Cardiac arrest & resuscitation
Predicting recurrent cardiac arrest in individuals surviving Out-of-Hospital cardiac arrest
Authors' conclusion
Survivors of an OHCA have a high risk of suffering a re-arrest or death within 1 year from hospital discharge. A machine learning model with 15 different variables, among which age, socioeconomic factors and neurofunctional status at hospital discharge, achieved almost the same predictive capabilities with reasonable precision as the full model with 886 variables.
Study context
- Population
- Patients ≥18 years surviving Out-of-Hospital Cardiac Arrest (OHCA) and discharged from hospital, Swedish Register for Cardiopulmonary Resuscitation
- Participants
- 5,098 patients
- Exposure
- Full model vs model with 15 most important variables
- Outcome
- Death or re-arrest
- Follow-up
- 1 year from discharge
Methodological detailsregistry-based, machine learning prediction model
- Registry-based
- Machine learning prediction model
Main finding
As reported in the abstract
Death or re-arrest within 1 year from discharge
Recurrent cardiac arrest or death within a year
902
∼18%
ROC AUC, ML model with 886 variables
0.73
AUC, model with the 15 most important variables
0.69
Observational data: associations, not effects.
Original publication
Predicting recurrent cardiac arrest in individuals surviving Out-of-Hospital cardiac arrest. Resuscitation. Published 26 December 2022. doi:10.
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