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. 2023 Jan 27;15(3):652.
doi: 10.3390/nu15030652.

Nutritional Biomarkers as Predictors of Dysphonia Severity in Patients with Ischemic Stroke

Affiliations

Nutritional Biomarkers as Predictors of Dysphonia Severity in Patients with Ischemic Stroke

Ji Min Kim et al. Nutrients. .

Abstract

Dysphonia and malnutrition are major problems in patients who have suffered an ischemic stroke. Tools to assess dysphonia severity include the dysphonia severity index (DSI) and maximum phonation time (MPT). This study aimed to investigate whether the nutritional biomarkers transferrin, albumin, and prealbumin could be predictors of dysphonia severity. A retrospective analysis was conducted between January 2018 and October 2022. A total of 180 patients who had suffered an ischemic stroke were included. Serum transferrin, albumin, and prealbumin levels were significantly correlated with DSI and MPT levels. In a multiple regression analysis, prealbumin and transferrin were significant predictors of DSI, whereas only prealbumin was a significant predictor of MPT. Serum transferrin, albumin, and prealbumin levels in patients who have suffered an ischemic stroke may correlate with dysphonia severity as assessed using DSI and MPT. These results may provide objective evidence that nutritional biomarkers affect dysphonia severity.

Keywords: dysphonia severity index; ischemic stroke; maximum phonation time; nutrition biomarkers.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Flow chart of study participants enrollment.

References

    1. Feigin V.L., Brainin M., Norrving B., Martins S., Sacco R.L., Hacke W., Fisher M., Pandian J., Lindsay P. World stroke organization (wso): Global stroke fact sheet 2022. Int. J. Stroke. 2022;17:18–29. doi: 10.1177/17474930211065917. - DOI - PubMed
    1. Tulics M.G., Vicsi K. The automatic assessment of the severity of dysphonia. Int. J. Speech Technol. 2019;22:341–350. doi: 10.1007/s10772-019-09592-y. - DOI
    1. Venketasubramanian N., Seshadri R., Chee N. Vocal cord paresis in acute ischemic stroke. Cerebrovasc. Dis. 1999;9:157–162. doi: 10.1159/000015947. - DOI - PubMed
    1. Naunheim M.R., Goldberg L., Dai J.B., Rubinstein B.J., Courey M.S. Measuring the impact of dysphonia on quality of life using health state preferences. Laryngoscope. 2020;130:E177–E182. doi: 10.1002/lary.28148. - DOI - PubMed
    1. Evitts P.M., Starmer H., Teets K., Montgomery C., Calhoun L., Schulze A., MacKenzie J., Adams L. The impact of dysphonic voices on healthy listeners: Listener reaction times, speech intelligibility, and listener comprehension. Am. J. Speech Lang. Pathol. 2016;25:561–575. doi: 10.1044/2016_AJSLP-14-0183. - DOI - PubMed