Risk of Incident Heart Failure With Atrial Fibrillation
Risk of Incident Heart Failure With Atrial Fibrillation
The current study was performed in two cohorts of the Framingham Heart Study: the Original cohort enrolled in 1948 and Offspring cohort enrolled in the early 1970s. Individuals were eligible if they had AF diagnosed after 1960 and before 31 December 1999 (n = 1236). We excluded individuals for the following reasons: HF onset prior to AF (including first diagnosis of HF and AF on the same day, n = 58) or lack of follow-up (n = 295), HF onset within 30 days after first diagnosis of AF (n = 9), death within 30 days after AF onset (n = 99), or missing risk factor data (n = 108). We determined the incidence of HF over 10 years, up to 31 December 2009. The Boston University Medical Center Institutional Review Board approved all study protocols, and participants signed consent at every examination. All authors have read and agree to the manuscript as written.
Participants undergo standardized cardiovascular disease risk factor assessment at regular Framingham Heart Study clinic visits (biennial clinic visits for the Original cohort and every 4–8 years for the Offspring participants) including physician physical examinations, ECGs, questionnaires, and laboratory tests. During routine follow-up, records and ECGs from outpatient visits or hospitalizations for cardiovascular disease were obtained. The diagnosis of AF was based on the presence of atrial flutter or AF on ECGs from Framingham clinic visits, outside physician or hospital charts, or Holter reports adjudicated by at least two Framingham cardiologists. We used Framingham clinical variables collected during the examination at or antecedent but closest to AF diagnosis.
Cardiovascular events were adjudicated by a panel of three Framingham investigators reviewing Framingham clinic visits, and outside physician or hospital records. The outcome HF was diagnosed based on major (paroxysmal nocturnal dyspnoea or orthopnoea, auscultatory rales, third heart sound, distended neck veins, hepatojugular reflux, significant weight loss on diuretic therapy, and radiographic pulmonary oedema or increasing cardiomegaly) and minor (night cough, ankle oedema, dyspnoea on exertion, pleural effusion, hepatomegaly, radiographic pulmonary vascular redistribution, tachycardia, and decrease in vital capacity) criteria.
In secondary analyses, we further differentiated incident HF into reduced systolic function (LVEF <50% or fractional shortening <29%) and preserved EF (LVEF ≥50% or fractional shortening ≥29%). HF was unknown or unclassified if information was insufficient for classification into the above-mentioned categories.
Myocardial infarction was ascertained and classified as described previously. The Presence of increased voltage and a strain pattern were interpreted as ECG signs of LV hypertrophy. Prevalent cardiovascular disease comprised myocardial infarction, coronary insufficiency, angina, stroke, transient ischaemic attack, and intermittent claudication.
The definition of cardiovascular disease risk factors included fasting glucose ≥126 mg/dL, non-fasting blood glucose ≥200 mg/dL, or use of hypoglycaemic medications for diabetes; systolic blood pressure ≥140 or diastolic blood pressure ≥90 mmHg, or treatment for hypertension. Framingham clinic physician auscultated grade ≥3 out of 6 systolic murmur or any diastolic murmur was considered a significant cardiac murmur. Current smoking was self-reported regular use of one or more cigarettes/day within the year prior to the Heart Study examination.
Incidence rates for the number of HF cases/100 person-years of observation and 95% confidence intervals (CIs) were calculated based on the Haenszel method. We estimated sex-pooled multivariable Cox regression models to assess risk factors for HF incidence over a 10-year follow-up period; after 10 years, follow-up was censored. Death was considered a censoring event except for competing risks models. Hazard ratios for risk factors were assessed for 1 unit deviation increase for continuous variables and the condition present (vs. absent) for dichotomous risk factors. The proportionality assumption of the Cox regression models was not violated. We selected risk factors for analysis based on previous reports and availability in clinical practice. Besides age and sex, we examined Framingham clinic systolic and diastolic blood pressure, pulse pressure, hypertension, antihypertensive medication, height, weight, body mass index, current cigarette smoking, diabetes mellitus, significant murmur, ECG LV hypertrophy, heart rate, and prevalent myocardial infarction or cardiovascular disease at or prior to the onset of AF.
Biologically plausible potential interactions for age and sex among risk factors were examined and added to the final model if they improved discrimination and calibration. To account for possible secular trends in HF risk factors, we assessed the calendar period of AF onset and forced the year of AF onset into the regression models. Further, we checked for statistical interactions between decade and risk factors for HF onset, and provide characteristics of individuals developing HF by decade. We used the final Cox model for the development of a risk algorithm for incident HF that retained variables significant at the 0.05 level in multivariable models. We applied the C-statistic approach to assess discrimination, and estimated the consistency between expected 10-year HF events from the risk algorithm and actually observed events through the Hosmer–Lemeshow statistic modified for survival data. We assessed model fit and calibration in younger ( ≤70 years) and older (>70 years) individuals.
In pre-specified secondary analyses, we examined subtypes of HF with reduced systolic function and preserved EF. Considering the relatively high age of the participants at baseline, we performed additional models using the Fine and Gray method to adjust the risk estimates for the potential bias of the competing risk of death. All analyses were performed using SAS software, version 9.2 (SAS Institute, Cary, NC, USA) and the R 2.11.1 software package. A two-tailed P value of <0.05 was considered statistically significant.
This work received no defined internal or external funding with direct impact on the study's design, conduct, and reporting.
Methods
Setting and Participants
The current study was performed in two cohorts of the Framingham Heart Study: the Original cohort enrolled in 1948 and Offspring cohort enrolled in the early 1970s. Individuals were eligible if they had AF diagnosed after 1960 and before 31 December 1999 (n = 1236). We excluded individuals for the following reasons: HF onset prior to AF (including first diagnosis of HF and AF on the same day, n = 58) or lack of follow-up (n = 295), HF onset within 30 days after first diagnosis of AF (n = 9), death within 30 days after AF onset (n = 99), or missing risk factor data (n = 108). We determined the incidence of HF over 10 years, up to 31 December 2009. The Boston University Medical Center Institutional Review Board approved all study protocols, and participants signed consent at every examination. All authors have read and agree to the manuscript as written.
Outcomes and Follow-up
Participants undergo standardized cardiovascular disease risk factor assessment at regular Framingham Heart Study clinic visits (biennial clinic visits for the Original cohort and every 4–8 years for the Offspring participants) including physician physical examinations, ECGs, questionnaires, and laboratory tests. During routine follow-up, records and ECGs from outpatient visits or hospitalizations for cardiovascular disease were obtained. The diagnosis of AF was based on the presence of atrial flutter or AF on ECGs from Framingham clinic visits, outside physician or hospital charts, or Holter reports adjudicated by at least two Framingham cardiologists. We used Framingham clinical variables collected during the examination at or antecedent but closest to AF diagnosis.
Cardiovascular events were adjudicated by a panel of three Framingham investigators reviewing Framingham clinic visits, and outside physician or hospital records. The outcome HF was diagnosed based on major (paroxysmal nocturnal dyspnoea or orthopnoea, auscultatory rales, third heart sound, distended neck veins, hepatojugular reflux, significant weight loss on diuretic therapy, and radiographic pulmonary oedema or increasing cardiomegaly) and minor (night cough, ankle oedema, dyspnoea on exertion, pleural effusion, hepatomegaly, radiographic pulmonary vascular redistribution, tachycardia, and decrease in vital capacity) criteria.
In secondary analyses, we further differentiated incident HF into reduced systolic function (LVEF <50% or fractional shortening <29%) and preserved EF (LVEF ≥50% or fractional shortening ≥29%). HF was unknown or unclassified if information was insufficient for classification into the above-mentioned categories.
Myocardial infarction was ascertained and classified as described previously. The Presence of increased voltage and a strain pattern were interpreted as ECG signs of LV hypertrophy. Prevalent cardiovascular disease comprised myocardial infarction, coronary insufficiency, angina, stroke, transient ischaemic attack, and intermittent claudication.
The definition of cardiovascular disease risk factors included fasting glucose ≥126 mg/dL, non-fasting blood glucose ≥200 mg/dL, or use of hypoglycaemic medications for diabetes; systolic blood pressure ≥140 or diastolic blood pressure ≥90 mmHg, or treatment for hypertension. Framingham clinic physician auscultated grade ≥3 out of 6 systolic murmur or any diastolic murmur was considered a significant cardiac murmur. Current smoking was self-reported regular use of one or more cigarettes/day within the year prior to the Heart Study examination.
Statistical Analysis
Incidence rates for the number of HF cases/100 person-years of observation and 95% confidence intervals (CIs) were calculated based on the Haenszel method. We estimated sex-pooled multivariable Cox regression models to assess risk factors for HF incidence over a 10-year follow-up period; after 10 years, follow-up was censored. Death was considered a censoring event except for competing risks models. Hazard ratios for risk factors were assessed for 1 unit deviation increase for continuous variables and the condition present (vs. absent) for dichotomous risk factors. The proportionality assumption of the Cox regression models was not violated. We selected risk factors for analysis based on previous reports and availability in clinical practice. Besides age and sex, we examined Framingham clinic systolic and diastolic blood pressure, pulse pressure, hypertension, antihypertensive medication, height, weight, body mass index, current cigarette smoking, diabetes mellitus, significant murmur, ECG LV hypertrophy, heart rate, and prevalent myocardial infarction or cardiovascular disease at or prior to the onset of AF.
Biologically plausible potential interactions for age and sex among risk factors were examined and added to the final model if they improved discrimination and calibration. To account for possible secular trends in HF risk factors, we assessed the calendar period of AF onset and forced the year of AF onset into the regression models. Further, we checked for statistical interactions between decade and risk factors for HF onset, and provide characteristics of individuals developing HF by decade. We used the final Cox model for the development of a risk algorithm for incident HF that retained variables significant at the 0.05 level in multivariable models. We applied the C-statistic approach to assess discrimination, and estimated the consistency between expected 10-year HF events from the risk algorithm and actually observed events through the Hosmer–Lemeshow statistic modified for survival data. We assessed model fit and calibration in younger ( ≤70 years) and older (>70 years) individuals.
Secondary Analyses
In pre-specified secondary analyses, we examined subtypes of HF with reduced systolic function and preserved EF. Considering the relatively high age of the participants at baseline, we performed additional models using the Fine and Gray method to adjust the risk estimates for the potential bias of the competing risk of death. All analyses were performed using SAS software, version 9.2 (SAS Institute, Cary, NC, USA) and the R 2.11.1 software package. A two-tailed P value of <0.05 was considered statistically significant.
Role of the Funding Source
This work received no defined internal or external funding with direct impact on the study's design, conduct, and reporting.
Source...