Background There is currently limited evidence to guide prehospital identification of patients with cardiopulmonary arrest on arrival (CPAOA) to hospital who have potentially favourable neurological function. This study aimed to develop a simple scoring system that can be determined at the contact point with emergency medical services to predict neurological outcomes.
Methods We analysed data from patients with CPAOA using a regional Japanese database (SOS-KANTO), from January 2012 to March 2013. Patients were randomly assigned into derivation and validation cohorts. Favourable neurological outcomes were defined as cerebral performance category 1 or 2. We developed a new scoring system using logistic regression analysis with the following predictors: age, no-flow time, initial cardiac rhythm and arrest place. The model was internally validated by assessing discrimination and calibration.
Results Among 4907 patients in the derivation cohort and 4908 patients in the validation cohort, the probabilities of favourable outcome were 0.9% and 0.8%, respectively. In the derivation cohort, age ≤70 years (OR 5.11; 95% CI 2.35 to 11.14), no-flow time ≤5 min (OR 4.06; 95% CI 2.06 to 8.01) and ventricular tachycardia or fibrillation as initial cardiac rhythm (OR 6.66; 95% CI 3.45 to 12.88) were identified as predictors of favourable outcome. The ABC score consisting of Age, information from Bystander and Cardiogram was created. The areas under the receiver operating characteristic curves of this score were 0.863 in the derivation and 0.885 in the validation cohorts. Positive likelihood ratios were 6.15 and 6.39 in patients with scores >2 points and were 11.06 and 17.75 in those with 3 points.
Conclusion The ABC score showed good accuracy for predicting favourable neurological outcomes in patients with CPAOA. This simple scoring system could potentially be used to select patients for extracorporeal cardiopulmonary resuscitation and minimise low-flow time.
- clinical management
- clinical management
Data availability statement
Data are available on reasonable request. If you are a member of the Kanto Regional Chapter of the Japanese Society of Emergency Medicine and have a reasonable research plan, you can use the SOS-KANTO 2012 dataset. For more information, see the following URL: http: // jaam-kanto.umin.ne.jp / sos_kanto.html.
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