 4.76, p = 0.0093) and right ventricular end-diastolic diameter (AIC = 2.49, p = 0.0342) were associated with 30-day mortality and were used to build our predictive model and nomogram. The area under the receiver-operating characteristics curve for the model was 0.84. The model achieved a C-statistic of 0.7974, with internally validated acceptable calibration (intercept: -0.0190, slope: 0.7772) and low error rates (mean absolute error: 0.040).

Conclusion

The model we have developed may be suitable for early risk assessment of patients receiving TTM as part of primary post-resuscitation care. The calculator needed for scoring can be accessed at the following link: https://www.rapidscore.eu/.

EPOS-OHCA: Early Predictors of Outcome and Survival after non-traumatic Out-of-Hospital Cardiac Arrest

Background

Post-cardiac arrest syndrome (PCAS) after out-of-hospital cardiac arrest (OHCA) poses significant challenges due to its complex pathomechanisms involving inflammation, ischemia, and reperfusion injury. The identification of early available prognostic indicators is essential for optimizing therapeutic decisions and improving patient outcomes.

Methods

In this retrospective single-center study, we analyzed real-world data from 463 OHCA patients with either prehospital or in-hospital return of spontaneous circulation (ROSC), treated at the Cardiac Arrest Center of the University Hospital of Marburg (MCAC) from January 2018 to December 2022. We evaluated demographic, prehospital, and clinical variables, including initial rhythms, resuscitation details, and early laboratory results. Statistical analyses included logistic regression to identify predictors of survival and neurological outcomes.

Results

Overall, 46.9% (n = 217) of patients survived to discharge, with 70.1% (n = 152) achieving favorable neurological status (CPC 1 or 2). Age, initial shockable rhythm, resuscitation time to return of spontaneous circulation (ROSC), and early laboratory parameters like lactate, C-reactive protein, and glomerular filtration rate were identified as independent and combined Early Predictors of Outcome and Survival (EPOS), with high significant predictive value for survival (AUC 0.86 [95% CI 0.82-0.89]) and favorable neurological outcome (AUC 0.84 [95% CI 0.80-0.88]).

Conclusion

Integration of EPOS into clinical procedures may significantly improve clinical decision making and thus patient prognosis in the early time-crucial period after OHCA. However, further validation in other patient cohorts is needed.

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

INTRODUCTION

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSION

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

External Validation of the CAST and rCAST Score in Patients With Out-of-Hospital Cardiac Arrest Who Underwent Extracorporeal Cardiopulmonary Resuscitation: A Secondary Analysis of the SAVE-J II Study

BACKGROUND

Risk stratification is important in patients with post-cardiac arrest syndrome. The Post-Cardiac Arrest Syndrome for Therapeutic Hypothermia (CAST) and revised CAST (rCAST) scores have been well validated for predicting neurological outcomes, particularly for conventionally resuscitated patients with post-cardiac arrest syndrome. However, no studies have evaluated patients undergoing extracorporeal cardiopulmonary resuscitation.

METHODS AND RESULTS

Adult patients with out-of-hospital cardiac arrest who underwent extracorporeal cardiopulmonary resuscitation were analyzed in this retrospective observational multicenter cohort study. We validated the accuracy of the CAST/rCAST scores for predicting neurological outcomes at 30 days. Moreover, we compared the predictive performance of these scores with the TiPS65 risk score derived from patients with out-of-hospital cardiac arrest who were resuscitated using extracorporeal cardiopulmonary resuscitation. A total of 1135 patients were analyzed. The proportion of patients with favorable neurological outcomes was 16.6%. In the external validation, the area under the receiver operating characteristic curve of the CAST score was significantly higher than that of the rCAST score (area under the receiver operating characteristic curve 0.677 versus 0.603; P<0.001), but there was no significant difference with that of the TiPS65 score (versus 0.633; P=0.154). Both CAST/rCAST risk scores showed good calibration (Hosmer-Lemeshow test: P=0.726 and 0.674), and the CAST score showed significantly better predictability in net reclassification compared with the rCAST (P<0.001) and TiPS65 scores (P=0.001).

CONCLUSIONS

The prognostic accuracy of the CAST score was significantly better than that of other risk scores in net reclassification. The CAST score may help to predict neurological outcomes in patients with out-of-hospital cardiac arrest who undergo extracorporeal cardiopulmonary resuscitation. However, the predictive value of the CAST score was not sufficiently high for clinical application.

REGISTRATION

URL: https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000041577; Unique identifier: UMIN000036490.

Prediction of the neurological outcomes post-cardiac arrest: A prospective validation of the CAST and rCAST

INTRODUCTION

The neurologic prognosis of out-of-hospital cardiac arrest (OHCA) patients in whom return of spontaneous circulation (ROSC) is achieved remains poor. The aim of this study was to externally and prospectively validate two scoring systems developed by us: the CAST score, a scoring system to predict the neurological prognosis of OHCA patients undergoing targeted temperature management (TTM), and a simplified version of the same score developed for improved ease of use in clinical settings, the revised CAST (rCAST) score.

METHODS

This study was a prospective, multicenter, observational study conducted using the SOS KANTO 2017 registry, an OHCA registry involving hospitals in the Kanto region (including Tokyo) of Japan. The primary outcome was favorable neurological outcome (defined as Cerebral Performance Category score of 1 or 2) at 30 days and the secondary outcomes were favorable neurological outcome at 90 days and survival at 30 and 90 days. The predictive accuracies of the original CAST (oCAST) and rCAST scores were evaluated by using area under the receiver operating characteristic curve (AUC).

RESULTS

Of 9909 OHCA patients, 565 showed ROSC and received TTM. Of these, we analyzed the data of 259 patients in this study. The areas under the receiver operating characteristic curve (AUCs) of the oCAST and rCAST scores for predicting a favorable neurological outcome at 30 days were 0.86 and 0.87, respectively, and those for predicting a favorable neurological outcome at 90 days were 0.87 and 0.88, respectively. The rCAST showed a higher predictive accuracy for the neurological outcome as compared with the NULL-PLEASE score. The patients with a favorable neurological outcome who had been classified into the high severity group based on the rCAST tended to have hypothermia at hospital arrival and to not show any signs of loss of gray-white matter differentiation on brain CT. Neurological function at 90 days was correlated with the rCAST (r = 0.63, p < 0.001).

CONCLUSIONS

rCAST showed high predictive accuracy for the neurological prognosis of OHCA patients managed by TTM, comparable to that of the oCAST score. The scores on the rCAST were strongly correlated with the neurological functions at 90 days, implying that the rCAST is a useful scale for assessing the severity of brain injury after cardiac arrest.

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

AIM

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

METHODS

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

RESULTS

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

CONCLUSION

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