Periodic Reporting for period 2 - SAECG (Prediction of AF incidence using PR interval measurements, echocardiographic data and biomarker profiles: Analyses within epidemiological Framingham Heart Study and LIFE Health Care Study cohorts)
Periodo di rendicontazione: 2021-09-01 al 2022-08-31
• What is the problem/issue being addressed?
During the outgoing phase at Boston University, I worked on the project analyzing P-wave signal averaged ECG (P-SAECG) in Framingham Heart Study (FHS). FHS is the one of the most famous and important epidemiological cohorts with a very long follow-up period allowing to analyze risk factors, prediction of cardiovascular outcomes during a long period of time. The main aim of my project was to analyze the role of P-SAECG – a noninvasive, high fidelity measurement of atrial electric function – in FHS. Up to date, the P-SAECG had been analyzed in relatively small cohorts and showed discrepant results. Thus, P-SAECG analysis in one of the largest epidemiological cohorts – Framingham Heart Study – was an excellent opportunity to report reference values, association with clinical factors, and heritability. The next step which we are going to address is to assess the role of P-SAECGs predicting adverse clinical outcomes – incident AF and stroke.
• Why is it important for society?
With increased average global life expectancy and longer survival with chronic conditions, incidence and prevalence of atrial fibrillation (AF) has reached the dimension of a 21st century cardiovascular disease (CVD) epidemic. Despite multifaceted research efforts, the prevention of AF and its related complications remains challenging. The ECG is a widely available tool to analyze cardiac electrical activity. While the 12-lead resting ECGs are mostly used in clinical routine, the P-SAECG is considered as a more precise and advanced measure. Due to its association with severe adverse events – such as thromboembolic complications (e.g. stroke), heart failure, dementia, and death – it is crucial to predict AF and implement individualized risk management and treatment – especially in individuals at risk. Therefore, P-SAECG might represent a unique non-invasive diagnostic tool for prediction of AF and related adverse outcomes.
• What are the overall objectives?
The overall objective of analysis performed could be divided in two phases. During the first phase, the objective was to analyze P-SAECG reference values and association with clinical factors as well as heritability of different P-SAECG traits. The second phase is aimed to assess relation between P-SAECG with incident AF and stroke.
Although the implementation of the action has been hindered by COVID, the scientific goals have been achieved to a wide extent. The action had a positive impact on my career development and helped me to get my current position as an internetionally recognized researcher involved in large epidemiologic studies in US (Boston University) and EU (Netherlands, Groningen University).
During the outgoing phase at Boston University, I worked on the project analyzing P-wave signal averaged ECG (P-SAECG) in Framingham Heart Study (FHS). FHS is the one of the most famous and important epidemiological cohorts with a very long follow-up period allowing to analyze risk factors, prediction of cardiovascular outcomes during a long period of time. The main aim of my project was to analyze the role of P-SAECG – a noninvasive, high fidelity measurement of atrial electric function – in FHS. Up to date, the P-SAECG had been analyzed in relatively small cohorts and showed discrepant results. Thus, P-SAECG analysis in one of the largest epidemiological cohorts – Framingham Heart Study – was an excellent opportunity to report reference values, association with clinical factors, and heritability. The next step which we are going to address is to assess the role of P-SAECGs predicting adverse clinical outcomes – incident AF and stroke.
• Why is it important for society?
With increased average global life expectancy and longer survival with chronic conditions, incidence and prevalence of atrial fibrillation (AF) has reached the dimension of a 21st century cardiovascular disease (CVD) epidemic. Despite multifaceted research efforts, the prevention of AF and its related complications remains challenging. The ECG is a widely available tool to analyze cardiac electrical activity. While the 12-lead resting ECGs are mostly used in clinical routine, the P-SAECG is considered as a more precise and advanced measure. Due to its association with severe adverse events – such as thromboembolic complications (e.g. stroke), heart failure, dementia, and death – it is crucial to predict AF and implement individualized risk management and treatment – especially in individuals at risk. Therefore, P-SAECG might represent a unique non-invasive diagnostic tool for prediction of AF and related adverse outcomes.
• What are the overall objectives?
The overall objective of analysis performed could be divided in two phases. During the first phase, the objective was to analyze P-SAECG reference values and association with clinical factors as well as heritability of different P-SAECG traits. The second phase is aimed to assess relation between P-SAECG with incident AF and stroke.
Although the implementation of the action has been hindered by COVID, the scientific goals have been achieved to a wide extent. The action had a positive impact on my career development and helped me to get my current position as an internetionally recognized researcher involved in large epidemiologic studies in US (Boston University) and EU (Netherlands, Groningen University).
2019:
I started the project with manual analysis and revision of available P-SAECG.
2019/20:
P-SAECG analysis Framingham Heart Study, data cleaning
2020:
After revision and data cleaning the statistical analyses were performed in June 2020. The results were summarized in a manuscript published at Heart Rhythm journal (https://doi.org/10.1016/j.hrthm.2021.05.009(si apre in una nuova finestra)) and presented as poster at ACC.21 scientific sessions. The project was also presented at national AF-SFRN fellowship.
2020:
Statistical analysis
2020:
Presentation of P-SAECG results during AF-SFRN fellowship conference
2021:
Poster presentation during ACC.21 (Atlanta, GA), Publication at Heart Rhythm (doi: 10.1016/j.hrthm.2021.05.009)
2022:
I continued clinical reviews at regular basis as a clinical reviewer at the Framingham Endpoint Review Committee
2022:
In July 2022 I participated in AHA Ten Day Seminar – an epidemiologic workshop with leading US epidemiologists in cardiovascular disease and prevention. The participation was a unique opportunity for me as a non-US researcher to join the epidemiologists’ community in US and build a network for my next career and research goals
2022:
In August 2022 I worked at Framingham Heart Study Research Center and analysed the raw data. In September and October I continued data analyses remotely.
I started the project with manual analysis and revision of available P-SAECG.
2019/20:
P-SAECG analysis Framingham Heart Study, data cleaning
2020:
After revision and data cleaning the statistical analyses were performed in June 2020. The results were summarized in a manuscript published at Heart Rhythm journal (https://doi.org/10.1016/j.hrthm.2021.05.009(si apre in una nuova finestra)) and presented as poster at ACC.21 scientific sessions. The project was also presented at national AF-SFRN fellowship.
2020:
Statistical analysis
2020:
Presentation of P-SAECG results during AF-SFRN fellowship conference
2021:
Poster presentation during ACC.21 (Atlanta, GA), Publication at Heart Rhythm (doi: 10.1016/j.hrthm.2021.05.009)
2022:
I continued clinical reviews at regular basis as a clinical reviewer at the Framingham Endpoint Review Committee
2022:
In July 2022 I participated in AHA Ten Day Seminar – an epidemiologic workshop with leading US epidemiologists in cardiovascular disease and prevention. The participation was a unique opportunity for me as a non-US researcher to join the epidemiologists’ community in US and build a network for my next career and research goals
2022:
In August 2022 I worked at Framingham Heart Study Research Center and analysed the raw data. In September and October I continued data analyses remotely.
• Preparation for the longitudinal analyses – Association between P wave SAECG and incident AF and stroke
This has been a crucial and very important task to learn more, whether P-SAECG is able to predict incident AF and related outcomes. If our hypothesis should be confirmed, the results would pave the way toward AF screening using P-SAECG, especially among individuals at risk for AF and its complications
• Proposal for P wave indices analysis at the Jackson Heart Study – Association with atrial cardiomyopathy and stroke
I have analyzed the ECGs in the Jackson Heart Study (JHS). JHS is a unique cohort, which includes individuals of African-American ancestry. The underrepresentation of non-White population in clinical and epidemiological studies is a known scientific issue. Therefore, the association between ECG traits and AF in African-Americans is understudied. So far, a biracial cohort in the Atherosclerosis Risk in Communities Study (ARIC) includes only 26% of African-Americans. Participation in ECG analysis in JHS cohort opens an opportunity to learn more about AF pathophysiology in African-Americans and compare the findings with other epidemiological cohorts.
This has been a crucial and very important task to learn more, whether P-SAECG is able to predict incident AF and related outcomes. If our hypothesis should be confirmed, the results would pave the way toward AF screening using P-SAECG, especially among individuals at risk for AF and its complications
• Proposal for P wave indices analysis at the Jackson Heart Study – Association with atrial cardiomyopathy and stroke
I have analyzed the ECGs in the Jackson Heart Study (JHS). JHS is a unique cohort, which includes individuals of African-American ancestry. The underrepresentation of non-White population in clinical and epidemiological studies is a known scientific issue. Therefore, the association between ECG traits and AF in African-Americans is understudied. So far, a biracial cohort in the Atherosclerosis Risk in Communities Study (ARIC) includes only 26% of African-Americans. Participation in ECG analysis in JHS cohort opens an opportunity to learn more about AF pathophysiology in African-Americans and compare the findings with other epidemiological cohorts.