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Technological developments in the recent decades has enabled the integration of electronic and digital components in the stethoscope design, in an attempt to improve auditory performance and, moreover, to assist in improving user's diagnostic accuracy by incorporating computerized, digital technologies, artificial intelligence capabilities and deep-learning-based algorithms enhancing these devices.
We believe that these technologies can be used to significantly improve the diagnostic performance in the primary care phase, by means of a sophisticated stethoscope that enables auscultation to sounds and signals typically found in the sub-sound frequency level. Their transformation into the sound range, and the use of artificial intelligence and machine learning techniques to characterize sound patterns that correspond to specific problems or diseases can substantially enhance the physician's or other care giver's performance to the benefit of the patients.
At this stage, the software in development does not purport to make diagnostic decisions, but only to provide information that will enhance decision and diagnosis making process, therefore enable a more accurate and definitive diagnostic decision and perhaps decrease the number of additional diagnostic tests requested.
Up to 200 patients will participate in an open, prospective and multi-center study.
Patients diagnosed as positive to COVID-19 will be referred to a VOQX examination. All patients will receive detailed explanation about the purpose of the examination, its impact and will provide their consent prior to the examination. The VOQX device output will have no influence on the decision-making process of the physicians and care givers. The VOQX Stethoscope membrane will be put on the patient's chest area in predefined anterior and posterior points. The data collected in the form of breath sound signals in particular infra-sound will be transferred to an external computer and processed by machine learning algorithm developed by the company. The algorithm will seek patterns typical for the diagnosed disease for each corresponding case diagnosed.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Open Label | Experimental | Up to 200 patients will participate in this open study. Before each examination with the study device, data from each patient (Current medical condition, medical history and demographic data) will be inserted to a computer and added to the database of the study for further processing in conjunction with the study device results. The study device electronic stethoscope membrane will be put on the patient's chest area in predefined anterior and posterior points. At the end of each examination the data will be transferred to a computer and stored in the patient's file. Each patient will be requested to attend the examination once. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Electronic stethoscope | Diagnostic Test | Electronic stethoscope |
|
| Measure | Description | Time Frame |
|---|---|---|
| Performance outcome | Detection and identification of pulmonary sound signals ranging from infra-sound to auditory sound which are typical to specific pathologies of COVID-19 | Through study completion, an average of 1 year |
| Performance outcome | Use machine learning technologies to identify the above sound patterns and corresponding pathologies | through study completion, an average of 1 year |
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Inclusion Criteria:
Patients over the age of 18 years
RT-PCR positive for COVID 19
Patients diagnosed with the following pulmonary pathology:
The diagnosis is confirmed if possible, by:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Hadas Sapir | Contact | 972 54 7826543 | shadas@gsap.co.il |
| Name | Affiliation | Role |
|---|---|---|
| David Linhard | Sanolla | Study Director |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Barzilai Medical Center | Recruiting | Ashkelon | 7830604 | Israel | ||
| Hille Yaffe Medical Center |
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| Recruiting |
| Hadera |
| 38100 |
| Israel |
| Shamir Medical Center (Assaf Harofah) | Recruiting | Zrifin | 703000 | Israel |
| ID | Term |
|---|---|
| D000086382 | COVID-19 |
| D004194 | Disease |
| ID | Term |
|---|---|
| D011024 | Pneumonia, Viral |
| D011014 | Pneumonia |
| D012141 | Respiratory Tract Infections |
| D007239 | Infections |
| D014777 | Virus Diseases |
| D018352 | Coronavirus Infections |
| D003333 | Coronaviridae Infections |
| D030341 | Nidovirales Infections |
| D012327 | RNA Virus Infections |
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
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