Poor evidence for poor R wave progression in coronary disease: A scoping review.

BACKGROUND: Poor R wave progression (PRWP) and reversed R wave progression (RRWP) have long been noted in electrocardiograms as potential indicators of anterior wall fibrosis or chronic coronary artery disease; however, the quantity and quality of evidence supporting these associations warrants closer examination. OBJECTIVE: The aim of this scoping review is to assess the breadth of evidence regarding the diagnostic significance of PRWP and RRWP, explore the extent of research, study populations and methodologies, and the presence of gaps in knowledge regarding these electrocardiographic phenomena and their association with coronary diseases. DESIGN: We conducted a comprehensive search across PubMed, Web of Science, and Scopus, covering literature on PRWP or RRWP in the context of myocardial infarction, ischemia, or fibrosis from any time period and in any language. RESULTS: A total of 20 studies were included in this review, highlighting the severe paucity of data. No high-quality accuracy studies have been identified, and existing research suffers from methodological issues, in particular selection bias. Prevalence and prognostic studies showed significant heterogeneity in terms of definitions and outcomes, which contributes to an alarming risk of bias. CONCLUSIONS: The lack of solid evidence for PRWP and RRWP as diagnostic markers for acute and chronic coronary artery disease necessitates caution in clinical interpretation. Future research should focus on well-designed case-control studies to clarify the diagnostic accuracy of these markers. Until robust evidence is available, the reliance on PRWP/RRWP for diagnosing anterior infarction should be discouraged, reflecting a gap between clinical practice and evidence-based medicine.

Poor evidence for poor R wave progression in coronary disease: a scoping review

BACKGROUND Poor R wave progression (PRWP) and reversed R wave progression (RRWP) have long been noted in electrocardiograms as potential indicators of anterior wall fibrosis or chronic coronary artery disease; however, the quantity and quality of evidence supporting these associations warrants closer examination. OBJECTIVE The aim of this scoping review is to assess the breadth of evidence regarding the diagnostic significance of PRWP and RRWP, explore the extent of research, study populations and methodologies, and the presence of gaps in knowledge regarding these electrocardiographic phenomena and their association with coronary diseases. DESIGN We conducted a comprehensive search across PubMed, Web of Science, and Scopus, covering literature on PRWP or RRWP in the context of myocardial infarction, ischemia, or fibrosis from any time period and in any language. RESULTS A total of 20 studies were included in this review, highlighting the severe paucity of data. No high-quality accuracy studies have been identified, and existing research suffers from methodological issues, in particular selection bias. Prevalence and prognostic studies showed significant heterogeneity in terms of definitions and outcomes, which contributes to an alarming risk of bias. CONCLUSIONS The lack of solid evidence for PRWP and RRWP as diagnostic markers for acute and chronic coronary artery disease necessitates caution in clinical interpretation. Future research should focus on well-designed case-control studies to clarify the diagnostic accuracy of these markers. Until robust evidence is available, the reliance on PRWP/RRWP for diagnosing anterior infarction should be discouraged, reflecting a gap between clinical practice and evidence-based medicine.

Systematic review and meta-analysis of diagnostic test accuracy of ST-segment elevation for acute coronary occlusion.

OBJECTIVE: To evaluate the diagnostic sensitivity and specificity of ST-segment elevation on a 12­lead ECG in detecting ACO across any coronary artery, challenging the current STEMI-NSTEMI paradigm. METHODS: Studies from MEDLINE and Scopus (2012-2023) comparing ECG findings with coronary angiograms were systematically reviewed and analyzed following PRISMA-DTA guidelines. QUADAS-2 assessed the risk of bias. STUDY SELECTION: Studies included focused on AMI patients and provided data enabling the construction of contingency tables for sensitivity and specificity calculation, excluding those with non-ACS conditions, outdated STEMI criteria, or a specific focus on bundle branch blocks or other complex diagnoses. Data were extracted systematically and pooled test accuracy estimates were computed using MetaDTA software, employing bivariate analyses for within- and between-study variation. The primary outcomes measured were the sensitivity and specificity of ST-segment elevation in detecting ACO. RESULTS: Three studies with 23,704 participants were included. The pooled sensitivity of ST-segment elevation for detecting ACO was 43.6% (95% CI: 34.7%-52.9%), indicating that over half of ACO cases may not exhibit ST-segment elevation. The specificity was 96.5% (95% CI: 91.2%-98.7%). Additional analysis using the OMI-NOMI strategy showed improved sensitivity (78.1%, 95% CI: 62.7%-88.3%) while maintaining similar specificity (94.4%, 95% CI: 88.6%-97.3%). CONCLUSION: The findings reveal a significant diagnostic gap in the current STEMI-NSTEMI paradigm, with over half of ACO cases potentially lacking ST-segment elevation. The OMI-NOMI strategy could offer an improved diagnostic approach. The high heterogeneity and limited number of studies necessitate cautious interpretation and further research in diverse settings.

Systematic review and meta-analysis of diagnostic test accuracy of ST-segment elevation for acute coronary occlusion

OBJECTIVE: To evaluate the diagnostic sensitivity and specificity of ST-segment elevation on a 12­lead ECG in detecting ACO across any coronary artery, challenging the current STEMI-NSTEMI paradigm. METHODS: Studies from MEDLINE and Scopus (2012-2023) comparing ECG findings with coronary angiograms were systematically reviewed and analyzed following PRISMA-DTA guidelines. QUADAS-2 assessed the risk of bias. STUDY SELECTION: Studies included focused on AMI patients and provided data enabling the construction of contingency tables for sensitivity and specificity calculation, excluding those with non-ACS conditions, outdated STEMI criteria, or a specific focus on bundle branch blocks or other complex diagnoses. Data were extracted systematically and pooled test accuracy estimates were computed using MetaDTA software, employing bivariate analyses for within- and between-study variation. The primary outcomes measured were the sensitivity and specificity of ST-segment elevation in detecting ACO. RESULTS: Three studies with 23,704 participants were included. The pooled sensitivity of ST-segment elevation for detecting ACO was 43.6% (95% CI: 34.7%-52.9%), indicating that over half of ACO cases may not exhibit ST-segment elevation criteria. The specificity was 96.5% (95% CI: 91.2%-98.7%). Additional analysis using the OMI-NOMI strategy showed improved sensitivity (78.1%, 95% CI: 62.7%-88.3%) while maintaining similar specificity (94.4%, 95% CI: 88.6%-97.3%). CONCLUSION: The findings reveal a significant diagnostic gap in the current STEMI-NSTEMI paradigm, with over half of ACO cases potentially lacking ST-segment elevation. The OMI-NOMI strategy could offer an improved diagnostic approach. The high heterogeneity and limited number of studies necessitate cautious interpretation and further research in diverse settings.

Leveraging advanced ai algorithms for predicting outcomes in non-acute coronary syndrome chest pain patients

INTRODUCTION: Chest pain is often encountered in emergency rooms and the detection of acute coronary syndrome (ACS) is a major focus. However, a notable percentage of patients present with a diverse range of nonACS conditions. Accurately identifying the causes and outcomes of these cases can prevent unnecessary interventions, reduce healthcare costs, and optimize resource allocation. This study aims to explore how advanced AI algorithms can enhance risk assessment, refine classification, and predict outcomes in nonACS chest pain patients using conventional ECG analysis. METHODS: We studied 3458 nonACS patients referred to the Emergency Room at Instituto Dante Pazzanese de Cardiologia with chest pain. A total of 185 features, including sex, height, ECG diagnostic statements, and measures, were used. The predicted outcome was defined as hospitalization within 14 days and/or death (1 or 0). We employed the AutoGluon framework for feature engineering and early model selection. XGBoost, a tree-based model, was chosen as the architecture. Training and k-fold stratified cross-validation were performed using an oversampled balanced dataset, and evaluation metrics such as AUROC, specificity, and sensitivity were measured using the original data. RESULTS: In this study, 18.2% (630 patients) had a positive outcome. The sex distribution was comparable between outcome groups, with men accounting for 57-58% and women for 42-43%. Significant differences (p<0.01) were observed in ECG intervals (QRS, corrected QT, RR interval, PSP) between the groups. The AI model identified important diagnostic statements, including normal ECG (19.4), atrial fibrillation (7.4), left ventricular hypertrophy (7.1), Ischemic T-wave inversion in inferior leads (6.7), T-wave changes in inferior leads (5.9), and first-degree atrioventricular block (5.8). The AI model performed exceptionally well, with a sensitivity of 97.93%, specificity of 96.08%, and an AUROC of 0.97. CONCLUSIONS: The AI model demonstrated its ability to predict outcomes in patients with acute chest pain without ACS, making it an appealing tool for effective risk stratification. The early identification provided by the AI model presents an opportunity for timely intervention to mitigate adverse outcomes.

Right Bundle-Branch Block Pattern in Precordial Leads and Left Bundle-Branch Block Pattern With Left Axis Deviation in Frontal Plane Leads-What Does This Mean?

This case report describes a patient in their 70s who presented to the emergency department with a history of syncope that occurred 7 days before admission.