Scoring Systems to Predict Survival or Neurological Recovery after Out-of-hospital Cardiac Arrest

Simultaneous prognostic score validation in patients with out-of-hospital cardiac arrest by a post-hoc analysis based on national multicenter registry

Using a nationwide multicenter prospective registry in Japan's data, we calculated prognostic and predictive scores, including the Out-of-Hospital Cardiac Arrest (OHCA); Cardiac Arrest Hospital Prognosis (CAHP); Nonshockable rhythm, Unwitnessed arrest, Long no-flow or Long low-flow period, blood PH < 7.2, Lactate > 7.0 mmol/L, End-stage chronic kidney disease on dialysis, Age ≥ 85 years, Still resuscitation, and Extracardiac cause (NULL-PLEASE); revised post-Cardiac Arrest Syndrome for Therapeutic hypothermia (rCAST); and MIRACLE2 scores, for adult patients with cardiac arrest. The MIRACLE2 score was validated with the modified MIRACLE2 score, which excludes information of pupillary reflexes. Each score was calculated only for the cases with no missing data for the variables used. These scores' accuracies were compared using neurological outcomes 30 days after out-of-hospital cardiac arrest (OOHCA). Patients with a cerebral performance category scale of 1 or 2 were designated as having favorable neurological outcomes. Each score's discrimination ability was evaluated by the receiver operating characteristic curve's area under the curve (AUC). To assess in detail in areas of high specificity and high sensitivity, which are areas of interest to clinicians, partial AUCs were also used. The analysis included 11,924 hospitalized adult patients. The AUCs of the OHCA, MIRACLE2, CAHP, rCAST, and NULL-PLEASE scores for favorable neurological outcomes were 0.713, 0.727, 0.785, 0.761, and 0.831, respectively. The CAHP and NULL-PLEASE scores were significantly more accurate than the rest. Accuracies did not differ significantly between the CAHP and NULL-PLEASE scores. The NULL-PLEASE score was significantly better at discriminating favorable neurological prognoses at 30 days in patients with OOHCA compared to other scoring systems.

A Simple Scoring System for Identifying Favorable Neurologic Outcomes Among Out-of-Hospital Cardiac Arrest Patients With Asystole

STUDY OBJECTIVE

Asystole is the most common initial rhythm in out-of-hospital cardiac arrest (OHCA) but indicates a low likelihood of neurologic recovery. This study aimed to develop a novel scoring system to be easily applied at the time of emergency department arrival for identifying favorable neurologic outcomes in OHCA survivors with an asystole rhythm.

METHODS

This study is a secondary analysis based on a previously collected nationwide database, targeting nontraumatic adult OHCA patients aged ≥18 years with an asystole rhythm who achieved return of spontaneous circulation (ROSC) between January 2016 and December 2020. The primary outcome was a favorable neurologic outcome defined as Cerebral Performance Categories scores of 1 or 2 at hospital discharge. A prediction model was developed through multivariable logistic regression analysis in a derivation cohort in the form of a scoring system (WBC-ASystole). The performance and calibration of the model were tested using an internal validation cohort.

RESULTS

Among 19,803 OHCA patients with survival to hospital admission, 6,322 had asystole, and 285 (4.5%) achieved good neurologic outcomes. Factors associated with favorable outcomes included age, witness arrest, bystander cardiopulmonary resuscitation, time from call to hospital arrival, and out-of-hospital ROSC achievement. The WBC-ASystole score, totaling 11 points, exhibited a predictive performance with an area under the receiver operating characteristic curve of 0.80 (95% confidence interval [CI] 0.76 to 0.83) and 0.79 (95% CI 0.74 to 0.83) in the derivation and validation cohorts, respectively. After categorizing patients into 3 groups based on probability for good neurologic outcomes, the sensitivity and specificity were as follows: 0.98 (95% CI 0.97 to 0.99) and 0.09 (95% CI 0.09 to 0.10) for the very low predicted probability group (WBC-ASystole ≤2), 0.85 (95% CI 0.82 to 0.89) and 0.54 (95% CI 0.53 to 0.55) for the low predicted probability group (WBC-ASystole 3 to 4), and 0.36 (95% CI 0.34 to 0.39) and 0.93 (95% CI 0.92 to 0.93) for fair predicted probability group (WBC-ASystole≥5), respectively.

CONCLUSIONS

Although external validation studies must be performed, among OHCA patients with asystole, the WBC-ASystole scoring system may identify those patients who are likely to have a favorable neurologic outcome.

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.

A locally optimised machine learning approach to early prognostication of long-term neurological outcomes after out-of-hospital cardiac arrest

Background

Out-of-hospital cardiac arrest (OHCA) represents a major burden for society and health care, with an average incidence in adults of 67 to 170 cases per 100,000 person-years in Europe and in-hospital survival rates of less than 10%. Patients and practitioners would benefit from a prognostication tool for long-term good neurological outcomes.

Objective

We aim to develop a machine learning (ML) pipeline on a local database to classify patients according to their neurological outcomes and identify prognostic features.

Methods

We collected clinical and biological data consecutively from 595 patients who presented OHCA and were routed to a single regional cardiac arrest centre in the south of France. We applied recursive feature elimination and ML analyses to identify the main features associated with a good neurological outcome, defined as a Cerebral Performance Category score less than or equal to 2 at six months post-OHCA.

Results

We identified 12 variables 24 h after admission, capable of predicting a six-month good neurological outcome. The best model (extreme gradient boosting) achieved an AUC of 0.96 and an accuracy of 0.92 in the test cohort.

Conclusion

We demonstrated that it is possible to build accurate, locally optimised prediction and prognostication scores using datasets of limited size and breadth. We proposed and shared a generic machine-learning pipeline which allows external teams to replicate the approach locally.

Diagnostic Value of Serum Lactate Dehydrogenase Level Measured in the Emergency Department in Predicting Clinical Outcome in Out-of-Hospital Cardiac Arrest: A Multicenter, Observational Study

INTRODUCTION

Out-of-hospital cardiac arrest (OHCA) is complex, and risk stratification tools have the potential to include components other than clinical risk indicators, thus requiring extensive studies. Simple and accurate biomarkers for OHCA patients with poor prognoses are still needed. Serum lactate dehydrogenase (LDH) has been identified as a risk factor in patients with various diseases, such as cancer, liver disease, severe infections, and sepsis. The primary aim of this study was to assess the accuracy of LDH values at initial presentation in the emergency department (ED) in predicting the clinical outcome in OHCA.

METHODS

This retrospective multicenter observational study was performed in the ED of two tertiary university hospitals and one general hospital between January 2015 and December 2021. All patients with OHCA who visited the ED were included. The primary outcome was the sustained return of spontaneous circulation (ROSC; >20 min) after advanced cardiac life support (ACLS). The secondary outcome was survival to discharge (including home care and nursing care discharge) among patients with ROSC. The neurological prognosis was considered a tertiary outcome in patients who survived to discharge.

RESULTS

In total, 759 patients were enrolled in the final analysis. The median LDH level in the ROSC group was 448 U/L (range: 112-4500), which was significantly lower than that in the no-ROSC group (p < 0.001). The median LDH level in the survival-to-discharge group was 376 U/L (range: 171-1620), which was significantly lower than that in the death group (p < 0.001). Using the adjusted model, the odds ratio of the LDH value (≤634 U/L) for primary outcomes was 2.418 (1.665-3.513) and the odds ratio of LDH value (≤553 U/L) for secondary outcomes was 4.961 (2.184-11.269).

CONCLUSIONS

In conclusion, the serum LDH levels of patients with OHCA measured in the ED can potentially serve as a predictive marker for clinical outcomes such as ROSC and survival to discharge, although it may be difficult to predict neurological outcomes.