Predicting death after acute myocardial infarction

Serum IGFBP5 as a predictor of major adverse cardiac events in patients with acute myocardial infarction

BACKGROUND

Acute myocardial infarction (AMI) is a serious condition with high mortality rates. Early risk stratification is of significant importance to assess the prognosis. Insulin-like growth factor-binding protein 5 (IGFBP5) levels in AMI patients and its potential as a prognosis biomarker were unclear.

OBJECTIVE

To investigate serum IGFBP5 levels in AMI and its prognostic value for short-term major adverse cardiovascular events (MACE).

METHODS

We collected serum IGFBP5 levels from 200 patients with new-onset AMI and 71 coronary heart disease (CAD) patients without AMI. Linear regression was used to analyze the relationship between IGFBP5 and baseline variables. AMI patients were followed up, and the risk of major adverse cardiovascular events (MACE) was assessed using Kaplan-Meier curve, multivariate Cox models and restricted cubic spline (RCS) analysis.

RESULTS

During a median follow-up of 217 days, 40 patients developed MACE. Serum IGFBP5 was associated with serum cardiac troponin T (cTnT) and C-reactive protein (CRP) (P = 0.013 and P = 0.013). In multivariable survival analyses, higher IGFBP5 was associated with an increased risk of MACE [HR = 1.183, 95%CI (1.104, 1.268), P < 0.001)]. There was a positive and linear association between IGFBP5 levels and the occurrence of MACE (P for nonlinearity = 0.283). The positive association between IGFBP5 and MACE risk consist across subgroups characterized by demographics and comorbidities.

CONCLUSION

Serum IGFBP5 was highly expressed in patients with AMI and positively associated with the short-term risk of MACE. Circulating IGFBP5 may be a diagnostic and prognostic indicator for AMI, and further studies with larger sample and longer follow-up are warranted.

Influence of prediabetes on the prognosis of patients with myocardial infarction: a meta-analysis

BACKGROUND

Previous studies evaluating the association between prediabetes the prognosis of patients with acute myocardial infarction (AMI) showed inconsistent results. The aim of the meta-analysis was to compare the long-term incidence of major adverse cardiovascular events (MACEs) between AMI patients with prediabetes and normoglycemia.

METHODS

Relevant prospective cohort studies were obtained by searching Medline, Web of Science, and Embase databases. Only studies with follow-up duration of at least one year were included. A random-effects model was utilized to pool the results by incorporating the influence of heterogeneity.

RESULTS

Twelve studies with 6972 patients with AMI were included. Among them, 2998 were with prediabetes and 3974 were with normoglycemia. During a mean follow-up of 52.6 months, 2100 patients developed MACEs. Compared to those with normoglycemia, AMI patients with prediabetes were associated with a higher incidence of MACEs (risk ratio [RR]: 1.30, 95% confidence interval: 1.07 to 1.58, p = 0.008; I2 = 67%). Subgroup analysis showed a stronger association between prediabetes and MACEs in studies of patients with mean age ≥ 60 years compared to < 60 years (RR: 1.66 versus 1.10, p for subgroup difference = 0.04), with proportion of men < 75% compared to ≥ 75% (RR: 1.87 versus 1.08, p for subgroup difference = 0.01), and in prediabetes evaluated at or after discharge compared to that evaluated within three days of AMI onset (RR: 1.39 versus 0.78, p for subgroup difference = 0.01).

CONCLUSIONS

Prediabetes may be associated with a higher risk of MACEs in patients with AMI.

Development and Validation of an Explainable Deep Learning Model to Predict In-Hospital Mortality for Patients With Acute Myocardial Infarction: Algorithm Development and Validation Study

BACKGROUND

Acute myocardial infarction (AMI) is one of the most severe cardiovascular diseases and is associated with a high risk of in-hospital mortality. However, the current deep learning models for in-hospital mortality prediction lack interpretability.

OBJECTIVE

This study aims to establish an explainable deep learning model to provide individualized in-hospital mortality prediction and risk factor assessment for patients with AMI.

METHODS

In this retrospective multicenter study, we used data for consecutive patients hospitalized with AMI from the Chongqing University Central Hospital between July 2016 and December 2022 and the Electronic Intensive Care Unit Collaborative Research Database. These patients were randomly divided into training (7668/10,955, 70%) and internal test (3287/10,955, 30%) data sets. In addition, data of patients with AMI from the Medical Information Mart for Intensive Care database were used for external validation. Deep learning models were used to predict in-hospital mortality in patients with AMI, and they were compared with linear and tree-based models. The Shapley Additive Explanations method was used to explain the model with the highest area under the receiver operating characteristic curve in both the internal test and external validation data sets to quantify and visualize the features that drive predictions.

RESULTS

A total of 10,955 patients with AMI who were admitted to Chongqing University Central Hospital or included in the Electronic Intensive Care Unit Collaborative Research Database were randomly divided into a training data set of 7668 (70%) patients and an internal test data set of 3287 (30%) patients. A total of 9355 patients from the Medical Information Mart for Intensive Care database were included for independent external validation. In-hospital mortality occurred in 8.74% (670/7668), 8.73% (287/3287), and 9.12% (853/9355) of the patients in the training, internal test, and external validation cohorts, respectively. The Self-Attention and Intersample Attention Transformer model performed best in both the internal test data set and the external validation data set among the 9 prediction models, with the highest area under the receiver operating characteristic curve of 0.86 (95% CI 0.84-0.88) and 0.85 (95% CI 0.84-0.87), respectively. Older age, high heart rate, and low body temperature were the 3 most important predictors of increased mortality, according to the explanations of the Self-Attention and Intersample Attention Transformer model.

CONCLUSIONS

The explainable deep learning model that we developed could provide estimates of mortality and visual contribution of the features to the prediction for a patient with AMI. The explanations suggested that older age, unstable vital signs, and metabolic disorders may increase the risk of mortality in patients with AMI.

Protective effect of esculentoside A against myocardial infarction via targeting C-X-C motif chemokine receptor 2

Myocardial infarction (MI) is the primary cause of cardiac mortality. Esculentoside A (EsA), a triterpenoid saponin, has anti-inflammatory and antioxidant activities. However, its effect on MI remains unknown. In this study, the protective effect and mechanisms of EsA against MI were investigated. EsA significantly alleviated hypoxia-induced HL-1 cell injury, including increasing cell viability, inhibiting reactive oxygen species (ROS) production, mitochondrial membrane potential (MMP) and lactate dehydrogenase (LDH) leakage. In mouse MI model by left coronary artery (LAD) ligating, EsA obviously restored serum levels of creatine kinase isoenzymes (CK-MB), cardiac troponin I (cTnI), superoxide dismutase (SOD) and malondialdehyde (MDA). In addition, the cardioprotective effect of EsA was further confirmed by infarct size, electrocardiogram and echocardiography. Mechanistically, the targeted binding relationship between EsA and C-X-C motif chemokine receptor 2 (CXCR2) was predicted by molecular docking and dynamics, and validated by small molecule pull-down and surface plasmon resonance tests. EsA inhibited CXCR2 level both in vitro and in vivo, correspondingly alleviated oxidative stress by suppressing NOX1 and NOX2 and relieved inflammation through inhibiting p65 and p-p65. It demonstrated that EsA could play a cardioprotective role by targeting CXCR2. However, the effect of EsA against MI was abolished in combination with CXCR2 overexpression both in vitro and in vivo. This study revealed that EsA showed excellent cardioprotective activities by targeting CXCR2 to alleviate oxidative stress and inflammation in MI. EsA may function as a novel CXCR2 inhibitor and a potent candidate for the prevention and intervention of MI in the future.

A Prediction Model Based on Systemic Immune-Inflammatory Index Combined with Other Predictors for Major Adverse Cardiovascular Events in Acute Myocardial Infarction Patients

Objective

To evaluate the prognostic value of the systemic immune-inflammatory index (SII) for predicting in-hospital major adverse cardiovascular events (MACEs) in patients with acute myocardial infarction (AMI) and establish a relevant nomogram.

Methods

This study included 954 AMI patients. We examined three inflammatory factors (SII, platelet to lymphocyte ratio (PLR) and neutrophil to lymphocyte ratio (NLR)) to see which one predicts in-hospital MACEs better. The predictors were subsequently screened using bidirectional stepwise regression method, and a MACE nomogram was constructed via logistic regression analysis. The predictive value of the model was evaluated using the area under the curve (AUC), sensitivity and specificity. In addition, the clinical utility of the nomogram was evaluated using decision curve analysis. We also compared the nomogram with the Global Registry of Acute Coronary Events (GRACE) scoring system.

Results

334 (35.0%) patients had MACEs. The SII (AUC =0.684) had a greater predictive value for in-hospital MACEs in AMI patients than the PLR (AUC =0.597, P<0.001) or NLR (AUC=0.654, P=0.01). The area under the curve (AUC) of the SII-based multivariable model for predicting MACEs, which was based on the SII, Killip classification, left ventricular ejection fraction, age, urea nitrogen (BUN) concentration and electrocardiogram-based diagnosis, was 0.862 (95% CI: 0.833-0.891). Decision curve and calibration curve analysis revealed that SII-based multivariable model demonstrated a good fit and calibration and provided positive net benefits than the model without SII. The predictive value of the SII-based multivariable model was greater than that of the GRACE scoring system (P<0.001).

Conclusion

SII is a promising, reliable biomarker for identifying AMI patients at high risk of in-hospital MACEs, and SII-based multivariable model may serve as a quick and easy tool to identify these patients.

Data analytics approach for short- and long-term mortality prediction following acute non-ST-elevation myocardial infarction (NSTEMI) and Unstable Angina (UA) in Asians

BACKGROUND

Traditional risk assessment tools often lack accuracy when predicting the short- and long-term mortality following a non-ST-segment elevation myocardial infarction (NSTEMI) or Unstable Angina (UA) in specific population.

OBJECTIVE

To employ machine learning (ML) and stacked ensemble learning (EL) methods in predicting short- and long-term mortality in Asian patients diagnosed with NSTEMI/UA and to identify the associated features, subsequently evaluating these findings against established risk scores.

METHODS

We analyzed data from the National Cardiovascular Disease Database for Malaysia (2006-2019), representing a diverse NSTEMI/UA Asian cohort. Algorithm development utilized in-hospital records of 9,518 patients, 30-day data from 7,133 patients, and 1-year data from 7,031 patients. This study utilized 39 features, including demographic, cardiovascular risk, medication, and clinical features. In the development of the stacked EL model, four base learner algorithms were employed: eXtreme Gradient Boosting (XGB), Support Vector Machine (SVM), Naive Bayes (NB), and Random Forest (RF), with the Generalized Linear Model (GLM) serving as the meta learner. Significant features were chosen and ranked using ML feature importance with backward elimination. The predictive performance of the algorithms was assessed using the area under the curve (AUC) as a metric. Validation of the algorithms was conducted against the TIMI for NSTEMI/UA using a separate validation dataset, and the net reclassification index (NRI) was subsequently determined.

RESULTS

Using both complete and reduced features, the algorithm performance achieved an AUC ranging from 0.73 to 0.89. The top-performing ML algorithm consistently surpassed the TIMI risk score for in-hospital, 30-day, and 1-year predictions (with AUC values of 0.88, 0.88, and 0.81, respectively, all p < 0.001), while the TIMI scores registered significantly lower at 0.55, 0.54, and 0.61. This suggests the TIMI score tends to underestimate patient mortality risk. The net reclassification index (NRI) of the best ML algorithm for NSTEMI/UA patients across these periods yielded an NRI between 40-60% (p < 0.001) relative to the TIMI NSTEMI/UA risk score. Key features identified for both short- and long-term mortality included age, Killip class, heart rate, and Low-Molecular-Weight Heparin (LMWH) administration.

CONCLUSIONS

In a broad multi-ethnic population, ML approaches outperformed conventional TIMI scoring in classifying patients with NSTEMI and UA. ML allows for the precise identification of unique characteristics within individual Asian populations, improving the accuracy of mortality predictions. Continuous development, testing, and validation of these ML algorithms holds the promise of enhanced risk stratification, thereby revolutionizing future management strategies and patient outcomes.

Favorable factors for the survival of ST-segment elevation myocardial infarction patients with medium- and high-risk thrombolysis in myocardial infarction scores

OBJECTIVE

ST-segment myocardial infarction (STEMI) is a time-sensitive emergency. This study screened the favorable factors for the survival of STEMI patients with medium- and high-risk thrombolysis in myocardial infarction (TIMI) scores.

METHODS

According to the TIMI scores at admission, 433 STEMI patients were retrospectively and consecutively selected and allocated into low-/medium-/high-risk groups, with their general information/blood routine/biochemical indicators/coagulation indicators documented. The factors influencing the in-hospital survival of STEMI patients were analyzed using univariate and multivariate logistic regression analyses. Moreover, the predictive value of favorable factors was analyzed by receiver operating characteristics (ROC) curve, and patients were assigned into high/low level groups based on the cut-off value of these factors, with their in-hospital survival rates compared.

RESULTS

The in-hospital survival rate of the medium-/high-risk groups was lower than that of the low-risk group. Emergency percutaneous coronary intervention (PCI), lymphocyte (LYM), total protein (TP), albumin (ALB), and sodium (Na) were independent favorable factors for in-hospital survival in the medium-/high-risk groups. Besides, LYM > 1.275 × 109/L, TP > 60.25 g/L, ALB > 34.55 g/L, and Na > 137.9 mmo1/L had auxiliary predictive value for the survival of STEMI patients with medium-/high-risk TIMI scores. Patients with high levels of LYM, TP, ALB, and Na exhibited higher in-hospital survival rates than patients with low levels.

CONCLUSION

For STEMI patients with medium- and high-risk TIMI scores, accepting emergency PCI and normal levels of LYM, TP, ALB, and Na were more conducive to in-hospital survival.

The predictive value of machine learning for mortality risk in patients with acute coronary syndromes: a systematic review and meta-analysis

BACKGROUND

Acute coronary syndromes (ACS) are the leading cause of global death. Optimizing mortality risk prediction and early identification of high-risk patients is essential for developing targeted prevention strategies. Many researchers have built machine learning (ML) models to predict the mortality risk in ACS patients. Our meta-analysis aimed to evaluate the predictive value of various ML models in predicting death in ACS patients at different times.

METHODS

PubMed, Embase, Web of Science, and Cochrane Library were searched systematically from database establishment to March 12, 2022 for studies developing or validating at least one ML predictive model for death in ACS patients. We used PROBAST to assess the risk of bias in the reported predictive models and a random-effects model to assess the pooled C-index and accuracy of these models.

RESULTS

Fifty papers were included, involving 216 ML prediction models, 119 of which were externally validated. The combined C-index of the ML models in the validation cohort predicting the in-hospital mortality, 30-day mortality, 3- or 6-month mortality, and 1 year or above mortality in ACS patients were 0.8633 (95% CI 0.8467-0.8802), 0.8296 (95% CI 0.8134-0.8462), 0.8205 (95% CI 0.7881-0.8541), and 0.8197 (95% CI 0.8042-0.8354), respectively, with the corresponding combined accuracy of 0.8569 (95% CI 0.8411-0.8715), 0.8282 (95% CI 0.7922-0.8591), 0.7303 (95% CI 0.7184-0.7418), and 0.7837 (95% CI 0.7455-0.8175), indicating that the ML models were relatively excellent in predicting ACS mortality at different times. Furthermore, common predictors of death in ML models included age, sex, systolic blood pressure, serum creatinine, Killip class, heart rate, diastolic blood pressure, blood glucose, and hemoglobin.

CONCLUSIONS

The ML models had excellent predictive power for mortality in ACS, and the methodologies may need to be addressed before they can be used in clinical practice.

Associations of physical activity types and intensity with cardiovascular diseases by age and gender among 18,730 Chinese adults

The associations of physical activity (PA) intensity and types with CVD (cardiovascular diseases) in different population are inconsistent and remains not very clear. A total of 7854 males and 10,876 females over 15 years were selected by multistage random sampling methods. In males, moderate-intensity physical activity (MPA) had no effect, while vigorous-intensity physical activity (VPA) played a significant protective role (OR = 1.319 and 0.615). However, in females, both MPA and VPA had significant protective effects (OR = 0.593 and 0.537). VPA presented as a significant protective factor in stroke patients and combined CVDs for males in all age groups; however, in females, the results suggested that, for those aged over 60-74 years, MPA was a protective factor. Furthermore, for the middle-aged or younger participants, the area under the curves (AUCs) of work, housework, and leisure activity were generally higher than that of other types, while for patients aged over 60 years, the AUCs of sedentary time and sleep activity seemed much higher. VPA had a better protective effect for preventing cardiovascular events, while the young and female population could benefit from MPA as well. Regardless of the types of PA, leisure activities were strongly recommended, and young people were much more likely to benefit from exercise than older people.

The ratio of QRS/RV6-V1: a new electrocardiographic predictor of short- and long-term adverse clinical outcomes in patients with acute myocardial infarction combined with new-onset right bundle branch block

Background

A few studies have focused on electrocardiography (ECG) parameters correlating with clinical prognosis in patients with acute myocardial infarction (AMI) combined with new-onset right bundle branch block (RBBB).

Objective

To assess the prognostic value of a new ECG parameter, namely, the ratio of QRS duration/RV₆-V₁ interval (QRS/RV₆-V₁), in patients with AMI combined with new-onset RBBB.

Materials and methods

A total of 272 AMI patients combined with new-onset RBBB who received primary percutaneous coronary intervention (P-PCI) were retrospectively enrolled in the study. First, the patients were divided into survival group and non-survival group. Demographic, angiographic, and ECG characteristics were compared between the two groups. Receiver operating characteristic (ROC) curve was used to screen the best ECG parameter for predicting 1-year mortality. Second, the ratio of QRS/RV₆-V₁, a continuous variable, was converted to the high ratio group and low ratio group according to the optimal cutoff value point determined by the X-tile software. We compared the patient's demographic, angiographic, and ECG characteristics, in-hospital major adverse cardiovascular events (MACE), and 1-year mortality between the two groups. Multivariate logistic and Cox regressions were used to evaluate whether the ratio of QRS/RV₆-V₁ was an independent prognostic factor of in-hospital MACE and 1-year mortality.

Results

The ROC curve showed that the ratio of QRS/RV₆-V₁ had a higher value for predicting in-hospital MACE and 1-year mortality than the QRS duration, RV₆-V₁ interval, and RV₁ interval. The patients in the high ratio group had significantly higher CK-MB peak and Killip class, lower ejection fraction (EF%), higher ratio of the left anterior (LAD) descending artery as infarct-related artery (IRA), and longer total ischemia time (TIT) than those in the low ratio group. The QRS duration was wider in the high ratio group than that in the low ratio group, whereas RV₆-V₁ was narrower in the high ratio group compared with that in the low ratio group. The in-hospital MACE rate (93.3% vs. 31.0%, p < 0.001) and 1-year mortality rate (86.7% vs. 13.2%, p < 0.001) in the high ratio group were higher than those in the low ratio group. The higher ratio of QRS/RV₆-V₁ was an independent predictor of in-hospital MACE (odds ratio, 8.55; 95% CI, 1.40-52.37; p = 0.02) after adjusting other confounders. Cox regression showed that the higher ratio of QRS/RV₆-V₁ predicted higher 1-year mortality of the patients with AMI combined with new-onset RBBB [hazard ratios (HR), 12.4; 95% CI, 7.26-21.22); p < 0.001] than the lower ratio of QRS/RV₆-V₁, and the HR still stayed at 2.21 even after a multivariable adjustment (HR, 2.21; 95% CI, 1.05-4.64); p = 0.037).

Conclusion

According to the results of our study, the high ratio of QRS/RV₆-V₁ (>3.0) was a valuable predictor of short- and long-term adverse clinical outcomes in AMI patients combined with new-onset RBBB. The implications of the high ratio of QRS/RV₆-V₁ were severe ischemia and pseudo synchronization between bi-ventricle.

Development and Validation of a Diagnostic Model Based on Hypoxia-Related Genes in Myocardial Infarction

Purpose

Myocardial infarction (MI) is a common cardiovascular disease, and its underlying pathological mechanism remains unclear. We aimed to develop a diagnostic model to distinguish different subtypes of MI.

Patients and Methods

The gene expression profiles of MI from the GEO database and hypoxia-related genes (HRGs) from MSigDB were downloaded. Then, the different MI subtypes based on HRGs were identified with unsupervised clustering. The difference of expression patterns and hypoxic-immune status among different subtypes of MI were investigated. The diagnostic model to distinguish the different subtypes of MI was developed and validated.

Results

Based on HRGs, MI samples were divided into two subtypes, cluster A and cluster B. A total of 211 genes showed significant changes in expression between the two subtypes. Cluster A was characterized by high hypoxia status and low immunity status. Based on weighted gene co-expression network analysis, ROC analysis and LASSO regression algorithm, 5 genes were identified as potential diagnostic markers. Finally, a diagnostic model based on these 5 genes was established, which can distinguish the two subtypes well.

Conclusion

The five hub genes, including ANKRD36, HLTF, KIF3A, OXCT1 and VPS13A, may be associated with the different subtypes of MI.

Circulating tumor necrosis factor-α, interleukin-1β, and interleukin-17A estimates increased major adverse cardiac event risk in acute myocardial infarction patients

BACKGROUND

Inflammatory cytokines are implicated in the development of atherosclerosis and cardiomyocyte injury during acute myocardial infarction (AMI). This study aimed to investigate the correlation of eight common inflammatory cytokines with major adverse cardiac event (MACE) risk and further establish a prognostic model in AMI patients.

METHODS

Serum samples of 210 AMI patients and 20 angina pectoris patients were, respectively, collected at admission, to detect tumor necrosis factor-alpha (TNF-α), interleukin (IL)-1β, IL-6, IL-8, IL-10, IL-17A, vascular cell adhesion molecule-1 (VCAM-1), and intercellular adhesion molecule 1 (ICAM-1) via enzyme-linked immunosorbent assay.

RESULTS

TNF-α, IL-6, IL-8, IL-17A, VCAM-1, and ICAM-1 were elevated (all p < 0.050); IL-10 (p = 0.009) was declined; IL-1β (p = 0.086) was not varied in AMI patients compared with angina pectoris patients. TNF-α (p = 0.008), IL-17A (p = 0.003), and VCAM-1 (p = 0.014) were elevated in patients with MACE occurrence compared to patients without MACE occurrence; meanwhile, they possessed a relatively good value for identifying MACE risk via receiver-operating characteristic (ROC) analysis. Subsequent multivariate logistic regression analysis revealed that the independent risk factors for MACE contained TNF-α (odds ratio (OR) = 1.038, p < 0.001), IL-1β (OR = 1.705, p = 0.044), IL-17A (OR = 1.021, p = 0.009), history of diabetes mellitus (OR = 4.188, p = 0.013), history of coronary heart disease (OR = 3.287, p = 0.042), and symptom-to-balloon time (OR = 1.064, p = 0.030), whose combination disclosed a satisfying prognostic value for MACE risk (area under the curve: 0.877, 95% CI: 0.817-0.936).

CONCLUSION

Elevated levels of serum TNF-α, IL-1β, and IL-17A independently correlated with MACE risk in AMI patients, which perhaps provide novel auxiliary for AMI prognostic prediction.

LncRNA AC005332.7 Inhibited Ferroptosis to Alleviate Acute Myocardial Infarction Through Regulating miR-331-3p/CCND2 Axis

BACKGROUND AND OBJECTIVES

Acute myocardial infarction (AMI) often occurs suddenly and leads to fatal consequences. Ferroptosis is closely related to the progression of AMI. However, the specific mechanism of ferroptosis in AMI remains unclear.

METHODS

We constructed a cell model of AMI using AC16 cells under oxygen and glucose deprivation (OGD) conditions and a mice model of AMI using the left anterior descending (LAD) ligation. The 3-(4, 5-dimethylthiazol-2-yl)-2, 5 diphenyltetrazolium bromide was employed to determine cell viability. The levels of lactate dehydrogenase, creatine kinase, reactive oxygen species (ROS), glutathione (GSH), malondialdehyde (MDA), and iron were measured using corresponding kits. Dual luciferase reporter gene assay, RNA-binding protein immunoprecipitation, and RNA pull-down were performed to validate the correlations among AC005332.7, miR-331-3p, and cyclin D2 (CCND2). Hematoxylin and eosin staining was employed to evaluate myocardial damage.

RESULTS

AC005332.7 and CCND2 were lowly expressed, while miR-331-3p was highly expressed in vivo and in vitro models of AMI. AC005332.7 sufficiency reduced ROS, MDA, iron, and ACSL4 while boosting the GSH and GPX4, indicating that AC005332.7 sufficiency impeded ferroptosis to improve cardiomyocyte injury in AMI. Mechanistically, AC005332.7 interacted with miR-331-3p, and miR-331-3p targeted CCND2. Additionally, miR-331-3p overexpression or CCND2 depletion abolished the suppressive impact of AC005332.7 on ferroptosis in OGD-induced AC16 cells. Moreover, AC005332.7 overexpression suppressed ferroptosis in mice models of AMI.

CONCLUSIONS

AC005332.7 suppressed ferroptosis in OGD-induced AC16 cells and LAD ligation-operated mice through modulating miR-331-3p/CCND2 axis, thereby mitigating the cardiomyocyte injury in AMI, which proposed novel targets for AMI treatment.

Interaction between Acute Hepatic Injury and Early Coagulation Dysfunction on Mortality in Patients with Acute Myocardial Infarction

BACKGROUND

In acute myocardial infarction (AMI), acute hepatic injury is an independent risk factor for prognosis and is associated with complex coagulation dynamics. This study aims to determine the interaction between acute hepatic injury and coagulation dysfunction on outcomes in AMI patients.

METHODS

The Medical Information Mart for Intensive Care (MIMIC-III) database was used to identify AMI patients who underwent liver function testing within 24 h of admission. After ruling out previous hepatic injury, patients were divided into the hepatic injury group and the nonhepatic injury group based on whether the alanine transaminase (ALT) level at admission was >3 times the upper limit of normal (ULN). The primary outcome was intensive care unit (ICU) mortality.

RESULTS

Among 703 AMI patients (67.994% male, median age 65.139 years (55.757-76.859)), acute hepatic injury occurred in 15.220% (n = 107). Compared with the nonhepatic injury group, patients with hepatic injury had a higher Elixhauser comorbidity index (ECI) score (12 (6-18) vs. 7 (1-12), p < 0.001) and more severe coagulation dysfunction (85.047% vs. 68.960%, p < 0.001). In addition, acute hepatic injury was associated with increased in-hospital mortality (odds ratio (OR) = 3.906; 95% CI: 2.053-7.433; p < 0.001), ICU mortality (OR = 4.866; 95% CI: 2.489-9.514; p < 0.001), 28-day mortality (OR = 4.129; 95% CI: 2.215-7.695; p < 0.001) and 90-day mortality (OR = 3.407; 95% CI: 1.883-6.165; p < 0.001) only in patients with coagulation disorder but not with normal coagulation. Unlike patients with coagulation disorder and normal liver, patients with both coagulation disorder and acute hepatic injury had greater odds of ICU mortality (OR = 8.565; 95% CI: 3.467-21.160; p < 0.001) than those with normal coagulation.

CONCLUSIONS

The effects of acute hepatic injury on prognosis are likely to be modulated by early coagulation disorder in AMI patients.

Association between red blood cell distribution width-to-albumin ratio and prognosis of patients with acute myocardial infarction

BACKGROUND

Red blood cell distribution width (RDW) and albumin level were considered to be related to the prognosis of patients with acute myocardial infarction (AMI). This study aims to investigate the correlation between RAR and 90-day mortality in AMI patients.

METHODS

Data of AMI patients were obtained from the Medical Information Mart for Intensive Care III (MIMIC-III) database. According to the median, RAR < 4.32 was regarded as low RAR level group, and RAR ≥ 4.32 as high RAR level group; low RDW level group was defined as < 14.00%, and high RDW level group as ≥ 14.00%; albumin < 3.30 g/dL was low level group, and albumin ≥ 3.30 g/dL as high level group. The outcome was the mortality rate within 90 days after admission to ICU. Univariate and multivariate Cox models were performed to determine the relationship between RAR and 90-day mortality in AMI patients with hazard ratio (HR) and 95% confidence interval (CI). Stratification analyses were conducted to explore the effect of RAR on 90-day mortality in different subgroups of age, gender, simplified acute physiology score II (SAPS II), elixhauser comorbidity index (ECI) score, treatment modalities and white blood cell.

RESULTS

Of the total 2081 AMI patients, 543 (26.09%) died within 90-day follow-up duration. The results showed that high RAR (HR = 1.65, 95% CI 1.34-2.03) and high RDW levels (HR = 1.31, 95% CI 1.08-1.61) were associated with an increased risk of death in AMI patients, and that high albumin level was related to a decreased risk of death (HR = 0.77, 95%CI 0.64-0.93). The relationship of RAR level and the mortality of AMI patients was also observed in the subgroup analysis. Additionally, the finding indicated that RAR might be a more effective biomarker for predicting 90-day mortality of AMI patients than albumin, RDW.

CONCLUSION

RAR may be a potential marker for the prognostic assessment of AMI, and a high RAR level was correlated with increased risk of 90-day mortality of AMI patients.

SGLT2 Inhibitors: New Hope for the Treatment of Acute Myocardial Infarction?

Among all of the new antidiabetic drugs, an increasing number of studies have evaluated the relationship between the sodium-glucose cotransporter 2 inhibitors (SGLT2i) and acute myocardial infarction (AMI). Since SGLT2i like empagliflozin, canagliflozin, and recently, dapagliflozin have shown impressive positive effects in patients with chronic heart failure with reduced ejection fraction (HFrEF), it has increased research interest to explore the cardiac molecular mechanisms underlying the clinical benefits and attracted more attention to the effects of SGLT2i on a series of cardiovascular events. Experimental and clinical data on SGLT2i treatment after AMI is limited. This is a review of the clinical and preclinical effects of SGLT2i, focusing on available data on the effects of SGLT2i in AMI patients with a brief overview of ongoing trials.

The Value of Different Short-Term Risk Scoring Models in Predicting Long-Term Death of Acute Myocardial Infarction

Background and aims: To compare the value of three commonly used cardiovascular short-term risk scoring models, the GRACE score, TIMI score, and HEART score, in predicting the long-term prognosis of patients with acute myocardial infarction. Methods: The hospitalization data of patients who were hospitalized in West China Hospital of Sichuan University from 2011 to 2013 and diagnosed with acute myocardial infarction (AMI) were collected. The patients were scored by GRACE score, TIMI score, and HEART score. The long-term follow-up of patients was conducted until the end of January 2021. All-cause death and time of death of patients were confirmed by telephone follow-up, electronic medical record query, and household registration information. The predictive ability of different risk scores for long-term prognosis was compared according to the receiver operating characteristic (ROC) area under the curve (AUC), and the ability to distinguish patients with different risk levels was compared according to Kaplan−Meier survival curves. Results: The study ultimately included 2220 patients, with a median follow-up of 8 years and 454 (20.5%) deaths until the end of follow-up. Whether in ST-segment elevation myocardial infarction (STEMI) patients or non-ST-segment elevation myocardial infarction (NSTEMI) patients, the AUC value of the GRACE score (both AUC = 0.734) was significantly higher than the TIMI score (AUC = 0.675, p < 0.01; AUC = 0.665, p < 0.01) and HEART score (AUC = 0.632, p < 0.01; AUC = 0.611, p < 0.01) until the end of follow-up. In terms of risk stratification, the Kaplan−Meier survival curve shows that both THE GRACE score and TIMI score can distinguish AMI patients with different risk levels (p < 0.01), but the risk stratification ability of the HEART score in AMI patients was poor (p > 0.05). Conclusion: The GRACE risk score could represent a more accurate model to assess long-term death of acute myocardial infarction, but further studies are required.

Prognostic implications for patients after myocardial infarction: an integrative literature review and in-depth interviews with patients and experts

Background

As patients with myocardial infarction (MI) survive for a long time after acute treatment, it is necessary to pay attention to the prevention of poor prognosis such as heart failure (HF). To identify the influencing factors of adverse clinical outcomes through a review of prospective cohort studies of post-MI patients, and to draw prognostic implications through in-depth interviews with post-MI patients who progressed to HF and clinical experts.

Methods

A mixed-method design was used that combined a scoping review of 21 prospective cohort studies, in-depth interviews with Korean post-MI patients with HF, and focus group interviews with cardiologists and nurses.

Results

A literature review showed that old age, diabetes, high Killip class, low left ventricular ejection fraction, recurrent MI, comorbidity of chronic disease and current smoking, and low socioeconomic status were identified as influencing factors of poor prognosis. Through interviews with post-MI patients, these influencing factors identified in the literature as well as a lack of disease awareness and lack of self-care were confirmed. Experts emphasized the importance of maintaining a healthy lifestyle after acute treatment with the recognition that it is a chronic disease that must go together for a lifetime.

Conclusion

This study confirmed the factors influencing poor prognosis after MI and the educational needs of post-MI patients with transition to HF. Healthcare providers should continue to monitor the risk group, which is expected to have a poor prognosis, along with education emphasizing the importance of self-care such as medication and lifestyle modification.

The potential role of circulating exosomes in protecting myocardial injury in acute myocardial infarction via regulating miR-190a-3p/CXCR4/CXCL12 pathway

Exosomes of different origins have been found to be protective against ischemic-induced myocardial injury. This study examined the protective effects of circulating exosomes in the mice model of acute myocardial infarction (AMI) and explored the underlying molecular mechanisms. The effects of exosomes on myocardial injury were assessed in the AMI mice model. The in vivo studies showed that circulating exosomes reduced the infarcted size, improved the morphology of heart tissues and also reduced apoptosis of the heart tissues. In addition, the model mice showed an increase in the CD34 + /VEGFR2 + cell population and CD31, CXCR4 and CXCL12 expression after exosomes treatment. MiR-190a-3p was significantly down-regulated in the exosomes derived from the culture medium of hypoxia-treated human cardiomyocytes (HCMs). Further analysis revealed that miR-190a-3p could physically interact with CXCR4/CXCL12 by targeting the respective 3'UTRs. These exosomes could up-regulated CXCR4 and CXCL12 expression in the EPCs; in addition, miR-190a-3p mimics repressed CXCR4/CXCL12 expression in EPCs, while its inhibitor had opposite effects. The in vitro functional assays showed that miR-190a-3p overexpression suppressed the cell viability, proliferation, migration, adhesion and tube formation of EPCs; while miR-190a-3p inhibitor had the opposite effects; exosomes derived from the culture medium of hypoxia-treated HCMs exhibited similar actions of miR-190a-3p inhibitor. Moreover, miR-190a-3p was down-regulated in exosomes from serum in the AMI group when compared to that from sham group. Treatment with exosomes from serum in the AMI group promoted cell proliferation, migration, adhesion and tube formation of EPCs when compared to that in the sham group. More importantly, IT1t attenuated the enhanced effects of miR-190a-3p inhibition on EPC proliferation, migration, adhesion and tube formation. In conclusion, circulating exosomes exerted protective effects on myocardial injury in the AMI mice model, and down-regulation of miR-190a-3p in the circulating exosomes may exert protective effects against myocardial injury. Hypoxia induced the downregulation of miR-190a-3p in the culture medium of HCMs, and the mechanistic investigations indicated that exosomes of hypoxia-conditioned HCM culture medium promoted the cell viability, proliferation, migration, adhesion and tube formation of EPCs via regulating miR-190a-3p/CXCR4/CXCL12 pathway.

Traditional Chinese Medicine Shen-Yuan-Dan (SYD) Improves Hypoxia-Induced Cardiomyocyte Apoptosis in Neonatal Rats by Upregulating miR-24/Bim Pathway

Background: Acute myocardial infarction (AMI) is the leading cause of malignant arrhythmia, heart failure, and sudden death. However, safe and effective drugs for the treatment of AMI are unavailable to date. The present study aimed to investigate the role of traditional Chinese medicine shen-yuan-dan (SYD) in hypoxia-induced cardiomyocyte apoptosis in neonatal rats. In addition, the study explored the possible mechanism through which SYD could reduce myocardial ischemia apoptosis and regulate the expression of the miR-24/Bim pathway. Methods: Hypoxia-induced neonatal rat cardiomyocytes were used for the experiments. These cardiomyocytes were transfected with an miR-24 mimic and an miR-24 inhibitor and then cocultured with SYD-containing serum. MTT and lactate dehydrogenase (LDH) assays, AnnexinV/PI double staining, flow cytometry, and TUNEL staining were used to determine the cell viability and apoptosis under hypoxic conditions. Furthermore, the expression level of Bim in the hypoxia-induced cardiomyocytes was determined through western blotting and quantitative real-time polymerase chain reaction. Results: After 48 h of hypoxia, LDH and creatine phosphokinase (CPK) activities increased, cell viability decreased, and miR-24 expression upregulated in the cardiomyocytes. SYD alleviated hypoxia-induced cardiomyocyte injury, decreased LDH and CPK activities, increased cell viability, and reduced apoptosis in the neonatal rat cardiomyocytes. Moreover, SYD could upregulate miR-24 expression and downregulate Bim expression. Upregulation of miR-24 expression significantly enhanced the effect of SYD, thereby improving myocardial cell apoptosis. Dual-luciferase reporter assay and western blot analysis confirmed that Bim was a direct target of miR-24. Conclusion: SYD treatment reduces hypoxia-induced myocardial apoptosis by upregulating miR-24 expression. This study provides new insights into the molecular mechanism underlying the therapeutic potential of SYD in promoting the recovery of myocardial function and delaying the incidence of heart failure.

LncRNA HOTTIP Knockdown Attenuates Acute Myocardial Infarction via Regulating miR-92a-2/c-Met Axis

Increasing investigations have focused on long non-coding RNAs (lncRNAs) in various human diseases, including acute myocardial infarction (AMI). Although lncRNA HOTTIP has been identified to play an important role in coronary artery diseases, its role and specific mechanism in AMI remain unclear. To investigate the potential role of HOTTIP in MI, HOTTIP expression in hypoxia-treated cardiomyocytes and myocardial tissues of MI mice was evaluated. The potential targets of HOTTIP and miR-92a-2 were predicted using Starbase and Targetscan. To further determine the cardio-protective effects of HOTTIP in vivo, si-HOTTIP and miR-92a-2 mimics were individually or co-injected into mice through intramyocardial injection. Moreover, their roles were further confirmed in rescue experiments. HOTTIP was significantly upregulated in ischemic myocardium of MI mice and hypoxia-induced cardiomyocytes. Moreover, HOTTIP knockdown markedly promoted cardiomyocyte growth and inhibited cardiomyocyte apoptosis in vitro. Luciferase reporter assay showed that HOTTIP could directly sponge miR-92a-2 to negatively regulate miR-92a-2 expression. In addition, c-Met was identified as a direct target of miR-92a-2, and their correlation was confirmed by luciferase reporter assay. MiR-92a-2 overexpression significantly enhanced the protective effect of HOTTIP knockdown against AMI through partially inhibiting c-Met expression. Our results demonstrated that HOTTIP downregulation attenuated AMI progression via the targeting miR-92a-2/c-Met axis and suggested that HOTTIP might be a potential therapeutic target for AMI.

Network Pharmacology-Based Investigation and Experimental Exploration of the Antiapoptotic Mechanism of Colchicine on Myocardial Ischemia Reperfusion Injury

Background: The beneficial effects of colchicine on cardiovascular disease have been widely reported in recent studies. Previous research demonstrated that colchicine has a certain protective effect on ischemic myocardium and has the potential to treat myocardial ischemia reperfusion injury (MIRI). However, the potential targets and pharmacological mechanism of colchicine to treat MIRI has not been reported.

Methods: In this study, we used network pharmacology and experimental verification to investigate the pharmacological mechanisms of colchicine for the treatment of MIRI. Potential targets of colchicine and MIRI related genes were screened from public databases. The mechanism of colchicine in the treatment of MIRI was determined by protein-protein interaction (PPI), gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Additionally, we evaluated the effect of colchicine on H9C2 cell activity using CCK-8 assays, observed the effect of colchicine on H9C2 cell apoptosis via flow cytometry, and further verified the expression of key targets after colchicine treated by Western blot.

Results: A total of 626 target genes for colchicine and 1549 MIRI disease targets were obtained. 138 overlapping genes were determined as potential targets of colchicine in treating MIRI. the PPI network analysis demonstrated that the targets linked to MIRI were ALB, TNF, ACTB, AKT1, IL6, TP53, IL1B, CASP3 and these targets showed nice affinity with colchicine in molecular docking experiments. The results of GO analysis and KEGG pathway enrichment demonstrated that the anti-MIRI effect of colchicine involves in apoptotic signaling pathway. Further tests suggested that colchicine can protect H9C2 cell from Hypoxia/Reoxygenation (H/R) injury through anti-apoptotic effects. Western blot results demonstrated that colchicine can inhibited MIRI induced apoptosis of H9C2 cell by enhancing the decreased levels of Caspase-3 in myocardial injure model induced by H/R and activating the PI3K/AKT/eNOS pathway.

Conclusions: we performed network pharmacology and experimental evaluation to reveal the pharmacological mechanism of colchicine against MIRI. The results from this study could provide a theoretical basis for the development and clinical application of colchicine.

MARKER DIAGNOSTIC HEART FAILURE PROGRESSION IN THE POST-INFARCTION PERIOD

OBJECTIVE

The aim: To study the relationship between the concentration of copeptin, NT-proBNP, ST2 and indicators of myocardial remodeling, the dynamics of these indicators in order to predict the occurrence of decompensated heart failure (HF) in patients with acute myocardial infarction (AMI).

PATIENTS AND METHODS

Materials and methods: The study is based on the results of the examination of 160 patients with MI, including 120 patients with decompensated CHF II A-B stage according to Vasylenko-Strazhesko classification of (FC) III-IV (according to NYHA) and 40 patients with MI without signs of decompensated CHF, as well as 20 medically healthy individuals. The level of copeptin, NT-proBNP, ST2 were determined.

RESULTS

Results: In patients with signs of decompensated HF there were significantly higher levels of NT-proBNP in the blood serum that amounted to (950.38±3.15) pg/ml, in patients without decompensated HF after MI (580.15±3.03) pg/ml compared to healthy individuals (111.20±3.47) pg/ml (p<0.05). The mean value of copeptin concentration in patients with decompensated CHF was recorded (18.11±0.12) pg/ml, compared to (12.03±0.14) pg/ml in patients with MI without signs of CHF decompensation.

CONCLUSION

Conclusions: The most significant for clinical and prognostic assessment of the post-infarction period complicated by decompensated HF is the response of the patient's body to dosed physical exertion and the levels of NT-prpBNP, copeptin and ST2.

Potential biomarkers of acute myocardial infarction based on co‑expression network analysis

Acute myocardial infarction (AMI) is a common cause of death in numerous countries. Understanding the molecular mechanisms of the disease and analyzing potential biomarkers of AMI is crucial. However, specific diagnostic biomarkers have thus far not been fully established and candidate regulatory targets for AMI remain to be determined. In the present study, the AMI gene chip dataset GSE48060 comprising blood samples from control subjects with normal cardiac function (n=21) and patients with AMI (n=26) was downloaded from Gene Expression Omnibus. The differentially expressed genes (DEGs) between the AMI and control groups were identified with the online tool GEO2R. The co-expression network of DEGs was analyzed by calculating the Pearson correlation coefficient of all gene pairs, mutual rank screening and cutoff threshold screening. Subsequently, the Gene Ontology (GO) database was used to analyze the genes' functions and pathway enrichment of genes in the most important modules was performed. Kyoto Encyclopedia of Genes and Genomes (KEGG) Disease and BioCyc were used to analyze the hub genes in the module to determine important sub-pathways. In addition, the expression of hub genes was confirmed by reverse transcription-quantitative PCR in AMI and control specimens. In the present study, 52 DEGs, including 26 upregulated and 26 downregulated genes, were identified. As key hub genes, three upregulated genes (AKR1C3, RPS24 and P2RY12) and three downregulated genes (ACSL1, B3GNT5 and MGAM) were identified from the co-expression network. Furthermore, GO enrichment analysis of all AMI co-expression network genes revealed functional enrichment mainly in ‘RAGE receptor binding’ and ‘negative regulation of T cell cytokine production’. In addition, KEGG Disease and BioCyc analysis indicated functional enrichment of the genes RPS24 and P2RY12 in ‘cardiovascular diseases’, of AKR1C3 in ‘cardenolide biosynthesis’, of MGAM in ‘glycogenolysis’, of B3GNT5 in ‘glycosphingolipid biosynthesis’ and of ACSL1 in ‘icosapentaenoate biosynthesis II’. In conclusion, the hub genes AKR1C3, RPS24, P2RY12, ACSL1, B3GNT5 and MGAM are potential markers of AMI, and have potential application value in the diagnosis of AMI.

Pyroptosis inhibition improves the symptom of acute myocardial infarction

Acute myocardial infarction (AMI), the leading cause of mortality worldwide, is a rapidly developing and irreversible disease. Therefore, proper prompt intervention at the early stage of AMI is crucial for its treatment. However, the molecular features in the early stage have not been clarified. Here, we constructed mouse AMI model and profiled transcriptomes and proteomes at the early stages of AMI progress. Immune system was extensively activated at 6-h AMI. Then, pyroptosis was activated at 24-h AMI. VX-765 treatment, a pyroptosis inhibitor, significantly reduced the infarct size and improved the function of cardiomyocytes. Besides, we identified that WIPI1, specifically expressed in heart, was significantly upregulated at 1 h after AMI. Moreover, WIPI1 expression is significantly higher in the peripheral blood of patients with AMI than healthy control. WIPI1 can serve as a potential early diagnostic biomarker for AMI. It likely decelerates AMI progress by activating autophagy pathways. These findings shed new light on gene expression dynamics in AMI progress, and present a potential early diagnostic marker and a candidate drug for clinical pre-treatment to prolong the optimal cure time.

CircRNA MFACR Is Upregulated in Myocardial Infarction and Downregulates miR-125b to Promote Cardiomyocyte Apoptosis Induced by Hypoxia

ABSTRACT

Circular RNA (circRNA) MFACR promotes cardiomyocyte death that leads to myocardial infarction (MI). This study aimed to explore the role of MFACR in MI. T-qPCRs were performed to measure the expression levels of MFACR and miR-125b in plasma samples from both MI patients (n = 61) and healthy controls (n = 61). MFACR or miR-125b was overexpressed in AC16 cells (cardiomyocytes) to explore the interaction between them. Methylation of miR-125b gene in cells with the overexpression of MFACR was detected by methylation-specific PCR. Cell apoptosis after transfections was detected by cell apoptosis assay. MI model was constructed to further demonstrate the effect of MFACR in vivo. We found that MFACR was upregulated in MI and inversely correlated with miR-125b. In AC16 cells, hypoxia treatment increased the expression levels of MFACR and decreased the expression levels of miR-125b. In AC16 cells, overexpression of MFACR decreased the expression levels of miR-125b and increased the methylation of miR-125b gene. Under hypoxia treatment, overexpression of MFACR increased AC16 cell apoptosis, and overexpression of miR-125b decreased cell apoptosis. In addition, overexpression of miR-125b reversed the effects of overexpression of MFACR on cell apoptosis both in vivo and in vitro.

The efficacy of ivabradine in the treatment of acute myocardial infarction: A protocol for systematic review and meta-analysis

BACKGROUND

Cardiovascular diseases have become a prominent threat to public health and quality of life. In recent years, some studies have reported that ivabradine can improve the cardiac function and prognosis of patients with acute myocardial infarction (AMI). Therefore, we perform a protocol for systematic review and meta-analysis to evaluate the efficacy of ivabradine for treating AMI.

METHODS

This protocol of systematic review and meta-analysis has been drafted under the guidance of the preferred reporting items for systematic reviews and meta-analyses protocols. We will search PubMed, Cochrane Library, Embase, Web of Science, and Medline databases for relevant studies. In addition, we will also collect 4 databases of China: China National Knowledge Infrastructure, China Biomedical Literature Database, China Science Journal Database, and Wan-fang Database. Risk of bias will be assessed using the Cochrane Handbook risk of bias assessment tool version (V.5.1.0). We will use STATA 16.0 software (Stata Corporation, College Station, TX) to perform data analysis.

RESULTS

The results of this systematic review and meta-analysis will be published in a peer-reviewed journal.

CONCLUSION

We hypothesized that ivabradine can reduce the resting heart rate and improve heart function in patients with AMI.

Machine learning enhances the performance of short and long-term mortality prediction model in non-ST-segment elevation myocardial infarction

Machine learning (ML) has been suggested to improve the performance of prediction models. Nevertheless, research on predicting the risk in patients with acute myocardial infarction (AMI) has been limited and showed inconsistency in the performance of ML models versus traditional models (TMs). This study developed ML-based models (logistic regression with regularization, random forest, support vector machine, and extreme gradient boosting) and compared their performance in predicting the short- and long-term mortality of patients with AMI with those of TMs with comparable predictors. The endpoints were the in-hospital mortality of 14,183 participants and the three- and 12-month mortality in patients who survived at discharge. The performance of the ML models in predicting the mortality of patients with an ST-segment elevation myocardial infarction (STEMI) was comparable to the TMs. In contrast, the areas under the curves (AUC) of the ML models for non-STEMI (NSTEMI) in predicting the in-hospital, 3-month, and 12-month mortality were 0.889, 0.849, and 0.860, respectively, which were superior to the TMs, which had corresponding AUCs of 0.873, 0.795, and 0.808. Overall, the performance of the predictive model could be improved, particularly for long-term mortality in NSTEMI, from the ML algorithm rather than using more clinical predictors.

Mechanism and therapeutic strategies of depression after myocardial infarction

Depression resulted as an important factor associated with the myocardial infarction (MI) prognosis. Patients with MI also have a higher risk for developing depression. Although the issue of depression after MI has become a matter of clinical concern, the molecular mechanism underlying depression after MI remains unclear, whereby several strategies suggested have not got ideal effects, such as selective serotonin reuptake inhibitors. In this review, we summarized and discussed the occurrence mechanism of depression after MI, such as 5-hydroxytryptamine (5-HT) dysfunction, altered hypothalamus-pituitary-adrenal (HPA) axis function, gut microbiota imbalance, exosomal signal transduction, and inflammation. In addition, we offered a succinct overview of treatment, as well as some promising molecules especially from natural products for the treatment of depression after MI.

Sequential Pattern Mining to Predict Medical In-Hospital Mortality from Administrative Data: Application to Acute Coronary Syndrome

Prediction of a medical outcome based on a trajectory of care has generated a lot of interest in medical research. In sequence prediction modeling, models based on machine learning (ML) techniques have proven their efficiency compared to other models. In addition, reducing model complexity is a challenge. Solutions have been proposed by introducing pattern mining techniques. Based on these results, we developed a new method to extract sets of relevant event sequences for medical events' prediction, applied to predict the risk of in-hospital mortality in acute coronary syndrome (ACS). From the French Hospital Discharge Database, we mined sequential patterns. They were further integrated into several predictive models using a text string distance to measure the similarity between patients' patterns of care. We computed combinations of similarity measurements and ML models commonly used. A Support Vector Machine model coupled with edit-based distance appeared as the most effective model. We obtained good results in terms of discrimination with the receiver operating characteristic curve scores ranging from 0.71 to 0.99 with a good overall accuracy. We demonstrated the interest of sequential patterns for event prediction. This could be a first step to a decision-support tool for the prevention of in-hospital death by ACS.

Long non-coding RNA XIST promotes the proliferation of cardiac fibroblasts and the accumulation of extracellular matrix by sponging microRNA-155-5p

Acute myocardial infarction (AMI) is characterized by cardiomyocyte death followed by myocardial fibrosis, eventually leading to heart failure. Long non-coding (lnc)RNA X-inactive specific transcript (XIST) serves a vital role in the regulation of fibrosis. The aim of the present study was to determine whether myocardial fibrosis may be regulated by XIST and to elucidate the underlying mechanism. The relative mRNA expression levels of the target genes were evaluated using reverse transcription-quantitative polymerase chain reaction. Cell viability and apoptosis were determined using a Cell Counting Kit-8 assay and flow cytometry, respectively. The apoptosis and fibrosis-related protein expression levels were detected using western blot analysis. Finally, the interaction between XIST and microRNA (miR)-155-5p was analyzed using a luciferase reporter assay. XIST-overexpression increased proliferation and the expression level of the fibrosis-related proteins in the human cardiac fibroblast cells (HCFs). XIST directly targeted miR-155-5p and downregulated its expression, while miR-155-5p downregulation abolished the effect of XIST-silencing on cell viability and the expression level of the fibrosis-related proteins in the HCFs. XIST promoted cell proliferation and the expression level of fibrosis-related proteins by sponging miR-155-5p. Therefore, XIST may represent a novel effective target for AMI treatment.

Prediction Factors of 6-Month Poor Prognosis in Acute Myocardial Infarction Patients

Background: Acute myocardial infarction (AMI) is among the leading causes of death worldwide. Patients with AMI may have the risk of developing recurrent cardiovascular events leading to rehospitalization or even death. The present study aimed to investigate the prediction factors of poor prognosis (mortality and/or readmission) after AMI during a 6-month follow-up.

Methods: A total of 206 consecutive patients hospitalized for the first visit with AMI were enrolled. Data collection included demographic characteristics, medical history, clinical information, laboratory results, and oral medications within 24 h of admission. At 1, 3, and 6 months after discharge, AMI patients were followed up to assess the occurrence of composite endpoint events including in-hospital and out-of-hospital death and/or readmission due to recurrent myocardial infarction (MI) or exacerbated symptoms of heart failure following MI.

Results: After 6-month follow-up, a total of 197 AMI patients were available and divided in two groups according to good prognosis (n = 144) and poor prognosis (n = 53). Our data identified serum myoglobin ≥651 ng/mL, serum creatinine ≥96 μM, Killip classification 2–4, and female gender as independent predictors of 6-month mortality and/or readmission after AMI. Moreover, we demonstrated that Killip classification 2–4 combined with either myoglobin (AUC_{Killip class 2−4+myoglobin} = 0.784, sensitivity = 69.8%, specificity = 79.9%) or creatinine (AUC_{Killip class 2−4+creatinine} = 0.805, sensitivity = 75.5%, specificity = 77.1%) could further enhance the predictive capacity of poor 6-month prognosis among AMI patients.

Conclusions: Patients with AMI ranked in the higher Killip class need to be evaluated and monitored with attention. Multibiomarker approach using Killip classification 2–4 and myoglobin or creatinine may be an effective way for 6-month prognosis prediction in AMI patients.

Prognostic Value of Braden Scale in Patients With Acute Myocardial Infarction: From the Retrospective Multicenter Study for Early Evaluation of Acute Chest Pain

BACKGROUND

The Braden Scale (BS) is a routine nursing measure used to predict pressure ulcer events; it is recommended as a frailty identification instrument.

OBJECTIVE

We aimed to evaluate the predictive utility of the BS in patients with acute myocardial infarction (AMI) undergoing primary percutaneous coronary intervention.

METHODS

We enrolled 2285 patients with AMI from the Retrospective Multicenter Study for Early Evaluation of Acute Chest Pain. The patients were divided into 3 groups (B1, B2, and B3) according to their BS score (≤12 vs 13-14 vs ≥15). The primary endpoint was all-cause death.

RESULTS

There were 264 (12.0%) all-cause deaths during the median follow-up period of 10.5 (7.9-14.2) months. In-hospital and midterm mortality and other adverse outcomes increased with decreases in the BS score. The Kaplan-Meier survival analysis showed that patients with a lower BS score had a lower cumulative survival rate (P < .001). The multivariate Cox regression analysis showed that a decreased BS score was an independent predictor for all-cause mortality (B2 vs B1: hazard ratio, 0.610; 95% confidence interval, 0.440-0.846; P = .003; B3 vs B1: hazard ratio, 0.345; 95% confidence interval, 0.241-0.493; P < .001).

CONCLUSIONS

The BS at admission may be a useful routine nursing measure to evaluate the prognosis of patients with AMI. The BS may be used to stratify risk at early stages and to identify those who may benefit from further assessment and intervention due to frailty syndrome.

lncRNA-ZFAS1 induces mitochondria-mediated apoptosis by causing cytosolic Ca2+ overload in myocardial infarction mice model

Previously, we have identified ZFAS1 as a potential new long non-coding RNA (lncRNA) biomarker of acute myocardial infarction (MI) and as a sarcoplasmic reticulum Ca²⁺-ATPase 2a (SERCA2a) inhibitor, causing intracellular Ca²⁺ overload and contractile dysfunction in a mouse model of MI. In the current study, we aimed to evaluate the effects of ZFAS1 on the apoptosis of cardiomyocytes in the MI mouse model. Knockdown of endogenous ZFAS1 by virus-mediated silencing shRNA or siZFAS1 partially abrogated the ischemia-induced apoptosis of cardiomyocytes. Overexpression of ZFAS1 in normal cardiomyocytes reduced the cell viability, similar to that observed in hypoxia-treated cardiomyocytes. Moreover, ZFAS1 cardiac-specific knock-in mice showed impaired cardiac function, adversely altered Ca²⁺ homeostasis, repressed expression and activities of SERCA2a, and increased apoptosis. At the subcellular level, ZFAS1 induced mitochondrial swelling and showed a pronounced decrease in mitochondrial membrane potential. At the molecular level, ZFAS1 activated the mitochondria apoptosis pathway, which could be nearly abolished by a calcium chelator. The effects of ZFAS1 were readily reversible upon knockdown of this lncRNA. Notably, ZFAS1-FD (only functional domain) mimicked the effects of full-length ZFAS1 in regulation of cardiomyocyte apoptosis. In conclusion, our study shows that ZFAS1, an endogenous SERCA2a inhibitor, induces mitochondria-mediated apoptosis via cytosolic Ca²⁺ overload. Therefore, anti-ZFAS1 might be considered a new therapeutic strategy for protecting cardiomyocytes from MI-induced apoptosis.

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

Introduction: Reinfarction after incidence of myocardial infarction is a serious complication and is responsible for high mortality. Various factors are responsible for reinfarction including smoking, prior procedures or surgeries, and use of medications such as aspirin, β-blocker, and angiotensin-converting enzyme Iihibitor or angiotensin receptor blockers.

Material and Methods: This prospective study was conducted with 243 participants. Participants were divided into two groups: patients who had a reinfarction during hospital and patients who did not.

Results: There were 142 (58.4%) men and 101 (41.6%) women in the study. A total of 17 (6.9%) patients had reinfarction. Age (68.4±10.9 vs. 64.4±11.8; 0.001), diabetes (47.05% vs. 22.12%; 0.02), and history of myocardial infarction (29.5% vs. 11.4%; 0.02) were identified as risk factors for reinfarction

Conclusion: Our study reports that certain parameters such as age, obesity, diabetes mellitus,, and history of myocardial infarction can be used to assess the risk of reinfarction among these patients.

Comparative hazards of acute myocardial infarction among hospitalized patients with methamphetamine- or cocaine-use disorders: A retrospective cohort study

BACKGROUND

It is assumed that recreational use of methamphetamine can trigger acute myocardial infarction (AMI) events, but estimates of longitudinal hazards of AMI among methamphetamine users are lacking.

METHODS

Retrospective cohort study: Competing-risks analysis was used to estimate time-to-AMI patterns in methamphetamine versus matched appendicitis (population-proxy) and matched cocaine (drug-control) groups. Cohorts were propensity-score-matched using demographic and clinical variables.

SETTING

California, 1990-2005.

PARTICIPANTS

Cohorts of individuals with no prior or concurrent history of AMI hospitalized with methamphetamine- (n = 73,056), cocaine- (n = 47,726), or appendicitis-related conditions (n = 330,109).

MEASUREMENTS

ICD-9/ICD-10 indications of AMI (ICD-9 410.X; ICD-10 I21.X) in death records or inpatient hospital data.

RESULTS

Patients in methamphetamine cohort were more likely to develop subsequent AMI in comparison to those in matched appendicitis cohort [Hazard ratio (HR): 1.41; 95% CI, 1.23-1.62, p < 0.0001], with increased risk most marked in young methamphetamine users (age 15-34 years; HR: 2.04; 95% CI, 1.63-2.57, p = 0. 0001). Risk was slightly increased vs. that in matched cocaine group (HR: 1.19; 95% CI, 1.02-1.39, p = 0. 029). Individuals in cocaine cohort were also more likely to experience AMI outcome vs. appendicitis cohort (HR: 1.25; 95% CI, 1.08-1.45, p = 0. 0023).

CONCLUSION

Our longitudinal data support results of earlier epidemiological studies suggesting that persons with methamphetamine- (or cocaine-) use disorders might have increased AMI risk. However, because of potential study limitations and the unexpectedly modest magnitude of the observed increased AMI hazard, these findings must be considered preliminary and require replication.