Literature DB >> 32382594

The ventricular tachycardia prediction model: Derivation and validation data.

Anthony H Kashou1, Christopher V DeSimone2, David O Hodge3, Rickey Carter3, Grace Lin2, Samuel J Asirvatham2, Peter A Noseworthy2, Abhishek J Deshmukh2, Adam M May4.   

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.
© 2020 The Author(s).

Entities:  

Keywords:  Computerized electrocardiogram interpretation; Electrocardiogram; Supraventricular tachycardia; Ventricular tachycardia; Wide complex tachycardia

Year:  2020        PMID: 32382594      PMCID: PMC7200856          DOI: 10.1016/j.dib.2020.105515

Source DB:  PubMed          Journal:  Data Brief        ISSN: 2352-3409


Specifications table

Value of the data

Enclosed data summarizes the patient demographics, clinical features, and ECG laboratory interpretation codes of patient cohorts used to derive and validate a novel WCT differentiation method known as the VT Prediction Model. Featured data also describes electrocardiographic characteristics of WCTs accurately and erroneously classified by the VT Prediction Model. Data would be valuable to researchers wanting to understand the patient demographics, clinical characteristics, and electrocardiographic features of WCT events customarily encountered in general clinical practice. Data would be of value to researchers aiming to specify clinical and ECG features to be examined in prospective evaluations that compare the diagnostic performance of WCT differentiation algorithms.

Data description

Table 1 summarizes the clinical and ECG laboratory diagnosis data for the derivation cohort. Heart rhythm or non-heart rhythm cardiologists were responsible for most (85.6%) clinical diagnoses. The ECG laboratory assigned definitive or probable interpretive diagnoses to a sizeable majority (94.8%) of WCTs. A minority of evaluated WCTs (32.1%) were derived from patients who underwent an electrophysiology procedure. A sizeable proportion of evaluated WCTs (38.2%) was derived from patients who possessed an implantable intra-cardiac device (e.g., pacemaker).
Table 1

Derivation Cohort: clinical and ECG laboratory diagnosis.

SWCT (n  = 328)VT (n  = 273)P-Value
Diagnosing provider
 Heart rhythm cardiologists141 (43.0)248 (90.8)
Non-heart rhythm cardiologists109 (33.2)17 (6.2)< 0.0001
 Non-cardiologists78 (23.8)8 (2.9)
ECG lab interpretation
 Definite VT10 (3.0)226 (82.8)< 0.0001
 Probable VT16 (4.9)26 (9.5)
 Definite SWCT265 (80.8)6 (2.2)
 Probable SWCT16 (4.9)5 (1.8)
 Undifferentiated21 (6.4)10 (3.7)
Time separation between WCT and baseline ECG (hours)
 Mean (SD)381.7 (2183.2)160.2 (632.4)0.77
 Median6.38.1
 Q1, Q31.0, 43.11.1, 46.3
Time separation between WCT and baseline ECG
 < 3 h134 (40.9)111 (40.8)0.04
 3 - 24 h88 (26.8)63 (23.1)
 24 h - 30 days78 (23.8)87 (319)
 > 30 days28 (8.5)12 (4.4)
Electrophysiology procedure
 Yes51 (15.5)142 (52.0)< 0.0001
Implanted Device
 Yes49 (14.9)181 (66.3)< 0.0001

Numbers in parentheses are percent (%) of n or standard deviation. SD = standard deviation; SWCT = supraventricular tachycardia; VT = ventricular tachycardia.

Derivation Cohort: clinical and ECG laboratory diagnosis. Numbers in parentheses are percent (%) of n or standard deviation. SD = standard deviation; SWCT = supraventricular tachycardia; VT = ventricular tachycardia. Table 2 describes the patient characteristics of the derivation cohort. The VT group included more ECG pairs from patients with coronary artery disease, prior myocardial infarction, ischemic cardiomyopathy, non-ischemic cardiomyopathy, active antiarrhythmic drug use, and implanted cardioverter-defibrillator. The supraventricular wide complex tachycardia (SWCT) group comprised more patients having an implanted pacemaker. Baseline ECGs demonstrating ventricular pacing were more prevalent in the ventricular tachycardia (VT) group than the SWCT group. Baseline bundle branch block was more common in the SWCT group than the VT group. No SWCTs (0.0%) demonstrated pre-excitation.
Table 2

Derivation cohort: patient characteristics.

SWCT (n  = 328)VT (n  = 273)P-Value
Age (years)
 Mean (SD)70.6 (14.6)65.8 (13.1)< 0.0001
 Range18.0 - 98.027.0 - 90.0
Gender
 Male212 (64.6)225 (82.4)< 0.0001
 Female116 (35.4)48 (17.6)
Clinical Characteristics
 Coronary artery disease160 (48.8)188 (68.9)< 0.0001
 Prior myocardial infarction93 (28.4)157 (57.5)< 0.0001
 Prior heart surgery123 (37.5)118 (43.2)0.15
 Congenital heart disease18 (5.5)19 (7.0)0.45
 Anti-arrhythmic drug use52 (15.9)165 (60.4)< 0.0001
 Ischemic cardiomyopathy52 (15.9)138 (50.5)< 0.0001
 Non-ischemic cardiomyopathy77 (23.5)89 (32.6)0.01
 AICD22 (6.7)176 (64.5)< 0.0001
 Pacemaker27 (8.2)5 (1.8)0.0005
Left ventricular ejection fraction (%)
 Unknown LVEF14 (4.3)1 (0.4)< 0.0001
 LVEF (<= 30)66 (20.1)118 (43.2)
 LVEF (49 - 31)59 (18.0)85 (31.1)
 LVEF (>= 50)189 (57.6)69 (25.3)
Baseline ECG
 Baseline bundle branch block217 (66.2)39 (14.3)< 0.0001
 Baseline ventricular pacing19 (5.8)110 (40.3)< 0.0001
SWCT with pre-excitation
 Yes0 (0.0%)******

Numbers in parentheses are percent (%) of n or standard deviation. AICD = automatic implantable cardioverter-defibrillator; LVEF = left ventricular ejection fraction; SD = standard deviation; SWCT = supraventricular tachycardia; VT = ventricular tachycardia.

Derivation cohort: patient characteristics. Numbers in parentheses are percent (%) of n or standard deviation. AICD = automatic implantable cardioverter-defibrillator; LVEF = left ventricular ejection fraction; SD = standard deviation; SWCT = supraventricular tachycardia; VT = ventricular tachycardia. Table 3 summarizes the clinical and ECG laboratory diagnosis data for the validation cohort. Heart rhythm or non-heart rhythm cardiologists were responsible for most (90.5%) clinical diagnoses. Definitive or probable diagnoses were assigned to the vast majority (95.0%) of WCTs interpreted by the ECG laboratory. About one-third (34.4%) of evaluated WCTs were derived from patients who underwent an electrophysiology procedure. A substantial percentage (40.2%) of evaluated WCTs were derived from patients who possessed an implantable intra-cardiac device.
Table 3

Validation cohort: clinical and ECG laboratory diagnosis.

SWCT (n  = 144)VT (n  = 97)P-Value
Diagnosing provider
 Heart rhythm cardiologists59 (41.0)82 (84.5)< 0.001
 Non-heart rhythm cardiologists63 (43.8)14 (14.4)
 Non-cardiologists22 (15.3)1 (1.0)
ECG lab interpretation
 Definite VT9 (6.2)68 (70.1)< 0.001
 Probable VT1 (0.7)9 (9.3)
 Definite SWCT87 (60.4)3 (3.1)
 Probable SWCT41 (28.5)11 (11.3)
 Undifferentiated6 (4.2)6 (6.2)
Time separation between WCT and baseline ECG (hours)
 Mean (SD)275.9 (1293.8)104.3 (434.8)0.075
 Median10.15.1
 Q1, Q31.5, 46.60.6, 33.8
Time separation between WCT and Baseline ECG
 < 3 h47 (32.6)45 (46.4)0.174
 3 - 24 h46 (31.9)23 (23.7)
 24 h - 30 days46 (31.9)27 (27.8)
 > 30 days5 (3.5)2 (2.1)
Electrophysiology procedure
 Yes26 (18.1)57 (58.8)< 0.001
Implanted device
 Yes27 (18.8)70 (72.2)< 0.001

Numbers in parentheses are percent (%) of n or standard deviation. SD = standard deviation; SWCT = supraventricular tachycardia; VT = ventricular tachycardia.

Validation cohort: clinical and ECG laboratory diagnosis. Numbers in parentheses are percent (%) of n or standard deviation. SD = standard deviation; SWCT = supraventricular tachycardia; VT = ventricular tachycardia. Table 4 details the clinical characteristics of patients comprising the validation cohort. The VT group included more ECG pairs from patients with coronary artery disease, prior myocardial infarction, ischemic cardiomyopathy, active antiarrhythmic drug use, and implanted cardioverter-defibrillator. The SWCT group comprised more ECG pairs from patients having an implanted pacemaker. Baseline ECGs demonstrating ventricular pacing were more prevalent in the VT group than the SWCT group. Baseline bundle branch block was more common in the SWCT group than the VT group. Four SWCTs (2.8%) demonstrated pre-excitation.
Table 4

Validation cohort: clinical and ECG laboratory diagnosis.

SWCT (n = 144)VT (n = 97)P-Value
Age (years)
 Mean (SD)69.4 (14.8)67.5 (10.8)0.027
Gender
 Male102 (70.8)87 (89.7)< 0.001
 Female42 (29.2)10 (10.3)
Clinical Characteristics
 Coronary artery disease54 (37.5)71 (73.2)< 0.001
 Prior myocardial infarction34 (23.6)67 (69.1)< 0.001
 Prior heart surgery45 (31.2)29 (29.9)0.823
 Congenital heart disease5 (3.5)0 (0.0)0.064
 Anti-arrhythmic drug use25 (17.4)48 (49.5)< 0.001
 Ischemic cardiomyopathy27 (18.8)63 (64.9)< 0.001
 Non-ischemic cardiomyopathy49 (34.0)24 (24.7)0.124
 AICD21 (14.6)70 (72.2)< 0.001
 Pacemaker7 (4.9)0 (0.0)0.028
Left ventricular ejection fraction (%)
 Unknown LVEF7 (4.9)1 (1.0)< 0.001
 LVEF (<= 30)35 (24.3)45 (46.4)
 LVEF (49 - 31)27 (18.8)31 (32.0)
 LVEF (>= 50)75 (52.1)20 (20.6)
Baseline ECG
 Baseline bundle branch block90 (62.5)17 (17.5)< 0.001
 Baseline ventricular pacing8 (5.6)33 (34.0)< 0.001
SWCT with Pre-excitation
 Yes4 (2.8)******

Numbers in parentheses are percent (%) of n or standard deviation. AICD = automatic implantable cardioverter-defibrillator; LVEF = left ventricular ejection fraction; SD = standard deviation; SWCT = supraventricular tachycardia; VT = ventricular tachycardia.

Validation cohort: clinical and ECG laboratory diagnosis. Numbers in parentheses are percent (%) of n or standard deviation. AICD = automatic implantable cardioverter-defibrillator; LVEF = left ventricular ejection fraction; SD = standard deviation; SWCT = supraventricular tachycardia; VT = ventricular tachycardia. Table 5 summarizes electrocardiographic characteristics of correct and incorrect diagnoses established by the VT Prediction Model for the derivation cohort. According to a 50% VT probability partition to establish VT diagnoses (VT > = 50.0% and SWCT < 50.0%), 53 out of 278 (19.1%) clinical VTs were incorrectly branded as SWCT by the VT Prediction Model. In comparison with correctly identified VTs, erroneous classifications of clinical VT as SWCT displayed shorter WCT QRS duration and constrained changes in QRS duration, QRS axis, and T axis between paired baseline and WCT ECGs. According to a 50% VT probability partition to establish VT diagnoses (VT > = 50.0% and SWCT < 50.0%), 38 out of 323 (11.8%) clinical SWCTs were erroneously categorized as VT by the VT Prediction Model. In comparison with correctly identified SWCTs, erroneous classifications of clinical SWCT as VT demonstrated more prolonged WCT QRS intervals and larger changes in QRS duration, QRS axis, and T axis between paired baseline and WCT ECGs.
Table 5

Derivation cohort: correct and erroneous WCT diagnoses.

WCT (n = 601)
VT (n = 273)
SWCT (n = 328)
Erroneous SWCT Prediction (n = 53)Correct VT Prediction (n = 220)P-valueErroneous VT Prediction (n = 38)Correct SWCT Prediction (n = 290)P-value
WCT QRS duration (ms)147.7 (19.7)183.9 (30.3)< 0.0001163.6 (20.1)140.3.6 (15.7)< 0.0001
QRS duration change (ms)24.7 (17.9)51.5 (35.9)< 0.000141.5 (33.6)13.7 (14.2)< 0.0001
QRS axis change (°)35.2 (36.5)99.0 (54.8)< 0.000168.7 (56.9)20.1 (23.7)< 0.0001
T axis change (°)50.1 (46.4)101.8 (55.8)< 0.000192.9 (47.8)34.1 (35.1)< 0.0001

Displayed numbers represent mean values. Numbers in parentheses are standard deviation. The erroneous VT prediction group comprise clinical SWCTs assigned high VT probability (>= 50%). The erroneous SWCT prediction group comprise clinical VTs assigned low VT probability (< 50%). SWCT = supraventricular wide complex tachycardia; VT= ventricular tachycardia; WCT = wide complex tachycardia.

Derivation cohort: correct and erroneous WCT diagnoses. Displayed numbers represent mean values. Numbers in parentheses are standard deviation. The erroneous VT prediction group comprise clinical SWCTs assigned high VT probability (>= 50%). The erroneous SWCT prediction group comprise clinical VTs assigned low VT probability (< 50%). SWCT = supraventricular wide complex tachycardia; VT= ventricular tachycardia; WCT = wide complex tachycardia. Fig. 1 illustrates the diagnostic performance of the VT Prediction Model for the derivation cohort (AUC 0.924; CI 0.903 – 0.944).
Fig. 1

VT prediction model diagnostic performance: derivation cohort.

VT prediction model diagnostic performance: derivation cohort. Fig. 2 illustrates the diagnostic performance of the VT Prediction Model when implemented on the validation cohort (AUC 0.900; CI 0.862 – 0.939).
Fig. 2

VT prediction model diagnostic performance: validation cohort.

VT prediction model diagnostic performance: validation cohort. Fig. 3 provides an example of paired VT (A) and baseline (B) ECGs assigned high VT probability (99.0006%) by the VT Prediction Model. WCT QRS duration = 182 ms; QRS duration change = 48 ms; QRS axis change = 134°; T axis change = 93°
Fig. 3

Appropriate high VT probability assignment.

Appropriate high VT probability assignment. Fig. 4 provides an example of paired SWCT (A) and baseline (B) ECGs assigned low VT probability (4.3609%) by the VT Prediction Model. WCT QRS duration = 130 ms; QRS duration change = 46 ms; QRS axis change = 1°; T axis change = 8°
Fig. 4

Appropriate low VT probability assignment.

Appropriate low VT probability assignment. Fig. 5 provides an example of paired SWCT (A) and baseline (B) ECGs assigned low VT probability (6.3613%) by the VT Prediction Model. WCT QRS duration = 120 ms; QRS duration change = 36 ms; QRS axis change = 48°; change T axis change = 13°
Fig. 5

Appropriate low VT probability assignment.

Appropriate low VT probability assignment. Fig. 6 provides an example of paired VT (A) and baseline (B) ECGs assigned low VT probability (9.8704%) by the VT Prediction Model. WCT QRS duration = 126 ms; QRS duration change = 6 ms; QRS axis change = 63°; T axis change = 30°
Fig. 6

Erroneous low VT probability assignment.

Erroneous low VT probability assignment. Fig. 7 provides an example of paired SWCT (A) and baseline (B) ECGs assigned high VT probability (54.0039%) by the VT Prediction Model. WCT QRS duration = 170 ms; QRS duration change = 52 ms; QRS axis change = 3°; T axis change = 89°
Fig. 7

Erroneous high VT probability assignment.

Erroneous high VT probability assignment.

Experimental design, materials, and methods

Our recent publication [1] describes the derivation and implementation of a new WCT differentiation method that produces explicit VT probability estimations for paired WCT and baseline ECGs. In this report, a logistic regression model (i.e., VT Prediction Model) was derived and tested using two using separate patient cohorts: derivation and validation. First, a derivation cohort of paired WCT and baseline ECGs was evaluated to identify independent predictors to be consolidated into the VT Prediction Model. After that, the VT Prediction Model was trialed against a separate validation cohort of paired WCT and baseline ECGs. The overall diagnostic performance of the VT Prediction Model was appraised according to its agreement with the final clinical diagnosis established by patients' supervising physicians. Paired WCT and baseline ECGs were derived from actual clinical settings throughout the entire Mayo Clinic enterprise between September 2011 and December 2018. Evaluated ECGs were standard 12-lead paper recordings (speed: 25 mm/s, voltage calibration: 10 mm/mV) acquired from Mayo Clinic's ECG data archives (GE Healthcare; Milwaukee, WI). Included WCTs were required to fulfill WCT criteria (QRS duration ≥ 120 ms and heart rate ≥ 100 bpm) plus an official ECG laboratory interpretation of (1) "ventricular tachycardia," (2) "supraventricular tachycardia," or (3) "wide complex tachycardia." Baseline ECGs were either the first subsequent ECG (i.e., for the derivation cohort) or nearest ECG (i.e., for the validation cohort), not fulfilling WCT criteria. The derivation cohort encompassed 601 paired WCT (273 VT, 328 SWCT) and baseline ECGs from 421 patients presenting to Mayo Clinic Rochester or Mayo Clinic Health System of South Eastern Minnesota (September 2011 through November 2016). The validation cohort comprised 241 WCT (97 VT, 144 SWCT) and baseline ECG pairs from 177 patients presenting to the whole Mayo Clinic enterprise (January 2018 through December 2018) – including three large medical centers (Rochester, Minnesota; Jacksonville, Florida; and Phoenix/Scottsdale, Arizona) and auxiliary patient care locations (e.g., community hospitals). Data relating to clinical diagnosis, ECG laboratory examination, and patient characteristics were discovered from an electronic medical record review. Standard ECG measurements rendered by GE Healthcare's MUSE ECG interpretation software were acquired from archived ECG recordings. Basic arithmetical computations (QRS axis change, T wave axis change, QRS duration change) were processed using electronic measurements routinely displayed on ECG recordings. The Mayo Clinic Institutional Review Board approved patient data acquisition and analysis. Similar patient selection processes and data reporting were previously adopted in a separate analysis [2,3].
Subject areaCardiology
More specific subject areaElectrocardiology, computerized electrocardiogram interpretation
Type of dataTables, figures, and images
How data was acquiredReview of health records and automated measurements provided by computerized electrocardiogram interpretation software (MUSE by GE Healthcare; Milwaukee, WI)
Data formatRaw and analyzed data
Parameters for data collectionEvaluated electrocardiograms were paired wide complex tachycardia and baseline electrocardiograms attained within clinical settings throughout the entire Mayo Clinic enterprise between September 2011 and December 2018.
Description of data collectionEvaluated electrocardiograms were standard 12-lead recordings obtained from Mayo Clinic's centralized electrocardiogram data archives. Wide complex tachycardias were required to fulfill wide complex tachycardia criteria (QRS duration ≥ 120 ms; heart rate ≥ 100 bpm) plus a formal ECG laboratory interpretation of (i) "ventricular tachycardia," (ii) "supraventricular tachycardia," or (iii) "wide complex tachycardia." Baseline electrocardiograms were either the first subsequent electrocardiogram or most proximate that did not fulfill wide complex tachycardia criteria.
Data source locationMayo Clinic
Data accessibilityData is included in this article
Related research articleA.M. May, C.V. DeSimone, A.H. Kashou, H. Sridhar, D.O. Hodge, R. Carter, G. Lin, S.J. Asirvatham, P.A. Noseworthy, A.J. Deshmukh. The VT Prediction Model: A Simplified Means to Differentiate Wide Complex Tachycardias. Journal of Cardiovascular Electrophysiology. December 2019. 10.1111/jce.14321.
  3 in total

1.  The WCT Formula: A novel algorithm designed to automatically differentiate wide-complex tachycardias.

Authors:  Adam M May; Christopher V DeSimone; Anthony H Kashou; David O Hodge; Grace Lin; Suraj Kapa; Samuel J Asirvatham; Abhishek J Deshmukh; Peter A Noseworthy; Peter A Brady
Journal:  J Electrocardiol       Date:  2019-02-25       Impact factor: 1.438

2.  The VT Prediction Model: A simplified means to differentiate wide complex tachycardias.

Authors:  Adam M May; Christopher V DeSimone; Anthony H Kashou; Haarini Sridhar; David O Hodge; Rickey Carter; Grace Lin; Samuel J Asirvatham; Peter A Noseworthy; Abhishek J Deshmukh
Journal:  J Cardiovasc Electrophysiol       Date:  2019-12-25

3.  The Wide Complex Tachycardia Formula: Derivation and validation data.

Authors:  Adam M May; Christopher V DeSimone; Anthony H Kashou; David O Hodge; Grace Lin; Suraj Kapa; Samuel J Asirvatham; Abhishek J Deshmukh; Peter A Noseworthy; Peter A Brady
Journal:  Data Brief       Date:  2019-04-17
  3 in total
  2 in total

Review 1.  Differentiating wide complex tachycardias: A historical perspective.

Authors:  Anthony H Kashou; Christopher M Evenson; Peter A Noseworthy; Thoddi R Muralidharan; Christopher V DeSimone; Abhishek J Deshmukh; Samuel J Asirvatham; Adam M May
Journal:  Indian Heart J       Date:  2020-09-23

2.  Automatic wide complex tachycardia differentiation using mathematically synthesized vectorcardiogram signals.

Authors:  Anthony H Kashou; Sarah LoCoco; Trevon D McGill; Christopher M Evenson; Abhishek J Deshmukh; David O Hodge; Daniel H Cooper; Sandeep S Sodhi; Phillip S Cuculich; Samuel J Asirvatham; Peter A Noseworthy; Christopher V DeSimone; Adam M May
Journal:  Ann Noninvasive Electrocardiol       Date:  2021-09-25       Impact factor: 1.468

  2 in total

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