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The Prediction of Risk of Penetration–Aspiration Via Hyoid Bone Displacement Features

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Abstract

Videofluoroscopic swallow studies are widely used in clinical and research settings to assess swallow function and to determine physiological impairments, diet recommendations, and treatment goals for people with dysphagia. Videofluoroscopy can be used to analyze biomechanical events of swallowing, including hyoid bone displacement, to differentiate between normal and disordered swallow functions. Previous research has found significant associations between hyoid bone displacement and penetration/aspiration during swallowing, but the predictive value of hyoid bone displacement during swallowing has not been explored. The primary objective of this study was to build a model based on aspects of hyoid bone displacement during swallowing to predict the extent of airway penetration or aspiration during swallowing. Aspects of hyoid bone displacement from 1433 swallows from patients referred for videofluoroscopy were analyzed to determine which aspects predicted risk of penetration and aspiration according to the Penetration–Aspiration Scale. A generalized estimating equation incorporating components of hyoid bone displacement and variables shown to impact penetration and aspiration (such as age, bolus volume, and viscosity) was used to evaluate penetration and aspiration risk. Results indicated that anterior-horizontal hyoid bone displacement was the only aspect of hyoid bone displacement predictive of penetration and aspiration risk. Further research should focus on improving the model performance by identifying additional physiological swallowing events that predict penetration and aspiration risk. The model built for this study, and future modified models, will be beneficial for clinicians to use in the assessment and treatment of people with dysphagia, and for potentially tracking improvement in hyolaryngeal excursion resulting from dysphagia treatment, thus mitigating adverse outcomes that can occur secondary to dysphagia.

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Acknowledgement

The authors acknowledge Dr. Aliaa Elbahnasy Sabry for her critical review and suggestions on the final manuscript.

Funding

This study was funded by two grants from the Eunice Kennedy Shriver National Institute of Child Health & Human Development of the National Institutes of Health under Award Number R01HD092239, while the data was collected under Award Number R01HD074819. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, 15261, USA

    Zhenwei Zhang & Ervin Sejdić

  2. Division of Geriatrics, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, 15261, USA

    Subashan Perera

  3. Department of Communication Science and Disorders, University of Pittsburgh, Pittsburgh, PA, 15260, USA

    Cara Donohue, Atsuko Kurosu, Amanda S. Mahoney & James L. Coyle

Authors
  1. Zhenwei Zhang
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  2. Subashan Perera
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  3. Cara Donohue
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  4. Atsuko Kurosu
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  5. Amanda S. Mahoney
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  6. James L. Coyle
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  7. Ervin Sejdić
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Corresponding author

Correspondence to Ervin Sejdić.

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We have no conflict of interest to declare.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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Informed consent was obtained from all individual participants included in the study.

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Appendix

Appendix

Prediction equation steps:

  1. 1.

    Let \(XB=-3.479-0.0583\times (x1_min2max_distance)+ 0.0265\times (age)-0.0004\times (duration)\)

  2. 2.

    Subtract from XB 0.4435 if the swallow is single, add to XB 0.4545 if the swallow is multiple 1, or do nothing if multiple 2.

  3. 3.

    Subtract from XB 0.1398 if the \(\hbox {sex}=2(\hbox {female}?)\), or do nothing if \(\hbox {sex}=1(\hbox {male}?)\).

  4. 4.

    Add 1.2862 to XB if \(\hbox {viscosity}=\hbox {thin}\), add 0.7049 if nectar, subtract 0.5334 if pudding, and do nothing if cookie.

  5. 5.

    Add to XB 0.1622 if spoon, or do nothing if cup.

  6. 6.

    Add to XB 0.0994 if chin down, or do nothing if head position is neutral.

  7. 7.

    Compute the probability of a high PA swallow as \(exp(XB)/(1+exp(XB))\).

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Zhang, Z., Perera, S., Donohue, C. et al. The Prediction of Risk of Penetration–Aspiration Via Hyoid Bone Displacement Features. Dysphagia 35, 66–72 (2020). https://doi.org/10.1007/s00455-019-10000-5

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  • DOI: https://doi.org/10.1007/s00455-019-10000-5

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