Association Between Postresuscitation 12-Lead ECG Features and Early Mortality After Out-of-Hospital Cardiac Arrest: A Post Hoc Subanalysis of the PEACE Study.
Francesca Romana GentileEnrico BaldiCatherine KlersySebastian SchnaubeltMaria Luce CaputoChristian ClodiJolie BrunoSara CompagnoniAlessandro FasolinoClaudio BenvenutiHans DomanovitsRoman BurkartRoberto PrimiGerhard RuzickaMichael HolzerAngelo AuricchioSimone SavastanoPublished in: Journal of the American Heart Association (2023)
Background Once the return of spontaneous circulation after out-of-hospital cardiac arrest is achieved, a 12-lead ECG is strongly recommended to identify candidates for urgent coronary angiography. ECG has no apparent role in mortality risk stratification. We aimed to assess whether ECG features could be associated with 30-day survival in patients with out-of-hospital cardiac arrest. Methods and Results All the post-return of spontaneous circulation ECGs from January 2015 to December 2018 in 3 European centers (Pavia, Lugano, and Vienna) were collected. Prehospital data were collected according to the Utstein style. A total of 370 ECGs were collected: 287 men (77.6%) with a median age of 62 years (interquartile range, 53-70 years). After correction for the return of spontaneous circulation-to-ECG time, age >62 years (hazard ratio [HR], 1.78 [95% CI, 1.21-2.61]; P =0.003), female sex (HR, 1.5 [95% CI, 1.05-2.13]; P =0.025), QRS wider than 120 ms (HR, 1.64 [95% CI, 1.43-1.87]; P <0.001), the presence of a Brugada pattern (HR, 1.49 [95% CI, 1.39-1.59]; P <0.001), and the presence of ST-segment elevation in >1 segment (HR, 1.75 [95% CI, 1.59-1.93]; P <0.001) were independently associated with 30-day mortality. A score ranging from 0 to 26 was created, and by dividing the population into 3 tertiles, 3 classes of risk were found with significantly different survival rate at 30 days (score 0-4, 73%; score 5-7, 66%; score 8-26, 45%). Conclusions The post-return of spontaneous circulation ECG can identify patients who are at high risk of mortality after out-of-hospital cardiac arrest earlier than other forms of prognostication. This provides important risk stratification possibilities in postcardiac arrest care that could help to direct treatments and improve outcomes in patients with out-of-hospital cardiac arrest.
Keyphrases
- heart rate variability
- heart rate
- healthcare
- magnetic resonance imaging
- palliative care
- free survival
- cardiac arrest
- mass spectrometry
- adipose tissue
- coronary artery disease
- blood pressure
- ejection fraction
- magnetic resonance
- machine learning
- heart failure
- electronic health record
- metabolic syndrome
- cardiovascular disease
- cardiac resynchronization therapy
- ms ms
- cell proliferation
- contrast enhanced
- artificial intelligence