Predictive Model of Good Clinical Outcomes in Patients Undergoing Coronary Angiography after Out-of-Hospital Cardiac Arrest: A Prospective, Multicenter Observational Study Conducted by the Korean Cardiac Arrest Research Consortium

Author:

Beom Jin,Park IncheolORCID,You Je,Roh Yun,Kim MinORCID,Park YooORCID,

Abstract

This observational study aimed to develop novel nomograms that predict the benefits of coronary angiography (CAG) after resuscitating patients with out-of-hospital cardiac arrest (OHCA) regardless of the electrocardiography findings and to perform an external validation of these models. Data were extracted from a prospective, multicenter registry of resuscitated patients with OHCA (October 2015–June 2018). New nomograms were developed based on variables associated with survival discharge and neurologic outcomes; their analysis included 723 and 709 patients, respectively. Patient age (p < 0.001), prehospital defibrillation by emergency medical technicians (EMTs) (p = 0.003), prehospital return of spontaneous circulation (ROSC) (p = 0.02), and time from collapse to ROSC (p < 0.001) were associated with survival discharge. Patient age (p < 0.001), prehospital defibrillation by EMTs (p < 0.001), and time from collapse to ROSC (p < 0.001) were associated with neurologic outcomes. The new nomogram had a good predictive performance, with an area under the curve (AUC) of 0.8832 (95% confidence interval (CI): 0.8358–0.9305) for survival discharge and an AUC of 0.9048 (95% CI: 0.8627–0.9469) for neurologic outcomes. Novel nomograms that predict survival discharge and good neurological outcomes after CAG in patients with OHCA were developed and validated; they can be quickly and easily applied to identify patients who will benefit from CAG.

Publisher

MDPI AG

Subject

General Medicine

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