JACC: CLINICAL ELECTROPHYSIOLOGY
VOL. 8, NO. 7, 2022
ª 2022 BY THE AMERICAN COLLEGE OF CARDIOLOGY FOUNDATION
PUBLISHED BY ELSEVIER
ORIGINAL RESEARCH
VENTRICULAR ARRHYTHMIAS - ELECTROCARDIOGRAPHY
Simplified Integrated Clinical and
Electrocardiographic Algorithm for
Differentiation of Wide QRS Complex
Tachycardia
The Basel Algorithm
Federico Moccetti, MD,a,b,c Mrinal Yadava, MD,b Yllka Latifi, MD,b,d Ivo Strebel, PHD,a Nikola Pavlovic, MD, PHD,a,e
Sven Knecht, DSC,a Babken Asatryan, MD, PHD,f Beat Schaer, MD,a Michael Kühne, MD,a Charles A. Henrikson, MD,b
Frank-Peter Stephan, MD,a Stefan Osswald, MD,a Christian Sticherling, MD,a Tobias Reichlin, MDa,f
ABSTRACT
BACKGROUND Prompt differential diagnosis of wide QRS complex tachycardia (WCT) is crucial to patient management. However, distinguishing ventricular tachycardia (VT) from supraventricular tachycardia (SVT) with wide QRS
complexes remains problematic, especially for nonelectrophysiologists.
OBJECTIVES This study aimed to develop a simple-to-use algorithm with integration of clinical and electrocardiographic (ECG) parameters for the differential diagnosis of WCT.
METHODS The 12-lead ECGs of 206 monomorphic WCTs (153 VT, 53 SVT) with electrophysiology-confirmed diagnoses
were analyzed. In the novel Basel algorithm, VT was diagnosed in the presence of at least 2 of the following criteria:
1) clinical high risk features; 2) lead II time to first peak >40 ms; and 3) lead aVR time to first peak >40 ms. The algorithm
was externally validated in 203 consecutive WCT cases (151 VT, 52 SVT). Its’ diagnostic performance and clinical
applicability were compared with those of the Brugada and Vereckei algorithms.
RESULTS The Basel algorithm showed a sensitivity, specificity, and accuracy of 92%, 89%, and 91%, respectively, in
the derivation cohort and 93%, 90%, and 93%, respectively, in the validation cohort. There were no significant
differences in the performance characteristics between the 3 algorithms. The evaluation of the clinical applicability of
the Basel algorithm showed similar diagnostic accuracy compared with the Brugada algorithm (80% vs 81%; P ¼ 1.00),
but superiority compared with the Vereckei algorithm (72%; P ¼ 0.03). The Basel algorithm, however, enabled a faster
diagnosis (median 36 seconds vs 105 seconds for the Brugada algorithm [P ¼ 0.002] and 50 seconds for the Vereckei
algorithm [P ¼ 0.02]).
CONCLUSIONS The novel Basel algorithm based on simple clinical and ECG criteria allows for a rapid and accurate
differential diagnosis of WCT. (J Am Coll Cardiol EP 2022;8:831–839) © 2022 by the American College of Cardiology
Foundation.
From the aDivision of Cardiology, Department of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland;
b
Knight Cardiovascular Institute, Oregon Health and Science University, Portland, Oregon, USA; cHeart Center Lucerne, Luzerner
Kantonsspital, Lucerne, Switzerland; dCardiology Spital Uster, Uster, Switzerland; eCardiology, Klinicki Bolnicki Centar Sestre
Milosrdnice, Zagreb, Croatia; and the fDepartment of Cardiology, Inselspital, Bern University Hospital, University of Bern, Bern,
Switzerland.
The authors attest they are in compliance with human studies committees and animal welfare regulations of the authors’
institutions and Food and Drug Administration guidelines, including patient consent where appropriate. For more information,
visit the Author Center.
Manuscript received October 18, 2021; revised manuscript received March 22, 2022, accepted March 28, 2022.
ISSN 2405-500X/$36.00
https://doi.org/10.1016/j.jacep.2022.03.017
832
Moccetti et al
JACC: CLINICAL ELECTROPHYSIOLOGY VOL. 8, NO. 7, 2022
JULY 2022:831–839
Basel Algorithm for Diagnosis of SVT/VT
A
ABBREVIATIONS
AND ACRONYMS
ECG = electrocardiography
wide
tachycardia
patients undergoing EP studies for regular WCT at the
(WCT) on the surface electrocardio-
Knight Cardiovascular Institute of the Oregon Health
gram (ECG) prompts a complex dif-
and Science University, Portland, Oregon, were
ferential
EP = electrophysiology
SVT = supraventricular
tachycardia
VT = ventricular tachycardia
WCT = wide QRS complex
QRS
diagnosis
complex
of
arrhythmias
with
The study was performed in accordance with the
potentially lethal, requiring different treat-
principles of the Declaration of Helsinki. The study
ment strategies.1,2 While WCT is a manifesta-
protocol
tion of ventricular tachycardia (VT) in around
committees.
80% of cases,2 other potential causes of WCT
tachycardia
retrospectively identified.
prognoses ranging from utterly benign to
include pre-excited supraventricular tachycardia (SVT), SVT with abnormal intraventricular conduction, ventricular-paced rhythm, and drug- and
electrolyte-induced QRS widening.3,4 Rapid recognition of the underlying cause of the WCT is of critical
importance for timely initiation of the appropriate
treatment, 5 because delayed diagnosis or inappropriate management in patients with VT may have
deleterious consequences. 6-8 Therefore, a simplified,
was
approved
by
the
local
ethics
ECG ANALYSIS. The 12-lead ECGs were analyzed by 2
of the authors (F.M. and M.Y.) blinded to the EP
diagnosis at a sweep speed of 25 mm/s. As in previous
studies assessing the accuracy of ECG algorithms, the
12-lead ECGs of the tachycardias acquired during the
EP studies were assessed.10,12 The criterion standard
diagnosis of VT vs SVT was the one obtained during
the EP study. All ECGs from the derivation and validation cohorts were assessed according to: 1) the
novel simplified integrated ECG algorithm (“the Basel
algorithmic, and practical approach to WCTs is crucial
algorithm”); 2) the Brugada algorithm; 10 and 3) the
for all clinicians responsible for ECG interpretation,
Vereckei algorithm. 12 Interobserver agreement for the
whether in emergency medicine, cardiology, or primary care.9
measurements in lead II and aVR were assessed in the
validation cohort.
SEE PAGE 840
DERIVATION OF THE BASEL ALGORITHM. The per-
Over the past 3 decades, several criteria and algo-
formance of several ECG candidate criteria was tested
rithms have been proposed to distinguish VT from
in the derivation cohort and the 2 with the highest
SVT with abnormal intraventricular conduction.10-17
area under the receiver operating characteristic (ROC)
Among them the Brugada algorithm and Vereckei
curve for the diagnosis of VT (lead II time to first
algorithm are the most commonly used. Despite
peak, lead aVR time to first peak) were chosen.
the
Accordingly, the proposed Basel algorithm is based on
high
sensitivity
(SN)
and
specificity
(SP)
reported in original cohorts, their use in the clinical
3 criteria (Figure 1, Central Illustration): 1) clinical high
setting has consistently showed low reproducibility
risk feature; 2) lead II time to first peak >40 ms; and 3)
(Supplemental Table 1).18-23 Furthermore, these WCT
lead aVR time to first peak >40 ms. VT was diagnosed
algorithms are rather complex, involving multiple
if at least 2 of those 3 criteria were met. If 0 or 1 cri-
sequential steps and requiring evaluation of WCT
terion was positive, the diagnosis was SVT. Examples
morphology, and are difficult to recall in an emer-
of ECGs with WCT demonstrating successful and un-
gency setting. These factors render the everyday use
successful diagnoses of VT and of SVT are shown in
of WCT algorithms challenging, particularly for non-
Figure 2.
electrophysiologist (non-EP) practitioners.
The clinical high risk feature criterion is considered
To address these remaining challenges in the dif-
to be met if the patient has a history of myocardial
ferential diagnosis of WCT we aimed to develop a
infarction, a history of congestive heart failure with
user-friendly algorithm based on clinical and ECG
left
parameters to facilitate a rapid and accurate diagnosis
implanted implantable cardioverter-defibrillator or
ventricular
ejection
fraction
#35%
(or
an
in patients presenting with monomorphic regular
cardiac resynchronization therapy–defibrillator). The
WCT.
lead II and lead aVR time to first peak criterion is
considered to be positive if the time from the begin-
METHODS
PATIENT POPULATIONS AND STUDY DESIGN. For
the derivation cohort, consecutive patients undergo-
ning of the QRS to the first change in polarity, ie, the
first positive or negative deflection (or “peak”), is
>40 ms. This can be expressed as a QRS complex
beginning with an r- or R-wave >40 ms, or beginning
ing electrophysiological (EP) studies for regular WCT
with a q-, Q-, or QS-wave >40 ms.
at the University Hospital of Basel, Switzerland, from
EVALUATION OF THE CLINICAL APPLICABILITY OF
January 2010 to December 2014 were retrospectively
THE NOVEL BASEL ALGORITHM. To evaluate the
identified. For the validation cohort, consecutive
“real-world”
clinical
applicability
of
the
novel
Moccetti et al
JACC: CLINICAL ELECTROPHYSIOLOGY VOL. 8, NO. 7, 2022
JULY 2022:831–839
Basel Algorithm for Diagnosis of SVT/VT
F I G U R E 1 Graphical Representation of the Novel Basel Algorithm
CHF ¼ congestive heart failure; CRT ¼ cardiac resynchronization therapy; ICD ¼ implantable cardioverter-defibrillator; LVEF ¼ left ventricular
ejection fraction; SVT¼ supraventricular tachycardia; VT¼ ventricular tachycardia.
algorithm, a total of 8 physicians (2 EPs, 2 general
DATA
cardiologists, 2 cardiology fellows, and 2 internal
article cannot be shared publicly owing to privacy of
AVAILABILITY. The
medicine residents) analyzed a random subset of 50
the individuals that were investigated in the study.
WCT ECGs (25 VTs and 25 SVTs) at a sweep speed of
The data will be shared on reasonable request to the
25 mm/s. Each of them analyzed the 50 ECGs indi-
corresponding author provided that it in accordance
vidually, blinded to the criterion standard diagnosis.
with the institutional ethical guidelines as well as
The ECG analysis was performed at 6 different time
regulations and legislation.
data
underlying
this
points (with at least 2 weeks interval in between)
according to 5 existing algorithms (Brugada, Vereckei,
Pava, Jastrzebski, and Chen) 10,13-16 and the novel
RESULTS
Basel algorithm. The time to diagnosis was recorded
BASELINE CHARACTERISTICS OF THE PATIENTS. In
for every ECG assessed.
the derivation cohort, a total of 206 WCT episodes
STATISTICAL ANALYSIS. Continuous variables are
presented as median (IQR) and compared with the use
of the Mann-Whitney U test. Chi-square tests were
used to compare categoric variables. To assess the
algorithm performance, SN, SP, positive predictive
value, negative predictive value, and diagnostic ac-
(153 VT, 53 SVT) were recorded in 124 patients. In the
validation cohort, 203 WCT episodes (151 VT, 52 SVT)
were recorded in 112 patients. Baseline characteristics
of the patients and the ECG characteristics of the 2
cohorts are presented in Tables 1 and 2. The underlying arrhythmias in the groups of SVTs and VTs are
curacy were calculated from 2 2 cross-tables.
presented in Table 3.
McNemar’s test was used to compare the perfor-
DERIVATION
mance of the Basel algorithm with those of the Bru-
analysis of several candidate criteria in the derivation
gada
and
Vereckei
algorithms.
OF
THE
NOVEL
ALGORITHM. After
Interobserver
cohort, time to first peak in lead II and lead aVR
agreement for measurements performed in lead II
showed the best performance characteristics (area
and aVR were assessed with the use of correlation
under the ROC curve: 0.91 for both). ROC derived
coefficients and Bland-Altman plots in the validation
optimal cutoffs were 51 ms for lead II time to peak and
cohort.
46 ms for lead aVR time to peak (Supplemental
For the clinical validation, SN, SP, positive pre-
Table 2). For the algorithm, a cutoff of 40 ms was
dictive value, negative predictive value, diagnostic
chosen to facilitate user-friendly application in clin-
accuracy, and average time to diagnosis using the 3
ical practice.
algorithms were compared by means of Tukey’s
multiple comparisons test.
Observer
agreement
(Supplemental
Figure
1)
showed good correlation for lead II and aVR (r 2 ¼ 0.94
A P value <0.05 was considered to be statistically
and r2 ¼0.92, respectively). Bland-Altman plots
significant. The statistical analyses were performed
showed a small bias (0.4 ms and 0.8 ms for lead II
with the use of SPSS version 24.0 (IBM), Prism
and aVR, respectively) and narrow 95% limits of
Graphpad version 8.2.1 (Graphpad Software), and R (R
agreement (14.8 and 14.0 ms for lead II, 17.0 and
Foundation for Statistical Computing.
15.4 ms for lead aVR).
833
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JULY 2022:831–839
Basel Algorithm for Diagnosis of SVT/VT
C E NT R AL IL L U STR AT IO N Simplified Integrated Clinical and Electrocardiographic Algorithm for Differentiation
of Wide QRS Complex Tachycardia
Derivation, 206 ECGs
Validation, 203 ECGs
I
II
V1
V2
Novel Simplified Algorithm for the Differential Diagnosis of WCT
Structural Heart
Disease
Lead II
Time to First Peak
>40 ms
+
+
Lead aVR
Time to First Peak
>40 ms
Structural Heart Disease:
- Myocardial Infarction (history)
- CHF (LVEF <35%)
- Device (ICD, CRT)
120 ms
0 or 1 criteria fulfilled → SVT
≥2 criteria fulfilled → VT
III
V3
Comparison of Algorithm Performance
100%
aVR
V4
90%
80%
aVL
70%
V5
60%
50%
Sensitivity
aVF
V6
Specificity
Accuracy
Basel-Algorithm
Derivation / Validation
Brugada-Algorithm
Derivation / Validation
Vereckei-Algorithm
Derivation / Validation
Clinical Validation
Diagnostic Accuracy
Time to Diagnosis
P = 1.0
P = 0.002
P = 0.02
P = 0.003 P = 0.02
Seconds
%
P = 0.03
100
90
80
70
60
50
40
30
Brugada Vereckei
Novel
160
140
120
100
80
60
40
20
0
Brugada Vereckei
EP Attending
Cardiology Attending
Cardiology Fellow
Internal Medicine Resident
Novel
Moccetti F, et al. J Am Coll Cardiol EP. 2022;8(7):831–839.
CHF ¼ congestive heart failure; CRT ¼ cardiac resynchronization therapy; ECG ¼ electrocardiogram; EP ¼ electrophysiology; ICD ¼ implantable cardioverterdefibrillator; LVEF ¼ left ventricular ejection fraction; SVT ¼ supraventricular tachycardia; VT ¼ ventricular tachycardia; WCT ¼ wide QRS complex tachycardia.
Moccetti et al
JACC: CLINICAL ELECTROPHYSIOLOGY VOL. 8, NO. 7, 2022
JULY 2022:831–839
Basel Algorithm for Diagnosis of SVT/VT
F I G U R E 2 Examples of Electrocardiograms With Wide QRS Complex Tachycardia Demonstrating Successful and Unsuccessful Diagnoses
of VT and SVT
(A) Ventricular tachycardia (VT) with a focus in the left ventricular outflow tract correctly classified as VT with the Basel algorithm (time to first
peak >40 ms in leads II and aVR). (B) Fascicular VT incorrectly classified with the Basel algorithm (time to first peak <40 ms in leads II and
aVR). (C) Typical atrial flutter with 1:1 atrioventricular conduction and right bundle branch block aberrancy correctly classified as supraventricular tachycardia (SVT) with the Basel algorithm (time to first peak <40 ms in leads II and aVR). (D) SVT incorrectly classified as VT with the
Basel algorithm (time to first peak >40 ms in leads II and aVR).
PERFORMANCE OF THE NOVEL ALGORITHM IN THE
performance of each criterion, are presented in
DERIVATION AND THE VALIDATION COHORT. The
Table 4. The novel algorithm reached SN and SP of,
diagnostic performance of the Brugada algorithm, the
respectively, 91.5% and 88.7% in the derivation
Vereckei algorithm and the novel Basel algorithm in
cohort and 93.3% and 90.4% in the validation cohort.
the derivation and the validation cohort, including
This was similar to the Brugada and Vereckei
T A B L E 1 Patient Characteristics
Derivation Cohort
All
(N ¼ 124)
VT
(n ¼ 74)
SVT
(n ¼ 50)
65 (50-74)
64 (50-72)
Male
82 (69)
Structural heart disease
Age, y
LVEF, %
Validation Cohort
P Value
All
(N ¼ 112)
VT
(n ¼ 64)
SVT
(n ¼ 48)
P Value
68 (51-77)
0.46
61 (42-69)
61 (42-70)
58 (34-69)
0.23
51 (69)
31 (69)
0.45
64 (57)
49 (77)
30 (63)
0.14
65 (55)
51 (69)
14 (31)
<0.05
56 (50)
49 (52)
7 (15)
<0.05
50 (34-60)
40 (27-55)
56 (50-60)
<0.001
45 (30-60)
30 (25-55)
60 (51-63)
<0.001
<0.001
Antiarrhythmic drugs
Any
97 (78)
60 (81)
37 (74)
0.38
72 (64)
53 (83)
18 (38)
Class I
4 (3.2)
1 (1.4)
3 (6)
0.30
19 (17)
16 (25)
3 (6)
0.01
Class II
89 (72)
54 (73)
35 (70)
0.84
69 (62)
50 (78)
13 (27)
<0.001
Class III
37 (30)
27 (37)
10 (20)
0.07
31 (28)
29 (45)
2 (4.2)
<0.001
Class IV
4 (3.2)
1 (1.4)
3 (6)
0.30
0
0
0
1.00
Values are median (IQR) or n (%).
LVEF ¼ left ventricular ejection fraction; SVT ¼ supraventricular tachycardia; VT¼ ventricular tachycardia.
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JULY 2022:831–839
Basel Algorithm for Diagnosis of SVT/VT
T A B L E 2 ECG Characteristics of Wide QRS Complex Tachycardias in the Derivation and Validation Groups
Derivation Cohort
Validation Cohort
All
(N ¼ 206)
VT
(n ¼ 153)
SVT
(n ¼ 53)
P Value
All
(N ¼ 203)
VT
(n ¼ 151)
SVT
(n ¼ 52)
Cycle length, ms
380 (312-440)
376 (312-440)
P Value
400 (314-440)
0.30
405 (322-469)
402 (312-464)
413 (331-492)
Heart rate, beats/min
158 (136-192)
0.38
160 (136-192)
150 (137-191)
0.30
149 (127-186)
160 (129-191)
155 (122-185)
QRS duration, ms
0.38
160 (140-188)
172 (152-196)
140 (135-144)
<0.001
165 (149-196)
182 (157-202)
155 (138-154)
<0.001
RBBB
116 (58)
88 (58)
28 (58)
<0.06
114 (56)
84 (56)
30 (59)
0.87
LBBB
84 (42)
64 (42)
20 (42)
<0.07
89 (44)
67 (44)
22 (41)
0.11
Values are median (IQR) or n (%).
LBBB ¼ left bundle branch block; RBBB ¼ right bundle branch block; other abbreviations as in Table 1.
algorithms, in the derivation, validation, and overall
[IQR: 58%-73%]; P ¼ 0.03), and no differences were
cohorts (Supplemental Table 3). The diagnostic per-
found between the Basel algorithm and the other al-
formance of each step/criterion of the Brugada, Ver-
gorithms (Figure 3, Central Illustration).
eckei, and novel Basel algorithm in both the
Average time to diagnosis was significantly shorter
derivation and the validation cohorts are presented in
using the Basel algorithm (median 38 [IQR: 2947]
Supplemental Table 4.
seconds) compared with the Brugada algorithm (me-
EVALUATION OF THE CLINICAL APPLICABILITY OF
THE NOVEL ALGORITHM. The SN and SP of the cli-
nicians’ interpretation are shown in Figure 3. SP was
higher with the use of the Basel algorithm vs the
Vereckei algorithm (median 80% [IQR: 72%-86%] vs
dian 106 [IQR: 76-135] seconds; P ¼ 0.002) and Vereckei algorithms (median 48 [IQR: 43-59] seconds;
P ¼ 0.02). No differences were found between the
Basel algorithm and the other algorithms (Figure 3,
Central Illustration).
median 58% [IQR: 46%-72%]; P ¼ 0.007), but no other
ALGORITHM PERFORMANCE IN SPECIAL SITUATIONS. We
differences were observed between the Basel algo-
tested the performance of the Basel algorithm in 3
rithm and the other algorithms.
clinically challenging albeit rare scenarios: fascicular
The Basel algorithm showed a higher diagnostic
ventricular tachycardia (n ¼ 3), antidromic atrioven-
accuracy (median 81% [IQR: 76.5%-83.5%]) compared
tricular re-entrant tachycardia (n ¼ 1), and Mahaim-
with the Vereckei algorithm (median 72% [IQR: 65%-
fiber tachycardia (n ¼ 3). Similar to the Brugada and
76%]; P ¼ 0.002) and the Chen algorithm (median 72%
Vereckei algorithms, the performance of the novel
Basel algorithm was poor in these tachycardias
(Supplemental Table 5).
T A B L E 3 Underlying Causes of SVT and VT
Derivation Cohort
Validation Cohort
(n ¼ 53)
(n ¼ 52)
Atrial flutter
22 (42)
21 (40)
AVNRT
17 (34)
18 (35)
AVRT
4 (8)
3 (6)
Atrial tachycardia
8 (15)
8 (15)
validated a novel, simple, reproducible, sensitive,
Mahaim
2 (4)
1 (2)
and specific algorithm based on clinical and ECG pa-
Antidromic AVRT
0 (0)
1 (2)
rameters to discriminate VT from SVT in patients with
(n ¼ 153)
(n ¼ 151)
regular monomorphic WCT. Compared with the cur-
Ischemic
93 (63)
65 (43)
rent standard of care,10,13 the proposed Basel algo-
DCM
32 (21)
49 (32)
Other
28 (18)
37 (25)
ARVC
5 (3)
4 (3)
RVOT
9 (6)
3 (2)
offering a simplified approach based on clear-cut
2 (1)
1 (0.7)
easy-to-use criteria and by avoiding measurements
1 (0.7)
1 (0.7)
of complex and morphology-based parameters that
SVT
VT
Fascicular
HCM
DISCUSSION
By analyzing data from 2 large cohorts of patients
with EP-confirmed diagnosis, we developed and
rithm provides similarly high diagnostic accuracy and
performance characteristics while at the same time
are difficult to assess in the emergency setting (eg, V i /
Values are n (%).
ARVC ¼ arrhythmogenic right ventricular cardiomyopathy; AVNRT ¼ atrioventricular non-reentrant tachycardia; AVRT ¼ atrioventricular re-entrant tachycardia;
DCM ¼ dilated cardiomyopathy; HCM ¼ hypertrophic cardiomyopathy;
RVOT ¼ right ventricular outflow tract; other abbreviations as in Table 1.
V t).23 Since a common shortcoming for the Brugada
and Vereckei algorithms is their lower accuracy in the
“real-world” setting compared with the performance
described in original publications (Supplemental
Moccetti et al
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Basel Algorithm for Diagnosis of SVT/VT
Table 1), 10-12,18,19,23 we sought to further validate the
Basel algorithm in a clinical setting. When applied by
T A B L E 4 Diagnostic Performance Characteristics of the Brugada, 10
Vereckei, 12 and Basel Algorithms
clinicians with different training/background, in a
head-to-head
comparison
against
the
Brugada,
Vereckei, and 3 other previously published algorithms,14-16 the novel Basel algorithm showed a
Sensitivity
Specificity
PPV
NPV
Diagnostic
Accuracy
Derivation cohort (n ¼ 206)
Brugada
92.8
90.6
96.6
81.4
92.2
diagnostic performance similar to that of the Brugada
Vereckei
96.7
86.8
95.5
90.2
94.2
algorithm and higher than that of the Vereckei algo-
Basel
90.8
91.5
88.7
95.9
78.3
rithm, while requiring significantly shorter time for
Criterion I (clinical)
73.9
69.8
87.6
48.1
72.8
diagnosis. This difference in time was most pro-
Criterion II (lead II)
86.9
94.3
97.8
71.4
88.8
Criterion III (lead aVR)
79.1
92.5
96.8
60.5
82.5
nounced when applied by cardiology fellows and internal
medicine
residents.
Such
performance
Validation cohort (n ¼ 203)
Brugada
93.3
88.5
95.9
82.1
92.1
characteristics indicate that the low complexity and
Vereckei
91.3
84.6
94.5
77.2
89.6
high accuracy of the Basel algorithm make it highly
Basel
92.6
93.3
90.4
96.6
82.5
applicable in clinical practice and particularly useful
Criterion I (clinical)
84.7
80.8
92.7
64.4
83.7
for physicians in training to ensure timely diagnosis
Criterion II (lead II)
89.3
84.6
94.4
73.3
88.1
of WCT.
Similar to the lead aVR (Vereckei) algorithm13 and
Criterion III (lead aVR)
86.0
96.1
98.5
70.0
88.6
the R-wave peak time (RWPT) algorithm,14 the Basel
Values are %.
NPV ¼ negative predictive value; PPV ¼ positive predictive value.
algorithm is based on the analysis of the electrical
vector in the frontal plane only. However, the aforementioned algorithms operate based on only 1 lead
(leads aVR or II), with the diagnosis of WCT primarily
CLINICAL IMPLICATIONS. The Basel WCT algorithm
determined by R-wave parameters. Alongside clinical
can be used for a quick and accurate differential
parameters highly sensitive for VT, the Basel algo-
diagnosis of WCT by EP and non-EP practitioners. Of
rithm offers an integrated yet simplified and accurate
note, the focus on leads aVR and II in the Basel al-
version of 2 ECG criteria from the 2 aforementioned
gorithm make it potentially suitable for the use in
algorithms: RWPT >40 ms in lead aVR, which is the
emergency settings and for incorporation in Holter
second step of the Vereckei algorithm,
13
and a posi-
tive or negative RWPT $50 ms in lead II, the criterion
14
and telemetry analysis software that include information on only limb leads.
The theory behind
STUDY LIMITATIONS. The findings of this study
both criteria is that SVT with bundle branch block
should be viewed in the light of a few potential limi-
results in rapid initial activation of the ventricular
tations. 1) The derivation and validation cohorts
myocardium owing to impulse conductance through
comprised patients from tertiary EP centers, so referral
the His-Purkinje system (steeper QRS in both aVR and
bias cannot be excluded. 2) All patients included in this
II leads), with a delayed muscle-to-muscle spread of
study had EP-confirmed diagnoses. While this meth-
activation, resulting in widening of the terminal QRS.
odology allows having a criterion standard for diag-
In contrast, during VT, initial ventricular activation is
nosing the mechanism of WCT, a selection bias might
through muscle-to-muscle spread of the impulse,
be present because not all patients with WCT undergo
which is slower than terminal activation mediated
an EP study. 3) Both cohorts contained a relatively low
through the His-Purkinje system after the impulse
number of cases with preexcitation-related tachy-
reaches the conduction system. This results in
cardia. Although pre-excited SVTs are a rare cause of
steeper terminal QRS.
WCT,13 the Basel algorithm needs to be further studied
behind the RWPT algorithm.
It should be recognized that identifying the initia-
in those cases. 4) For some of the patients, more than 1
tion, peak, and termination of the QRS complex might
VT ECG was included. These were, however, ECGs from
at times be challenging for any given single lead,
different VTs with different ECG morphologies. 5)
particularly for aVR13; thus, integration of 2 limb leads
Neither our approach nor the available algorithms are
in the Basel algorithm will likely help in determining
perfect. Given the rapid implementation of techno-
the time to first peak in either of the leads, when
logic advances in clinical care, development of an
measurements in single leads are difficult. Further
automated application that uses a complex WCT dif-
prospective studies comparing the Basel algorithm
ferential algorithm, with incorporation of the Basel
with other proposed criteria are needed to determine
and or other WCT algorithm, might enable a more ac-
the validity of our criteria in distinguishing between
curate and quicker differential diagnosis of WCT in the
VT and SVT with wide QRS complexes.
near future.
837
838
Moccetti et al
JACC: CLINICAL ELECTROPHYSIOLOGY VOL. 8, NO. 7, 2022
JULY 2022:831–839
Basel Algorithm for Diagnosis of SVT/VT
F I G U R E 3 Clinical Validation of the Basel Algorithm
Comparison of sensitivity, specificity, diagnostic accuracy, and average time for electrocardiographic analysis of the Basel algorithm with the
Vereckei,13 Brugada,10 Jastrzebski,15 Pava,14 and Chen16 algorithms based on a subset of the derivation cohort and stratified by the observers’
specialties. EP ¼ electrophysiology; IM ¼ internal medicine.
CONCLUSIONS
reached in a shorter time, particularly when applied
by physicians in training.
We constructed an easy-to-use and accurate algo-
FUNDING SUPPORT AND AUTHOR DISCLOSURES
rithm to distinguish VT from SVT with aberrant conduction with the use of a 6-lead limb ECG. The Basel
Dr Schaer has received personal fees from Medtronic. Dr Kühne has
algorithm consists of 3 criteria and had a performance
received grants from the Swiss National Science Foundation, the Swiss
similar to that of the established Brugada and Ver-
Heart Foundation, Daiichi-Sankyo, Bayer, Pfizer BMS, and Boston
Scientific; and has received personal fees from Bayer, Boehringer
eckei algorithms in both derivation and validation
Ingelheim, Pfizer BMS, Daiichi-Sankyo, Medtronic, Biotronik, Boston
cohorts. When applied by physicians with different
Scientific, and Johnson & Johnson, all outside the submitted work. Dr
training levels and backgrounds, the novel algorithm
showed a high accuracy similar to the Brugada and
Vereckei algorithms while allowing a diagnosis to be
Henrikson has received fellowship support from Abbott, Boston Scientific, and Medtronic; and has served as chair of the clinical endpoints
committee for Biotronik. Dr Sticherling has received grants from
Biosense-Webster; and has received lecture fees from Abbott,
Moccetti et al
JACC: CLINICAL ELECTROPHYSIOLOGY VOL. 8, NO. 7, 2022
JULY 2022:831–839
Basel Algorithm for Diagnosis of SVT/VT
Medtronic, Biosense-Webster, Boston Scientific, Microport, and Biotronik. Dr Reichlin has received speaker/consulting honoraria or travel
PERSPECTIVES
support from Abbott/SJM, AstraZeneca, Brahms, Bayer, BiosenseWebster, Biotronik, Boston-Scientific, Daiichi-Sankyo, Medtronic,
Pfizer BMS, and Roche, all for work outside the submitted study; and
has received support for his institution’s fellowship program from
COMPETENCY IN MEDICAL KNOWLEDGE: The novel
algorithm can be used for rapid and accurate differential diag-
Abbott/SJM, Biosense-Webster, Biotronik, Boston-Scientific, and
nosis of wide QRS complex tachycardias by physicians with
Medtronic for work outside the submitted study. All other authors have
different backgrounds and training levels.
reported that they have no relationships relevant to the contents of this
paper to disclose.
ADDRESS
FOR
CORRESPONDENCE:
Prof Tobias
Reichlin, Department of Cardiology, Inselspital, Bern
University Hospital, University of Bern, Freiburgstrasse 10, CH-3010 Bern, Switzerland. E-mail: tobias.
TRANSLATIONAL OUTLOOK :The development of automated applications using combinations of complex algorithms
might further improve the differential diagnosis of wide QRS
complex tachycardias.
reichlin@insel.ch.
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A PP END IX For supplemental tables and a
figure, please see the online version of this
paper.
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