Trial Outcomes & Findings for Screening for Pregnancy Related Heart Failure in Nigeria (NCT NCT05438576)
NCT ID: NCT05438576
Last Updated: 2025-05-16
Results Overview
Number of participants diagnosed with left ventricular ejection fraction (LVEF) \<50% by echocardiography during pregnancy or within 12 months postpartum.
Recruitment status
COMPLETED
Study phase
NA
Target enrollment
1232 participants
Primary outcome timeframe
18 months
Results posted on
2025-05-16
Participant Flow
Participant milestones
| Measure |
Intervention
Participants had ECGs analyzed with artificial intelligence for cardiomyopathy detection.
Digital stethoscope electrocardiogram: Digital stethoscope artificial intelligence enabled electrocardiogram (AI-ECG). An artificial intelligence algorithm which analyses ECG data and generates prediction probabilities for a diagnosis of cardiomyopathy.
|
Control
Participants had standard clinical ECGs acquired.
|
|---|---|---|
|
Overall Study
STARTED
|
616
|
616
|
|
Overall Study
COMPLETED
|
587
|
608
|
|
Overall Study
NOT COMPLETED
|
29
|
8
|
Reasons for withdrawal
| Measure |
Intervention
Participants had ECGs analyzed with artificial intelligence for cardiomyopathy detection.
Digital stethoscope electrocardiogram: Digital stethoscope artificial intelligence enabled electrocardiogram (AI-ECG). An artificial intelligence algorithm which analyses ECG data and generates prediction probabilities for a diagnosis of cardiomyopathy.
|
Control
Participants had standard clinical ECGs acquired.
|
|---|---|---|
|
Overall Study
Death
|
1
|
1
|
|
Overall Study
Withdrawal by Subject
|
4
|
2
|
|
Overall Study
Not Eligible
|
2
|
1
|
|
Overall Study
Did not complete baseline testing
|
22
|
4
|
Baseline Characteristics
Screening for Pregnancy Related Heart Failure in Nigeria
Baseline characteristics by cohort
| Measure |
Intervention
n=587 Participants
Participants had ECGs analyzed with artificial intelligence for cardiomyopathy detection.
Digital stethoscope electrocardiogram: Digital stethoscope artificial intelligence enabled electrocardiogram (AI-ECG). An artificial intelligence algorithm which analyses ECG data and generates prediction probabilities for a diagnosis of cardiomyopathy.
|
Control
n=608 Participants
Participants had standard clinical ECGs acquired.
|
Total
n=1195 Participants
Total of all reporting groups
|
|---|---|---|---|
|
Age, Continuous
|
31 years
n=99 Participants
|
31 years
n=107 Participants
|
31 years
n=206 Participants
|
|
Sex: Female, Male
Female
|
587 Participants
n=99 Participants
|
608 Participants
n=107 Participants
|
1195 Participants
n=206 Participants
|
|
Sex: Female, Male
Male
|
0 Participants
n=99 Participants
|
0 Participants
n=107 Participants
|
0 Participants
n=206 Participants
|
|
Race (NIH/OMB)
American Indian or Alaska Native
|
0 Participants
n=99 Participants
|
0 Participants
n=107 Participants
|
0 Participants
n=206 Participants
|
|
Race (NIH/OMB)
Asian
|
0 Participants
n=99 Participants
|
0 Participants
n=107 Participants
|
0 Participants
n=206 Participants
|
|
Race (NIH/OMB)
Native Hawaiian or Other Pacific Islander
|
0 Participants
n=99 Participants
|
0 Participants
n=107 Participants
|
0 Participants
n=206 Participants
|
|
Race (NIH/OMB)
Black or African American
|
587 Participants
n=99 Participants
|
608 Participants
n=107 Participants
|
1195 Participants
n=206 Participants
|
|
Race (NIH/OMB)
White
|
0 Participants
n=99 Participants
|
0 Participants
n=107 Participants
|
0 Participants
n=206 Participants
|
|
Race (NIH/OMB)
More than one race
|
0 Participants
n=99 Participants
|
0 Participants
n=107 Participants
|
0 Participants
n=206 Participants
|
|
Race (NIH/OMB)
Unknown or Not Reported
|
0 Participants
n=99 Participants
|
0 Participants
n=107 Participants
|
0 Participants
n=206 Participants
|
|
Race/Ethnicity, Customized
Ethnicity - Hausa
|
163 Participants
n=99 Participants
|
174 Participants
n=107 Participants
|
337 Participants
n=206 Participants
|
|
Race/Ethnicity, Customized
Ethnicity - Igbo
|
61 Participants
n=99 Participants
|
68 Participants
n=107 Participants
|
129 Participants
n=206 Participants
|
|
Race/Ethnicity, Customized
Ethnicity - other
|
35 Participants
n=99 Participants
|
41 Participants
n=107 Participants
|
76 Participants
n=206 Participants
|
|
Race/Ethnicity, Customized
Ethnicity - Yoruba
|
328 Participants
n=99 Participants
|
325 Participants
n=107 Participants
|
653 Participants
n=206 Participants
|
|
Region of Enrollment
Nigeria
|
587 participants
n=99 Participants
|
608 participants
n=107 Participants
|
1195 participants
n=206 Participants
|
PRIMARY outcome
Timeframe: 18 monthsPopulation: Analysis was categorized by pregnant and post-partum participants. Total of each group equals the overall number of participants analyzed per arm.
Number of participants diagnosed with left ventricular ejection fraction (LVEF) \<50% by echocardiography during pregnancy or within 12 months postpartum.
Outcome measures
| Measure |
Intervention
n=587 Participants
Participants had ECGs analyzed with artificial intelligence for cardiomyopathy detection.
Digital stethoscope electrocardiogram: Digital stethoscope artificial intelligence enabled electrocardiogram (AI-ECG). An artificial intelligence algorithm which analyses ECG data and generates prediction probabilities for a diagnosis of cardiomyopathy.
|
Control
n=608 Participants
Participants had standard clinical ECGs acquired.
|
|---|---|---|
|
Left Ventricular Ejection Fraction (LVEF) <50%
Pregnant
|
3 Participants
|
1 Participants
|
|
Left Ventricular Ejection Fraction (LVEF) <50%
Post partum
|
21 Participants
|
11 Participants
|
SECONDARY outcome
Timeframe: 18 monthsPopulation: To explain the differences in number analyzed for each section below, details are provided: Sensitivity, is calculated as True Positive (TP) / (TP + FN), as such the denominator in this case is 17. Specificity is calculated as True Negatives (TN) divided by True Negatives and False Positives (TN + FP), and the denominator is 563. Positive Predictive Value (PPV) = TP / (TP + FP), with a denominator of 122 and Negative Predictive Value (PPV) = TN / (TN + FN) with a denominator of 458.
This is defined as a positive point-of-care AI prediction for LVEF ≤ 35% (maximum prediction across all stethoscope recording locations) confirmed with echocardiography
Outcome measures
| Measure |
Intervention
n=587 Participants
Participants had ECGs analyzed with artificial intelligence for cardiomyopathy detection.
Digital stethoscope electrocardiogram: Digital stethoscope artificial intelligence enabled electrocardiogram (AI-ECG). An artificial intelligence algorithm which analyses ECG data and generates prediction probabilities for a diagnosis of cardiomyopathy.
|
Control
Participants had standard clinical ECGs acquired.
|
|---|---|---|
|
Effectiveness of AI-ECG for Cardiomyopathy Detection in the Intervention Arm for Left Ventricular Ejection Fraction (LVEF) ≤ 35%
LVEF ≤ 35% (Sensitivity)
|
17 Participants
|
—
|
|
Effectiveness of AI-ECG for Cardiomyopathy Detection in the Intervention Arm for Left Ventricular Ejection Fraction (LVEF) ≤ 35%
LVEF ≤ 35% (Specificity)
|
458 Participants
|
—
|
|
Effectiveness of AI-ECG for Cardiomyopathy Detection in the Intervention Arm for Left Ventricular Ejection Fraction (LVEF) ≤ 35%
LVEF ≤ 35% (PPV)
|
17 Participants
|
—
|
|
Effectiveness of AI-ECG for Cardiomyopathy Detection in the Intervention Arm for Left Ventricular Ejection Fraction (LVEF) ≤ 35%
LVEF ≤ 35% (NPV)
|
458 Participants
|
—
|
SECONDARY outcome
Timeframe: 18 monthsPopulation: To explain the differences in number analyzed for each section below, details are provided: Sensitivity, is calculated as True Positive (TP) / (TP + FN), as such the denominator in this case is 20. Specificity is calculated as True Negatives (TN) divided by True Negatives and False Positives (TN + FP), and the denominator is 560. Positive Predictive Value (PPV) = TP / (TP + FP), with a denominator of 122 and Negative Predictive Value (PPV) = TN / (TN + FN) with a denominator of 458.
This is defined as a positive point-of-care AI prediction for LVEF \< 40% (maximum prediction across all stethoscope recording locations) confirmed with echocardiography
Outcome measures
| Measure |
Intervention
n=587 Participants
Participants had ECGs analyzed with artificial intelligence for cardiomyopathy detection.
Digital stethoscope electrocardiogram: Digital stethoscope artificial intelligence enabled electrocardiogram (AI-ECG). An artificial intelligence algorithm which analyses ECG data and generates prediction probabilities for a diagnosis of cardiomyopathy.
|
Control
Participants had standard clinical ECGs acquired.
|
|---|---|---|
|
Effectiveness AI-ECG for Cardiomyopathy Detection in the Intervention Arm in LVEF < 40%
LVEF < 40% (Sensitivity)
|
20 Participants
|
—
|
|
Effectiveness AI-ECG for Cardiomyopathy Detection in the Intervention Arm in LVEF < 40%
LVEF < 40% (Specificity)
|
458 Participants
|
—
|
|
Effectiveness AI-ECG for Cardiomyopathy Detection in the Intervention Arm in LVEF < 40%
LVEF < 40% (PPV)
|
20 Participants
|
—
|
|
Effectiveness AI-ECG for Cardiomyopathy Detection in the Intervention Arm in LVEF < 40%
LVEF < 40% (NPV)
|
458 Participants
|
—
|
SECONDARY outcome
Timeframe: 18 monthsPopulation: To explain the differences in number analyzed for each section below, details are provided: Sensitivity, is calculated as True Positive (TP) / (TP + FN), as such the denominator in this case is 23. Specificity is calculated as True Negatives (TN) divided by True Negatives and False Positives (TN + FP), and the denominator is 557. Positive Predictive Value (PPV) = TP / (TP + FP), with a denominator of 122 and Negative Predictive Value (PPV) = TN / (TN + FN) with a denominator of 458.
This is defined as a positive point-of-care AI prediction for LVEF \<45% (maximum prediction across all stethoscope recording locations) confirmed with echocardiography
Outcome measures
| Measure |
Intervention
n=587 Participants
Participants had ECGs analyzed with artificial intelligence for cardiomyopathy detection.
Digital stethoscope electrocardiogram: Digital stethoscope artificial intelligence enabled electrocardiogram (AI-ECG). An artificial intelligence algorithm which analyses ECG data and generates prediction probabilities for a diagnosis of cardiomyopathy.
|
Control
Participants had standard clinical ECGs acquired.
|
|---|---|---|
|
Effectiveness AI-ECG for Cardiomyopathy Detection in the Intervention Arm in LVEF < 45%
LVEF < 45% (Sensitivity)
|
22 Participants
|
—
|
|
Effectiveness AI-ECG for Cardiomyopathy Detection in the Intervention Arm in LVEF < 45%
LVEF < 45% (Specificity)
|
457 Participants
|
—
|
|
Effectiveness AI-ECG for Cardiomyopathy Detection in the Intervention Arm in LVEF < 45%
LVEF < 45% (PPV)
|
22 Participants
|
—
|
|
Effectiveness AI-ECG for Cardiomyopathy Detection in the Intervention Arm in LVEF < 45%
LVEF < 45% (NPV)
|
457 Participants
|
—
|
SECONDARY outcome
Timeframe: 18 monthsPopulation: To explain the differences in number analyzed for each section below, details are provided: Sensitivity, is calculated as True Positive (TP) / (TP + FN), as such the denominator in this case is 23. Specificity is calculated as True Negatives (TN) divided by True Negatives and False Positives (TN + FP), and the denominator is 557. Positive Predictive Value (PPV) = TP / (TP + FP), with a denominator of 122 and Negative Predictive Value (PPV) = TN / (TN + FN) with a denominator of 458.
This is defined as a positive point-of-care AI prediction for LVEF \<50% (maximum prediction across all stethoscope recording locations) confirmed with echocardiography
Outcome measures
| Measure |
Intervention
n=587 Participants
Participants had ECGs analyzed with artificial intelligence for cardiomyopathy detection.
Digital stethoscope electrocardiogram: Digital stethoscope artificial intelligence enabled electrocardiogram (AI-ECG). An artificial intelligence algorithm which analyses ECG data and generates prediction probabilities for a diagnosis of cardiomyopathy.
|
Control
Participants had standard clinical ECGs acquired.
|
|---|---|---|
|
Effectiveness AI-ECG for Cardiomyopathy Detection in the Intervention Arm in LVEF < 50%
LVEF < 50% (Sensitivity)
|
22 Participants
|
—
|
|
Effectiveness AI-ECG for Cardiomyopathy Detection in the Intervention Arm in LVEF < 50%
LVEF < 50% (Specificity)
|
457 Participants
|
—
|
|
Effectiveness AI-ECG for Cardiomyopathy Detection in the Intervention Arm in LVEF < 50%
LVEF < 50% (PPV)
|
22 Participants
|
—
|
|
Effectiveness AI-ECG for Cardiomyopathy Detection in the Intervention Arm in LVEF < 50%
LVEF < 50% (NPV)
|
457 Participants
|
—
|
OTHER_PRE_SPECIFIED outcome
Timeframe: 18 monthsThe number of subjects to experience composite cardiovascular events with include any of the following: diastolic heart failure, gestational hypertension, pre-eclampsia, eclampsia, valvular heart disease, atrial arrhythmias and sustained ventricular arrhythmias.
Outcome measures
| Measure |
Intervention
n=587 Participants
Participants had ECGs analyzed with artificial intelligence for cardiomyopathy detection.
Digital stethoscope electrocardiogram: Digital stethoscope artificial intelligence enabled electrocardiogram (AI-ECG). An artificial intelligence algorithm which analyses ECG data and generates prediction probabilities for a diagnosis of cardiomyopathy.
|
Control
n=608 Participants
Participants had standard clinical ECGs acquired.
|
|---|---|---|
|
Composite Adverse Cardiovascular Events
|
56 Participants
|
53 Participants
|
OTHER_PRE_SPECIFIED outcome
Timeframe: 18 monthsPopulation: Data was not collected nor analyzed for this outcome measure
Determine the impact of an AI-ECG on echocardiography utilization
Outcome measures
Outcome data not reported
OTHER_PRE_SPECIFIED outcome
Timeframe: 18 monthsPopulation: Data was not collected nor analyzed for this outcome measure
Develop and evaluate the diagnostic performance of an AI-enhanced point of care screening tool
Outcome measures
Outcome data not reported
Adverse Events
Intervention
Serious events: 56 serious events
Other events: 1 other events
Deaths: 12 deaths
Control
Serious events: 53 serious events
Other events: 4 other events
Deaths: 3 deaths
Serious adverse events
| Measure |
Intervention
n=587 participants at risk
Participants had ECGs analyzed with artificial intelligence for cardiomyopathy detection.
Digital stethoscope electrocardiogram: Digital stethoscope artificial intelligence enabled electrocardiogram (AI-ECG). An artificial intelligence algorithm which analyses ECG data and generates prediction probabilities for a diagnosis of cardiomyopathy.
|
Control
n=608 participants at risk
Participants had standard clinical ECGs acquired.
|
|---|---|---|
|
Cardiac disorders
Diastolic heart failure
|
0.34%
2/587 • Long-term clinical outcomes including mortality were passively tracked for all participants (for up to 18 months) beyond the duration of active trial participation. These outcomes are also described as "adverse cardiovascular events" in order to match prevailing descriptions in published literature but are completely unrelated to the study intervention. Study defined adverse events per protocol were collected for up to 3 hours following study intervention (ECG and Echo recording).
Anticipated study related risk is limited to potential skin irritation from placement of ECG lead electrode stickers directly on the skin for ECG measurements. The "adverse cardiovascular events" reported in the manuscript are not "events" in the context of this clinical trial. They are described collectively as "adverse cardiovascular events" to facilitate a comprehensive grouping for descriptive and summarization purposes, and to ensure consistency with the existing literature.
|
0.16%
1/608 • Long-term clinical outcomes including mortality were passively tracked for all participants (for up to 18 months) beyond the duration of active trial participation. These outcomes are also described as "adverse cardiovascular events" in order to match prevailing descriptions in published literature but are completely unrelated to the study intervention. Study defined adverse events per protocol were collected for up to 3 hours following study intervention (ECG and Echo recording).
Anticipated study related risk is limited to potential skin irritation from placement of ECG lead electrode stickers directly on the skin for ECG measurements. The "adverse cardiovascular events" reported in the manuscript are not "events" in the context of this clinical trial. They are described collectively as "adverse cardiovascular events" to facilitate a comprehensive grouping for descriptive and summarization purposes, and to ensure consistency with the existing literature.
|
|
Cardiac disorders
Atrial Arrhythmias
|
0.00%
0/587 • Long-term clinical outcomes including mortality were passively tracked for all participants (for up to 18 months) beyond the duration of active trial participation. These outcomes are also described as "adverse cardiovascular events" in order to match prevailing descriptions in published literature but are completely unrelated to the study intervention. Study defined adverse events per protocol were collected for up to 3 hours following study intervention (ECG and Echo recording).
Anticipated study related risk is limited to potential skin irritation from placement of ECG lead electrode stickers directly on the skin for ECG measurements. The "adverse cardiovascular events" reported in the manuscript are not "events" in the context of this clinical trial. They are described collectively as "adverse cardiovascular events" to facilitate a comprehensive grouping for descriptive and summarization purposes, and to ensure consistency with the existing literature.
|
0.00%
0/608 • Long-term clinical outcomes including mortality were passively tracked for all participants (for up to 18 months) beyond the duration of active trial participation. These outcomes are also described as "adverse cardiovascular events" in order to match prevailing descriptions in published literature but are completely unrelated to the study intervention. Study defined adverse events per protocol were collected for up to 3 hours following study intervention (ECG and Echo recording).
Anticipated study related risk is limited to potential skin irritation from placement of ECG lead electrode stickers directly on the skin for ECG measurements. The "adverse cardiovascular events" reported in the manuscript are not "events" in the context of this clinical trial. They are described collectively as "adverse cardiovascular events" to facilitate a comprehensive grouping for descriptive and summarization purposes, and to ensure consistency with the existing literature.
|
|
Cardiac disorders
Sustained Ventricular Arrhythmias
|
0.00%
0/587 • Long-term clinical outcomes including mortality were passively tracked for all participants (for up to 18 months) beyond the duration of active trial participation. These outcomes are also described as "adverse cardiovascular events" in order to match prevailing descriptions in published literature but are completely unrelated to the study intervention. Study defined adverse events per protocol were collected for up to 3 hours following study intervention (ECG and Echo recording).
Anticipated study related risk is limited to potential skin irritation from placement of ECG lead electrode stickers directly on the skin for ECG measurements. The "adverse cardiovascular events" reported in the manuscript are not "events" in the context of this clinical trial. They are described collectively as "adverse cardiovascular events" to facilitate a comprehensive grouping for descriptive and summarization purposes, and to ensure consistency with the existing literature.
|
0.00%
0/608 • Long-term clinical outcomes including mortality were passively tracked for all participants (for up to 18 months) beyond the duration of active trial participation. These outcomes are also described as "adverse cardiovascular events" in order to match prevailing descriptions in published literature but are completely unrelated to the study intervention. Study defined adverse events per protocol were collected for up to 3 hours following study intervention (ECG and Echo recording).
Anticipated study related risk is limited to potential skin irritation from placement of ECG lead electrode stickers directly on the skin for ECG measurements. The "adverse cardiovascular events" reported in the manuscript are not "events" in the context of this clinical trial. They are described collectively as "adverse cardiovascular events" to facilitate a comprehensive grouping for descriptive and summarization purposes, and to ensure consistency with the existing literature.
|
|
Pregnancy, puerperium and perinatal conditions
Gestational Hypertension
|
5.1%
30/587 • Long-term clinical outcomes including mortality were passively tracked for all participants (for up to 18 months) beyond the duration of active trial participation. These outcomes are also described as "adverse cardiovascular events" in order to match prevailing descriptions in published literature but are completely unrelated to the study intervention. Study defined adverse events per protocol were collected for up to 3 hours following study intervention (ECG and Echo recording).
Anticipated study related risk is limited to potential skin irritation from placement of ECG lead electrode stickers directly on the skin for ECG measurements. The "adverse cardiovascular events" reported in the manuscript are not "events" in the context of this clinical trial. They are described collectively as "adverse cardiovascular events" to facilitate a comprehensive grouping for descriptive and summarization purposes, and to ensure consistency with the existing literature.
|
4.9%
30/608 • Long-term clinical outcomes including mortality were passively tracked for all participants (for up to 18 months) beyond the duration of active trial participation. These outcomes are also described as "adverse cardiovascular events" in order to match prevailing descriptions in published literature but are completely unrelated to the study intervention. Study defined adverse events per protocol were collected for up to 3 hours following study intervention (ECG and Echo recording).
Anticipated study related risk is limited to potential skin irritation from placement of ECG lead electrode stickers directly on the skin for ECG measurements. The "adverse cardiovascular events" reported in the manuscript are not "events" in the context of this clinical trial. They are described collectively as "adverse cardiovascular events" to facilitate a comprehensive grouping for descriptive and summarization purposes, and to ensure consistency with the existing literature.
|
|
Pregnancy, puerperium and perinatal conditions
Preeclampsia
|
3.6%
21/587 • Long-term clinical outcomes including mortality were passively tracked for all participants (for up to 18 months) beyond the duration of active trial participation. These outcomes are also described as "adverse cardiovascular events" in order to match prevailing descriptions in published literature but are completely unrelated to the study intervention. Study defined adverse events per protocol were collected for up to 3 hours following study intervention (ECG and Echo recording).
Anticipated study related risk is limited to potential skin irritation from placement of ECG lead electrode stickers directly on the skin for ECG measurements. The "adverse cardiovascular events" reported in the manuscript are not "events" in the context of this clinical trial. They are described collectively as "adverse cardiovascular events" to facilitate a comprehensive grouping for descriptive and summarization purposes, and to ensure consistency with the existing literature.
|
3.1%
19/608 • Long-term clinical outcomes including mortality were passively tracked for all participants (for up to 18 months) beyond the duration of active trial participation. These outcomes are also described as "adverse cardiovascular events" in order to match prevailing descriptions in published literature but are completely unrelated to the study intervention. Study defined adverse events per protocol were collected for up to 3 hours following study intervention (ECG and Echo recording).
Anticipated study related risk is limited to potential skin irritation from placement of ECG lead electrode stickers directly on the skin for ECG measurements. The "adverse cardiovascular events" reported in the manuscript are not "events" in the context of this clinical trial. They are described collectively as "adverse cardiovascular events" to facilitate a comprehensive grouping for descriptive and summarization purposes, and to ensure consistency with the existing literature.
|
|
Pregnancy, puerperium and perinatal conditions
Eclampsia
|
1.0%
6/587 • Long-term clinical outcomes including mortality were passively tracked for all participants (for up to 18 months) beyond the duration of active trial participation. These outcomes are also described as "adverse cardiovascular events" in order to match prevailing descriptions in published literature but are completely unrelated to the study intervention. Study defined adverse events per protocol were collected for up to 3 hours following study intervention (ECG and Echo recording).
Anticipated study related risk is limited to potential skin irritation from placement of ECG lead electrode stickers directly on the skin for ECG measurements. The "adverse cardiovascular events" reported in the manuscript are not "events" in the context of this clinical trial. They are described collectively as "adverse cardiovascular events" to facilitate a comprehensive grouping for descriptive and summarization purposes, and to ensure consistency with the existing literature.
|
0.66%
4/608 • Long-term clinical outcomes including mortality were passively tracked for all participants (for up to 18 months) beyond the duration of active trial participation. These outcomes are also described as "adverse cardiovascular events" in order to match prevailing descriptions in published literature but are completely unrelated to the study intervention. Study defined adverse events per protocol were collected for up to 3 hours following study intervention (ECG and Echo recording).
Anticipated study related risk is limited to potential skin irritation from placement of ECG lead electrode stickers directly on the skin for ECG measurements. The "adverse cardiovascular events" reported in the manuscript are not "events" in the context of this clinical trial. They are described collectively as "adverse cardiovascular events" to facilitate a comprehensive grouping for descriptive and summarization purposes, and to ensure consistency with the existing literature.
|
|
Cardiac disorders
Valvular Disease
|
0.17%
1/587 • Long-term clinical outcomes including mortality were passively tracked for all participants (for up to 18 months) beyond the duration of active trial participation. These outcomes are also described as "adverse cardiovascular events" in order to match prevailing descriptions in published literature but are completely unrelated to the study intervention. Study defined adverse events per protocol were collected for up to 3 hours following study intervention (ECG and Echo recording).
Anticipated study related risk is limited to potential skin irritation from placement of ECG lead electrode stickers directly on the skin for ECG measurements. The "adverse cardiovascular events" reported in the manuscript are not "events" in the context of this clinical trial. They are described collectively as "adverse cardiovascular events" to facilitate a comprehensive grouping for descriptive and summarization purposes, and to ensure consistency with the existing literature.
|
0.16%
1/608 • Long-term clinical outcomes including mortality were passively tracked for all participants (for up to 18 months) beyond the duration of active trial participation. These outcomes are also described as "adverse cardiovascular events" in order to match prevailing descriptions in published literature but are completely unrelated to the study intervention. Study defined adverse events per protocol were collected for up to 3 hours following study intervention (ECG and Echo recording).
Anticipated study related risk is limited to potential skin irritation from placement of ECG lead electrode stickers directly on the skin for ECG measurements. The "adverse cardiovascular events" reported in the manuscript are not "events" in the context of this clinical trial. They are described collectively as "adverse cardiovascular events" to facilitate a comprehensive grouping for descriptive and summarization purposes, and to ensure consistency with the existing literature.
|
Other adverse events
| Measure |
Intervention
n=587 participants at risk
Participants had ECGs analyzed with artificial intelligence for cardiomyopathy detection.
Digital stethoscope electrocardiogram: Digital stethoscope artificial intelligence enabled electrocardiogram (AI-ECG). An artificial intelligence algorithm which analyses ECG data and generates prediction probabilities for a diagnosis of cardiomyopathy.
|
Control
n=608 participants at risk
Participants had standard clinical ECGs acquired.
|
|---|---|---|
|
Skin and subcutaneous tissue disorders
Skin Irritation
|
0.17%
1/587 • Long-term clinical outcomes including mortality were passively tracked for all participants (for up to 18 months) beyond the duration of active trial participation. These outcomes are also described as "adverse cardiovascular events" in order to match prevailing descriptions in published literature but are completely unrelated to the study intervention. Study defined adverse events per protocol were collected for up to 3 hours following study intervention (ECG and Echo recording).
Anticipated study related risk is limited to potential skin irritation from placement of ECG lead electrode stickers directly on the skin for ECG measurements. The "adverse cardiovascular events" reported in the manuscript are not "events" in the context of this clinical trial. They are described collectively as "adverse cardiovascular events" to facilitate a comprehensive grouping for descriptive and summarization purposes, and to ensure consistency with the existing literature.
|
0.66%
4/608 • Long-term clinical outcomes including mortality were passively tracked for all participants (for up to 18 months) beyond the duration of active trial participation. These outcomes are also described as "adverse cardiovascular events" in order to match prevailing descriptions in published literature but are completely unrelated to the study intervention. Study defined adverse events per protocol were collected for up to 3 hours following study intervention (ECG and Echo recording).
Anticipated study related risk is limited to potential skin irritation from placement of ECG lead electrode stickers directly on the skin for ECG measurements. The "adverse cardiovascular events" reported in the manuscript are not "events" in the context of this clinical trial. They are described collectively as "adverse cardiovascular events" to facilitate a comprehensive grouping for descriptive and summarization purposes, and to ensure consistency with the existing literature.
|
Additional Information
Results disclosure agreements
- Principal investigator is a sponsor employee
- Publication restrictions are in place