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https://codas.org.br/article/doi/10.1590/2317-1782/20212021214en
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Videokymographic index of glottic function: an analysis of diagnostic accuracy

Índice videoquimográfico da função glótica: análise da precisão diagnóstica

Alice Braga de Deus; Roberto da Costa Quinino; Marco Aurélio Rocha Santos; Ana Cristina Côrtes Gama

http://dx.doi.org/10.1590/2317-1782/20212021214en CoDAS, vol.35, n1, e20210214, 2023
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Abstract

Purpose

To develop the Videokymographic Index of Glottic Function (VIGF), a composite indicator from digital videokymography parameters, captured by high-speed videolaryngoscopy exams of women with and without laryngeal alterations of behavioral etiology.

Methods

The sample consisted of 92 women aged between 18 and 45 years. Fifty-five (55) women with behavioral dysphonia, presenting with laryngeal and voice alterations, and thirty-seven (37) women without any laryngeal and voice alterations. Voice evaluation was performed by consensus via an auditory-perceptual analysis of the sustained vowel /a/ at a habitual pitch and loudness. Voice classification was obtained by means of a general degree of dysphonia, where G0 indicated neutral voice quality and G1 to G3 indicated altered voice quality. Laryngeal images were captured via digital videokymography analysis of a sustained vowel /i/ at a habitual pitch and loudness. The VIGF was based on the midpoint of the glottal region for analysis. Logistic regression was performed using the MINITAB 19 program.

Results

Logistic regression was composed of two stages: Stage 1 consisted of the analysis of all variables, where the maximum opening and closed quotient variables showed statistical significance (p-value <0.05) and the model was well adjusted according to the Hosmer-Lemeshow test (p-value=0.794). Stage 2 consisted of the re-analysis of the selected variables, also showing a well-adjusted model (p-value=0.198). The VIGF was defined as follows: VIGF=e^(8.1318-0.2941AbMax-0.0703FechGlo)/1+e^(8.1318-0.2941AbMax-0.0703FechGlo).

Conclusion

The VIGF demonstrated a cut-off value equal to 0.71. The probability of success was 81.5%, sensitivity 76.4%, and specificity 89.2%.

Keywords

Kymography; Voice; Dysphonia; Diagnostic Test Approval; Larynx

Resumo

Objetivo

Elaborar um indicador composto denominado Índice Videoquimográfico da Função Glótica – IVFG, a partir de parâmetros da videoquimografia digital, captados pelo exame de videolaringoscopia de alta velocidade de mulheres sem e com alterações laríngeas de etiologia comportamental.

Método

A amostra foi composta por 92 mulheres, destas 55 apresentaram disfonia comportamental, com presença de alterações laríngeas e vocais, e 37 mulheres sem alterações laríngeas e vocais, entre 18 a 45 anos. A avaliação vocal foi realizada por consenso pela análise perceptivo-auditiva da vogal /a/ em frequência e intensidade habituais, e classificação através do grau geral da disfonia, onde G0 indicou qualidade vocal neutra e G1 a 3 qualidade vocal alterada. As imagens laríngeas foram obtidas pela gravação da emissão da vogal /i/, em frequência e intensidade habituais para análise da videoquimografia digital. A construção do IVFG se deu pela escolha do ponto médio da glote para análise e, elaboração foi realizada regressão logística pelo programa MINITAB 19.

Resultados

A regressão logística contou com duas etapas, sendo que a etapa 1 constou da análise de todas as variáveis, onde as variáveis abertura máxima e fechamento glótico apresentaram significância estatística (p-valor <0.05) e o modelo se encontrou bem ajustado de acordo com o teste de Hosmer-Lemeshow (p-valor=0,794); na etapa 2, as variáveis selecionadas foram novamente analisadas e o modelo também se mostrou bem ajustado (p-valor=0,198). O IVFG foi definido por IVFG=e^(8,1318-0,2941AbMax-0,0703FechGlo)/1+e^(8,1318-0,2941AbMax-0,0703FechGlo).

Conclusão

O IVFG apresenta valor de corte igual a 0,71. A probabilidade de acerto é de 81,5%, sensibilidade 76,4%, especificidade de 89,2%.

Palavras-chave

Quimografia; Voz; Disfonia; Aprovação de Teste de Diagnóstico; Laringe

Referências

  1. Behlau M, Azevedo R, Pontes P. Conceito de voz normal e classificação das disfonias. In: Behlau M, editor. Voz: o livro do especialista. 1ª ed. Rio de Janeiro: Revinter; 2001. p. 53-84.
  2. Patel RR, Awan SN, Barkmeier-Kraemer J, Courey M, Deliyski D, Eadie T, et al. Recommended protocols for instrumental assessment of voice: american speech-language-hearing association expert panel to develop a protocol for instrumental assessment of vocal function. Am J Speech Lang Pathol. 2018;27(3):887-905. http://dx.doi.org/10.1044/2018_AJSLP-17-0009 PMid:29955816.
  3. Góes TRV, Ferracciu CCS, Silva DRO. Associação entre a adesão da terapia vocal e perfil de atividades vocais em pacientes disfônicos comportamentais. CoDAS. 2016;28(5):595-601. http://dx.doi.org/10.1590/2317-1782/20162015232 PMid:27812672.
  4. Baravieira PB, Brasolotto AG, Hachiya A, Takahashi-Ramos MT, Tsuji DH, Montagnoli AN. Comparative analysis of vocal fold vibration using high-speed videoendoscopy and digital kymography. J Voice. 2014;28(5):603-7. http://dx.doi.org/10.1016/j.jvoice.2013.12.019 PMid:24726330.
  5. Nascimento UN, Santos MAR, Gama ACC. Digital videokymography: analysis of glottal closure in adults. J Voice. 2021. No prelo. PMid:34417083.
  6. Patel R, Dubrovskiy D, Dollinger M. Characterizing vibratory kinematics in children and adults with high-speed digital imaging. J Speech Lang Hear Res. 2014;57(2):S674-86. PMid:24686982.
  7. Larsson H, Hertegård S, Lindestad PA, Hammarberg B. Vocal fold vibrations: high-speed imaging, kymography, and acoustic analysis: a preliminary report. Laryngoscope. 2000;110(12):2117-22. http://dx.doi.org/10.1097/00005537-200012000-00028 PMid:11129033.
  8. Tsuji D, Dajer M, Ishikawa C, Takahashi M, Montagnoli A, Hachiya A. Improvement of vocal pathologies diagnosis using high-speed videolaryngoscopy. Int Arch Otorhinolaryngol. 2014;18(3):294-302. http://dx.doi.org/10.1055/s-0034-1372512 PMid:25992109.
  9. Svec JG, Schutte HK. Kymographic imaging of laryngeal vibrations. Curr Opin Otolaryngol Head Neck Surg. 2012;20(6):458-65. http://dx.doi.org/10.1097/MOO.0b013e3283581feb PMid:22931907.
  10. Tsutsumi M, Isotani S, Pimenta RA, Dajer ME, Hachiya A, Tsuji DH, et al. High-speed videolaryngoscopy: quantitative parameters of glottal area waveforms and high-speed kymography in healthy individuals. J Voice. 2017;31(3):282-90. http://dx.doi.org/10.1016/j.jvoice.2016.09.026 PMid:27793519.
  11. Svec JG, Schutte HK. Videokymography: high-speed line scanning of vocal fold vibration. J Voice. 1996;10(2):201-5. http://dx.doi.org/10.1016/S0892-1997(96)80047-6 PMid:8734395.
  12. Sulica L. Laryngoscopy, stroboscopy and other tools for the evaluation of voice disorders. Otolaryngol Clin North Am. 2013;46(1):21-30. http://dx.doi.org/10.1016/j.otc.2012.09.001 PMid:23177402.
  13. Mingoti SA. Análise de dados através de métodos de estatística multivariada: uma abordagem aplicada de dados. Belo Horizonte: UFMG; 2005. 295 p.
  14. Kim H, Gao S, Yi B, Shi R, Wan Q, Huang Z. Validation of the dysphonia severity index in the Dr. Speech Program. J Voice. 2019;33(6):948.e23-9. http://dx.doi.org/10.1016/j.jvoice.2019.08.011 PMid:31526665.
  15. Awan SN, Roy N, Zhang D, Cohen SM. Validation of the Cepstral Spectral Index of Dysphonia (CSID) as a screening tool for voice disorders: development of clinical cutoff scores. J Voice. 2016;30(2):130-44. http://dx.doi.org/10.1016/j.jvoice.2015.04.009 PMid:26361215.
  16. Englert M, Barsties V, Latoszek B, Maryn Y, Behlau M. Validation of the acoustic voice quality index, version 03.01, to the Brazilian Portuguese Language. J Voice. 2021;35(1):160.e15-21. http://dx.doi.org/10.1016/j.jvoice.2019.07.024 PMid:31474432.
  17. Cohen JF, Korevaar DA, Altman DG, Bruns DE, Gatsonis CA, Hooft L, et al. STARD 2015 guidelines for reporting diagnostic accuracy studies: explanation and elaboration. BMJ Open. 2016;6(11):e012799. http://dx.doi.org/10.1136/bmjopen-2016-012799 PMid:28137831.
  18. Englert M, Barsties V, Latoszek B, Maryn Y, Behlau M. Validation of the acoustic breathiness index to the Brazilian Portuguese language. Logoped Phoniatr Vocol. 2022;47(1):56-62. http://dx.doi.org/10.1080/14015439.2020.1864467 PMid:33404289.
  19. Dejonckere PH, Bradley P, Clemente P, Cornut G, Crevier-Buchman L, Friedrich G, et al. A basic protocol for functional assessment of voice pathology, especially for investigating the efficacy of (phonosurgical) treatments and evaluating new assessment techniques: guideline elaborated by the Committee on Phoniatrics of the European Laryngological Society (ELS). Eur Arch Otorhinolaryngol. 2001;258(2):77-82. http://dx.doi.org/10.1007/s004050000299 PMid:11307610.
  20. van Houtte E, van Lierde K, D’Haeseleer E, Claeys S. The prevalence of laryngeal pathology in a treatment-seeking population with dysphonia. Laryngoscope. 2010;120(2):306-12. http://dx.doi.org/10.1002/lary.20696 PMid:19957345.
  21. Woo P. Objective measures of laryngeal imaging: what have we learned since Dr. Paul Moore. J Voice. 2013;28(1):69-81. http://dx.doi.org/10.1016/j.jvoice.2013.02.001 PMid:24094798.
  22. Hosmer DW, Lemeshow S. Applied logistic regression. 2nd ed. New York: John Wiley & Sons; 1985. p. 156-64.
  23. Louviere JJ, Hensher AD, Swait DJ. Stated choice methods. New York: Cambridge University Press; 2000. http://dx.doi.org/10.1017/CBO9780511753831
  24. Menard S. Coefficients of determination for multiple logistic regression analysis. Am Stat. 2000;54:17-24.
  25. Mittlböck M, Schemper M. Explained variation in logistic regression. Stat Med. 1996;15(19):1987-97. http://dx.doi.org/10.1002/(SICI)1097-0258(19961015)15:19<1987::AID-SIM318>3.0.CO;2-9 PMid:8896134.
  26. Behrman A. Common practices of voice therapists in the evaluation of patients. J Voice. 2005;19(3):454-69. http://dx.doi.org/10.1016/j.jvoice.2004.08.004 PMid:16102671.
  27. Wittenberg T, Tigges M, Mergell P, Eysholdt U. Functional imaging of vocal fold vibration: digital multislice high-speed kymography. J Voice. 2000;14(3):422-42. http://dx.doi.org/10.1016/S0892-1997(00)80087-9 PMid:11021509.
  28. Qiu Q, Schutte HK, Gu L, Yu Q. An automatic method to quantify the vibration properties of human vocal folds via videokymography. Folia Phoniatr Logop. 2003;55(3):128-36. http://dx.doi.org/10.1159/000070724 PMid:12771464.
  29. Deliyski DD. Endoscope motion compensation for laryngeal high-speed videoendoscopy. J Voice. 2005;19(3):485-96. http://dx.doi.org/10.1016/j.jvoice.2004.07.006 PMid:16102674.
  30. Patel R, Dailey S, Bless D. Comparison of high-speed digital imaging with stroboscopy for laryngeal imaging of glottal disorders. Ann Otol Rhinol Laryngol. 2008;117(6):413-24. http://dx.doi.org/10.1177/000348940811700603 PMid:18646437.
  31. Pigozzo MN, Laganá DC, Campos TN, Yamada MCM. A importância dos índices em pesquisa clínica odontológica: uma revisão da literatura. Odontol Univ Cid São Paulo. 2008;20(3):280-7.
  32. Popolo PS, Johnson AM. Relating cepstral peak prominence to cyclical parameters of vocal fold vibration from high-speed videoendoscopy using machine learning: a pilot study. J Voice. 2021;35(5):703-16. http://dx.doi.org/10.1016/j.jvoice.2020.01.026 PMid:32173147.
     
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