Mortality of Inherited Arrhythmia Syndromes Insight Into Their Natural History

Background-For most arrhythmia syndromes, the risk of sudden cardiac death for asymptomatic mutation carriers is ill defined. Data on the natural history of these diseases, therefore, are essential. The family tree mortality ratio method offers the unique possibility to study the natural history at a time when the disease was not known and patients received no treatment. Methods and Results-In 6 inherited arrhythmia syndromes caused by specific mutations, we analyzed all-cause mortality with the family tree mortality ratio method (main outcome measure, standardized mortality ratio [SMR]). In long-QT syndrome (LQTS) type 1, severely increased mortality risk during all years of childhood was observed (1-19 years), in particular during the first 10 years of life (SMR, 2.9; 95% CI, 1.5-5.1). In LQTS type 2, we observed increasing SMRs starting from age 15 years, which just reached significance between age 30 and 39 (SMR, 4.0; 95% CI, 1.1-10.0). In LQTS type 3, the SMR was increased between age 15 and 19 years (SMR, 5.8; 95% CI, 1.2-16.9). In the SCN5A overlap syndrome, excess mortality was observed between age 10 and 59 years, with a peak between 20 and 39 years (SMR, 3.8; 95% CI, 2.5-5.7). In catecholaminergic polymorphic ventricular tachycardia, excess mortality was restricted to ages 20 to 39 years (SMR, 3.0; 95% CI, 1.3-6.0). In Brugada syndrome, excess mortality was observed between age 40 and 59 (SMR, 1.79; 95% CI, 1.2-2.4), particularly in men. Conclusions-We identified age ranges during which the mortality risk manifests in an unselected and untreated population, which can guide screening in these families. (Circ Cardiovasc Genet. 2012;5:183-189.

Prevalence, pathophysiology, prediction and health-related quality of life of long COVID: study protocol of the longitudinal multiple cohort CORona Follow Up (CORFU) study

INTRODUCTION: The variety, time patterns and long-term prognosis of persistent COVID-19 symptoms (long COVID-19) in patients who suffered from mild to severe acute COVID-19 are incompletely understood. Cohort studies will be combined to describe the prevalence of long COVID-19 symptoms, and to explore the pathophysiological mechanisms and impact on health-related quality of life. A prediction model for long COVID-19 will be developed and internally validated to guide care in future patients. METHODS AND ANALYSIS: Data from seven COVID-19 cohorts will be aggregated in the longitudinal multiple cohort CORona Follow Up (CORFU) study. CORFU includes Dutch patients who suffered from COVID-19 at home, were hospitalised without or with intensive care unit treatment, needed inpatient or outpatient rehabilitation and controls who did not suffer from COVID-19. Individual cohort study designs were aligned and follow-up has been synchronised. Cohort participants will be followed up for a maximum of 24 months after acute infection. Next to the clinical characteristics measured in individual cohorts, the CORFU questionnaire on long COVID-19 outcomes and determinants will be administered digitally at 3, 6, 12, 18 and 24 months after the infection. The primary outcome is the prevalence of long COVID-19 symptoms up to 2 years after acute infection. Secondary outcomes are health-related quality of life (eg, EQ-5D), physical functioning, and the prevalence of thromboembolic complications, respiratory complications, cardiovascular diseases and endothelial dysfunction. A prediction model and a patient platform prototype will be developed. ETHICS AND DISSEMINATION: Approval was obtained from the medical research ethics committee of Maastricht University Medical Center+ and Maastricht University (METC 2021-2990) and local committees of the participating cohorts. The project is supported by ZonMW and EuroQol Research Foundation. Results will be published in open access peer-reviewed scientific journals and presented at (inter)national conferences. TRIAL REGISTRATION NUMBER: NCT05240742

Prevalence, pathophysiology, prediction and health-related quality of life of long COVID:study protocol of the longitudinal multiple cohort CORona Follow Up (CORFU) study

INTRODUCTION: The variety, time patterns and long-term prognosis of persistent COVID-19 symptoms (long COVID-19) in patients who suffered from mild to severe acute COVID-19 are incompletely understood. Cohort studies will be combined to describe the prevalence of long COVID-19 symptoms, and to explore the pathophysiological mechanisms and impact on health-related quality of life. A prediction model for long COVID-19 will be developed and internally validated to guide care in future patients. METHODS AND ANALYSIS: Data from seven COVID-19 cohorts will be aggregated in the longitudinal multiple cohort CORona Follow Up (CORFU) study. CORFU includes Dutch patients who suffered from COVID-19 at home, were hospitalised without or with intensive care unit treatment, needed inpatient or outpatient rehabilitation and controls who did not suffer from COVID-19. Individual cohort study designs were aligned and follow-up has been synchronised. Cohort participants will be followed up for a maximum of 24 months after acute infection. Next to the clinical characteristics measured in individual cohorts, the CORFU questionnaire on long COVID-19 outcomes and determinants will be administered digitally at 3, 6, 12, 18 and 24 months after the infection. The primary outcome is the prevalence of long COVID-19 symptoms up to 2 years after acute infection. Secondary outcomes are health-related quality of life (eg, EQ-5D), physical functioning, and the prevalence of thromboembolic complications, respiratory complications, cardiovascular diseases and endothelial dysfunction. A prediction model and a patient platform prototype will be developed. ETHICS AND DISSEMINATION: Approval was obtained from the medical research ethics committee of Maastricht University Medical Center+ and Maastricht University (METC 2021-2990) and local committees of the participating cohorts. The project is supported by ZonMW and EuroQol Research Foundation. Results will be published in open access peer-reviewed scientific journals and presented at (inter)national conferences. TRIAL REGISTRATION NUMBER: NCT05240742