Comorbidities prior to out-of-hospital cardiac arrest and diagnoses at discharge among survivors.

BACKGROUND: Out-of-hospital cardiac arrest (OHCA) has a dismal prognosis with overall survival around 10%. Previous studies have shown conflicting results regarding the prevalence and significance of comorbidities in OHCA, as well as the underlying causes. Previously, 80% of sudden cardiac arrest have been attributed to coronary artery disease. We studied comorbidities and discharge diagnoses in OHCA in all of Sweden. METHODS: We used the Swedish Registry of Cardiopulmonary Resuscitation, merged with the Inpatient Registry and Outpatient Registry to identify patients with OHCA from 2010 to 2020 and to collect all their comorbidities as well as discharge diagnoses (among those admitted to hospital). Patient characteristics were described using means, medians and SD. Survival curves were performed among hospitalised patients with acute myocardial infarction (AMI) as well as heart failure. RESULTS: A total of 54 484 patients with OHCA were included, of whom 35 894 (66%) were men. The most common comorbidities prior to OHCA were hypertension (43.6%), heart failure (23.6%), chronic ischaemic heart disease (23.6%) and atrial fibrillation (22.0%). Previous AMI was prevalent in 14.8% of men and 10.9% of women. Among women, 18.0% had type 2 diabetes, compared with 19.6% of the men. Among hospitalised patients, 30% were diagnosed with AMI, 27% with hypertension, 20% with ischaemic heart disease and 18% with heart failure as discharge diagnoses. CONCLUSION: In summary, we find evidence that nowadays a minority of cardiac arrests are due to coronary artery disease and AMIs and its complications. Only 30% of all cases of OHCA admitted to hospital were diagnosed with AMI. Coronary artery disease is now likely in the minority with regard to causes of OHCA.

Association between exercise load, resting heart rate, and maximum heart rate and risk of future ST-segment elevation myocardial infarction (STEMI).

OBJECTIVE: This study aimed to examine the association between exercise workload, resting heart rate (RHR), maximum heart rate and the risk of developing ST-segment elevation myocardial infarction (STEMI). METHODS: The study included all participants from the UK Biobank who had undergone submaximal exercise stress testing. Patients with a history of STEMI were excluded. The allowed exercise load for each participant was calculated based on clinical characteristics and risk categories. We studied the participants who exercised to reach 50% or 35% of their expected maximum exercise tolerance. STEMI was adjudicated by the UK Biobank. We used Cox regression analysis to study how exercise tolerance and RHR were related to the risk of STEMI. RESULTS: A total of 66 949 participants were studied, of whom 274 developed STEMI during a median follow-up of 7.7 years. After adjusting for age, sex, blood pressure, smoking, forced vital capacity, forced expiratory volume in 1 s, peak expiratory flow and diabetes, we noted a significant association between RHR and the risk of STEMI (p=0.015). The HR for STEMI in the highest RHR quartile (>90 beats/min) compared with that in the lowest quartile was 2.92 (95% CI 1.26 to 6.77). Neither the maximum achieved exercise load nor the ratio of the maximum heart rate to the maximum load was significantly associated with the risk of STEMI. However, a non-significant but stepwise inverse association was noted between the maximum load and the risk of STEMI. CONCLUSION: RHR is an independent predictor of future STEMI. An RHR of >90 beats/min is associated with an almost threefold increase in the risk of STEMI.

Predicting recurrent cardiac arrest in individuals surviving Out-of-Hospital cardiac arrest.

BACKGROUND: Despite improvements in short-term survival for Out-of-Hospital Cardiac Arrest (OHCA) in the past two decades, long-term survival is still not well studied. Furthermore, the contribution of different variables on long-term survival have not been fully investigated. AIM: Examine the 1-year prognosis of patients discharged from hospital after an OHCA. Furthermore, identify factors predicting re-arrest and/or death during 1-year follow-up. METHODS: All patients 18 years or older surviving an OHCA and discharged from the hospital were identified from the Swedish Register for Cardiopulmonary Resuscitation (SRCR). Data on diagnoses, medications and socioeconomic factors was gathered from other Swedish registers. A machine learning model was constructed with 886 variables and evaluated for its predictive capabilities. Variable importance was gathered from the model and new models with the most important variables were created. RESULTS: Out of the 5098 patients included, 902 (∼18%) suffered a recurrent cardiac arrest or death within a year. For the outcome death or re-arrest within 1 year from discharge the model achieved an ROC (receiver operating characteristics) AUC (area under the curve) of 0.73. A model with the 15 most important variables achieved an AUC of 0.69. CONCLUSIONS: 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.