Digital diagnoSis of Cardiac sOUNd in peDiatric Patients [DI-SOUND Study]

NCT07542509 | Recruiting DMC

• 2 other identifiers: PNRR-MR1-2022-12376762PNRR: M6/C2_CALL 2022
• Study Type: observational
• Target: 1,000
• Locations: 1 country
• Sites: 5

Brief Summary

Neonatal screening procedures for potentially life-threatening congenital cardiovascular diseases (i.e., duct-dependent systemic or pulmonary circulation), currently implemented at the national level, rely primarily on cardiovascular physical examination performed by a neonatologist. More recently, this approach has been complemented by the assessment of hemoglobin oxygen saturation at both the upper and lower extremities (pre- and post-ductal saturation) in order to improve diagnostic sensitivity, although this practice has not yet been uniformly adopted nationwide. Converging evidence indicates that these screening strategies are affected by significant limitations in both sensitivity (failure to identify affected individuals) and specificity (false-positive findings in healthy subjects). These limitations are associated with substantial overall costs for the healthcare system. Failure to correctly identify affected neonates may result in increased morbidity and mortality, whereas overdiagnosis leads to unnecessary second-level diagnostic investigations and imposes a considerable psychological burden on families, who remain understandably anxious until diagnostic confirmation is achieved. The aim of the present research project (proof-of-concept study) is to develop a digital classifier capable to categorize heart sounds with commercially available digital stethoscopes into a binary classification system distinguishing physiological from pathological sounds. The derivation phase will be followed by a prospective validation phase, in which the classifier will be applied to assess its diagnostic performance. This phase will also evaluate the economic impact of the digital screening approach compared with standard practice. During the derivation phase, neonates with known cardiovascular status, as determined by prior echocardiographic assessment (including both healthy subjects and those with congenital heart disease), will be enrolled. Heart sounds will be recorded in a quiet environment under standard clinical conditions, without sedation. Digital recordings will be stored in WAV format and analyzed to develop a binary classification algorithm capable of distinguishing healthy from pathological cases. Following development, the classifier will be prospectively applied to a validation cohort of neonates undergoing conventional cardiovascular screening (clinical examination and pre- and post-ductal pulse oximetry), followed by classification using the digital tool under investigation. All participants will subsequently undergo confirmatory echocardiography. Diagnostic performance metrics, including sensitivity, specificity, positive and negative predictive values, and likelihood ratios, will be calculated for both the digital and conventional screening modalities. Furthermore, the number of missed pathological cases and the number of unnecessary second-level investigations resulting from false-positive findings will be used to define the economic benefit profile of the proposed screening strategy. Monte Carlo simulation techniques will be employed to extrapolate these findings at the national level, using ISTAT data on birth rates and disease prevalence. It is anticipated that the development of a digital classifier for the binary classification of neonatal heart sounds will be feasible. Moreover, it is expected that this tool will demonstrate superior diagnostic performance compared with current neonatal screening strategies, with beneficial implications not only for the accurate identification of affected and healthy neonates but also for reducing overall healthcare costs associated with missed diagnoses and inappropriate overdiagnosis.

Conditions

Cardiac Disease; Auscultation of Heart; Machine Learning

Outcome Measures

Primary Outcomes (1)

• Binary classifier for normal versus abnormal cardiac sounds in newborns

  An algorithm will be developed capable of distinguishing normal from pathological heart sounds based on cardiac auscultation performed using a digital stethoscope

  one year

Secondary Outcomes (1)

• Validation of the binary classifier in a consecutive, independent cohort of newborns

  one year

Other Outcomes (1)

• Cost-effective analysis of digital versus standard screening modality for CHD in newborns

  Six months

Eligibility Criteria

• Age: 7 Days - 30 Days
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17)
• Sampling Method: Probability Sample

Study Population

The study population will consist of newborns (both male and female). Infants aged 7 to 30 days will be eligible for inclusion, excluding those with a body weight below 1.5 kg and those for whom a diagnostic echocardiogram is not feasible.

You may qualify if:

• Age \< 30 days
• Signed informed consent obtained from parent(s) or representative(s)

You may not qualify if:

• Inability to acquire a diagnostic echocardiogram
• Weight less than 1.5Kg

Sponsors & Collaborators

• IRCCS Azienda Ospedaliero-Universitaria di Bologna: lead

Study Sites (5)

IRCCS Azienda Ospedaliero-Universitaria di Bologna Sant'Orsola-Malpighi

Bologna, BO, 40138, Italy

RECRUITING

Politecnico di Milano

Milan, Michigan, 20133, Italy

ACTIVE NOT RECRUITING

Policlinico Umberto I di Roma

Roma, RM, 00161, Italy

RECRUITING

IRCCS Ospedale Pediatrico Bambin Gesu', Roma

Roma, RM, Italy

RECRUITING

Azienda Ospedaliera Monaldi di Napoli

Naples, 80131, Italy

RECRUITING

Related Publications (30)

• Yang Y, Huang Y, Knight JH, Oster ME, Kochilas LK. Association of Rurality With Mortality After Congenital Heart Surgery. Circ Cardiovasc Qual Outcomes. 2025 Jun;18(6):e011708. doi: 10.1161/CIRCOUTCOMES.124.011708. Epub 2025 May 13.

  PMID: 40358979 BACKGROUND

• Hom LA, Martin GR. U.S. international efforts on critical congenital heart disease screening: can we have a uniform recommendation for Europe? Early Hum Dev. 2014 Sep;90 Suppl 2:S11-4. doi: 10.1016/S0378-3782(14)50004-7.

  PMID: 25220118 BACKGROUND

• Zhang NS, Yang JY, Goldhaber JI, Phan BAP, Cheitlin MD. Cardiac auscultation skills among medical trainees. Am Heart J. 2025 Aug;286:14-17. doi: 10.1016/j.ahj.2025.03.006. Epub 2025 Mar 15.

  PMID: 40096938 BACKGROUND

• Lai WW, Geva T, Shirali GS, Frommelt PC, Humes RA, Brook MM, Pignatelli RH, Rychik J; Task Force of the Pediatric Council of the American Society of Echocardiography; Pediatric Council of the American Society of Echocardiography. Guidelines and standards for performance of a pediatric echocardiogram: a report from the Task Force of the Pediatric Council of the American Society of Echocardiography. J Am Soc Echocardiogr. 2006 Dec;19(12):1413-30. doi: 10.1016/j.echo.2006.09.001. No abstract available.

  PMID: 17138024 BACKGROUND

• Wazed E, Lee J, Jeong H. Deep Learning for Heart Sound Abnormality of Infants: Proof-of-Concept Study of 1D and 2D Representations. Children (Basel). 2025 Sep 12;12(9):1221. doi: 10.3390/children12091221.

  PMID: 41007086 BACKGROUND

• Jabbar A, Grooby E, Poh YY, Ahmad KI, Hassanuzzaman M, Mostafa R, Khandoker AH, Marzbanrad F. Automated detection of pediatric congenital heart disease from phonocardiograms using deep and handcrafted feature fusion. Comput Biol Med. 2025 Oct;197(Pt A):110993. doi: 10.1016/j.compbiomed.2025.110993. Epub 2025 Sep 9.

  PMID: 40929795 BACKGROUND

• Thompson WR, Reinisch AJ, Unterberger MJ, Schriefl AJ. Artificial Intelligence-Assisted Auscultation of Heart Murmurs: Validation by Virtual Clinical Trial. Pediatr Cardiol. 2019 Mar;40(3):623-629. doi: 10.1007/s00246-018-2036-z. Epub 2018 Dec 12.

  PMID: 30542919 BACKGROUND

• Sharma P, Newman K, Long CS, Gasiewski AJ, Barnes F. Use of Wavelet Transform to Detect Compensated and Decompensated Stages in the Congestive Heart Failure Patient. Biosensors (Basel). 2017 Sep 20;7(3):40. doi: 10.3390/bios7030040.

  PMID: 28930184 BACKGROUND

• Sepehri AA, Kocharian A, Janani A, Gharehbaghi A. An Intelligent Phonocardiography for Automated Screening of Pediatric Heart Diseases. J Med Syst. 2016 Jan;40(1):16. doi: 10.1007/s10916-015-0359-3. Epub 2015 Oct 30.

  PMID: 26573653 BACKGROUND

• Pedrosa J, Castro A, Vinhoza TT. Automatic heart sound segmentation and murmur detection in pediatric phonocardiograms. Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:2294-7. doi: 10.1109/EMBC.2014.6944078.

  PMID: 25570446 BACKGROUND

• Beritelli F, Capizzi G, Lo Sciuto G, Napoli C, Scaglione F. Automatic heart activity diagnosis based on Gram polynomials and probabilistic neural networks. Biomed Eng Lett. 2017 Aug 22;8(1):77-85. doi: 10.1007/s13534-017-0046-z. eCollection 2018 Feb.

  PMID: 30603192 BACKGROUND

• Chowdhury MEH, Khandakar A, Alzoubi K, Mansoor S, M Tahir A, Reaz MBI, Al-Emadi N. Real-Time Smart-Digital Stethoscope System for Heart Diseases Monitoring. Sensors (Basel). 2019 Jun 20;19(12):2781. doi: 10.3390/s19122781.

  PMID: 31226869 BACKGROUND

• Elgendi M, Kumar S, Guo L, Rutledge J, Coe JY, Zemp R, Schuurmans D, Adatia I. Detection of Heart Sounds in Children with and without Pulmonary Arterial Hypertension--Daubechies Wavelets Approach. PLoS One. 2015 Dec 2;10(12):e0143146. doi: 10.1371/journal.pone.0143146. eCollection 2015.

  PMID: 26629704 BACKGROUND

• Huang Y, Zhong S, Zhang X, Kong L, Wu W, Yue S, Tian N, Zhu G, Hu A, Xu J, Zhu H, Sun A, Qin F, Wang Z, Wu S. Large scale application of pulse oximeter and auscultation in screening of neonatal congenital heart disease. BMC Pediatr. 2022 Aug 12;22(1):483. doi: 10.1186/s12887-022-03540-7.

  PMID: 35962379 BACKGROUND

• Freud LR, McElhinney DB, Marshall AC, Marx GR, Friedman KG, del Nido PJ, Emani SM, Lafranchi T, Silva V, Wilkins-Haug LE, Benson CB, Lock JE, Tworetzky W. Fetal aortic valvuloplasty for evolving hypoplastic left heart syndrome: postnatal outcomes of the first 100 patients. Circulation. 2014 Aug 19;130(8):638-45. doi: 10.1161/CIRCULATIONAHA.114.009032. Epub 2014 Jul 22.

  PMID: 25052401 BACKGROUND

• Kotb MA, Elmahdy HN, Seif El Dein HM, Mostafa FZ, Refaey MA, Rjoob KWY, Draz IH, Basanti CWS. The Machine Learned Stethoscope Provides Accurate Operator Independent Diagnosis of Chest Disease. Med Devices (Auckl). 2020 Jan 23;13:13-22. doi: 10.2147/MDER.S221029. eCollection 2020.

  PMID: 32158281 BACKGROUND

• Durand LG, Pibarot P. Review: Most Recent Advancements in Digital Signal Processing of the Phonocardiogram. Crit Rev Biomed Eng. 2017;45(1-6):453-509. doi: 10.1615/CritRevBiomedEng.v45.i1-6.170.

  PMID: 29953386 BACKGROUND

• Banerjee R, Dutta Choudhury A, Deshpande P, Bhattacharya S, Pal A, Mandana KM. A robust dataset-agnostic heart disease classifier from Phonocardiogram. Annu Int Conf IEEE Eng Med Biol Soc. 2017 Jul;2017:4582-4585. doi: 10.1109/EMBC.2017.8037876.

  PMID: 29060917 BACKGROUND

• Hoff H, Quary S, Keesari R, Oster ME. Evaluating the Modified American Academy of Pediatrics Screening Algorithm for Critical Congenital Heart Disease. Am J Perinatol. 2025 Apr;42(5):674-682. doi: 10.1055/a-2416-5637. Epub 2024 Sep 17.

  PMID: 39288909 BACKGROUND

• Gardiner HM, Kovacevic A, van der Heijden LB, Pfeiffer PW, Franklin RC, Gibbs JL, Averiss IE, Larovere JM. Prenatal screening for major congenital heart disease: assessing performance by combining national cardiac audit with maternity data. Heart. 2014 Mar;100(5):375-82. doi: 10.1136/heartjnl-2013-304640. Epub 2013 Nov 22.

  PMID: 24270748 BACKGROUND

• Sharland G. Fetal cardiac screening and variation in prenatal detection rates of congenital heart disease: why bother with screening at all? Future Cardiol. 2012 Mar;8(2):189-202. doi: 10.2217/fca.12.15.

  PMID: 22413979 BACKGROUND

• Martin GR, Ewer AK, Gaviglio A, Hom LA, Saarinen A, Sontag M, Burns KM, Kemper AR, Oster ME. Updated Strategies for Pulse Oximetry Screening for Critical Congenital Heart Disease. Pediatrics. 2020 Jul;146(1):e20191650. doi: 10.1542/peds.2019-1650. Epub 2020 Jun 4.

  PMID: 32499387 BACKGROUND

• Arlettaz R, Bauschatz AS, Monkhoff M, Essers B, Bauersfeld U. The contribution of pulse oximetry to the early detection of congenital heart disease in newborns. Eur J Pediatr. 2006 Feb;165(2):94-8. doi: 10.1007/s00431-005-0006-y. Epub 2005 Oct 7.

  PMID: 16211399 BACKGROUND

• Khammari Nystrom F, Petersson G, Stephansson O, Johansson S, Altman M. Diagnostic values of the femoral pulse palpation test. Arch Dis Child Fetal Neonatal Ed. 2020 Jul;105(4):375-379. doi: 10.1136/archdischild-2019-317066. Epub 2019 Oct 9.

  PMID: 31597727 BACKGROUND

• Aggarwal V, Mulukutla V, Maskatia S, Justino H, Mullins CE, Qureshi AM. Outcomes after Balloon Pulmonary Valvuloplasty for Critical Pulmonary Stenosis and Incidence of Coronary Artery Fistulas. Am J Cardiol. 2018 Jun 15;121(12):1617-1623. doi: 10.1016/j.amjcard.2018.02.049. Epub 2018 Mar 13.

  PMID: 29681368 BACKGROUND

• Durand I, Deverriere G, Thill C, Lety AS, Parrod C, David N, Barre E, Hazelzet T. Prenatal Detection of Coarctation of the Aorta in a Non-selected Population: A Prospective Analysis of 10 Years of Experience. Pediatr Cardiol. 2015 Aug;36(6):1248-54. doi: 10.1007/s00246-015-1153-1. Epub 2015 Apr 7.

  PMID: 25845939 BACKGROUND

• Tworetzky W, Wilkins-Haug L, Jennings RW, van der Velde ME, Marshall AC, Marx GR, Colan SD, Benson CB, Lock JE, Perry SB. Balloon dilation of severe aortic stenosis in the fetus: potential for prevention of hypoplastic left heart syndrome: candidate selection, technique, and results of successful intervention. Circulation. 2004 Oct 12;110(15):2125-31. doi: 10.1161/01.CIR.0000144357.29279.54. Epub 2004 Oct 4.

  PMID: 15466631 BACKGROUND

• Norwood WI, Lang P, Hansen DD. Physiologic repair of aortic atresia-hypoplastic left heart syndrome. N Engl J Med. 1983 Jan 6;308(1):23-6. doi: 10.1056/NEJM198301063080106. No abstract available.

  PMID: 6847920 BACKGROUND

• Chakraborty A, Gorla SR, Swaminathan S. Impact of prenatal diagnosis of complex congenital heart disease on neonatal and infant morbidity and mortality. Prenat Diagn. 2018 Nov;38(12):958-963. doi: 10.1002/pd.5351. Epub 2018 Sep 27.

  PMID: 30171818 BACKGROUND

• van der Linde D, Konings EE, Slager MA, Witsenburg M, Helbing WA, Takkenberg JJ, Roos-Hesselink JW. Birth prevalence of congenital heart disease worldwide: a systematic review and meta-analysis. J Am Coll Cardiol. 2011 Nov 15;58(21):2241-7. doi: 10.1016/j.jacc.2011.08.025.

  PMID: 22078432 BACKGROUND

MeSH Terms

Conditions

Heart Diseases

Condition Hierarchy (Ancestors)

Cardiovascular Diseases

Study Officials

• Gabriele Egidy Assenza, MD

  IRCCS Azienda Ospedaliero-Universitaria di Bologna Sant'Orsola-Malpighi

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Gabriele Egidy Assenza, MD

CONTACT

0512149072; gabriele.egidyassenza@aosp.bo.it

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Medical Doctor

Study Record Dates

• First Submitted: April 15, 2026
• First Posted: April 21, 2026
• Study Start: July 18, 2024
• Primary Completion: February 1, 2026
• Study Completion (Estimated): January 1, 2027
• Last Updated: April 21, 2026

Record last verified: 2026-04

Locations

IT (5)