TIMI Score Research Articles

Examining prognostic scores for short-term major adverse cardiovascular events prediction following primary PCI: a comparative analysis

Abstract Background Accurately predicting short-term MACE (major adverse cardiac events) following primary PCI remains a clinical challenge. This study aims to assess the effectiveness of four established risk scores in predicting short-term MACE after primary PCI (percutaneous coronary intervention). Methodology We enrolled a cohort of consecutive adult patients diagnosed with STEMI (ST elevation myocardial infarction) undergoing primary PCI in this prospective observational study. Patients were followed at the interval of 3 months up for up to 12 months, and MACE events were recorded. Additionally, we obtained TIMI, PAMI, CADILLAC, and GRACE scores. Results A total of 2839 patients (79.3% male, mean age 55.6 ± 11.2 years) were included. Over a median follow-up of 244 days, the composite MACE rate was 18.3% (519). All-cause mortality was 13.5% (384), re-infarction requiring revascularization was 4.3% (121), heart failure-related re-hospitalization was 2.6% (74), stent thrombosis occurred in 5.6% (160), and CVA (cerebrovascular accident) events were documented in 1% (28). The AUC (area under the curve) for TIMI, PAMI, CADILLAC, and GRACE scores were 0.658 [0.630-0.685], 0.658 [0.632-0.684], 0.669 [0.644-0.695], and 0.675 [0.649-0.701], respectively, for the prediction of MACE. On multivariable Cox regression, medium and high-risk categories based on GRACE score were independent predictors of MACE with adjusted HR (hazard ratio) of 1.52 [1.21-1.92]; p<0.001 and 1.92 [1.34-2.75]; p<0.001, respectively. Conclusion A significant proportion of patients experienced short-term MACE after primary PCI. While none of the assessed scores demonstrated significant predictive power, the GRACE score exhibited comparatively better predictive ability than TIMI, PAMI, and CADILLAC scores

Development of an Initial Screening Scale to Detect Patients With Chest Pain From Acute Coronary Syndrome in the Emergency Department.

Identifying patients with chest pain potentially due to acute coronary syndrome (ACS) early is crucial for triage nurses. They need a reliable, validated screening tool. This study aims to develop an initial screening scale to detect ACS in patients presenting with chest pain in the emergency department. We analyzed electronic medical records of 3131 chest pain patients from 103,041 emergency department visits between January 2018 and December 2019. ACS diagnosis was confirmed by cardiologists through clinical symptoms, electrocardiograms, and cardiac enzyme levels. The study proceeded in four stages: (1) identifying potential ACS predictors through a literature review, (2) validating these predictors with experts, (3) comparing data between ACS and non-ACS patients and (4) developing a screening scale based on identified predictors. Statistical methods included univariate analysis and binary logistic regression. The scale's accuracy was assessed using ROC curve analysis and compared to existing tools. Eight significant ACS predictors were identified: male sex, age over 49 for males and over 65 for females, typical symptoms, initial pain scale score of 6 or higher, pain duration of at least 10 min, history of ACS, hypertension, and dyslipidemia. Each predictor was scored, with typical symptoms and severe pain receiving higher scores, totaling up to 10 points. A score of 6 or more indicated high ACS risk, demonstrating accuracy comparable to the HEART and TIMI score systems. This study developed a new ACS screening scale for use by triage nurses in emergency departments. This scale can facilitate early detection and intervention for patients at high risk of ACS.

A Machine Learning Model for Predicting In-Hospital Mortality in Chinese Patients With ST-Segment Elevation Myocardial Infarction: Findings From the China Myocardial Infarction Registry.

Machine learning (ML) risk prediction models, although much more accurate than traditional statistical methods, are inconvenient to use in clinical practice due to their nontransparency and requirement of a large number of input variables. We aimed to develop a precise, explainable, and flexible ML model to predict the risk of in-hospital mortality in patients with ST-segment elevation myocardial infarction (STEMI). This study recruited 18,744 patients enrolled in the 2013 China Acute Myocardial Infarction (CAMI) registry and 12,018 patients from the China Patient-Centered Evaluative Assessment of Cardiac Events (PEACE)-Retrospective Acute Myocardial Infarction Study. The Extreme Gradient Boosting (XGBoost) model was derived from 9616 patients in the CAMI registry (2014, 89 variables) with 5-fold cross-validation and validated on both the 9125 patients in the CAMI registry (89 variables) and the independent China PEACE cohort (10 variables). The Shapley Additive Explanations (SHAP) approach was employed to interpret the complex relationships embedded in the proposed model. In the XGBoost model for predicting all-cause in-hospital mortality, the variables with the top 8 most important scores were age, left ventricular ejection fraction, Killip class, heart rate, creatinine, blood glucose, white blood cell count, and use of angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin II receptor blockers (ARBs). The area under the curve (AUC) on the CAMI validation set was 0.896 (95% CI 0.884-0.909), significantly higher than the previous models. The AUC for the Global Registry of Acute Coronary Events (GRACE) model was 0.809 (95% CI 0.790-0.828), and for the TIMI model, it was 0.782 (95% CI 0.763-0.800). Despite the China PEACE validation set only having 10 available variables, the AUC reached 0.840 (0.829-0.852), showing a substantial improvement to the GRACE (0.762, 95% CI 0.748-0.776) and TIMI (0.789, 95% CI 0.776-0.803) scores. Several novel and nonlinear relationships were discovered between patients' characteristics and in-hospital mortality, including a U-shape pattern of high-density lipoprotein cholesterol (HDL-C). The proposed ML risk prediction model was highly accurate in predicting in-hospital mortality. Its flexible and explainable characteristics make the model convenient to use in clinical practice and could help guide patient management. ClinicalTrials.gov NCT01874691; https://clinicaltrials.gov/study/NCT01874691.

Plasma levels of bactericidal/permeability-increasing protein correlate with systemic inflammation in acute coronary syndrome

BackgroundNeutrophils play important roles in atherosclerosis and atherothrombosis. Bactericidal/permeability-increasing protein (BPI) is mainly expressed in the granules of human neutrophils in response to inflammatory stress. This observational, cross-sectional study investigated the plasma level of BPI in patients with acute coronary syndrome (ACS) and its correlation with blood neutrophil counts and circulating inflammatory biomarkers. MethodsA total of 367 patients who had acute chest pain and who were admitted to our hospital for coronary angiography (CAG) and/or percutaneous coronary intervention (PCI) from May 1, 2020 to August 31, 2020 were recruited. Among them, 256 had a cardiac troponin value above the 99th percentile upper reference limit and were diagnosed with ACS. The remaining patients (n = 111) were classified as non-ACS. The TIMI and GRACE scores were calculated at admission. The Gensini score based on CAG was used to determine atherosclerotic burden. Plasma levels of interleukin (IL)-1β, myeloperoxidase-DNA (MPO-DNA), high sensitivity C-reactive protein (hs-CRP), S100A8/A9, and BPI were measured using enzyme-linked immunosorbent assays. Correlations of plasma BPI levels with examination scores and levels of circulating inflammatory biomarkers were explored. Receiver operating characteristic (ROC) curve analysis was used to determine the diagnostic efficacy of BPI for ACS and myocardial infarction. ResultsPatients in the ACS group showed significantly higher plasma BPI levels compared to the non-ACS group (46.42 ± 16.61 vs. 16.23 ± 6.19 ng/mL, p < 0.05). Plasma levels of IL-1β, MPO-DNA, hs-CRP, and S100A8/A9 in the ACS group were also significantly higher than those in the non-ACS group (all p < 0.05). In addition, plasma BPI levels were positively correlated with the TIMI, GRACE, and Gensini scores (r = 0.176, p = 0.003; r = 0.320, p < 0.001; r = 0.263, p < 0.001, respectively) in patients with ACS. Plasma BPI levels were also positively correlated with blood neutrophil counts (r = 0.266, p < 0.001) and levels of circulating inflammatory biomarkers (IL-1β, r = 0.512; MPO-DNA, r = 0.452; hs-CRP, r = 0.554; S100A8/A9, r = 0.434; all p < 0.001) in patients with ACS. ROC curve analysis revealed that the diagnostic efficacy of BPI for ACS was not inferior to that of IL-1β, MPO-DNA, hs-CRP, S100A8/A9, or blood neutrophil counts. ROC analysis also showed that the diagnostic efficacy of BPI for myocardial infarction was not inferior to that of creatine kinase (CK)-MB or cardiac troponin I. ConclusionBPI is associated with systemic inflammation in ACS and may be involved in the process of atherosclerosis and atherothrombosis. The potential of BPI as a prognostic and diagnostic biomarker for ACS should be investigated in clinical settings.

THE ENIGMA OF THE ‘SMOKER‘S PARADOX‘ : RESULTS FROM A SINGLE–CENTER REGISTRY OF PATIENTS WITH STEMI UNDERGOING PRIMARY PERCUTANEOUS CORONARY INTERVENTION

Abstract Background Smoker’s paradox usually refers to the common observation of a favourable outcome of smoker patients in acute myocardial infarction. The interpretation of this phenomenon is still controversial and not fully explained. We aimed at assessing whether smoking could be associated with mortality in a large cohort of prospectively enrolled patients with ST segment elevation myocardial infarction (STEMI) referred to primary percutaneous coronary intervention (PCI). Methods From April 2006 to December 2018 a population of 2456 STEMI patients treated with primary PCI were prospectively enrolled in the MATRIX registry. Ischemic time, clinical, demographics, angiographic data and 1–year follow–up were collected. Results Among 2546 patients admitted with STEMI 1007 (41%) were current smokers. Smokers were 10 years younger and had lower crude in–hospital and 1–year mortality (1.5% vs 6%, p&amp;lt;0.0001 and 5% vs 11%, p&amp;lt;0.0001), shorter ischemic time (203 [147–299] vs 220 [154–334] minutes, p=0.002) and shorter decision time (60 [30–135] vs 70 [36–170] minutes, p=0.0063). After propensity–matching, age, cardiogenic shock and low TIMI score were associated with in–hospital mortality, while smoking habit was still associated with reduced mortality. Smoking was also associated with reduced death rate at 1–year follow–up (HR 0.54, 95% CI [0.37 – 0.78]; p&amp;lt;0.001). Conclusions Our data show a protective link between smoking status and mortality in patients with STEMI, the so called “smoker’s paradox”. This could be explained not only by the shorter ischemic time and younger age of the smoking population but also by a specific pathogenetic effect of smoking underlying the onset of STEMI and response to therapies.

The Relationship Between CHA2DS2-VASc Scores and The Degree of TIMI Flow in Patients with Acute ST-Segment Elevation Myocardial Infarction Who Underwent Primary Percutaneous Coronary Intervention at Dr. Saiful Anwar Malang

Background: Suboptimal reperfusion of the compromised myocardium in the area of the culprit coronary arteries is one of the main problems associated with primary PCI that need reliable risk stratification methods to accurately predict the occurrence of decreased TIMI flow given its complex pathophysiology. Some parameters are included CHA2DS2-VASc score. Objective: To understand the relationship between CHA2DS2-VASc and the decreased TIMI flow in STE-ACS patients who had underwent primary PCI at RSUD dr. Saiful Anwar Malang. Material and Methods: The study was cohort retrospective with the inclusion criteria being all STE-ACS patients who underwent primary PCI in RSUD Dr. Saiful Anwar Malang from January 2018 – August 2023. Patients were assigned to TIMI flow grade &lt;3 group (N =169) and TIMI flow grade 3 (N = 677) according to TIMI Flow degree after primary PCI. All the patient’s angiogram were evaluated for TIMI score and CHA2DS2-VASc score is based on a guideline. We concluded data in SPSS program and used the Spearman test and p value of .05 was considered as significant. Result: From a total sample of 846 patients, the correlation between STE-ACS onset and TIMI flow indicates that a higher number of patients with STE-ACS onset &lt;12 hours was found in the TIMI flow &lt;3 and 3 groups (p=0.000). The cutoff CHA2DS2 VASC score's sensitivity and specificity values were ascertained using ROC analysis with cut off value 2.5. The incidence of decreased TIMI flow rate was more significant in the CHA2DS2-VASc ≥3 group with DM (+) and age ≥64 (OR value 0.156, p=0.000) than in the CHA2DS2-VASc ≥3 group without DM and age &lt; 64. With an OR value of 2.94 (p=0.000), Killip class &gt; 2 is another powerful predictor of lower TIMI flow. Conclusion: The only variables in the CHA2DS2-VASc score component that are most strongly associated with the risk of reducing the degree of TIMI flow are DM, age, and Killip class. Keyword: Acute Coronary Syndrome, CHA2DS2-VASc Score, Intervention, Percutaneous Coronary Slow Flow- No Reflow Phenomena, TIMI Flow Degree.

ChatGPT provides inconsistent risk-stratification of patients with atraumatic chest pain.

ChatGPT-4 is a large language model with promising healthcare applications. However, its ability to analyze complex clinical data and provide consistent results is poorly known. Compared to validated tools, this study evaluated ChatGPT-4's risk stratification of simulated patients with acute nontraumatic chest pain. Three datasets of simulated case studies were created: one based on the TIMI score variables, another on HEART score variables, and a third comprising 44 randomized variables related to non-traumatic chest pain presentations. ChatGPT-4 independently scored each dataset five times. Its risk scores were compared to calculated TIMI and HEART scores. A model trained on 44 clinical variables was evaluated for consistency. ChatGPT-4 showed a high correlation with TIMI and HEART scores (r = 0.898 and 0.928, respectively), but the distribution of individual risk assessments was broad. ChatGPT-4 gave a different risk 45-48% of the time for a fixed TIMI or HEART score. On the 44-variable model, a majority of the five ChatGPT-4 models agreed on a diagnosis category only 56% of the time, and risk scores were poorly correlated (r = 0.605). While ChatGPT-4 correlates closely with established risk stratification tools regarding mean scores, its inconsistency when presented with identical patient data on separate occasions raises concerns about its reliability. The findings suggest that while large language models like ChatGPT-4 hold promise for healthcare applications, further refinement and customization are necessary, particularly in the clinical risk assessment of atraumatic chest pain patients.

TIMI score as a predictor of severity of coronary artery disease in patients with STEMI.

Objective: To investigate the TIMI (Thrombolysis in Myocardial Infarction) score as a predictive tool for assessing the severity of coronary artery disease in patients presenting with ST-segment elevation myocardial infarction (STEMI). Study Design: Prospective, Observational Cohort study. Setting: Hayatabad Medical Complex Peshawar. Period: January 2021 to June 2022. Material &amp; Methods: Consecutive patients presenting with STEMI to the emergency department of the participating hospital was considered for inclusion. Inclusion criteria were including patients aged 21 years or older, with symptoms consistent with STEMI and ST-segment elevation of at least 1 mm in two or more contiguous leads on the electrocardiogram (ECG). Patients with a known history of coronary artery disease or previous myocardial infarction were excluded from the study. Results: The age of the patients ranged widely, with a mean±SD age of 60.18±15.38 years. Gender distribution showed a predominance of males, constituting 67.79% of the sample, while females accounted for 32.20%. In terms of comorbidities, 22.03% of patients were obese, 52.54% had diabetes mellitus, 18.64% had hypertension, 25.42% had hyperlipidemia, 11.86% had a family history of myocardial infarction, and 47.45% were smokers. Moderate risk group shows a lower incidence at 71.11%, and the High risk group has the lowest incidence at 50%. The p-value for this comparison is highly significant at 0.0001, indicating that there is a substantial difference in the occurrence of LV dysfunction among these risk groups. Conclusion: Our study demonstrates a strong association between TIMI risk groups and the occurrence of post-myocardial infarction complications, including LV dysfunction, arrhythmias, cardiogenic shock, and death.

Factors in Predicting Short Term Mortality in ST Elevation Myocardial Infarction Patients Undergoing Primary Percutaneous Coronary Intervention

Background: Percutaneous coronary angiography and intervention have been applied in the diagnosis and treatment of coronary artery disease at Gia Dinh People's Hospital since April 2009 until now with very positive results, contributing to improving the quality of diagnosis and treatment. Treating cardiovascular patients with high technology. However, there is currently no research to help evaluate performance as well as prognostic factors affecting treatment outcomes at this unit. Therefore, we conducted this study with the research question: Short-term mortality rate in patients with ST-elevation acute myocardial infarction undergoing primary percutaneous coronary intervention at Gia Dinh People's Hospital. What is the year 2022 - 2023? What factors predict short-term mortality in patients with acute ST-segment elevation myocardial infarction undergoing primary percutaneous coronary intervention. Materials and methods: There were 163 patients at the Gia Dinh People's Hospital from November 2022 to September, 2023. This was a cohort study. Results: In-hospital and 30-day mortality rates after intervention were 4.29% and 4.91%, respectively. Short-term mortality prognostic factors include systolic blood pressure &lt; 100 mmHg, arrhythmia at admission, TIMI score &gt; 6, cardiogenic shock before the procedure, blood potassium concentration with mortality rate within 30 days after PCI, with p &lt; 0.05. Conclusion: In clinical practice, attention should be paid to factors predicting 30-day mortality in STEMI patients include systolic blood pressure &lt; 100 mmHg, arrhythmia at admission, TIMI score &gt; 6, cardiogenic shock before the procedure, blood potassium concentration with mortality rate within 30 days after PCI.

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

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. 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. 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. 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. 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.

The assessment of no-reflow phenomenon incidence in early versus delayed percutaneous coronary intervention following a primary fibrinolysis.

Percutaneous coronary intervention (PCI) is the gold standard approach to ST-Segment Elevation Myocardial Infarction (STEMI). Fibrinolysis followed by PCI has been recommended. The current study aims to investigate the no-reflow phenomenon incidence in patients undergoing post-thrombolytic therapy PCI. This cross-sectional study was conducted on 250 patients with STEMI who primarily received fibrinolytic therapy followed by early (3-24 hours) (n=231) or delayed (> 24 hours) (n=19) PCI. They were also subcategorized into four intervals: <6 hours (n=98), 6-12 hours (n=93), 12-24 hours (n=38), and ≥24 hours (n=21). The demographic and medical data of the patients were retrieved. The Thrombolysis in Myocardial Infarction score (TIMI) was assessed at baseline and at the end of PCI. A TIMI score other than 3 was defined as no-reflow. The incidence of the no-reflow phenomenon was not associated with any of the underlying demographic and medical characteristics of the patients (P-value>0.05). Despite the significantly higher rate of improvement in TIMI grading among those undergoing early PCI (P-value=0.04), as well as within less than 6 hours after thrombolytic therapy (P-value=0.031), the rate of the no-reflow phenomenon did not differ between the groups, neither by sorting them as early versus delayed (P-value=0.518) nor by categorizing them into four intervals (P-value=0.367). Based on the findings of the current study, early PCI after fibrinolysis led to significantly improved TIMI flow. However, the incidence of no-reflow did not differ between the groups with early versus delayed post-fibrinolysis PCI.

Avaliação Crítica do Manejo da Angina Instável em Pronto-Socorro Terciário de Cardiologia

Abstract Background: The management of unstable angina (UA) presents a challenge due to its subjective diagnosis and limited representation in randomized clinical trials that inform current practices. Objectives: This study aims to identify key factors associated with the indication for invasive versus non-invasive stratification in this population and to evaluate factors associated with stratification test results. Methods: This retrospective cohort study included patients hospitalized with UA over a consecutive 20-month period. To assess factors associated with stratification strategies, patients were divided into invasive stratification (coronary angiography) and non-invasive stratification (other methods) groups. For the analysis of factors related to changes in stratification tests, patients were categorized into groups with or without obstructive coronary artery disease (CAD) or ischemia, as per the results of the requested tests. Comparisons between groups and multiple logistic regression analyses were performed, with statistical significance set at a 5% level. Results: A total of 729 patients were included, with a median age of 63 years and a predominance of males (64.6%). Factors associated with invasive stratification included smoking (p = 0.001); type of chest pain (p &lt; 0.001); "crescendo" pain (p = 0.006); TIMI score (p = 0.006); HEART score (p = 0.011). In multivariate analysis, current smokers (OR 2.23, 95% CI 1.13-4.8), former smokers (OR 2.19, 95% CI 1.39-3.53), and type A chest pain (OR 3.39, 95% CI 1.93-6.66) were independently associated. Factors associated with obstructive CAD or ischemia included length of hospital stay (p &lt; 0.001); male gender (p = 0.032); effort-induced pain (p = 0.037); Diamond-Forrester score (p = 0.026); TIMI score (p = 0.001). In multivariate analysis, only chest pain (type B chest pain: OR 0.6, 95% CI 0.38-0.93, p = 0.026) and previous CAD (OR 1.42, 95% CI 1.01-2.0, p = 0.048) were independently associated. Conclusion: The type of chest pain plays a crucial role not only in the diagnosis of UA but also in determining the appropriate treatment. Our results highlight the importance of incorporating pain characteristics into prognostic scores endorsed by guidelines to optimize UA management.

Critical Assessment of the Management of Unstable Angina in a Specialized Cardiology Emergency Room.

The management of unstable angina (UA) presents a challenge due to its subjective diagnosis and limited representation in randomized clinical trials that inform current practices. This study aims to identify key factors associated with the indication for invasive versus non-invasive stratification in this population and to evaluate factors associated with stratification test results. This retrospective cohort study included patients hospitalized with UA over a consecutive 20-month period. To assess factors associated with stratification strategies, patients were divided into invasive stratification (coronary angiography) and non-invasive stratification (other methods) groups. For the analysis of factors related to changes in stratification tests, patients were categorized into groups with or without obstructive coronary artery disease (CAD) or ischemia, as per the results of the requested tests. Comparisons between groups and multiple logistic regression analyses were performed, with statistical significance set at a 5% level. A total of 729 patients were included, with a median age of 63 years and a predominance of males (64.6%). Factors associated with invasive stratification included smoking (p = 0.001); type of chest pain (p < 0.001); "crescendo" pain (p = 0.006); TIMI score (p = 0.006); HEART score (p = 0.011). In multivariate analysis, current smokers (OR 2.23, 95% CI 1.13-4.8), former smokers (OR 2.19, 95% CI 1.39-3.53), and type A chest pain (OR 3.39, 95% CI 1.93-6.66) were independently associated. Factors associated with obstructive CAD or ischemia included length of hospital stay (p < 0.001); male gender (p = 0.032); effort-induced pain (p = 0.037); Diamond-Forrester score (p = 0.026); TIMI score (p = 0.001). In multivariate analysis, only chest pain (type B chest pain: OR 0.6, 95% CI 0.38-0.93, p = 0.026) and previous CAD (OR 1.42, 95% CI 1.01-2.0, p = 0.048) were independently associated. The type of chest pain plays a crucial role not only in the diagnosis of UA but also in determining the appropriate treatment. Our results highlight the importance of incorporating pain characteristics into prognostic scores endorsed by guidelines to optimize UA management.

Comparison of grace, timi risk scores for prediction of major adverse cardiac events in patients with acute myocardial infarction, Vietnam

Acute myocardial infarction (MI) is one of the leading causes of cardiovascular death and can experience many events during illness. Therefore, many risk prediction scales have been established to stratify patients with acute MI, in which TIMI and GRACE scores are common. We conducted this study to compare the predictability of GRACE and TIMI scores in patients with acute MI within 12 months. A prospective cohort study was performed on 195 patients with acute MI, of which 86 patients had ST elevation (STEMI) and 109 patients without ST elevation (NSTEMI). The study looked at five major events including death, coronary re-intervention, bleeding due to drug use, re-hospitalization, and stroke. As a result, the heart rate in the STEMI group was 83.06 ± 14.78, higher than the heart rate of the NSTEMI group at admission (78.59 ± 10.63), the difference was significant with p = 0.015. The study has not shown the predictive effect of GRACE and TIMI scores on the occurrence of events in patients with acute MI within 12 months. However, the study showed that GRACE can better ability to stratify the risk for the group of subjects that had not yet occurred.

Association of CHADVASC Score in Predicting In-Hospital Mortality in Patients with ST-Segment Elevation Myocardial Infarction Undergoing Primary PCI

Objective: To assess CHADVASC score in predicting in-hospital mortality in patients presenting to the hospital with ST segment Elevation Myocardial Infarction undergoing primary PCI. Study Design: Analytical Cross-sectional study. Place and Duration of Study: Armed Forces Institute of Cardiology/National Institute of Heart Diseases, Rawalpindi,Pakistan, from Mar 2023 to Apr 2023. Methodology: A total of 198 patients were enrolled. Their CHADVASC scores were recorded and were divided into Group-A (score of 0-1), B (score 2-3) and C (score 4 and above). Sampling was done by using non-probability consecutive sampling. A brief clinical history including duration of symptoms, comorbid, duration of hospital stay and survivability status were recorded. Chi-square and Independent sample t-test were applied to find the association between In-hospital mortality and CHADVASC score, duration of hospital stay as well as comorbids. p-value &lt;0.05 was taken as significant Results: Among study participants, majority were males 133(67.2%). Mean age of patients was 60.86±9.02 years. In-hospital mortality was noted in 13(6.56%) patients. There was a significant association between CHADVASC score and mortality (p&lt;0.001). It was also noted that mortality increased with prolonged duration of stay in hospital (p=0.03). Another observation noted was that males presented at an earlier age (59.45±9.79 years) than females (63.63±6.54 years).Conclusion: CHADVASC score like the TIMI score and GRACE score can be used to stratify risk in patients presenting with Acute Coronary Syndrome (ACS). It is a fairly easy to use test at bed side and can help clinicians decide further treatment strategies and how .............

Clinical particulars of acute coronary syndrome course in patients with COVID-19

Background: Cardiovascular complications of COVID-19 result in challenges for differential diagnosis, patients referral and treatment, which negatively affect the outcomes.&#x0D; Aim: To identify clinical particulars of various types acute coronary syndrome course in patients with COVID-19.&#x0D; Materials and methods: This retrospective cross-sectional study included 202 patients with COVID-19 and acute coronary syndrome (ACS) admitted to a primary vascular medicine center from September to December 2020. Their medical records were used for the analysis of ACS and COVID-19 clinical course, including physical and history data, laboratory and instrumental work-up. For the analysis, the patient sampling was divided into three study groups: 50 patients with unstable angina (UA), 107 patients with acute myocardial infarction with ST segment elevation (STEMI), and 45 patients with acute myocardial infarction without ST segment elevation (non-STEMI).&#x0D; Results: There were no differences in clinical manifestations of ACS in the study groups. As far as clinical manifestations of coronavirus infections are concerned, the patients differed significantly as per prevalence of fever and dry cough. Fever was present in 22 (44%) UA patients, 18 (17%) of STEMI patients and in 10 (22%) of non-STEMI patients (p 0.001 for comparison of 3 groups, Kruskall-Wallis test), whereas dry cough was present in 18 (36%), 19 (18%), and 14 (31%) patients, respectively (p = 0.029). Paired comparison (Mann-Whitney test with Bonferroni adjustment) showed significant differences between US and STEMI groups for both symptoms. The number of involved vessels (median [25%; 75%]) in UA patients was 0 [0; 2], in STEMI and non-STEMI patients 2 [1; 3] (p 0.001). A left coronary artery stenosis was detected in 2 (6%) of the UA patients, 13 (14%) of the STEMI and 4 (13%) of the non-STEMI patients (p = 0.452); left anterior descending artery stenosis, in 12 (36%), 67 (72%) and 23 (72%) patients, respectively (p 0.001). In the pairwise comparison, there were differences between UA and STEMI groups and between UA and non-STEMI groups. A left circumflex artery stenosis was found in 7 (21%) of the UA patients, 45 (48%) of the STEMI and 18 (56%) of the non-STEMI patients (p = 0.008); the pairwise comparisons showed the difference between UA and non-STEMI study groups. A right coronary artery stenosis was identified in 9 (27%), 64 (69%) and 18 (56%) of the study patients, respectively (p 0.001); in the pairwise comparison the difference was found between the UA and STEMI group. There were significant differences in the percentage of the right descendent and right coronary artery stenosis: the right descending artery stenosis was 70% [45; 80] in the UA patients, 90% [70; 100] in the STEMI and 95% [70; 100] in the non-STEMI patients (p = 0.013), whereas the right coronary artery stenosis was 50% [45; 80], 90% [70; 100], 90% [60; 100], respectively (p = 0.018). In the pairwise comparison, the differences were found between the UA and STEMI patients in both arteries. The STEMI patients had higher TIMI thrombus grade scores than those with non-STEMI: 3 [0; 5] vs 0 [0; 4] (p = 0.023). The rates of successful percutaneous coronary intervention and achievement of TIMI flow grade 3 between them was not significantly different (p = 0.170).&#x0D; Conclusion: The ACS patients with ACS and COVID-19 have high thrombotic load according to coronary angiography and TIMI score in the case of STEMI and more frequent absence of hemodynamically significant stenosis in those with UA and non-STEMI. The absence of any difference in clinical manifestations of ACS and viral infection between the study groups (except fever and dry cough difference between the UA and STEMI patients) indicates that specific characteristics of the ACS course in COVID-19 patients can be identified only by coronaroangiography.

The incremental value of non-necrosis biomarkers to risk stratification in acute chest pain, with MI excluded: the first prospective long term cohort study in the high sensitive troponin era

Abstract Background Approximately 90% of patients presenting to ED (Emergency Department) with suspected Acute Coronary Syndrome (ACS) have Myocardial Infarction (MI) excluded. Long term outcome and risk stratification for this cohort has rarely been studied. Purpose To study long term cardiovascular outcomes in patients with acute Chest Pain (CP) in whom MI is excluded, and to investigate the incremental value of biomarkers of inflammation, myocardial ischaemia and stress, for risk stratification, to that of existing methods of stratifying risk including absolute values of two high sensitive troponins below the 99th percentile. Methods A prospective observational study in a large university teaching hospital with a median follow-up of 5.8-year. Cardiovascular outcomes studied included adjudicated type 1 MI (to 4th universal definition), unstable angina requiring urgent revascularisation and cardiovascular death. Inclusion criteria included CP with features of ischaemia but with MI excluded (High sensitive cardiac troponin [hs-cTn] T ≤99th percentile). Exclusion criteria included non-cardiac chest pain, chronic atrial fibrillation, heart failure and recent ACS. The biomarkers HFABP, GDF-15, NT-proBNP, Galectin-3, HS-CRP taken on first venepuncture for high sensitive cardiac troponins were investigated using univariable and multivariable backward stepwise elimination logistic modelling, receiver operator characteristic (ROC) analysis, and Net Reclassification Indices (NRI). They were compared to absolute values of both sub-99th percentile hs-cTnT (Roche Elecsys) and hs-cTnI (Abbot Architect) both as a single entity or when the troponin values were incorporated with HEART and TIMI scores. Results 487 consented patients were enrolled. The mean age of the population was 56 years (SD 11.8), 44% were female, 16.2% were diabetic, 20.9% had a previous MI, 13.8% previous PCI and 5.1% coronary artery bypass grafting. 100% follow-up was achieved. There were 48 events in follow-up. (event rate 9.9%). Multivariable Cox Proportional Hazards analysis including hs-cTnT or hs-cTnI (below 99th percentile) demonstrated incremental improvement in risk stratification with absolute values of either hs-cTn below the 99th percentile when added to either TIMI or HEART risk score. The results were consistent with NRI analysis. Only GDF-15 demonstrated significance in multivariable analysis when analysed with the HEART score regardless of troponin assay and the TIMI score with HS-cTnI but not with HS-cTnT. Conclusion Absolute values of hs-cTnT or I, below 99th percentiles, significantly improve risk modelling for cardiovascular outcomes in acute CP patients, presenting to ED, who have MI excluded. No other biomarker retains independent risk with the exception of GDF-15. Effective dichotomisation of sub99th percentile hstnT or I, used alone or incorporated into risk scores, could allow improved targeting of resources for investigation and management for this large pool of patients.

Predicting the risk of in-hospital Asian NSTEMI patients using stacked ensemble learning

Abstract Background NSTEMI affects 60–75% of patients with MI and has a variety of clinical manifestations and prognoses. Ensemble learning (EL) utilizes the machine learning (ML) models on a classification task to make more accurate predictions than any single ML model. It has also been demonstrated to be superior to conventional risk scores in predicting mortality risk. However, no studies on the application of EL to ASIAN NSTEMI patients have been published. Purpose To identify factors associated with Asian in-hospital NSTEMI patients using ML and to develop a stacking EL-based NSTEMI risk score that is specifically tailored to the Asian population. Methods From 2006 to 2016, 10464 data were collected from the Malaysian National Cardiovascular Disease Database (NCVD-ACS) registry on hospitalized multiethnic Asian patients admitted with NSTEMI. This study utilized 39 variables, including demographic, cardiovascular risk, medication, and clinical variables. For stacked EL model development, four algorithms, Support Vector Machine (SVM), Random Forest (RF), eXtreme Gradient Boosting (XGB), and Naive Bayes (NB), are used as base learners, and Generalized Linear Model (GLM) is used as the meta learner. Significant variables were chosen and ranked using ML variable importance with backward elimination. As a predictive performance metric, the area under the curve (AUC) was used. Using a validation dataset, algorithms were validated against the TIMI for NSTEMI, and the net reclassification index (NRI) was calculated. Results The stacked EL models developed using SVM feature selection (13 predictors, AUC = 0.823, CI: 0.779 - 0.867) outperforms the conventional risk score, TIMI (AUC = 0.563, CI: 0.515 - 0.610). RF contributes the most to the EL model predictions, followed by NB, XGB and SVM (Figure 1). Common predictors between SVM feature selection and TIMI are; age, hypertension and ECG-type depression. SVM feature selection also identified gender, MI history, chronic lung disease, heart rate, systolic blood pressure, Killip class, fasting blood glucose, LMWH, beta-blockers and angiotensin II receptor blocker as predictors that improve mortality prediction in ASIAN NSTEMI patients. Our findings indicate that the TIMI score underestimates the mortality risk of NSTEMI patients. Stacked EL model using selected predictors classified 47.4% of nonsurvivors as high risk (risk probabilities &amp;gt; 50%), whereas TIMI (score &amp;gt; 5) classified only 3.3% of nonsurvivors as high risk (Figure 2). The NRI of NSTEMI patients using the EL model (SVM selected var) resulted in an NRI of 79.8% with a p-value &amp;lt; 0.00001 when compared to the TIMI for NSTEMI risk score. Conclusions The stacked EL algorithm classifies ASIAN NSTEMI patients more accurately than the single ML model and TIMI score. A precise prognosis is useful for selecting the appropriate level of care and pharmacological or invasive treatment for patients with Asian NSTEMI.Relative influence of each ML modelsStacked EL performance on validation set

Severe angina increases the probability of Takotsubo syndrome diagnosis among MINOCA patients

Abstract Background/Introduction Myocardial infarction with non-obstructive coronary arteries (MINOCA) still consists an "enigmatic" and heterogenous clinical entity. Takotsubo syndrome (TTS) represents a significant proportion of such cases. Despite its predominance on female sex and its imaging characteristics of the "signature" apical form, it remains hardly distinguishable from MINOCA without the contribution of cardiac magnetic resonance (CMR). On the other hand, INTERTAK score is the only risk model to estimate the probability of TTS, whereas angina characteristics were not used in this model. Considering the guarded prognosis of MINOCA and TTS, an early risk stratification and differential diagnosis could improve therapeutic decisions and prognosis. Purpose The aim of our study was to investigate potential prognostic markers of early diagnosis and risk stratification among patients admitted with a working diagnosis of MINOCA. Methods In a multicenter prospective study, we enrolled 111 patients aged 38-85 years old who fulfilled the diagnostic criteria of MINOCA. All patients received treatment according to the latest guidelines and consensus documents and CMR was performed within 30 days of the acute event. Patients with findings of myocarditis were excluded (n=21) and the remaining population was divided into TTS (n=38) and non-TTS (n=52) groups according to clinical assessment and multimodality imaging results. Non-TTS group included MINOCA patients with ischemic pattern of late-gadolinium enhancement (LGE) and patients with clear CMR representing the "MINOCA of unknown etiology" group. The investigated potential prognostic markers were parameters derived of blood pressure and heart rate variability assessed by 24hr ECG and blood pressure monitoring, as well as clinical parameters used in the most common risk stratification tools used in the setting of ACS, such as TIMI and GRACE scores. Results In our population, female sex (94.7% vs 55.8%, p&amp;lt;0.001), older age (67 ± 10 vs 60 ±12, p=0.003) were more frequent in TTS group. Focusing on angina characteristics, "severe angina" expressed as 2 or more episodes of angina within 24 hours as included in the established TIMI score was significantly more frequent among the TTS compared to the non-TTS patients (54.1% vs 24%, p=0.007). Μultivariate analysis revealed that "severe angina" (OR, 0.153; CI 95%: 0.039 – 0.605, p=0.007) is predictive of TTS independently of age, ECG pattern, peak troponin and even after the inclusion of INTERTAK score in the model. Conclusions In our preliminary analysis, "severe angina" emerged as a potent and independent predictor of TTS diagnosis. Due to lack of availability of CMR, clinical tools as the INTERTAK score are useful in everyday practice. Based on our finding, inspired by the TIMI score, the presence of "severe angina" may strengthen the predictive value of the INTERTAK score when integrated with the latter.

Predictive values of age shock index and age modified shock index for in-hospital mortality in patients with ST-segment elevation myocardial infarction

Abstract Background and Purpose This study aimed to evaluate the predictive values of admission age shock index (age SI) and age modified shock index (age MSI) for short-term outcomes in patients with ST-segment elevation myocardial infarction (STEMI). Methods 7324 patients with STEMI were included in the present study. Shock index (SI), modified shock index (MSI), age SI, age MSI and the TIMI score were calculated on admission. The primary outcome was all-cause mortality and the secondary outcomes were recurrent MI, cardiogenic shock and major adverse cardiovascular events (MACEs) during 30-day follow-up. Univariate and multivariate Cox regression were performed to evaluate the association between age SI, age MSI and outcomes. Predictive values of SI, MSI, age SI, age MSI and the TIMI score were evaluated and compared through analysis of the receiver operating characteristic (ROC) curves and integrated discrimination improvement (IDI). Results According to the ROC curve, the best cutoff of age SI for 30-day all-cause mortality were 50.0. Patients with elevated age SI had more comorbidities, received less evidence-based treatments and carried worse 30-day mortality. Multivariate Cox regressions demonstrated that age SI and age MSI were independent predictors of 30-day all-cause mortality and MACEs. The predictive values of age MSI for 30-day mortality were comparable to that of the TIMI score (c statistic: 0.743 vs. 0.758, z=1.740, p=0.082; IDI: 0.011, p=0.055) and better than that of SI (c statistic: 0.743 vs. 0.660, z=14.317, p&amp;lt;0.001; IDI: 0.046, p&amp;lt;0.001). The prognostic performance of age MSI was slightly inferior to that of the TIMI score (c statistic: 0.741 vs. 0.758, z=2.060, p=0.039; IDI: -0.001, p=0.846). Conclusion Age SI and age MSI were independent predictors for 30-day all-cause mortality and MACEs in patients with STEMI. The predictive value of age SI was comparable with the TIMI score but better than SI. Age SI and age MSI are practical risk stratification tools for STEMI.Figure.Receiver operating characterisTable.Discrimination and Calibration