Clinical Nomogram to Predict Major Adverse Cardiac Events in Acute Myocardial Infarction Patients within 1 Year of Percutaneous Coronary Intervention

Global longitudinal strain and the risk of major adverse cardiac events in post-myocardial infarction patients: A retrospective cohort study

BACKGROUND

This study evaluates the relationship between global longitudinal strain (GLS) and late major adverse cardiovascular events (MACEs) in patients after acute myocardial infarction (AMI).

METHODS

Data of newly diagnosed AMI patients between March 2010 and July 2014 were retrospectively evaluated. The patients underwent serial echocardiography at admission and at third and sixth months post-admission. We calculated GLS by averaging the strain from all myocardial segments using speckle-tracking echocardiography (STE). We used multivariate Cox regression analysis and receiver operating characteristic (ROC) curve analyses to assess the relationship between GLS at admission and late MACEs.

RESULTS

Eighty-nine newly diagnosed AMI patients were enrolled. The average age at diagnosis was 61 ± 12.5 years, and approximately 89.9% of the patients were men. The average level of GLS was -17.5 ± 3.9%. The overall prevalence of MACEs was 23.6% (21/89), compared with 44% (11/25) in the group with GLS≥-15% and 17.9% (5/28) in the group with GLS<-20%. GLS was positively linked with MACEs in the fully adjusted Cox proportional hazard model (hazard ratio [HR], 1.19; 95% confidence interval [CI], 1.04-1.37; P=0.014) after adjusting potential confounders. The ROC curve analysis for one year MACEs between GLS at admission, with the most significant area under the curve(AUC) 78.1% (95% CI, 63.8% - 92.6%).

CONCLUSIONS

Myocardial dysfunction, characterized by impaired GLS, is often observed in AMI patients, and a decrease in GLS levels at admission were associated with an increased risk of long-term MACEs in post-myocardial infarction patients.

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.

Prediction models for major adverse cardiovascular events after percutaneous coronary intervention: a systematic review

Background

The number of models developed for predicting major adverse cardiovascular events (MACE) in patients undergoing percutaneous coronary intervention (PCI) is increasing, but the performance of these models is unknown. The purpose of this systematic review is to evaluate, describe, and compare existing models and analyze the factors that can predict outcomes.

Methods

We adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 during the execution of this review. Databases including Embase, PubMed, The Cochrane Library, Web of Science, CNKI, Wanfang Data, VIP, and SINOMED were comprehensively searched for identifying studies published from 1977 to 19 May 2023. Model development studies specifically designed for assessing the occurrence of MACE after PCI with or without external validation were included. Bias and transparency were evaluated by the Prediction Model Risk Of Bias Assessment Tool (PROBAST) and Transparent Reporting of a multivariate Individual Prognosis Or Diagnosis (TRIPOD) statement. The key findings were narratively summarized and presented in tables.

Results

A total of 5,234 articles were retrieved, and after thorough screening, 23 studies that met the predefined inclusion criteria were ultimately included. The models were mainly constructed using data from individuals diagnosed with ST-segment elevation myocardial infarction (STEMI). The discrimination of the models, as measured by the area under the curve (AUC) or C-index, varied between 0.638 and 0.96. The commonly used predictor variables include LVEF, age, Killip classification, diabetes, and various others. All models were determined to have a high risk of bias, and their adherence to the TRIPOD items was reported to be over 60%.

Conclusion

The existing models show some predictive ability, but all have a high risk of bias due to methodological shortcomings. This suggests that investigators should follow guidelines to develop high-quality models for better clinical service and dissemination.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=400835, Identifier CRD42023400835.

Predicting long-term prognosis after percutaneous coronary intervention in patients with acute coronary syndromes: a prospective nested case-control analysis for county-level health services

Purpose

We aimed to establish and authenticate a clinical prognostic nomogram for predicting long-term Major Adverse Cardiovascular Events (MACEs) among high-risk patients who have undergone Percutaneous Coronary Intervention (PCI) in county-level health service.

Patients and methods

This prospective study included Acute Coronary Syndrome (ACS) patients treated with PCI at six county-level hospitals between September 2018 and August 2019, selected from both the original training set and external validation set. Least Absolute Shrinkage and Selection Operator (LASSO) regression techniques and logistic regression were used to assess potential risk factors and construct a risk predictive nomogram. Additionally, the potential non-linear relationships between continuous variables were tested using Restricted Cubic Splines (RCS). The performance of the nomogram was evaluated based on the Receiver Operating Characteristic (ROC) curve analysis, Calibration Curve, Decision Curve Analysis (DCA), and Clinical Impact Curve (CIC).

Results

The original training set and external validation set comprised 520 and 1,061 patients, respectively. The final nomogram was developed using nine clinical variables: Age, Killip functional classification III-IV, Hypertension, Hyperhomocysteinemia, Heart failure, Number of stents, Multivessel disease, Low-density Lipoprotein Cholesterol, and Left Ventricular Ejection Fraction. The AUC of the nomogram was 0.79 and 0.75 in the training set and external validation set, respectively. The DCA and CIC validated the clinical value of the constructed prognostic nomogram.

Conclusion

We developed and validated a prognostic nomogram for predicting the probability of 3-year MACEs in ACS patients who underwent PCI at county-level hospitals. The nomogram could provide a precise risk assessment for secondary prevention in ACS patients receiving PCI.

In-hospital major adverse cardiovascular events after primary percutaneous coronary intervention in patients with acute ST-segment elevation myocardial infarction: a retrospective study under the China chest pain center (standard center) treatment system

BACKGROUND

Patients with acute ST-segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PCI) are at high risk of major adverse cardiovascular events (MACE) despite timely treatment. This study aimed to investigate the independent predictors and their predictive value of in-hospital MACE after primary PCI in patients with acute STEMI under the China chest pain center (standard center) treatment system.

METHODS

We performed a single-center, retrospective study of 151 patients with acute STEMI undergoing primary PCI. All patients were treated under the China chest pain center (standard center) treatment system. The data collected included general data, vital signs, auxiliary examination results, data related to interventional therapy, and various treatment delays. The primary endpoint was the in-hospital MACE defined as the composite of all-cause death, stroke, nonfatal recurrent myocardial infarction, new-onset heart failure, and malignant arrhythmias.

RESULTS

In-hospital MACE occurred in 71 of 151 patients with acute STEMI undergoing primary PCI. Logistic regression analysis showed that age, cardiac troponin I (cTnI), serum creatinine (sCr), multivessel coronary artery disease, and Killip class III/IV were risk factors for in-hospital MACE, whereas estimated glomerular filtration rate (eGFR), left ventricular ejection fraction (LVEF), systolic blood pressure (SBP), diastolic blood pressure (DBP), were protective factors, with eGFR, LVEF, cTnI, SBP, and Killip class III/IV being independent predictors of in-hospital MACE. The prediction model had good discrimination with an area under the curve = 0. 778 (95%CI: 0.690-0.865). Good calibration and clinical utility were observed through the calibration and decision curves, respectively.

CONCLUSIONS

Our data suggest that eGFR, LVEF, cTnI, SBP, and Killip class III/IV independently predict in-hospital MACE after primary PCI in patients with acute STEMI, and the prediction model constructed based on the above factors could be useful for individual risk assessment and early management guidance.

Meta-Analysis of the Effects of Recombinant Human Brain Natriuretic Peptides on Left Ventricular Remodeling in Patients with Acute Myocardial Infarction

Objective

Systematic evaluation of the efficacy of natriuretic recombination in human brain on disease myocardial infarction, left ventricular heart failure, and the efficacy and safety of long-term left ventricular remodeling.

Methods

Computerized search of CNKI, Wanfang database, Wipro Chinese Technology Publications (VIP) numerical database, Chinese Biomedical Literature Database (CBM), Medline Cochrane Library, clinical Trail.Gov clinical collection, and other documents. Randomized controlled trials (RCT) of recombinant human brain natriuretic peptide in the treatment of acute myocardial infarction from inception to December 2021 were searched. Based on the Jadad scale, inclusion-exclusion data for diseases were collected and elaborated by meta by RevMan 5.3 simulation software. In a total of 23 randomized controlled trials, 2 024 cases were used as the basic data, the control group was routinely treated for 1 012 cases, and 1 012 cases in the experimental group were also treated with natriuretic peptide in the recombinant human brain on the previous basis.

Results

In terms of overall efficacy, the experimental group was better than the control group, statistically significant (OR = 4.30, 95% CI (3.26, 5.67), P < 0.000 01), left ventricular ejection fraction in the experimental group than the control group (OR = 1.58, 95% CI (1.27, 1.90), P < 0.000 01). In terms of a myocardial strain in the left ventricle, the experimental group was superior to the control group. The difference was significant (OR = −0.91, 95% CI (-1.50, -0.33), P = 0.002). In terms of the cardiac output volume, the experimental group was superior to the control group (OR = 1.24, 95% CI (0.55, 1.94), P = 0.0005). Regarding brain natriuretic peptide precursors, the experimental group was superior to the control group (OR = −4.37, 95% CI (-6.21, -3.25), P < 0.00001). In terms of the heart rate, the experimental group was superior to the control group. Measurement of differential significance is as follows: OR = −13.70, 95% CI (-14.95, -12.46), P < 0.00001. In terms of contraction, the experimental group was superior to the comparison group (OR = −12.38, 95% CI (-17.98, -6.79), P < 0.00001). The experimental group outperformed the control group (OR = −7.42, 95% CI (-8.53, -6.30), P < 0.00001). In terms of bad influence, the measurement is as follows: OR = 0.95, 95% CI (0.29, 3.16), P = 0.94.

Conclusion

In patients with acute myocardial infarction and left ventricular remodeling, if treated with a heavy treatment of the group of cerebral natriuretic peptide mode, it can increase clinical treatment, improve the cardiac effect, inhibit ventricular remodeling, improve blood pressure and heart rhythm, and have greater clinical treatment and safety.