Features of the use of traditional means of lung auscultation for primary diagnostics
DOI:
https://doi.org/10.31649/1681-7893-2026-51-1-204-210Keywords:
auscultation, pulmonary abnormalities, diagnosis, low clinical accuracy, epidemiology, implementation challenges.Abstract
This article analyses the issues surrounding the use of traditional auscultation as a means of primary lung diagnosis, as well as the risks associated with diagnostic mistakes. It examines the effectiveness of this clinical practice, the epidemiological characteristics of the spread of lung diseases in Ukraine, the stages of implementation, and the legislative framework for digital diagnostic tools for lung abnormalities. Calculations of the effectiveness of physical auscultation were carried out using mathematical modelling, based on a hypothetical cohort and utilising real-world values for the method’s sensitivity and specificity. The existence of the problem and the need to resolve it are substantiated. A possible solution is considered through the introduction of electronic stethoscopes with filtration systems and automated decision support systems. The consequences and challenges of introducing digital devices are analysed using the examples of Ukraine and the worldwide practices, and the prospects for further developments in this field are identified. The research results demonstrate the low diagnostic accuracy and high subjectivity of traditional auscultation, and the need to address this problem.
References
Sarkar, M., Madabhavi, I., Niranjan, N., & Dogra, M. (2015). Auscultation of the respiratory system. Annals of Thoracic Medicine, 10(3), 158–168. https://doi.org/10.4103/1817-1737.160831
Arts, L., Lim, E. H. T., van de Ven, P. M., Heunks, L., & Tuinman, P. R. (2020). The diagnostic accuracy of lung auscultation in adult patients with acute pulmonary pathologies: A meta-analysis. Scientific Reports. https://doi.org/10.1038/s41598-020-64405-6
Sharma, S., Poudyal, J. K., Sharma, V. K., Parajuli, S., & Dhungana, G. P. (2026). Factors associated with delayed diagnosis of pulmonary tuberculosis in Chitwan district of Nepal. PLOS Global Public Health, 6(1), Article e0005718. https://doi.org/10.1371/journal.pgph.0005718
Lazarovici, M., Trentzsch, H., & Prückner, S. (2017). Human factors in medicine. Der Anaesthesist, 66, 63–80. https://doi.org/10.1007/s00101-016-0261-5
Hafke-Dys, H., Bręborowicz, A., Kleka, P., Kociński, J., & Biniakowski, A. (2019). The accuracy of lung auscultation in the practice of physicians and medical students. PLOS ONE, 14(8), Article e0220606. https://doi.org/10.1371/journal.pone.0220606
Aviles-Solis, J. C., Vanbelle, S., Halvorsen, P. A., Francis, N., Cals, J. W. L., Andreeva, E. A., Marques, A., Piirilä, P., Pasterkamp, H., & Melbye, H. (2017). International perception of lung sounds: A comparison of classification across some European borders. BMJ Open Respiratory Research, 4(1). https://doi.org/10.1136/bmjresp-2017-000250
Tawfik, D. S., Profit, J., Morgenthaler, T. I., Sinsky, C. A., Dyrbye, L. N., Tait, V. F., Shanafelt, T. D., & Trockel, M. T. (2018). Physician Burnout, Well-being, and Work Unit Safety Grades in Relationship to Reported Medical Errors. Mayo Clinic Proceedings, 93(11), 1571–1580. https://doi.org/10.1016/j.mayocp.2018.05.014
Park, D. E., Watson, N. L., Focht, C., Feikin, D., Hammitt, L. L., Brooks, W. A., Howie, S. R. C., Kotloff, K. L., Levine, O. S., Madhi, S. A., Murdoch, D. R., O'Brien, K. L., Scott, J. A. G., Thea, D. M., Amorninthapichet, T., Awori, J., Bunthi, C., Ebruke, B., Elhilali, M., … McCollum, E. D. (2022). Digitally recorded and remotely classified lung auscultation compared with conventional stethoscope classifications among children aged 1–59 months enrolled in the Pneumonia Etiology Research for Child Health (PERCH) case–control study. BMJ Open Respiratory Research, 9(1), Article e001144. https://doi.org/10.1136/bmjresp-2021-001144
Stoycheva, K., Cristea, V., Ködmön, C., Rosales-Klintz, S., Zenner, D., Vasiliu, A., van der Werf, M., & Lange, C. (2024). Tuberculosis in people of Ukrainian origin in the European Union and the European Economic Area, 2019 to 2022. Eurosurveillance, 29(12), Article 2400094. https://doi.org/10.2807/1560-7917.ES.2024.29.12.2400094
World Health Organization. (n.d.). Tuberculosis profile: Ukraine. Доступ отримано квітня 28, 2026, from https://worldhealthorg.shinyapps.io/tb_profiles/?inputs&tab=%22charts%22&lan=%22EN%22&iso3=%22UKR%22&entity_type=%22country%22
World Health Organization. (2025, March 5). Funding cuts impact access to TB services endangering millions of lives. https://www.who.int/news/item/05-03-2025-funding-cuts-to-tuberculosis-programmes-endanger-millions-of-lives
Stop TB Partnership. (2025, March 3). Report on the impact of US government funding halt on TB responses in high TB burden countries. https://www.stoptb.org/sites/default/files/documents/Disruption%20US%20FUNDING%20halt030325.pdf
Guyatt, G., Rennie, D., Meade, M. O., & Cook, D. J. (2015). Users’ guides to the medical literature: A manual for evidence-based clinical practice (3rd ed.). McGraw-Hill Education. 740.
Xu, X., & Sankar, R. (2024). Classification and recognition of lung sounds using artificial intelligence and machine learning: A literature review. Big Data and Cognitive Computing, 8(10), Article 127. https://doi.org/10.3390/bdcc8100127
Kalinauskienė, E., Razvadauskas, H., Morse, D. J., Maxey, G. E., & Naudžiūnas, A. (2019). A comparison of electronic and traditional stethoscopes in the heart auscultation of obese patients. Medicina, 55(4), Article 94.. https://doi.org/10.3390/medicina55040094
Sueaseenak, D., Boonsat, P., Tantisatirapong, S., Rujipong, P., Tulatamakit, S., & Phokaewvarangkul, O. (2025). Early diagnosis of pneumonia and chronic obstructive pulmonary disease with a smart stethoscope with cloud server-embedded machine learning in the post-COVID-19 era. Biomedicines, 13(2), Article 354. https://doi.org/10.3390/biomedicines13020354
Wei, T.-J., Hsiung, P.-Y., Liu, J.-H., Lin, T.-C., Kuo, F.-T., & Wu, C.-Y. (2022). Use of electronic auscultation in full personal protective equipment to detect ventilation status in selective lung ventilation: A randomized controlled trial. Frontiers in Medicine, 9, Article 851395.. https://doi.org/10.3389/fmed.2022.851395
Arjoune, Y., Nguyen, T. N., Doroshow, R. W., & Shekhar, R. (2023). Technical characterisation of digital stethoscopes: Towards scalable artificial intelligence-based auscultation. Journal of Medical Engineering & Technology, 47(3), 165–178. https://doi.org/10.1080/03091902.2023.2174198
Oudbier, S. J., Souget-Ruff, S. P., Chen, B. S. J., Ziesemer, K. A., Meij, H. J., & Smets, E. M. A. (2024). Implementation barriers and facilitators of remote monitoring, remote consultation and digital care platforms through the eyes of healthcare professionals: A review of reviews. BMJ Open, 14(6), Article e075833. https://doi.org/10.1136/bmjopen-2023-075833
Canada Health Infoway. (2024). 2024 National survey of Canadian physicians: Barriers and challenges to digital health technologies. https://insights.infoway-inforoute.ca/2024-cma-barriers-challenges-digital-health-technologies/
Livieri, G., Mangina, E., Protopapadakis, E. D., & Panayiotou, A. G. (2025). The gaps and challenges in digital health technology use as perceived by patients: A scoping review and narrative meta-synthesis. Frontiers in Digital Health, 7, Article 1474956. https://doi.org/10.3389/fdgth.2025.1474956
Bisikalo, O.; Kharchenko, V.; Kovtun, V.; Krak, I.; Parameterization of the Stochastic Model for Evaluating Variable Small Data in the Shannon Entropy Basis. Entropy 2023, 25, 184.
Ivanov Yu. Yu., Maloshtan T. V., Zvuzdetsky E. O. Modified algorithm for decoding block codes of turbo products. Bulletin of the Institute of Informatics. 2025. No. 4. P. 90–94. DOI: 10.31649/1997-9266-2025-181-4-90-94.
Intellectual technologies in medical diagnostics, treatment and rehabilitation: monograph / [S.V. Pavlov, O.G. Avrunin, S.M. Zlepko, E.V. Bodianskyi and others]; edited by S. Pavlov, O. Avrunin. – Vinnytsia: PP “TD “Edelweiss and K”, 2019. – 260 p.
Ministry of Health of Ukraine. (2025, February 10). Pro vnesennia zmin do Prymirnoho tabelia materialno-tekhnichnoho osnashchennia zakladiv okhorony zdorovia ta fizychnykh osib-pidpryiemtsiv, yaki nadaiut pervynnu medychnu dopomohu
World Bank. (2024). Service Delivery Indicators Health Survey for Ukraine: Survey report 2024. https://documents.worldbank.org/en/publication/documents-reports/documentdetail/099011426095032380
Downloads
-
PDF (Українська)
Downloads: 4
Published
How to Cite
Issue
Section
License
Автори, які публікуються у цьому журналі, погоджуються з наступними умовами:- Автори залишають за собою право на авторство своєї роботи та передають журналу право першої публікації цієї роботи на умовах ліцензії Creative Commons Attribution License, котра дозволяє іншим особам вільно розповсюджувати опубліковану роботу з обов'язковим посиланням на авторів оригінальної роботи та першу публікацію роботи у цьому журналі.
- Автори мають право укладати самостійні додаткові угоди щодо неексклюзивного розповсюдження роботи у тому вигляді, в якому вона була опублікована цим журналом (наприклад, розміщувати роботу в електронному сховищі установи або публікувати у складі монографії), за умови збереження посилання на першу публікацію роботи у цьому журналі.
- Політика журналу дозволяє і заохочує розміщення авторами в мережі Інтернет (наприклад, у сховищах установ або на особистих веб-сайтах) рукопису роботи, як до подання цього рукопису до редакції, так і під час його редакційного опрацювання, оскільки це сприяє виникненню продуктивної наукової дискусії та позитивно позначається на оперативності та динаміці цитування опублікованої роботи (див. The Effect of Open Access).
