The optimal definition and prediction nomogram for left ventricular remodelling after acute myocardial infarction

Prognostic impact of changes in left ventricular ejection fraction and wall motion score index in patients with myocardial infarction

Background

The prognostic significance of changes in left ventricular ejection fraction (LVEF) and wall motion score index (WMSI) in patients with myocardial infarction remains unclear.

Methods

This study evaluated whether changes in LVEF and WMSI can predict clinical outcomes and LV remodeling in post-AMI patients. Using data from the Korea Acute Myocardial Infarction Registry-National Institutes of Health (KAMIR-NIH), 3,510 AMI patients who underwent percutaneous coronary intervention (PCI) were retrospectively analyzed. LVEF and WMSI were assessed via echocardiography at baseline and one-year post-PCI. The primary outcome was major cardiovascular adverse events (MACE), a composite of all-cause death, recurrent myocardial infarction (MI), and rehospitalization for heart failure at three years.

Results

Among 3,510 AMI patients, 1,561 (44.5%) showed improvement in both LVEF and WMSI at one year after PCI, 1,150 (32.8%) experienced improvement in either LVEF or WMSI, while 799 (22.8%) had deterioration in both. The incidence of MACE was significantly lower in patients with improvement in both LVEF and WMSI (7.8% vs. 12.5% vs. 17.1%, P < 0.001). These patients also exhibited the highest rate of LV reverse remodeling and the lowest rate of adverse remodeling. Both the random forest and logistic regression models identified changes in LVEF and WMSI as significant predictors of MACE and LV remodeling.

Conclusion

In AMI patients, improvement in both LVEF and WMSI post-PCI was associated with a lower risk of MACE and a higher likelihood of LV reverse remodeling. These findings highlight the prognostic value of LVEF and WMSI changes in guiding long-term management strategies.

[The Possibilities of Predicting Left Ventricular Ejection Fraction 12 Months After ST-Segment Elevation Myocardial Infarction]

Aim    To identify predictors and develop a model for prognosis of left ventricular (LV) ejection fraction (EF) 12 months after ST-segment elevation myocardial infarction (STEMI) on electrocardiogram (ECG).Material and methods    This was a prospective registry study of patients admitted within 24 h of STEMI. Concentrations of soluble suppression of tumorigenicity 2, proprotein convertase subtilisin/kexin type 9, N-terminal pro-B-type natriuretic peptide (NTproBNP), high-sensitivity troponin I (TnI), and C-reactive protein were measured. LVEF was determined using the Simpson method at one, 10-12 days, and 12 months after STEMI. The study included 138 patients; after 12 months, LVEF was determined in 112 patients. The patients were divided into groups based on their LVEF: with preserved EF (pLVEF), LVEF ≥50% (n=51); moderately reduced EF (mrLVFE), LVEF 41-49% (n=40); and reduced EF (rLVEF), LVEF ≤40% (n=11).Results     A model for predicting LVEF 12 months after STEMI was constructed using the ordinal regression. The model sensitivity was 88.2% for predicting pLVEF, 71.8% for predicting mrLVEF, and 72.5% for predicting rLVEF. The model specificity was 59.1%. The factors determining LVEF in STEMI patients after 12 months included the formation of postinfarction LV aneurysm, LVEF on days 10-12 after STEMI, the magnitude in mm of ST segment elevation on the ECG upon admission, and the TnI concentration on the first day of STEMI.Conclusions    The obtained model for predicting LVEF 12 months after STEMI allows prognosing LVEF in all its ranges with a sensitivity of more than 70%.

Neutrophil to high-density lipoprotein cholesterol ratio predicts left ventricular remodeling and MACE after PCI in patients with acute ST-segment elevation myocardial infarction

Background

The neutrophil to high-density lipoprotein cholesterol ratio (NHR) has been proposed as a potential marker for predicting cardiovascular events. However, its prognostic role following percutaneous coronary intervention (PCI) in patients with acute ST-segment elevation myocardial infarction (STEMI) remains unclear. This study aimed to evaluate the predictive value of NHR for left ventricular remodeling (LVR) and long-term outcomes in STEMI patients post-PCI.

Methods

This retrospective study included 299 STEMI patients who underwent PCI and were followed for 24 months post-procedure. Echocardiography was performed upon admission and at 6 months post-myocardial infarction (MI). LVR was defined as an increase in left ventricular diastolic volume (LVEDV) of at least 20% from baseline. Based on their VR status, patients were divided into LVR (n = 81) and non-LVR (n = 218) groups and clinical data were compared. A weighted logistic regression model was used to study the correlation between NHR and LVR. Weighted Cox proportional risk models were used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) for major adverse cardiovascular events (MACE). And the NHR was analyzed using receiver operating characteristic (ROC) curves to predict the occurrence of postoperative LVR and MACE in STEMI patients. Restricted cubic spline (RCS) analysis was used to explore the linear or non-linear relationship between NHR and LVR or MACE. Cox survival analysis was used to assess the relationship between NHR, LVR and survival time.

Results

Among the 299 STEMI patients enrolled in the study, LVR was observed in 81 patients after 24 months of follow-up. The LVR group had significantly higher NHR levels compared to the non-LVR group (8.19 ± 1.95 vs. 6.23 ± 1.91, P < 0.001). After adjusting for potential confounders, a significant positive correlation was found between NHR and LVR. Each standard deviation increase in NHR was associated with a 43% higher risk of MACE (HR: 1.43, 95% CI: 1.25-1.64, P < 0.001). ROC curve analysis demonstrated that NHR could predict both LVR (AUC: 0.762) and MACE (AUC: 0.722). An NHR cut-off value of >8.13 was significantly linked to an increased risk of MACE (HR: 4.30, 95% CI: 2.41-7.69).

Conclusions

NHR is an independent predictor of LVR and MACE after PCI in STEMI patients. Monitoring NHR may aid in identifying high-risk patients early, facilitating individualized treatment.

Prognostic Value of Advanced Echocardiography in Patients with Ischemic Heart Disease: A Comprehensive Review

Cardiovascular (CV) diseases caused 20.5 million deaths in 2021, making up nearly one-third of global mortality. This highlights the need for practical prognostic markers to better classify patients and guide treatment, especially in ischemic heart disease (IHD), which represents one of the leading causes of CV mortality. Transthoracic echocardiography (TTE) is a key, non-invasive imaging tool widely used in cardiology for diagnosing and managing a range of CV conditions. It is the first choice for diagnosing and monitoring patients with acute coronary syndrome (ACS). Alongside well-established echocardiographic measures, new techniques have proven useful for predicting adverse events in IHD patients, such as three-dimensional (3D) and tissue Doppler imaging (TDI), and speckle tracking technology. This review aims to explore the latest echocardiographic tools that could provide new prognostic markers for patients in the acute phase and during follow-up after an acute myocardial infarction (AMI). We focus on new imaging methods like TDI, myocardial work index (MWI), speckle-tracking strain, and 3D technologies using TTE, which are easy to use and widely available at all stages of coronary artery disease (CAD).

Preoperative Albumin to Alkaline Phosphatase Ratio and Inflammatory Burden Index for Rectal Cancer Prognostic Nomogram-Construction: Based on Multiple Machine Learning

Purpose

Preoperative albumin to alkaline phosphatase ratio (AAPR) and inflammatory burden index (IBI) are prognostic indicators for a multitude of cancers, and our study focuses on evaluating the prognostic significance of the AAPR and the IBI on rectal cancer (RC) patients to provide a more accurate guideline for patient prognosis.

Patients and Methods

This study enrolled patients who underwent laparoscopic rectal cancer surgery from January 2016 to January 2021. We utilized three machine learning approaches to select variables most relevant to prognosis in the training cohort. Finally, based on the screened variables, a nomogram was established to predict RC patients' overall survival (OS). The improvement in predictive ability and clinical benefit was assessed through the concordance index (C-index), receiver operating characteristic (ROC), calibration curve, and decision curve analysis (DCA).

Results

A total of 356 patients were enrolled and they were randomly divided into a training cohort (60%, n=214) and a validation cohort (40%, n=143). Overall survival (OS) was worse for patients in either the low AAPR or the high AAPR group, whereas patients in the low AAPR with both high IBI group had the lowest OS (P<0.001). Finally, five variables were obtained after screening the best variables by three machine learning, and the nomogram was constructed. In both the development and validation cohorts, the C-index values exceeded 0.85, indicating that the predictive model has a strong predictive performance in terms of overall survival. The calibration curves and the decision curve analysis (DCA) showed that the nomogram demonstrated a superior benefit.

Conclusion

Preoperative AAPR and IBI can serve as effective indicators for predicting the OS of RC patients. We have developed a nomogram for predicting the OS of patients who underwent laparoscopic rectal cancer surgery.

Establishment and validation of nomogram model for predicting major adverse cardiac events in patients with acute ST-segment elevation myocardial infarction based on glycosylated hemoglobin A1c to apolipoprotein A1 ratio: An observational study

The objective of the current study is to assess the usefulness of HbA1cAp ratio in predicting in-hospital major adverse cardiac events (MACEs) among acute ST-segment elevation myocardial infarction (STEMI) patients that have undergone percutaneous coronary intervention (PCI). Further, the study aims to construct a ratio nomogram for prediction with this ratio. The training cohort comprised of 511 STEMI patients who underwent emergency PCI at the Huaibei Miners' General Hospital between January 2019 and May 2023. Simultaneously, 384 patients treated with the same strategy in First People's Hospital of Hefei formed the validation cohort during the study period. LASSO regression was used to screen predictors of nonzero coefficients, multivariate logistic regression was used to analyze the independent factors of in-hospital MACE in STEMI patients after PCI, and nomogram models and validation were established. The LASSO regression analysis demonstrated that systolic blood pressure, diastolic blood pressure, D-dimer, urea, and glycosylated hemoglobin A1c (HbA1c)/apolipoprotein A1 (ApoA1) were significant predictors with nonzero coefficients. Multivariate logistic regression analysis was further conducted to identify systolic blood pressure, D-dimer, urea, and HbA1c/ApoA1 as independent factors associated with in-hospital MACE after PCI in STEMI patients. Based on these findings, a nomogram model was developed and validated, with the C-index in the training set at 0.77 (95% CI: 0.723-0.817), and the C-index in the validation set at 0.788 (95% CI: 0.734-0.841), indicating excellent discrimination accuracy. The calibration curves and clinical decision curves also demonstrated the good performance of the nomogram models. In patients with STEMI who underwent PCI, it was noted that a higher HbA1c of the ApoA1 ratio is significantly associated with in-hospital MACE. In addition, a nomogram is constructed having considered the above-mentioned risk factors to provide predictive information on in-hospital MACE occurrence in these patients. In particular, this tool is of great value to the clinical practitioners in determination of patients with a high risk.

Construction and validation of nomogram model for predicting the risk of ventricular arrhythmia after emergency PCI in patients with acute myocardial infarction

OBJECTIVE

To make predictions about the risk of MVA (Malignant Ventricular Arrhythmia) after primary PCI (Percutaneous Coronary Intervention) in patients with AMI (Acute Myocardial Infarction) through constructing and validating the Nomogram model.

METHODS

311 AMI patients who suffered from emergency PCI in Hefei Second People's Hospital from January 2020 to May 2023 were selected as the training set; 253 patients suffering from the same symptom in Hefei First People's Hospital during the same period were selected as the validation set. Risk factors were further screened by means of multivariate logistic and stepwise regression. The nomogram model was constructed, and then validated by using C-index, ROC curve, decision curve and calibration curve.

RESULTS

Multivariate logistic analysis revealed that urea, systolic pressure, hypertension, Killip class II-IV, as well as LVEF (Left Ventricular Ejection Fraction) were all unrelated hazards for MVA after emergency PCI for AMI (P<0.05); a risk prediction nomogram model was constructed. The C-index was calculated to evaluate the predictive ability of the model. Result showed that the index of the training and the validation set was 0.783 (95% CI: 0.726-0.84) and 0.717 (95% CI: 0.65-0.784) respectively, which suggested that the model discriminated well. Meanwhile, other tools including ROC curve, calibration curve and decision curve also proved that this nomogram plays an effective role in forecasting the risk for MVA after PCI in AMI patients.

CONCLUSIONS

The study successfully built the nomogram model and made predictions for the development of MVA after PCI in AMI patients.

Prognostic value of triglyceride-glucose index for left ventricular remodeling in nondiabetic ST-elevation myocardial infarction patients

Background: The triglyceride-glucose (TyG) index is a marker of insulin resistance and is associated with cardiovascular mortality and morbidity. Left ventricular remodeling (LVR) after myocardial infarction (STEMI) is associated with poor prognosis. Methods: This retrospective study included 293 STEMI patients. Echocardiography was performed before discharge and 3 months after MI. Results: Compared with the non-LVR group, TyG index value was found to be higher in the LVR group (p < 0.001). Logistic regression analysis showed that higher maximal troponin I value, higher calculated TyG index value, higher N-terminal prohormone of brain natriuretic peptide level and the presence of anterior MI were independently associated with the development of LVR. Conclusion: A high TyG index level may contribute to the prediction of LVR in nondiabetic STEMI patients undergoing successful primary percutaneous coronary intervention.