Impact of age on survival of patients with out-of-hospital cardiac arrest transported to tertiary emergency medical institutions in Osaka, Japan

Increasing neurologically intact survival after out-of-hospital cardiac arrest among elderly: Singapore Experience

Objectives

With more elderly presenting with Out-of-Hospital Cardiac Arrests (OHCAs) globally, neurologically intact survival (NIS) should be the aim of resuscitation. We aimed to study the trend of OHCA amongst elderly in a large Asian registry to identify if age is independently associated with NIS and factors associated with NIS.

Methods

All adult OHCAs aged ≥18 years attended by emergency medical services (EMS) from April 2010 to December 2019 in Singapore was extracted from the Pan-Asian Resuscitation Outcomes Study (PAROS) registry. Cases pronounced dead at scene, non-EMS transported, traumatic OHCAs and OHCAs in ambulances were excluded. Patient characteristics and outcomes were compared across four age categories (18-64, 65-79, 80-89, ≥90). Multivariable logistic regression analysis determined the factors associated with NIS.

Results

19,519 eligible cases were analyzed. OHCA incidence increased with age almost doubling in octogenarians (from 312/100,000 in 2011 to 652/100,000 in 2019) and tripling in those ≥90 years (from 458/100,000 in 2011 to 1271/100,000 in 2019). The proportion of patients with NIS improved over time for the 18-64, 65-79- and 80-89-years age groups, with the greatest improvement in the youngest group. NIS decreased with each increasing year of age and minute of response time. NIS increased in the arrests of presumed cardiac etiology, witnessed and bystander CPR.

Conclusions

Survival with good outcomes has increased even amongst the elderly. Regardless of age, NIS is possible with good-quality CPR, highlighting its importance. End-of-life planning is a complex yet necessary decision that requires qualitative exploration with elderly, their families and care providers.

Clustering out‐of‐hospital cardiac arrest patients with non‐shockable rhythm by machine learning latent class analysis

Aim

We aimed to identify subphenotypes among patients with out‐of‐hospital cardiac arrest (OHCA) with initial non‐shockable rhythm by applying machine learning latent class analysis and examining the associations between subphenotypes and neurological outcomes.

Methods

This study was a retrospective analysis within a multi‐institutional prospective observational cohort study of OHCA patients in Osaka, Japan (the CRITICAL study). The data of adult OHCA patients with medical causes and initial non‐shockable rhythm presenting with OHCA between 2012 and 2016 were included in machine learning latent class analysis models, which identified subphenotypes, and patients who presented in 2017 were included in a dataset validating the subphenotypes. We investigated associations between subphenotypes and 30‐day neurological outcomes.

Results

Among the 12,594 patients in the CRITICAL study database, 4,849 were included in the dataset used to classify subphenotypes (median age: 75 years, 60.2% male), and 1,465 were included in the validation dataset (median age: 76 years, 59.0% male). Latent class analysis identified four subphenotypes. Odds ratios and 95% confidence intervals for a favorable 30‐day neurological outcome among patients with these subphenotypes, using group 4 for comparison, were as follows; group 1, 0.01 (0.001–0.046); group 2, 0.097 (0.051–0.171); and group 3, 0.175 (0.073–0.358). Associations between subphenotypes and 30‐day neurological outcomes were validated using the validation dataset.

Conclusion

We identified four subphenotypes of OHCA patients with initial non‐shockable rhythm. These patient subgroups presented with different characteristics associated with 30‐day survival and neurological outcomes.

Clinical Phenotyping of Out-of-Hospital Cardiac Arrest Patients With Shockable Rhythm - Machine Learning-Based Unsupervised Cluster Analysis

BACKGROUND

The hypothesis of this study is that latent class analysis could identify the subphenotypes of out-of-hospital cardiac arrest (OHCA) patients associated with the outcomes and allow us to explore heterogeneity in the effects of extracorporeal cardiopulmonary resuscitation (ECPR).Methods and Results:This study was a retrospective analysis of a multicenter prospective observational study (CRITICAL study) of OHCA patients. It included adult OHCA patients with initial shockable rhythm. Patients from 2012 to 2016 (development dataset) were included in the latent class analysis, and those from 2017 (validation dataset) were included for evaluation. The association between subphenotypes and outcomes was investigated. Further, the heterogeneity of the association between ECPR implementation and outcomes was explored. In the study results, a total of 920 patients were included for latent class analysis. Three subphenotypes (Groups 1, 2, and 3) were identified, mainly characterized by the distribution of partial pressure of O₂(PO₂), partial pressure of CO₂(PCO₂) value of blood gas assessment, cardiac rhythm on hospital arrival, and estimated glomerular filtration rate. The 30-day survival outcomes were varied across the groups: 15.7% in Group 1; 30.7% in Group 2; and 85.9% in Group 3. Further, the association between ECPR and 30-day survival outcomes by subphenotype groups in the development dataset was as varied. These results were validated using the validation dataset.

CONCLUSIONS

The latent class analysis identified 3 subphenotypes with different survival outcomes and potential heterogeneity in the effects of ECPR.

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.