Research Article

Data-Driven Development of a Tinnitus Risk Level Classification System Based on Clinical Information

Nguyen-Ngan-Ha Lam 1, Ming-Jui Wu 2 3, Chun-Lin Kuo 1, Yi-Chun Du 1 *
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1 Department of Biomedical Engineering, National Cheng Kung University, Tainan 701, Taiwan 2 College of Pharmacy & Health Care, Tajen University, Pingtung County 90741, Taiwan3 Department of Internal Medicine, Kaohsiung Veterans General Hospital Tainan Branch , Tainan, 710, Taiwan* Corresponding Author
International Journal of Clinical Medicine and Bioengineering, 5(4), December 2025, 1-9, https://doi.org/10.35745/ijcmb2025v05.04.0001
Submitted: 15 April 2025, Published: 30 December 2025
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ABSTRACT

Tinnitus affects approximately 15% of the global population, with prevalence rising to 25% among adults over the age of 60. Its complex and multifactorial cause, including hearing loss, psychological stress, mental health disorders, and neurological conditions, makes diagnosis and management particularly challenging. The severity of tinnitus varies widely and often disrupts daily functioning, yet the absence of a standardized screening method for assessing tinnitus risk contributes to delays in diagnosis and inefficient use of healthcare resources. This study aims to develop and validate a tinnitus risk screening tool tailored to the Taiwanese population, based on easily accessible medical information such as hypertension, diabetes, obesity, and lifestyle habits (e.g., smoking, alcohol use). A two-stage framework was implemented, combining rule-based analysis with a quantitative risk scoring system to classify individuals into low-, moderate-, and high-risk categories. Validation against expert clinical judgment achieved 88.2% accuracy in identifying high-risk tinnitus cases. By leveraging routine clinical data, this tool facilitates prompt care for individuals with serious tinnitus, particularly in primary care or resource-limited settings lacking specialized diagnostic tools. The proposed screening model offers practical value for healthcare providers, patients, and caregivers, enabling timely intervention and reducing the medical, emotional, and economic burdens associated with tinnitus
Keywords: Tinnitus, Risk classification, Screening model, Taiwanese population, Risk stratification, Early intervention

CITATION (APA)

Lam, N.-N.-H., Wu, M.-J., Kuo, C.-L., & Du, Y.-C. (2025). Data-Driven Development of a Tinnitus Risk Level Classification System Based on Clinical Information. International Journal of Clinical Medicine and Bioengineering, 5(4), 1-9. https://doi.org/10.35745/ijcmb2025v05.04.0001

REFERENCES

  1. Jarach, C.M.; Lugo, A.; Scala, Met ; et al. Global Prevalence and Incidence of Tinnitus: A Systematic Review and Meta-analysis. JAMA Neurol. 2022, 79, 888–900. https://doi.org/10.1001/jamaneurol.2022.2189.
  2. Oosterloo, B.C.; Croll, P.H.; de Jong, R.J.B.; et al. Prevalence of Tinnitus in an Aging Population and Its Relation to Age and Hearing Loss. Otolaryngol. Head Neck Surg. 2021, 164, 859–868. https://doi.org/10.1177/0194599820957296.
  3. Trochidis, I.; Lugo, A.; Borroni, E.; et al. Systematic Review on Healthcare and Societal Costs of Tinnitus. Int. J. Environ. Res. Public Health 2021, 18, 6881. https://doi.org/10.3390/ijerph18136881.
  4. Haider, H.F.; Bojić, T.; Ribeiro, S.F.; et al. Pathophysiology of Subjective Tinnitus: Triggers and Maintenance. Front. Neurosci. 2018, 12, 866. https://doi.org/10.3389/fnins.2018.00866.
  5. Pegge, S.A.H.; Steens, S.C.A.; Kunst, H.P.M.; et al. Pulsatile Tinnitus: Differential Diagnosis and Radiological Work-Up. Curr. Radiol. Rep. 2017, 5, 5. https://doi.org/10.1007/s40134-017-0199-7.
  6. Bektas, D.; Çaylan, R. Non-pulsatile Subjective Tinnitus Without Hearing Loss May Be Caused by Undetectable Sounds Originating from Venous System of the Brain. Med. Hypotheses 2008, 71, 245–248. https://doi.org/10.1016/j.mehy.2008.03.024.
  7. Li, Y.L.; Hsu, Y.C.; Lin, C.Y.; Wu, J.L. Sleep Disturbance and Psychological Distress in Adult Patients with Tinnitus. J. Formos. Med. Assoc. 2022, 121, 995–1002. https://doi.org/10.1016/j.jfma.2021.07.022.
  8. Lin, C.E.; Chen, L.F.; Chou, P.H.; Chung, C.H. Increased Prevalence and Risk of Anxiety Disorders in Adults with Tinnitus: A Population-Based Study in Taiwan. Gen. Hosp. Psychiatry 2018, 50, 131–136. https://doi.org/10.1016/j.genhosppsych.2017.11.006.
  9. Wang, H.; Tang, D.; Wu, Y. ; et al. The State of the Art of Sound Therapy for Subjective Tinnitus in Adults. Ther. Adv. Chronic Dis. 2020, 11, 2040622320956426. https://doi.org/10.1177/2040622320956426.
  10. Niu, Y.; You, Y. The Effect of Music Therapy on Tinnitus: A Systematic Review. Medicine 2023, 102, e36199. https://doi.org/10.1097/MD.0000000000036199.
  11. Lam, N.N.H.; Lin, C.H.; Li, Y.L.; et al. An IoT-enabled EEG Headphones with Customized Music for Chronic Tinnitus Assessment and Symptom Management. Internet Things 2024, 28, 101411. https://doi.org/10.1016/j.iot.2024.101411.
  12. Simoes, J.; Schlee, W.; Schecklmann, M.; et al. Toward Personalized Tinnitus Treatment: An Exploratory Study Based on Internet Crowdsensing. Front. Public Health 2019, 7, 157. https://doi.org/10.3389/fpubh.2019.00157.
  13. Stockdale, D.; McFerran, D.; Brazier, P.; et al. An Economic Evaluation of the Healthcare Cost of Tinnitus Management in the UK. BMC Health Serv. Res. 2017, 17, 577. https://doi.org/10.1186/s12913-017-2527-2.
  14. Goldstein, E.; Ho, C.X.; Hanna, R.; et al. Cost of Care for Subjective Tinnitus in Relation to Patient Satisfaction. Otolaryngol. Head Neck Surg. 2015, 152, 518–523. https://doi.org/10.1177/0194599814566179.
  15. Chang, N.C.; Dai, C.Y.; Lin, W.Y.; et al. Prevalence of Persistent Tinnitus and Dizziness in an Elderly Population in Southern Taiwan. J. Int. Adv. Otol. 2019, 15, 99–105. https://doi.org/10.5152/iao.2019.6257.
  16. Newman, C.W.; Jacobson, G.P.; Spitzer, J.B. Development of the Tinnitus Handicap Inventory. Arch. Otolaryngol. Head Neck Surg. 1996, 122, 143–148. https://doi.org/10.1001/archotol.1996.01890140029007.
  17. Raj-Koziak, D.; Gos, E.; Swierniak, W.; et al. Visual Analogue Scales as a Tool for Initial Assessment of Tinnitus Severity: Psychometric Evaluation in a Clinical Population. Audiol. Neurotol. 2018, 23, 229–237. https://doi.org/10.1159/000494021.
  18. Adamchic, I.; Langguth, B.; Hauptmann, C.; Tass, P.A. Psychometric Evaluation of Visual Analog Scale for the Assessment of Chronic Tinnitus. Am. J. Audiol. 2012, 21, 215–225. https://doi.org/10.1044/1059-0889(2012/12-0010).
  19. Henry, J.A.; Griest, S.; Zaugg, T.L.; et al. Tinnitus Screener: Results from the First 100 Participants in an Epidemiology Study. Am. J. Audiol. 2016, 25, 153–160. https://doi.org/10.1044/2016_AJA-15-0076.
  20. Thielman, E.J.; Hall, D.A.; Henry, J.A. Tinnitus Screener: Short-Term Test–Retest Reliability. Am. J. Audiol. 2023, 32, 332–342. https://doi.org/10.1044/2022_AJA-22-00140.
  21. Lee, H.J.; Lee, D.C.; Kim, C.O. The Association between Serum Lipid Levels and Tinnitus Prevalence and Severity in Korean Elderly: A Nationwide Population-Based Cross-Sectional Study. Yonsei Med. J. 2024, 65, 156–162. https://doi.org/10.3349/ymj.2022.0626.
  22. Maihoub, S.; Mavrogeni, P.; Molnár, V.; et al. Tinnitus and Its Comorbidities: A Comprehensive Analysis of Their Relationships. J. Clin. Med. 2025, 14, 1285. https://doi.org/10.3390/jcm14041285.
  23. Boecking, B.; Klasing, S.; Brueggemann, P.; et al. Lipid Parameters and Depression in Patients with Chronic Tinnitus: A Cross-Sectional Observation. J. Psychosom. Res. 2024, 179, 111613. https://doi.org/10.1016/j.jpsychores.2024.111613.
  24. Erdogdu, S. The Frequency of Dyslipidemia in Patients with Idiopathic Tinnitus. North. Clin. Istanb. 2022, 9, 223–227. https://doi.org/10.14744/nci.2021.90187.
  25. Szumilas, M. Explaining Odds Ratios. J. Can. Acad. Child Adolesc. Psychiatry 2010, 19, 227–229.
  26. Langguth, B.; De Ridder, D. Minimal Clinically Important Difference of Tinnitus Outcome Measurement Instruments—A Scoping Review. J. Clin. Med. 2023, 12, 7117. https://doi.org/10.3390/jcm12227117.
  27. Piarulli, A.; Xu, W.; Tanglay, O.; et al. Tinnitus and Distress: An Electroencephalography Classification Study. Brain Commun. 2023, 5, fcad018. https://doi.org/10.1093/braincomms/fcad018.