Risk Of New-onset Atrial Fibrillation In Patients Research Articles

Establishment and evaluation of a nomogram for in-hospital new-onset atrial fibrillation after percutaneous coronary intervention for acute myocardial infarction.

New-onset atrial fibrillation (NOAF) is prognostic in acute myocardial infarction (AMI). The timely identification of high-risk patients is essential for clinicians to improve patient prognosis. A total of 333 AMI patients were collected who underwent percutaneous coronary intervention (PCI) at Zhejiang Provincial People's Hospital between October 2019 and October 2020. Least absolute shrinkage and selection operator regression (Lasso) and multivariate logistic regression analysis were applied to pick out independent risk factors. Secondly, the variables identified were utilized to establish a predicted model and then internally validated by 10-fold cross-validation. The discrimination, calibration, and clinical usefulness of the prediction model were evaluated using the receiver operating characteristic (ROC) curve, calibration curve, Hosmer-Lemeshow test decision curve analyses, and clinical impact curve. Overall, 47 patients (14.1%) developed NOAF. Four variables, including left atrial dimension, body mass index (BMI), CHA2DS2-VASc score, and prognostic nutritional index, were selected to construct a nomogram. Its area under the curve is 0.829, and internal validation by 10-fold cross-folding indicated a mean area under the curve is 0.818. The model demonstrated good calibration according to the Hosmer-Lemeshow test (P = 0.199) and the calibration curve. It showed satisfactory clinical practicability in the decision curve analyses and clinical impact curve. This study established a simple and efficient nomogram prediction model to assess the risk of NOAF in patients with AMI who underwent PCI. This model could assist clinicians in promptly identifying high-risk patients and making better clinical decisions based on risk stratification.

A Predictive Model of New-Onset Atrial Fibrillation After Percutaneous Coronary Intervention in Acute Myocardial Infarction Based on the Lymphocyte to C-Reactive Protein Ratio.

Lymphocyte to C-reactive protein ratio (LCR) is a recognized systemic inflammatory marker and novel prognostic indicator for several cancers. This study investigated the relationship between preoperative LCR and new-onset atrial fibrillation (NOAF) in patients with acute myocardial infarction (AMI) after percutaneous coronary intervention (PCI). Patients with AMI (n=662) with no history of atrial fibrillation (AF) were enrolled and classified into NOAF and non-NOAF groups based on the occurrence of postoperative NOAF during hospitalization. Logistic regression models were used to analyze NOAF risk factors and to assess the association between preoperative LCR and NOAF incidence. We constructed a new nomogram from the selected NOAF risk factors, and tested its predictive performance, degree of calibration, and clinical utility using receiver operating characteristic and calibration curves, decision curve analysis, and clinical impact curves. Overall, 84 (12.7%) patients developed NOAF during hospitalization. The LCR was significantly lower in the NOAF group. Preoperative LCR accurately predicted NOAF after AMI and was correlated with increased NOAF risk. Age, body mass index, diabetes, serum albumin levels, uric acid levels, left atrium (LA) diameter, left ventricular ejection fraction, left circumflex artery stenosis > 50%, and Killip class II status were independent predictors of NOAF after AMI. In addition, a new nomogram combined with LCR was constructed to stratify the risk of NOAF in patients with AMI. The performance of the new nomogram was satisfactory, as shown by the receiver operating characteristic curve, calibration curve, decision curve analysis and clinical impact curve. Preoperative LCR was an independent predictor of NOAF in patients with AMI after PCI. The novel nomogram combined with LCR could rapidly and individually identify and treat patients at a high risk of NOAF.

Association of Dexmedetomidine With New-Onset Atrial Fibrillation in Patients With Critical Illness

Dexmedetomidine is a widely used sedative in the intensive care unit (ICU) and has unique properties that may be associated with reduced occurrence of new-onset atrial fibrillation (NOAF). To investigate whether the use of dexmedetomidine is associated with the incidence of NOAF in patients with critical illness. This propensity score-matched cohort study was conducted using the Medical Information Mart for Intensive Care-IV database, which includes records of patients admitted to the ICU at Beth Israel Deaconess Medical Center in Boston dating 2008 through 2019. Included patients were those aged 18 years or older and hospitalized in the ICU. Data were analyzed from March through May 2022. Patients were divided into 2 groups according to dexmedetomidine exposure: those who received dexmedetomidine within 48 hours after ICU admission (dexmedetomidine group) and those who never received dexmedetomidine (no dexmedetomidine group). The primary outcome was the occurrence of NOAF within 7 days of ICU admission, as defined by the nurse-recorded rhythm status. Secondary outcomes were ICU length of stay, hospital length of stay, and in-hospital mortality. This study included 22 237 patients before matching (mean [SD] age, 65.9 [16.7] years; 12 350 male patients [55.5%]). After 1:3 propensity score matching, the cohort included 8015 patients (mean [SD] age, 61.0 [17.1] years; 5240 males [65.4%]), among whom 2106 and 5909 patients were in the dexmedetomidine and no dexmedetomidine groups, respectively. Use of dexmedetomidine was associated with a decreased risk of NOAF (371 patients [17.6%] vs 1323 patients [22.4%]; hazard ratio, 0.80; 95% CI, 0.71-0.90). Although patients in the dexmedetomidine group had longer median (IQR) length of stays in the ICU (4.0 [2.7-6.9] days vs 3.5 [2.5-5.9] days; P < .001) and hospital (10.0 [6.6-16.3] days vs 8.8 [5.9-14.0] days; P < .001), dexmedetomidine was associated with decreased risk of in-hospital mortality (132 deaths [6.3%] vs 758 deaths [12.8%]; hazard ratio, 0.43; 95% CI, 0.36-0.52). This study found that dexmedetomidine was associated with decreased risk of NOAF in patients with critical illness, suggesting that it may be necessary and warranted to evaluate this association in future clinical trials.

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

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. 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. 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. 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.

Antihyperglycemic drugs use and new-onset atrial fibrillation: A population-based nested case control study.

Currently, the potential risk of atrial fibrillation associated with antihyperglycemic drug use has been a topic of considerable interest. However, it remains uncertain whether different classes of antihyperglycemic drug therapy are associated with the risk of atrial fibrillation risk. Here, we investigated the association between different classes of antihyperglycemic drugs and new-onset atrial fibrillation (NAF). A case-matched study was performed based on the National Health Insurance Program in Taiwan. Patients who had NAF were considered the NAF group and were matched in a 1:4 ratio with patients without NAF, who were assigned to the non-NAF group. Patients were matched according to sex, age, diabetes mellitus duration, index date, and Charlson Comorbidity Index score. We used multivariate logistic regression controlling for potential confounders to examine the association between different classes of antihyperglycemic drug use and the risk of NAF. Overall, we identified 2,882 cases and 11,528 matched controls for the study. After adjusting for sex, age, comorbidities, and concurrent medications, users of biguanides or thiazolidinediones were at a lower risk of developing NAF when compared with non-users (odds ratio [OR] 0.81, 95% confidence interval [CI] 0.71–0.95 and OR 0.72, 95% CI 0.63–0.83, respectively). In contrast, users of insulin were at a higher risk of developing NAF than were non-users (OR 1.19, 95% CI 1.06–1.35). Sulfonylureas, glinides, α-glucosidase inhibitors, and dipeptidyl peptidase-4 inhibitors were not associated with developing the risk of NAF. In conclusion, the use of biguanides or thiazolidinediones may be associated with a low risk of NAF, whereas insulin may be associated with a significant increase in the risk of NAF in patients with type 2 diabetes mellitus during long-term follow-up. Further prospective randomized studies should investigate which specific class of antihyperglycemic drug treatment for diabetes mellitus can prevent or postpone NAF.