A risk scoring system for predicting Streptococcus suis hearing loss: A 13-year retrospective cohort study

• Main Authors: Ajaree Rayanakorn, Wasan Katip, Bey Hing Goh, Peninnah Oberdorfer, Learn Han Lee
• Format: Journal
• Published: 2020
• Subjects: Agricultural and Biological Sciences; Biochemistry, Genetics and Molecular Biology; Multidisciplinary
• Online Access: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85078983845&origin=inward; http://cmuir.cmu.ac.th/jspui/handle/6653943832/68205
• Institution: Chiang Mai University

© 2020 Rayanakorn et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Background Streptococcus suis (S.suis) is an emerging zoonosis disease with a high prevalence in Southeast Asia. There are over 1,500 cases reported globally in which majority of cases are from Thailand followed by Vietnam. The disease leads to meningitis in human with sensorineural hearing loss (SNHL) as the most common complication suffered by the patients. Early diagnosis and treatment is important to prevent severe neurological complication. In this study, we aim to develop an easy-to-use risk score to promote early diagnosis and detection of S.suis in patients who potentially develop hearing loss. Methods Data from a retrospective review of 13-year S.suis patient records in a tertiary hospital in Chiang Mai, Northern, Thailand was obtained. Univariate and multivariate logistic regressions were employed to develop a predictive model. The clinical risk score was constructed from the coefficients of significant predictors. Area under the receiver operator characteristic curve (AuROC) was identified to verify the model discriminative performance. Bootstrap technique with 1000-fold bootstrapping was used for internal validation. Key Results Among 133 patients, the incidence of hearing loss was 31.6% (n = 42). Significant predictors for S. suis hearing loss were meningitis, raw pork consumption, and vertigo. The predictive score ranged from 0-4 and correctly classified 81.95% patients as being at risk of S.suis hearing loss. The model showed good power of prediction (AuROC: 0.859; 95%CI 0.785- 0.933) and calibration (AuROC: 0.860; 95%CI 0.716-0.953). Conclusions To our best knowledge, this is the first risk scoring system development for S.suis hearing loss. We identified meningitis, raw pork consumption and vertigo as the main risk factors of S.suis hearing loss. Future studies are needed to optimize the developed scoring system and investigate its external validity before recommendation for use in clinical practice.