INTRODUCTION: Elevated troponin, while essential for diagnosing myocardial infarction, can also be present in non-myocardial infarction conditions. The myocardial-ischaemic-injury-index (MI3) algorithm is a machine learning algorithm that considers age, sex and cardiac troponin I (TnI) results to risk-stratify patients for type 1 myocardial infarction. METHOD: Patients aged ≥25 years who presented to the emergency department (ED) of Singapore General Hospital with symptoms suggestive of acute coronary syndrome with no diagnostic 12-lead electrocardiogram (ECG) changes were included. Participants had serial ECGs and high-sensitivity troponin assays performed at 0, 2 and 7 hours. The primary outcome was the adjudicated diagnosis of type 1 myocardial infarction at 30 days. We compared the performance of MI3 in predicting the primary outcome with the European Society of Cardiology (ESC) 0/2-hour algorithm as well as the 99th percentile upper reference limit (URL) for TnI. RESULTS: There were 1351 patients included (66.7% male, mean age 56 years), 902 (66.8%) of whom had only 0-hour troponin results and 449 (33.2%) with serial (both 0 and 2-hour) troponin results available. MI3 ruled out type 1 myocardial infarction with a higher sensitivity (98.9, 95% confidence interval [CI] 93.4-99.9%) and similar negative predictive value (NPV) 99.8% (95% CI 98.6-100%) as compared to the ESC strategy. The 99th percentile cut-off strategy had the lowest sensitivity, specificity, positive predictive value and NPV. CONCLUSION The MI3 algorithm was accurate in risk stratifying ED patients for myocardial infarction. The 99th percentile URL cut-off was the least accurate in ruling in and out myocardial infarction compared to the other strategies.
Humans ; Male ; Female ; Emergency Service, Hospital ; Middle Aged ; Electrocardiography ; Machine Learning ; Singapore ; Chest Pain/blood* ; Troponin I/blood* ; Myocardial Infarction/blood* ; Risk Assessment/methods* ; Aged ; Algorithms ; Acute Coronary Syndrome/blood* ; Adult ; Sensitivity and Specificity

BACKGROUND: Several randomized controlled studies have suggested that the prophylactic use of proton pump inhibitors (PPIs) in intensive care unit (ICU) patients could not reduce the incidence of gastrointestinal bleeding (GIB) and may increase adverse events such as intestinal infection and pneumonia. Gut microbiota may play a critical role in the process. PPIs have been widely prescribed for GIB prophylaxis in patients with acute coronary syndrome (ACS). This study aimed to determine the short-term effects of PPI and histamine-2 receptor antagonist (H2RA) treatment on gut microbiota of ACS patients. METHODS: The study was designed as a single-blind, multicenter, three-parallel-arm, randomized controlled trial conducted at three centers in Beijing, China. We enrolled ACS patients at low-to-medium risk of GIB and randomized (2:2:1) them to either PPI ( n = 40), H2RA ( n = 31), or control group ( n = 21). The primary outcomes were the alterations in gut microbiota after 7 days of acid suppressant therapy. Stool samples were collected at baseline and 7 days and analyzed by 16S ribosomal RNA (rRNA) gene sequencing. RESULTS: There were no significant changes in the diversity of gut microbiota after the short-term use of acid suppressants, but the abundance of Fusobacterium significantly increased and that of Bifidobacterium significantly decreased, especially in PPI users. In addition, the abundance of some pathogenic bacteria, including Enterococcus and Desulfovibrio, was significantly elevated in the PPI users. The fecal microbiota of the PPI users included more arachidonic acid metabolism than that of control group. CONCLUSIONS: PPIs may increase the risk of infection by adversely altering gut microbiota and elevating arachidonic acid metabolism, which may produce multiple proinflammatory mediators. For ACS patients at low-to-medium risk of GIB, sufficient caution should be paid when acid-suppressant drugs are prescribed, especially PPIs. REGISTRATION www.chictr.org.cn (ChiCTR2000029552).
Humans ; Proton Pump Inhibitors/therapeutic use* ; Acute Coronary Syndrome/microbiology* ; Female ; Gastrointestinal Microbiome/drug effects* ; Male ; Middle Aged ; Histamine H2 Antagonists/therapeutic use* ; Aged ; Single-Blind Method

BACKGROUND

In the Philippines, Acute Coronary Syndrome (ACS) is a major cause of mortality. Recognizing high-risk ACS patients quickly is crucial. The Modified Shock Index (MSI), a concise bedside risk scoring system, may enhance triaging by predicting short-term outcomes, facilitating a more aggressive approach for timely intervention.

The aim of this study is to determine MSI’s predictive value for in-hospital mortality in ACS patients, comparing its sensitivity and specificity to Thrombolysis In Myocardial Infarction (TIMI) risk scoring. It also intends to determine association between MSI and major adverse cardiovascular events (MACE).

This retrospective cohort study was conducted in a tertiary hospital with 172 patients aged 18 and above admitted for ACS from January 2017 to December 2022, focused on in-hospital mortality as the primary outcome and other MACE as secondary outcomes. Chi-square test customized for multiple response sets was done to determine association between MSI and clinical outcomes. The study employed ROC analysis for MSI, generating a curve to illustrate sensitivity-specificity trade-offs, Youden Index determined to identify optimal cut-off points, and DeLong’s test to compare efficacy of MSI and TIMI.

A high MSI (≥1) was significantly and independently linked to in-hospital all-cause mortality in ACS patients (p < 0.001). MSI exhibits 82.35% sensitivity and 82.89% specificity for predicting in-hospital mortality. Chi-square test customized for multiple response sets revealed statistically significant association between MSI and the occurrences of cardiogenic shock, revascularization, life-threatening arrhythmia, and cardiac arrest. ROC analysis reveals MSI and TIMI scores as strong predictors (AUC values: 0.848 and 0.787 respectively), with comparable performance indicated by the DeLong test.

MSI proved a reliable parameter for predicting in-hospital mortality in patients presenting with ACS in Notre Dame de Chartres Hospital.

BACKGROUND

Chest pain is a common reason for emergency room visits. The HEART score is used as a risk stratification tool to aid in clinical decision making. The HEART score is a useful tool due to its good sensitivity, however it has low specificity. The SVEAT score was developed as an improved risk stratification tool which outperformed the HEART score in previous studies. Both the performance of HEART and SVEAT scores lack data in our locality.

To compare the performance of Symptoms, Vascular disease, Electrocardiography, Age, Troponin-I (SVEAT) score and History, Electrocardiography, Age, Risk factors, Troponin-I (HEART) score as predictors of in-hospital Major Adverse Cardiovascular Events (MACE) among adult patients admitted in Chong Hua Hospital Cebu for chest pain.

This single-center, retrospective, observational analytic study included adult patients, ages 18 years old and above, who were admitted for chest pain from January 1, 2022 to December 31, 2022. All patients who passed the inclusion and exclusion criteria were included in the data analysis. Both SVEAT and HEART scores were calculated for each of the included subjects. The performance of both scoring criteria was compared using logistic regression and area under the receiving-operator characteristic curve.

A total of 113 cases were analyzed after exclusion criteria were applied. A total of 50 (44.2%) individuals suffered MACE. The difference in AUC of both SVEAT (0.946, 95%CI) and HEART (0.936, 95%CI) was not statistically significant (95% CI – 0.013 – 0.033, p = 0.400). With a cut-off ofCONCLUSION

SVEAT and HEART scores had similar performance in predicting in hospital MACE. Using a cut-off value of
Human ; Chest Pain ; Heart ; Myocardial Infarction ; Acute Coronary Syndrome

Introduction: Red cell distribution width (RDW) is a parameter that is readily available as part of a standard complete blood count (CBC). Studies have shown that an elevated RDW is associated with increased cardiovascular events including acute coronary syndrome (ACS). This cross- sectional retrospective study was conducted to determine the association of RDW in patients with ACS admitted to Bataan General Hospital and Medical Center (BGHMC). Methods: A cross-sectional study was performed in a 500-bed tertiary care hospital in Bataan, Philippines. The clinical medical records of patients with ACS were analyzed retrospectively. A total of 811 patients was admitted as cases of ACS from January 2017 to December 2019. Using Slovin’s formula, the computed sample size was 261 patients. However, only 205 cases were included in the study in accordance to the eligibility criteria. The baseline RDW were recorded from the CBC obtained upon admission of patients with ACS. Results: Based on the data collected from January 2017 to December 2019 from patients admitted to BGHMC, there was no significant association between RDW and in-house morbidity and mortality and classification of ACS. Conclusions There were no significant association between RDW and in-house morbidity and mortality and classification of ACS. The authors recommend to conduct the study for a longer duration to have more population included and to include other parameters such as cardiac enzymes, electrocardiogram (ECG) changes and presence of co-morbidities.
Erythrocyte Indices ; Acute Coronary Syndrome ; Angina, Unstable ; ST Elevation Myocardial Infarction

BACKGROUND: Studies have shown that inflammation plays a role in the pathogenesis of acute coronary syndrome (ACS). The use of platelet-to-lymphocyte ratio (PLR) as a marker for inflammatory conditions such as malignancy, systemic lupus erythematosus, and rheumatoid arthritis has been demonstrated in several studies. The aim of this study is to determine whether an elevated PLR taken on admission is associated with in-hospital mortality and major adverse cardiac events among ACS patients. METHODS: This is a single-center, retrospective correlational study. It included all ACS STsegment elevation myocardial infarction and non–ST-segment elevation myocardial infarction adult patients admitted from January 2011 to December 2020. Complete blood count on admission was used to derive the PLR. Patient’s course in the ward was reviewed for development of adverse clinical outcomes such as in-hospital mortality, arrhythmias, heart failure, cardiogenic shock, and reinfarction. Primary outcome for this study was in-hospital mortality, and the secondary outcomes were the development of other complications previously mentioned. Optimal cutoff value associated with in-hospital mortality was determined using receiver operating characteristic curve. RESULTS: A total of 342 patients were included in the study. Forty-three (12.57%) of the sample had in-hospital mortality and was noted to have higher PLR compared with patients who did not develop complications. Univariate logistic regression analysis showed a significant relationship between a high PLR and occurrence of in-hospital mortality (P = 0.0039). The optimal cutoff value of PLR that can predict in-hospital mortality is 165, with 52.17% sensitivity, 56.76% specificity, and an area under the curve of 59.69%. On the other hand, a high PLR did not show association with the development of complications during the hospital stay. CONCLUSION A PLR of >165 is a cheap, readily available marker that can be used to predict in-hospital mortality among Filipino patients with ACS.
Acute Coronary Syndrome

BACKGROUND: Acute coronary syndrome (ACS) is a leading cause of admission and mortality in a tertiary care hospital in the Philippines. The significant burden of the disease necessitates that evidence-based care set by international and local guidelines be met to improve service delivery and quality of care (QOC). Institution-specific QOC studies showed gaps between guideline recommendations and compliance. Development and utilization of a clinical pathway are among the identified strategies to improve compliance. It is also crucial for implementation of standard-of-care set specific to a hospital setting based on its needs and resources. METHODS: This is a descriptive research on the development of a clinical pathway for ACS appropriate for the emergency room setting of a tertiary care hospital from March 2021 to August 2022. Local QOC studies and evidence behind the latest international guideline recommendations on the management of ACS were reviewed to create the interim ACS Pathway. Two-level content validation of the interim pathway was done: internal validation with the consultants and fellows of the Division of Cardiovascular Medicine and external validation through focused group discussions with different hospital units and stakeholders to assess applicability and feasibility based on the resources of the setting, identify hindrances, and propose solutions in its implementation. RESULTS: An evidence-based clinical pathway for ACS that encompasses identification and management of ST-segment elevation myocardial infarction and non–ST-segment elevation acute coronary syndrome with judicious use of locally available and feasible resources applicable for local emergency room hospital setting was created. CONCLUSION Review of local QOC studies and interdepartmental collaboration are necessary components in developing institution-specific clinical pathway for ACS.
Acute Coronary Syndrome ; Critical Pathways ; Quality of Health Care

Objectives: Type 2 Diabetics have elevated risk for acute coronary syndrome (ACS). The current management algorithm focuses on atherosclerotic cardiovascular (ASCVD) risk score to stratify this risk. However, in medically managed subjects, this algorithm may not be accurate. This study compares the ASCVD risk score in an Indian population with T2DM under medical supervision and the actual incidence of ACS. It also compared the ASCVD risk scores in cases with T2DM who developed ACS to controls and tried to estimate whether the ASCVD risk score is different in the two subsets, evaluating the utility of the ASCVD risk score in predicting ACS. Methodology: This is an electronic medical record (EMR) based case-control study. Only records of subjects with T2DM where details of age, sex, body mass index, blood pressure, duration of diabetes, family history of ACS, lipid profile, renal and liver function tests were included. The incidence of ACS was calculated in the selected records, and the records of subjects with ACS were compared with age and sex-matched subjects without ACS. Data are summarized as median and interquartile range (IQR). Wilcoxon rank-sum test was used for checking differences in continuous variables and Pearson’s Chi-squared test for categorical data. Univariate and multivariate logistic regression analyses were used to check the effect of ASCVD scores and other variables on the occurrence of ACS. Statistical data analyses were performed using JASP, version 0.16.4 (JASP Team [2022]) for MS Windows. Results: Of the 1226 EMRs included in the analysis, 207 had ACS. The actual incidence of ACS was 16.85% in 6 years, higher than the mean predicted 10-year incidence of 14.56 percent (p <0.05). The cases were age and sex-matched with controls and the ASCVD incidence was estimated in the two groups. The mean ASCVD score in the cases was 14.565 ± 8.709 (Min: 1.5, Max: 38.3) and controls 13.114 ± 8.247 (Min: 1.4, Max: 45). The chance of development of ACS increases with elevated systolic blood pressure (per mmHg rise OR: 1.04, 95% CI: 1.03, 1.06; p <0.001), positive family history (OR: 5.70, 95% CI: 3.41, 9.77; p <0.001), statin use (OR: 2.26, 95% CI: 1.46, 3.52; p <0.001), and longer duration of diabetes (for every year increase OR: 1.19, 95% CI: 1.13, 1.25; p <0.001) Conclusion The ASCVD risk score underestimates the ACS risk in subjects with T2DM under medical supervision and may not differ in those who developed and did not develop ACS. We also conclude that factors like a negative family history (30% less risk), longer duration of diabetes, and higher SBP are relevant in those who developed ACS.
Acute Coronary Syndrome

Objective: To investigate the predictive value of glycosylated hemoglobin A1c/apolipoprotein A-1 (HbA1c/ApoA-1) ratio for major adverse cardiovascular events (MACEs) in patients with acute coronary syndrome (ACS). Methods: The present study is a retrospective cohort study. ACS patients who were hospitalized and underwent coronary angiography at Beijing Hospital from March 2017 to March 2019 were enrolled. Baseline information such as sex, age, previous history, Gensini score, HbA1c and ApoA-1 were analyzed. Patients were divided into two groups according to presence or absence of MACEs and the difference on HbA1c/ApoA-1 ratio was compared between the two groups. According to the tertiles of HbA1c/ApoA-1 levels, patients were divided into high (5.87-16.12), medium (4.50-5.83) and low (2.11-4.48) HbA1c/ApoA-1 groups. Cox proportional risk model was used to evaluate the differences in MACEs and all-cause mortality among the three groups. Kaplan-Meier survival analysis was used to compare the differences of MACEs between the various HbA1c/ApoA-1 groups. Results: A total of 366 ACS patients were included in this study. The mean age of the patients was (65.9±10.3) years. There were 59 MACEs and 10 all-cause deaths during the mean of (22.3±4.4) months follow-up. After adjusting for age, systolic blood pressure, history of diabetes and Gensini score, the incidence of MACEs was 2.45 times higher in the high HbA1c/ApoA-1 group than in the low HbA1c/ApoA-1 group (95%CI 1.16-5.18, P=0.019). There was no significant difference in all-cause mortality between the high and low HbA1c/ApoA-1 groups (P=1.000). Kaplan-Meier survival analysis showed that patients in the high HbA1c/ApoA-1 group had the highest risk of MACEs, while patients in the low HbA1c/ApoA-1 group had the lowest risk of MACEs (P<0.01). Spearman rank correlation analysis showed that HbA1/ApoA-1 ratio was positively correlated with Gensini score in ACS patients (r=0.274, P<0.01). Conclusion: High HbA1c/ApoA-1 ratio was an independent risk factor for MACEs in ACS patients. Patients with high HbA1c/ApoA-1 ratio had more severe coronary artery disease lesions. HbA1c/ApoA-1 ratio may be used as a potential risk stratification biomarker for ACS patients, it might be useful for the early identification of high-risk population and for predicting the incidence of MACEs among ACS patients.
Aged ; Humans ; Middle Aged ; Acute Coronary Syndrome/diagnosis* ; Apolipoprotein A-I/analysis* ; Biomarkers/analysis* ; Glycated Hemoglobin/analysis* ; Percutaneous Coronary Intervention ; Retrospective Studies ; Risk Factors ; Predictive Value of Tests

OBJECTIVE: We aimed to assess the feasibility and superiority of machine learning (ML) methods to predict the risk of Major Adverse Cardiovascular Events (MACEs) in chest pain patients with NSTE-ACS. METHODS: Enrolled chest pain patients were from two centers, Beijing Anzhen Emergency Chest Pain Center Beijing Bo'ai Hospital, China Rehabilitation Research Center. Five classifiers were used to develop ML models. Accuracy, Precision, Recall, F-Measure and AUC were used to assess the model performance and prediction effect compared with HEART risk scoring system. Ultimately, ML model constructed by Naïve Bayes was employed to predict the occurrence of MACEs. RESULTS: According to learning metrics, ML models constructed by different classifiers were superior over HEART (History, ECG, Age, Risk factors, & Troponin) scoring system when predicting acute myocardial infarction (AMI) and all-cause death. However, according to ROC curves and AUC, ML model constructed by different classifiers performed better than HEART scoring system only in prediction for AMI. Among the five ML algorithms, Linear support vector machine (SVC), Naïve Bayes and Logistic regression classifiers stood out with all Accuracy, Precision, Recall and F-Measure from 0.8 to 1.0 for predicting any event, AMI, revascularization and all-cause death ( vs. HEART ≤ 0.78), with AUC from 0.88 to 0.98 for predicting any event, AMI and revascularization ( vs. HEART ≤ 0.85). ML model developed by Naïve Bayes predicted that suspected acute coronary syndrome (ACS), abnormal electrocardiogram (ECG), elevated hs-cTn I, sex and smoking were risk factors of MACEs. CONCLUSION Compared with HEART risk scoring system, the superiority of ML method was demonstrated when employing Linear SVC classifier, Naïve Bayes and Logistic. ML method could be a promising method to predict MACEs in chest pain patients with NSTE-ACS.
Humans ; Acute Coronary Syndrome/epidemiology* ; Bayes Theorem ; Feasibility Studies ; Risk Assessment/methods* ; Chest Pain/etiology* ; Myocardial Infarction/diagnosis*