The Signal-averaged ElectrocArdiogram in Long Term Follow-up of Chronic CHagas Disease - RIO de Janeiro Cohort (SEARCH-Rio)
|First Received Date ICMJE||April 21, 2011|
|Last Updated Date||December 9, 2013|
|Start Date ICMJE||June 1995|
|Primary Completion Date||March 2001 (Final data collection date for primary outcome measure)|
|Current Primary Outcome Measures ICMJE
||Cardiac death [Time Frame: up to 10 years ] [ Time Frame: up tp 10 years ]
Defined as intractable heart failure, arrhythmic, coronary occlusion, or sudden death.
Assessment twice an year by active and direct contact to subjects or relatives and review of medical records.
|Original Primary Outcome Measures ICMJE||Same as current|
|Change History||Complete list of historical versions of study NCT01340963 on ClinicalTrials.gov Archive Site|
|Current Secondary Outcome Measures ICMJE
|Original Secondary Outcome Measures ICMJE
|Current Other Outcome Measures ICMJE||Not Provided|
|Original Other Outcome Measures ICMJE||Not Provided|
|Brief Title ICMJE||The Signal-averaged ElectrocArdiogram in Long Term Follow-up of Chronic CHagas Disease - RIO de Janeiro Cohort|
|Official Title ICMJE||Prognostic Value of the Spectral Turbulence Analysis of the Signal-averaged Electrocardiogram in Chagas Heart Disease|
The study investigated 100 subjects, both genders, with chronic Chagas disease, confirmed by at least two distinct serological tests, and classified according to Los Andes classification in a long term follow-up aiming at identifying the predictive value of the signal-averaged electrocardiogram for cardiac death and ventricular tachycardia.
All subjects admitted to the study were submitted to clinical history taking, physical examination, and noninvasive assessment, including blood pressure measurement, resting 12-lead surface electrocardiogram, 24h ambulatory electrocardiogram monitoring, M-Mode/two-dimensional echocardiogram, signal-averaged electrocardiogram in both time and frequency domains. Selected subjects were further submitted to treadmill stress test and coronary angiography to rule out coronary heart disease.
Subjects were followed by non-investigational primary care assistance at three to six months scheduled clinical visits on an outpatients basis. Both noninvasive and invasive evaluation during follow-up were requested at discretion of primary evaluation. Adverse outcomes were ascertained by review of medical records and active contact to either study subjects or their relatives.
Longitudinal prospective study, with a cohort of 100 consecutive outpatient subjects (34 to 74 years old; 31 females) with Chagas' disease followed-up for at least 10 years at the cardiomyopathy outpatient clinic of University Hospital, Rio de Janeiro, RJ, Brazil, a tertiary care center. Enrollment was from 1995 to 1999. Subjects were born in endemic regions of Minas Gerais, Goias or Bahia States of Brazil and Chagas' disease was diagnosed on basis of two positive serum tests, hemagglutination cruzipain-ELISA and indirect immunofluorescence. All subjects were referred to the arrhythmia for risk stratification. At the time of admission none had received nitroderivative therapy. Subjects were classified according to the severity of heart involvement according to Los Andes classification, and divided into three groups: class I - 28 subjects (group 1), class II - 48 subjects (group 2), and class III - 24 subjects (group 3). Clinical and laboratory data were assessed during a personal interview and review of medical records. On admission, all subjects were in New York Heart Association functional class I or II, had normal sinus rhythm and normal PR intervals. Exclusion criteria at initial enrollment were: any degree of atrioventricular block or non-sinus rhythm, previous documented acute coronary events (unstable angina or myocardial infarction), chronic obstructive pulmonary disease, rheumatic valvular heart disease, alcohol addiction, thyroid dysfunction or abnormal serum electrolytes. Treadmill stress test and/or coronary artery angiogram were indicated in selected subjects to rule out concomitant coronary artery disease. World Health Organization and Helsinki Treaty regulations reviewed in Venice (1983) were followed and all subjects provided informed consent to participate.
All subjects have been followed-up by the same team of physicians. Medical visits have been scheduled at the outpatient clinics in a three to six-month interval. Medications were prescribed at the discretion of the physician who performed the primary evaluation. Body weight varied <2 kg during follow-up, and serum potassium varied from 3.5 to 5 milliequivalent/L. Mild systemic arterial hypertension (systolic arterial pressure ranging from 140 mmHg and 155 mmHg, or diastolic arterial pressure ranging from 90 mmHg and 105 mmHg) was observed in 41% of the subjects and all received anti-hypertensive medication (converting enzyme inhibitors, diuretics, vasodilators and/or beta-blockers) at the discretion of the physician who performed the primary evaluation in order to reduce blood pressure levels to less than 140/90 mmHg. All regularly followed at scheduled clinical visits. The endpoints were described elsewhere in this registry. All causes of adverse events were ascertained by active search of relatives and review of the medical records.
Resting surface 12-lead ECG and plain chest roentgenogram
For each patient, standard resting 12-lead ECGs were recorded in the supine position (with simultaneous 3-lead acquisition) with a Cardimax ECAPS 12 2000 Compliant Electrocardiograph (Nihon-Kohden Co, Tokyo, Japan). Electrocardiographic abnormalities were classified according to standard criteria for conduction disturbances (intraventricular and atrioventricular), chamber overload, and abnormal Q waves . The electrocardiographic variables assessed is sinus rhythm were: maximum P-wave duration and PR interval (typically in lead II), QRS complex duration (the longest ventricular duration in precordial leads), maximal absolute QRS complex in any precordial lead, presence of bundle branch block and/or left fascicular-block, presence of abnormal Q waves (Q-wave, defined as the first QRS deflection >1-mm deep and >0.04-ms wide), and left atrial overload (P-wave duration in lead II >110 ms or Morris index in V1 >4 millivolt.ms). In antero-septal leads (V1, V2 and V3) and in inferior leads (L2, L3 and aVF) the presence of Q-wave in two out of three leads was considered abnormal. An independent observer blind to the study analyzed the electrocardiographic records that were automatically obtained from electrocardiograph equipment. Subsequent 12-lead resting ECGs were recorded at each clinical visit in order to assess cardiac rhythm during follow-up. Plain chest roentgenogram was carried out on the same day and cardiomegaly was defined by a cardiothoracic ratio of more than 0.50.
M-mode and two-dimensional echocardiograms were performed using an Apogee CX-200 equipment (ATL, Bothell, Washington, USA) with a 4-megahertz broadband transducer. The echocardiograms were analyzed by a trained observer blinded to the study protocol Echocardiographic parameters were assessed according to standard procedures of the Section of Echocardiography of the Department of Cardiology, with special care taken to detect left ventricular apical aneurysms. The echocardiographic parameters assessed were left ventricular ejection fraction (LVEF) calculated by the teichholz method, left atrial diameter (LAD), presence of pulmonary arterial hypertension (defined as maximal pulmonary arterial pressure > 30 mmHg, diastolic dysfunction, and the presence of an apical aneurysm. Normal cut-off value for LVEF was defined as >50%. Routine echocardiograms were performed in order to track changes in LVEF during follow-up.
24h Ambulatory ECG Monitoring
Twenty-four-hour ambulatory ECG monitoring was performed using a three-channel DMS-cassette-tape recorder and carefully analyzed using the Del-Mar Avionics StrataScan System (Del Mar Avionics, Irvine, California, USA) by a trained observer blind to the study in order to assess the presence of ventricular arrhythmia and atrioventricular conduction disturbances. Variables assessed in the 24h ambulatory ECG were: i) isolated premature supraventricular contractions ii) nonsustained supraventricular tachycardia defined as a sequence of three of more supraventricular ectopic beats, iii) isolated premature ventricular contractions, and iv) ventricular tachycardia episodes (defined as: heart rate >100 bpm, QRS duration >120 ms, three or more consecutive ventricular complexes, and atrial-ventricular dissociation).
The standard-deviation of all consecutive normal interbeat intervals in 24h (24h SDNN) was employed to assess heart rate variability. Normal cut-off point was defined at >=100ms. During follow-up, 24h ambulatory ECG were performed at the discretion of attending physician's judgment in order to assess cardiac rhythm and arrhythmia. One trained specialist blind to Los Andes classification groups analyzed all tape recordings immediately after their acquisition.
Signal-averaged electrocardiogram (SAECG) was employed to asses the presence of both ventricular late potentials and intraventricular electrical transients (IVET).
SAECG was acquired in sinus rhythm with a Predictor-IIc equipment (ART Inc., Fitchburg, Massachusetts, USA) using modified XYZ Frank orthogonal leads and QRS-triggered coherent-averaged up to the noise level of 0.3 microvolt. SAECGs were analyzed in both time and frequency domains by an independent observer blinded to the study patients information. After signal average ECG acquisition, time domain analysis was carried out on vector magnitude (VM), using a bidirectional 4th order 40 Hz to 250 Hz band-pass Butterworth filter. The variables extracted from VM were: duration of VM (DUR [ms]), root-mean-squared voltage of last 40ms of VM (RMS40[microvolt]) duration of potentials below 40 microvolt at the terminal portion of VM (LAS40[ms]). Due to the presence of bundle branch block as a common finding in Chagas disease, normal cut-off point for DUR was defined at >150ms.
The onset and offset points of VM delimited the analytic region for frequency domain analysis, by using the spectral turbulence analysis approach. The analytic region in VM was preprocessed to extract the first derivative, aiming at removing the high-amplitude low-frequency components. The derived signal was cut into slices to build a power spectral density time-frequency map by applying the short-time Fourier transform. Each data segment was limited in 25 ms, with 2 ms interval between successive segments to assure adequate time-resolution, tapered by a Blackmann-Harris window after mean removal, and zero-padded to 64 points. After Fourier transform of a particular segment, its spectral amplitude was squared to obtain the estimated power spectral density function. Successive power spectral density function estimates in the analytic region were attached in a three-dimensional map. The boundaries of the analytic region (up to 200 ms duration) were placed 25 ms prior to the onset of the VM and to a point on the ST segment 50 ms after the offset of the VM. In the time frequency map, spectral turbulence was studied by comparing sequential spectral estimates. We calculated Pearson's correlation coefficient between adjacent power spectral function estimates throughout ventricular activation, and deployed the correlation coefficients in a time series, of which the mean and the standard deviation of the intersegment spectral correlation (abbreviated as MSC and SSC, respectively) were calculated. Additionally, we calculated the frequency corresponding to 80% of the total area under a particular power spectral function estimate, starting at zero Hz, which practically represented the edge or the border, and deployed the edge frequency, thus calculated, in a time series. The mean and the standard deviation of the electrical transients (abbreviated as MET and SET, respectively) of the edge frequency series were extracted. Power spectral estimates were limited to the range from 0 to 300 Hz in order to avoid interference of high frequency noise during correlation. MSC and SSC were multiplied by 100 to simplify calculations. Normality threshold values have been defined previously as MSC>94, SSC<=6, MET<=78 and The SET<=31. The presence of intraventricular electrical transients (IVET+) was optimally defined when 2 out of 4 variables were outside normality range. We used the above method based on our hypothesis that the presence of high frequency electrical transients, representing underlying electrically unstable myocardial areas, would determine the reduction of intersegment correlation. Likewise, high frequency transients would increase the energy content of a spectral estimate and the shift the spectral border rightward, to a higher frequency.
|Study Type ICMJE||Observational|
|Study Design ICMJE||Observational Model: Cohort
Time Perspective: Prospective
|Target Follow-Up Duration||Not Provided|
|Sampling Method||Non-Probability Sample|
|Study Population||One hundred clinically stable subjects with at least 10 years of regular outpatients follow-up and positive epidemiological history and serological confirmation of Chagas disease with ate least two immunological tests.|
|Intervention ICMJE||Not Provided|
* Includes publications given by the data provider as well as publications identified by ClinicalTrials.gov Identifier (NCT Number) in Medline.
|Recruitment Status ICMJE||Completed|
|Completion Date||December 2012|
|Primary Completion Date||March 2001 (Final data collection date for primary outcome measure)|
|Eligibility Criteria ICMJE||
|Ages||18 Years to 75 Years (Adult, Senior)|
|Accepts Healthy Volunteers||No|
|Contacts ICMJE||Contact information is only displayed when the study is recruiting subjects|
|Listed Location Countries ICMJE||United States, Brazil|
|Removed Location Countries|
|NCT Number ICMJE||NCT01340963|
|Other Study ID Numbers ICMJE||012345/96|
|Has Data Monitoring Committee||Yes|
|U.S. FDA-regulated Product||Not Provided|
|Plan to Share Data||Not Provided|
|IPD Description||Not Provided|
|Responsible Party||Paulo Roberto Benchimol Barbosa, Universidade Gama Filho|
|Study Sponsor ICMJE||Universidade Gama Filho|
|Information Provided By||Universidade Gama Filho|
|Verification Date||December 2013|
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