The effect of type 1 diabetes mellitus on voice in pediatric patients

Kara, İrfan; Temiz, Fatih; Doğaner, Adem; Yıldız, Muhammed Gazi; Bilal, Nagihan; Orhan, İsrafil

doi:10.1007/s00405-022-07543-z

Cited by 2 publications

(2 citation statements)

References 29 publications

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“…There is also a significant lowering maximum phonation time in individuals with diabetes neuropathy 25 . There is only one study in pediatric individuals between 6 and 18 years that found no significant difference in acoustic voice quality index in children with type 1 diabetes compared to age and sex-matched healthy participants 26 . Further study on voice characteristic analysis are needed to understand more about effect of diabetes in voice.…”

Section: Discussionmentioning

confidence: 95%

Predicting glycemic control status and high blood glucose levels through voice characteristic analysis in patients with cystic fibrosis-related diabetes (CFRD)

Suppakitjanusant,

Kasemkosin,

Sivapiromrat

et al. 2023

Sci Rep

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Cystic fibrosis-related diabetes (CFRD) is associated with reduced life expectancy in adults with cystic fibrosis (CF). Voice analysis may be a convenient method for diagnosing and monitoring CFRD. This study aims to determine the relationship between voice characteristics and markers of glucose and glycemic control and to identify if voice analysis can predict high blood glucose levels and glycemic control in adults with CFRD. We conducted a prospective cross-sectional study in adults with CF from March to December 2021. We recorded 3-second voice samples of a sustained /a/ vowel and analyzed voice characteristic using the Computerized Speech Lab with the Multi-Dimensional Voice Program. In female participants with CFRD, the noise-to-harmonic ratio was significantly lower in those with HbA1c ≥ 7. Furthermore, fundamental frequency variation was significantly lower in both male and female participants with CFRD who had a glucose level of 200 mg/dL or higher at the time of collection. This finding was also associated with a high level of point-of-care glucose. The human voice has potential as a non-invasive tool for measuring glucose levels and glycemic control status in CFRD patients in the future.

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Section: Discussionmentioning

confidence: 95%

Predicting glycemic control status and high blood glucose levels through voice characteristic analysis in patients with cystic fibrosis-related diabetes (CFRD)

Suppakitjanusant,

Kasemkosin,

Sivapiromrat

et al. 2023

Sci Rep

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show abstract

“…The technique was determined to be useful by the authors, and the perceived phonatory effort decreased significantly at the last assessment point [39]. The authors of [40] attempted to assess the influence of type 1 diabetes mellitus on the voice in pediatric patients using voice quality analysis. The study findings revealed that the AVQI value was higher in the patient group, although not statistically significant.…”

Section: State Of the Art Reviewmentioning

confidence: 99%

Pareto-Optimized AVQI Assessment of Dysphonia: A Clinical Trial Using Various Smartphones

et al. 2023

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Multiparametric indices offer a more comprehensive approach to voice quality assessment by taking into account multiple acoustic parameters. Artificial intelligence technology can be utilized in healthcare to evaluate data and optimize decision-making processes. Mobile devices provide new opportunities for remote speech monitoring, allowing the use of basic mobile devices as screening tools for the early identification and treatment of voice disorders. However, it is necessary to demonstrate equivalence between mobile device signals and gold standard microphone preamplifiers. Despite the increased use and availability of technology, there is still a lack of understanding of the impact of physiological, speech/language, and cultural factors on voice assessment. Challenges to research include accounting for organic speech-related covariables, such as differences in conversing voice sound pressure level (SPL) and fundamental frequency (f0), recognizing the link between sensory and experimental acoustic outcomes, and obtaining a large dataset to understand regular variation between and within voice-disordered individuals. Our study investigated the use of cellphones to estimate the Acoustic Voice Quality Index (AVQI) in a typical clinical setting using a Pareto-optimized approach in the signal processing path. We found that there was a strong correlation between AVQI results obtained from different smartphones and a studio microphone, with no significant differences in mean AVQI scores between different smartphones. The diagnostic accuracy of different smartphones was comparable to that of a professional microphone, with optimal AVQI cut-off values that can effectively distinguish between normal and pathological voice for each smartphone used in the study. All devices met the proposed 0.8 AUC threshold and demonstrated an acceptable Youden index value.

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The effect of type 1 diabetes mellitus on voice in pediatric patients

Cited by 2 publications

References 29 publications

Predicting glycemic control status and high blood glucose levels through voice characteristic analysis in patients with cystic fibrosis-related diabetes (CFRD)

Predicting glycemic control status and high blood glucose levels through voice characteristic analysis in patients with cystic fibrosis-related diabetes (CFRD)

Pareto-Optimized AVQI Assessment of Dysphonia: A Clinical Trial Using Various Smartphones

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