Hailei Liu MD , Thien Tan Tri Tai Truyen MD , Harpriya Chugh MSHS , Kyndaron Reinier PhD , Ashkan Ehdaie MD , Eugenio Cingolani MD , Archana Ramireddy MD , Eric D. Braunstein MD , Michael Shehata MD , Xunzhang Wang MD , Sumeet S. Chugh MD
{"title":"一种准确诊断既往下位心肌梗死的新型心电图方法","authors":"Hailei Liu MD , Thien Tan Tri Tai Truyen MD , Harpriya Chugh MSHS , Kyndaron Reinier PhD , Ashkan Ehdaie MD , Eugenio Cingolani MD , Archana Ramireddy MD , Eric D. Braunstein MD , Michael Shehata MD , Xunzhang Wang MD , Sumeet S. Chugh MD","doi":"10.1016/j.jacadv.2025.101968","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>The accuracy of diagnosing prior inferior wall myocardial infarction (IMI) on the 12-lead electrocardiogram (ECG) remains limited.</div></div><div><h3>Objectives</h3><div>The aim of the study was to use predictive model building to select the optimal ECG criteria specific to the diagnoses of true-IMI.</div></div><div><h3>Methods</h3><div>From an ongoing health system-based cohort study (n = 382,121), all consecutive subjects with ECG-based diagnoses of prior IMI (n = 9,676; 2019-2023) were assessed. Subjects with at least 1 cardiac imaging test performed were identified (n = 5,924). Discovery (2019-2022, n = 329) and validation (2023, n = 185) subgroups were identified by random sampling. Subjects with true- vs pseudo-IMI were identified from a combination of ECG and imaging. Logistic regression was used in the discovery cohort to identify ECG parameters associated with true-IMI, and optimal cutoff values were determined using the Youden Index.</div></div><div><h3>Results</h3><div>In the discovery sample, 209 subjects (63.5%) were identified as pseudo-IMI. A combination of lead II Q-wave duration >20 ms and/or amplitude ratio >0.2, derived from logistic regression and selected to optimize diagnostic performance while minimizing false negatives, improved sensitivity and specificity to 100.0% and 96.7%. The positive and negative predictive values were 94.5% and 100.0%, respectively. Findings were consistent in the validation cohort.</div></div><div><h3>Conclusions</h3><div>Using the prevailing definition for electrocardiographic diagnosis of prior IMI had a significantly high rate of pseudo-IMI. Refinement using simple ECG lead II criteria substantially improved the accuracy of the ECG-based diagnosis. These findings have potential implications for clinical practice and highlight the need for large, multicenter studies to further define the optimal criteria for the ECG diagnosis of structural heart disease.</div></div>","PeriodicalId":73527,"journal":{"name":"JACC advances","volume":"4 8","pages":"Article 101968"},"PeriodicalIF":0.0000,"publicationDate":"2025-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Novel Electrocardiographic Approach for Accurate Diagnosis of Prior Inferior Myocardial Infarction\",\"authors\":\"Hailei Liu MD , Thien Tan Tri Tai Truyen MD , Harpriya Chugh MSHS , Kyndaron Reinier PhD , Ashkan Ehdaie MD , Eugenio Cingolani MD , Archana Ramireddy MD , Eric D. Braunstein MD , Michael Shehata MD , Xunzhang Wang MD , Sumeet S. Chugh MD\",\"doi\":\"10.1016/j.jacadv.2025.101968\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>The accuracy of diagnosing prior inferior wall myocardial infarction (IMI) on the 12-lead electrocardiogram (ECG) remains limited.</div></div><div><h3>Objectives</h3><div>The aim of the study was to use predictive model building to select the optimal ECG criteria specific to the diagnoses of true-IMI.</div></div><div><h3>Methods</h3><div>From an ongoing health system-based cohort study (n = 382,121), all consecutive subjects with ECG-based diagnoses of prior IMI (n = 9,676; 2019-2023) were assessed. Subjects with at least 1 cardiac imaging test performed were identified (n = 5,924). Discovery (2019-2022, n = 329) and validation (2023, n = 185) subgroups were identified by random sampling. Subjects with true- vs pseudo-IMI were identified from a combination of ECG and imaging. Logistic regression was used in the discovery cohort to identify ECG parameters associated with true-IMI, and optimal cutoff values were determined using the Youden Index.</div></div><div><h3>Results</h3><div>In the discovery sample, 209 subjects (63.5%) were identified as pseudo-IMI. A combination of lead II Q-wave duration >20 ms and/or amplitude ratio >0.2, derived from logistic regression and selected to optimize diagnostic performance while minimizing false negatives, improved sensitivity and specificity to 100.0% and 96.7%. The positive and negative predictive values were 94.5% and 100.0%, respectively. Findings were consistent in the validation cohort.</div></div><div><h3>Conclusions</h3><div>Using the prevailing definition for electrocardiographic diagnosis of prior IMI had a significantly high rate of pseudo-IMI. Refinement using simple ECG lead II criteria substantially improved the accuracy of the ECG-based diagnosis. These findings have potential implications for clinical practice and highlight the need for large, multicenter studies to further define the optimal criteria for the ECG diagnosis of structural heart disease.</div></div>\",\"PeriodicalId\":73527,\"journal\":{\"name\":\"JACC advances\",\"volume\":\"4 8\",\"pages\":\"Article 101968\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-07-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JACC advances\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2772963X25003904\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JACC advances","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772963X25003904","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Novel Electrocardiographic Approach for Accurate Diagnosis of Prior Inferior Myocardial Infarction
Background
The accuracy of diagnosing prior inferior wall myocardial infarction (IMI) on the 12-lead electrocardiogram (ECG) remains limited.
Objectives
The aim of the study was to use predictive model building to select the optimal ECG criteria specific to the diagnoses of true-IMI.
Methods
From an ongoing health system-based cohort study (n = 382,121), all consecutive subjects with ECG-based diagnoses of prior IMI (n = 9,676; 2019-2023) were assessed. Subjects with at least 1 cardiac imaging test performed were identified (n = 5,924). Discovery (2019-2022, n = 329) and validation (2023, n = 185) subgroups were identified by random sampling. Subjects with true- vs pseudo-IMI were identified from a combination of ECG and imaging. Logistic regression was used in the discovery cohort to identify ECG parameters associated with true-IMI, and optimal cutoff values were determined using the Youden Index.
Results
In the discovery sample, 209 subjects (63.5%) were identified as pseudo-IMI. A combination of lead II Q-wave duration >20 ms and/or amplitude ratio >0.2, derived from logistic regression and selected to optimize diagnostic performance while minimizing false negatives, improved sensitivity and specificity to 100.0% and 96.7%. The positive and negative predictive values were 94.5% and 100.0%, respectively. Findings were consistent in the validation cohort.
Conclusions
Using the prevailing definition for electrocardiographic diagnosis of prior IMI had a significantly high rate of pseudo-IMI. Refinement using simple ECG lead II criteria substantially improved the accuracy of the ECG-based diagnosis. These findings have potential implications for clinical practice and highlight the need for large, multicenter studies to further define the optimal criteria for the ECG diagnosis of structural heart disease.