Accuracy of Cardiac Arrhythmias and Conduction Disorders Diagnosis Using a Smartwatch

NCT04437914 | Recruiting DMC

• 1 other identifier: FUPiaui
• Study Type: observational
• Target: 110
• Locations: 1 country
• Sites: 1

Brief Summary

Implantable devices increase the detection of silent atrial fibrillation in high-risk populations, being a useful tool in the early diagnosis of these patients, allowing monitoring for a longer time. Currently, these devices can be used for monitoring and possible early diagnosis of abnormalities in order to prevent health complications and bring about better outcomes, as well as monitor the user's progress and thus prevent more serious developments. Objective: to analyze, in patients with cardiovascular disease, the electrocardiographic aspects detected from the device in comparison to the conventional electrocardiogram, identifying aspects of similarity between the tracings obtained and automatic diagnostic accuracy by the device and by the visual assessment of the tracing. Method: a cross-sectional observational study of diagnostic accuracy will be carried out at the University Hospital of the Federal University of Piaui. The following parameters were considered: significance level of 95%, test power of 80%, value of the disease diagnosis rate of 84%, area under the receiver operating characteristic curve of 94% and an equal proportion of the number of positive and negative cases. The minimum sample size consisted of 100 patients, and an additional 10% will be added to compensate for possible losses. A total of 110 patients will be invited to participate in the study. Patients aged ≥ 18 years will be included, with the presence of one or more diagnoses below: systemic arterial hypertension, heart failure, valvular disease, coronary atherosclerotic disease, myocardial infarction, endocarditis, myocarditis, diabetes, cardiac arrhythmias and patients with cardiac pace or implantable automatic defibrillator. The variables analyzed will be: clinical-demographic data of the patients, including age, sex, race, socioeconomic profile; comorbidities and electrocardiographic findings as measured by the clock and conventional ECG. The data will be analyzed comparatively between the groups: 1 = EKG on the clock; 2 = 12-lead conventional EKG and DI (single lead). The primary outcome will be the positive diagnostic correlation of the data obtained in group 1 in relation to group 2. Secondary outcomes: successful measurement of the electrocardiographic record by the clock; diagnostic accuracy of atrial fibrillation and other heart rhythm disorders.

Conditions

Cardiovascular Diseases; Cardiac Arrhythmia; Conduction Disturbance

Keywords

Artificial Intelligence; Cardiac Arrhythmia; Smartwatch; Cardiac Conduction System Disturbance

Outcome Measures

Primary Outcomes (1)

• Positive diagnostic correlation

  Positive diagnostic correlation of the data obtained in group 1 (clock) in relation to group 2 (conventional ECG 12 leads and DI - single lead).

  30 days

Secondary Outcomes (2)

• Diagnostic accuracy 1

  30 days

• Diagnostic accuracy 2

  30 days

Study Arms (2)

Group 1 - Smartwatch - single lead (D1)

To obtain the automatic electrocardiographic diagnosis of the clock, two ECG tracings of 30 seconds will be obtained, in a calm environment, with the patient at rest, in the horizontal supine position. The device will be attached to the wrist on the left side with the use of the fingers of the right hand on the sensor button of the watch to complete the electrocardiographic DI derivation following the Einthoven triangle derivation criteria. The automatic diagnosis obtained must be the same in both plots to be validated. The specific results of the automatic diagnosis obtained by the watch will be: low beats with FC≤40 beats per minute (bpm); high beats with HR≥120bpm; sinus rhythm when interpreted as normal by the clock, atrial fibrillation, inconclusive and does not allow analysis due to poor technical quality and did not allow tracing.

Diagnostic Test: Electrocardiogram diagnosis

Group 2 - conventional ECG

The conventional ECG tracing will be obtained in the 12 leads of the frontal plane (DI, DII, DIII, aVR, AVL, AVF) and the horizontal plane (V1 to V6) and a 30-second rhythm trace in the DI lead. The diagnostic results of conventional ECG tracings will be: normal or abnormal; sinus rhythm, AF, atrial flutter or other non-sinus rhythm; intraventricular conduction disorder: left bundle branch block (BRE), right bundle branch block (BRD), right posteroinferior lower block (BDPI or left anterior superior (BDAS), isolated or associated; normal electrical axis, shifted to the right or shifted to the right) left, inconclusive and does not allow analysis due to poor technical quality.

Interventions

Electrocardiogram diagnosis DIAGNOSTIC_TEST

Electrocardiographic diagnosis will be made in a double-blind manner by two specialists in cardiology and cardiac arrhythmias and the results will be compared between the groups studied.

Group 1 - Smartwatch - single lead (D1)

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Patients followed up in the cardiology sector, hospitalized or outpatient, with the presence of the inclusion criteria and without exclusion criteria. The sample size was calculated using MedCalc Statistical Software version 19.2.3 (MedCalc Software Ltd, Ostend, Belgium). For the sample calculation, the following parameters were considered: significance level of 95%, test power of 80%, value of the disease diagnosis rate of 84%, area under the ROC curve of 94% and equal proportion of number of positive and negative cases. The minimum sample size consisted of 100 patients, and an additional 10% will be added to compensate for possible losses. A total of 110 patients will be invited to participate in the study.

You may qualify if:

• Age ≥ 18 years;
• Presence of one or more of the following diagnoses: systemic arterial hypertension, heart failure, valve disease, coronary atherosclerotic disease, myocardial infarction, endocarditis, myocarditis, diabetes, cardiac arrhythmias and patients with cardiac pacemakers or implantable automatic defibrillators.

You may not qualify if:

• Patients who have electrocardiographic tracings, whether obtained from the watch or the conventional method, of poor quality that make it impossible or that makes the diagnosis difficult due to the technical aspect of the performance.
• Withdrawal of the consent form at the request of the patient or guardian.

Sponsors & Collaborators

• Federal University of Piaui: lead

Study Sites (1)

Carlos Eduardo B. de Lima

Teresina, Piauí, 64048-350, Brazil

RECRUITING

Related Publications (1)

• Lima C, Martinelli M, Peixoto GL, Siqueira SF, Wajngarten M, Silva RT, Costa R, Filho R, Ramires JA. Silent Atrial Fibrillation in Elderly Pacemaker Users: A Randomized Trial Using Home Monitoring. Ann Noninvasive Electrocardiol. 2016 May;21(3):246-55. doi: 10.1111/anec.12294. Epub 2015 Sep 28.

  PMID: 26413928 RESULT

MeSH Terms

Conditions

Cardiovascular Diseases; Arrhythmias, Cardiac

Condition Hierarchy (Ancestors)

Heart Diseases; Pathologic Processes; Pathological Conditions, Signs and Symptoms

Study Officials

• Carlos Eduardo B de Lima, MD, PhD

  Federal University of Piaui

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Carlos Eduardo B. Lima, MD, PhD

CONTACT

+5586981805000; carlos.lima@ufpi.edu.br

Carlos Eduardo B. Lima, MD, PhD

CONTACT

+55863085-3048; cardiolima.medicalcenter@hotmail.com.br

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: CROSS SECTIONAL
• Target Duration: 6 Months
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor of Medicine (Cardiology)

Study Record Dates

• First Submitted: June 16, 2020
• First Posted: June 18, 2020
• Study Start: June 7, 2021
• Primary Completion: August 30, 2024
• Study Completion: June 30, 2025
• Last Updated: September 25, 2024

Record last verified: 2024-09

Data Sharing

• IPD Sharing: Will not share

Locations

BR (1)