Adverse Outcomes Associated with Pre-Existing and New-Onset Atrial Fibrillation in Patients with Acute Coronary Syndrome: A Retrospective Cohort Study

Bidirectional Association Between Atrial Fibrillation and Myocardial Infarction, and Relation to Mortality in the Framingham Heart Study

BACKGROUND

Individuals with both atrial fibrillation (AF) and myocardial infarction (MI) have higher mortality compared with individuals with only 1 condition. Whether mortality differs according to the temporal order of AF and MI is unclear.

METHODS AND RESULTS

We included participants from the FHS (Framingham Heart Study) from 1960 and onwards. We assessed the hazard ratio (HR) of new-onset AF and MI, and mortality according to MI and AF status (prevalent and interim) using multivariable-adjusted Cox proportional hazards models. Interim diseases were modeled as time-varying variables. For the analysis of new-onset AF, 10 923 participants (55% women; mean±SD age, 54±8 years) were included. For new-onset MI, 10 804 participants (55% women; mean±SD age, 54±8 years) were included. Compared with no MI, the hazard of new-onset AF was higher in participants with prevalent (HR, 1.60 [95% CI, 1.32-1.94]) and interim MI (HR, 3.96 [95% CI, 3.18-4.91]). Both ST-segment-elevation MI and non-ST-segment-elevation MI were associated with new-onset AF. Interim AF, not prevalent AF, was associated with higher hazard rate of new-onset MI (HR, 2.21 [95% CI, 1.67-2.92]). Interim AF was associated with both ST-segment-elevation MI and non-ST-segment-elevation MI. Mortality was significantly greater among participants with AF and MI compared with participants with 1 of the 2, regardless of temporal order.

CONCLUSIONS

We report a bidirectional association between AF and MI, which was observed for both non-ST-segment-elevation MI and ST-segment-elevation MI. Participants with both AF and MI had considerably higher mortality compared with participants with only 1 of the 2 conditions, regardless of order.

Construction of a predictive model for new-onset atrial fibrillation after acute myocardial infarction based on P-wave amplitude in lead V1

BACKGROUND

In this study, we aimed to identify the risk factors for new-onset atrial fibrillation (NOAF) after postcoronary intervention in patients with acute myocardial infarction (AMI) and to establish a nomogram prediction model.

METHODS

The clinical data of 506 patients hospitalized for AMI from March 2020 to February 2023 were retrospectively collected, and the patients were randomized into a training cohort (70%; n = 354) and a validation cohort (30%; n = 152). Independent risk factors were determined using least absolute shrinkage and selection operator and multivariate logistic regression. Predictive nomogram modeling was performed using R software. Nomograms were evaluated based on discrimination, correction, and clinical efficacy using the C-statistic, calibration plot, and decision curve analysis, respectively.

RESULTS

The multivariate logistic regression analysis showed that P-wave amplitude in lead V1, age, and infarct type were independent risk factors for NOAF, and the area under the receiver operating characteristic curve of the training and validation sets was 0.760 (95% confidence interval [CI] 0.674-0.846) and 0.732 (95% CI 0.580-0.883), respectively. The calibration curves showed good agreement between the predicted and observed values in both the training and validation sets, supporting that the actual predictive power was close to the ideal predictive power.

CONCLUSIONS

P-wave amplitude in lead V1, age, and infarct type were independent risk factors for NOAF in patients with AMI after intervention. The nomogram model constructed in this study can be used to assess the risk of NOAF development and has some clinical application value.

New-onset atrial fibrillation and chronic coronary syndrome in the CLARIFY registry

BACKGROUND AND AIMS

Data on new-onset atrial fibrillation (NOAF) in patients with chronic coronary syndromes (CCS) are scarce. This study aims to describe the incidence, predictors, and impact on cardiovascular (CV) outcomes of NOAF in CCS patients.

METHODS

Data from the international (45 countries) CLARIFY registry (prospeCtive observational LongitudinAl RegIstry oF patients with stable coronary arterY disease) were used. Among 29 001 CCS outpatients without previously reported AF at baseline, patients with at least one episode of AF/flutter diagnosed during 5-year follow-up were compared with patients in sinus rhythm throughout the study.

RESULTS

The incidence rate of NOAF was 1.12 [95% confidence interval (CI) 1.06-1.18] per 100 patient-years (cumulative incidence at 5 years: 5.0%). Independent predictors of NOAF were increasing age, increasing body mass index, low estimated glomerular filtration rate, Caucasian ethnicity, alcohol intake, and low left ventricular ejection fraction, while high triglycerides were associated with lower incidence. New-onset atrial fibrillation was associated with a substantial increase in the risk of adverse outcomes, with adjusted hazard ratios of 2.01 (95% CI 1.61-2.52) for the composite of CV death, non-fatal myocardial infarction, or non-fatal stroke, 2.61 (95% CI 2.04-3.34) for CV death, 1.64 (95% CI 1.07-2.50) for non-fatal myocardial infarction, 2.27 (95% CI 1.85-2.78) for all-cause death, 8.44 (95% CI 7.05-10.10) for hospitalization for heart failure, and 4.46 (95% CI 2.85-6.99) for major bleeding.

CONCLUSIONS

Among CCS patients, NOAF is common and is strongly associated with worse outcomes. Whether more intensive preventive measures and more systematic screening for AF would improve prognosis in this population deserves further investigation.

Does Atrial Fibrillation Deteriorate the Prognosis in Patients With Septic or Cardiogenic Shock?

Atrial fibrillation (AF) is associated with increased risk of mortality in various clinical conditions. However, the prognostic role of preexisting and new-onset AF in critically ill patients, such as patients with septic or cardiogenic shock remains unclear. This study investigates the prognostic impact of preexisting and new-onset AF on 30-day all-cause mortality in patients with septic or cardiogenic shock. Consecutive patients with sepsis, or septic or cardiogenic shock were enrolled in 2 prospective, monocentric registries from 2019 to 2021. Statistical analyses included Kaplan-Meier, multivariable logistic, and Cox proportional regression analyses. In total, 644 patients were included (cardiogenic shock: n = 273; sepsis/septic shock: n = 361). The prevalence of AF was 41% (29% with preexisting AF, 12% with new-onset AF). Within the entire study cohort, neither preexisting AF (log-rank p = 0.542; hazard ratio [HR] 1.075, 95% confidence interval [CI] 0.848 to 1.363, p = 0.551) nor new-onset AF (log-rank p = 0.782, HR = 0.957, 95% CI 0.683 to 1.340, p = 0.797) were associated with 30-day all-cause mortality compared with non-AF. In patients with AF, ventricular rates >120 beats/min compared with ≤120 beats/min were shown to increase the risk of reaching the primary end point in AF patients with cardiogenic shock (log-rank p = 0.006, HR 1.886, 95% CI 1.164 to 3.057, p = 0.010). Furthermore, logistic regression analyses suggested increased age was the only predictor of new-onset AF (odds ratio 1.042, 95% CI 1.018 to 1.066, p = 0.001). In conclusion, neither the presence of preexisting AF nor the occurrence of new-onset AF was associated with the risk of 30-day all-cause mortality in consecutive patients admitted with cardiogenic shock.

The bidirectional association between atrial fibrillation and myocardial infarction

Atrial fibrillation (AF) is associated with an increased risk of myocardial infarction (MI) and vice versa. This bidirectional association relies on shared risk factors as well as on several direct and indirect mechanisms, including inflammation, atrial ischaemia, left ventricular remodelling, myocardial oxygen supply-demand mismatch and coronary artery embolism, through which one condition can predispose to the other. Patients with both AF and MI are at greater risk of stroke, heart failure and death than patients with only one of the conditions. In this Review, we describe the bidirectional association between AF and MI. We discuss the pathogenic basis of this bidirectional relationship, describe the risk of adverse outcomes when the two conditions coexist, and review current data and guidelines on the prevention and management of both conditions. We also identify important gaps in the literature and propose directions for future research on the bidirectional association between AF and MI. The Review also features a summary of methodological approaches for the study of bidirectional associations in population-based studies.

Prediction Model of New Onset Atrial Fibrillation in Patients with Acute Coronary Syndrome

OBJECTIVE

Atrial fibrillation (AF) is one of the most common complications of acute coronary syndrome (ACS) patients. Possible risk factors related to new-onset AF (NOAF) in ACS patients have been reported in some studies, and several prediction models have been established. However, the predictive power of these models was modest and lacked independent validation. The aim of this study is to define risk factors of NOAF in patients with ACS during hospitalization and to develop a prediction model and nomogram for individual risk prediction.

METHODS

Retrospective cohort studies were conducted. A total of 1535 eligible ACS patients from one hospital were recruited for model development. External validation was performed using an external cohort of 1635 ACS patients from another hospital. The prediction model was created using multivariable logistic regression and validated in an external cohort. The discrimination, calibration, and clinical utility of the model were evaluated, and a nomogram was constructed. A subgroup analysis was performed for unstable angina (UA) patients.

RESULTS

During hospitalization, the incidence of NOAF was 8.21% and 6.12% in the training and validation cohorts, respectively. Age, admission heart rate, left atrial diameter, right atrial diameter, heart failure, brain natriuretic peptide (BNP) level, less statin use, and no percutaneous coronary intervention (PCI) were independent predictors of NOAF. The AUC was 0.891 (95% CI: 0.863-0.920) and 0.839 (95% CI: 0.796-0.883) for the training and validation cohort, respectively, and the model passed the calibration test (P > 0.05). The clinical utility evaluation shows that the model has a clinical net benefit within a certain range of the threshold probability.

CONCLUSION

A model with strong predictive power was constructed for predicting the risk of NOAF in patients with ACS during hospitalization. It might help with the identification of ACS patients at risk and early intervention of NOAF during hospitalization.

Long-Term Outcomes for Patients With Acute Coronary Syndrome and Nonvalvular Atrial Fibrillation

Short-term outcomes are worse for patients with acute coronary syndrome (ACS) with a history of nonvalvular atrial fibrillation (NVAF). However, long-term prognosis remains unclear. We linked administrative health databases to identify patients hospitalized with ACS (ST-elevation myocardial infarction [STEMI], non-STEMI [NSTEMI], and unstable angina) between 2008 and 2019 in Alberta, Canada. Patients were stratified according to history of NVAF before hospitalization. The primary outcome was a composite of all-cause mortality, hospitalization for myocardial infarction, or stroke at 3 years. Cox models were constructed to estimate the association between ACS, NVAF, and outcomes. Of 54,309 ACS hospitalizations, 6,351 patients (11.7%) had a history of NVAF. Compared with patients without NVAF, patients with previous NVAF were older (75.6 ± 11.6 vs 64.9 ± 13.4 years), women (35.1% vs 30.0%), had higher comorbid burden (Charlson co-morbidity index 3.0 vs 1.0), and more often presented with NSTEMI (57.5% vs 49.0%). The primary outcome occurred in 37.0% of patients with previous NVAF and 17.4% without (p <0.001). In the multivariable analysis, there was a 1.14-fold (95% confidence interval [CI] 1.09 to 1.20) higher risk of the primary outcome in patients with previous NVAF. There was a significant association with STEMI (adjusted harazard ratio [aHR] 1.24, 95% CI 1.12 to 1.36) and NSTEMI (aHR 1.12, 95% CI 1.06 to 1.19) but not with unstable angina (aHR 1.04, 95% CI 0.90 to 1.22). In conclusion, in this population-based study, we identified that a history of NVAF at ACS presentation is associated with worse long-term prognosis, particularly for STEMI and NSTEMI.

Newly Diagnosed Atrial Fibrillation in Acute Myocardial Infarction

Background

It remains controversial whether long‐term clinical impact of newly diagnosed atrial fibrillation (AF) in the acute phase of acute myocardial infarction (AMI) is different from that of prior AF diagnosed before the onset of AMI.

Methods and Results

The current study population from the CREDO‐Kyoto AMI (Coronary Revascularization Demonstrating Outcome Study in Kyoto Acute Myocardial Infarction) Registry Wave‐2 consisted of 6228 patients with AMI who underwent percutaneous coronary intervention. The baseline characteristics and long‐term clinical outcomes were compared according to AF status (newly diagnosed AF: N=489 [7.9%], prior AF: N=589 [9.5%], and no AF: N=5150 [82.7%]). Median follow‐up duration was 5.5 years. Patients with newly diagnosed AF and prior AF had similar baseline characteristics with higher risk profile than those with no AF including older age and more comorbidities. The cumulative 5‐year incidence of all‐cause death was higher in newly diagnosed AF and prior AF than no AF (38.8%, 40.7%, and 18.7%, P<0.001). The adjusted hazard ratios (HRs) for mortality of newly diagnosed AF and prior AF relative to no AF remained significant with similar magnitude (HR, 1.31; 95% CI, 1.12–1.54; P<0.001, and HR, 1.32; 95% CI, 1.14–1.52; P<0.001, respectively). The cumulative 5‐year incidence of stroke decreased in the order of newly diagnosed AF, prior AF and no AF (15.5%, 12.9%, and 6.3%, respectively, P<0.001). The higher adjusted HRs of both newly diagnosed AF and prior AF relative to no AF were significant for stroke, with a greater risk of newly diagnosed AF than that of prior AF (HR, 2.05; 95% CI, 1.56–2.69; P<0.001, and HR, 1.33; 95% CI, 1.00–1.78; P=0.048, respectively). The higher stroke risk of newly diagnosed AF compared with prior AF was largely driven by the greater risk within 30 days. The higher adjusted HRs of newly diagnosed AF and prior AF relative to no AF were significant for heart failure hospitalization (HR, 1.73; 95% CI, 1.35–2.22; P<0.001, and HR, 2.23; 95% CI, 1.82–2.74; P<0.001, respectively) and major bleeding (HR, 1.46; 95% CI, 1.23–1.73; P<0.001, and HR, 1.36; 95% CI, 1.15–1.60; P<0.001, respectively).

Conclusions

Newly diagnosed AF in AMI had risks for mortality, heart failure hospitalization, and major bleeding higher than no AF, and comparable to prior AF. The risk of newly diagnosed AF for stroke might be higher than that of prior AF.