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NCT03600051
Automated Phonocardiography Analysis in Adults
trial testing Automated Heart Murmur Detection AI in Aortic Insufficiency in 90 participants. Completed in 31 January 2017.
18 January 2017
Quick facts
| Lead sponsor | CSD Labs GmbH |
|---|---|
| Status | Completed |
| Study type | OBSERVATIONAL |
| Enrollment | 90 |
| Start date | 10 December 2015 |
| Primary completion | 18 January 2017 |
| Estimated completion | 31 January 2017 |
| Sites | 1 location across Austria |
Drugs / interventions tested
- Automated Heart Murmur Detection AI
Conditions studied
- Aortic Insufficiency — all drugs for Aortic Insufficiency →
- Aortic Stenosis — all drugs for Aortic Stenosis →
- Mitral Insufficiency — all drugs for Mitral Insufficiency →
- Mitral Insufficiency and Aortic Stenosis — all drugs for Mitral Insufficiency and Aortic Stenosis →
Sponsor
CSD Labs GmbH
Who can join
18 and older, any sex, with Aortic Insufficiency or Aortic Stenosis. Patients with the condition only — healthy volunteers not accepted.
Sponsor's own description
Background: Computer aided auscultation in the differentiation of pathologic (AHA class I) from no- or innocent murmurs (AHA class III) via artificial intelligence algorithms could be a useful tool to assist healthcare providers in identifying pathological heart murmurs and may avoid unnecessary referrals to medical specialists. Objective: Assess the quality of the artificial intelligence (AI) algorithm that autonomously detects and classifies heart murmurs as either pathologic (AHA class I) or as no- or innocent (AHA class III). Hypothesis: The algorithm used in this study is able to analyze and identify pathologic heart murmurs (AHA class I) in an adult population with valve defects with a similar sensitivity compared to medical specialist. Methods: Each patient is auscultated and diagnosed independently by a medical specialist by means of standard auscultation. Auscultation findings are verified via gold-standard echocardiogram diagnosis. For each patient, a phonocardiogram (PCG) - a digital recording of the heart sounds - is acquired. The recordings are later analyzed using the AI algorithm. The algorithm results are compared to the findings of the medical professionals as well as to the echocardiogram findings.
Publications & conference data
No peer-reviewed publications indexed yet for this trial. Completed trials usually publish results within 12-18 months.
Verify or expand the search:
- PubMed search for NCT03600051
- Europe PMC full search
- ASCO Meeting Library
- ESMO Meeting Library
- bioRxiv preprints
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Related trials
Other trials of Automated Heart Murmur Detection AI
Trials testing the same drug.
- NCT03227848 — eMurmur ID - Clinical Performance Evaluation · completed
Other recruiting trials for Aortic Insufficiency
Currently open trials in the same condition.
- NCT06835946 — Impact of Anesthesia, Positive Pressure Ventilation and Modality of Imaging on the Echocardiographic Assessment of the S · recruiting
- NCT06377449 — Influence of Lung Ultrasonography on the Prognosis and Postoperative Outcomes in Cardiac Surgical Patients · NA · recruiting
- NCT06420895 — Health Data Warehouse on Aortic Insufficiency · active not recruiting
Other CSD Labs GmbH trials
Trials by the same sponsor.
- NCT03227848 — eMurmur ID - Clinical Performance Evaluation · completed
Verify against primary sources
- ClinicalTrials.gov — authoritative US registry record
- WHO ICTRP — international registry index
- EU Clinical Trials Register
- Sponsor press releases (Google)
- Trial protocol + status: ClinicalTrials.gov NCT03600051 (US National Library of Medicine, public domain)
- Drug + disease cross-links: matched in real time against Drug Landscape's normalised drug + company + condition tables
- Sponsor: as reported to ClinicalTrials.gov by CSD Labs GmbH
- Last refreshed: 26 July 2018
Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT03600051.
Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing