Evaluation of Risk Factors Associated with Reinfarction: A Multicenter Observational Study

Support vector machine deep mining of electronic medical records to predict the prognosis of severe acute myocardial infarction

Cardiovascular disease is currently one of the most important diseases causing death in China and the world, and acute myocardial infarction is a major cause of cardiovascular disease. This study provides an analytical technique for predicting the prognosis of patients with severe acute myocardial infarction using a support vector machine (SVM) technique based on information gleaned from electronic medical records in the Medical Information Marketplace for Intensive Care (MIMIC)-III database. The MIMIC-III database provided 4785 electronic medical records data for inclusion in the model development after screening 7070 electronic medical records of patients admitted to the intensive care unit for treatment of acute myocardial infarction. Adopting the APS-III score as the criterion for identifying anticipated risk, the dimensions of data information incorporated into the mathematical model design were found using correlation coefficient matrix heatmaps and ordered logistic analysis. An automated prognostic risk-prediction model was developed using SVM, and the fit was evaluated by 5× cross-validation. We used a grid search method to further optimize the parameters and improve the model fit. The excellent generalization ability of SVM was fully verified by calculating the 95% confidence interval of the area under the receiver operating characteristic curve (AUC) for six algorithms (linear discriminant, tree, Kernel Naive Bayes, RUSBoost, KNN, and SVM). Compared to the remaining five models, its confidence interval was the narrowest with higher fitting accuracy and better performance. The patient prognostic risk prediction model constructed using SVM had a relatively impressive accuracy (92.2%) and AUC value (0.98). In this study, a model was designed for fitting that can maximize the potential information to be gleaned in the electronic medical records data. It was demonstrated that SVM models based on electronic medical records data can offer an effective solution for clinical disease prognostic risk assessment and improved clinical outcomes and have great potential for clinical application in the clinical treatment of myocardial infarction.

Vasorelaxant and Antioxidant Effects of Aframomum pruinosum Gagnep. (Zingiberaceae) Seed Extracts May Mediate Their Cardioprotective Activity against Isoproterenol-Induced Myocardial Infarction

Aframomum pruinosum seeds are traditionally used in Cameroon to treat cardiac palpitations. The present work evaluates the cardioprotective effects of the aqueous (AE) and ethanolic (EE) extracts from A. pruinosum seeds against isoproterenol-induced myocardial infarction. Male Wistar rats were pretreated for 14 days with AE or EE at doses of 75 and 150 mg/kg/day or propranolol (10 mg/kg/day). On days 15 and 16, they were injected subcutaneously with isoproterenol (85 mg/kg/day). Blood pressure and heart rate were weekly recorded by tail-cuff plethysmography during pretreatment and 24 hours after the second dose of isoproterenol. At the end of the treatment period, serum Lactate Dehydrogenase (LDH), Alanine Aminotransferase (ALT), Aspartate Aminotransferase (AST), cardiac nitric oxide (NO), myeloperoxidase (MPO), and oxidative stress parameters (SOD, catalase, MDA, and GSH) were assayed. Sections of left ventricle tissue were subjected to histological analysis. The vasorelaxant effects of cumulative concentrations of AE or EE (3–300 µg/mL) were evaluated on intact or endothelium-denuded isolated aorta rings precontracted with noradrenaline (1 µM). The vasorelaxant effects of the plant extracts were also tested in the presence of N^ω-nitro-L-arginine methyl ester (L-NAME; 100 µM). AE and EE significantly prevented blood pressure decrease and heart rate increase elicited by isoproterenol. Both plant extracts inhibited the increase in ALT, AST, NO, and MPO but did not prevent LDH surge. Oxidative stress parameters were improved following A. pruinosum pretreatment. AE and EE highly reduced cardiomyocyte necrosis and fibrosis but did not prevent leukocyte infiltration. Both extracts induced a concentration-dependent vasorelaxation that was significantly inhibited by the destruction of the endothelium and by L-NAME. Extracts of A. pruinosum exhibited cardioprotective effects, and EE was the most active. The cardioprotective effects of A. pruinosum extracts could be ascribed to their antioxidant, antinecrotic, and endothelium-dependent vasorelaxant effects.

When More Means Less: The Prognosis of Recurrent Acute Myocardial Infarctions

Recurrent acute myocardial infarctions (AMI) are common and associated with dismal outcomes. We evaluated the clinical characteristics and the prognosis of AMI survivors according to the number of recurrent AMIs (ReAMI) and the time interval of events (TI). A retrospective analysis of patients who survived following hospitalization with an AMI throughout 2002–2017 was conducted. The number of ReAMIs for each patient during the study period was recorded and classified based on following: 0 (no ReAMIs), 1, 2, ≥3. Primary outcome: all-cause mortality up to 10 years post-discharge from the last AMI. A total of 12,297 patients (15,697 AMI admissions) were analyzed (age: 66.1 ± 14.1 years, 68% males). The mean number of AMIs per patient was 1.28 ± 0.7; the rates of 0, 1, 2, ≥3 ReAMIs were 81%, 13.4%, 3.6% and 1.9%, respectively. The risk of mortality increased in patients with greater number of AMIs, HR = 1.666 (95% CI: 1.603–1.720, p < 0.001) for each additional event (study group), attenuated following adjustment for potential confounders, AdjHR = 1.135 (95% CI: 1.091–1.181, p < 0.001). Increased risk of mortality was found with short TI (<6-months), AdjHR = 2.205 (95% CI: 1.418–3.429, p < 0.001). The risk of mortality following AMI increased as the number of ReAMIs increased, and the TI between the events shortened. These findings should guide improved surveillance and management of this high-risk group of patients (i.e., ReAMI).