Reporting of data from out-of-hospital cardiac arrest has to involve emergency medical dispatching—Taking the recommendations on reporting OHCA the Utstein style a step further

Introduction: In-hospital early warning system scores for prediction of clinical deterioration have been well-developed. However, such prediction tools in prehospital setting remain unavailable. Hypothesis: To develop a model for predicting patients with emergency medical technicians witnessed out-of-hospital cardiac arrest (EMT-witnessed OHCA) . Methods: We used the fire-based emergency medical service (EMS) data from Taipei city to develop the prediction model. Patients included in this study were those initially alive, non-traumatic, and aged ≧20 years. Data were extracted from records of ambulance run sheets and OHCA registry in Taipei. The primary outcome (i.e. EMT-witnessed OHCA) was defined as cardiac arrest occurring during EMT services before arrival at the receiving hospital. The prediction model was developed through the standard cross-validation method (i.e. divided dataset for training group and validation group). Area under the receiver operating characteristic curve (AUC) and Hosmer-Lemeshow (HL) test were used to test discrimination and calibration. The point value system with Youden’s J Index was used to find the best cut-off value for practical application. Results: From 2011 to 2015, a total of 252,771 patients were included. Of them, 660 (0.26%) were EMT-witnessed OHCA. The prediction model, including gender, respiratory rate, heart rate, systolic blood pressure, level of consciousness and oxygen saturation, showed excellent discrimination (AUC 0.94) and calibration ( p =0.42 for HL test). When applied to the validation dataset, it maintained good discriminatory ability (AUC 0.94) and calibration ( p =0.11). The optimal cut-off value (≧13) of the point value system of the tool showed high sensitivity (87.84%) and specificity (86.20%). Conclusions: The newly developed prediction model will help identify high-risk patients with EMT-witnessed OHCA and indicate potential prevention by situation awareness in EMS.

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Abstract 01: Dispatching Lay Rescuers Through a Smartphone Application is Associated With Increased Bystander Defibrillation in Out-of-Hospital Cardiac Arrest

Circulation ◽

10.1161/circ.138.suppl_2.01 ◽

2018 ◽

Vol 138 (Suppl_2) ◽

Author(s):

Linn Andelius ◽

Carolina Malta Hansen ◽

Freddy Lippert ◽

Lena Karlsson ◽

Christian Torp-Pedersen ◽

...

Keyword(s):

Cardiac Arrest ◽

Smartphone Application ◽

Automated External Defibrillator ◽

Early Defibrillation ◽

Emergency Medical Dispatch ◽

Capital Region ◽

Electronic Survey ◽

Emergency Medical ◽

Hospital Cardiac Arrest ◽

External Defibrillator

Introduction: Survival after out-of-hospital cardiac arrest (OHCA) is dependent on early defibrillation. To increase bystander defibrillation in OHCAs, a first-responder program dispatching lay rescuers (Heart Runners) through a smartphone application (Heart Runner-app) was implemented in the Capital Region of Denmark. We investigated the proportion of Heart Runners arriving prior to the Emergency Medical Services (EMS) and rates of bystander defibrillation. Methods: The Capital Region of Denmark comprises 1.8 mil. inhabitants and 19,048 Heart Runners were registered. In cases of suspected OHCA, the Heart Runner-app was activated by the Emergency Medical Dispatch Center. Up to 20 Heart Runners < 1.8 km from the OHCA were dispatched to either start cardiopulmonary resuscitation (CPR) or to retrieve and use a publicly accessible automated external defibrillator (AED). Through an electronic survey, Heart Runners reported if they arrived before EMS and if they applied an AED. OHCAs where at least one Heart Runner arrived before EMS were compared with OHCAs where EMS arrived first. All OHCAs from September 2017 to May 2018, where Heart Runners had been dispatched, were included. Results: Of 399 EMS treated OHCAs, 78% (n=313/399) had a matching survey. A Heart Runner arrived before EMS in 47% (n=147/313) of the cases, and applied an AED in 41% (n=61/147) of these cases. Rate of bystander defibrillation was 2.5-fold higher compared to cases where the EMS arrived first (Table 1). Conclusions: By activation of the Heart Runner-app, Heart Runners arrived prior to EMS in nearly half of all the OHCA cases. Bystander defibrillation rate was significantly higher when Heart Runners arrived prior to EMS.

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Nineteen years’ experience of out-of-hospital cardiac arrest in Gothenburg—reported in Utstein style

Resuscitation ◽

10.1016/s0300-9572(03)00115-1 ◽

2003 ◽

Vol 58 (1) ◽

pp. 37-47 ◽

Cited By ~ 30

Author(s):

Martin Fredriksson ◽

Johan Herlitz ◽

J Engdahl

Keyword(s):

Cardiac Arrest ◽

Utstein Style ◽

Hospital Cardiac Arrest

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Bystander Cardiopulmonary Resuscitation Quality: Potential for Improvements in Cardiac Arrest Resuscitation

Journal of the American Heart Association ◽

10.1161/jaha.120.017930 ◽

2021 ◽

Author(s):

Richard Chocron ◽

Julia Jobe ◽

Sally Guan ◽

Madeleine Kim ◽

Mia Shigemura ◽

...

Keyword(s):

Cardiac Arrest ◽

Cardiopulmonary Resuscitation ◽

Performance Metrics ◽

Medical System ◽

Emergency Medical System ◽

Compression Rate ◽

Emergency Medical ◽

Bystander Cardiopulmonary Resuscitation ◽

Bystander Cpr ◽

Hospital Cardiac Arrest

Background Bystander cardiopulmonary resuscitation (CPR) is a critical intervention to improve survival following out‐of‐hospital cardiac arrest. We evaluated the quality of bystander CPR and whether performance varied according to the number of bystanders or provision of telecommunicator CPR (TCPR). Methods and Results We investigated non‐traumatic out‐of‐hospital cardiac arrest occurring in a large metropolitan emergency medical system during a 6‐month period. Information about bystander care was ascertained through review of the 9‐1‐1 recordings in addition to emergency medical system and hospital records to determine bystander CPR status (none versus TCPR versus unassisted), the number of bystanders on‐scene, and CPR performance metrics of compression fraction and compression rate. Of the 428 eligible out‐of‐hospital cardiac arrest, 76.4% received bystander CPR including 43.7% unassisted CPR and 56.3% TCPR; 35.2% had one bystander, 33.3% had 2 bystanders, and 31.5% had ≥3 bystanders. Overall compression fraction was 59% with a compression rate of 88 per minute. CPR differed according to TCPR status (fraction=52%, rate=87 per minute for TCPR versus fraction=69%, rate=102 for unassisted CPR, P <0.05 for each comparison) and the number of bystanders (fraction=55%, rate=87 per minute for 1 bystander, fraction=59%, rate=89 for 2 bystanders, fraction=65%, rate=97 for ≥3 bystanders, test for trend P <0.05 for each metric). Additional bystander actions were uncommon to include rotation of compressors (3.1%) or application of an automated external defibrillator (8.0%). Conclusions Bystander CPR quality as gauged by compression fraction and rate approached guideline goals though performance depended upon the type of CPR and number of bystanders.

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