Risk factors for new-onset atrial fibrillation in patients with chronic obstructive pulmonary disease: a systematic review and meta-analysis

Detrimental Impact of Atrial Fibrillation among Patients Hospitalized for Acute Exacerbation of COPD: Results of a Population-Based Study in Spain from 2016 to 2021

Background/Objectives: To analyze changes in the prevalence of atrial fibrillation (AF) in patients hospitalized for acute exacerbation of chronic obstructive pulmonary disease (AE-COPD); to evaluate hospital outcomes according to AF status, assessing sex differences; to identify factors associated with AF presence; and to analyze variables associated with in-hospital mortality (IHM) in AE-COPD patients with AF. Methods: We used data from the Registry of Specialized Care Activity-Basic Minimum Data Set (RAE-CMBD) to select patients aged ≥40 years with COPD in Spain (2016-2021). We stratified the study population according to AF presence and sex. The propensity score matching (PSM) methodology was employed to create comparable groups based on age, admission year, and comorbidities at the time of hospitalization. Results: We identified 399,196 hospitalizations that met the inclusion criteria. Among them, 20.58% had AF. The prevalence of AF rose from 2016 to 2021 (18.26% to 20.95%), though the increase was only significant in men. The median length of hospital stay (LOHS) and IHM were significantly higher in patients with AF than in those without AF. After PSM, IHM remained significantly higher for man and women with AF. Older age, male sex, and several comorbidities were factors associated with AF. Additionally, older age, male sex, different comorbidities including COVID-19, hospitalization in the year 2020, mechanical ventilation, and intensive care unit (ICU) admission were associated with higher IHM in patients with AE-COPD and AF. Conclusions: AF prevalence was high in patients hospitalized for AE-COPD, was higher in men than in women, and increased over time. AF presence was associated with worse outcomes. The variables associated with IHM in hospitalized AE-COPD patients with AF were older age, male sex, different comorbidities including COVID-19 presence, hospitalization in the year 2020, need of mechanical ventilation, and ICU admission.

Factors associated with non-fatal heart failure and atrial fibrillation or flutter within the first 30 days post COPD exacerbation: a nested case-control study

BACKGROUND

An immediate, temporal risk of heart failure and arrhythmias after a Chronic Obstructive Pulmonary Disease (COPD) exacerbation has been demonstrated, particularly in the first month post-exacerbation. However, the clinical profile of patients who develop heart failure (HF) or atrial fibrillation/flutter (AF) following exacerbation is unclear. Therefore we examined factors associated with people being hospitalized for HF or AF, respectively, following a COPD exacerbation.

METHODS

We conducted two nested case-control studies, using primary care electronic healthcare records from the Clinical Practice Research Datalink Aurum linked to Hospital Episode Statistics, Office for National Statistics for mortality, and socioeconomic data (2014-2020). Cases had hospitalization for HF or AF within 30 days of a COPD exacerbation, with controls matched by GP practice (HF 2:1;AF 3:1). We used conditional logistic regression to explore demographic and clinical factors associated with HF and AF hospitalization.

RESULTS

Odds of HF hospitalization (1,569 cases, 3,138 controls) increased with age, type II diabetes, obesity, HF and arrhythmia history, exacerbation severity (hospitalization), most cardiovascular medications, GOLD airflow obstruction, MRC dyspnea score, and chronic kidney disease. Strongest associations were for severe exacerbations (adjusted odds ratio (aOR)=6.25, 95%CI 5.10-7.66), prior HF (aOR=2.57, 95%CI 1.73-3.83), age≥80 years (aOR=2.41, 95%CI 1.88-3.09), and prior diuretics prescription (aOR=2.81, 95%CI 2.29-3.45). Odds of AF hospitalization (841 cases, 2,523 controls) increased with age, male sex, severe exacerbation, arrhythmia and pulmonary hypertension history and most cardiovascular medications. Strongest associations were for severe exacerbations (aOR=5.78, 95%CI 4.45-7.50), age≥80 years (aOR=3.15, 95%CI 2.26-4.40), arrhythmia (aOR=3.55, 95%CI 2.53-4.98), pulmonary hypertension (aOR=3.05, 95%CI 1.21-7.68), and prescription of anticoagulants (aOR=3.81, 95%CI 2.57-5.64), positive inotropes (aOR=2.29, 95%CI 1.41-3.74) and anti-arrhythmic drugs (aOR=2.14, 95%CI 1.10-4.15).

CONCLUSIONS

Cardiopulmonary factors were associated with hospitalization for HF in the 30 days following a COPD exacerbation, while only cardiovascular-related factors and exacerbation severity were associated with AF hospitalization. Understanding factors will help target people for prevention.

Predictive nomogram models for atrial fibrillation in COPD patients: A comprehensive analysis of risk factors and prognosis

The aim of the present study was to identify the independent risk factors and prognostic indicators for atrial fibrillation (AF) in patients with chronic obstructive pulmonary disease (COPD) and to develop predictive nomogram models. This retrospective study included a total of 286 patients with COPD who were admitted to the Second Affiliated Hospital of Guilin Medical College between January 2020 and May 2022. The average age of the patients was 77.11±8.67 years. Based on the presence or absence of AF, the patients were divided into two groups: The AF group (n=87) and the non-AF group (n=199). Logistic regression analysis was conducted to identify variables with significant differences between the two groups. Nomogram models were constructed to predict the occurrence of AF in COPD patients and to assess prognosis. Survival analysis was performed using the Kaplan-Meier method. The follow-up period for the present study extended until April 31, 2023. Survival time was defined as the duration from the date of the interview to the date the participant succumbed or the end of the follow-up period. In the present study, age, uric acid (UA) and left atrial diameter (LAD) were found to be independent risk factors for the development of AF in patients diagnosed with COPD. The stepwise logistic regression analysis revealed that age had an odds ratio (OR) of 1.072 [95% confidence interval (CI): 1.019-1.128; P=0.007], UA had an OR of 1.004 (95% CI: 1.001-1.008; P=0.010) and LAD had an OR of 1.195 (95% CI: 1.098-1.301; P<0.001). Univariate and multivariate Cox regression analysis revealed that LAD and UA were independent prognostic factors for long-term mortality in COPD patients with AF. LAD had a hazard ratio (HR) of 1.104 (95% CI: 1.046-1.165; P<0.001) and UA had an HR of 1.004 (95% CI: 1.000-1.008; P=0.042). Based on these findings, predictive nomogram models were developed for AF in COPD patients, which demonstrated good discrimination ability with an area under the curve of 0.886. The prognostic nomogram for COPD patients with AF also showed good predictive accuracy with a concordance index of 0.886 (95% CI: 0.842-0.930). These models can provide valuable information for risk assessment and prognosis evaluation in clinical practice. Age, UA and LAD are independent risk factors for AF in COPD patients. The developed nomogram models provide a reliable tool for predicting AF in COPD patients and for prognosis assessment.

Risk of Death and Cardiovascular Events Following an Exacerbation of COPD: The EXACOS-CV US Study

Purpose

This study estimated the magnitude and duration of risk of cardiovascular events and mortality following acute exacerbations of chronic obstructive pulmonary disease (AECOPD), and whether risks varied by number and severity of exacerbation in a commercially insured population in the United States.

Methods

This was a retrospective cohort study of newly diagnosed COPD patients ≥40 years old in the Healthcare Integrated Research Database from 2012 to 2019. Patients experiencing exacerbations comprised the "exacerbation cohort". Moderate exacerbations were outpatient visits with contemporaneous antibiotic or glucocorticoid administration; severe exacerbations were emergency department visits or hospitalizations for AECOPD. Follow-up started on the exacerbation date. Distribution of time between diagnosis and first exacerbation was used to assign index dates to the "unexposed" cohort. Cox proportional hazards models estimated risks of a cardiovascular event or death following an exacerbation adjusted for medical and prescription history and stratified by follow-up time, type of cardiovascular event, exacerbation severity, and rank of exacerbation (first, second, or third).

Results

Among 435,925 patients, 170,236 experienced ≥1 exacerbation. Risk of death was increased for 2 years following an exacerbation and was highest during the first 30 days (any exacerbation hazard ratio (HR)=1.79, 95% CI=1.58-2.04; moderate HR=1.22, 95% CI=1.04-1.43; severe HR=5.09, 95% CI=4.30-6.03). Risks of cardiovascular events were increased for 1 year following an AECOPD and highest in the first 30-days (any exacerbation HR=1.34, 95% CI=1.23-1.46; moderate HR=1.23 (95% CI 1.12-1.35); severe HR=1.93 (95% CI=1.67-2.22)). Each subsequent AECOPD was associated with incrementally higher rates of both death and cardiovascular events.

Conclusion

Risk of death and cardiovascular events was greatest in the first 30 days and rose with subsequent exacerbations. Risks were elevated for 1-2 years following moderate and severe exacerbations, highlighting a sustained increased cardiopulmonary risk associated with exacerbations.

Spirometry in atrial fibrillation: what's the catch?

INTRODUCTION

People with COPD rarely have COPD alone, and the commonest co-morbidities occurring with COPD are cardiovascular. Whilst multiple studies have explored the association between major cardiovascular events and COPD, less attention has been paid to arrhythmias, specifically atrial fibrillation (AF). AF and COPD frequently occur together, posing challenges in diagnosis and management. In this review, we describe the relationship between AF and COPD epidemiologically and physiologically, demonstrating the role of spirometry as a diagnostic and disease management tool.

AREAS COVERED

We provide epidemiological evidence that COPD and AF are independent risk factors for one another, that either disease is highly prevalent amongst people with the other, and that they have shared risk factors; all of which contribute to adverse prognostic. We elucidated common pathophysiological mechanisms implicated in AF-COPD. We ultimately present the epidemiological and physiological evidence with a view to highlight specific areas where we feel spirometry is of value in the management of AF-COPD.

EXPERT OPINION

AF and COPD commonly co-occur, there is often diagnostic delay, increased risk of reduced cardioversion success, and missed opportunity to intervene to reduce stroke risk. Greater awareness and timelier diagnosis and guideline directed management may improve outcomes for people with both diseases.

Prediction of post-operative atrial fibrillation in patients after cardiac surgery using heart rate variability

PURPOSE

Post-operative atrial fibrillation (PoAF) occurs in ~ 30% of patients after cardiac surgery. The etiology of PoAF is complex, but a disbalance in autonomic systems plays an important role. The goal of this study was to assess whether pre-operative heart rate variability analysis can predict the risk of PoAF.

METHODS

Patients without a history of AF with an indication for cardiac surgery were included. Two-hour ECG recordings one day before surgery was used for the HRV analysis. Univariate and multivariate logistic regression, including all HRV parameters, their combination, and clinical variables, were calculated to find the best predictive model for post-operative AF.

RESULTS

One hundred and thirty-seven patients (33 women) were enrolled in the study. PoAF occurred in 48 patients (35%, AF group); the remaining 89 patients were in the NoAF group. AF patients were significantly older (69.1 ± 8.6 vs. 63.4 ± 10.5 yrs., p = 0.002), and had higher CHA₂DS₂-VASc score (3 ± 1.4 vs. 2.5 ± 1.3, p = 0.01). In the multivariate regression model, parameters independently associated with higher risk of AF were pNN50, TINN, absolute power VLF, LF and HF, total power, SD2, and the Porta index. A combination of clinical variables with HRV parameters in the ROC analysis achieved an AUC of 0.86, a sensitivity of 0.95, and a specificity of 0.57 and was more effective in PoAF prediction than a combination of clinical variables alone.

CONCLUSION

A combination of several HRV parameters is helpful in predicting the risk of PoAF. Attenuation of heart rate variability increases the risk for PoAF.

Impact of COPD or Asthma on the Risk of Atrial Fibrillation: A Systematic Review and Meta-Analysis

Background:

Respiratory diseases related to chronic pulmonary ventilation dysfunction are mainly composed of chronic obstructive pulmonary disease (COPD) and asthma. Our meta-analysis aimed to illustrate the association of COPD or asthma with risk of atrial fibrillation (AF).

Methods

We systematically searched the databases of the PubMed, Embase, and Cochrane library until December 2021 for studies focusing on the relationship between COPD or asthma and AF risk. Due to the potential heterogeneity across studies, the random-effects model was used to pool the studies.

Results

Our meta-analysis included 14 studies. Based on the random-effects model, the pooled analysis showed that COPD (risk ratio[RR] = 1.74, 95% confidence interval [CI]: 1.70–1.79) and asthma (RR = 1.08, 95% CI: 1.04–1.12) were significantly associated with an increased risk of AF. The results did not change after each study was excluded.

Conclusion

Our current data suggested that COPD or asthma with associated with an increased risk of AF.

Frequency of Atrial Fibrillation in Patients Presenting With Decompensated Heart Failure

Background

Atrial fibrillation (AF) is a common concern in patients with heart disease, especially those with acute decompensated heart failure (ADHF). We conducted a cross-sectional study to determine the frequency of AF and associated risk factors among patients with ADHF at a tertiary care hospital in Peshawar, Pakistan.

Methods

We conducted a cross-sectional analytical study of hospitalized patients with ADHF treated in a tertiary care hospital in Peshawar, Pakistan, from June 5 to October 30, 2021. The study's primary outcome was the proportion of patients with ADHF who had AF, and our secondary outcome was examining the risk factors for AF. The College of Physicians and Surgeons Pakistan provided ethical approval of the study design. Data were analyzed using IBM SPSS Statistics for Windows version 24.0 (IBM Corp., Armonk, NY, USA). We applied the chi-square test to compare the proportion of AF concerning risk factors (i.e., comorbidities).

Results

One hundred ninety-four patients with ADHF were included in the study; 54.6% were male and 45.4% female. Most (56.7%) were older than 60, and 38.1% were aged 40-60. The prevalence of AF was 38.1%. Diabetes, hypertension, previous stroke, myocardial infarction (MI), and chronic obstructive pulmonary disease (COPD) were the most common comorbidities. All patients with ADHF with AF also had MI and hypertension. Patients of known coronary artery disease (CAD) but without MI, previous percutaneous coronary intervention (PCI), or coronary artery bypass graft (CABG) surgery were less associated with AF than other comorbidities.

Conclusions

We conducted this study to determine the incidence of AF among patients with ADHF. AF occurs in a significant amount of patients with ADHF, and the risk factors associated with AF in these patients include hypertension, history of MI, diabetes, and COPD. Healthcare professionals should screen patients with ADHF for AF, especially those with common risk factors.

Obesity phenotypes and their relationships with atrial fibrillation

Background

This study assessed the associations of metabolic obesity phenotypes with the risk of atrial fibrillation (Afib).

Methods

This prospective cohort study categorized Taiwanese adults according to their body mass index (BMI) and metabolic health status at baseline. We assigned the participants to the underweight (BMI < 18.5 kg/m²), normal weight (BMI = 18.5-23.9 kg/m²), and overweight/obesity groups (BMI ≥ 24 kg/m²). Metabolically healthy was defined as absence of hypertension, diabetes, and hyperlipidemia and the presence of healthy metabolic profiles.

Results

In total, 5,742 adults were included. During a median follow-up of 13.7 years, 148 patients developed Afib. Compared to the metabolically healthy normal weight group, the risk of Afib was significantly higher than those in the metabolically unhealthy overweight/obesity (hazard ratio = 2.20, 95% confidence interval [1.12-4.33]) and metabolically unhealthy normal weight groups (HR = 2.64, 95% CI [1.34-5.17]). Additionally, the point estimate suggested a 1.97-fold greater risk among the metabolically healthy overweight/obesity group, although this difference was not significant given the wide confidence interval (HR = 1.97, 95% CI [0.80-4.86]).

Conclusion

Our results demonstrated the relationships of metabolic health and weight regarding the risk of Afib in Taiwanese adults. The Afib risk among metabolic and obesity phenotypes is associated with a metabolically unhealthy status. A trend toward a higher Afib risk with obesity among metabolically healthy subjects was observed. However, the result was not robust and it still suggested further study.