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DOI: 10.1055/s-0038-1640127
Prediction of aspiration by means of Murray's secretion severity rating scale in head-and-neck cancer patients
Introduction:
Pharyngo-laryngo-tracheal accumulations of secretion are supposed to be indicative of dysphagia in head-and-neck cancer patients. However, it remains unclear whether such accumulations are associated with the risk of aspiration and to what extent they can predict a higher risk for aspirations. These two issues were examined in this study.
Methods:
A total of 239 head-and-neck cancer patients (age range 18 – 69 years, 80% males, tumor sites: 25% oral cavity, 48% oropharynx, 27% larynx/hypopharynx; UICC tumor stages I-IV) underwent a standardized FEES® procedure, including Murray's secretion severity rating scale (SSRS) and Rosenbek's penetration-aspiration scale (PAS). PAS values were categorized in 1 – 2, 3 – 5, 6 – 8 and cross-tabled with SSRS values. The association between SSRS values on the one hand and PAS values, age, tumor site, tumor stage, and therapy type on the other hand was assessed by Spearman correlations and Kruskal-Wallis H tests.
Results:
Results in the PAS categories 1 – 2 (80%) and 3 – 5 (53%) corresponded predominantly to the SSRS value 0 (χ2(6)= 64.20, p<.001). PAS category 6 – 8 was equally distributed over SSRS values 0 – 3. A moderate correlation was found between SSRS and PAS values (ρ=.503, p<.001). No significant associations were identified between SSRS and patients' tumor stage, age, and therapy type. SSRS values of patients with tumors in oral cavity were lower than those of patients with tumors in larynx/hypopharynx, and the latter yielded lower results than patients with tumors in oropharynx (χ2(2)= 9.54, p =.008).
Conclusions:
Accumulations of secretion in head-and-neck cancer patients do not allow to draw conclusions on the severity of aspiration, although the absence of such accumulations tends to correlate with the absence of aspiration.
Publikationsverlauf
Publikationsdatum:
18. April 2018 (online)
© 2018. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).
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