Incidence and impact of atrial fibrillation in heart failure patients: real‐world data in a large community

Diaz, Javier; Martínez, Fernando; Calderón, José Miguel; Fernández, Antonio García; Sauri, Inmaculada; Uso, Ruth; Trillo, J.L.; Redón, Josep; Forner, María José

doi:10.1002/ehf2.14124

Cited by 7 publications

(3 citation statements)

References 33 publications

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Section: Introductionmentioning

confidence: 99%

“…The mechanisms include activation of the renin angiotensin aldosterone system (RAAS), mechanical traction on the left atrium, and atrial electrophysiological remodelling [10, 12, 13-15]. AF also plays a role in the occurrence and progression of AHF [16]. Thus far, research has mainly focused on the incidence of AF in patients with AHF; few studies have examined the incidence of AHF in patients with AF.…”

Section: Introductionmentioning

confidence: 99%

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Nomograms for Predicting the Risk of Acute Heart Failure in ICU Patients with Atrial Fibrillation: A Retrospective Cohort Study

Wu,

Qiao,

Yan

et al. 2023

Preprint

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AimThis study developed two nomograms to predict the incidence of acute heart failure (AHF) in patients of atrial fibrillation (AF) and evaluated the predictive value of the nomograms.Method18179 patients of AF from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database were analysed. The patients were randomly divided into two groups in a seven-to-three ratio to form a training cohort (n = 12725) and a validation cohort (n = 5454). Least absolute shrinkage and selection operator (LASSO) regression analyses were used to identify associated risk variables. Two nomograms were established to predict the rate of AHF in patients of AF for use by patients and clinicians, respectively. The new models were assessed in terms of the concordance index (C-index), the area under the curve (AUC) of receiver operating characteristic (ROC) analysis, calibration curve, and decision curve analysis (DCA).ResultsLeast absolute shrinkage and selection operator (LASSO) regression analysis identified seven potential predictors of acute heart failure in nomogram 1 and three potential predictors in nomogram 2. Multivariate logistic regression analysis was used to evaluate the effects of these predictors and create final models. The concordance index values were 0.768 and 0.696, respectively. The areas under the curves for the training and validation sets in nomogram 1 were 0.768 and 0.763, respectively. The areas under the curves for the training and validation sets in nomogram 2 were 0.696 and 0.692, respectively.ConclusionThe age, respiratory rate, fluid management, mean corpuscular hemoglobin concentration (MCHC), bicarbonate, blood urea nitrogen (BUN) and chloride were identified as predictors of the development of acute heart failure in patients with atrial fibrillation in nomogram 1. The charlson score, lods score and sapsII score were identified as predictors of the development of acute heart failure in nomogram 2. Our nomograms are reliable convenient approaches for predicting acute heart failure in patients with atrial fibrillation.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Nomograms for Predicting the Risk of Acute Heart Failure in ICU Patients with Atrial Fibrillation: A Retrospective Cohort Study

Wu,

Qiao,

Yan

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…The mechanisms include activation of the renin angiotensin aldosterone system (RAAS), mechanical traction on the left atrium, and atrial electrophysiological remodelling [7,8]. AF also plays a role in the occurrence and progression of AHF [9]. Thus far, research has mainly focused on the incidence of AF in patients with AHF; few studies have examined the incidence of AHF in patients with AF.…”

Section: Introductionmentioning

confidence: 99%

Nomograms for Predicting the Risk of Acute Heart Failure in ICU Patients with Atrial Fibrillation

Wu,

Qiao,

Yan

et al. 2023

Preprint

View full text Add to dashboard Cite

Background This study developed two nomograms to predict the incidence of acute heart failure (AHF) in patients of atrial fibrillation (AF) and evaluated the predictive value of the nomograms. Methods 18179 patients of AF from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database were randomly divided into two groups in a seven-to-three ratio to form a training cohort (n = 12725) and a validation cohort (n = 5454). Least absolute shrinkage and selection operator (LASSO) regression analyses were used to identify associated risk variables. Two nomograms were established. The new models were assessed in terms of the concordance index (C-index), the area under the curve (AUC) of receiver operating characteristic (ROC) analysis, calibration curve, and decision curve analysis (DCA). Results Least absolute shrinkage and selection operator (LASSO) regression analysis identified seven potential predictors of acute heart failure in nomogram 1 and three potential predictors in nomogram 2. Multivariate logistic regression analysis was used to evaluate the effects of these predictors and create final models. The concordance index values were 0.768 and 0.696, respectively. The areas under the curves for the training and validation sets in nomogram 1 were 0.768 and 0.763, respectively. The areas under the curves for the training and validation sets in nomogram 2 were 0.696 and 0.692, respectively. Conclusion Seven variables were identified as predictors in nomogram 1 and three variables were identified in nomogram 2. Our nomograms are reliable convenient approaches for predicting acute heart failure in patients with atrial fibrillation.

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Incidence and impact of atrial fibrillation in heart failure patients: real‐world data in a large community

et al. 2022

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AimsThe objective of the present study is to assess the bidirectional association between heart failure (HF) and atrial fibrillation (AF) using real-world data. Methods and resultsFrom an electronic health recording with a population of 3 799 885 adult subjects, those with prevalent or incident HF were selected and followed throughout a study period of 5 years. Prevalence and incidence of AF, and their impact in the risk for acute HF hospitalization, worsening renal function, ischaemic and haemorrhagic stroke, and all-cause mortality were identified. We analysed all incident and prevalent patients with HF and AF, 128 086 patients (S1), and subsequently analysed a subset of patients with incident HF and AF, 57 354 patients (S2). We analysed all incident and prevalent patients with HF and AF, 128 086 patients (S1), and subsequently a subset of patients with incident HF and AF, 57 354 patients (S2). The prevalence of AF was 59 906 (46.7%) of the HF patients, while incidence in the S2 was 231/1000 patients/year. In both cohorts, S1 and S2, AF significantly increases the risk of acute heart failure hospitalization [incidence 79.1/1000 and 97.5/1000 patients/year; HR 1.53 (1.48-1.59 95% CI) and HR 1.32 (1.24-1.41 95% CI), respectively], risk of decreased renal function (eGFR reduced by >20%) [66.2/1000 and 94.0/1000 patients/year; HR 1.13 (1.09-1.18 95% CI) and HR 1.22 (1.14-1.31 95% CI), respectively] and all-cause mortality [203/1000 and 294/1000 patients/year; HR 1.62 (1.58-1.65 95% CI) and HR 1.65 (1.59-1.70 95% CI), respectively]. The number of episodes of hospitalization for acute heart failure was also significantly higher in the AF patients (27 623 vs. 10 036, P < 0.001). However, the risk for ischaemic stroke was reduced in the AF subjects [HR 0.66 (0.63-0.74 95% CI)], probably due to the anticoagulant treatment. Conclusions AF is associated with an increment in the risk of episodes of acute heart failure as well as decline of renal function and increment of all-cause mortality.

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Incidence and impact of atrial fibrillation in heart failure patients: real‐world data in a large community

Cited by 7 publications

References 33 publications

Nomograms for Predicting the Risk of Acute Heart Failure in ICU Patients with Atrial Fibrillation: A Retrospective Cohort Study

Nomograms for Predicting the Risk of Acute Heart Failure in ICU Patients with Atrial Fibrillation: A Retrospective Cohort Study

Nomograms for Predicting the Risk of Acute Heart Failure in ICU Patients with Atrial Fibrillation

Incidence and impact of atrial fibrillation in heart failure patients: real‐world data in a large community

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