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Kashou AH, LoCoco S, Gardner MR, Webb J, Jentzer JC, Noseworthy PA, DeSimone CV, Deshmukh AJ, Asirvatham SJ, May AM. Mayo Clinic VT calculator: A practical tool for accurate wide complex tachycardia differentiation. Ann Noninvasive Electrocardiol 2023; 28:e13085. [PMID: 37670480 PMCID: PMC10646384 DOI: 10.1111/anec.13085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 07/25/2023] [Accepted: 08/14/2023] [Indexed: 09/07/2023] Open
Abstract
The discrimination of ventricular tachycardia (VT) versus supraventricular wide complex tachycardia (SWCT) via 12-lead electrocardiogram (ECG) is crucial for achieving appropriate, high-quality, and cost-effective care in patients presenting with wide QRS complex tachycardia (WCT). Decades of rigorous research have brought forth an expanding arsenal of applicable manual algorithm methods for differentiating WCTs. However, these algorithms are limited by their heavy reliance on the ECG interpreter for their proper execution. Herein, we introduce the Mayo Clinic ventricular tachycardia calculator (MC-VTcalc) as a novel generalizable, accurate, and easy-to-use means to estimate VT probability independent of ECG interpreter competency. The MC-VTcalc, through the use of web-based and mobile device platforms, only requires the entry of computerized measurements (i.e., QRS duration, QRS axis, and T-wave axis) that are routinely displayed on standard 12-lead ECG recordings.
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Affiliation(s)
- Anthony H. Kashou
- Department of Cardiovascular MedicineMayo ClinicRochesterMinnesotaUSA
| | - Sarah LoCoco
- Department of MedicineWashington University School of MedicineSt. LouisMissouriUSA
| | | | - Jocelyn Webb
- Mayo Clinic Center for Digital HealthMayo ClinicRochesterMinnesotaUSA
| | - Jacob C. Jentzer
- Department of Cardiovascular MedicineMayo ClinicRochesterMinnesotaUSA
| | | | | | | | | | - Adam M. May
- Cardiovascular DivisionWashington University School of MedicineSt. LouisMissouriUSA
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Kashou AH, LoCoco S, Shaikh PA, Katbamna BB, Sehrawat O, Cooper DH, Sodhi SS, Cuculich PS, Gleva MJ, Deych E, Zhou R, Liu L, Deshmukh AJ, Asirvatham SJ, Noseworthy PA, DeSimone CV, May AM. Computerized electrocardiogram data transformation enables effective algorithmic differentiation of wide QRS complex tachycardias. Ann Noninvasive Electrocardiol 2022; 28:e13018. [PMID: 36409204 PMCID: PMC9833371 DOI: 10.1111/anec.13018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Revised: 10/16/2022] [Accepted: 10/19/2022] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Accurate automated wide QRS complex tachycardia (WCT) differentiation into ventricular tachycardia (VT) and supraventricular wide complex tachycardia (SWCT) can be accomplished using calculations derived from computerized electrocardiogram (ECG) data of paired WCT and baseline ECGs. OBJECTIVE Develop and trial novel WCT differentiation approaches for patients with and without a corresponding baseline ECG. METHODS We developed and trialed WCT differentiation models comprised of novel and previously described parameters derived from WCT and baseline ECG data. In Part 1, a derivation cohort was used to evaluate five different classification models: logistic regression (LR), artificial neural network (ANN), Random Forests [RF], support vector machine (SVM), and ensemble learning (EL). In Part 2, a separate validation cohort was used to prospectively evaluate the performance of two LR models using parameters generated from the WCT ECG alone (Solo Model) and paired WCT and baseline ECGs (Paired Model). RESULTS Of the 421 patients of the derivation cohort (Part 1), a favorable area under the receiver operating characteristic curve (AUC) by all modeling subtypes: LR (0.96), ANN (0.96), RF (0.96), SVM (0.96), and EL (0.97). Of the 235 patients of the validation cohort (Part 2), the Solo Model and Paired Model achieved a favorable AUC for 103 patients with (Solo Model 0.87; Paired Model 0.95) and 132 patients without (Solo Model 0.84; Paired Model 0.95) a corroborating electrophysiology procedure or intracardiac device recording. CONCLUSION Accurate WCT differentiation may be accomplished using computerized data of (i) the WCT ECG alone and (ii) paired WCT and baseline ECGs.
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Affiliation(s)
- Anthony H. Kashou
- Department of Cardiovascular MedicineMayo ClinicMinnesotaRochesterUSA
| | - Sarah LoCoco
- Department of MedicineWashington University School of MedicineMissouriSt. LouisUSA
| | - Preet A. Shaikh
- Department of Medicine, Division of Cardiovascular DiseasesWashington University School of MedicineMissouriSt. LouisUSA
| | - Bhavesh B. Katbamna
- Department of MedicineWashington University School of MedicineMissouriSt. LouisUSA
| | - Ojasav Sehrawat
- Department of Cardiovascular MedicineMayo ClinicMinnesotaRochesterUSA
| | - Daniel H. Cooper
- Department of Medicine, Division of Cardiovascular DiseasesWashington University School of MedicineMissouriSt. LouisUSA
| | - Sandeep S. Sodhi
- Department of Medicine, Division of Cardiovascular DiseasesWashington University School of MedicineMissouriSt. LouisUSA
| | - Phillip S. Cuculich
- Department of Medicine, Division of Cardiovascular DiseasesWashington University School of MedicineMissouriSt. LouisUSA
| | - Marye J. Gleva
- Department of Medicine, Division of Cardiovascular DiseasesWashington University School of MedicineMissouriSt. LouisUSA
| | - Elena Deych
- Division of BiostatisticsWashington University School of MedicineMissouriSt. LouisUSA
| | - Ruiwen Zhou
- Division of BiostatisticsWashington University School of MedicineMissouriSt. LouisUSA
| | - Lei Liu
- Division of BiostatisticsWashington University School of MedicineMissouriSt. LouisUSA
| | | | | | | | | | - Adam M. May
- Department of Medicine, Division of Cardiovascular DiseasesWashington University School of MedicineMissouriSt. LouisUSA
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Kashou AH, LoCoco S, McGill TD, Evenson CM, Deshmukh AJ, Hodge DO, Cooper DH, Sodhi SS, Cuculich PS, Asirvatham SJ, Noseworthy PA, DeSimone CV, May AM. Automatic wide complex tachycardia differentiation using mathematically synthesized vectorcardiogram signals. Ann Noninvasive Electrocardiol 2021; 27:e12890. [PMID: 34562325 PMCID: PMC8739609 DOI: 10.1111/anec.12890] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 08/21/2021] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND Automated wide complex tachycardia (WCT) differentiation into ventricular tachycardia (VT) and supraventricular wide complex tachycardia (SWCT) may be accomplished using novel calculations that quantify the extent of mean electrical vector changes between the WCT and baseline electrocardiogram (ECG). At present, it is unknown whether quantifying mean electrical vector changes within three orthogonal vectorcardiogram (VCG) leads (X, Y, and Z leads) can improve automated VT and SWCT classification. METHODS A derivation cohort of paired WCT and baseline ECGs was used to derive five logistic regression models: (i) one novel WCT differentiation model (i.e., VCG Model), (ii) three previously developed WCT differentiation models (i.e., WCT Formula, VT Prediction Model, and WCT Formula II), and (iii) one "all-inclusive" model (i.e., Hybrid Model). A separate validation cohort of paired WCT and baseline ECGs was used to trial and compare each model's performance. RESULTS The VCG Model, composed of WCT QRS duration, baseline QRS duration, absolute change in QRS duration, X-lead QRS amplitude change, Y-lead QRS amplitude change, and Z-lead QRS amplitude change, demonstrated effective WCT differentiation (area under the curve [AUC] 0.94) for the derivation cohort. For the validation cohort, the diagnostic performance of the VCG Model (AUC 0.94) was similar to that achieved by the WCT Formula (AUC 0.95), VT Prediction Model (AUC 0.91), WCT Formula II (AUC 0.94), and Hybrid Model (AUC 0.95). CONCLUSION Custom calculations derived from mathematically synthesized VCG signals may be used to formulate an effective means to differentiate WCTs automatically.
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Affiliation(s)
| | - Sarah LoCoco
- Division of Cardiovascular Diseases, Department of Medicine, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA
| | - Trevon D McGill
- Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Christopher M Evenson
- Division of Cardiovascular Diseases, Department of Medicine, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA
| | - Abhishek J Deshmukh
- Division of Cardiovascular Diseases, Department of Medicine, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA
| | - David O Hodge
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Daniel H Cooper
- Division of Cardiovascular Diseases, Department of Medicine, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA
| | - Sandeep S Sodhi
- Division of Cardiovascular Diseases, Department of Medicine, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA
| | - Phillip S Cuculich
- Division of Cardiovascular Diseases, Department of Medicine, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA
| | - Samuel J Asirvatham
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester, Minnesota, USA
| | - Peter A Noseworthy
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester, Minnesota, USA
| | | | - Adam M May
- Division of Cardiovascular Diseases, Department of Medicine, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA
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Kashou AH, Evenson CM, Noseworthy PA, Muralidharan TR, DeSimone CV, Deshmukh AJ, Asirvatham SJ, May AM. Differentiating wide complex tachycardias: A historical perspective. Indian Heart J 2020; 73:7-13. [PMID: 33714412 PMCID: PMC7961210 DOI: 10.1016/j.ihj.2020.09.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Revised: 09/03/2020] [Accepted: 09/10/2020] [Indexed: 11/02/2022] Open
Abstract
One of the most critical and challenging skills is the distinction of wide complex tachycardias into ventricular tachycardia or supraventricular wide complex tachycardia. Prompt and accurate differentiation of wide complex tachycardias naturally influences short- and long-term management decisions and may directly affect patient outcomes. Currently, there are many useful electrocardiographic criteria and algorithms designed to distinguish ventricular tachycardia and supraventricular wide complex tachycardia accurately; however, no single approach guarantees diagnostic certainty. In this review, we offer an in-depth analysis of available methods to differentiate wide complex tachycardias by retrospectively examining its rich literature base - one that spans several decades.
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Affiliation(s)
| | - Christopher M Evenson
- Cardiovascular Division, Washington University School of Medicine, St. Louis, MO, USA
| | | | - Thoddi R Muralidharan
- Department of Cardiology, Sri Ramachandra Medical Centre, Porur Chennai, Tamil Nadu, India
| | | | | | | | - Adam M May
- Cardiovascular Division, Washington University School of Medicine, St. Louis, MO, USA
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Kashou AH, DeSimone CV, Deshmukh AJ, McGill TD, Hodge DO, Carter R, Cooper DH, Cuculich PS, Noheria A, Asirvatham SJ, Noseworthy PA, May AM. The WCT Formula II: An effective means to automatically differentiate wide complex tachycardias. J Electrocardiol 2020; 61:121-129. [DOI: 10.1016/j.jelectrocard.2020.05.004] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 05/01/2020] [Accepted: 05/09/2020] [Indexed: 10/24/2022]
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Kashou AH, Noseworthy PA, DeSimone CV, Deshmukh AJ, Asirvatham SJ, May AM. Wide Complex Tachycardia Differentiation: A Reappraisal of the State-of-the-Art. J Am Heart Assoc 2020; 9:e016598. [PMID: 32427020 PMCID: PMC7428989 DOI: 10.1161/jaha.120.016598] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The primary goal of the initial ECG evaluation of every wide complex tachycardia is to determine whether the tachyarrhythmia has a ventricular or supraventricular origin. The answer to this question drives immediate patient care decisions, ensuing clinical workup, and long‐term management strategies. Thus, the importance of arriving at the correct diagnosis cannot be understated and has naturally spurred rigorous research, which has brought forth an ever‐expanding abundance of manually applied and automated methods to differentiate wide complex tachycardias. In this review, we provide an in‐depth analysis of traditional and more contemporary methods to differentiate ventricular tachycardia and supraventricular wide complex tachycardia. In doing so, we: (1) review hallmark wide complex tachycardia differentiation criteria, (2) examine the conceptual and structural design of standard wide complex tachycardia differentiation methods, (3) discuss practical limitations of manually applied ECG interpretation approaches, and (4) highlight recently formulated methods designed to differentiate ventricular tachycardia and supraventricular wide complex tachycardia automatically.
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Affiliation(s)
| | | | | | | | | | - Adam M May
- Cardiovascular Division Washington University School of Medicine St. Louis MO
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McGill TD, Kashou AH, Deshmukh AJ, LoCoco S, May AM, DeSimone CV. Wide complex tachycardia differentiation: An examination of traditional and contemporary approaches. J Electrocardiol 2020; 60:203-208. [DOI: 10.1016/j.jelectrocard.2020.04.006] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2020] [Revised: 04/03/2020] [Accepted: 04/11/2020] [Indexed: 10/24/2022]
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Kashou AH, DeSimone CV, Hodge DO, Carter R, Lin G, Asirvatham SJ, Noseworthy PA, Deshmukh AJ, May AM. The ventricular tachycardia prediction model: Derivation and validation data. Data Brief 2020; 30:105515. [PMID: 32382594 PMCID: PMC7200856 DOI: 10.1016/j.dib.2020.105515] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2020] [Revised: 03/10/2020] [Accepted: 03/24/2020] [Indexed: 11/23/2022] Open
Abstract
In a recent publication [1], we introduced and described a novel means (i.e. VT Prediction Model) to correctly categorize wide complex tachycardias (WCTs) into ventricular tachycardia (VT) and supraventricular wide complex tachycardia (SWCT) using routine measurements shown on electrocardiogram (ECG) paper recordings. In this article, we summarize data components relating to the derivation and validation of the VT Prediction Model.
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Affiliation(s)
| | | | - David O. Hodge
- Department of Department of Health Sciences Research, Mayo Clinic, United States
| | - Rickey Carter
- Department of Department of Health Sciences Research, Mayo Clinic, United States
| | - Grace Lin
- Department of Cardiovascular Diseases, Mayo Clinic, United States
| | | | | | | | - Adam M. May
- Department of Medicine, Division of Cardiovascular Diseases, Washington University in St. Louis, United States
- Corresponding author.
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May AM, DeSimone CV, Kashou AH, Sridhar H, Hodge DO, Carter R, Lin G, Asirvatham SJ, Noseworthy PA, Deshmukh AJ. The VT Prediction Model: A simplified means to differentiate wide complex tachycardias. J Cardiovasc Electrophysiol 2019; 31:185-195. [DOI: 10.1111/jce.14321] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2019] [Revised: 11/12/2019] [Accepted: 12/12/2019] [Indexed: 11/28/2022]
Affiliation(s)
- Adam M. May
- Division of Cardiovascular Disease, Department of MedicineWashington University in St. LouisSt. Louis Missouri
| | | | | | | | - David O. Hodge
- Department of Health Sciences ResearchMayo ClinicJacksonville Florida
| | - Rickey Carter
- Department of Health Sciences ResearchMayo ClinicJacksonville Florida
| | - Grace Lin
- Department of Cardiovascular DiseasesMayo ClinicRochester Minnesota
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