Hypertension and atrial fibrillation: the clinical impact of hypertension on perioperative outcomes of atrial fibrillation ablation and its optimal control for the prevention of recurrence

Hypertension (HTN) is one of the major risk factors for developing atrial fibrillation (AF), and it has been estimated that approximately 70% of hypertensive patients are at risk of developing AF. On the other hand, 60-80% of AF patients have HTN. These two diseases share many risk factors such as diabetes mellitus, obesity, alcohol consumption, and sleep apnea syndrome during their onset and disease progression. The mutual presence of these diseases has the potential to create a negative spiral, exacerbating each other's impact and ultimately leading to cardiovascular events such as heart failure and cerebrovascular disorders, thereby increasing mortality rates. With regard to the treatment of HTN, the variety of antihypertensive drugs and treatment options have significantly increased. Alongside the widespread adoption of antihypertensive therapy, a certain level of efficacy has been recognized in suppressing the incidence of new-onset AF. Catheter ablation is an established and effective treatment for AF. However, a notable recurrence rate persists. In recent years, management of these multiple risk factors has been recognized to be essential for suppressing AF recurrence, and recent guidelines for AF underscore the significance of proactively managing these risks before treatment. Notably, effective HTN management assumes paramount importance given its impact on the morbidity of AF patients. This review summarizes the correlation between HTN control before and after ablation and the risk of AF recurrence. The focus is on elucidating the pathophysiological background and its impact on clinical outcomes.

Low remnant cholesterol and the subsequent risk of new-onset atrial fibrillation: A prospective cohort study

BACKGROUND

Atrial fibrillation (AF) is a common arrhythmia with high morbidity and mortality implications. Several studies have described a paradoxical inverse relationship between serum cholesterol and the risk of AF, but it remains unknown whether remnant cholesterol (RC) is associated with AF incidence.

OBJECTIVE

This study aims to prospectively investigate the association between RC and AF.

METHODS

A total of 392,783 participants free of AF at baseline from the UK Biobank were included for the analysis. Cox proportional hazards model, subgroup analysis, and sensitivity analyses were used to evaluate the independent association between RC levels and the risk of new-onset AF. Furthermore, we performed a discordance analysis by using the median cutoff points of low-density lipoprotein cholesterol (LDL-C) and RC.

RESULTS

After a median follow-up of 12.8 years (interquartile range 12.0-13.6 years), a total of 23,558 participants experienced incident AF. Compared with the highest RC level, the lower RC level was associated with an increased risk of AF incidence (quartile 1 vs quartile 4: hazard ratio 1.396; 95% confidence interval [CI] 1.343-1.452). The results remained robust across a series of sensitivity analyses. In the discordance analyses, a significantly higher risk of AF was observed in participants with discordant low RC/high LDL-C levels than in those with concordant high RC/LDL-C levels. In the low LDL-C group, RC reduction even contributed to an additional 15.8% increased rate of incident AF (low RC/low LDL-C: hazard ratio 1.303; 95% CI 1.260-1.348 vs high RC/low LDL-C: hazard ratio 1.125; 95% CI 1.079-1.172).

CONCLUSION

Low RC levels were associated with an increased risk of incident AF independent of traditional cardiovascular risk factors.

External validation of the FAscore scale to evaluate the risk of atrial fibrillation in patients with arterial hypertension

BACKGROUND AND AIM

To use a risk scale or predictive model outside the population of origin, it is necessary to evaluate the predictive indicators through external validation. The aim was to validate the FAscore, originally constructed in hypertensive patients in primary care in the Valencian Region, in an external cohort with hypertension in primary care in the Basque Country.

METHODS

A retrospective cohort study was designed to perform an external validation of the FAscore app in patients affiliated with 26 health centers in the municipality of Bilbao. The area under the ROC curve and predictive indicators were calculated with their 95% confidence intervals.

RESULTS

Thirty-six thousand eight hundred nine patients were included: 53.6% (n=19,719) were women, the mean age was 75.1 years, 41.8% (n=15,381). Over the four-year follow-up period, 1420 patients were diagnosed with AF (cumulative incidence 3.9%). The median risk estimated by FAscore was 4.5%, and the 5th, 25th, 75th, and 95th percentiles were 1.0%, 2.5%, 6.1%, and 14.8%, respectively. The ROC curve for the risk estimated by FAscore and the cases of atrial fibrillation observed was AUC 0.715 (95% CI 0.703-0.727). The 5% risk cutoff provides a sensitivity of 70.8%, specificity of 61.0%, positive predictive value of 6.8%, negative predictive value of 98.1%, and positive and negative likelihood ratios of 1.82 and 0.48, respectively.

CONCLUSION

This study reports on the external validation of the atrial fibrillation risk scale in hypertensive patients, which shows an acceptable predictive capacity. The best-performing risk cutoff, providing good predictive indicators, can be set at 5%.

Precise risk-prediction model including arterial stiffness for new-onset atrial fibrillation using machine learning techniques

Atrial fibrillation (AF) is the most common clinically significant cardiac arrhythmia and is an important risk factor for ischemic cerebrovascular events. This study used machine learning techniques to develop and validate a new risk prediction model for new-onset AF that incorporated the use electrocardiogram to diagnose AF, data from participants with a wide age range, and considered hypertension and measures of atrial stiffness. In Japan, Industrial Safety and Health Law requires employers to provide annual health check-ups to their employees. This study included 13 410 individuals who underwent health check-ups on at least four successive years between 2005 and 2015 (new-onset AF, n = 110; non-AF, n = 13 300). Data were entered into a risk prediction model using machine learning methods (eXtreme Gradient Boosting and Shapley Additive Explanation values). Data were randomly split into a training set (80%) used for model construction and development, and a test set (20%) used to test performance of the derived model. The area under the receiver operator characteristic curve for the model in the test set was 0.789. The best predictor of new-onset AF was age, followed by the cardio-ankle vascular index, estimated glomerular filtration rate, sex, body mass index, uric acid, γ-glutamyl transpeptidase level, triglycerides, systolic blood pressure at cardio-ankle vascular index measurement, and alanine aminotransferase level. This new model including arterial stiffness measure, developed with data from a general population using machine learning methods, could be used to identify at-risk individuals and potentially facilitation the prevention of future AF development.

Relationship between ω3 and ω6 polyunsaturated fatty acids and atrial fibrillation in acute ischemic stroke

BACKGROUND & AIMS

Some ω3 polyunsaturated fatty acids (PUFAs) are said to demonstrate a dose-related risk of atrial fibrillation (AF), conversely, some ω6 PUFAs might have AF protective potential. However, few investigated the relation among ischemic strokes. Primarily, we aimed to examine a relation between ω3 and ω6 PUFAs and the presence of AF in ischemic strokes. Further, since, some PUFAs are said to affect the cardiac load, we secondarily aimed to investigate the association between ω3 and ω6 PUFAs and brain natriuretic peptide (BNP) and the occurrence of cerebral large vessel occlusion (LVO) in ischemic strokes with AF.

METHODS

Consecutive patients with ischemic stroke admitted between 2012 and 2022 were retrospectively screened. Plasma levels of PUFAs, including eicosapentaenoic acid (EPA), docosahexaenoic acid, dihomo-γ-linolenic acid (DGLA) and arachidonic acid (AA), were assayed. Data were analyzed using a Poisson regression analysis with a robust variance estimator and a multiple linear regression analysis.

RESULTS

We screened 2112 consecutive ischemic strokes, including 1574 (1119 [71%] males, median age 69 years). Lower DGLA (prevalence ratio (PR) 0.885, 95% CI 0.811-0.966, p = 0.006), lower AA (PR 0.797, 95% CI 0.649-0.978, p = 0.030), and higher EPA/AA ratio (PR 1.353, 95% CI 1.036-1.767, p = 0.026) were associated with AF. Checking the linearity between AF and PUFAs, negative linear trends were observed between DGLA quartiles (Q1: PR 1.901, Q2: PR 1.550, Q3: PR 1.423, Q4: 1.000, p < 0.001 for trend) and AA quartiles (Q1: PR 1.499, Q2: PR 1.204, Q3: PR 1.125, Q4: 1.000, p = 0.004 for trend), with positive linear trends between EPA/AA ratio quartiles (Q1: 1.000, Q2: PR 1.555, Q3: PR 1.612, Q4: PR 1.797, p = 0.001 for trend). Among patients with AF, a negative association between AA and BNP (unstandardized coefficient -1.316, 95% CI -2.290∼-0.342, p = 0.008) was observed, and lower AA was associated with LVO (PR 0.707, 95% CI 0.527-0.950, p = 0.021).

CONCLUSION

Lower DGLA and AA and a higher EPA/AA ratio might be related to the development of AF in ischemic strokes. Further, AA might have a cardio-cerebrovascular protective role in ischemic strokes with AF.

Simple risk scoring using sinus rhythm electrocardiograms predicts the incidence of atrial fibrillation in the general population

Atrial fibrillation (AF) is an arrhythmic disease. Prediction of AF development in healthy individuals is important before serious complications occur. We aimed to develop a risk prediction score for future AF using participants' data, including electrocardiogram (ECG) measurements and information such as age and sex. We included 88,907 Japanese participants, aged 30-69 years, who were randomly assigned to derivation and validation cohorts in a ratio of 1:1. We performed multivariate logistic regression analysis and obtained the standardised beta coefficient of relevant factors and assigned scores to them. We created a score based on prognostic factors for AF to predict its occurrence after five years and applied it to validation cohorts to assess its reproducibility. The risk score ranged from 0 to 17, consisting of age, sex, PR prolongation, QT corrected for heart rate prolongation, left ventricular hypertrophy, premature atrial contraction, and left axis deviation. The area under the curve was 0.75 for the derivation cohort and 0.73 for the validation cohort. The incidence of new-onset AF reached over 2% at 10 points of the risk score in both cohorts. Thus, in this study, we showed the possibility of predicting new-onset AF using ECG findings and simple information.

Upregulated Genes in Atrial Fibrillation Blood and the Left Atrium

INTRODUCTION

Atrial fibrillation (AF) is a common arrhythmia associated with aging. Many known risk factors are associated with AF, but many senior individuals do not develop AF despite having multiple risk factors. This finding suggests that other factors may be involved in AF onset. This study aimed to identify upregulated genes in the peripheral blood and left atrium of patients with AF. These genes may serve as potential biomarkers to predict AF onset risk and its complications.

METHODS

Gene expression data were analyzed from blood (n = 3) and left atrial samples (n = 15) of patients with AF and sinus rhythm. We evaluated the significant genes identified using p value analysis of weighted average difference to confirm their rankings. We created figures for the genes using GeneMANIA and performed a functional analysis using Cytoscape3.10.1. Hub and bottleneck genes were identified based on degree and betweenness centrality. We used reference expression (RefEx) to confirm the organs in which the extracted genes were expressed. Heatmaps and Gene ontology term evaluation were performed to further elucidate the biological functions of the genes.

RESULTS

We identified 12 upregulated genes (CAST, ASAH1, MAFB, VCAN, DDIT4, FTL, HEXB, PROS1, BNIP3L, PABPC1, YBX3, and S100A6) in both the blood and left atrium of patients with AF. We analyzed the gene functions using GeneMANIA and Cytoscape. The identified genes were involved in a variety of pathways, including lysosomal function and lipid and sphingolipid catabolism. Next, we investigated whether the 12 identified genes identified were systemically expressed or had high organ specificity. Finally, RefEx was used to analyze the gene expression levels in various tissues. Four genes, FTL, ASAH1, S100A6, and PABPC1, were highly expressed in the normal heart tissue. Finally, we evaluated the expression levels of the 12 genes in the blood of patients with AF using a heatmap. Our findings suggest that the 12 genes identified in this study, especially the lysosome-related genes (FTL and ASAH1), may be involved in AF pathogenesis.

CONCLUSION

Lysosome-related genes may be important to understand the AF pathophysiology and to develop AF-related future studies.

Association between paroxysmal or persistent atrial fibrillation and hyperuricemia in patients who underwent coronary computed tomography angiography: from the FU-CCTA-AF Registry

BACKGROUND

Hyperuricemia (HU) and hypertension (HTN) contribute to atherosclerotic cardiovascular disease, and both are also involved in the onset and development of atrial fibrillation (AF).

OBJECTIVE

In the present study, we investigated the association between risk factors for atherosclerosis [including HU, HTN, blood pressure and serum uric acid (UA) levels] and paroxysmal atrial fibrillation (Paro-AF) or persistent atrial fibrillation (Pers-AF) in patients who underwent coronary computed tomography angiography (CCTA).

METHODS

We enrolled 263 patients from the Fukuoka University-CCTA-AF (FU-CCTA-AF Registry) who underwent CCTA prior to AF ablation therapy. AF was classified as either Paro-AF (≤ 7 days) or Pers-AF (> 7 days). HU was diagnosed by a serum UA level > 7.0 mg/dl, and coronary artery disease (CAD) was diagnosed when CCTA results showed ≥ 50% significant coronary artery stenosis. The number of significantly diseased coronary artery vessels (VD), the Gensini score and the coronary artery calcification score (CACS) were measured. Left atrial morphology was also evaluated.

RESULTS

Diastolic blood pressure and HbA1c in the Pers-AF group were significantly higher than those in the Paro-AF group. The Pers-AF group showed a significantly higher prevalence of HU and higher UA levels than the Paro-AF group. In a multivariate logistic regression analysis, HU was an independent associated factor to Pers-AF (odds ratio: 2.023, 95% confidence interval: 1.055-3.881, p = 0.034), while HTN was not.

CONCLUSION

In patients with AF, HU is associated with Pers-AF.

Fatty Liver Index and the Risk of Atrial Fibrillation in a General Japanese Population - The Suita Study

BACKGROUND

Atrial fibrillation (AF) is the most diagnosed arrhythmia in clinical settings. The fatty liver index (FLI) is a marker of liver steatosis with potential cardiovascular implications. This study investigated whether FLI could predict the risk of AF.

METHODS AND RESULTS

We used data from the Suita Study, a Japanese population-based prospective cohort study. A total of 2,346 men and 3,543 women, aged 30-84 years, without prevalent AF were included and followed up. The diagnosis of AF was established during follow-up using electrocardiograms, hospital records, and death certificates. FLI was assessed during a baseline health checkup. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated for incident AF per FLI quintile and log-transformed FLI. Within a median 14.5 years of follow-up, 142 men and 105 women developed AF. Compared with women in the third (middle) FLI quintile, women in the first (lowest), fourth, and fifth (highest) quintiles showed a higher risk of AF, with multivariable-adjusted HRs of 2.37 (95% CI 1.06-5.31), 2.60 (95% CI 1.30-5.17), and 2.04 (95% CI 1.00-4.18), respectively. No corresponding associations were observed in men. The change in log-transformed FLI was not associated with the risk of AF in either sex.

CONCLUSIONS

A U-shaped association between FLI and AF risk was detected in Japanese women. FLI could be a screening tool to detect women at high risk of developing AF.

Meta-analysis of the Current Research on the Relationship Between Blood Lipid Levels and the Occurrence of Atrial Fibrillation

BACKGROUND

There is still debate in the literature about the relationship between lipid profile and the occurrence of atrial fibrillation (AF). In order to assess the association between blood lipid profiles and incidence of AF, this review was conducted to perform a meta-analysis of all available studies.

METHODS

This review analysed all studies up to 28 February 2023 in PubMed, Google Scholar, and the Cochrane Library that included data regarding blood lipid levels and incidence of AF. For the purpose of calculating pooled estimates, the hazard ratios were extracted from all studies.

RESULTS

Fourteen studies including 19 cohorts with 3,990,484 patients were included in this meta-analysis. An elevation of one standard deviation in total cholesterol (TC) level was associated with an 8% reduction (HR=0.92, 0.88-0.96; p<0.01) in the risk of developing AF. Although increased low-density lipoprotein cholesterol levels were associated with a 7% reduction in the development of AF (HR=0.93, 0.87-1.00; p=0.04), there was high heterogeneity in the random effects model (I2=92%). Changes in high-density lipoprotein cholesterol and triglyceride levels were not found to be associated with AF risk in the pooled analysis. Dose-response meta-analysis showed that TC was inversely linearly associated with the risk of AF (p<0.001).

CONCLUSIONS

Higher TC levels were shown to be independently attributed to an increased risk of AF in individuals without cardiovascular disease. There was no association between the incidence of AF and triglyceride, high-density lipoprotein cholesterol, or low-density lipoprotein cholesterol blood levels.

Association between cardiovascular risk factors and atrial fibrillation

Background

The most prevalent sustained arrhythmia in medical practice, atrial fibrillation (AF) is closely associated with a high risk of cardiovascular disease. Nevertheless, the risk of AF associated with cardiovascular risk factors has not been well elucidated. We pooled all published studies to provide a better depiction of the relationship among cardiovascular risk factors with AF.

Methods

Studies were searched in the MEDLINE, Web of Science, and EMBASE databases since initiation until January 15, 2022. Prospective cohort studies assessing the relationship a minimum of single cardiovascular risk factors to AF incidence were included if they contained adequate data for obtaining relative risks (RR) and 95% confidence intervals (CI). Random-effects models were utilized to perform independent meta-analyses on each cardiovascular risk factor. PROSPERO registry number: CRD42022310882.

Results

A total of 17,098,955 individuals and 738,843 incident cases were reported for data from 101 studies included in the analysis. In all, the risk of AF was 1.39 (95% CI, 1.30-1.49) for obesity, 1.27 (95% CI, 1.22-1.32) per 5 kg/m2 for increase in body mass index, 1.19 (95% CI, 1.10-1.28) for former smokers, 1.23 (95% CI, 1.09-1.38) for current smokers, 1.31 (95% CI, 1.23-1.39) for diabetes mellitus, 1.68 (95% CI, 1.51-1.87) for hypertension, and 1.12 (95% CI, 0.95-1.32) for dyslipidemia.

Interpretation

Adverse cardiovascular risk factors correlate with an increased risk of AF, yet dyslipidemia does not increase the risk of AF in the general population, potentially providing new insights for AF screening strategies among patients with these risk factors.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/, PROSPERO identifier (CRD42022310882).

Risk factor profile for newly diagnosed atrial fibrillation: 4-year follow-up of annual health examinations in a Japanese Adult Cohort

BACKGROUND

Detecting unknown atrial fibrillation (AF) would provide an opportunity to prevent ischemic stroke by instituting appropriate anticoagulation. Although opportunistic screening of older patients is recommended in current guidelines, which patients may benefit from intensive AF screening remains unclear. We sought to clarify the risk factor profile for newly diagnosed AF in annual health examinations of a Japanese adult cohort.

METHODS

Among 141 441 Japanese patients who underwent annual health examinations in 2014, 87 872 patients aged ≥20 years without known AF who had undergone electrocardiography were analyzed (mean age: 47 ± 12 years; 64% men). The absence of known AF was confirmed by prior electrocardiography in 2012 and/or 2013. Newly diagnosed AF was observed in 244 patients in 2014-2017 (mean age: 62 ± 12 years; 83% men).

RESULTS

In the multivariable analysis, waist circumference obesity (hazard ratio [HR], 1.5; 95% confidence interval [CI], 1.13-1.99; p = .005) high blood pressure (HR, 1.9; 95% CI, 1.01-3.59; p = .047), on-treatment hypertension (HR, 1.53; 95% CI, 1.01-2.31; p = .046), and daily alcohol drinking (HR, 2.18; 95% CI, 1.52-3.12; p < .001) were significantly associated with newly diagnosed AF.

CONCLUSIONS

In this Japanese cohort, waist circumference obesity, hypertension, and alcohol drinking were independent predictors of newly diagnosed AF in annual medical examinations. This finding encourages further evaluation of systematic AF screening programs in at-risk populations.

Impact of glycated hemoglobin on 2-year clinical outcomes in elderly patients with atrial fibrillation: sub-analysis of ANAFIE Registry, a large observational study

BACKGROUND

This ANAFIE Registry sub-analysis investigated 2-year outcomes and oral anticoagulant (OAC) use stratified by glycated hemoglobin (HbA1c) levels among Japanese patients aged ≥ 75 years with non-valvular atrial fibrillation (NVAF) with and without clinical diagnosis of diabetes mellitus (DM).

METHODS

The ANAFIE Registry was a large-scale multicenter, observational study conducted in Japan; this sub-analysis included patients with baseline HbA1c data at baseline. The main endpoints evaluated (stroke/systemic embolic events [SEE], major bleeding, intracranial hemorrhage, cardiovascular death, all-cause death, and net clinical outcome [a composite of stroke/SEE, major bleeding, and all-cause death]) were stratified by HbA1c levels (< 6.0%; 6.0% to < 7.0%; 7.0% to < 8.0%; and ≥ 8.0%).

RESULTS

Of 17,526 patients with baseline HbA1c values, 8725 (49.8%) patients had HbA1c < 6.0%, 6700 (38.2%) had 6.0% to < 7.0%, 1548 (8.8%) had 7.0% to < 8.0%, and 553 (3.2%) had ≥ 8.0%. Compared with other subgroups, patients with HbA1c ≥ 8.0% were more likely to have lower renal function, higher CHA₂DS₂-VASc and HAS-BLED scores, higher prevalence of non-paroxysmal AF, and lower direct OAC (DOAC) administration, but higher warfarin administration. The HbA1c ≥ 8.0% subgroup had higher event rates for all-cause death (log-rank P = 0.003) and net clinical outcome (log-rank P = 0.007). Similar trends were observed for stroke/SEE. In multivariate analysis, risk of all-cause death (adjusted hazard ratio [aHR]: 1.46 [95% confidence interval 1.11-1.93]) and net clinical outcome (aHR 1.33 [1.05-1.68]) were significantly higher in the HbA1c ≥ 8.0% subgroup. No significant differences were observed in risks of major bleeding or other outcomes in this and other subgroups. No interaction was observed between HbA1c and OACs. Use/non-use of antidiabetic drugs was not associated with risk reduction; event risks did not differ with/without injectable antidiabetic drugs.

CONCLUSIONS

Among elderly Japanese patients with NVAF, only HbA1c ≥ 8.0% was associated with increased all-cause death and net clinical outcome risks; risks of the events did not increase in other HbA1c subgroups. Relative event risks between patients treated with DOACs and warfarin were not modified by HbA1c level.

TRIAL REGISTRATION

UMIN000024006; date of registration: September 12, 2016.

Artificial intelligence in cardiovascular prevention: new ways will open new doors

Prevention and effective treatment of cardiovascular disease are progressive issues that grow in tandem with the average age of the world population. Over recent decades, the potential role of artificial intelligence in cardiovascular medicine has been increasingly recognized because of the incredible amount of real-world data (RWD) regarding patient health status and healthcare delivery that can be collated from a variety of sources wherein patient information is routinely collected, including patient registries, clinical case reports, reimbursement claims and billing reports, medical devices, and electronic health records. Like any other (health) data, RWD can be analysed in accordance with high-quality research methods, and its analysis can deliver valuable patient-centric insights complementing the information obtained from conventional clinical trials. Artificial intelligence application on RWD has the potential to detect a patient's health trajectory leading to personalized medicine and tailored treatment. This article reviews the benefits of artificial intelligence in cardiovascular prevention and management, focusing on diagnostic and therapeutic improvements without neglecting the limitations of this new scientific approach.

New 2019 JSH guidelines and the risk of incident cardiovascular disease: The Suita Study

Hypertension is the most critical risk factor for cardiovascular disease (CVD). Since the definition of hypertension varies across guidelines, identifying blood pressure (BP) categories that should be targeted to prevent CVD is needed. Herein, we investigated the association between BP per the 2019 Japanese Society of Hypertension (JSH) guidelines and the risk of CVD, stroke, and coronary heart disease (CHD) using data from 7,643 participants (30-84 years) registered in the Suita Study. Within 113,838 person-years (16.6 median years of follow-up), 690 participants developed CVD (411 cases of stroke and 279 cases of CHD). Compared to normal BP (Systolic BP (SBP) < 120 and diastolic BP (DBP) < 80 mmHg), elevated BP (SBP 130-139 and/or DBP 80-89 mmHg) and hypertension (SBP ≥ 140 and/or DBP ≥ 90 mmHg) were associated with a higher risk of CVD, stroke, and CHD. High-normal BP (SBP 120-129 and DBP < 80 mmHg) was associated with a higher risk of CVD and CHD. In conclusion, CVD preventive interventions should begin at lower BP levels than those applied in the 2019 JSH guidelines.

Blood Pressure Classification Using the 2017 ACC/AHA Guideline and Heart Failure in Patients With Cancer

PURPOSE

Despite the growing recognition of the importance of hypertension in patients with cancer, little is known about whether high blood pressure (BP) among patients with cancer is associated with incident heart failure (HF) and other cardiovascular disease (CVD) events and what BP levels are linked to these events. We examined the association of BP classification on the basis of the 2017 American College of Cardiology/American Heart Association BP guideline with the risk of HF and CVD events in patients with cancer.

METHODS

We studied 33,991 patients with a history of breast, colorectal, or stomach cancer (median age, 53 years; 34.1% men). Patients receiving treatment with BP-lowering medications or having a history of CVD including HF were excluded. Using BP measurements at baseline, 33,991 participants were categorized as having normal BP (n = 17,444), elevated BP (n = 4,733), stage 1 hypertension (n = 7,502), or stage 2 hypertension (n = 4,312). The primary outcome was HF.

RESULTS

Over a mean follow-up of 2.6 ± 2.2 years, 779 HF events were recorded. After multivariable adjustment, the hazard ratios (HRs) for HF were 1.15 (95% CI, 0.93 to 1.44) for elevated BP, 1.24 (95% CI, 1.03 to 1.49) for stage 1 hypertension, and 1.99 (95% CI, 1.63 to 2.43) for stage 2 hypertension. A stepwise increase in risk with BP categories was also observed in other CVD events. This association was observed even in patients undergoing active cancer treatment. The relationship between hypertension and the risk of developing HF in patients with cancer was confirmed in the Korean National Health Insurance Service database.

CONCLUSION

Medication-naïve stage 1 and 2 hypertension was associated with a greater risk of HF and other CVD events in patients with cancer. Our results suggest the importance of multidisciplinary collaboration (eg, oncologists and cardiologists) to establish the optimal management strategy for hypertension in patients with cancer.

Association Between White Blood Cell Count and Atrial Fibrillation Risk - A Population-Based Prospective Cohort Study

BACKGROUND

The incidence and prevalence of atrial fibrillation (AF) are increasing. The white blood cell (WBC) count is an indicator of systemic inflammation and is related to increased cardiovascular disease risk. Using data from the Suita Study, we investigated the association between WBC count and AF risk in the general Japanese population.

METHODS AND RESULTS

This prospective cohort study included 6,884 people, aged 30-84 years, with no baseline AF. Cox regression was used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for AF incidence by WBC count quintile. Within a median follow-up period of 14.6 years, 312 AF cases were diagnosed. Compared with the lowest WBC count quintile, the highest quintile was associated with an increased AF risk (HR 1.57; 95% CI 1.07-2.29). The association was more pronounced among women than men (HR 2.16 [95% CI 1.10-4.26] and 1.55 [95% CI 0.99-2.44], respectively; P interaction=0.07), and among current than non-smokers (HR 4.66 [95% CI 1.89-11.50] and 1.61 [95% CI 1.01-2.57], respectively; P interaction=0.20). For each 1.0×109-cells/L increment in WBC count, AF risk increased by 9% in men (9% in non-smokers, 10% in current smokers) and 20% in women (13% in non-smokers, 32% in current smokers).

CONCLUSIONS

A higher WBC count was positively associated with an elevated AF risk in the general Japanese population, especially in women who smoked.

Accuracy of wristwatch-type photoplethysmography in detecting atrial fibrillation in daily life. EUROPEAN HEART JOURNAL. DIGITAL HEALTH 2022;3:455-464. [PMID: 36712156 PMCID: PMC9707983 DOI: 10.1093/ehjdh/ztac041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Aims

Detection of asymptomatic paroxysmal atrial fibrillation is challenging. Smartphone- or smartwatch-based photoplethysmography is efficient at detecting irregular rhythms using pulse waves but is too complex for older patients. We aimed to evaluate the detection accuracy of atrial fibrillation by a wristwatch-type continuous pulse wave monitor (PWM) in daily life.

Methods and results

Patients at high risk of atrial fibrillation but with no history of atrial fibrillation (n = 163; mean CHADS₂ score, 1.9) and patients with known atrial fibrillation (n = 123, including 34 with persistent atrial fibrillation) underwent PWM and telemetry electrocardiogram recording for 3 days. Risk of atrial fibrillation was judged using the 'Kyorin Atrial Fibrillation Risk Score', a scoring system based on previously reported atrial fibrillation risk scoring systems. The PWM assessed the presence of atrial fibrillation at 30 min intervals, and the results were compared with the telemetry electrocardiogram findings. The PWMs accurately diagnosed two patients with paroxysmal atrial fibrillation in the high-risk group. The PWMs accurately diagnosed 48 of the 55 patients with atrial fibrillation in the known-atrial fibrillation group. The PWM accuracy in detecting patients with atrial fibrillation was as follows: sensitivity, 98.0%; specificity, 90.6%; positive predictive value, 69.4%; negative predictive value, 99.5%. The respective values for intervals with atrial fibrillation were 86.9%, 98.8%, 89.6%, and 98.5%.

Conclusion

The wristwatch-type PWM has shown feasibility in detecting atrial fibrillation in daily life and showed the possibility of being used as a screening tool.

Predictive ability of arterial stiffness parameters for renal function decline: a retrospective cohort study comparing cardio-ankle vascular index, pulse wave velocity and cardio-ankle vascular index 0

OBJECTIVE

The relative usefulness of arterial stiffness parameters on renal function remains controversial. This study aimed to compare the predictive ability of three arterial stiffness parameters at baseline; cardio-ankle vascular index (CAVI), heart-ankle pulse wave velocity (haPWV) and CAVI 0 , a variant of CAVI that theoretically excludes dependence on blood pressure, for renal function decline in Japanese general population.

METHODS

A total of 27 864 Japanese urban residents without renal impairment at baseline who participated in two to eight consecutive (mean 3.5 ± 1.7 times) annual health examinations were studied.

RESULTS

During the study period, 6.6% of participants developed renal function decline (estimated glomerular filtration rate <60 ml/min per 1.73 m 2 ), all of whom had relatively high values in all arterial stiffness parameters. In receiver-operating characteristic curve analysis, the discriminatory power for renal function decline showed a decreasing trend of CAVI to haPWV to CAVI 0 (C-statistic: 0.740 vs. 0.734 vs. 0.726). The cut-offs were CAVI 8.0, haPWV 7.23 and CAVI 0 11.6. In Cox-proportional hazards analysis for increase of each parameter above cut-off or by 1 standard deviation (SD) adjusted for two models of confounders, only CAVI always contributed significantly to renal function decline. Restricted cubic spline regression analysis suggested that CAVI most accurately reflected the risk of renal function decline.

CONCLUSION

Increase in arterial stiffness parameters, especially CAVI, may represent a major modifiable risk factor for renal function decline in the general population. Further research is needed to examine whether CAVI-lowering interventions contribute to the prevention of chronic kidney disease.

Is machine learning the future for atrial fibrillation screening?

Atrial fibrillation (AF) is the most common arrhythmia and causes significant morbidity and mortality. Early identification of AF may lead to early treatment of AF and may thus prevent AF-related strokes and complications. However, there is no current formal, cost-effective strategy for population screening for AF. In this review, we give a brief overview of targeted screening for AF, AF risk score models used for screening and describe the different screening tools. We then go on to extensively discuss the potential applications of machine learning in AF screening.

Relationship of normal-weight central obesity with the risk for heart failure and atrial fibrillation: analysis of a nationwide health check-up and claims database

Aims

There have been scarce data on the relationship of normal-weight central obesity (NWCO) with the subsequent risk for heart failure (HF) and atrial fibrillation (AF). Using a nationwide health check-up and administrative claims database, we sought to clarify whether NWCO would be associated with the incidence of HF and AF.

Methods and results

Medical records of 1 697 903 participants without prior history of cardiovascular disease (CVD) and normal-weight (body mass index of 18.5–23.0 kg/m²) were extracted from the JMDC Claims Database, which is a health check-up and claims database. We defined NWCO as normal-weight and CO (waist circumference ≥ 90 cm for men or ≥ 80 cm for women). The median age was 44.0 (37.0–52.0) years and 872 578 (51.4%) participants were men. Overall, 154 778 individuals (9.1%) had CO. The mean follow-up period was 3.3 ± 2.6 years. Participants with NWCO were older and more likely to be women than those without. HF and AF occurred in 26 936 (1.6%) and 6554 (0.4%) participants, respectively. People having NWCO were associated with a greater risk for HF [hazard ratio (HR): 1.072, 95% confidence interval (CI) 1.026–1.119] and AF (HR: 1.202, 95% CI: 1.083–1.333) compared with those having normal-weight without CO.

Conclusion

Our analysis of a nationwide health check-up and administrative claims database including ∼1.7 million participants without prevalent CVD history demonstrated the potential impact of NWCO on the risk for HF and AF, suggesting the importance of abdominal obesity in the developing HF and AF even in normal-weight individuals.

QRS transitional zone rotations and the risk of atrial fibrillation: the Suita Study

ECG screening can detect people at risk of developing atrial fibrillation (AF). Recent literature indicated that QRS transitional zone rotations could predict several cardiovascular events. Herein, we investigated the association between QRS transitional zone rotations and the future risk of AF. This prospective cohort study included 6794 participants (3178 men and 3616 women), aged 30-84 years, from the urban Japanese city of Suita. QRS transitional zone rotations were diagnosed by ECG during baseline, while AF was diagnosed by ECG, hospital records, and checkups during follow-up. The Cox regression was used to compute the sex-specified hazard ratios (HRs) and 95% confidence intervals (CIs) of incident AF for participants with counterclockwise and clockwise QRS transitional zone rotations compared to those with normal rotation. Within a median follow-up period of 14.6 years, 311 participants (206 men and 105 women) developed AF. Counterclockwise rotation was associated with the reduced risk of AF among men, but not women, in the age-adjusted model: HR (95% CI) = 0.66 (0.44, 0.98) and the multivariable-adjusted model: HR (95% CI) = 0.65 (0.43, 0.97). Clockwise rotation was not associated with AF risk in either sex. To the best of our knowledge, this is the first study to indicate that counterclockwise rotation could be associated with the reduced risk of AF in men. More studies are needed to confirm our findings and elucidate possible mechanisms.

Exploring and Identifying Prognostic Phenotypes of Patients with Heart Failure Guided by Explainable Machine Learning

Identifying patient prognostic phenotypes facilitates precision medicine. This study aimed to explore phenotypes of patients with heart failure (HF) corresponding to prognostic condition (risk of mortality) and identify the phenotype of new patients by machine learning (ML). A unsupervised ML was applied to explore phenotypes of patients in a derivation dataset (n = 562) based on their medical records. Thereafter, supervised ML models were trained on the derivation dataset to classify these identified phenotypes. Then, the trained classifiers were further validated on an independent validation dataset (n = 168). Finally, Shapley additive explanations were used to interpret decision making of phenotype classification. Three patient phenotypes corresponding to stratified mortality risk (high, low, and intermediate) were identified. Kaplan−Meier survival curves among the three phenotypes had significant difference (pairwise comparison p < 0.05). Hazard ratio of all-cause mortality between patients in phenotype 1 (n = 91; high risk) and phenotype 3 (n = 329; intermediate risk) was 2.08 (95%CI 1.29−3.37, p = 0.003), and 0.26 (95%CI 0.11−0.61, p = 0.002) between phenotype 2 (n = 142; low risk) and phenotype 3. For phenotypes classification by random forest, AUCs of phenotypes 1, 2, and 3 were 0.736 ± 0.038, 0.815 ± 0.035, and 0.721 ± 0.03, respectively, slightly better than the decision tree. Then, the classifier effectively identified the phenotypes for new patients in the validation dataset with significant difference on survival curves and hazard ratios. Finally, age and creatinine clearance rate were identified as the top two most important predictors. ML could effectively identify patient prognostic phenotypes, facilitating reasonable management and treatment considering prognostic condition.

Sleep duration and atrial fibrillation risk in the context of predictive, preventive, and personalized medicine: the Suita Study and meta-analysis of prospective cohort studies

Background

Short and long sleep durations are common behaviors that could predict several cardiovascular diseases. However, the association between sleep duration and atrial fibrillation (AF) risk is not well-established. AF is preventable, and risk prevention approaches could reduce its occurrence. Investigating whether sleep duration could predict AF incidence for possible preventive interventions and determining the impact of various lifestyle and clinical characteristics on this association to personalize such interventions are essential. Herein, we investigated the association between sleep duration and AF risk using a prospective cohort study and a meta-analysis of epidemiological evidence.

Methods

Data of 6898 people, aged 30-84 years, from the Suita Study, were analyzed. AF was diagnosed during the follow-up by ECG, medical records, checkups, and death certificates, while a baseline questionnaire was used to assess sleep duration. The Cox regression was used to compute the hazard ratios (HRs) and 95% confidence intervals (CIs) of AF risk for daily sleep ≤ 6 (short sleep), ≥ 8 (long sleep), and irregular sleep, including night-shift work compared with 7 h (moderate sleep). Then, we combined our results with those from other eligible prospective cohort studies in two meta-analyses for the short and long sleep.

Results

In the Suita Study, within a median follow-up period of 14.5 years, short and irregular sleep, but not long sleep, were associated with the increased risk of AF in the age- and sex-adjusted models: HRs (95% CIs) = 1.36 (1.03, 1.80) and 1.62 (1.16, 2.26) and the multivariable-adjusted models: HRs (95% CIs) = 1.34 (1.01, 1.77) and 1.63 (1.16, 2.30), respectively. The significant associations between short and irregular sleep and AF risk remained consistent across different ages, sex, smoking, and drinking groups. However, they were attenuated among overweight and hypertensive participants. In the meta-analyses, short and long sleep durations were associated with AF risk: pooled HRs (95% CIs) = 1.21 (1.02, 1.42) and 1.18 (1.03, 1.35). No signs of significant heterogeneity across studies or publication bias were detected.

Conclusion

Short, long, and irregular sleep could be associated with increased AF risk. In the context of predictive, preventive, and personalized medicine, sleep duration should be considered in future AF risk scores to stratify the general population for potential personalized lifestyle modification interventions. Sleep management services should be considered for AF risk prevention, and these services should be individualized according to clinical characteristics and lifestyle factors.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-022-00275-4.

Validating risk models versus age alone for atrial fibrillation in a young Dutch population cohort: should atrial fibrillation risk prediction be expanded to younger community members?

BACKGROUND

Advancing age is the primary selection criterion for community screening for atrial fibrillation (AF), with selection often restricted to those aged ≥65 years. If multivariable models were shown to have considerable additional value over age alone in predicting AF risk among younger individuals, AF screening could be expanded to patients with lower age, but with high AF risk as per a validated risk model.

METHODS

We validated risk models CHARGE-AF (Cohorts for Heart and Aging Research in Genomic Epidemiology model for AF) and FHS-AF (Framingham Heart Study model for AF), and risk scores CHA₂DS₂-VASc and CHA₂DS₂-VA, and presented their predictive abilities for 5-year and 10-year AF risk versus that of age alone in a young Dutch population cohort (PREVEND) free from AF at baseline. We assessed discrimination by the C-statistic and calibration by the calibration plot and stratified Kaplan-Meier plot using survey-weighted Cox models.

RESULTS

During 5-year and 10-year follow-up there were n=98 (2.46/1000 person-years) and n=249 (3.29/1000 person-years) new AF cases, respectively, among 8265 participants with mean age 49±13 years. CHARGE-AF and FHS-AF both showed good discrimination for 5-year and 10-year AF (C-statistic range 0.83-0.86) with accurate calibration for 5-year AF, but overestimation of 10-year AF risk in highest-risk individuals. CHA₂DS₂-VASc and CHA₂DS₂-VA relatively underperformed. Age alone showed similar discrimination to that of CHARGE-AF and FHS-AF both in the overall, young PREVEND cohort and in subgroups for lower age and lower stroke risk.

CONCLUSION

Multivariable models accurately discriminate for 5-year and 10-year AF risk among young European community-dwelling individuals. However, their additional discriminatory value over age alone was limited. Selection strategies for primary AF screening using multivariable models should not be expanded to younger individuals.

Explainable Machine Learning for Atrial Fibrillation in the General Population Using a Generalized Additive Model - A Cross-Sectional Study

Background: Atrial fibrillation (AF) is the most common arrhythmia and is associated with increased thromboembolic stroke risk and heart failure. Although various prediction models for AF risk have been developed using machine learning, their output cannot be accurately explained to doctors and patients. Therefore, we developed an explainable model with high interpretability and accuracy accounting for the non-linear effects of clinical characteristics on AF incidence. Methods and Results: Of the 489,073 residents who underwent specific health checkups between 2009 and 2018 and were registered in the Kanazawa Medical Association database, data were used for 5,378 subjects with AF and 167,950 subjects with normal electrocardiogram readings. Forty-seven clinical parameters were combined using a generalized additive model algorithm. We validated the model and found that the area under the curve, sensitivity, and specificity were 0.964, 0.879, and 0.920, respectively. The 9 most important variables were the physical examination of arrhythmia, a medical history of coronary artery disease, age, hematocrit, γ-glutamyl transpeptidase, creatinine, hemoglobin, systolic blood pressure, and HbA1c. Further, non-linear relationships of clinical variables to the probability of AF diagnosis were visualized. Conclusions: We established a novel AF risk explanation model with high interpretability and accuracy accounting for non-linear information obtained at general health checkups. This model contributes not only to more accurate AF risk prediction, but also to a greater understanding of the effects of each characteristic.

Sex Difference in the Association between Lipid Profile and Incident Cardiovascular Disease among Young Adults

AIM

Using a nationwide epidemiological database, we sought to examine whether there was a sex difference in the association between lipid profiles and subsequent cardiovascular disease (CVD) in young adults.

METHODS

Medical records of 1,909,362 young adults (20-49 years old) without a prior history of CVD and not taking lipid-lowering medications were extracted. We conducted multivariable Cox regression analyses to identify the association between the number of abnormal lipid profiles and incident CVD.

RESULTS

After a mean follow-up of 3.4±2.6 years, myocardial infarction (MI), angina pectoris (AP), stroke, and heart failure (HF) developed in 2,575 (0.1%), 26,006 (1.4%), 10,748 (0.6%), and 24,875 (1.3%) subjects, respectively. The incidence of MI, AP, and HF increased with the number of abnormal lipid profiles in both men and women, whereas the incidence of stroke increased with the number of abnormal lipid profiles only in men but not in women. Multivariable adjusted hazard ratios (HRs) for MI per 1-point higher abnormal lipid profile were 1.57 (95% confidence interval [CI] 1.49-1.65) in men and 1.25 (95% CI 1.07-1.47) in women. HRs for AP, stroke, and HF per 1-point higher abnormal lipid profile were 1.14 (95% CI 1.12-1.16), 1.06 (95% CI 1.02-1.09), and 1.10 (95% CI 1.08-1.12) in men and 1.18 (95% CI 1.13-1.23), 1.09 (95% CI 1.03-1.16), and 1.10 (95% CI 1.05-1.14) in women.

CONCLUSION

Our analysis demonstrated an association between the number of abnormal lipid profiles and incident CVD in both men and women. The association between the number of abnormal lipid profiles and incident MI was pronounced in men.

The Lifelong Health Support 10: a Japanese prescription for a long and healthy life

BACKGROUND

Although the age-adjusted incidence and mortality of cancer and cardiovascular disease (CVD) have been decreasing steadily in Japan, both diseases remain major contributors to morbidity and mortality along with the aging society. Herein, we aim to provide a prescription of 10 health tips for long and healthy life named the "Lifelong Health Support 10 (LHS10)."

METHOD

The LHS10 was developed by the preventive medicine specialists at the National Cerebral and Cardiovascular Center in Suita, where it has been used for health guidance to prevent CVD, cancer, and cognitive decline in addition to their major risk factors such as hypertension, diabetes, and obesity. It consisted of the lifestyle modification recommendations of the 2014 Japanese Society of Hypertension guidelines and the 2017 Japan Atherosclerosis Society Guidelines for preventing atherosclerotic CVD. Further, it came in line with other international lifestyle modification guidelines. In this narrative review, we summarized the results of several Japanese epidemiological studies investigating the association between the LHS10 items and the risk of cancer, CVD, and other chronic diseases including dementia, diabetes, and chronic kidney disease.

RESULTS

The LHS10 included avoiding smoking and secondhand smoke exposure, engaging in physical activity, refraining from excessive alcohol drinking, reducing fried foods and sugary soft drinks, cutting salt in food, consuming more vegetables, fruits, fish, soy foods, and fibers, and maintaining proper body weight. All items of the LHS10 were shown to reduce the risk of cancer, CVD, and other chronic diseases.

CONCLUSIONS

The LHS10 can be a helpful tool for health guidance.

Developing a Stroke Risk Prediction Model Using Cardiovascular Risk Factors: The Suita Study

INTRODUCTION

Stroke remains a major cause of death and disability in Japan and worldwide. Detecting individuals at high risk for stroke to apply preventive approaches is recommended. This study aimed to develop a stroke risk prediction model among urban Japanese using cardiovascular risk factors.

METHODS

We followed 6,641 participants aged 30-79 years with neither a history of stroke nor coronary heart disease. The Cox proportional hazard model estimated the risk of stroke incidence adjusted for potential confounders at the baseline survey. The model's performance was assessed using the receiver operating characteristic curve and the Hosmer-Lemeshow statistics. The internal validity of the risk model was tested using derivation and validation samples. Regression coefficients were used for score calculation.

RESULTS

During a median follow-up duration of 17.1 years, 372 participants developed stroke. A risk model including older age, current smoking, increased blood pressure, impaired fasting blood glucose and diabetes, chronic kidney disease, and atrial fibrillation predicted stroke incidence with an area under the curve = 0.76 and p value of the goodness of fit = 0.21. This risk model was shown to be internally valid (p value of the goodness of fit in the validation sample = 0.64). On a risk score from 0 to 26, the incidence of stroke for the categories 0-5, 6-7, 8-9, 10-11, 12-13, 14-15, and 16-26 was 1.1%, 2.1%, 5.4%, 8.2%, 9.0%, 13.5%, and 18.6%, respectively.

CONCLUSION

We developed a new stroke risk model for the urban general population in Japan. Further research to determine the clinical practicality of this model is required.

Uric acid and incident atrial fibrillation of 14 years population-based cohort study: The Suita Study

BACKGROUND

Higher baseline uric acid (UA) was significantly associated with higher atrial fibrillation (AF) incidence in Japanese women. However, no prospective study is evident in the association between UA and incident AF in Japanese urban residents.

METHODS

A total of 6863 participants (aged 30-79 years; 47% men) without prior AF were followed for 13.9 years on average in the Suita Study. According to the UA categories, cox proportional hazards regression models were used to estimating the Hazard Ratios (HRs) and 95% confidence intervals (CIs) for incident AF.

RESULTS

During 95178 person-years of follow-up, we observed 311 cases of incident AF (204 cases in men and 107 cases in women). Compared to the subjects with UA of 4.0-4.9 mg/dL, multivariable-adjusted HR (95% CIs) of incident AF was 1.50 (1.01-2.25) (P = .047) for the subjects with UA ≥7.0 mg/dL.

CONCLUSION

High UA was associated with an increased risk for incident AF in the Japanese population.

Risk Factors and Lifestyles in the Development of Atrial Fibrillation Among Individuals Aged 20-39 Years

Epidemiological evidence on the relationship of modifiable risk factors and lifestyles with incident atrial fibrillation (AF) in young adults remains insufficient. We aimed to identify the determinants of AF among young adults using a nationwide epidemiological database. Medical records of 286,876 individuals (20-39 years) without prior history of cardiovascular disease were extracted from the JMDC Claims Database. We analyzed the association of modifiable risk factors with the incidence of AF. The median (interquartile range) age was 34 (29-37) years, and 54.4% were men. After a mean follow-up of 1,017 ± 836 days, 267 individuals (0.1%) developed AF. Multivariable Cox regression analysis demonstrated that high waist circumference, hypertension, cigarette smoking, and poor sleep quality as well as age and sex were associated with increased incidence of AF. Kaplan-Meier curves showed that number of modifiable components including high waist circumference, hypertension, cigarette smoking, and poor sleep quality clearly stratified the risk of AF development (Log rank test, p < 0.001). Age- and sex-adjusted Cox regression analyses showed individuals with one (hazard ratio [HR] 1.56, 95% confidence interval [CI] 1.13-2.18), two (HR 2.03, 95% CI 1.40-2.95), three (HR 3.48, 95% CI 2.19-5.54), and four (HR 10.78, 95% CI 5.26-22.11) components were associated with an increased incidence of AF compared with individuals with no components. In conclusion, high waist circumference, hypertension, cigarette smoking, and poor sleep quality were associated with the development of AF among young adults, suggesting the importance of maintaining these modifiable factors for the primordial prevention of AF in young adults.

Semiquantitative assessed proteinuria and risk of heart failure: Analysis of a nationwide epidemiological database

BACKGROUND

Heart failure (HF) is increasing in prevalence worldwide. We explored whether adults with trace and positive proteinuria were at a high risk for incident HF compared with those with negative proteinuria using a nationwide epidemiological database.

METHODS

This is an obserevational cohort study using the JMDC Claims Database collected between 2005 and 2020. This is a population-based sample (n = 1,021,943; median age [interquartile range], 44 [37-52] years; 54.8% men). No participants had a known history of cardiovascular disease. Each participant was categorized into three groups according to the urine dipstick test results: negative proteinuria (n = 902,273), trace proteinuria (n = 89,599), and positive proteinuria (≥1+) (n = 30,071). The primary outcome was HF. The secondary outcomes were myocardial infarction, stroke, and atrial fibrillation. We performed multivariable Cox regression analyses to identify the association between the proteinuria category and incient HF and other cardiovascular disease events.

RESULTS

Over a mean follow-up of 1,150 ± 920 days, 17,182 incident HF events occurred. After multivariable adjustment, hazard ratios (HRs) for HF events were 1.09 (95% confidence interval [CI], 1.03-1.15) and 1.59 (95% CI, 1.49-1.70) for trace proteinuria and positive proteinuria vs. negative proteinuria, respectively. This association was present irrespective of clinical characteristics. A stepwise increase in the risk of myocardial infarction, stroke, and atrial fibrillation with proteinuria category was also observed. Our primary results were confirmed in participants after multiple imputation for missing values and in those having no medications for hypertension, diabetes mellitus, and dyslipidemia. Discriminative predictive value for HF events improved by adding the results of urine dipstick test to traditional risk factors (net reclassification improvement 0.0497, 95% CI 0.0346-0.0648, p < 0.001).

CONCLUSIONS

Not only positive proteinuria but also trace proteinuria was associated with a greater incidence of HF in the general population. Semiquantitative assessment of proteinuria would be informative for the risk stratification of HF.

Risk Prediction Model for Incident Atrial Fibrillation in a General Japanese Population - The Hisayama Study

BACKGROUND

The risk prediction of incident atrial fibrillation (AF) is useful to prevent AF and its complications. The aim of this study is to develop a new risk prediction model for incident AF using the prospective longitudinal data from a general Japanese population.Methods and Results:A total of 2,442 community-dwelling AF-free residents aged ≥40 years were followed up from 1988 to 2012 (46,422 person-years). The development of AF was confirmed by a standard 12-lead electrocardiogram at repeated health examinations and by medical records at clinics or hospitals. The risk prediction model for incident AF was developed using a Cox proportional hazards model. During the follow up, 230 AF events were confirmed. Age, sex, systolic blood pressure, waist circumference, estimated glomerular filtration rate, abnormal cardiac murmur, high R-wave amplitude, and arrhythmia other than AF were selected for inclusion in the model. This model showed good discrimination (Harrell's c statistics: 0.785) and calibration (Greenwood-Nam-D'Agostino test: P=0.87) for AF risk at 10 years.

CONCLUSIONS

The new risk prediction model showed good performance on the individual risk assessment of the future onset of AF in a general Japanese population. As this model included commonly used clinical parameters, it may be useful for determining the requirements for the careful evaluation of AF, such as frequent electrocardiogram examinations in clinical settings, and subsequent reductions in the risk of AF-related complications.

Prediction models for atrial fibrillation applicable in the community: a systematic review and meta-analysis

Aims

Atrial fibrillation (AF) is a common arrhythmia associated with an increased stroke risk. The use of multivariable prediction models could result in more efficient primary AF screening by selecting at-risk individuals. We aimed to determine which model may be best suitable for increasing efficiency of future primary AF screening efforts.

Methods and results

We performed a systematic review on multivariable models derived, validated, and/or augmented for AF prediction in community cohorts using Pubmed, Embase, and CINAHL (Cumulative Index to Nursing and Allied Health Literature) through 1 August 2019. We performed meta-analysis of model discrimination with the summary C-statistic as the primary expression of associations using a random effects model. In case of high heterogeneity, we calculated a 95% prediction interval. We used the CHARMS (Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies) checklist for risk of bias assessment. We included 27 studies with a total of 2 978 659 unique participants among 20 cohorts with mean age ranging from 42 to 76 years. We identified 21 risk models used for incident AF risk in community cohorts. Three models showed significant summary discrimination despite high heterogeneity: CHARGE-AF (Cohorts for Heart and Aging Research in Genomic Epidemiology) [summary C-statistic 0.71; 95% confidence interval (95% CI) 0.66–0.76], FHS-AF (Framingham Heart Study risk score for AF) (summary C-statistic 0.70; 95% CI 0.64–0.76), and CHA₂DS₂-VASc (summary C-statistic 0.69; 95% CI 0.64–0.74). Of these, CHARGE-AF and FHS-AF had originally been derived for AF incidence prediction. Only CHARGE-AF, which comprises easily obtainable measurements and medical history elements, showed significant summary discrimination among cohorts that had applied a uniform (5-year) risk prediction window.

Conclusion

CHARGE-AF appeared most suitable for primary screening purposes in terms of performance and applicability in older community cohorts of predominantly European descent.

Relationship Between Radiation Exposure and Incident Atrial Fibrillation Among Atomic Bomb Survivors

Background: Atrial fibrillation (AF) is a common arrhythmia. Although radiation exposure is associated with an elevated risk of cardiovascular disease, the effects of radiation on arrhythmia, especially AF, are unclear. We evaluated the relationship between radiation and AF in a cohort of atomic bomb survivors. Methods and Results: From a baseline enrollment period (1967-1969) to 2009, 7,379 Hiroshima and Nagasaki atomic bomb survivors (mean baseline age 50.6 years, 65.8% women, 72.9% from Hiroshima) without AF and who had been exposed to estimated radiation doses between 0 and 3.614 Gy were followed-up once every 2 years. AF was identified by 12-lead electrocardiograms and medical records. Treating age as the time scale, AF incidence was modeled with Cox proportional hazards models adjusting for demographics, AF risk factors, and radiation. We modeled radiation as both a continuous variable and categorized according to radiation dose (Control [<0.005 Gy] and 5 equal-sized groups based on radiation dose quintiles in the cohort). Over 4 decades of follow-up, we identified 276 AF cases in 176,687 person-years, for an incidence rate of 1.56 per 1,000 person-years. After adjusting for sex and city, neither categorized, linear, nor linear-quadratic models showed substantive evidence of radiation effects. Similar results were obtained after adjusting for AF risk factors. Conclusions: There were no clear positive associations between radiation dose and AF risk, rather null or non-significant inverse associations.

The Risk of Fasting Triglycerides and its Related Indices for Ischemic Cardiovascular Diseases in Japanese Community Dwellers: the Suita Study

Aim: A prospective cohort study in a Japanese urban general population was performed to investigate whether triglyceride (TG) and its related indices were associated with the risk for the incidence of ischemic cardiovascular disease (CVD) after the adjustment for low-density lipoprotein cholesterol (LDL-C) in Asian community dwellers.

Methods: A 15.1-year prospective cohort study was performed in 6,684 Japanese community dwellers aged 30–79 years without a history of CVD and whose fasting TG levels were ＜400 mg/dL. After adjusting for covariates, including LDL-C, the multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) of the deciles (D) of TG and those of 1-standard deviation (SD) increment of log-transformed TG (1-SD of TG) according to LDL-C level (≥ 140 and ＜140 mg/dL) for ischemic CVD incidence were estimated. The multivariable-adjusted HRs and 95%CIs of the quintiles (Q) of TG, TG/HDL-C, and the cardiometabolic index (CMI) for ischemic CVD were also estimated.

Results: In 101,230 person-years, 464 ischemic CVD cases occurred. For D ₁₀ of TG, the HR (95%CI) was 1.56 (1.05–2.32), and for 1-SD of TG, it was 1.30 (1.00–1.70) in participants with LDL-C ＜140 mg/dL and 1.07 (0.77–1.50) in those with LDL-C ≥ 140 mg/dL. For Q ₅ of the CMI, the multivariable-adjusted HR was higher than those of TG and TG/HDL-C.

Conclusions: Fasting TG was an independent predictor for ischemic CVD incidence after adjusting for LDL-C in Japanese community dwellers with TG ＜400 mg/dL. Among TG, TG/HDL-C, and the CMI, the CMI could be the most powerful predictor for ischemic CVD.

Utility of risk prediction models to detect atrial fibrillation in screened participants

AIMS

Atrial fibrillation (AF) is associated with higher risk of stroke. While the prevalence of AF is low in the general population, risk prediction models might identify individuals for selective screening of AF. We aimed to systematically identify and compare the utility of established models to predict prevalent AF.

METHODS AND RESULTS

Systematic search of PubMed and EMBASE for risk prediction models for AF. We adapted established risk prediction models and assessed their predictive performance using data from 2.5M individuals who attended vascular screening clinics in the USA and the UK and in the subset of 1.2M individuals with CHA2DS2-VASc ≥2. We assessed discrimination using area under the receiver operating characteristic (AUROC) curves and agreement between observed and predicted cases using calibration plots. After screening 6959 studies, 14 risk prediction models were identified. In our cohort, 10 464 (0.41%) participants had AF. For discrimination, six prediction model had AUROC curves of 0.70 or above in all individuals and those with CHA2DS2-VASc ≥2. In these models, calibration plots showed very good concordance between predicted and observed risks of AF. The two models with the highest observed prevalence in the highest decile of predicted risk, CHARGE-AF and MHS, showed an observed prevalence of AF of 1.6% with a number needed to screen of 63. Selective screening of the 10% highest risk identified 39% of cases with AF.

CONCLUSION

Prediction models can reliably identify individuals at high risk of AF. The best performing models showed an almost fourfold higher prevalence of AF by selective screening of individuals in the highest decile of risk compared with systematic screening of all cases.

REGISTRATION

This systematic review was registered (PROSPERO CRD42019123847).

Clinical risk scores for the prediction of incident Atrial Fibrillation: A modernized review

Atrial fibrillation (AF) is considered the most common sustained arrhythmia. Major cardiovascular risk factors that have been identified to initiate and perpetuate AF include age, sex, arterial hypertension, heart failure, valvular heart disease and diabetes mellitus. In the literature, several studies aimed to formulate easily - applied and accurate risk stratification scores, based on antecedent cardiovascular events, comorbidities and biomarkers for the prediction of new-onset AF. The present narrative review addresses the most universally accepted and efficient clinical scores, with an extended applicability in different populations and ages, particularly scores derived from the Framingham Heart Study, the Atherosclerosis Risk in Communities, the Malmo Diet and Cancer Study, as well as the CHARGE-AF, the CHADS2, CHA₂DS₂-VASc, HATCH and CH2EST scores. Identification of incident AF can be challenging, thus dictating for utilization of validated clinical instruments in everyday clinical practice.

Risk prediction for new-onset atrial fibrillation using the Minnesota code electrocardiography classification system

Background

Few risk models are available to predict future onset of atrial fibrillation (AF) in workers. We aimed to develop risk prediction models for new-onset AF, using annual health checkup (HC) data with electrocardiogram findings.

Methods and Results

We retrospectively included 56,288 factory or office workers (mean age = 51.5 years, 33.0% women) who underwent a HC at a medical center and fulfilled the following criteria; age ≥ 40 years, no history of AF, and greater than 1 annual follow-up HC in 2013–2016. Using Cox models with the Akaike information criterion, we developed and compared prediction models for new-onset AF with and without the Minnesota code information. We externally validated the discrimination accuracy of the models in a general Japanese population cohort, the Hisayama cohort. During the median 3.0-year follow-up, 209 (0.37%) workers developed AF. Age, sex, waist circumference, blood pressure, LDL cholesterol, and γ-GTP were associated with new-onset of AF. Using the Minnesota code information, the AUC significantly improved from 0.82 to 0.84 in the derivation cohort and numerically improved from 0.78 to 0.79 in the validation cohort, and from 0.77 to 0.79 in the Hisayama cohort. The NRI and IDI significantly improved in all and male subjects in both the derivation and validation cohorts, and in female subjects in both the validation and the Hisayama cohorts.

Conclusions

We developed useful risk model with Minnesota code information for predicting new-onset AF from large worker population validated in the original and external cohorts, although study interpretation is limited by small improvement of AUC.

Genetically determined tobacco and alcohol use and risk of atrial fibrillation

BACKGROUND

The causality between the use of alcohol and cigarettes and atrial fibrillation (AF) remains controversial. We conducted a Mendelian randomization (MR) study to evaluate the association of genetic variants related to tobacco and alcohol use with AF.

METHODS

Single nucleotide polymorphisms (SNPs) related to smoking initiation (N = 374), age at initiation of regular smoking (N = 10), cigarettes per day (N = 55), and smoking cessation (N = 24) were derived from a genome-wide association studies (GWAS) of tobacco use (N = 1.2 million individuals). SNPs related to heavy alcohol use (N = 6) were derived from a GWAS of UK biobank (N = 125,249 individuals). The genetically matching instrumented variables were obtained from the GWAS of AF (N = 588,190 individuals). The estimates between tobacco and alcohol use and AF were combined by inverse-variance weighted (IVW), simple median, weighted median, MR-robust adjusted profile score method, MR-PRESSO, and multivariable MR.

RESULTS

A total of 65,446 AF patients and 522,744 referents were included. In the IVW analysis, the odds ratio per one-unit increase of smoking initiation was 1.11 (95% CI, 1.06-1.16; P = 3.35 × 10-6) for AF. Genetically predicted age at initiation of regular smoking, cigarettes per day and smoking cessation were not associated with AF. The IVW estimate showed that heavy alcohol consumption increased AF risk (OR, 1.11; 95% CI, 1.04-1.18; P = 0.001). The results were consistent in complementary analyses and multivariable MR.

CONCLUSION

Our MR study indicated that regular smoking was associated with increased risk of AF, no matter the age at initiation of regular smoking, or the number of cigarettes smoked per day. Genetically predicted heavy alcohol consumption increased the risk of AF.

Lipid Profile and Subsequent Cardiovascular Disease among Young Adults Aged < 50 Years

Epidemiological evidence on the relationship between lipid profile and cardiovascular disease (CVD) events in young adults remains insufficient. Thus, we sought to explore the association of lipid profile with subsequent CVD among young adults. Medical records of 1,451,997 young adults (20 to 49 years old) without prior history of CVD and not taking lipid lowering medications were extracted from the Japan Medical Data Center, a nationwide epidemiological database. We conducted multivariable Cox regression analyses to identify the association between lipid profile and the subsequent risk of CVD and used multiple imputation for missing data on body mass index, waist circumference, hypertension, diabetes mellitus, and cigarette smoking in our database. The mean age was 39.0 ± 7.4 years, and 58.5% were men. After a mean follow-up of 1,148 ± 893 days, myocardial infarction, angina pectoris, stroke, and heart failure developed in 1,638 (0.1%), 15,887 (1.1%), 5,593 (0.4%), and 14,351 (1.0%) subjects, respectively. Multivariable Cox regression analyses including covariates after multiple imputation for missing values demonstrated that LDL-C ≥ 140 mg/dL, HDL-C < 40 mg/dL, and triglycerides ≥ 150 mg/dL were independently associated with the incidence of myocardial infarction, angina pectoris, and heart failure. However, they were not associated with the incidence of stroke. Multivariable Cox regression analyses including the number of abnormal lipid profiles and covariates showed that the incidence of myocardial infarction, angina, and heart failure increased stepwise with the number of abnormal lipid profiles. However, the number of abnormal lipid profiles was not associated with the subsequent risk of stroke. In conclusion, the comprehensive analysis of a nationwide epidemiological database demonstrated a close relationship between lipid profile and subsequent CVD, suggesting the importance of maintaining an optimal lipid profile for the primary prevention of CVD in young generations.

C2HEST score predicts clinical outcomes in heart failure with preserved ejection fraction: a secondary analysis of the TOPCAT trial

BACKGROUND

The C₂HEST score has been validated for predicting AF in the general population or post-stroke patients. We aimed to assess whether this risk score could predict incident AF and other clinical outcomes in heart failure with preserved ejection fraction (HFpEF) patients.

METHODS

A total of 2202 HFpEF patients without baseline AF in the TOPCAT trial were stratified by baseline C₂HEST score. Cox proportional hazard model and competing risk regression model was used to explore the relationship between C₂HEST score and outcomes, including incident AF, stroke, all-cause death, cardiovascular death, any hospitalization, and HF hospitalization. The discriminative ability of the C₂HEST score for various outcomes was assessed by calculating the area under the curve (AUC).

RESULTS

The incidence rates of incident AF, stroke, all-cause death, cardiovascular death, any hospitalization, and HF hospitalization were 1.79, 0.70, 3.81, 2.42, 15.50, and 3.32 per 100 person-years, respectively. When the C₂HEST score was analyzed as a continuous variable, increased C₂HEST score was associated with increased risk of incident AF (HR 1.50, 95% CI 1.29-1.75), as well as increased risks of all-cause death, cardiovascular death, any hospitalization, and HF hospitalization. The AUC for the C₂HEST score in predicting incident AF (0.694, 95% CI 0.640-0.748) was higher than all-cause death, cardiovascular death, any hospitalization, or HF hospitalization.

CONCLUSIONS

The C₂HEST score could predict the risk of incident AF as well as death and hospitalization with moderately good predictive abilities in patients with HFpEF. Its simplicity may allow the possibility of quick risk assessments in busy clinical settings.