Prevalence, Predictors, and Outcomes of Type 2 NSTEMI in Hospitalized Patients With COVID-19.

BACKGROUND: Data on the incidence of type 2 non-ST-segment-elevation myocardial infarction (T2MI) in hospitalized patients with COVID-19 has been limited to single-center studies. Given that certain characteristics, such as obesity and type 2 diabetes, have been associated with higher mortality in COVID-19 infections, we aimed to define the incidence of T2MI in a national cohort and identify pre-hospital patient characteristics associated with T2MI in hospitalized patients with COVID-19. METHODS AND RESULTS: Using the national American Heart Association COVID-19 Cardiovascular Disease Quality Improvement Registry, we performed a retrospective 4:1 matched (age, sex, race, and body mass index) analysis of controls versus cases with T2MI. We performed (1) conditional multivariable logistic regression to identify predictive pre-hospital patient characteristics of T2MI for patients hospitalized with COVID-19 and (2) stratified proportional hazards regression to investigate the association of T2MI with morbidity and mortality. From January 2020 through May 2021, there were 709 (2.2%) out of 32 015 patients with T2MI. Five hundred seventy-nine cases with T2MI were matched to 2171 controls (mean age 70; 43% female). Known coronary artery disease, heart failure, chronic kidney disease, hypertension, payor source, and presenting heart rate were associated with higher odds of T2MI. Anti-hyperglycemic medication and anti-coagulation use before admission were associated with lower odds of T2MI. Those with T2MI had higher morbidity and mortality (hazard ratio, 1.40 [95% CI, 1.13-1.74]; P=0.002). CONCLUSIONS: In hospitalized patients with COVID-19, those with a T2MI compared with those without had higher morbidity and mortality. Outpatient anti-hyperglycemic and anti-coagulation use were the only pre-admission factors associated with reduced odds of T2MI.

A Near Miss in the Emergency Department: Atypical Presentation of Acute Coronary Syndrome.

Acute coronary syndrome is an umbrella term encompassing three types of coronary artery disease that affect millions worldwide annually. Despite the availability of diagnostic tests (blood analysis, imaging, electrocardiogram, and screening tools), the diagnosis of myocardial infarction (MI) is still sometimes missed. According to the Centers for Disease Control and Prevention, the reported prevalence of heart disease is higher among males than females, with adults over the age of 75 having the highest prevalence. Typical "heart attack" features include chest pain that feels like pressure or squeezing, pain or discomfort in one or both arms that can radiate to the neck or jaw, shortness of breath, diaphoresis, nausea, vomiting, and lightheadedness. However, there are three subgroups where the typical warning signs do not always present: the elderly, individuals with diabetes, and females. The following is an atypical case presentation of unstable angina and non-ST-elevation MI.

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.

Coronary artery disease severity and risk stratification of patients with non ST-elevation acute coronary syndrome using CHA2DS2-VASc-HSF score.

BACKGROUND: Risk stratification assessment of patients with non-ST elevation acute coronary syndrome (NSTE ACS) plays an important role in optimal management and defines the patient's prognosis. This study aimed to evaluate the ability of CHA2DS2-VASc-HSF score (comprising of the components of the CHA2DS2-VASc score with a male instead of female sex category, hyperlipidemia, smoking, and family history of coronary artery disease respectively) to predict the severity and complexity of CAD and its efficacy in stratification for major adverse cardiovascular events (MACE) in patients with NSTE ACS without known atrial fibrillation. METHODS: This study included 200 patients (males 72.5%, mean age 55.8 ± 10.1 years) who were admitted with NSTE ACS. CHA2DS2-VASC-HSF score was calculated on admission. Patients were classified into three groups according to their CHA2DS2-VASC-HSF score: low score group (< 2; 29 patients), intermediate score group (2-4; 83 patients), and high score group (≥ 5; 88 patients). Coronary angiography was conducted and the Syntax score (SS) was calculated. Clinical follow-up at 6 months of admission for the development of MACE was recorded. RESULTS: SS was significantly high in the high CHA2DS2-VASc-HSF score group compared with low and intermediate score groups. CHA2DS2-VASc-HSF score had a significant positive strong correlation with syntax score (r = 0.64, P < 0.001). Smoking, vascular disease, hyperlipidemia, and CHA2DS2-VASc-HSF score were independent predictors of high SS. For the prediction of severe and complex CAD, CHA2DS2-VASc-HSF score had a good predictive power at a cut-off value ≥ 5 with a sensitivity of 86% and specificity of 65%. Hypertension, vascular disease, high SS, and CHA2DS2-VASc-HSF score were independent predictors of MACE. CHA2DS2-VASC-HSF score ≥ 4 was identified as an effective cut-off point for the development of MACE with 94% sensitivity and 70% specificity. CONCLUSIONS: CHA2DS2-VASC-HSF score is proposed to be a simple bedside score that could be used for the prediction of the severity and complexity of CAD as well as a risk stratification tool for the development of MACE in NSTE ACS patients.

Spontaneous Coronary Artery Dissection in a Healthy Man With Non-ST Elevation Myocardial Infarction.

This case report discusses a diagnosis of spontaneous coronary artery dissection in an otherwise healthy man with non­ST elevation myocardial infarction.

The prognostic impact of insulin resistance surrogates in patients with acute myocardial infarction with and without type 2 diabetes.

BACKGROUND: Cardiovascular disease is the major cause of morbidity and mortality, particularly in type 2 diabetes mellitus (T2DM). Novel markers of insulin resistance and progression of atherosclerosis include the triglycerides and glucose index (TyG index), the triglycerides and body mass index (Tyg-BMI) and the metabolic score for insulin resistance (METS-IR). Establishing independent risk factors for in-hospital death and major adverse cardiac and cerebrovascular events (MACCE) in patients with myocardial infarction (MI) remains critical. The aim of the study was to assess the risk of in-hospital death and MACCE within 12 months after ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI) in patients with and without T2DM based on TyG index, Tyg-BMI and METS-IR. METHODS: Retrospective analysis included 1706 patients with STEMI and NSTEMI hospitalized between 2013 and 2021. We analyzed prognostic value of TyG index, Tyg-BMI and METS-IR for in-hospital death and MACCE as its components (death from any cause, MI, stroke, revascularization) within 12 months after STEMI or NSTEMI in patients with and without T2DM. RESULTS: Of 1706 patients, 58 in-hospital deaths were reported (29 patients [4.3%] in the group with T2DM and 29 patients [2.8%] in the group without T2DM; p = 0.1). MACCE occurred in 18.9% of the total study population (25.8% in the group with T2DM and 14.4% in the group without T2DM; p < 0.001). TyG index, Tyg-BMI and METS-IR were significantly higher in the group of patients with T2DM compared to those without T2DM (p < 0.001). Long-term MACCE were more prevalent in patients with T2DM (p < 0.001). The area under the ROC curve (AUC-ROC) for the prediction of in-hospital death and the TyG index was 0.69 (p < 0.001). The ROC curve for predicting in-hospital death based on METS-IR was 0.682 (p < 0.001). The AUC-ROC values for MACCE prediction based on the TyG index and METS-IR were 0.582 (p < 0.001) and 0.57 (p < 0.001), respectively. CONCLUSIONS: TyG index was an independent risk factor for in-hospital death in patients with STEMI or NSTEMI. TyG index, TyG-BMI and METS-IR were not independent risk factors for MACCE at 12 month follow-up. TyG index and METS-IR have low predictive value in predicting MACCE within 12 months after STEMI and NSTEMI.

Association of Use and Dose of Lipid-Lowering Therapy Post Acute Myocardial Infarction With 5-Year Survival in Older Adults.

BACKGROUND: Older people are underrepresented in randomized trials. The association between lipid-lowering therapy (LLT) and its intensity after acute myocardial infarction and long-term mortality in this population deserves to be assessed. METHODS: The FAST-MI (French Registry of Acute ST-Elevation or Non-ST-Elevation Myocardial Infarction) program consists of nationwide French surveys including all patients admitted for acute myocardial infarction ≤48 hours from onset over a 1- to 2-month period in 2005, 2010, and 2015, with long-term follow-up. Numerous data were collected and a centralized 10-year follow-up was organized. The present analysis focused on the association between prescription of LLT (atorvastatin ≥40 mg or equivalent, or any combination of statin and ezetimibe) and 5-year mortality in patients aged ≥80 years discharged alive. Cox multivariable analysis and propensity score matching were used to adjust for baseline differences. RESULTS: Among the 2258 patients aged ≥80 years (mean age, 85±4 years; 51% women; 39% ST-segment elevation myocardial infarction; 58% with percutaneous coronary intervention), 415 were discharged without LLT (18%), 866 with conventional doses (38%), and 977 with high-dose LLT (43%). Five-year survival was 36%, 47.5%, and 58%, respectively. Compared with patients without LLT, high-dose LLT was significantly associated with lower 5-year mortality (adjusted hazard ratio, 0.78 [95% CI, 0.66-0.92]), whereas conventional-intensity LLT was not (adjusted hazard ratio, 0.93 [95% CI, 0.80-1.09]). In propensity score-matched cohorts (n=278 receiving high-intensity LLT and n=278 receiving no statins), 5-year survival was 52% with high-intensity LLT at discharge and 42% without statins (hazard ratio, 0.78 [95% CI, 0.62-0.98]). CONCLUSIONS: In these observational cohorts, high-intensity LLT at discharge after acute myocardial infarction was associated with reduced all-cause mortality at 5 years in an older adult population. These results suggest that high-intensity LLT should not be denied to patients on the basis of old age. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifiers: NCT00673036, NCT01237418, and NCT02566200.

Retrospective review of non-ST segment elevation acute coronary syndrome presenting to the emergency department of a major tertiary center in Saudi Arabia.

BACKGROUND: Acute coronary syndrome (ACS) comprises a spectrum of diseases ranging from unstable angina (UA), non-ST elevation myocardial infarction (non-STEMI) and ST elevation myocardial infarction (STEMI). Treatment of ACS without STEMI (NSTEMI-ACS) can vary, depending on the severity of presentation and multiple other factors. OBJECTIVE: Analyze the NSTEMI-ACS patients in our institution. DESIGN: Retrospective observational. SETTING: A tertiary care institution with accredited chest pain center. PATIENTS AND METHODS: The travel time from ED booking to the final disposition for patients presenting with chest pain was retrieved over a period of 6 months. The duration of each phase of management was measured with a view to identify the factors that influence their management and time from the ED to their final destination. The data was analyzed using descriptive statistics. MAIN OUTCOME MEASURES: Travel time from ED to final destination. SAMPLE SIZE: 300 patients. RESULTS: The majority of patients were males (64%) between 61 and 80 years of age (45%). The median disposition time (from ED booking to admission order by the cardiology team) was 5 hours and 19 minutes. Cardiology admissions took 10 hours and 20 minutes from ED booking to the inpatient bed. UA was diagnosed in 153 (51%) patients and non-STEMI in 52 (17%). Coronary catheterization was required in 79 (26%) patients, 24 (8%) had coronary artery bypass grafting (CABG) and 8 (3%) had both catheterization and CABG. CONCLUSION: The time from ED booking to final destination for NSTEMI-ACS patients is delayed due to multiple factors, which caused significant delays in overall management. Additional interventional steps can help improve the travel times, diagnosis, management and disposition of these patients. LIMITATIONS: Single center study done in a tertiary care center so the results from this study may not be extrapolated to other centers.

The CRP troponin test (CTT) stratifies mortality risk in patients with non-ST elevation myocardial infarction (NSTEMI).

INTRODUCTION: The C-reactive protein (CRP)-troponin-test (CTT) comprises simultaneous serial measurements of CRP and cardiac troponin and might reflect the systemic inflammatory response in patients with acute coronary syndrome. We sought to test its ability to stratify the short- and long-term mortality risk in patients with non-ST elevation myocardial infarction (NSTEMI). METHODS: We examined 1,675 patients diagnosed with NSTEMI on discharge who had at least two successive measurements of combined CRP and cardiac troponin within 48 h of admission. A tree classifier model determined which measurements and cutoffs could be used to best predict mortality during a median follow-up of 3 years [IQR 1.8-4.3]. RESULTS: Patients with high CRP levels ( > 90th percentile, >54 mg/L) had a higher 30-day mortality rate regardless of their troponin test findings (16.7% vs. 2.9%, p < 0.01). However, among patients with "normal" CRP levels ( < 54 mg/L), those who had high troponin levels ( > 80th percentile, 4,918 ng/L) had a higher 30-day mortality rate than patients with normal CRP and troponin concentrations (7% vs. 2%, p < 0.01). The CTT test result was an independent predictor for overall mortality even after adjusting for age, sex, and comorbidities (HR = 2.28 [95% CI 1.56-3.37], p < 0.01 for patients with high troponin and high CRP levels). CONCLUSIONS: Early serial CTT results may stratify mortality risk in patients with NSTEMI, especially those with "normal" CRP levels. The CTT could potentially assess the impact of inflammation during myocardial necrosis on the outcomes of patients with NSTEMI and identify patients who could benefit from novel anti-inflammatory therapies.

A unique cause of acute bypass graft failure: think outside the box.

A 62-year-old male presented with non-ST elevation myocardial infarction. Cardiac catheterization revealed multivessel coronary artery disease.

C-reactive protein to albumin ratio may predict in-hospital mortality in non-ST elevation myocardial infarction.

Objective: The authors investigated the value of novel inflammatory markers, systemic immune-inflammation index and C-reactive protein to albumin ratio (CAR), to predict in-hospital mortality in patients with non-ST elevation myocardial infarction (NSTEMI). Materials & methods: A total of 308 patients who underwent percutaneous coronary intervention because of NSTEMI were retrospectively included in the study. Killip classification, Thrombolysis in Myocardial Infarction score, SYNTAX score, and CAR and systemic immune-inflammation index values were calculated. Results: CAR (cutoff: 0.0864; sensitivity: 94.1%; specificity: 40.5%; p = 0.008) and Killip classification (cutoff: 2.5; sensitivity: 64.7%; specificity: 8.9%; p = 0.001) were found to be significantly higher in determining in-hospital mortality. Conclusion: This study revealed that CAR is an inexpensive and significant factor in predicting in-hospital mortality in patients undergoing percutaneous coronary intervention for NSTEMI.

[Acute coronary syndrome: diagnosis and treatment].

INTRODUCTION: In Switzerland, about 20 000 people experience an acute coronary syndrome (ACS) event each year. Acute coronary syndromes comprise ST-segment elevation myocardial infarction (STEMI), non-ST-segment elevation myocardial infarction (NSTEMI), and unstable angina. The diagnosis is made based on the clinical presentation, a rise in cardiac biomarkers, and ischemic ECG changes. In patients with acute STEMI, urgent coronary angiography with primary percutaneous coronary intervention (PCI) to open the occluded artery is indicated. In patients with NSTEMI and unstable angina, the timing of coronary angiography and PCI is based on the clinical presentation and on a comprehensive and individualized risk stratification. Optimal secondary prevention and aggressive cardiovascular risk factor control are important following the acute event. Keywords.

Sex-Based Disparities in Acute Myocardial Infarction Treatment Patterns and Outcomes in Older Adults Hospitalized Across 6 High-Income Countries: An Analysis From the International Health Systems Research Collaborative.

BACKGROUND: Sex differences in acute myocardial infarction treatment and outcomes are well documented, but it is unclear whether differences are consistent across countries. The objective of this study was to investigate the epidemiology, use of interventional procedures, and outcomes for older females and males hospitalized with ST-segment-elevation myocardial infarction (STEMI) and non-ST-segment-elevation myocardial infarction (NSTEMI) in 6 diverse countries. METHODS: We conducted a serial cross-sectional cohort study of 1 508 205 adults aged ≥66 years hospitalized with STEMI and NSTEMI between 2011 and 2018 in the United States, Canada, England, the Netherlands, Taiwan, and Israel using administrative data. We compared females and males within each country with respect to age-standardized hospitalization rates, rates of cardiac catheterization, percutaneous coronary intervention, and coronary artery bypass graft surgery within 90 days of hospitalization, and 30-day age- and comorbidity-adjusted mortality. RESULTS: Hospitalization rates for STEMI and NSTEMI decreased between 2011 and 2018 in all countries, although the hospitalization rate ratio (rate in males/rate in females) increased in virtually all countries (eg, US STEMI ratio, 1.58:1 in 2011 and 1.73:1 in 2018; Israel NSTEMI ratio, 1.71:1 in 2011 and 2.11:1 in 2018). Rates of cardiac catheterization, percutaneous coronary intervention, and coronary artery bypass graft surgery were lower for females than males for STEMI in all countries and years (eg, US cardiac catheterization in 2018, 88.6% for females versus 91.5% for males; Israel percutaneous coronary intervention in 2018, 76.7% for females versus 84.8% for males) with similar findings for NSTEMI. Adjusted mortality for STEMI in 2018 was higher for females than males in 5 countries (the United States, Canada, the Netherlands, Israel, and Taiwan) but lower for females than males in 5 countries for NSTEMI. CONCLUSIONS: We observed a larger decline in acute myocardial infarction hospitalizations for females than males between 2011 and 2018. Females were less likely to receive cardiac interventions and had higher mortality after STEMI. Sex disparities seem to transcend borders, raising questions about the underlying causes and remedies.

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

BACKGROUND: Traditional risk assessment tools often lack accuracy when predicting the short- and long-term mortality following a non-ST-segment elevation myocardial infarction (NSTEMI) or Unstable Angina (UA) in specific population. OBJECTIVE: To employ machine learning (ML) and stacked ensemble learning (EL) methods in predicting short- and long-term mortality in Asian patients diagnosed with NSTEMI/UA and to identify the associated features, subsequently evaluating these findings against established risk scores. METHODS: We analyzed data from the National Cardiovascular Disease Database for Malaysia (2006-2019), representing a diverse NSTEMI/UA Asian cohort. Algorithm development utilized in-hospital records of 9,518 patients, 30-day data from 7,133 patients, and 1-year data from 7,031 patients. This study utilized 39 features, including demographic, cardiovascular risk, medication, and clinical features. In the development of the stacked EL model, four base learner algorithms were employed: eXtreme Gradient Boosting (XGB), Support Vector Machine (SVM), Naive Bayes (NB), and Random Forest (RF), with the Generalized Linear Model (GLM) serving as the meta learner. Significant features were chosen and ranked using ML feature importance with backward elimination. The predictive performance of the algorithms was assessed using the area under the curve (AUC) as a metric. Validation of the algorithms was conducted against the TIMI for NSTEMI/UA using a separate validation dataset, and the net reclassification index (NRI) was subsequently determined. RESULTS: Using both complete and reduced features, the algorithm performance achieved an AUC ranging from 0.73 to 0.89. The top-performing ML algorithm consistently surpassed the TIMI risk score for in-hospital, 30-day, and 1-year predictions (with AUC values of 0.88, 0.88, and 0.81, respectively, all p < 0.001), while the TIMI scores registered significantly lower at 0.55, 0.54, and 0.61. This suggests the TIMI score tends to underestimate patient mortality risk. The net reclassification index (NRI) of the best ML algorithm for NSTEMI/UA patients across these periods yielded an NRI between 40-60% (p < 0.001) relative to the TIMI NSTEMI/UA risk score. Key features identified for both short- and long-term mortality included age, Killip class, heart rate, and Low-Molecular-Weight Heparin (LMWH) administration. CONCLUSIONS: In a broad multi-ethnic population, ML approaches outperformed conventional TIMI scoring in classifying patients with NSTEMI and UA. ML allows for the precise identification of unique characteristics within individual Asian populations, improving the accuracy of mortality predictions. Continuous development, testing, and validation of these ML algorithms holds the promise of enhanced risk stratification, thereby revolutionizing future management strategies and patient outcomes.

Differential gene expression patterns in ST-elevation Myocardial Infarction and Non-ST-elevation Myocardial Infarction.

The ST-elevation Myocardial Infarction (STEMI) and Non-ST-elevation Myocardial Infarction (NSTEMI) might occur because of coronary artery stenosis. The gene biomarkers apply to the clinical diagnosis and therapeutic decisions in Myocardial Infarction. The aim of this study was to introduce, enrich and estimate timely the blood gene profiles based on the high-throughput data for the molecular distinction of STEMI and NSTEMI. The text mining data (50 genes) annotated with DisGeNET data (144 genes) were merged with the GEO gene expression data (5 datasets) using R software. Then, the STEMI and NSTEMI networks were primarily created using the STRING server, and improved using the Cytoscape software. The high-score genes were enriched using the KEGG signaling pathways and Gene Ontology (GO). Furthermore, the genes were categorized to determine the NSTEMI and STEMI gene profiles. The time cut-off points were identified statistically by monitoring the gene profiles up to 30 days after Myocardial Infarction (MI). The gene heatmaps were clearly created for the STEMI (high-fold genes 69, low-fold genes 45) and NSTEMI (high-fold genes 68, low-fold genes 36). The STEMI and NSTEMI networks suggested the high-score gene profiles. Furthermore, the gene enrichment suggested the different biological conditions for STEMI and NSTEMI. The time cut-off points for the NSTEMI (4 genes) and STEMI (13 genes) gene profiles were established up to three days after Myocardial Infarction. The study showed the different pathophysiologic conditions for STEMI and NSTEMI. Furthermore, the high-score gene profiles are suggested to measure up to 3 days after MI to distinguish the STEMI and NSTEMI.

Discriminatory power of a circulating multi-noncoding RNA panel in acute coronary syndrome subtypes: Towards precision detection.

BACKGROUND: Acute Coronary Syndrome (ACS) stands as a significant contributor to cardiovascular mortality, necessitating improved diagnostic tools for early detection and tailored therapeutic interventions. Current diagnostic modalities, exhibit limitations in sensitivity and specificity, urging the quest for novel biomarkers to enhance discrimination of the different stages of ACS including unstable angina, Non-ST-segment Elevation Myocardial Infarction (NSTEMI), and ST-segment Elevation Myocardial Infarction (STEMI). METHODS: This study investigated the potential of a plasma-circulating multi-noncoding RNA (ncRNA) panel, comprising four miRNAs (miR-182-5p, miR-23a-3p, miR-146a-5p, and miR-183-5p) and three lncRNAs (SNHG15, SNHG5, and RMRP), selected based on their intricate involvement in ACS pathogenesis and signaling pathways regulating post-myocardial infarction (MI) processes. The differential expression of these ncRNAs was validated in sera of ACS patients and healthy controls via real-time polymerase chain reaction (RT-PCR). RESULTS: Analysis revealed a marked upregulation of the multi-ncRNAs panel in ACS patients. Notably, miRNA-182-5p and lncRNA-RMRP exhibited exceptional discriminatory power, indicated by the high area under the curve (AUC) values (0.990 and 0.980, respectively). Importantly, this panel displayed superior efficacy in discriminating between STEMI and NSTEMI, outperforming conventional biomarkers like creatine kinase-MB and cardiac troponins. Additionally, the four miRNAs and lncRNA RMRP showcased remarkable proficiency in distinguishing between STEMI and unstable angina. CONCLUSION: The findings underscore the promising potential of the multi-ncRNA panel as a robust tool for early ACS detection, and precise differentiation among ACS subtypes, and as a potential therapeutic target.

Trends and In-Hospital Mortality for Perioperative Myocardial Infarction After the Introduction of a Diagnostic Code for Type 2 Myocardial Infarction in the United States Between 2016 and 2018.

BACKGROUND: The frequency of perioperative myocardial infarction has been declining; however, previous studies have only described type 1 myocardial infarctions. Here, we evaluate the overall frequency of myocardial infarction with the addition of an International Classification of Diseases 10th revision (ICD-10-CM) code for type 2 myocardial infarction and the independent association with in-hospital mortality. METHODS: A longitudinal cohort study spanning the introduction of the ICD-10-CM diagnostic code for type 2 myocardial infarction using the National Inpatient Sample (NIS) from 2016 to 2018. Hospital discharges that included a primary surgical procedure code for intrathoracic, intraabdominal, or suprainguinal vascular surgery were included. Type 1 and type 2 myocardial infarctions were identified using ICD-10-CM codes. We used segmented logistic regression to estimate change in frequency of myocardial infarctions and multivariable logistic regression to determine the association with in-hospital mortality. RESULTS: A total of 360,264 unweighted discharges were included, representing 1,801,239 weighted discharges, with median age 59 and 56% female. The overall incidence of myocardial infarction was 0.76% (13,605/1,801,239). Before the introduction of type 2 myocardial infarction code, there was a small baseline decrease in the monthly frequency of perioperative myocardial infarctions (odds ratio [OR], 0.992; 95% confidence interval [CI], 0.984-1.000; P = .042), but no change in the trend after the introduction of the diagnostic code (OR, 0.998; 95% CI, 0.991-1.005; P = .50). In 2018, where there was an entire year where type 2 myocardial infarction was officially a diagnosis, the distribution of myocardial infarction type 1 was 8.8% (405/4580) ST elevation myocardial infarction (STEMI), 45.6% (2090/4580) non-ST elevation myocardial infarction (NSTEMI), and 45.5% (2085/4580) type 2 myocardial infarction. STEMI and NSTEMI were associated with increased in-hospital mortality (OR, 8.96; 95% CI, 6.20-12.96; P < .001 and OR, 1.59; 95% CI, 1.34-1.89; P < .001). A diagnosis of type 2 myocardial infarction was not associated with increased odds of in-hospital mortality (OR, 1.11; 95% CI, 0.81-1.53; P = .50) when accounting for surgical procedure, medical comorbidities, patient demographics, and hospital characteristics. CONCLUSIONS: The frequency of perioperative myocardial infarctions did not increase after the introduction of a new diagnostic code for type 2 myocardial infarctions. A diagnosis of type 2 myocardial infarction was not associated with increased in-patient mortality; however, few patients received invasive management that may have confirmed the diagnosis. Further research is needed to identify what type of intervention, if any, may improve outcomes in this patient population.

Prognosis of cardiogenic shock with and without acute myocardial infarction: results from a prospective, monocentric registry.

OBJECTIVE: The study investigates the prognostic impact of cardiogenic shock (CS) stratified by the presence or absence of acute myocardial infarction (AMI). BACKGROUND: Intensive care unit (ICU) related mortality in CS patients remains unacceptably high despite improvement concerning the treatment of CS patients. METHODS: Consecutive patients with CS from 2019 to 2021 were included monocentrically. The prognostic impact of CS related to AMI was compared to patients without AMI-related CS. The primary endpoint was 30-day all-cause mortality. Statistical analyses included Kaplan-Meier analyses, multivariable Cox proportional regression analyses and propensity score matching. RESULTS: 273 CS patients were included (AMI-related CS: 49%; non-AMI-related CS: 51%). The risk of 30-day all-cause mortality was increased in patients with AMI-related CS (64% vs. 47%; HR = 1.653; 95% CI 1.199-2.281; p = 0.002), which was still observed after multivariable adjustment (HR = 1.696; 95% CI 1.153-2.494; p = 0.007). Even after propensity score matching (i.e., 87 matched pairs), AMI was still an independent predictor of 30-day mortality (HR = 1.524; 95% CI 1.020-2.276; p = 0.040). In contrast, non-ST-segment AMI (NSTEMI) and STEMI were associated with comparable prognosis (log-rank p = 0.528). CONCLUSION: AMI-related CS was associated with increased 30-day all-cause mortality compared to patients with CS not related to AMI. In contrast, the prognosis of STEMI- and NSTEMI-CS patients was comparable.

Association between anaemia and long-term prognosis in patients with non-ST segment elevation myocardial infarction.

BACKGROUND: The majority of existing studies examining the association between anaemia and the prognosis of patients with acute coronary syndrome (ACS) have focused on all patients with ACS without further categorisation. As a result, there is a dearth of research specifically exploring the relationship between anaemia and the long-term prognosis of patients with non-ST segment elevation myocardial infarction (NSTEMI). To address this gap, this study aimed to investigate the correlation between anaemia and the long-term prognosis of NSTEMI patients. METHODS: This study included 482 NSTEMI patients who underwent percutaneous coronary intervention (PCI) at the First Affiliated Hospital of Chongqing Medical University from September 1, 2016 to May 31, 2022, and the patients were classified into the major adverse cardiovascular events (MACE) group and non-MACEs group according to whether or not they had developed MACE as of February 28, 2023 at follow-up.COX regression analysis was used to assess whether anaemia was an independent factor influencing MACE occurrence in patients with NSTEMI. Receiver operating characteristic (ROC) curve analysis was conducted to determine if haemoglobin levels could enhance the predictive capacity of the Global Registry of Acute Coronary Events (GRACE) score for the prognosis of NSTEMI patients. Haemoglobin levels were categorised into two groups based on the optimal cut-off value and transformed into binary data. The log-rank test was performed to compare the two groups, and a risk function was plotted. RESULTS: During a median follow-up period of 31 months, 124 (25.7%) MACE were identified. Univariate and multivariate COX regression analyses revealed that sex, age, smoking history, diabetes, creatinine, erythrocyte count, and haemoglobin level were independent risk factors that significantly influenced survival time. Subsequently, ROC curve analysis was performed to evaluate the predictive accuracy of specific variables. When the cut-off value for the decline ratio of haemoglobin was set at 128.50, the area under the curve (AUC) was determined to be 0.604, with a sensitivity of 0.403 and a specificity of 0.771. Similarly, setting the cut-off value for the reduction ratio of the GRACE score at 141.5 yielded an AUC of 0.700, with a sensitivity of 0.645 and a specificity of 0.709. Furthermore, when the cut-off value for the predicted probability of haemoglobin combined with the GRACE score was 0.270, the AUC was calculated as 0.702, with a sensitivity of 0.677 and a specificity of 0.696. CONCLUSION: Haemoglobin levels were identified as an independent factor influencing the survival duration of patients with NSTEMI.