Wellens Syndrome in a patient with a history of hypertension and chronic obstructive pulmonary disease: a case report.

Wellens syndrome, an ST Elevation Myocardial Infarction (STEMI) equivalent, is also known as T-wave left anterior descending (LAD) coronary artery disease. Wellens syndrome is characterized by a unique electrocardiogram (ECG) pattern that suggests a significant stenosis in the left anterior descending coronary artery that warrants immediate intervention. Hereby, we present a case report of Wellens syndrome in a patient with a history of hypertension and chronic obstructive pulmonary disease (COPD) that may be potentially mistaken for pseudo- Wellens syndrome because the ECG pattern mimics left ventricular strain pattern (LVSP) in left ventricular hypertrophy (LVH). Thus, cautious examination of recent chest pain and ECG is important to differentiate Wellens syndrome and LVSP in patients with hypertension and COPD to perform early detection and aggressive intervention since they may help to lessen the adverse results.

An Intramyocardial Mass Mimicking ST-Segment Elevation Myocardial Infarct at Presentation.

ST-segment elevation on the electrocardiogram typically indicates acute myocardial infarction but can mimic ST-segment elevation myocardial infarction in various conditions. We present a case of a patient with an intramyocardial mass and anterior ST-segment elevation without significant myocardial biomarker elevation. Multimodality imaging was crucial in revealing cardiac metastasis as the attributable cause.

Temporal trends and prognostic impact of reperfusion modalities in Tunisian patients presenting with ST-elevation myocardial infarction: A 20-year analysis.

INTRODUCTION: With the advent of reperfusion therapies, management of patients presenting with ST-elevation myocardial infarction (STEMI) has witnessed significant changes during the last decades. AIM: We sought to analyze temporal trends in reperfusion modalities and their prognostic impact over a 20-year period in patients presenting with STEMI the Monastir region (Tunisia). METHODS: Patients from Monastir region presenting for STEMI were included in a 20-year (1998-2017) single center registry. Reperfusion modalities, early and long-term outcomes were studied according to five four-year periods. RESULTS: Out of 1734 patients with STEMI, 1370 (79%) were male and mean age was 60.3 ± 12.7 years. From 1998 to 2017, primary percutaneous coronary intervention (PCI) use significantly increased from 12.5% to 48.3% while fibrinolysis use significantly decreased from 47.6% to 31.7% (p<0.001 for both). Reperfusion delays for either fibrinolysis or primary PCI significantly decreased during the study period. In-hospital mortality significantly decreased from 13.7% during Period 1 (1998-2001) to 5.4% during Period 5 (2014-2017), (p=0.03). Long-term mortality rate (mean follow-up 49.4 ± 30.7 months) significantly decreased from 25.3% to 13% (p<0.001). In multivariate analysis, age, female gender, anemia on-presentation, akinesia/dyskinesia of the infarcted area and use of plain old balloon angioplasty were independent predictors of death at long-term follow-up whereas primary PCI use and preinfaction angina were predictors of long-term survival. CONCLUSIONS: In this long-term follow-up study of Tunisian patients presenting for STEMI, reperfusion delays decreased concomitantly to an increase in primary PCI use. In-hospital and long-term mortality rates significantly decreased from 1998 to 2017.

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.

AI-enabled ECG index for predicting left ventricular dysfunction in patients with ST-segment elevation myocardial infarction.

Electrocardiogram (ECG) changes after primary percutaneous coronary intervention (PCI) in ST-segment elevation myocardial infarction (STEMI) patients are associated with prognosis. This study investigated the feasibility of predicting left ventricular (LV) dysfunction in STEMI patients using an artificial intelligence (AI)-enabled ECG algorithm developed to diagnose STEMI. Serial ECGs from 637 STEMI patients were analyzed with the AI algorithm, which quantified the probability of STEMI at various time points. The time points included pre-PCI, immediately post-PCI, 6 h post-PCI, 24 h post-PCI, at discharge, and one-month post-PCI. The prevalence of LV dysfunction was significantly associated with the AI-derived probability index. A high probability index was an independent predictor of LV dysfunction, with higher cardiac death and heart failure hospitalization rates observed in patients with higher indices. The study demonstrates that the AI-enabled ECG index effectively quantifies ECG changes post-PCI and serves as a digital biomarker capable of predicting post-STEMI LV dysfunction, heart failure, and mortality. These findings suggest that AI-enabled ECG analysis can be a valuable tool in the early identification of high-risk patients, enabling timely and targeted interventions to improve clinical outcomes in STEMI patients.

Prognostic Value of Coronary Microvascular Dysfunction Assessed by Coronary Angiography-Derived Index of Microcirculatory Resistance in Patients With ST-Segment Elevation Myocardial Infarction.

BACKGROUND: CaIMR is proposed as a novel angiographic index designed to assess microcirculation without the need for pressure wires or hyperemic agents. We aimed to investigate the impact of caIMR on predicting clinical outcomes in STEMI patients. METHODS: One hundred and forty patients with STEMI who received PCI in Putuo Hospital of Shanghai from October 2021 to September 2022 were categorized into CMD and non-CMD groups according to the caIMR value. The baseline information, patient-related examinations, and the occurrence of MACE at the 12-month follow-up were collected to investigate risk factors in patients with STEMI. RESULTS: We divided 140 patients with STEMI enrolled into two groups according to caIMR results, including 61 patients diagnosed with CMD and 79 patients diagnosed with non-CMD. A total of 21 MACE occurred during the 1 year of follow-up. Compared with non-CMD group, patients with CMD showed a significantly higher risk of MACE. A multivariate Cox regression model was conducted for the patients, and it was found thatcaIMR was a significant predictor of prognosis in STEMI patients (HR: 8.921). Patients with CMD were divided into culprit vascular CMD and non-culprit vascular CMD, and the result found that culprit vascular CMD was associated with the incidence of MACE (OR: 4.75) and heart failure (OR: 7.50). CONCLUSION: CaIMR is a strong predictor of clinical outcomes and can provide an objective risk stratification for patients with STEMI. There is a strong correlation among leukocyte index, the use of furosemide, Killips classification, and clinical outcomes.

Beyond STEMI-NSTEMI Paradigm: Dante Pazzanese's Proposal for Occlusion Myocardial Infarction Diagnosis. / Além do Paradigma IAMCSST-IAMSSST: Proposta do Instituto Dante Pazzanese para o Diagnóstico de Oclusão Coronariana Aguda.

Although the existing framework for classifying acute myocardial infarction (AMI) into STEMI and NSTEMI has been beneficial, it is now considered to be falling short in addressing the complexity of acute coronary syndromes. The study aims to scrutinize the current STEMI-NSTEMI paradigm and advocate for a more nuanced framework, termed as occlusion myocardial infarction (OMI) and non-occlusion myocardial infarction (NOMI), for a more accurate diagnosis and management of AMI. A comprehensive analysis of existing medical literature was conducted, with a focus on the limitations of the STEMI-NSTEMI model. The study also outlines a new diagnostic approach for patients presenting with chest pain in emergency settings. The traditional STEMI-NSTEMI model falls short in diagnostic precision and effective treatment, especially in identifying acute coronary artery occlusions. The OMI-NOMI framework offers a more anatomically and physiologically accurate model, backed by a wealth of clinical research and expert opinion. It underscores the need for quick ECG assessments and immediate reperfusion therapies for suspected OMI cases, aiming to improve patient outcomes. The OMI-NOMI framework offers a new avenue for future research and clinical application. It advocates for a more comprehensive understanding of the underlying mechanisms of acute coronary syndromes, leading to individualized treatment plans. This novel approach is expected to ignite further scholarly debate and research, particularly in the Brazilian cardiology sector, with the goal of enhancing diagnostic accuracy and treatment effectiveness in AMI patients.

Embora o modelo existente de classificação do infarto agudo do miocárdio (IAM) em IAMCSST e IAMSSST tenha sido benéfico, considera-se hoje que ele falha em abordar a complexidade das síndromes coronarianas agudas. O estudo tem como objetivo examinar o atual paradigma IAMCSST-IAMSSST e defender um modelo mais detalhado, chamado de oclusão coronariana aguda (OCA) e Ausência de Oclusão Coronária Aguda (NOCA), para um diagnóstico e um manejo do IAM mais precisos. Realizou-se uma análise abrangente da literatura médica existente, com foco nas limitações do modelo IAMCSST-IAMSSST. O estudo também descreve uma nova abordagem diagnóstica para pacientes apresentando do torácica nos departamentos de emergência. O modelo IAMCSST-IAMSSST tradicional falha em prover um diagnóstico preciso e um tratamento efetivo, principalmente na identificação de oclusões da artéria coronária. O modelo OCA-NOCA é mais preciso em termos anatômicos e fisiológicos, e apoiado por pesquisa clínica extensa e opiniões de especialistas. Ele destaca a necessidade de rápida realização de eletrocardiogramas (ECGs) e terapias de reperfusão para casos suspeitos de OCA, visando melhorar os desfechos dos pacientes. O modelo OCA-NOCA abre um novo caminho para pesquisas e aplicações clínicas futuras. Ele defende um entendimento mais abrangente dos mecanismos subjacentes das síndromes coronarianas agudas, levando a planos individualizados de tratamentos. Espera-se que essa nova abordagem incite novos debates e pesquisas acadêmicas, principalmente na área de cardiologia no Brasil, com o objetivo de aumentar a precisão diagnóstica e a eficácia do tratamento de pacientes com IAM.

Septal Artery Strangulation Causing Brugada Phenocopy: A Rare Presentation.

Brugada phenocopies are conditions that have an electrocardiography (ECG) pattern that mimics typical patterns seen in Brugada syndrome (BS). We report a rare case of a patient who had a Brugada-like ECG pattern caused by ischemia due to strangulation of the septal artery. The patient was treated with thrombolytic therapy after a probable diagnosis of ST-elevation myocardial infarction (STEMI), which resulted in hematologic complications.

Evaluation of the ODISEA APP for improving a STEMI regional network.

BACKGROUND: The use of technological innovations in ST elevation myocardial infarction (STEMI) care networks has been shown to be effective in improving information flow and coordination, and thus reducing the time to reperfusion. We developed a smartphone application called ODISEA to improve our STEMI care network and evaluated the results of its use. METHOD: Quasi-experimental study that compared the outcomes of STEMI suspected patients with an alert and indication for transfer to a cath lab during a previous period and a period in which the ODISEA APP was used. The main objective was to examine differences in reperfusion time and the proportion of patients with a final diagnosis other than acute coronary syndrome. RESULTS: A total of 699 patients were included (415 before and 284 during the ODISEA-APP period). No differences were observed in patient characteristics, infarct type, or acute complications. We observed a reduction in the time from diagnostic ECG to wire crossing with the use of the ODISEA APP (117 vs 102 min, p < 0.001) and a reduction in the percentage of patients with a final diagnosis other than acute coronary syndrome (17.1% vs 9.5%, p = 0.004). CONCLUSIONS: The use of the ODISEA APP in the management of patients with suspected STEMI may be useful for reducing the time from diagnostic ECG to wire crossing and the percentage of patients with a final diagnosis other than acute coronary syndrome.

Cluster analysis of clinical, angiographic, and laboratory parameters in patients with ST-segment elevation myocardial infarction.

INTRODUCTION: ST-segment elevation myocardial infarction (STEMI) represents the most harmful clinical manifestation of coronary artery disease. Risk assessment plays a beneficial role in determining both the treatment approach and the appropriate time for discharge. Hierarchical agglomerative clustering (HAC), a machine learning algorithm, is an innovative approach employed for the categorization of patients with comparable clinical and laboratory features. The aim of the present study was to investigate the role of HAC in categorizing STEMI patients and to compare the results of these patients. METHODS: A total of 3205 patients who were diagnosed with STEMI at the university hospital emergency clinic between 2015 and 2023 were included in the study. The patients were divided into 2 different phenotypic disease clusters using the HAC method, and their outcomes were compared. RESULTS: In the present study, a total of 3205 STEMI patients were included; 2731 patients were in cluster 1, and 474 patients were in cluster 2. Mortality was observed in 147 (5.4%) patients in cluster 1 and 108 (23%) patients in cluster 2 (chi-square P value < 0.01). Survival analysis revealed that patients in cluster 2 had a significantly greater risk of death than patients in cluster 1 did (log-rank P < 0.001). After adjustment for age and sex in the Cox proportional hazards model, cluster 2 exhibited a notably greater risk of death than did cluster 1 (HR = 3.51, 95% CI = 2.71-4.54; P < 0.001). CONCLUSION: Our study showed that the HAC method may be a potential tool for predicting one-month mortality in STEMI patients.

Phenotypic clustering of patients hospitalized in intensive cardiac care units: Insights from the ADDICT-ICCU study.

BACKGROUND: Intensive cardiac care units (ICCUs) were created to manage ventricular arrhythmias after acute coronary syndromes, but have diversified to include a more heterogeneous population, the characteristics of which are not well depicted by conventional methods. AIMS: To identify ICCU patient subgroups by phenotypic unsupervised clustering integrating clinical, biological, and echocardiographic data to reveal pathophysiological differences. METHODS: During 7-22 April 2021, we recruited all consecutive patients admitted to ICCUs in 39 centers. The primary outcome was in-hospital major adverse events (MAEs; death, resuscitated cardiac arrest or cardiogenic shock). A cluster analysis was performed using a Kamila algorithm. RESULTS: Of 1499 patients admitted to the ICCU (69.6% male, mean age 63.3±14.9 years), 67 (4.5%) experienced MAEs. Four phenogroups were identified: PG1 (n=535), typically patients with non-ST-segment elevation myocardial infarction; PG2 (n=444), younger smokers with ST-segment elevation myocardial infarction; PG3 (n=273), elderly patients with heart failure with preserved ejection fraction and conduction disturbances; PG4 (n=247), patients with acute heart failure with reduced ejection fraction. Compared to PG1, multivariable analysis revealed a higher risk of MAEs in PG2 (odds ratio [OR] 3.13, 95% confidence interval [CI] 1.16-10.0) and PG3 (OR 3.16, 95% CI 1.02-10.8), with the highest risk in PG4 (OR 20.5, 95% CI 8.7-60.8) (all P<0.05). CONCLUSIONS: Cluster analysis of clinical, biological, and echocardiographic variables identified four phenogroups of patients admitted to the ICCU that were associated with distinct prognostic profiles. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT05063097.

Machine-learning clustering analysis identifies novel phenogroups in patients with ST-elevation acute myocardial infarction.

BACKGROUND: Machine learning clustering of patients with ST-elevation acute myocardial infarction (STEMI) may provide important insights into their risk profile, management and prognosis. METHODS: All adult discharges for STEMI in the National Inpatient Sample (October 2015 to December 2019) were included, excluding patients with prior myocardial infarction. Machine-learning clustering analysis was used to define clusters based on 21 clinical attributes of interest. Main outcomes of the study were cluster-based comparison of risk profile, in-hospital clinical outcomes and utilization of invasive management. Binomial hierarchical multivariable logistic regression with adjusted odds ratios (aOR) and 95% confidence intervals (95% CI) was used to detect the between-cluster differences. RESULTS: Out of overall 470,960 STEMI cases, the machine-learning analysis revealed 4 different clusters with 205,640 (cluster 0: 'behavioural risk cluster'), 146,400 (cluster 1: 'least comorbidity cluster'), 45,100 (cluster 2: 'diabetes with end-organ damage cluster') and 73,820 (cluster 3: 'cardiometabolic cluster') cases. Attributes with the highest importance for clustering were hypertension and diabetes. After multivariable adjustment, patients from 'diabetes with end-organ damage cluster' exhibited the worst mortality, MACCE and ischemic stroke (p < 0.001 for all), as well as the lowest utilization of invasive management (p < 0.001 for all), in comparison to other clusters. Patients from 'behavioural risk cluster' exhibited the best in-hospital prognosis and the highest utilization of invasive management, compared to other clusters (p < 0.001 for all). CONCLUSIONS: Machine learning driven clustering of inpatients with STEMI reveals important population subgroups with distinct prevalence, risk profile, prognosis and management. Data driven approaches may identify high risk phenogroups and warrants further study.

The Impact of Microvascular Resistance Reserve on the Outcome of Patients With STEMI.

BACKGROUND: Microvascular resistance reserve (MRR) can characterize coronary microvascular dysfunction (CMD); however, its prognostic impact in ST-segment elevation myocardial infarction (STEMI) patients remains undefined. OBJECTIVES: This study sought to investigate the prevalence of CMD in STEMI patients and to elucidate the prognostic performance of MRR. METHODS: This prospective cohort study enrolled 210 STEMI patients with multivessel disease who underwent successful revascularization and returned at 3 months for coronary physiology assessments with bolus thermodilution. The prevalence of CMD (MRR <3) and the association between MRR and major adverse cardiovascular and cerebrovascular events (MACCEs) at 12 months were investigated. RESULTS: The median age of patients was 65 years, and 59.5% were men. At the 3-month follow-up, 56 patients (27%) had CMD (MRR <3.0). The number of MACCEs at 12 months was higher in patients with vs without CMD (48.2% vs 11.0%; P < 0.001). MRR was independently associated with 12-month MACCEs (HR: 0.45 per unit increase; 95% CI: 0.31-0.67; P < 0.001) and with stroke, heart failure, and poorer recovery in left ventricular systolic function. The areas under the receiver-operating characteristic curves for predicting MACCEs at 12 months with fractional flow reserve, coronary flow reserve (CFR), the index of microvascular resistance (IMR), and MRR were 0.609, 0.762, 0.781, and 0.743, respectively. The prognostic performance of CFR, IMR, and MRR were all comparable. CONCLUSIONS: The novel parameter MRR is a prognostic marker of MACCEs in STEMI patients with a comparable performance to CFR and IMR. (Impact of TMAO Serum Levels on Hyperemic IMR in STEMI Patients [TAMIR]; NCT05406297).

Metabolomics Analysis Identifies Differential Metabolites as Biomarkers for Acute Myocardial Infarction.

Myocardial infarction (MI), including ST-segment elevation MI (STEMI) and non-ST-segment elevation MI (NSTEMI), is still a leading cause of death worldwide. Metabolomics technology was used to explore differential metabolites (DMs) as potential biomarkers for early diagnosis of STEMI and NSTEMI. In the study, 2531 metabolites, including 1925 DMs, were discovered. In the selected 27 DMs, 14 were successfully verified in a new cohort, and the AUC values were all above 0.8. There were 10 in STEMI group, namely L-aspartic acid, L-acetylcarnitine, acetylglycine, decanoylcarnitine, hydroxyphenyllactic acid, ferulic acid, itaconic acid, lauroylcarnitine, myristoylcarnitine, and cis-4-hydroxy-D-proline, and 5 in NSTEMI group, namely L-aspartic acid, arachidonic acid, palmitoleic acid, D-aspartic acid, and palmitelaidic acid. These 14 DMs may be developed as biomarkers for the early diagnosis of MI with high sensitivity and specificity. These findings have particularly important clinical significance for NSTEMI patients because these patients have no typical ECG changes.

ST-segment elevation myocardial infarction (STEMI) caused by spontaneous coronary artery dissection (SCAD) in a patient with von Willebrand disease.

A postpartum woman in her early 40s, with a history of pre-eclampsia and von Willebrand disease (VWD), presented to the emergency room with chest pain suggestive of an acute coronary syndrome. Initial workup revealed an evolving anterior wall ST-segment elevation myocardial infarction on ECG and elevated cardiac biomarkers, confirming myocardial damage. Point-of-care ultrasound showed apical hypokinesis and coronary angiography revealed a distal dissection of the left anterior descending coronary artery. There was TIMI 3 flow and no evidence of plaque rupture. No percutaneous coronary intervention was performed and the patient was managed conservatively.Fibromuscular dysplasia was ruled out on screening CT angiography. Dual antiplatelet therapy was initiated for an amended course of 3 months given the history of VWD. Our patient had an uncomplicated course in the hospital with a downward trend in their cardiac biomarkers, resolving anterior ST elevation on serial ECGs, and no bleeding complications.

A 10-year review of presentation, management and outcomes of STEMI in a high-volume regional tertiary Australian centre.

OBJECTIVE: To assess the trends and impact of changes in management of ST Elevation Myocardial Infarction (STEMI) from 2010 to 2019. DESIGN: Retrospective analysis of data from STEMI hospitalisations including demographic, comorbidity, angiographic and outcome data. SETTING/PARTICIPANTS: High-volume non-surgical regional Australian tertiary referral centre. MAIN OUTCOME MEASUREMENTS: Index & 12-month mortality (all-cause & cardiovascular), door-to-balloon time, target-vessel failure, target-vessel revascularisation & procedure-related bleeding. RESULTS: From 2010 to 2019, 1299 patients presented with STEMI. The cardiovascular risk factor profile did not significantly change over the 10-year study period, p = 0.23. There was a significant trend toward culprit vessel percutaneous coronary intervention with stenting, rather than balloon angioplasty followed by surgical revascularisation, p = 0.029. The mean door-to-balloon time was 88 +/- 5.7 min and demonstrated a statistically significant improvement across the decade, p = 0.035. Radial access became the preferred angiographic approach (2010 92% femoral, 2019 91% radial). Drug-eluting stents (DES) replaced bare metal stent use. There was a statistically significant reduction in 12-month cardiovascular mortality across the decade (p = 0.042). However index hospitalisation (cardiovascular and all-cause) and 12-month all-cause mortality did not reduce. Young patients and women are important sub-groups of STEMI presentations with different risk factor profile. CONCLUSIONS: Advances in management of STEMI such as radial access, use of DES and a significant reduction in door-to-balloon time across the decade resulted in a reduction of 12-month cardiovascular mortality over the decade however there was no significant reduction in 12-month all-cause mortality, or index hospitalisation cardiovascular or index hospitalisation all-cause mortality. Further research is needed to ensure non-mortality outcomes, such as heart failure hospitalisation and quality of life, also demonstrate temporal improvement with STEMI management advances. Earlier cardiovascular risk assessment should be considered in smokers than is currently recommended in Australian guidelines (≥45yo for most individuals).