Oral Tactile Sensitivity in Stroke Patients

Overview

Orofacial impairment following stroke frequently involves a reduced chewing performance and dysphagia. This study investigated the sensitivity of oral tissues following stroke and its potential impact on chewing efficiency. The following two Null-hypotheses (H0) were tested: i. Post-stroke patients do not show a reduced intra-oral sensitivity compared to a healthy controls. ii. Intra-oral sensitivity is not correlated to chewing efficiency.

Material and Methods: Ethical approval was granted (Psy11-259, Psy 11-032) and written informed consent was obtained from all participants and/or their legal guardian. Patients were screened and recruited from the Division of Neurorehabilitation, Department of Clinical Neurosciences, University Hospital and University of Geneva, Geneva, Switzerland by a senior consultant neurologist (BL). Patients were included if they were hospitalized for stroke rehabilitation, were able to undergo psychophysical testing and presented with a facial impairment according to the House-Brackmann criteria ≥2 15. They were excluded if they presented with acute pain in the oro-facial sphere (nominal question) or an additional neuro-muscular disease. For the experiments, an in-depth oral examination was performed and the number of functional premolar units (OU) was noted. A premolar tooth with occluding antagonist counts as one OU whereas a molar is considered two OU (including third molars). Participants were asked with a simple dichotomic question if they perceived a dry mouth. Food-hoarding Food-hoarding was assessed with an ordinal Likert scale. Participants were asked if they currently "lost" foodstuff in the oral vestibule: Never (score 0), rarely (score1), occasionally (score2), frequently (score 3), very frequently (score 4) or always (score 5). Maximum voluntary bite force Maximum voluntary Bite Force (MBF) was assessed by means of an Occlusal Force-Meter GM 10® (Nagano Keiki, Higashimagome, Ohta-ku, Tokyo, Japan), which has an 8.6 mm thick bite element. The gauge was placed in-between the first molars and the participants were asked to bite three times as hard as possible for about three seconds. The MBF was tested independently on the right and left side. For the analysis, the peak MBF of each side was noted. Maximum voluntary lip force For the lip force measurements an oral screen (Dentaurum " Ulmer Modell " maxi, DENTAURUM GmbH\&Co.KG, Ispringen, Germany) was connected to a Dynamometer (ZP50-N, IMADA, Toyohashi, Japan). It was placed in the anterior oral vestibule and a horizontal pulling force was applied whilst the participant tried to withstand the force as long as possible. Per size, three peak recordings were averaged for analysis. Tactile detection thresholds The tactile detection threshold (TDT) of mechanoreceptors was evaluated using psychophysical testing methods. A touch sensation was elicited using von Frey filaments (OptiHair, MARSTOCK nerv test, Schriesheim, Germany) 16. This test kit consists of 11 monofilaments of varying stiffness, which are calibrated to apply defined forces of 0.25 - 512 mN (±10%). The filaments were pushed vertically for about 1 second to the different test sites on each side (ipsi- and contra-lesional in stroke-patients and right- and left side in controls). The tests started with a supra-threshold stimulus, which was consecutively lowered until the patient did not feel the filament anymore. Following the filament with the lowest perceived pressure, the applied force was re-increased until the patient recognized the touch again. This procedure was repeated twice in the same session to find the threshold with the stair-case-method. The final threshold was calculated from the mean of the three infra- and three supra-thresholds. If the patient felt even the lowest stimulus available (0.25mN), the infra-threshold was set to 0.125mN. Two-point discrimination To determine the patients' tactile spatial resolution, the static two-point discrimination threshold (2PD) was investigated 17. The smallest distance between two simultaneously presented punctiform stimuli was evaluated using a medical calliper (Schieblehre Zürcher Modell, 125mm, Hammacher Instrumente, Germany). The separation between the two tips ranged from 0 to 15 mm; the cut-off was set to 15 mm. A staircase method was used with descending distances. The participant was asked to indicate whether he/ she sensed one or two points and the corresponding distances were noted. The mean between those two distances was considered as individual minimum 2PD. The 2PD tests sites were the extraoral surface of the lip (approximately half way between philtrum and oral commissure) and the dorsum of the tongue opposing the second premolar. For TDT, the mucosa of the cheek opposing the second premolar and on the linea alba was used as additional test site. Whereas these test sites were evaluated on both sides, the 2PD test was additionally applied to the tip of the tongue without side discrimination. For one particular analysis all TDT readings per participant were averaged (TDT.global). Chewing efficiency Chewing efficiency was assessed with a previously developed and validated colour-mixing ability test, or bolus-kneading test, using chewing gum 18. The specimens used for this study were developed and produced for the 8020 Promotion Foundation (Japan) specifically for assessing masticatory performance in a research setting (Lotte™,Tokyo) and to be similar to the originally described method 19. The gum was composed of two individually packed beads (pink and azure colour) with similar hardness Shore Scale OO, Ø 2.4 mm, 1.11 N, pink beads: mean depth of indentation 0.2±0.01mm, mean Durometer 93.7; azure beads mean depth of indentation 0.1±0.02mm, mean Durometer 95.1). The two beads were manually stuck together and had a dimension of 18.8x14.2x3.9 mm; they were placed on the participant's tongue. The task was to chew the specimen for twenty cycles whilst being monitored by the operator (ED). The gum bolus was then retrieved from the oral cavity, placed into a plastic bag, pressed to a 1 mm thick wafer and both sides were scanned at 300dpi (Epson Perfection V750 Pro, Seiko Epson Corp., Japan). The compound images of both sides were then subject to a colourimetric evaluation using the custom-built software ViewGum© (dHAL Software, Greece, www.dhal.com). The software transposes the images to the HSI colour space and then calculates the hue value for each pixel in the pictures of the semi-automatically segmented gum wafers. If the colours are not mixed, two well-separated peaks on the hue axis are present which will gradually converge with increasing colour mixture. "Hue" is an angle in the HSI colour space, thus the circular variance of hue is defined as 1 minus the length of the average vector. ViewGum© displays the standard deviation between those colour peaks by taking the square root: SD = sqrt (Variance of Hue) 20. For consistency, the term Variance of Hue (VOH) will be used 18; it is considered as the measure of chewing performance in the context of this test - with a lower VOH indicating a higher the colour mixture and therefore a better chewing efficiency. Statistical analysis Normality of all numerical variables was rejected with empirical cumulative distribution function and QQ-plots. Therefore, results are reported as median values ± standard deviation. The two groups (stroke, controls) were compared with exact Wilcoxon-, Mann-Whitney-tests for numerical data and Fisher's exact tests for categorical data. Numerical and linear regression models were computed to analyse the impact of the investigated parameters on VOH. The relationship between a variable and a numerical end-point was measured with a Spearman correlation coefficient and a correlation test. In the case of a binary variable the end-point was transformed into a categorical variable that separates the values below and above the median. Odds Ratios OR and 95% Confidence Intervals (95%CI) were calculated to analyse the resulting 2x2 contingency table. All statistical tests were performed with R 3.2.2 (R Project for Statistical Computing, Vienna, Austria) by a senior bio-statistician.

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Outcomes