Associations of age at diagnosis of breast cancer with incident myocardial infarction and heart failure: A prospective cohort study.

Background: The associations of age at diagnosis of breast cancer with incident myocardial infarction (MI) and heart failure (HF) remain unexamined. Addressing this problem could promote understanding of the cardiovascular impact of breast cancer. Methods: Data were obtained from the UK Biobank. Information on the diagnosis of breast cancer, MI, and HF was collected at baseline and follow-ups (median = 12.8 years). The propensity score matching method and Cox proportional hazards models were employed. Results: A total of 251,277 female participants (mean age: 56.8 ± 8.0 years), of whom 16,241 had breast cancer, were included. Among breast cancer participants, younger age at diagnosis (per 10-year decrease) was significantly associated with elevated risks of MI (hazard ratio [HR] = 1.36, 95% confidence interval [CI] 1.19-1.56, p<0.001) and HF (HR = 1.31, 95% CI 1.18-1.46, p<0.001). After propensity score matching, breast cancer patients with younger diagnosis age had significantly higher risks of MI and HF than controls without breast cancer. Conclusions: Younger age at diagnosis of breast cancer was associated with higher risks of incident MI and HF, underscoring the necessity to pay additional attention to the cardiovascular health of breast cancer patients diagnosed at younger age to conduct timely interventions to attenuate the subsequent risks of incident cardiovascular diseases. Funding: This study was supported by grants from the National Natural Science Foundation of China (82373665 and 81974490), the Nonprofit Central Research Institute Fund of Chinese Academy of Medical Sciences (2021-RC330-001), and the 2022 China Medical Board-open competition research grant (22-466).

Unusual and very rare presentation of wrist pain in a man with acute anterior myocardial infarction, a case report and literature of review.

BACKGROUND: As acute myocardial infarction (AMI) prevalence is increasing because of lifestyle changes, the incidence of atypical symptoms in acute coronary syndrome (ACS) is rising and making misdiagnosing of this fatal event more probable. To better approach the patients with atypical symptoms, we tend to present a rare case of AMI with wrist pain. CASE REPORT: A 41-year-old man presented to the emergency room (ER) with severe both-hand wrist pain and mild epigastric pain. His electrocardiogram (ECG) showed anterior ST-elevation myocardial infarction (MI) with an ejection fraction of 35-40%. His angiography showed severe left anterior descending artery (LAD), and first obtuse marginal artery (OM1) artery stenosis. He underwent Primary percutaneous coronary intervention (PCI). The patient recovered without serious complications and was discharged the day after PCI. DISCUSSION: In this rare case of AMI with wrist pain, it is important to know that atypical symptoms can be present at various levels of symptoms, which prevents future misdiagnosis.

Association between C-reactive protein to albumin ratio and subclinical myocardial injury in the general population free from cardiovascular disease.

OBJECTIVE: The study aimed to examine the role of the C-reactive protein to albumin ratio (CAR) as an inflammatory biomarker in relation to subclinical myocardial injury (SC-MI), addressing the limited knowledge of their association. METHODS: The study included 5,949 individuals without cardiovascular disease (CVD) from the National Health and Nutrition Examination Survey. SC-MI was identified through a Cardiac Infarction Injury Score (CIIS) of ≥ 10 units based on a 12-lead electrocardiogram. The study used multivariate logistic regression models, adjusted for potential confounders, to evaluate the relationship between CAR and SC-MI. Subgroup analyses were conducted to substantiate the results, and the non-linear correlation was assessed via restricted cubic spline (RCS) regression. RESULTS: The RCS curve showed a significant positive correlation between CAR and SC-MI (P for nonlinear = 0.2496). When adjusted for all confounders, individuals in the highest tertile of CAR exhibited a higher likelihood of SC-MI compared to those in the lowest tertile, with an odds ratio (OR) of 1.21 (95% CI: 1.06-1.39, P for trend = 0.029). A 10-unit increment in CAR was linked to a 3.6% heightened risk of SC-MI [OR = 1.036 (95% CI: 1.006, 1.066)], with this association being more prominent among male adults, non-smokers, married individuals, those without diabetes mellitus, and those with no history of cancer. CONCLUSION: The findings of this study suggest a positive correlation between CAR and SC-MI among the US adult population, indicating the potential of CAR in enhancing SC-MI prevention strategies in the general population.

[The actual issues of detection of risk factors and prevention of myocardium infarction in sailors].

In Russia, increases morbidity of myocardial infarction. The statistics of recent years demonstrate failure in meeting target indicators of national programs on reducing number of deaths from this disease. At that, able-bodied population is in high risk zone and their professional activity is under influence of large combination of risk factors of myocardial infarction. This risk area covers profession of seafarer that is characterized by irregular work schedule, high levels of stress and mental tension, low physical activity or, contrariwise, increased working loads, unbalanced diet, isotherm stress and interaction with harmful substances. Besides that, situation is aggravated by limited set of first medical aid measures at exacerbation of disease in view of remoteness from hospitalization centers. Thus, considering high mortality rate from myocardial infarction, it is extremely important for ship crews to have full and timely information about diagnostic, symptomatic and prevention of this disease. The article examines statistics data of morbidity and mortality of myocardial infarction in population of the Russian Federation on the basis of Rosstat data and target indicators of the National project "Health Care". The risk factors of myocardial infarction established by INTERHEART studies are analyzed. The specifics of work conditions of crew members of marine vessels are established. The collection of professional modifying risk factors was selected. The recommendations for their correction were developed to enhance efficiency of primary preventive measures and to decrease morbidity and mortality among seafarers.

[Analysis of the unicentric registry of the Infarction Code program: retrospective cohort]. / Análisis del registro unicéntrico del programa Código Infarto: cohorte retrospectiva.

Background: Acute coronary syndrome (ACS) is the most serious manifestation of coronary heart disease. The Infarction Code (according to its initialism in Spanish, CI: Código Infarto) program aims to improve the care of these patients. Objective: To describe the clinical presentation and outcomes of CI program in a coronary care unit (CCU). Material and methods: A database of a CCU with 5 years of consecutive records was analyzed. Patients diagnosed with ACS were included. The groups with acute myocardial infarction with and without ST-segment elevation were compared using Student's t, Mann-Whitney U and chi-squared tests. We calculated the relative risk (RR) and 95% confidence intervals (95% CI) of cardiovascular risk factors for mortality. Results: A total of 4678 subjects were analyzed, 78.7% men, mean age 63 years (± 10.7). 80.76% presented acute myocardial infarction with positive ST-segment elevation and fibrinolytic was granted in 60.8% of cases. Percutaneous coronary intervention was performed in 81.4% of patients, which was successful in 82.5% of events. Patients classified as CI presented mortality of 6.8% vs. 11.7%, p = 0.001. Invasive mechanical ventilation had an RR of 26.58 (95% CI: 20.61-34.3) and circulatory shock an RR of 20.86 (95% CI: 16.16-26.93). Conclusions: The CI program decreased mortality by 4.9%. Early fibrinolysis and successful coronary angiography are protective factors for mortality within CCU.

Introducción: el síndrome coronario agudo (SICA) es la manifestación más grave de la enfermedad coronaria. El programa Código Infarto (CI) tiene como objetivo mejorar la atención de estos pacientes. Objetivo: describir la presentación clínica y los resultados del programa CI de una unidad de cuidados coronarios (UCC). Material y métodos: se analizó una base de datos de una UCC con 5 años de registros consecutivos. Se incluyeron pacientes con diagnóstico de SICA. Se compararon los grupos con infarto agudo de miocardio con y sin elevación del segmento ST mediante las pruebas t de Student, U de Mann-Whitney y chi cuadrada. Se calculó el riesgo relativo (RR) y el intervalo de confianza del 95% (IC 95%) de los factores de riesgo cardiovascular para mortalidad. Resultados: se analizaron 4678 sujetos, 78.7% hombres, con media de edad de 63 años (± 10.7). El 80.76% presentó infarto agudo de miocardio con desnivel positivo del segmento ST y se otorgó fibrinolítico en el 60.8% de los casos. Se realizó intervencionismo coronario percutáneo en el 81.4% de los pacientes, el cual fue exitoso en el 82.5% de los eventos. Los pacientes catalogados como CI presentaron mortalidad del 6.8% frente a 11.7%, p = 0.001. La ventilación mecánica invasiva tuvo una RR de 26.58 (IC 95%: 20.61-34.3) y el choque circulatorio una RR de 20.86 (IC 95%: 16.16-26.93). Conclusiones: el programa CI disminuyó 4.9% la mortalidad. La fibrinólisis temprana y la angiografía coronaria exitosa son factores protectores para mortalidad dentro de la UCC.

Predicting mortality amongst Jordanian men with heart attacks using the chi-square automatic interaction detection model.

Background: One of the most complicated cardiovascular diseases in the world is heart attack. Since men are the most likely to develop cardiac diseases, accurate prediction of these conditions can help save lives in this population. This study proposed the Chi-Squared Automated Interactive Detection (CHAID) model as a prediction algorithm to forecast death versus life among men who might experience heart attacks. Methods: Data were extracted from the electronic health solution system in Jordan using a retrospective, predictive study. Between 2015 and 2021, information on men admitted to public hospitals in Jordan was gathered. Results: The CHAID algorithm had a higher accuracy of 93.72% and an area under the curve of 0.792, making it the best top model created to predict mortality among Jordanian men. It was discovered that among Jordanian men, governorates, age, pulse oximetry, medical diagnosis, pulse pressure, heart rate, systolic blood pressure, and pulse pressure were the most significant predicted risk factors of mortality from heart attack. Conclusion: With heart attack complaints as the primary risk factors that were predicted using machine learning algorithms like the CHAID model, demographic characteristics and hemodynamic readings were presented.

Analysis of the prognostic value of mitochondria-related genes in patients with acute myocardial infarction.

BACKGROUND: Acute myocardial infarction (AMI) is a leading cause of death worldwide. Mitochondrial dysfunction is a key determinant of cell death post-AMI. Preventing mitochondrial dysfunction is thus a key therapeutic strategy. This study aimed to explore key genes and target compounds related to mitochondrial dysfunction in AMI patients and their association with major adverse cardiovascular events (MACE). METHODS: Differentially expressed genes in AMI were identified from the Gene Expression Omnibus (GEO) datasets (GSE166780 and GSE24519), and mitochondria-related genes were obtained from MitoCarta3.0 database. By intersection of the two gene groups, mitochondria-related genes in AMI were identified. Next, the identified genes related to mitochondria were subject to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses. Protein-protein interaction (PPI) network was constructed, and key genes were screened. Then, targeted drug screening and molecular docking were performed. Blood samples from AMI patients and healthy volunteers were analyzed for the key genes expressions using quantitative real time polymerase chain reaction (qRT-PCR). Later, receiver operating characteristic (ROC) curves assessed the diagnostic value of key genes, and univariate and multivariate COX analyses identified risk factors and protective factors for MACE in AMI patients. RESULTS: After screening and identification, 138 mitochondria-related genes were identified, mainly enriched in the processes and pathways of cellular respiration, redox, mitochondrial metabolism, apoptosis, amino acid and fatty acid metabolism. According to the PPI network, 5 key mitochondria-related genes in AMI were obtained: translational activator of cytochrome c oxidase I (TACO1), cytochrome c oxidase subunit Va (COX5A), PTEN-induced putative kinase 1 (PINK1), SURF1, and NDUFA11. Molecular docking showed that Cholic Acid, N-Formylmethionine interacted with COX5A, nicotinamide adenine dinucleotide + hydrogen (NADH) and NDUFA11. Subsequent basic experiments revealed that COX5A and NDUFA11 expressions were significantly lower in the blood of patients with AMI than those in the corresponding healthy volunteers; also, AMI patients with MACE had lower COX5A and NDUFA11 expressions in the blood than those without MACE (P < 0.01). ROC analysis also showed high diagnostic value for COX5A and NDUFA11 [area under the curve (AUC) > 0.85]. In terms of COX results, COX5A, NDUFA11 and left ventricular ejection fraction (LVEF) were protective factors for MACE in AMI, while C-reactive protein (CRP) was a risk factor. CONCLUSION: COX5A and NDUFA11, key mitochondria-related genes in AMI, may be used as biomarkers to diagnose AMI and predict MACE.

Clinical and Analytical Performance of a Novel Point-of-Care High-Sensitivity Cardiac Troponin I Assay.

BACKGROUND: Point-of-care (POC) high-sensitivity cardiac troponin assays may further accelerate the diagnosis of myocardial infarction (MI). OBJECTIVES: This study sought to assess the clinical and analytical performance of the novel high-sensitivity cardiac troponin I (hs-cTnI)-SPINCHIP POC test. METHODS: Adult patients presenting with acute chest discomfort to the emergency department were enrolled in an international, diagnostic, multicenter study. The final diagnosis was centrally adjudicated by 2 independent cardiologists using all clinical information. We compared the discriminatory performance of hs-cTnI-SPINCHIP with current established central laboratory assays and derived an assay-specific hs-cTnI-SPINCHIP 0/1-hour algorithm. Secondary analyses included sample type comparisons (whole blood, fresh/frozen plasma, and capillary finger prick) and precision analysis. RESULTS: MI was the adjudicated final diagnosis in 214 (19%) of 1,102 patients. Area under the receiver-operating characteristic curve was 0.94 (95% CI: 0.92-0.95) for hs-cTnI-SPINCHIP vs 0.94 (95% CI: 0.92-0.95) for hs-cTnI-Architect (P = 0.907) and 0.93 (95% CI: 0.91-0.95) for high-sensitivity cardiac troponin T Elecsys (P = 0.305). A cutoff <7 ng/L at presentation (if chest pain onset was >3 hours) or <7 ng/L together with a 0/1-hour delta of <4 ng/L ruled out 51% with a sensitivity and negative predictive value of 100% (95% CI: 97.7%-100%) and 100% (95% CI: 99.0%-100%), respectively. A hs-cTnI-SPINCHIP concentration ≥36 ng/L or a 0/1-hour delta ≥11 ng/L ruled in 27% with a specificity and positive predictive value of 90.9% (95% CI: 88.3%-92.9%) and 72.9% (95% CI: 66.4%-78.6%), respectively. Bootstrap internal validation confirmed excellent diagnostic performance. High agreement was observed between different sample types. CONCLUSIONS: The SPINCHIP hs-cTnI POC test has very high diagnostic accuracy. Its assay-specific 0/1-hour algorithm achieved very high sensitivity/negative predictive value and specificity/positive predictive value for rule-out/in MI. (Advantageous Predictors of Acute Coronary Syndromes Evaluation [APACE] Study [APACE]; NCT00470587).

Machine Learning Constructed Based on Patient Plaque and Clinical Features for Predicting Stent Malapposition: A Retrospective Study.

BACKGROUND: Stent malapposition (SM) following percutaneous coronary intervention (PCI) for myocardial infarction continues to present significant clinical challenges. In recent years, machine learning (ML) models have demonstrated potential in disease risk stratification and predictive modeling. HYPOTHESIS: ML models based on optical coherence tomography (OCT) imaging, laboratory tests, and clinical characteristics can predict the occurrence of SM. METHODS: We studied 337 patients from the Affiliated Hospital of Zunyi Medical University, China, who had PCI and coronary OCT from May to October 2023. We employed nested cross-validation to partition patients into training and test sets. We developed five ML models: XGBoost, LR, RF, SVM, and NB based on calcification features. Performance was assessed using ROC curves. Lasso regression selected features from 46 clinical and 21 OCT imaging features, which were optimized with the five ML algorithms. RESULTS: In the prediction model based on calcification features, the XGBoost model and SVM model exhibited higher AUC values. Lasso regression identified five key features from clinical and imaging data. After incorporating selected features into the model for optimization, the AUC values of all algorithmic models showed significant improvements. The XGBoost model demonstrated the highest calibration accuracy. SHAP values revealed that the top five ranked features influencing the XGBoost model were calcification length, age, coronary dissection, lipid angle, and troponin. CONCLUSION: ML models developed using plaque imaging features and clinical characteristics can predict the occurrence of SM. ML models based on clinical and imaging features exhibited better performance.

Barbed arrow-like structure membrane with ultra-high rectification coefficient enables ultra-fast, highly-sensitive lateral-flow assay of cTnI.

Acute myocardial infarction (AMI) has become a public health disease threatening public life safety due to its high mortality. The lateral-flow assay (LFA) of a typical cardiac biomarker, troponin I (cTnI), is essential for the timely warnings of AMI. However, it is a challenge to achieve an ultra-fast and highly-sensitive assay for cTnI (hs-cTnI) using current LFA, due to the limited performance of chromatographic membranes. Here, we propose a barbed arrow-like structure membrane (BAS Mem), which enables the unidirectional, fast flow and low-residual of liquid. The liquid is rectified through the forces generated by the sidewalls of the barbed arrow-like grooves. The rectification coefficient of liquid flow on BAS Mem is 14.5 (highest to date). Using BAS Mem to replace the conventional chromatographic membrane, we prepare batches of lateral-flow strips and achieve LFA of cTnI within 240 s, with a limit of detection of 1.97 ng mL-1. The lateral-flow strips exhibit a specificity of 100%, a sensitivity of 93.3% in detecting 25 samples of suspected AMI patients. The lateral-flow strips show great performance in providing reliable results for clinical diagnosis, with the potential to provide early warnings for AMI.

Effectiveness of Sodium-Glucose Cotransporter 2 Inhibitors in Patients With Acute Myocardial Infarction With or Without Type 2 Diabetes: A Systematic Review and Meta-analysis.

ABSTRACT: Recent studies have revealed the benefits of sodium-glucose cotransporter 2 inhibitors (SGLT2i) in heart failure patients. However, their effects on acute myocardial infarction (AMI) remain uncertain. Therefore, we conducted this meta-analysis to assess the effectiveness of SGLT2i in patients with AMI with or without diabetes. We conducted a comprehensive search of PubMed, Embase, and Cochrane Library encompassing data from inception until November 30, 2023. Relevant studies comparing SGLT2i with placebo or non-SGLT2i in patients with AMI were included. The mean difference and/or odds ratio (OR) with 95% confidence intervals were pooled using a fixed-effects model when the heterogeneity statistic (I2) was less than 50%; otherwise, a random-effects model was employed. Four randomized controlled trials and 4 observational studies involving 9397 patients with AMI were included in this meta-analysis. Patients treated with SGLT2i exhibited a significantly lower rate of hospitalization for heart failure (OR = 0.50, 95% CI: 0.32-0.80) and all-cause death (OR = 0.65, 95% CI: 0.44-0.95) compared with those treated with placebo or non-SGLT2i. Furthermore, the use of SGLT2i was associated with a significant increase in left ventricular ejection fraction (mean difference = 1.90, 95% CI: 1.62-2.17) and a greater reduction of N-terminal prohormone of brain natriuretic peptide (OR = 0.88, 95% CI 0.82-0.94). Subgroup analysis revealed that in patients with diabetes, SGLT2i exhibited similar effects. The present meta-analysis provided evidence indicating the effectiveness of SGLT2i in patients with AMI; SGLT2i may serve as an additional therapeutic option for patients with AMI, regardless of the presence or absence of diabetes.

The electronic frailty index and outcomes in patients with myocardial infarction.

BACKGROUND: Frailty is increasingly present in patients with acute myocardial infarction. The electronic Frailty Index (eFI) is a validated method of identifying vulnerable older patients in the community from routine primary care data. Our aim was to assess the relationship between the eFI and outcomes in older patients hospitalised with acute myocardial infarction. STUDY DESIGN AND SETTING: Retrospective cohort study using the DataLoch Heart Disease Registry comprising consecutive patients aged 65 years or over hospitalised with a myocardial infarction between October 2013 and March 2021. METHODS: Patients were classified as fit, mild, moderate, or severely frail based on their eFI score. Cox-regression analysis was used to determine the association between frailty category and all-cause mortality. RESULTS: In 4670 patients (median age 77 years [71-84], 43% female), 1865 (40%) were classified as fit, with 1699 (36%), 798 (17%) and 308 (7%) classified as mild, moderate and severely frail, respectively. In total, 1142 patients died within 12 months of which 248 (13%) and 147 (48%) were classified as fit and severely frail, respectively. After adjustment, any degree of frailty was associated with an increased risk of all-cause death with the risk greatest in the severely frail (reference = fit, adjusted hazard ratio 2.87 [95% confidence intervals 2.24 to 3.66]). CONCLUSION: The eFI identified patients at high risk of death following myocardial infarction. Automatic calculation within administrative data is feasible and could provide a low-cost method of identifying vulnerable older patients on hospital presentation.

Myocardial injury mimicking acute myocardial infarction due to coronavirus infection in adults with pre-existing apical hypertrophic cardiomyopathy.

Symptoms of apical hypertrophic cardiomyopathy (ApHCM) can mimic acute myocardial infarction (AMI). Following COVID-19 infection, the elevation of troponin in ApHCM might be confusing, due to its similarity with AMI. We report the case of a 64-year-old male patient presenting with exertional dyspnoea and chest discomfort. He had no history of coronary artery disease (CAD), but his swab test was positive for COVID-19. The physical examination was normal. The 12-lead electrocardiogram showed a sinus rhythm of 78 bpm, with deep inverted T waves in leads V2 to V6, I, and aVL, and left ventricular hypertrophy. An Echocardiographic examination showed an 18 mm apical wall thickness of the left ventricle. Laboratory tests revealed elevated hs- Troponin level, but diagnostic coronary angiography was normal. The diagnostic criteria fulfilled apical cardiac hypertrophic cardiomyopathy. Coronavirus can induce atypical cardiovascular symptoms in pre-existing ApHCM. Misdiagnosis and failure to recognize may result in inappropriate therapy and delay in definitive treatment.

Efficacy and safety of extracorporeal membrane oxygenation for cardiogenic shock complicating myocardial infarction: a systematic review and meta-analysis.

BACKGROUND: Extracorporeal membrane oxygenation (ECMO) has been presented as a potential therapeutic option for patients with cardiogenic shock complicating myocardial infarction (CS-MI). We aimed to investigate the efficacy and safety of ECMO in CS-MI. METHODS: A systematic review and meta-analysis synthesizing evidence from randomized controlled trials obtained from PubMed, Embase, Cochrane, Scopus, and Web of Science until September 2023. We used the random-effects model to report dichotomous outcomes using risk ratio and continuous outcomes using mean difference with a 95% confidence interval. Finally, we implemented a trial sequential analysis to evaluate the reliability of our results. RESULTS: We included four trials with 611 patients. No significant difference was observed between ECMO and standard care groups in 30-day mortality with pooled RR of 0.96 (95% CI: 0.81-1.13, p = 0.60), acute kidney injury (RR: 0.65, 95% CI: 0.41-1.03, p = 0.07), stroke (RR: 1.16, 95% CI: 0.38-3.57, p = 0.80), sepsis (RR: 1.06, 95% CI: 0.77-1.47, p = 0.71), pneumonia (RR: 0.99, 95% CI: 0.58-1.68, p = 0.96), and 30-day reinfarction (RR: 0.95, 95% CI: 0.25-3.60, p = 0.94). However, the ECMO group had higher bleeding events (RR: 2.07, 95% CI: 1.44-2.97, p < 0.0001). CONCLUSION: ECMO did not improve clinical outcomes compared to the standard of care in patients with CS-MI but increased the bleeding risk.

Using machine learning to predict acute myocardial infarction and ischemic heart disease in primary care cardiovascular patients.

BACKGROUND: Early recognition, which preferably happens in primary care, is the most important tool to combat cardiovascular disease (CVD). This study aims to predict acute myocardial infarction (AMI) and ischemic heart disease (IHD) using Machine Learning (ML) in primary care cardiovascular patients. We compare the ML-models' performance with that of the common SMART algorithm and discuss clinical implications. METHODS AND RESULTS: Patient-level medical record data (n = 13,218) collected between 2011-2021 from 90 GP-practices were used to construct two random forest models (one for AMI and one for IHD) as well as a linear model based on the SMART risk prediction algorithm as a suitable comparator. The data contained patient-level predictors, including demographics, procedures, medications, biometrics, and diagnosis. Temporal cross-validation was used to assess performance. Furthermore, predictors that contributed most to the ML-models' accuracy were identified. The ML-model predicting AMI had an accuracy of 0.97, a sensitivity of 0.67, a specificity of 1.00 and a precision of 0.99. The AUC was 0.96 and the Brier score was 0.03. The IHD-model had similar performance. In both ML-models anticoagulants/antiplatelet use, systolic blood pressure, mean blood glucose, and eGFR contributed most to model accuracy. For both outcomes, the SMART algorithm was substantially outperformed by ML on all metrics. CONCLUSION: Our findings underline the potential of using ML for CVD prediction purposes in primary care, although the interpretation of predictors can be difficult. Clinicians, patients, and researchers might benefit from transitioning to using ML-models in support of individualized predictions by primary care physicians and subsequent (secondary) prevention.

An important diagnostic marker of acute myocardial infarction patients: Plasma miRNA133 levels.

The objective of this study was to explore changes in miRNA133 levels as a basis for clinical diagnostic markers in patients with acute myocardial infarction (AMI). A total of 100 chest pain patient cases admitted to a hospital from June 2021 to December 2022 were used. The study involved the selection of 50 patients: 25 patients with unstable undetermined heart pain and 25 healthy subjects were included in the control group of 50 patients with non-AMI patients. Meanwhile, 50 patients with AMI were designated as the experimental group. Changes in miRNA133 levels in patients' plasma were analyzed for expression using quantitative fluorescence analysis. When the serum TPI, plasma NT-ProBNP, glycosylated hemoglobin, and plasma D-dimer index values were compared between the control and experimental groups, there was a statistically significant difference (P < .05). mi-RNA-133 had a mean plasma level value of 2.60 ±â€…1.01, the mean level value of mi-RNA-133 in patients with non-AMI was 1.34 ±â€…1.18, and the patients in the AMI group showed significantly high values of the mean plasma level of mi-RNA-133. The relative expression level value of cTnl in patients with AMI was 10.84 ±â€…12.64. Of the specificity and sensitivity diagnostics, mi-RNA-133 had the best diagnostic effect. The area under mi-RNA-133 in the regression curve was 95.4%, the specificity of the whole combination of indicators was 89.4% and the sensitivity was 100%. Finally, the correlation between mi-RNA-133 and white blood cell count (WBC) and TG was statistically significant (P < .05). In conclusion, changes in the level of mi-RNA-133 may be an important marker for diagnosing the status of patients with AMI, while a faster and more accurate method will emerge along with the improvement of the detection technology, and at the same time, due to the variability of the study cases and other limitations, further research will be carried out subsequently.

Case Report: Non-ischemic Papillary Muscle Rupture due to MRSA Myocarditis with Concurrent Thromboembolic Myocardial Infarction Secondary to Infective Endocarditis.

Non-ischemic papillary muscle rupture (PMR) is rare. PMR caused by myocarditis in the presence of concurrent infective endocarditis (IE) and myocardial infarction (MI) has not been described. We report a 46-year-old male with recurrent MRSA bacteremia who presented in septic shock and suffered cardiac arrest. Echocardiography revealed acute mitral valve regurgitation resulting from posteromedial PMR. An intra-aortic balloon pump was implanted. Angiography revealed thrombotic occlusion of a small distal left circumflex artery. Emergent mitral valve replacement surgery was performed. MRSA myocarditis and IE were diagnosed by tissue cultures. Coexistence of myocarditis, IE, and MI poses a challenge in determining etiology.

Exploratory analysis of predictors of ventricular aneurysm in a cohort of 291 patients with acute myocardial infarction.

OBJECTIVE: In this study, we explored the determinants of ventricular aneurysm development following acute myocardial infarction (AMI), thereby prompting timely interventions to enhance patient prognosis. METHODS: In this retrospective cohort analysis, we evaluated 297 AMI patients admitted to the First People's Hospital of Changzhou. The study was structured as follows. Comprehensive baseline data collection included hematological evaluations, ECG, echocardiography, and coronary angiography upon admission. Within 3 months post-AMI, cardiac ultrasounds were administered to detect ventricular aneurysm development. Univariate and multivariate logistic regression analysis were employed to pinpoint the determinants of ventricular aneurysm formation. Subsequently, a predictive model was formulated for ventricular aneurysm post-AMI. Moreover, the diagnostic efficacy of this model was appraised using the ROC curves. RESULTS: In our analysis of 291 AMI patients, spanning an age range of 32-91 years, 247 were male (84.9%). At the conclusion of a 3-month observational period, the cohort bifurcated into two subsets: 278 patients without ventricular aneurysm and 13 with evident ventricular aneurysm. Distinguishing features of the ventricular aneurysm subgroup were markedly higher values for age, B-type natriuretic peptide(BNP), Left atrium(LA), Left ventricular end-diastolic dimension (LEVDD), left ventricular end systolic diameter (LVEWD), E-wave velocity (E), Left atrial volume (LAV), E/A ratio (E/A), E/e ratio (E/e), ECG with elevated adjacent four leads(4 ST-Elevation), and anterior wall myocardial infarction(AWMI) compared to their counterparts (p < 0.05). Among the singular predictive factors, total cholesterol (TC) emerged as the most significant predictor for ventricular aneurysm development, exhibiting an AUC of 0.704. However, upon crafting a multifactorial model that incorporated gender, TC, an elevated ST-segment in adjacent four leads, and anterior wall infarction, its diagnostic capability: notably surpassed that of the standalone TC, yielding an AUC of 0.883 (z = -9.405, p = 0.000) as opposed to 0.704. Multivariate predictive model included gender, total cholesterol, ST elevation in 4 adjacent leads, anterior myocardial infarction, the multivariate predictive model showed better diagnostic efficacy than single factor index TC (AUC: 0. 883 vs. 0.704,z =-9.405, p = 0.000), it also improved predictive power for correctly reclassifying ventricular aneurysm occurrence in patients with AMI, NRI = 28.42% (95% CI: 6.29-50.55%; p = 0.012). Decision curve analysis showed that the use of combination model had a positive net benefit. CONCLUSION: Lipid combined with ECG model after myocardial infarction could be used to predict the formation of ventricular aneurysm and aimed to optimize and adjust treatment strategies.