Cardiology Research, ISSN 1923-2829 print, 1923-2837 online, Open Access
Article copyright, the authors; Journal compilation copyright, Cardiol Res and Elmer Press Inc
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Original Article

Volume 17, Number 1, February 2026, pages 10-22


Development and Validation of a Prognostic Model to Predict Mortality in Patients With Heart Failure With Mildly Reduced Ejection Fraction After Acute Myocardial Infarction

Figures

Figure 1.
Figure 1. Flow diagram for participant screening, eligibility, and analysis. HFmrEF: heart failure with mildly reduced ejection fraction; LVEF: left ventricular ejection fraction.
Figure 2.
Figure 2. LASSO regression coefficient path and CV LASSO regression coefficient path. (a) LASSO regression coefficient path. (b) CV LASSO regression coefficient path. The LASSO regression coefficient path displays how the coefficients of each variable change with increasing values of the regularization parameter λ. The CV LASSO regression coefficient path illustrates the coefficients’ behavior with λ tuned through cross-validation. Both paths provide insights into the impact of regularization on variable selection and coefficient estimation in the LASSO regression model. LASSO: least absolute shrinkage and selection operator.
Figure 3.
Figure 3. Area under the receiver operating characteristic (ROC) curve and bootstrap validation. (a) ROC curves for the training set at 6 months, 2 years, and 3 years. (b) ROC curves for the validation set at 6 months, 2 years, and 3 years. (c) Comparison of model stability between the original model and 500 rounds of bootstrap validation on the training set. (d) Comparison of model stability between the original model and 500 rounds of bootstrap validation on the validation set. AUC: area under the curve; CI: confidence interval.
Figure 4.
Figure 4. Calibration curves at different time points. (a) Calibration curves for the training set at 6 months, 2 years, and 3 years. (b) Calibration curves for the validation set at 6 months, 2 years, and 3 years. The calibration curves depict the agreement between the predicted probabilities and the observed outcomes at different time points. The curves represent the performance of the predictive model in terms of calibration, indicating how well the model’s predicted probabilities align with the actual probabilities. OS: overall survival.
Figure 5.
Figure 5. Decision curve analysis (DCA) with time and DCA nomogram. (a) DCA with time for the training set. (b) DCA with time for the validation set. (c) DCA nomogram for the training set. (d) DCA nomogram for the validation set. The DCA curves in Figure 5a and 5b illustrate the net benefit of the predictive model over a range of threshold probabilities at different time points for the training and validation sets. These curves provide insights into the clinical usefulness and added value of the model compared to alternative decision strategies. Additionally, the DCA nomograms in Figure 5c and 5d provide a graphical representation of the decision curves, allowing for a more intuitive interpretation and application of the model’s results. Hb: hemoglobin; NYHA: New York Heart Association; eGFR: estimated glomerular filtration rate; PCI: percutaneous coronary intervention.
Figure 6.
Figure 6. Nomogram for all-cause mortality risk prediction. The nomogram presents a visual tool for predicting the risk of all-cause mortality. It combines various predictors or risk factors into a comprehensive model that provides an individualized risk assessment. The nomogram allows for a simple and intuitive estimation of the probability of mortality based on the values assigned to each predictor. Clinicians can use this nomogram as a practical aid in risk assessment and shared decision-making with patients regarding appropriate interventions and management strategies. NYHA: New York Heart Association; eGFR: estimated glomerular filtration rate; PPCI: primary percutaneous coronary intervention.
Figure 7.
Figure 7. Rationality analysis: Kaplan-Meier survival curves of high-score and low-score groups. (a) Rationality analysis for the training set. (b) Rationality analysis for the validation set. The Kaplan-Meier survival curves depicted in Figure 7a and 7b demonstrate the differences in survival outcomes between the high-score and low-score groups. These curves serve as a rationality analysis to evaluate the predictive performance of the scoring system or model. The separation of the survival curves indicates the ability of the scoring system to stratify patients into distinct risk groups. This analysis provides insights into the reliability and validity of the scoring system in predicting survival outcomes and aids in assessing its clinical utility.

Tables

Table 1. Baseline Characteristics of Patients With HFmrEF After Acute Myocardial Infarction in the Mortality Prognostic Model Development and Validation
 
Training cohort (n = 611)Validation cohort (n = 262)P value
According to a 7:3 ratio, the population was randomly divided into a training cohort and a validation cohort. Categorical variables were presented as n (%). Values for continuous variables are given as means ± SD or medians with interquartile ranges. HFmrEF: heart failure with mildly reduced ejection fraction; NYHA: New York Heart Association; COPD: chronic obstructive pulmonary disease; ACEI: angiotensin-converting enzyme inhibitor; ARB: angiotensin receptor blocker; ARNI: angiotensin receptor-neprilysin inhibitor; SGLT2i: sodium–glucose cotransporter 2 inhibitors; NT-proBNP: N-terminal pro-brain natriuretic peptide; eGFR: estimated glomerular filtration rate; LVd: left ventricular end-diastolic diameter; RVd: right ventricular end-diastolic diameter; E/e’: early diastolic peak velocity/early diastolic peak velocity of the lateral or septal mitral annulus; PASP: pulmonary artery systolic pressure; SD: standard deviation.
Demographics
  Age, years69.0 (61.0; 77.0)69.0 (61.0; 77.0)0.734
  Male, n (%)434 (71.0%)174 (66.4%)0.201
  Body mass index, kg/m224.4 (22.8; 30.0)24.4 (22.9; 30.0)0.988
  NYHA III + IV, n (%)324 (53.0%)123 (46.9%)0.116
Medical history, n (%)
  Current smoker221 (36.2%)95 (36.3%)1.000
  Current drinker53 (8.67%)26 (9.92%)0.645
  Hypertension432 (70.7%)168 (64.1%)0.065
  Hyperlipidemia126 (20.6%)57 (21.8%)0.775
  Coronary heart disease605 (99.0%)261 (99.6%)0.681
  Atrial fibrillation71 (11.6%)28 (10.7%)0.778
  Stroke77 (12.6%)29 (11.1%)0.601
  COPD66 (10.8%)22 (8.40%)0.338
  Renal insufficiency127 (20.8%)42 (16.0%)0.124
  Diabetes206 (33.7%)96 (36.6%)0.450
Serology
  NT-proBNP/100, pg/mL17.7 (4.50; 57.5)21.1 (4.36; 63.3)0.797
  Hemoglobin, g/L126 (112; 139)130 (114; 142)0.164
  White blood cells, × 109/L8.33 (6.35; 10.8)8.41 (6.42; 10.7)0.959
  Platelets, × 109/L187 (150; 227)187 (148; 231)0.908
  Alanine aminotransferase, U/L25.7 (14.9; 43.8)26.9 (14.5; 46.9)0.756
  Aspartate aminotransferase, U/L32.1 (20.1; 150)36.2 (21.1; 134)0.413
  Creatine kinase-MB, U/L24.5 (14.0; 88.2)25.9 (14.8; 113)0.550
  Uric acid, µmol/L340 (276; 416)332 (264; 415)0.378
  eGFR, mL/min/1.73 m273.9 (51.0; 93.7)73.7 (57.6; 93.2)0.680
  Sodium, mg/L140 (137; 142)140 (137; 141)0.972
  Potassium, mg/L4.12 (3.80; 4.48)4.08 (3.77; 4.40)0.248
  Low-density lipoprotein, mmol/L2.42 (1.73; 3.13)2.50 (1.78; 3.18)0.280
Treatment, n (%)
  PPCI392 (64.2%)173 (66.0%)0.122
  Beta-blocker534 (87.4%)235 (89.7%)0.397
  ACEI or ARB498 (81.5%)221 (84.4%)0.361
  ARNI34 (5.56%)12 (4.58%)0.666
  SGLT2i2 (0.33%)1 (0.38%)1.000
  Diuretics319 (52.2%)130 (49.6%)0.530
  Spironolactone292 (47.8%)124 (47.3%)0.959
Echocardiography
  Aortic size, mm33.0 (31.0; 36.0)33.5 (31.0; 36.0)0.762
  Left atrium size, mm37.0 (34.0; 40.0)37.0 (35.0; 40.0)0.992
  LVd, mm51.0 (48.0; 55.0)51.0 (47.0; 55.0)0.160
  Right atrium size, mm35.0 (33.0; 38.0)36.0 (34.0; 38.0)0.023
  RVd, mm19.0 (17.0; 20.0)19.0 (18.0; 20.0)0.176
  E/e’, cm/s13.3 (9.80; 18.4)13.7 (10.4; 18.0)0.396
  PASP, mm Hg31.0 (18.0; 40.0)31.0 (22.0; 39.8)0.884
Clinical endpoints, n (%)
  Death128 (20.9%)55 (21.0%)1.000

 

Table 2. Univariate Cox Regression Analysis of Factors Associated With Mortality in Patients With HFmrEF After Acute Myocardial Infarction
 
characteristicsβSEHR95% CIZ scoreP value
aP < 0.05. HFmrEF: heart failure with mildly reduced ejection fraction; NYHA: New York Heart Association; COPD: chronic obstructive pulmonary disease; ACEI: angiotensin-converting enzyme inhibitors; ARB: angiotensin receptor blocker; ARNI: angiotensin receptor-neprilysin inhibitor; SGLT2i: sodium–glucose cotransporter 2 inhibitors; PPCI: primary percutaneous coronary intervention; NT-proBNP: N-terminal pro-brain natriuretic peptide; eGFR: estimated glomerular filtration rate; LVd: left ventricular end-diastolic diameter; RVd: right ventricular end-diastolic diameter; E/e’: early diastolic peak velocity/early diastolic peak velocity of the lateral or septal mitral annulus; PASP: pulmonary artery systolic pressure; SE: standard error; HR: hazard ratio; CI: confidence interval.
Age0.0770.0091.081.061–1.18.297< 0.001a
Male vs. female0.0740.1981.0760.73–1.5880.3710.711
Body mass index–0.0040.0220.9960.954–1.041–0.1590.874
Current smoker–0.2630.1910.7690.529–1.117–1.3780.168
Current drinker–0.2340.3290.7910.415–1.51–0.710.478
Diabetes0.3890.181.4761.037–2.12.160.031a
Renal insufficiency1.050.1832.8571.995–4.095.731< 0.001a
COPD0.8040.2232.2361.443–3.4633.603< 0.001a
Stroke1.0320.2022.8081.888–4.1755.1< 0.001a
Atrial fibrillation0.6840.2271.9821.27–3.0923.0150.003a
Hyperlipidemia–0.6170.2610.5390.324–0.899–2.3690.018a
Hypertension0.7820.2342.1871.381–3.4623.3380.001a
NYHA III + IV vs. NYHA II1.0060.2022.7351.84–4.0654.974< 0.001a
Low-density lipoprotein–0.1530.0950.8580.713–1.034–1.6080.108
Sodium0.050.1521.0520.781–1.4160.3320.74
Potassium0.0130.0251.0130.966–1.0630.5330.594
eGFR–0.0260.0030.9740.968–0.98–8.33< 0.001a
Uric acid0.0020.0011.0021.001–1.0043.2770.001a
Creatine kinase-MB–0.0030.0010.9970.995–0.999–3.0380.002a
Alanine aminotransferase–0.0020.0010.9980.996–0.999–2.7160.007a
Aspartate aminotransferase–0.0110.0040.990.982–0.997–2.6420.008a
White blood cells–0.0560.0270.9460.897–0.997–2.0630.039a
Hemoglobin–0.0320.0040.9690.962–0.976–8.512< 0.001a
NT-proBNP/1000.0050.0011.0051.003–1.0065.919< 0.001a
PASP0.010.0021.011.007–1.0135.826< 0.001a
E/e’0.0520.0111.0531.03–1.0774.562< 0.001a
RVd0.0280.0221.0280.985–1.0731.2820.2
Right atrium size0.0290.0171.0290.996–1.0631.7390.082
LVd0.0410.0141.0421.013–1.0722.8870.004a
Left atrium size0.0760.0151.0791.048–1.1115.121< 0.001a
Aortic size0.0470.0241.0481–1.0981.9730.049a
PPCI–1.0390.180.3540.249–0.504–5.772< 0.001a
Diuretics0.2620.1791.30.915–1.8471.4640.143
ARNI0.3430.4231.4090.616–3.2260.8120.417
ACEI or ARB–1.0320.1910.3560.245–0.518–5.402< 0.001a
Spironolactone–0.1410.1780.8680.613–1.229–0.7970.426
Beta-blocker–0.9130.2090.4010.266–0.604 ––4.37< 0.001a

 

Table 3. Multivariable Cox Regression Analysis of Factors Associated With Mortality in HFmrEF Patients
 
CharacteristicsβSEHR95% CIZ scoreP value
aP < 0.05. HFmrEF: heart failure with mildly reduced ejection fraction; eGFR: estimated glomerular filtration rate; PPCI: primary percutaneous coronary intervention; NYHA: New York Heart Association; SE: standard error; HR: hazard ratio; CI: confidence interval.
Age0.0520.0091.0531.034–1.0735.555< 0.001a
Hemoglobin–0.0160.0050.9840.975–0.993–3.420.001a
eGFR–0.0120.0040.9880.981–0.996–2.980.003a
PPCI–0.5940.1870.5520.383–0.797–3.1760.001a
Stroke0.5250.2051.691.13–2.5282.5560.011a
NYHA III + IV vs. NYHA II0.5140.2091.6731.111–2.5192.4620.014a