Clinical Trial Details
— Status: Enrolling by invitation
Administrative data
NCT number |
NCT06444425 |
Other study ID # |
KY-2024-108 |
Secondary ID |
|
Status |
Enrolling by invitation |
Phase |
|
First received |
|
Last updated |
|
Start date |
June 1, 2024 |
Est. completion date |
December 31, 2024 |
Study information
Verified date |
June 2024 |
Source |
The Fourth Affiliated Hospital of Zhejiang University School of Medicine |
Contact |
n/a |
Is FDA regulated |
No |
Health authority |
|
Study type |
Observational
|
Clinical Trial Summary
The Korotkoff Sounds(KS), which have been in use for over a century, are widely regarded as
the gold standard for measuring blood pressure. Furthermore, their potential extends beyond
diagnosis and treatment of cardiovascular disease; however, research on the KS remains
limited. Given the increasing incidence of heart failure (HF), there is a pressing need for a
rapid and convenient prehospital screening method. In this study, we propose employing deep
learning (DL) techniques to explore the feasibility of utilizing KS methodology in predicting
functional changes in cardiac ejection fraction (LVEF) as an indicator of cardiac
dysfunction.
Description:
Blood Pressure Measurement:Around 72 hours before and after the completion of the
patient's echocardiogram, considering the variability in the patient's blood
pressure and ejection fraction at different times, blood pressure should be measured in each
participant at least twice a day, up to a maximum of six times. Each patient should be
instructed to remain in a quiet state for 10 minutes before blood pressure measurement. Blood
pressure measurement should be conducted according to the following criteria: the cuff used
to measure blood pressure should be wrapped around the patient's arm above the elbow
joint, positioned 2-3 cm above the level of the heart, with a snugness that allows one finger
to fit underneath. Place the stethoscope head at the brachial artery pulse point on the left
elbow joint, then begin inflation. Inflate continuously until the sound of the pulse beat
disappears; then inflate an additional 20 mmHg before stopping inflation. Slowly deflate
while listening-the first audible pulse beat is the systolic pressure, and the disappearance
of the pulse sound is the diastolic pressure. Use the Hanhong POPULAR-3 electronic
stethoscope to record the aforementioned process, with each audio recording lasting 25
seconds uniformly.
Data Analysis Overview:
In terms of data analysis, deep learning models are developed based on Torch version 1.5.0,
utilizing Transformer network architecture to analyze the collected audio data.
Network One: Identifying the presence of cardiac functional abnormalities through Korotkoff
sounds.
Evaluation Metrics: Receiver Operating Characteristic (AUROC), sensitivity, specificity, and
F1 score (harmonic mean of sensitivity and specificity) to assess model performance on the
test dataset.
Network Two: NYHA classification of Korotkoff sounds. Evaluation Metrics: Confusion matrix,
weighted accuracy, multi-class ROC curve, F1 score.
Network Three: Heart failure classification of Korotkoff sounds in heart failure patients.
Evaluation Metrics: Confusion matrix, weighted accuracy, multi-class ROC curve, F1 score.
Network Four: Left Ventricular Ejection Fraction (LVEF) prediction from Korotkoff sounds.
Evaluation Metrics: Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Squared
Error (MSE), R2 Score.