This multicenter retrospective study enrolled 861 consecutive patients with NVAF and HFpEF from May 2017 to March 2022 in Zhongda Hospital. Additionally, the validation cohort included 586 patients with NVAF and HFpEF recruited at the Taizhou People’s Hospital between August 2018 and March 2022. All participants in the MACCE group experienced cardiovascular and cerebrovascular events within one year of discharge. This study was approved by the Ethics Committee of Zhongda hospital and Taizhou people’s Hospital, respectively. Additional details can be found in Fig. 1.

Fig. 1.

Flowchart of patient selection. HFpEF, heart failure with preserved ejection fraction; MACCE, major adverse cardiovascular and cerebrovascular events; NVAF, nonvalvular atrial fibrillation.

The diagnostic criteria for NVAF [8] and HFpEF [9] set forth by the European Society of Cardiology were adhered to in this study. Patients meeting any of the following conditions were excluded from the study: (1) individuals with coronary artery disease who had undergone coronary artery bypass grafting or had received three or more coronary stents; (2) patients with severe congenital heart diseases such as pulmonary stenosis, large atrial septal defect, ventricular septal defect, aortic coarctation, patent ductus arteriosus, or tetralogy of Fallot; (3) individuals with severe end-stage diseases affecting vital organs, including acute or chronic liver failure, renal failure requiring blood purification, previous extensive cerebral infarction, or hemorrhage; (4) patients with malignant clonal diseases such as leukemia, lymphoma, or malignant solid tumors; and (5) individuals lost to follow-up.

The following demographic data were collected: sex, age, body mass index, smoking history, systolic blood pressure, diastolic blood pressure, classification of AF, duration of AF, ablation therapy of AF, and poor medication compliance indicated by a score of less than 6 on the score of Medication Adherence Report Scale [10]. Additionally, we collected information the administration medications including angiotensin-converting enzyme inhibitors/angiotensin receptor antagonists, beta-blockers, mineralocorticoid receptor antagonists, angiotensin-receptor neprilysin inhibitors, and sodium-glucose co-transporter-2 (SGLT-2) inhibitors. The presence of comorbidities including hyperthyroidism, hypertension, coronary artery disease, stroke, and chronic obstructive pulmonary disease, was also documented. Lab tests were performed to measure serum levels of hemoglobin, low-density lipoprotein cholesterol, total cholesterol, uric acid, serum creatinine (Scr), estimated glomerular filtration rate (eGFR), serum potassium (K${}^{+}$), serum sodium (Na${}^{+}$), hemoglobin A1c, and N-terminal pro-brain natriuretic peptide (NT-proBNP). Finally, left ventricular ejection fraction and left ventricular end-diastolic dimension (LVEDd) were assessed through echocardiography. The circumferential end-diastolic stress (cEDS) was calculated using the following formula [11]:

$$\mathrm{cEDS}=\frac{DBP\times {\left(\text{LVIDs}÷2\right)}^2\times \left\{1+\frac{{\left(\text{LVIDs}÷2+PWTs\right)}^2}{{\left(\text{LVIDs}÷2+PWTs÷2\right)}^2}\right\}}{{\left(\text{LVIDs}÷2+PWTs\right)}^2-{\left(\text{LVIDs}÷2\right)}^2}$$

cEDS, the circumferential end-diastolic stress; DBP, diastolic blood pressure; LVIDs, left ventricular internal diameters; PWTs, Posterior wall thicknesses.

During the follow-up period, every patient was contacted via a phone call to ascertain the occurrence of MACCE. The primary outcome of follow-up was the occurrence of MACCE within one year of discharge [12], including all-cause death, nonfatal acute myocardial infarction, and nonfatal stroke.

Statistical analysis was performed using SPSS 20.0 (IBM, Inc., Chicago, IL, USA) and R (version 3.6.2; R Foundation for Statistical Computing, Vienna, Austria). The mean and standard deviation of continuous variables were calculated and compared using the unpaired Student’s t-test or Mann-Whitney U-test while categorical variables were compared using the $\chi$${}^2$ test or Fisher’s exact test. All clinical variables for both cohorts were obtained from the hospital information system. In the training cohort, univariate and multivariate analyses were conducted using the least absolute shrinkage and selection operator and logistic regression, respectively. The nomogram was established based on the results of the multivariate logistic regression via the rms package of R (version 3.6.2, R Foundation for Statistical Computing, Vienna, Austria). To achieve the optimal logistic regression, insignificant coefficients were removed from the model due to the regression penalty applied to all variables; independent variables were chosen to obtain the optimal logistic regression.

The final model to predict the occurrence of MACCE in patients with NVAF and HFpEF after discharge was developed using the rms package of R (version 3.6.2, R Foundation for Statistical Computing, Vienna, Austria). The performance of the final predictive model was evaluated by the calibration plot, Hosmer-Lemeshow test, and decision curve analysis (DCA) using the validation cohort (developed with the R packages of rms and rmda). All statistical tests were two-tailed; p 0.05 was considered statistically significant.

A total of 1392 patients were enrolled in the study, with 828 from Zhongda Hospital and 564 from Taizhou People’s Hospital. Out of these, 55 patients (33 from the training cohort and 22 from the validation cohort) were excluded from the study. There were no significant differences in the baseline data, including age, sex, body mass index, systolic blood pressure, diastolic blood pressure, hypertension, and stroke, between the MACCE and non-MACCE cohorts, except for the Scr and hemoglobin A1c levels, LVEDd, and cEDS. Detailed data analysis is shown in Table 1. The proportion of patients with MACCE in the training and validation cohorts was 20.8% and 26.4%, respectively. In the training cohort, 83 patients experienced nonfatal stroke, 37 patients experienced nonfatal myocardial infarction, and the remaining 52 patients experienced death from all-causes. In the validation cohort, 66 patients experienced nonfatal stroke, 29 patients experienced nonfatal myocardial infarction, and the remaining 54 patients experienced death from all-causes.

The training cohort underwent least absolute shrinkage and selection operator (LASSO) regression analysis to identify predictors for the nomogram. Among the predictors screened, six variables demonstrated the strongest correlation with the occurrence of MACCE in patients with NVAF and HFpEF within one year of discharge in the training cohort (Fig. 2). These predictors included duration of AF of $\ge$6 years, poor medication compliance, Scr level, hyperthyroidism, serum NT-proBNP level, and cEDS. Subsequently, a multivariable logistic regression analysis confirmed the significance of these six variables in predicting MAACE risk. The odds ratio and 95% confidence intervals for each variable are shown in Table 2. Based on the probability values obtained, a nomogram was constructed (as depicted in Fig. 3) to visualize the individualized risk for MACCE using the preselected predictors.

Fig. 2.

Feature selection via the LASSO binary logistic regression model. (A) LASSO coefficient profiles of the 24 texture features. A coefficient profile plot was produced against the log ($\lambda$) sequence. Six non-zero coefficients were sorted out by the optimal $\lambda$, when the vertical line was drawn at the value selected by 10-fold cross-validation. (B) Tuning parameter ($\lambda$) selection applied 10-fold cross-validation by minimum criteria in the LASSO model. The AUC curve was plotted vs. log ($\lambda$). Dotted vertical lines were drawn at the optimal values via the 1 standard error of the minimum criteria (the 1-SE criteria) and the minimum criteria. AUC, area under the curve; LASSO, least absolute shrinkage and selection operator; SE, standard error.

Fig. 3.

Nomogram to predict the risk of MACCE in patients with NVAF and HFpEF within one year of discharge. AF, atrial fibrillation; cEDS, circumferential end-diastolic stress; MACCE, major adverse cardiovascular and cerebrovascular events; NT-proBNP, N-terminal pro-brain natriuretic peptide; Scr, serum creatinine; NVAF, nonvalvular atrial fibrillation; HFpEF, heart failure with preserved ejection fraction.

To verify the clinical validity of the nomogram, we adopted DCA in both the training and validation cohorts (Fig. 4A,B). The DCA quantified the net benefit at different threshold probabilities, indicating a wide range of high-risk threshold probabilities in both cohorts. Moreover, a calibration plot was generated to evaluate the performance of the nomogram in both cohorts (Fig. 5A,B). To further assess the goodness-of-fit, the Hosmer-Lemeshow test was conducted, yielding p-values of 0.573 for the training cohort and 0.628 for the validation cohort. These results indicate a high level of agreement between the observed and predicted probabilities of MACCE in both cohorts, providing additional evidence for the reliability of the nomogram.

Fig. 4.

Decision curve analysis for the training cohort (A) and the validation cohort (B). The horizontal line indicates that all samples are negative and the net benefit is zero. The oblique line indicates that all samples are positive. The net benefit has a negative slope.

Fig. 5.

Calibration curve of a nomogram for the training cohort (A) and the validation cohort (B). The X-axis represents the overall predicted probability of MACCE within one year of discharge and the Y-axis represents the actual probability. Model calibration is indicated by the degree of fitting of the curve. MACCE, major adverse cardiovascular and cerebrovascular events.