Methods
Design and study population From February 2012 to May 2013, 14
667 children and young-adults (aged 40 years-old or less) of the central
region of Portugal participated in the SCD-SOS survey (NCT01845909). It
included a 12-lead ECG and a previously validated (5) questionnaire
about symptoms, personal and family history that was filled by 11878
patients willing to provide more information (Supplementary
Material 1 ). The SCD-SOS protocol was approved by the local Ethics
Committee (355/Sec/10/03/2011), Comissão de Ética do Centro Hospitalar
de Coimbra, Instituto Português do Ritmo Cardíaco e Comissão Nacional de
Protecção de Dados.
SCD-SOS Survey and etiologic evaluation This was a detailed,
digital-based, self-administered questionnaire, mainly composed of
multiple-choice questions and few boxes allowing participants to provide
additional details on their answers. It deemed to explore relevant
clinical characteristics in the setting of SCD risk, and detect syncope
related to potential causes of SCD. Based on the answers provided
(Supplementary Material 1 ), we were able to determine the most
probable etiology of the TLOC episodes reported. According to the 2018
ESC syncope guidelines, (7) reflex syncope (RS), either vasovagal or
situational, was assumed in individuals who reported an episode
precipitated by pain, emotion, fear, warm environment, or standing, with
or without at least one typical progressive prodrome (pallor, sweating,
and/or nausea). Orthostatic hypotension was presumed if syncope after or
while standing was described in the absence of any of the
previous prodromes, or if volume depletion was presumed based on the
specifications provided (post-surgery, after donating blood). The
remaining causes were ascertained based on the features ticked by the
participants and US was an exclusion diagnosis if any of the previously
described criteria were not satisfied (Figure 1 ). In addition,
we were able to perform a risk stratification of the syncopal event
based on the presence of 4 high-risk features (7) that were included in
the multiple-choice questionnaire: 2 minor - no warning symptoms and a
family history of SCD at young age; and 2 major – syncope during
exertion and palpitations immediately preceding syncope. Participants
could specify whether there were contexts or precipitating factors other
than the ones listed in the questionnaire in a blank field. This allowed
to classify the cases in which head trauma or other diseases were the
causes of TLOC. We did not consider TLOC related to other disease when
only “fever” was specified in the blank field.
Participants also provided information on whether they were physically
active, the type of sports and number of hours practiced per week. There
were questions on whether they had already practiced competitive or
semi-professional sports, and on the timing and duration of competition.
The type of exercise was specified in a box by each participant, thus
allowing the classification of sports into 9 levels of static and/or
dynamic components, based on previously-described hemodynamics and
cardiac adaptations of athletes who compete in each type of exercise.
(8) In the case of individuals who specified more than one modality
(maximum of three), all were individually considered for the purpose of
this analysis.
Finally, we studied potential predictors related to past medical
history. Besides from screening for past personal history of
palpitations, the questionnaire included information about relevant
personal and family history of cardiac disease, as well as specific
cardiac diagnosis in a multiple-choice format.
12-lead ECG analysis A 12-lead ECG was performed in supine
position using a Mortara ELI 10 Portable Resting ECG machine (Mortara
Instrument, Milwaukee, Wisconsin, USA) with a paper speed of 25 mm/s and
amplification of 0.1 mV/mm. The
heart rate, QRS duration, PR and QT interval were registered
using the recorder’s automatic
measurement software (VERITAS ECG algorithm, Mortara Instrument). The QT
corrected (QTc) interval was also automatically obtained using theFridericia correction, which was preset in the device and was
previously validated, as described in a paper published by our group.
(5) And the Bazett formula
(QTc=QT/square root of RR interval) was calculated based on the
automatic QT and RR intervals. The ECG of individuals who reported a
TLOC episode were manually revised by 4 authors (MC, DB, JP and RP) and
the following features were registered: atrioventricular (AV) block,
incomplete and complete right and left bundle branch block (RBBB and
LBBB), left (-30º to -90º) and right (>90º) axis deviation,
ventricular preexcitation and number of premature ventricular complexes
(PVCs). Left ventricular hypertrophy (LVH) was defined according to the
presence of either Sokolow-Lyon (S in V1 + R in V5 or V6 ≥35mm) or
Cornell criteria (S in V3 + R in aVL ≥20mm in men and ≥28mm in woman)
and analysis for associated pathologic ECG findings was performed in the
cases that fulfilled the voltage criteria. (9)
Statistical analysis We performed statistical analysis using
Stata 13.0 software. Categorical
variables were described as numbers of cases and percentages, and
continuous variables as means ± standard deviation or medians
[interquartile ranges] (as appropriate). We used qui-squared tests
to determine whether the presence of clinical and ECG features differed
between individuals with US and the remaining causes of TLOC. To express
the strength of these relations, we obtained the odds ratios (OR) with
95% confidence intervals (CI) through univariate logistic regression
for the outcome US. To compare the distribution of continuous variables
between individuals with US and the remaining causes of TLOC, we used
Student’s t-test or a non-parametric alternative (Mann-Whitney) where
appropriate. Multivariate logistic regression was used for establishing
a US predictor model, using variables significantly associated with US
on univariate analysis. A p-value
< 0.05 was regarded as significant and two-tailed tests were
applied.