Impact of dual dispatch system implementation on response times and survival outcomes in out-of-hospital cardiac arrest in rural areas

Intervention Group ◽

First Responders ◽

Survival Outcomes ◽

Historical Group ◽

Objectives: Dual dispatch early defibrillation in out-of-hospital cardiac arrest (OHCA) victims provided by firefighters in addition to Emergency medical services (EMS) has proven to increase rate of return of spontaneous circulation (ROSC) and thus survival in the metropolitan or suburban areas whereas the data in rural areas are scarce. Methods: This was a retrospective observational cohort study of EMS resuscitated OHCA victims in regions with dual dispatch of volunteer firefighters as first responders (intervention group). Historical group was based on all OHCAs occurring in these regions before the implementation of first responders (EMS response only). Multivariate logistic regression with following variables: intervention, age, gender, witnessed status, bystander cardiopulmonary resuscitation (CPR), first rhythm and etiology were used to control for confounding factors affecting ROSC. Results: A total of 312 OHCAs were included in the study (historical group, n = 115 and intervention group, n = 197). Median time to arrival of first help shortened significantly for all patients, patients with ROSC and patients with Cerebral Performance Category 1/2 (CPC 1/2) in intervention vs historical group (8 vs 12 min, p < 0.001; 7.5 vs 11 min, p = 0.002; 7 vs 10 min, p = 0.011; respectively). The proportion of patients with ROSC, 30-day survival and CPC 1/2 at hospital discharge remained unchanged in intervention vs historical group (21% vs 23%, p = 0.808; 7% vs 6%, p = 0.914; 6% vs 3%, p = 0.442; respectively). The logistic regression model of adjustment confirms the absence of improvement in the ROSC rate after the implementation of first responders. Conclusions: Introduction of a dual dispatch of local first responders in addition to EMS in cases of OHCA significantly shortened response times. However, reduced response times were not associated with better survival outcomes.

Impact of dual dispatch system implementation on response times and survival outcomes in out-of-hospital cardiac arrest in rural areas

10.22514/0.22514/sv.2021.134 ◽

2021 ◽

Keyword(s):

Logistic Regression ◽

Cardiac Arrest ◽

Rural Areas ◽

Response Times ◽

Intervention Group ◽

First Responders ◽

Survival Outcomes ◽

Historical Group ◽

The Influence of COVID-19 on Out-Hospital Cardiac Arrest Survival Outcomes: An Updated Systematic Review and Meta-Analysis

Journal of Clinical Medicine ◽

10.3390/jcm10235573 ◽

2021 ◽

Vol 10 (23) ◽

pp. 5573

Author(s):

Karol Bielski ◽

Agnieszka Szarpak ◽

Miłosz Jaroslaw Jaguszewski ◽

Tomasz Kopiec ◽

Jacek Smereka ◽

...

Keyword(s):

Systematic Review ◽

Cardiac Arrest ◽

Hospital Discharge ◽

Meta Analysis ◽

Spontaneous Circulation ◽

Survival Outcomes ◽

Cochrane Central Register ◽

Mortality And Morbidity ◽

Cardiopulmonary resuscitation in patients with out-of-hospital cardiac arrest (OHCA) is associated with poor prognosis. Because the COVID-19 pandemic may have impacted mortality and morbidity, both on an individual level and the health care system as a whole, our purpose was to determine rates of OHCA survival since the onset of the SARS-CoV2 pandemic. We conducted a systematic review and meta-analysis to evaluate the influence of COVID-19 on OHCA survival outcomes according to the PRISMA guidelines. We searched the literature using PubMed, Scopus, Web of Science and Cochrane Central Register for Controlled Trials databases from inception to September 2021 and identified 1775 potentially relevant studies, of which thirty-one articles totaling 88,188 patients were included in this meta-analysis. Prehospital return of spontaneous circulation (ROSC) in pre-COVID-19 and COVID-19 periods was 12.3% vs. 8.9%, respectively (OR = 1.40; 95%CI: 1.06–1.87; p < 0.001). Survival to hospital discharge in pre- vs. intra-COVID-19 periods was 11.5% vs. 8.2% (OR = 1.57; 95%CI: 1.37–1.79; p < 0.001). A similar dependency was observed in the case of survival to hospital discharge with the Cerebral Performance Category (CPC) 1–2 (6.7% vs. 4.0%; OR = 1.71; 95%CI: 1.35–2.15; p < 0.001), as well as in the 30-day survival rate (9.2% vs. 6.4%; OR = 1.63; 95%CI: 1.13–2.36; p = 0.009). In conclusion, prognosis of OHCA is usually poor and even worse during COVID-19.

Abstract 256: Outcome Prediction of Out of Hospital Cardiac Arrest with Environmental Information Using Machine Learning

Circulation ◽

10.1161/circ.142.suppl_4.256 ◽

2020 ◽

Vol 142 (Suppl_4) ◽

Author(s):

Samuel Harford ◽

Houshang Darabi ◽

Sara Heinert ◽

Marina Del Rios ◽

Keyword(s):

Machine Learning ◽

Cardiac Arrest ◽

Low Income ◽

Predictive Accuracy ◽

Survival Outcomes ◽

Convolutional Network ◽

Healthcare Facilities ◽

Neurologic Outcomes ◽

Background: The lethality of out-of-hospital cardiac arrest (OHCA) among minority and low income patients in large urban centers has been extensively described. Neighborhood disparities in OHCA survival outcomes cannot be fully explained by clinical variables alone. Machine Learning (ML) is a sub-field of Artificial Intelligence where algorithms can learn and improve themselves by studying high volumes of data and evaluating interactions that affect OHCA. We sought to determine whether incorporating neighborhood variables into a ML model of OHCA can increase its predictive accuracy of survival outcomes. Methods: Using OHCA data from the Cardiac Arrest Registry to Enhance Survival (CARES) database, we geocoded Chicago incidents that occurred outside of healthcare facilities and nursing homes from 2014 - 2019 into the 77 Chicago community areas. Neighborhood characteristics (e.g., access to healthcare, educational attainment, crime rates) were assigned to OHCA cases based on community area using publicly available data from the Chicago Health Atlas (CHA). The merged CARES and CHA data were used to train, validate, test, and analyze ML models for OHCA survival outcomes, defined as a binary outcome based on Cerebral Performance Category or CPC (Good = CPC 1 or 2; Poor=CPC 3, 4, or 5). ML models including deep neural networks were developed and compared using average class sensitivity to models developed using only CARES data. Results: ML algorithms were tested on 9,595 cases of OHCA. Baseline results using only CARES data on the Embedded Fully Convolutional Network (EFCN) show an average class sensitivity of 84%. Including neighborhood variables from the CHA dataset increased the average class sensitivity of the EFCN model to 86.5-86.9%. Conclusion: The use of neighborhood variables in combination with CARES data can predict neurologic outcomes with a higher level of accuracy than using CARES registry data alone. Future studies will use this newly developed model to perform simulation experiments to identify neighborhood level interventions to improve OHCA survival outcomes.

Abstract 149: Annual and Lifetime Economic Productivity Loss Due to Adult Out-of-hospital Cardiac Arrest in the United States

Circulation ◽

10.1161/circ.142.suppl_4.149 ◽

2020 ◽

Vol 142 (Suppl_4) ◽

Author(s):

Ryan A Coute ◽

Brian Nathanson ◽

Timothy J Mader ◽

Bryan F McNally ◽

Michael C Kurz

Keyword(s):

United States ◽

Cardiac Arrest ◽

Productivity Loss ◽

The United States ◽

Sensitivity Analyses ◽

Survival Outcomes ◽

Economic Productivity ◽

Productivity Losses ◽

Objective: To estimate the annual and lifetime economic productivity loss due to adult out-of-hospital cardiac arrest (OHCA) in the United States (U.S.) over a 5-year study period between 2013-2018. Methods: All adult (age≥ 18 years) non-traumatic EMS-treated OHCA with complete data for age, sex, race, and survival outcomes from the CARES database for the most recently available 5-year period were included. Annual and lifetime labor productivity values, based on age and gender, were obtained from previously published national economic data. Productivity losses for OHCA events were calculated by year. Productivity losses for survivors were assigned by cerebral performance category score (CPC): CPC 1 and 2 = 0% productivity loss; CPC 3-5 = 100% productivity loss. Sensitivity analyses were performed assigning CPC 2 varying productivity losses (0-100%). Lifetime productivity values assumed 1% annual growth and 3% discount rate. Productivity data are presented in U.S. dollars and adjusted for inflation based on 2016 values. Results were extrapolated to the annual U.S. population. Results: A total of 338,492 (96.5%) cases met inclusion criteria. The mean annual and lifetime productivity losses per OHCA in 2018 were $48,224 and $638,947 respectively. Total annual and lifetime productivity losses for the study population in 2018 were $3.8 billion and $50.6 billion, respectively. Sensitivity analyses assigning CPC 2 varying productivity losses yielded similar findings. Males had a much larger lifetime productivity loss to approximately age 65 years compared to females (FIGURE 1). For the U.S. population in 2018, the total annual and lifetime productivity losses due to OHCA were $11.3 billion and $150.2 billion, respectively. Conclusion: Adult non-traumatic OHCA events are associated with significant annual and lifetime economic productivity losses and should be the focus of public health resources to improve preventative measures and survival outcomes.

Abstract 415: Underlying Liver Disease and Survival Outcomes in Out-Of-Hospital Cardiac Arrest

Circulation ◽

10.1161/circ.140.suppl_2.415 ◽

2019 ◽

Vol 140 (Suppl_2) ◽

Author(s):

Jieun Pak ◽

Ki Hong Kim ◽

Jong Hwan Kim ◽

Sun Young Lee ◽

Ki Jeong Hong ◽

...

Keyword(s):

Cardiac Arrest ◽

Liver Disease ◽

Neurological Recovery ◽

Secondary Outcome ◽

Survival Outcomes ◽

Cross Sectional ◽

Underlying Liver Disease ◽

Significant Difference ◽

Introduction: It is unclear whether underlying liver disease can affect survival outcomes of out-of-hospital cardiac arrest (OHCA) patients. This study aims to evaluate the association between underlying liver disease and survival outcomes of OHCA patients. Methods: This study was a cross-sectional study using a nationwide OHCA registry in Korea. Adult OHCA patients with presumed cardiac etiology from 2013 to 2015 were included. The main exposure was underlying liver disease which was identified from medical record review. We categorized patients into 3 groups: chronic liver disease (CLD) with cirrhosis, CLD without cirrhosis and no CLD group. The primary outcome was discharge with good neurological recovery (cerebral performance category 1 or 2) and the secondary outcome was survival to discharge. Multivariable logistic regression was performed to calculate odds ratios (OR) with 95% confidence intervals (CIs) after adjusting for potential confounders. Results: A total of 8,844 patients, 1,323 (15%) patients had CLD with cirrhosis and 361 (4.1%) patients had CLD without cirrhosis. Good neurological recovery rate was 0.6% in CLD with cirrhosis group, 8.9% in CLD without cirrhosis group and 8.7% in no CLD group (P<0.0001). Compared to no CLD group, CLD with cirrhosis group was less likely to have favorable outcomes (adjusted OR [95% CI]: 0.28 [0.13-0.62] for good neurological recovery and 0.35 [0.21-0.59] for survival to discharge). There was no significant difference in favorable outcomes between no CLD group and CLD without cirrhosis group (adjusted OR [95% CI]: 1.64 [0.92-2.92] for good neurological recovery and 1.38 [0.87-2.19] for survival to discharge). Conclusion: Underlying CLD was associated with survival outcomes of OHCA patients. CLD with cirrhosis was associated with poor neurological recovery for OHCA patients.

Benefits of adding a physician-staffed ambulance to bystander-witnessed out-of-hospital cardiac arrest: a community-based, observational study in Niigata, Japan

BMJ Open ◽

10.1136/bmjopen-2019-032967 ◽

2019 ◽

Vol 9 (11) ◽

pp. e032967 ◽

Cited By ~ 2

Author(s):

Nobuhiro Sato ◽

Tasuku Matsuyama ◽

Kohei Akazawa ◽

Kyoko Nakazawa ◽

Yasuo Hirose

Keyword(s):

Logistic Regression ◽

Cardiac Arrest ◽

Neurological Outcome ◽

Population Based ◽

Secondary Outcome ◽

Community Based ◽

Neurological Outcomes ◽

Urban City ◽

ObjectiveThis study aimed to assess the benefits of adding a physician-staffed ambulance to bystander-witnessed out-of-hospital cardiac arrest using a community-based registry.DesignPopulation-based, retrospective cohort study.SettingAn urban city with approximately 800 000 residents.ParticipantsPatients aged ≥18 years with bystander-witnessed out-of-hospital cardiac arrests of medical aetiology in Niigata City, Japan, between January 2012 and December 2016, according to the Utstein style.Primary and secondary outcome measuresThe primary outcome was 1-month survival with a favourable neurological outcome, defined as a cerebral performance category score of 1 or 2. We used logistic regression analysis to assess the association between favourable neurological outcome and prehospital physician involvement.ResultsDuring the study period, a total of 4172 cardiac arrests were registered; of these, 892 patients with out-of-hospital cardiac arrest were eligible for this analysis, among whom 135 (15.1%) had prehospital physician involvement and 757 (84.9%) did not have prehospital physician involvement. The percentage of favourable neurological outcomes was 20.7% (28 of 135) in those with physician involvement and 10.4% (79 of 757) in those without physician involvement (p=0.001). Using multivariable logistic regression, prehospital physician involvement had an OR for a favourable neurological outcome of 3.44 (95% CI 1.64 to 7.23).ConclusionsAmong adults with out-of-hospital cardiac arrest, adding a physician-staffed ambulance was associated with significantly greater favourable neurological outcomes than standard emergency medical services.

Mechanical circulatory support for refractory out-of-hospital cardiac arrest: a Danish nationwide multicenter study

Critical Care ◽

10.1186/s13054-021-03606-5 ◽

2021 ◽

Vol 25 (1) ◽

Author(s):

Sivagowry Rasalingam Mørk ◽

Carsten Stengaard ◽

Louise Linde ◽

Jacob Eifer Møller ◽

Lisette Okkels Jensen ◽

...

Keyword(s):

Logistic Regression ◽

Cardiac Arrest ◽

Survival Rate ◽

Neurological Outcome ◽

Mechanical Circulatory Support ◽

Circulatory Support ◽

Good Neurological Outcome ◽

Factors Associated ◽

National Consensus ◽

Abstract Background Mechanical circulatory support (MCS) with either extracorporeal membrane oxygenation or Impella has shown potential as a salvage therapy for patients with refractory out-of-hospital cardiac arrest (OHCA). The objective of this study was to describe the gradual implementation, survival and adherence to the national consensus with respect to use of MCS for OHCA in Denmark, and to identify factors associated with outcome. Methods This retrospective, observational cohort study included patients receiving MCS for OHCA at all tertiary cardiac arrest centers (n = 4) in Denmark between July 2011 and December 2020. Logistic regression and Kaplan–Meier survival analysis were used to determine association with outcome. Outcome was presented as survival to hospital discharge with good neurological outcome, 30-day survival and predictors of 30-day mortality. Results A total of 259 patients were included in the study. Thirty-day survival was 26%. Sixty-five (25%) survived to hospital discharge and a good neurological outcome (Glasgow–Pittsburgh Cerebral Performance Categories 1–2) was observed in 94% of these patients. Strict adherence to the national consensus showed a 30-day survival rate of 30% compared with 22% in patients violating one or more criteria. Adding criteria to the national consensus such as signs of life during cardiopulmonary resuscitation (CPR), pre-hospital low-flow < 100 min, pH > 6.8 and lactate < 15 mmol/L increased the survival rate to 48%, but would exclude 58% of the survivors from the current cohort. Logistic regression identified asystole (RR 1.36, 95% CI 1.18–1.57), pulseless electrical activity (RR 1.20, 95% CI 1.03–1.41), initial pH < 6.8 (RR 1.28, 95% CI 1.12–1.46) and lactate levels > 15 mmol/L (RR 1.16, 95% CI 1.16–1.53) as factors associated with increased risk of 30-day mortality. Patients presenting signs of life during CPR had reduced risk of 30-day mortality (RR 0.63, 95% CI 0.52–0.76). Conclusions A high survival rate with a good neurological outcome was observed in this Danish population of patients treated with MCS for OHCA. Stringent patient selection for MCS may produce higher survival rates but potentially withholds life-saving treatment in a significant proportion of survivors.

Growth differentiation factor 15 and early prognosis after out-of-hospital cardiac arrest

Annals of Intensive Care ◽

10.1186/s13613-019-0593-9 ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 1

Author(s):

Ferran Rueda ◽

Germán Cediel ◽

Cosme García-García ◽

Júlia Aranyó ◽

Marta González-Lopera ◽

...

Keyword(s):

Cardiac Arrest ◽

Tissue Injury ◽

Neurologic Outcome ◽

Home Setting ◽

Growth Differentiation Factor 15 ◽

Poor Outcome ◽

Differentiation Factor ◽

Hospital Cardiac Arrest ◽

Early Predictor

Abstract Background Growth differentiation factor 15 (GDF-15) is an inflammatory cytokine released in response to tissue injury. It has prognostic value in cardiovascular diseases and other acute and chronic conditions. Here, we explored the value of GDF-15 as an early predictor of neurologic outcome after an out-of-hospital cardiac arrest (OHCA). Methods Prospective registry study of patients in coma after an OHCA, admitted in the intensive cardiac care unit from a single university center. Serum levels of GDF-15 were measured on admission. Neurologic status was evaluated according to the cerebral performance category (CPC) scale. The relationship between GDF-15 levels and poor neurologic outcome at 6 months was analyzed. Results Among 62 patients included, 32 (51.6%) presented poor outcome (CPC 3–5). Patients with CPC 3–5 exhibited significantly higher GDF-15 levels (median, 17.1 [IQR, 11.1–20.4] ng/mL) compared to those with CPC 1–2 (7.6 [IQR, 4.1–13.1] ng/mL; p = 0.004). Multivariable logistic regression analyses showed that age (OR, 1.09; 95% CI 1.01–1.17; p = 0.020), home setting arrest (OR, 8.07; 95% CI 1.61–40.42; p = 0.011), no bystander cardiopulmonary resuscitation (OR, 7.91; 95% CI 1.84–34.01; p = 0.005), and GDF-15 levels (OR, 3.74; 95% CI 1.32–10.60; p = 0.013) were independent predictors of poor outcome. The addition of GDF-15 in a dichotomous manner (≥ 10.8 vs. < 10.8 ng/mL) to the resulting clinical model improved discrimination; it increased the area under the curve from 0.867 to 0.917, and the associated continuous net reclassification improvement was 0.90 (95% CI 0.48–1.44), which allowed reclassification of 37.1% of patients. Conclusions After an OHCA, increased GDF-15 levels were an independent, early predictor of poor neurologic outcome. Furthermore, when added to the most common clinical factors, GDF-15 improved discrimination and allowed patient reclassification.

Predictive Value of Estimated Lean Body Mass for Neurological Outcomes after Out-of-Hospital Cardiac Arrest

Journal of Clinical Medicine ◽

10.3390/jcm10010071 ◽

2020 ◽

Vol 10 (1) ◽

pp. 71

Author(s):

Sung Eun Lee ◽

Hyuk Hoon Kim ◽

Minjung Kathy Chae ◽

Eun Jung Park ◽

Sangchun Choi

Keyword(s):

Cardiac Arrest ◽

Critically Ill ◽

Lean Body Mass ◽

Body Mass ◽

Multivariate Regression ◽

Characteristic Curve ◽

High Body Mass Index ◽

Neurological Outcomes ◽

Background: Postcardiac arrest patients with a return of spontaneous circulation (ROSC) are critically ill, and high body mass index (BMI) is ascertained to be associated with good prognosis in patients with a critically ill condition. However, the exact mechanism has been unknown. To assess the effectiveness of skeletal muscles in reducing neuronal injury after the initial damage owing to cardiac arrest, we investigated the relationship between estimated lean body mass (LBM) and the prognosis of postcardiac arrest patients. Methods: This retrospective cohort study included adult patients with ROSC after out-of-hospital cardiac arrest from January 2015 to March 2020. The enrolled patients were allocated into good- and poor-outcome groups (cerebral performance category (CPC) scores 1–2 and 3–5, respectively). Estimated LBM was categorized into quartiles. Multivariate regression models were used to evaluate the association between LBM and a good CPC score. The area under the receiver operating characteristic curve (AUROC) was assessed. Results: In total, 155 patients were analyzed (CPC score 1–2 vs. 3–5, n = 70 vs. n = 85). Patients’ age, first monitored rhythm, no-flow time, presumed cause of arrest, BMI, and LBM were different (p < 0.05). Fourth-quartile LBM (≥48.98 kg) was associated with good neurological outcome of postcardiac arrest patients (odds ratio = 4.81, 95% confidence interval (CI), 1.10–25.55, p = 0.04). Initial high LBM was also a predictor of good neurological outcomes (AUROC of multivariate regression model including LBM: 0.918). Conclusions: Initial LBM above 48.98kg is a feasible prognostic factor for good neurological outcomes in postcardiac arrest patients.