Applying a set of termination of resuscitation criteria to paediatric out-of-hospital cardiac arrest

The Latest in Resuscitation Research: Highlights From the 2022 American Heart Association's Resuscitation Science Symposium

BACKGROUND

Every year the American Heart Association's Resuscitation Science Symposium (ReSS) brings together a community of international resuscitation science researchers focused on advancing cardiac arrest care.

METHODS AND RESULTS

The American Heart Association's ReSS was held in Chicago, Illinois from November 4th to 6th, 2022. This annual narrative review summarizes ReSS programming, including awards, special sessions and scientific content organized by theme and plenary session.

CONCLUSIONS

By exploring both the science of resuscitation and important related topics including survivorship, disparities, and community-focused programs, this meeting provided important resuscitation updates.

Application of adult prehospital resuscitation rules to pediatric out of hospital cardiac arrest

BACKGROUND

Prehospital termination of resuscitation (TOR) rules can be recommended for adults with out-of-hospital cardiac arrests (OHCAs). This study aimed to investigate whether adult basic life support (BLS) and advanced life support (ALS) TOR rules can predict neurologically unfavorable one-month outcome for pediatric OHCA patients.

METHODS

From a nationwide population-based observational cohort study, we extracted data of consecutive pediatric OHCA patients (0-17 years old) from January 1, 2005, to December 31, 2011. The BLS TOR rule has three criteria, whereas the ALS TOR rule includes two additional criteria. We selected pediatric OHCA patients that met all criteria for each TOR rule and calculated the specificity and positive predictive value (PPV) of each TOR rule for identifying pediatric OHCA patients who did not have neurologically favorable one-month outcome.

RESULTS

Of the 12,740 pediatric OHCA patients eligible for the evaluation of the BLS TOR rule, 10,803 patients met the BLS TOR rule, with a specificity of 0.785 and a PPV of 0.987 for predicting a lack of neurologically favorable one-month survival. Of the 2,091 for the ALS TOR rule, 381 patients met the ALS TOR rule, with a specificity of 0.986 and a PPV of 0.997 for predicting neurologically unfavorable one-month outcome.

CONCLUSIONS

The adult BLS and ALS TOR rules had a high PPV for predicting pediatric OHCA patients without a neurologically favorable survival at one month after onset.

Identification of factors associated with return of spontaneous circulation after pediatric out-of-hospital cardiac arrest using natural language processing

Introduction: Prior studies examining prehospital characteristics related to return of spontaneous circulation (ROSC) in pediatric out-of-hospital cardiac arrest (OHCA) are limited to structured data. Natural language processing (NLP) could identify new factors from unstructured data using free-text narratives. The purpose of this study was to use NLP to examine EMS clinician free-text narratives for characteristics associated with prehospital ROSC in pediatric OHCA.Methods: This was a retrospective analysis of patients ages 0-17 with OHCA in 2019 from the ESO Data Collaborative. We performed an exploratory analysis of EMS narratives using NLP with an a priori token library. We then constructed biostatistical and machine learning models and compared their performance in predicting ROSC.Results: There were 1,726 included EMS encounters for pediatric OHCA; 60% were male patients, and the median age was 1 year (IQR 0-9). Most cardiac arrest events (61.3%) were unwitnessed, 87.3% were identified as having medical causes, and 5.9% had initial shockable rhythms. Prehospital ROSC was achieved in 23.1%. Words most positively correlated with ROSC were "ROSC" (r = 0.42), "pulse" (r = 0.29), "drowning" (r = 0.13), and "PEA" (r = 0.12). Words negatively correlated with ROSC included "asystole" (r = -0.25), "lividity" (r = -0.14), and "cold" (r = -0.14). The terms 'asystole,' 'pulse', 'no breathing', 'PEA', and 'dry' had the greatest difference in frequency of appearance between encounters with and without ROSC (p < 0.05). The best-performing model for predicting prehospital ROSC was logistic regression with random oversampling using free-text data only (area under the receiver operating characteristic curve 0.92).Conclusions: EMS clinician free-text narratives reveal additional characteristics associated with prehospital ROSC in pediatric OHCA. Incorporating those terms into machine learning models of prehospital ROSC improves predictive ability. Therefore, NLP holds promise as a tool for use in predictive models with the goal to increase evidence-based management of pediatric OHCA.

Resuscitation highlights in 2021

BACKGROUND

This review is the latest in a series of regular annual reviews undertaken by the editors and aims to highlight some of the key papers published in Resuscitation during 2021.

METHODS

Hand-searching by the editors of all papers published in Resuscitation during 2021. Papers were selected based on then general interest and novelty and were categorised into themes.

RESULTS

98 papers were selected for brief mention.

CONCLUSIONS

Resuscitation science continues to evolve and incorporates all links in the chain of survival.