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

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

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

Acute coronary syndrome (ACS) is one of the leading causes of death in cardiovascular disease. Percutaneous coronary intervention (PCI) is an important method for the treatment of coronary heart disease (CHD), and it has greatly reduced the mortality of ACS patients since its application. However, a series of new problems may occur after PCI, such as in-stent restenosis, no-reflow phenomenon, in-stent neoatherosclerosis, late stent thrombosis, myocardial ischemia-reperfusion injury, and malignant ventricular arrhythmias, which result in the occurrence of major adverse cardiac events (MACE) that seriously reduce the postoperative benefit for patients. The inflammatory response is a key mechanism of MACE after PCI. Therefore, examining effective anti-inflammatory therapies after PCI in patients with ACS is a current research focus to reduce the incidence of MACE. The pharmacological mechanism and clinical efficacy of routine Western medicine treatment for the anti-inflammatory treatment of CHD have been verified. Many Chinese medicine (CM) preparations have been widely used in the treatment of CHD. Basic and clinical studies showed that effectiveness of the combination of CM and Western medicine treatments in reducing incidence of MACE after PCI was better than Western medicine treatment alone. The current paper reviewed the potential mechanism of the inflammatory response and occurrence of MACE after PCI in patients with ACS and the research progress of combined Chinese and Western medicine treatments in reducing incidence of MACE. The results provide a theoretical basis for further research and clinical treatment.
Humans ; Percutaneous Coronary Intervention/methods* ; Acute Coronary Syndrome/drug therapy* ; Coronary Disease ; Treatment Outcome ; Stents/adverse effects*

Background: Acute coronary syndrome (ACS) is a major cardiovascular problem due to its high hospitalization and mortality rates. One of the risk factors for atherosclerosis that leads to ACS is insulin resistance (IR) which plays a role in the pathogenesis and development of cardiovascular events. This study aims to determine the relationship between IR and in-hospital outcomes in non-diabetic patients with ACS. Methodology: This was a cohort study conducted from January-June 2021. Insulin resistance was assessed using the Admission insulin resistance index (AIRI). This measurement was performed once during the patient's admission, and then the outcome was observed during hospitalization. The observed in-hospital outcomes were composite outcomes; namely, heart failure, arrhythmia, cardiogenic shock, and death. The statistical tests used were ANOVA, independent T and Chi-Square tests. Statistical test results were considered significant if p<0.05. Results: This study included 60 subjects (51 males and 9 females). Analysis revealed that AIRI was higher in patients with composite outcomes (mean 9.97 ± 4.08) than in patients without composite outcomes (mean 7.71 ± 4.06) (p<0.05); AIRI was higher in patients with heart failure (mean 10.72 ± 3.83) than in patients without heart failure (mean 7.25 ± 3.84) (p<0.001). Patients with IR had a higher rate of heart failure complications [OR 5.5 95% CI (1.56-19.38) (p=0.005)]. Conclusion There is an association between AIRI and composite outcomes. Patients with IR have 5.5 times the risk of developing heart failure.
insulin resistance ; acute coronary syndrome

Objective: For patients with atrial fibrillation (AF) complicated with acute coronary syndrome (ACS), both anticoagulant and antiplatelet therapy should be applied, but the use of anticoagulation therapy is still poor in these patients in China. The purpose of this study was to explore the status and adherence of antithrombotic therapy in AF patients with ACS and the impact on 1 year clinical outcomes. Methods: Patients with AF hospitalized for ACS were retrospectively included from 6 tertiary hospitals in China between July 2015 and December 2020. According to the use of anticoagulant drugs at discharge, patients were divided into two groups: anticoagulant treatment group and non-anticoagulant treatment group. Logistic regression model was used to analyze the main factors influencing the use of anticoagulant drugs in patients with atrial fibrillation complicated with ACS. Major adverse cardiac events (MACEs) were defined as all-cause death, non-fatal myocardial infarction or coronary revascularization, and ischemic stroke and Bleeding Academic Research Consortium (BARC) 3 bleeding events were also collected at 1 year after discharge. After propensity score matching, Cox proportional hazards models and Kaplan-Meier analysis were used to evaluate the effect of anticoagulant treatment and non-anticoagulant treatment on 1-year prognosis. The patients were divided into different groups according to whether anticoagulation was performed at discharge and follow-up, and the sensitivity of the results was analyzed. Results: A total of 664 patients were enrolled, and 273 (41.1%) were treated with anticoagulant therapy, of whom 84 (30.8%) received triple antithrombotic therapy, 91 (33.3%) received double antithrombotic therapy (single antiplatelet combined with anticoagulant), and 98 (35.9%) received single anticoagulant therapy. Three hundred and ninety-one (58.9%) patients were treated with antiplatelet therapy, including 253 (64.7%) with dual antiplatelet therapy and 138 (35.3%) with single antiplatelet therapy. After 1∶1 propensity score matching between the anticoagulant group and the non-anticoagulant group, a total of 218 pairs were matched. Multivariate logistic regression analysis showed that history of diabetes, HAS-BLED score≥3, and percutaneous coronary intervention were predictors of the absence of anticoagulant therapy, while history of ischemic stroke and persistent atrial fibrillation were predictors of anticoagulant therapy. At 1-year follow-up, 218 patients (79.9%) in the anticoagulant group continued to receive anticoagulant therapy, and 333 patients (85.2%) in the antiplatelet group continued to receive antiplatelet therapy. At 1-year follow-up, 36 MACEs events (13.2%) occurred in the anticoagulant group, and 81 MACEs events (20.7%) in the non-anticoagulant group. HR values and confidence intervals were calculated by Cox proportional risk model. Patients in the non-anticoagulant group faced a higher risk of MACEs (HR=1.802, 95%CI 1.112-2.921, P=0.017), and the risk of bleeding events was similar between the two group (HR=0.825,95%CI 0.397-1.715, P=0.607). Conclusions: History of diabetes, HAS-BLED score≥3, and percutaneous coronary intervention are independent factors for the absence of anticoagulant therapy in patients with AF complicated with ACS. The incidence of MACEs, death and myocardial infarction is lower in the anticoagulant group, and the incidence of bleeding events is similar between the two groups. The risk of bleeding and ischemia/thrombosis should be dynamically assessed during follow-up and antithrombotic regiments should be adjusted accordingly.
Humans ; Atrial Fibrillation/drug therapy* ; Platelet Aggregation Inhibitors/adverse effects* ; Acute Coronary Syndrome/drug therapy* ; Fibrinolytic Agents/therapeutic use* ; Retrospective Studies ; Treatment Outcome ; Anticoagulants ; Myocardial Infarction/complications* ; Hemorrhage ; Percutaneous Coronary Intervention ; Ischemic Stroke/drug therapy* ; Stroke

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*