Predictor Of Acute Myocardial Infarction Research Articles

Cortisol as a biomarker for risk prediction of acute myocardial infarction in type 2 diabetic and dyslipidemic patients

Cortisol as a biomarker for risk prediction of acute myocardial infarction in type 2 diabetic and dyslipidemic patients

Abstract 12945: Disparities in the Prevalence of Acute Myocardial Infarction Among Patients With Non-Alcoholic Fatty Liver Disease a Nationwide Database Analysis

Background: Non-alcoholic liver disease (NAFLD) is among leading causes of chronic liver disease. Recent evidence suggests an association of NAFLD with cardiovascular diseases; however, few studies have analyzed national level database for this relationships. We aimed to assess the trends and predictors of acute myocardial infarction (AMI) among NAFLD patients in the United States. Methods: The National Inpatient Sample (NIS) database from 2016 to 2019 was queried using international classification of disease (ICD-10) diagnostic codes to identify patients with primary diagnosis of NAFLD and secondary diagnosis of AMI. Basic demographic variables were analyzed to determine the disparities in prevalence of AMI among NAFLD patients. Univariate logistic regression model was used to compare the odds of development of AMI among NAFLD patients using demographic characteristics. Multivariate logistic regression analysis was done to determine whether NAFLD is an independent predictor of AMI. Results: A total of 58,519 patients had a diagnosis of NAFLD and of these, 5,448 had AMI. Of these, 61% were males, 82% were aged 50 years and over, 68% were white, 8% Black, 16% Hispanic, Asian or Pacific Islander. Females were less likely to have AMI [OR 0.46, 95% CI 0.43-0.48]. Patients <50 years with NAFLD were less likely to develop AMI [OR 0.41, 95% CI 0.38-0.44]. Compared to the whites, blacks [OR 0.57, 95% CI 0.51-0.61, p< 0.001] were less likely to have AMI. However, Hispanics [OR 1.16, 95% CI 1.07-1.25, p< 0.001] and Asian and Pacific Islanders [OR 1.31, 95% CI 1.13-1.51, p< 0.001] were more likely to have AMI compared to the whites. On multivariate analysis, NAFLD was found to be an independent predictor of AMI [OR 1.55, 95% CI 1.51-1.60, p< 0.001] after controlling for sociodemographic variables such as age, sex, race, smoking status, insurance status, hospital location and teaching status, and clinical variables such as previous MI, Congestive heart failure, diabetes mellitus, chronic kidney disease, hyperlipidemia, and hypertension. Conclusions: This analysis suggests older white males with NAFLD had a higher prevalence of AMI and that NAFLD is an independent predictor of AMI.

The effect of vitamin K2 supplementation on coronary artery disease in a randomized multicenter trial

Abstract Background Coronary artery calcification (CAC) and especially progression in CAC is a strong predictor of acute myocardial infarction (AMI) and cardiovascular mortality [1]. Observational studies suggest a protective role of vitamin K2 in the development of CAC [2]. Measurement of CAC score in Agatston Units (AU) is common practice, while novel software as AutoPlaque introduces new opportunities to measure coronary plaques [3]. Purpose The aim of this double-blinded randomized multicenter trial is to investigate if vitamin K2 supplementation can reduce the progression of CAC in a population without known coronary disease. Methods AVADEC is a multicenter trial investigating 389 participants randomized to vitamin K2 (720 μg/day) and vitamin D (25 μg/day) versus placebo with a 2-year follow-up from 2018–2019 [4]. The primary endpoint of AVADEC is change in aortic valve calcification. In this substudy, we examined the progression of CAC in participants with no prior coronary disease (no myocardial infarction and/or revascularization) at baseline. Secondary, the change in CAC was evaluated in two prespecified subgroups (low-risk: CAC score <400 AU and high-risk: CAC ≥400 AU at baseline). Non-contrast CT-scans were performed at baseline, 12 and 24 months of follow-up. Contrast CT-scans were performed at baseline and 24 months. CAC score was measured with established software and expressed in Agatston Units (AU). On contrast CT-scans, quantitative coronary plaque composition evaluations were performed by using Autoplaque. Moreover, events (AMI, revascularization and all cause death) were assessed. Results 304 participants (male, mean age 71 years) with no prior coronary disease were identified. The intervention and placebo groups were similar in all traditional cardiovascular risk factors except familial predisposition for cardiovascular disease (14.4% vs. 6.7%, p=0.046). We found progression of CAC in both the intervention and placebo group from baseline to 24 month follow-up (203 AU vs. 254 AU, p=0.089) (Figure 1). The patients with CAC score <400 AU at baseline were equal in progression (77 AU vs. 81 AU, p=0.846). In patients with CAC score ≥400, the progression of CAC was significantly lower in the intervention group (288 AU vs. 380 AU, p=0.047). Yet, preliminary analyses of contrast CT-scans in 180 participants showed no difference in the progression of non-calcified plaque volume (10 mm3 vs. 37 mm3, p=0.276). In addition, the number of events was significantly lower in participants receiving vitamin K2 and D (1.9% vs. 6.7%, p=0.048). Conclusion Patients with no prior coronary disease randomized to vitamin K2 supplementation had a non-significant reduction in CAC development over a 2-year follow-up period. High-risk patients with CAC ≥400 AU had a significantly lower progression of CAC. Additionally, vitamin K2 supplementation significantly reduced the risk of AMI, revascularization and all-cause death. Funding Acknowledgement Type of funding sources: Foundation. Main funding source(s): Danish Cardiovascular Academy (2/3) and the Region of Southern Denmark (1/3).

Triglyceride–glucose (TYG) index for acute myocardial infarction patients with or without metabolic fatty liver (MAFLD): A retrospective study

Background and Aims : There are no clear predictors for acute myocardial infarction (AMI) with metabolic-associated fatty liver disease (MAFLD). Triglyceride–glucose (TyG) index has a predictive effect on the prognosis of cardiovascular diseases. The purpose of this retrospective study was to evaluate the correlation of TyG index in AMI patients with or without MAFLD.

Prediction of acute myocardial infarction by multi-parameter coronary computed tomography angiography

To investigate the performance of multi-parameter coronary computed tomography angiography (CCTA), including stenosis, plaque qualitative-quantitative characteristics, and fractional flow reserve derived from CCTA (FFRct), to predict acute myocardial infarction (AMI) and build a combined model. Thirty patients with AMI 90 days after CCTA and 120 matched patients without AMI were enrolled retrospectively. Multiple CCTA parameters were analysed and compared. Independent risk factors were obtained through univariate and multivariate regression analyses, after which a multi-parameter model was built. A total of 150 patients were analysed successfully. The multi-parameter CCTA model (area under the curve, 0.944; p<0.001) had a higher predictive value than each single parameter (p<0.001, all). Independent risk factors were intra-plaque dye penetration (IDP; odds ratio [OR], 8.373; p=0.002), lipid plaque volume (LPV; OR, 1.263; p<0.001), and FFRct ≤0.83 (OR, 8.092; p=0.001). This one-stop multi-parameter CCTA model, comprising IDP, LPV, and FFRct as independent risk factors, has good performance to predict AMI.

Death and cardiovascular outcomes in end-stage renal failure patients on different modalities of dialysis

Cardiovascular morbidity and mortality in end-stage renal failure (ESRF) patients are high. We examined the incidence and predictors of death and acute myocardial infarction (AMI) in ESRF patients on different modalities of dialysis. Data were obtained from a population-based database (National Registry Disease Offices) in Singapore. The study cohort comprised all adult patients initiated on dialysis between 2007 and 2012 who were closely followed for the development of death and AMI until September 2014. Cox regression methods were used to identify predictors of death and AMI. Of 5,309 patients, 4,449 were on haemodialysis and 860 on peritoneal dialysis (PD). Mean age of the cohort was 61 (±13) years (44% women), of Chinese (67%), Malay (25%) and Indian (7%) ethnicities. By September 2014, the incidence of all-cause death was 34%; close to a third of the patients died from a cardiovascular cause. Age >60 years and the presence of ischaemic heart disease, diabetes, stroke, peripheral vascular disease and PD were identified as independent predictors of all-cause death. PD patients had lower odds of survival compared to patients on haemodialysis (hazard ratio 1.51, 95% confidence interval 1.35-1.70, P<0.0001). Predictors of AMI in this cohort were older age (>60 years) and the presence of ischaemic heart disease, diabetes, stroke, peripheral vascular disease and current/ex-smokers. There were no significant differences in the incidence of AMI between patients on PD and haemodialysis. The short-term incidence of death and AMI remains high in Singapore. Future studies should investigate the benefits of a tighter control of cardiovascular risk factors among ESRF patients on dialysis.

Construction of a pyroptosis-related classifier for risk prediction of acute myocardial infarction.

Acute myocardial infarction (AMI) is a common cardiovascular disease that has a high mortality. Pyroptosis is a programmed cell death mediated by inflammasome. It remains to be clarified on the expression pattern and risk predictive role of pyroptosis-related genes in AMI. The gene expression data were extracted from the Gene Expression Omnibus (GEO), and pyroptosis-related genes were obtained from published articles. Pyroptosis-related differential expressed genes were selected between normal and AMI samples and then we explored their immune infiltration level using CIBERSORT. Univariate Cox and LASSO regression were applied to establish a classifier based on pyroptosis-related genes. ROC analysis was utilized to evaluate the classifier. In this study, we obtained 20 pyroptosis-related genes which showed differential expression in AMI and normal samples. Among the differential expressed genes, GZMB was significantly positively associated with activated NK cells (R = 0.71, p < 0.01), while NLRP3 exhibited a negative correlation with resting NK cells (R = -0.66, p < 0.01). 9 genes (NLRP9, GSDMD, CASP8, AIM2, GPX4, NOD1, NOD2, SCAF11, GSDME) were eventually identified as a predictive risk classifier for AMI patients. With the classifier, patients at high and low risk could be discriminated. Further external validation showed the high accuracy of the classifier (AUC = 0.75). Pyroptosis-related genes are closely related to immune infiltration in AMI, and a 9-gene classifier has good performance in predicting the risk of AMI with high accuracy, which could provide a new way for targeted treatment in AMI.

Lipoprotein(a) as predictor of coronary artery disease and myocardial infarction in a multi-ethnic Asian population

Background and aimsThe role of Lp(a) in multi-ethnic Asian populations with coronary artery disease (CAD) has not been well established. The aims of this study were (i) to investigate whether Lp(a) is a predictor of CAD, and (ii) amongst patients with CAD, to ascertain whether Lp(a) is a predictor of acute myocardial infarction (AMI) and severity of CAD. MethodsWe compared three cardiovascular phenotypes from patients recruited at coronary angiography. CAD was defined as ≥50% coronary artery stenosis and subdivided into a group with AMI history (CAD+AMI+) and a group without (CAD+AMI-). Minimal CAD group (CAD-) was defined as normal or <30% coronary artery stenosis and no AMI. The severity of CAD was defined using the modified Gensini score. ResultsWe studied 2025 patients comprising 94.5% men and 61.4% of Chinese ethnicity. The median Lp(a) level was highest in CAD+AMI+, followed by CAD+AMI- and CAD- (26.2, 20.1, and 15.8 nmol/L respectively). Similarly, the frequency of patients with Lp(a) ≥120 nmol/L were in the same order (11.8%, 9.1% and 2.4%). Lp(a) levels were highest among Asian Indians, followed by Malays and Chinese patients (p < 0.001). Lp(a) levels and Lp(a) ≥120 nmol/L were significant predictors of CAD (Odds ratio (OR) = 1.12 per 10 nmol/L increment, p < 0.001, and OR = 5.41 p = 0.004 respectively). Among patients with CAD, higher Lp(a) levels were associated with increased AMI risk (OR = 1.02 per 10 nmol/L increment, p = 0.024). Lp(a) ≥120 nmol/L was positively associated with CAD severity (p = 0.020). ConclusionsPlasma Lp(a) concentration is a positive predictor of CAD and AMI in a mostly male South East Asian population.

Abstract 10022: Young Adults Hospitalized with Diabetes Remain at 25% Higher Risk of Acute Myocardial Infarction with Cannabis Use Disorder: A Nationwide Matched Analysis

Background: The impact of cannabis use on diabetes mellitus and associated cardiovascular events remains understudied. Rising trends in recreational cannabis use in the young prompted us to evaluate the risk and outcomes of acute myocardial infarction (AMI) in young diabetics with cannabis use disorder (CUD). Methods: We queried the National Inpatient Sample (2015 October-2017) to identify young adult admissions with diabetes. Demographically (age, sex, and race) matched (1:1) cohorts (CUD+ vs. CUD) were compared for comorbidities and risk of AMI and subsequent inpatient outcomes among young diabetics. Multivariable regression analysis was performed adjusting for confounders. Results: Of young adults admitted with diabetes (median 35 [29-40] years, 59.3% male, 42.3% white), demographically matched CUD+ (n=32170) and CUD- (n=32170) cohorts were obtained (Table 1). The CUD+ cohort often consisted of non-elective admissions (91.7% vs. 85.45%), Medicaid enrollees (51.6% vs. 38.7%), patients from lower household income quartile (47.9% vs. 43.1%) vs. CUD- cohort and had higher burden of smoking, alcohol abuse, chronic pulmonary disease, depression, psychosis and neurological disorders (p&lt;0.001). On adjusted multivariable analysis, the risk of AMI was 25% higher (OR:1.25, 95%CI:1.02-1.51, p=0.03) in CUD+ cohort, however, there was no significant difference in the subsequent inpatient mortality. Male sex (aOR1.35), non-elective admission (aOR2.46), Medicaid/self-pay enrollment (aOR 2.0/3.8), AIDS (aOR6.24), coagulopathy (aOR1.85), peripheral vascular disease (aOR 1.82), hypertension (aOR 2.12), hyperlipidemia (aOR2.53), smoking (aOR1.78), and obesity (aOR1.36) were independent predictors of AMI. Conclusion: Young diabetics with CUD may have 25% higher risk of AMI hospitalizations. Male sex, cardiovascular comorbidities, tobacco smoking, AIDS and coagulopathy independently predicted higher risk of AMI among young diabetics with CUD.

Prediction of acute myocardial infarction or death in acute chest pain patients with machine learning models or first troponin T alone

Abstract Background Machine learning approaches are increasingly being explored for use in healthcare systems, but there is a trade-off between increased accuracy and decreased explainability with more complex models. We aimed to evaluate the diagnostic performance for acute myocardial infarction (AMI) or death within 30 days of index visit. Machine learning models were trained using demographic factors, ECG and blood markers, and to compare them to a single high sensitivity TnT (hs-cTnT) value. Methods Using records from 9519 ED patients from two hospitals in Skåne, Sweden, we created machine learning models based on both logistic regression and artificial neural networks. Inputs in the models varied and included sex and age, first hs-cTnT value at the ED, glucose, creatinine, hemoglobin, and ECG signal data. The models were adapted to meet the following criteria for safe rule-out of 30-day myocardial infarction or death: Negative predictive value (NPV) &amp;gt;99.5% and sensitivity &amp;gt;99%. For rule-in of myocardial infarction or death, a positive predictive value (PPV) of &amp;gt;70% was set. The models were then compared to the performance of a first hs-cTnT &amp;lt;5 ng/L for rule-out, and &amp;gt;51 ng/L for rule-in. The patient population was split by arrival date and models were trained on the initial 50% of patients. Thresholds were selected from the subsequent 25%, and tests were performed on the final 25% (2379 patients). Results The best model, a convolutional neural network, identified 1309 (55%) patients for rule-out and 125 (5.3%) for rule-in, with the required NPV, sensitivity and PPV. In comparison, a single hs-cTnT value identified 1123 (47.2%) patients for rule-out and 158 (6.6%) for rule-in, but failed to reach the required sensitivity and PPV levels. Conclusions These results indicate that more complex models are able to safely identify a large proportion of patients for early rule-out or rule-in without the need for serial troponin tests. In future studies attempts should be made to improve the explainability of these models. Funding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): VR; grant no. 2019-00198

Soluble MICA versus Troponin as Early snd Specific Predictor for Acute Myocardial Infarction in Patients with Chronic Kidney Disease

Abstract Background Accurate early detection &amp; early management of MI as a life threatening condition in patients with CKD , who are more likely than those without it to have elevated troponin levels still challenging. Recently, MICA could be activated in the normal tissues by a variety of stimuli, such as ischemia/reperfusion-induced tissue injury. Aim of the Work To compare sensitivity and specificity of serum sMICA to that of Troponin for early and accurate diagnosis of AMI in patients with CKD. Patients and Methods Total 30 patients was enrolled in the study and divided into 2 groups A &amp; B (15 for each one) in NHI , cTnI and sMICA was assayed in both groups; in the group A,cTnI &amp; sMICA was assayed serially according to time from arrival of the patient to ED (0 hour , 3 hours, 6 hours, 12 hours, and 24 hours ) and recording the pattern of rising, peaking &amp; falling of both biomarkers.. ‘ Results At zero hour both markers were positive serum level in both groups but lower in sMICA then pattern of rising and peaking of sMICA was early than TnI in AMI group which peaks later. Conclusion sMICA could be considered as a novel predictor that more sensitive and specific than cTnI.

Nutrition Status and Renal Function as Predictors in Acute Myocardial Infarction with and without Cancer: A Single Center Retrospective Study.

Background: Clinical characteristics of nutrition status in acute myocardial infarction (AMI) patients with cancer remains unknown. Therefore, this study aimed to clarify the differences of clinical parameters, including nutrition status, between AMI patients with and without history of cancer. Methods and Results: This retrospective cohort study, using the database of AMI between 2014 and 2019 in Kurume University Hospital, enrolled 411 patients; AMI patients without cancer (n = 358, 87.1%) and with cancer (n = 53, 12.9%). AMI patients with cancer were significantly older with lower body weight, worse renal function, and worse nutrition status. Next, we divided the patients into 4 groups by cancer, age, and plaque area, detected by coronary image devices. The prediction model indicated that nutrition, lipid, and renal functions were significant predictors of AMI with cancer. The ordinal logistic regression model revealed that worse nutrition status, renal dysfunction, lower uric acid, and elevated blood pressure were significant predictors. Finally, we were able to calculate the probability of the presence of cancer, by combining each factor and scoring. Conclusions: Worse nutrition status and renal dysfunction were associated with AMI with cancer, in which nutrition status was a major different characteristic from those without cancer.

Diagnostic Value of Mean Platelet Volume in Prediction of Acute Myocardial Infarction

Background: Acute myocardial infarction (AMI) is one of the main etiologies of death globally. In AMI, platelets were demonstrated to play a main role in thrombotic processes that limit the patency of the recanalized, infarct-related coronary artery and contribute to reperfusion injury. Platelet volume is an important indicator for platelet function and activation. Objective: The aim of the present study was to evaluate mean platelet volume (MPV) as an early and independent predictor for AMI in patients with acute chest pain. Patients and methods: This retrospective observational analytical study included a total of 107 patients presenting with acute chest pain presenting to Mansoura Emergency Hospital within the period from January 2019 to January 2020. Of them, 36 cases were diagnosed as stable coronary artery disease and 71 cases were diagnosed as AMI. Results: There were statistically significant differences among both groups regarding age, female sex and BMI being increased in AMI group. Hypertension, DM and dyslipidemia were significantly increased among AMI cases compared to stable coronary artery disease ones. Stable coronary artery disease cases demonstrated significant increase in platelet count and significant decrease in MPV compared to AMI ones. Hypertension, DM, dyslipidemia, family history of CAD, prior MI, prior PCI and MPV could be used as significant predictors for AMI. Conclusion: The current study concluded that larger platelet volumes may be used as predictor for AMI as well as ischemic complications.

ПРЕДИКТОРЫ РАЗВИТИЯ ОСТРОГО ИНФАРКТА МИОКАРДА ДЛЯ ПЕРСОНАЛА ТРУДОСПОСОБНОГО ВОЗРАСТА НА РАДИАЦИОННО-ОПАСНЫХ ПРОИЗВОДСТВАХ

Purpose: To examine the predictors of acute myocardial infarction development and to evaluate the relationship of the radiation component (external γ-radiation) with the probability of developing acute myocardial infarction in workers of radiation-dangerous plants working age (under 60 for men, 55 for women), by the example of the Siberian Group of Chemical Enterprises personnel. &#x0D; Material and methods: The work is based on the results of a prospective population study (1998–2013). The diagnosis of acute myocardial infarction was verified in 540 people of working age (34 women and 506 men). For each case selected control (n = 1,080) among the employees of the Siberian Group of Chemical Enterprises, passed periodic medical examination in the study period. Every person was described by means of 46 variables including characteristics of social status, a number of risk factors, associated diseases, biochemical indices including the level of general cholesterol, the main clinical data, cumulative dose of external radiation and the amount of 239Pu content in an organism. &#x0D; Results: It was determined that in the group of the personnel of working age the most important traditional predictors of acute myocardial infarction, less important factor in the pathogenesis of the disease are conditions of the individual accumulation of a dose, but not the magnitude of the total external doses in the evaluation range. &#x0D; Conclusion: To improve the system of preventive measures aimed at reducing the level of morbidity and mortality from acute myocardial infarction, it is recommended to form risk groups taking into account the most significant predictors of this disease (age, systolic blood pressure, smoking). For the personnel of radiation dangerous plants working age insignificant conditions for the formation of radiation dose (age of first exposure, the rate of accumulation of radiation dose, duration of exposure) under conditions of trouble-free operation of the equipment. &#x0D; Active measures for the diagnosis of coronary heart disease and targeted correction of detected somatic disorders for the prevention of acute vascular catastrophes are expedient for workers of radiation hazardous industries from 40 to 60 years with an individual risk of acute myocardial infarction less than 50 % using the model described below.

Role of Genetic & Epigenetic Modifications of Low-Density Lipoprotein Receptor (LDLR) Gene in South Indian Acute Myocardial Infraction Patients

Background: Acute Myocardial Infarction (AMI) has conventional risk factors as well as genetic and epigenetic modifications of various genes. Among them gene coding for Low density lipoprotein receptor (LDLR) plays a strategic role in cholesterol homeostasis by eliminating excess LDL-C in blood. LDLR gene promoter polymorphism & DNA methylation status might regulate the expression of genes & its activity. Objective: The present study is designed to evaluate the association of LDLR gene promoter c.-139delCTCCCCCTGC polymorphism & DNA methylation status with Acute Myocardial Infarction (AMI). Methods: 300 angiographically documented MI patients and 300 healthy individuals were recruited for the study. Genomic DNA & RNA was extracted from the whole blood using commercially available assay kits further RNA was converted to cDNA. Biochemical parameters like Total cholesterol, LDL-C, HDL-C, and Triglycerides were estimated using kit methods. Results: The risk factors like systolic, diastolic blood pressures, hypertension, diabetes mellitus, smoking, lipids were found to be significantly higher in AMI patients compared to controls. The genotype and allele distributions of the LDLR c.-139del polymorphism revealed that DD genotype & D-allele were found to be higher among the AMI patients than that of controls. Furthermore, we have observed LDLR gene differential promoter DNA methylation status & mRNA expression. In addition, Insilco analysis have shown that there is a change in TF binding at the Insertion & Deletion sites. Conclusion: The findings of the study suggest that the LDLR c.-139del DD genotype might be used as prognostic marker in risk prediction of Acute Myocardial Infarction.

Uveitis as a potential predictor of acute myocardial infarction in patients with Behcet’s disease: a population-based cohort study

ObjectivesTo investigate whether uveitis is a predictor of acute myocardial infarction (AMI) among patients with Behcet’s disease (BD).DesignRetrospective cohort study.SettingPatients with BD were retrieved from the whole population of the...

CRAX: A simple cardiovascular risk assessment tool to predict risk of acute myocardial infarction or death

BackgroundDetermining the risk of cardiovascular events is essential to optimize patient management. Methods and Results5842 individuals underwent SPECT myocardial perfusion imaging (MPI) with 4.4 ± 1.2 years of follow-up. Models (the CRAX tool) were derived to predict the cumulative risk of death and acute myocardial infarction (AMI) at 1, 3, and 5 years using clinical and MPI variables. Predictors of AMI and death included age, number of hospitalizations in the 3 years preceding MPI, and left ventricular ejection fraction (LVEF). Additional predictors of death were the use of pharmacological stress, and global stress total perfusion deficit (sTPD), while transient ischemic dilation (TID), and ischemic total perfusion deficit (iTPD) change were predictive of AMI. CRAX predictions were significantly (P < .001) more accurate than clinical variables or MPI results alone, resulting in a significant net reclassification improvement (NRI, 7.5% for AMI, 14.5% death) compared to clinical variables alone. Accuracy for predicting major adverse cardiac events (MACE, comprising all-cause death, AMI, unstable angina, late revascularization) was comparable to that of AMI or death. ConclusionsCRAX is a risk assessment tool that predicts the risk of AMI, death, or MACE, and improves prediction compared to clinical variables or MPI results alone.

Abstract 15975: Association of Maximum Troponin Levels With Myocardial Infarction Diagnosis and Higher Mortality

Introduction: Cardiac troponin I (TnI) is a sensitive and specific marker of acute myocardial infarction (AMI). However, a wide range of non-AMI conditions can also cause significant elevations in cardiac troponins. Given the deleterious impact of misdiagnosis, the ability to risk stratify patients who present with an elevated troponin is paramount. Hypothesis: We hypothesized that maximum TnI would be more predictive of mortality and the diagnosis of AMI than the initial or change in TnI. Methods: Records of 30,173 patients from a nine-hospital system in Texas were reviewed over a 24-month period 2016-2018. Data were collected on patients &gt; 40 years of age and included international classification of disease (ICD-10) diagnoses, TnI, demographic data (age, sex, race, smoking status, chronic medical conditions), death during hospitalization, and readmission within 30 days. Results: Notable finding include TnI as a significant predictor of death with odds of death increased by 0.9% (1.009, 95% CI 1.004-1.013) for initial, and 0.7% (1.007, 95% CI 1.005-1.009) for delta and maximum TnI. An ROC curve demonstrated a statistically significant predictive ability of death for the maximum TnI level (0.6782, 95% CI (0.6576, 0.6989)) when compared to the initial and change in TnI. We analyzed the initial TnI as a significant predictor of AMI demonstrating the odds of AMI increased by 7.4% as initial TnI values increased (1.074, 95% CI 1.063-1.085), and 3.1% for delta and maximum TnI (1.031, 95% CI 1.028-1.034). A separate ROC curve demonstrated that the maximum TnI level 0.9401, 95% CI (0.9353, 0.9449) showed a statistically significant predictive ability to predict an AMI compared to initial change in TnI. Conclusions: Regardless of TnI level, a detectable TnI results in an increased risk of in-hospital mortality. Our study demonstrates that the maximum TnI level is a more sensitive and specific predictor of mortality when compared to delta or initial TnI. Similarly, the maximum TnI is the most predictive of an AMI versus other causes of TnI elevation. Further studies are needed to correlate TnI levels and clinical manifestations, which may be helpful in redefining AMI to better distinguish AMI from non-AMI diagnoses.

Mesa 1: Diabetes mellitus tipo 1 y enfermedad cardiovascular

La principal causa de muerte en personas con diabetes mellitus tipo 1 (DM1) es de origen cardiovascular (CV). La duración de la DM1 es uno de los predictores más importantes para infarto agudo de miocardio (IAM), junto con el colesterol de lipoproteínas de baja densidad (cLDL) y HbA1c. El desarrollo de DM1 antes de los 10 años de edad se asocia con un riesgo 90 veces mayor de IAM en mujeres. En la DM1 habría una mayor contribución de un estado de inflamación sistémica de bajo de grado.La combinación de electrocardiograma de ejercicio y una técnica de imagen proporciona valor diagnóstico para la detección de isquemia miocárdica y pronóstico. La evaluación del riesgo CV en el adulto mayor debe ser individualizado y categorizarlo según funcionalidad y comorbilidades a fin de fijar objetivos de control de factores glucémicos y no glucémicos personalizados.

Expression level and diagnostic value of exosomal NEAT1/miR-204/MMP-9 in acute ST-segment elevation myocardial infarction.

Acute myocardium infarction (AMI) is one of the main causes of cardiovascular death, and timely intervention and diagnosis are essential. Owing to the irreversible apoptosis and death of myocardial cells, which ultimately causes heart failure, the problem of myocardial repair after myocardial infarction needs to be urgently addressed. Exosomes can act as messengers between cells, delivering large amounts of proteins, RNA, and lipids to receptor cells, and regulating target cell functions. Studies have shown that exosomes can repair infarcted myocardium. We aimed to investigate the relationship between long non-coding RNA NEAT1 in serum exosomes of patients and AMI and its underlying mechanism. Subjects were divided into control, UA, and STEMI groups. RNA was extracted from the serum exosomes, and the expressions of lncRNA NEAT1 and miR-204 were detected by qRT-PCR. MMP-9 was detected by western blot, Spearman test was used to analyze the correlation among the three. Logistic regression and Receiver-operating characteristic curve (ROC) were used to evaluate the prediction of acute myocardial infarction. The expressions of NEAT1 and MMP-9 in serum exosomes of patients with acute ST-segment elevation myocardial infarction were up-regulated and positively correlated, miR-204 expression was down-regulated, there were no correlations between miR-204 with NEAT1, or MMP-9. Exosomal NEAT1, miR-204, and MMP-9 displayed potent biomarkers for diagnosis of acute ST-segment elevation myocardial infarction.