Prediction of Laryngeal Aspiration Using Voice Analysis

Can Voice Parameters Provide Cutoff Values to Predict Dysphagia in Individuals with Multiple Sclerosis?

In dysphagia assessment, along with well-defined measurements and signs, voice parameters can potentially support clinical decision as a marker, but more evidence is needed. This study aims to determine the voice parameters that can predict the risk of dysphagia and to determine optimal cutoff values in individuals with multiple sclerosis (IwMS). Seventy-six adults participated in the study, including 39 IwMS and 37 healthy individuals (HI). The study used the Dysphagia in Multiple Sclerosis Questionnaire (DYMUS), Gugging Swallowing Screen (GUSS), and Voice Handicap Index (VHI-10) and recorded voice samples using Praat programme. Voice recordings were taken pre- and post-swallowing. The voice parameters analysed are fundamental frequency (F0), standard deviation F0 (SD F0), jitter (local), shimmer (local), and harmonic-to-noise ratio (HNR). Roc analysis was performed to examine the diagnostic accuracy performance of the risk for dysphagia/penetration. The parameters of IwMS pre-swallowing differed significantly from those of HI on the VHI-10, DYMUS, GUSS scores, and jitter (local), shimmer (local), and HNR. IwMS but not HI exhibited significant differences in shimmer (local) and HNR between the pre- and post-swallowing measurements. In IwMS, GUSS revealed significant differences in shimmer (local) pre- and post-swallowing between the groups with and without dysphagia/penetration. In the ROC analysis results, the area under the curve (AUC) for shimmer (local) pre-swallowing was 73.1% (cutoff = 1.69); post-swallowing, it was 78.6% (cutoff = 1.57). In conclusion, IwMS can be associated with differences in shimmer (local) and HNR parameters, low quality of life-related to voice, and dysphagia/penetration risk. The AUC values for shimmer (local) in IwMS pre- and post-swallowing may help to strengthen diagnostic decisions of dysphagia risk.

A Scoping Review on the Intersection Between Voice and Swallowing Measures in Healthy and Disordered Populations

PURPOSE

Voice and swallowing are distinct functions that share anatomical and physiological properties; however, research investigating their intersection is limited. The purpose of this scoping review was to explore the literature surrounding the relationship between voice and swallowing measures in healthy adults and those with non-degenerative disorders. Specifically, we aimed to elucidate whether objective voice measures could be used as correlates of swallowing function.

METHOD

We systematically searched four databases (Embase, PubMed, CINAHL, and Web of Science) for relevant literature using a combination of key words and controlled vocabulary generated from the Yale Mesh Analyzer. The inclusion criteria consisted of peer-reviewed studies in the English language that reported on healthy adults and/or patients with non-degenerative neurological disorders and pulmonary diseases and contained instrumental and/or objective voice and swallowing measures. Two raters completed the abstract screening process followed by independent full-text reviews. Case studies, review studies, gray literature, or abstract-only studies were excluded.

RESULTS

Among 5,485 screened studies, 182 were fully reviewed, with only 11 studies meeting the inclusion criteria. Eight studies found an association between voice and swallowing objective measures, whereas the other three did not. Significant voice measures that were related to swallowing safety and/or physiology included maximum fundamental frequency (F0), F0 range, maximum phonation time, biomechanics of effortful pitch glides, and voice onset time.

CONCLUSIONS

Although there was heterogeneity in the measures used, specific objective voice measures showed promise in clinical practice as a screening tool for dysphagia. Further investigations are needed to validate the clinical utility of these measures across diverse patient populations.

Deep learning approach for dysphagia detection by syllable-based speech analysis with daily conversations

Dysphagia, a disorder affecting the ability to swallow, has a high prevalence among the older adults and can lead to serious health complications. Therefore, early detection of dysphagia is important. This study evaluated the effectiveness of a newly developed deep learning model that analyzes syllable-segmented data for diagnosing dysphagia, an aspect not addressed in prior studies. The audio data of daily conversations were collected from 16 patients with dysphagia and 24 controls. The presence of dysphagia was determined by videofluoroscopic swallowing study. The data were segmented into syllables using a speech-to-text model and analyzed with a convolutional neural network to perform binary classification between the dysphagia patients and control group. The proposed model in this study was assessed in two different aspects. Firstly, with syllable-segmented analysis, it demonstrated a diagnostic accuracy of 0.794 for dysphagia, a sensitivity of 0.901, a specificity of 0.687, a positive predictive value of 0.742, and a negative predictive value of 0.874. Secondly, at the individual level, it achieved an overall accuracy of 0.900 and area under the curve of 0.953. This research highlights the potential of deep learning modal as an early, non-invasive, and simple method for detecting dysphagia in everyday environments.

A deep learning approach to dysphagia-aspiration detecting algorithm through pre- and post-swallowing voice changes

Introduction

This study aimed to identify differences in voice characteristics and changes between patients with dysphagia-aspiration and healthy individuals using a deep learning model, with a focus on under-researched areas of pre- and post-swallowing voice changes in patients with dysphagia. We hypothesized that these variations may be due to weakened muscles and blocked airways in patients with dysphagia.

Methods

A prospective cohort study was conducted on 198 participants aged >40 years at the Seoul National University Bundang Hospital from October 2021 to February 2023. Pre- and post-swallowing voice data of the participants were converted to a 64-kbps mp3 format, and all voice data were trimmed to a length of 2 s. The data were divided for 10-fold cross-validation and stored in HDF5 format with anonymized IDs and labels for the normal and aspiration groups. During preprocessing, the data were converted to Mel spectrograms, and the EfficientAT model was modified using the final layer of MobileNetV3 to effectively detect voice changes and analyze pre- and post-swallowing voices. This enabled the model to probabilistically categorize new patient voices as normal or aspirated.

Results

In a study of the machine-learning model for aspiration detection, area under the receiver operating characteristic curve (AUC) values were analyzed across sexes under different configurations. The average AUC values for males ranged from 0.8117 to 0.8319, with the best performance achieved at a learning rate of 3.00e-5 and a batch size of 16. The average AUC values for females improved from 0.6975 to 0.7331, with the best performance observed at a learning rate of 5.00e-5 and a batch size of 32. As there were fewer female participants, a combined model was developed to maintain the sex balance. In the combined model, the average AUC values ranged from 0.7746 to 0.7997, and optimal performance was achieved at a learning rate of 3.00e-5 and a batch size of 16.

Conclusion

This study evaluated a voice analysis-based program to detect pre- and post-swallowing changes in patients with dysphagia, potentially aiding in real-time monitoring. Such a system can provide healthcare professionals with daily insights into the conditions of patients, allowing for personalized interventions.

Clinical Trial Registration

ClinicalTrials.gov, identifier NCT05149976.

Prediction of dysphagia aspiration through machine learning-based analysis of patients' postprandial voices

BACKGROUND

Conventional diagnostic methods for dysphagia have limitations such as long wait times, radiation risks, and restricted evaluation. Therefore, voice-based diagnostic and monitoring technologies are required to overcome these limitations. Based on our hypothesis regarding the impact of weakened muscle strength and the presence of aspiration on vocal characteristics, this single-center, prospective study aimed to develop a machine-learning algorithm for predicting dysphagia status (normal, and aspiration) by analyzing postprandial voice limiting intake to 3 cc.

METHODS

Conducted from September 2021 to February 2023 at Seoul National University Bundang Hospital, this single center, prospective cohort study included 198 participants aged 40 or older, with 128 without suspected dysphagia and 70 with dysphagia-aspiration. Voice data from participants were collected and used to develop dysphagia prediction models using the Multi-Layer Perceptron (MLP) with MobileNet V3. Male-only, female-only, and combined models were constructed using 10-fold cross-validation. Through the inference process, we established a model capable of probabilistically categorizing a new patient's voice as either normal or indicating the possibility of aspiration.

RESULTS

The pre-trained models (mn40_as and mn30_as) exhibited superior performance compared to the non-pre-trained models (mn4.0 and mn3.0). Overall, the best-performing model, mn30_as, which is a pre-trained model, demonstrated an average AUC across 10 folds as follows: combined model 0.8361 (95% CI 0.7667-0.9056; max 0.9541), male model 0.8010 (95% CI 0.6589-0.9432; max 1.000), and female model 0.7572 (95% CI 0.6578-0.8567; max 0.9779). However, for the female model, a slightly higher result was observed with the mn4.0, which scored 0.7679 (95% CI 0.6426-0.8931; max 0.9722). Additionally, the other models (pre-trained; mn40_as, non-pre-trained; mn4.0 and mn3.0) also achieved performance above 0.7 in most cases, and the highest fold-level performance for most models was approximately around 0.9. The 'mn' in model names refers to MobileNet and the following number indicates the 'width_mult' parameter.

CONCLUSIONS

In this study, we used mel-spectrogram analysis and a MobileNetV3 model for predicting dysphagia aspiration. Our research highlights voice analysis potential in dysphagia screening, diagnosis, and monitoring, aiming for non-invasive safer, and more effective interventions.

TRIAL REGISTRATION

This study was approved by the IRB (No. B-2109-707-303) and registered on clinicaltrials.gov (ID: NCT05149976).

Machine-learning assisted swallowing assessment: a deep learning-based quality improvement tool to screen for post-stroke dysphagia

Introduction

Post-stroke dysphagia is common and associated with significant morbidity and mortality, rendering bedside screening of significant clinical importance. Using voice as a biomarker coupled with deep learning has the potential to improve patient access to screening and mitigate the subjectivity associated with detecting voice change, a component of several validated screening protocols.

Methods

In this single-center study, we developed a proof-of-concept model for automated dysphagia screening and evaluated the performance of this model on training and testing cohorts. Patients were admitted to a comprehensive stroke center, where primary English speakers could follow commands without significant aphasia and participated on a rolling basis. The primary outcome was classification either as a pass or fail equivalent using a dysphagia screening test as a label. Voice data was recorded from patients who spoke a standardized set of vowels, words, and sentences from the National Institute of Health Stroke Scale. Seventy patients were recruited and 68 were included in the analysis, with 40 in training and 28 in testing cohorts, respectively. Speech from patients was segmented into 1,579 audio clips, from which 6,655 Mel-spectrogram images were computed and used as inputs for deep-learning models (DenseNet and ConvNext, separately and together). Clip-level and participant-level swallowing status predictions were obtained through a voting method.

Results

The models demonstrated clip-level dysphagia screening sensitivity of 71% and specificity of 77% (F1 = 0.73, AUC = 0.80 [95% CI: 0.78-0.82]). At the participant level, the sensitivity and specificity were 89 and 79%, respectively (F1 = 0.81, AUC = 0.91 [95% CI: 0.77-1.05]).

Discussion

This study is the first to demonstrate the feasibility of applying deep learning to classify vocalizations to detect post-stroke dysphagia. Our findings suggest potential for enhancing dysphagia screening in clinical settings. https://github.com/UofTNeurology/masa-open-source.

Dysphonia Outperforms Voice Change as a Clinical Predictor of Dysphagia

PURPOSE

Changes in voice quality after consuming food or drink have been used as a clinical indicator of dysphagia during the clinical swallowing evaluation (CSE); however, there is conflicting evidence of its efficacy. This study investigated if dysphonia and/or voice change after swallowing are valid predictors of penetration, aspiration, or pharyngeal residue. Our approach aimed to improve current methodologies by collecting voice samples in the fluoroscopy suite, implementing rater training to improve interrater reliability and utilizing continuous measurement scales, allowing for regression analyses.

METHOD

In this prospective study, 30 adults (aged 49-97 years) referred for a videofluoroscopic swallowing study (VFSS) were audio-recorded completing a sustained /i/ prior to VFSS and again after swallowing each bolus during the VFSS. Swallowing function was measured using the reorganized Penetration-Aspiration Scale and the Normalized Residue Ratio Scale. Following listener training, 84 voice samples were perceptually rated using the Consensus Auditory-Perceptual Evaluation of Voice (CAPE-V). Ordinal and logistic regression were used to determine whether voice quality and voice quality change after swallowing were predictors of airway invasion and pharyngeal clearance.

RESULTS

Results indicated that the presence of dysphonia at baseline during a sustained /i/ task as measured by the CAPE-V predicted airway invasion but not pharyngeal residue. Voice change after swallowing associated with vowel /i/ production as measured by the CAPE-V did not predict either dysphagia measure.

CONCLUSION

These results indicate that voice change during a sustained /i/ after swallowing appears unrelated to airway invasion or pharyngeal residue; however, in the absence of known laryngeal pathology, dysphonia prior to a CSE should alert speech-language pathologists of a possible comorbid dysphagia.

Assessment of radio(chemo)therapy-related dysphagia in head and neck cancer patients based on cough-related acoustic features: a prospective phase II national clinical trial (ACCOUGH-P/A trial)

BACKGROUND

Radiation-associated dysphagia is defined as impaired swallowing efficiency/safety following (chemo)radiotherapy in head and neck cancer patients. In a dysphagia framework, impaired coughing may lead to lung aspiration and fatal lung infection. Although cough efficacy is a predictor of the risk of aspiration, cough investigation is minimal in patients with radiation-associated dysphagia. Because cough is a transient signal, existing software for speech analysis are not appropriate. The goal of our project is to develop an assessment method using acoustic features related to voluntary and reflexive coughs as biomarkers of the risk of penetration/aspiration in patients with radiation-associated dysphagia.

METHODS

Healthy subjects and head and neck cancer patients with and without dysphagia will produce voluntary coughs, throat clearings and reflexive coughs. Recordings will be made using an acoustic microphone and a throat microphone. The recorded signals will be manually segmented and subsequently analysed with a software under development. Automatic final segmentation enables to measure cough duration. The first method of analysis includes temporal features: the amplitude contour, the sample entropy and the kurtosis. These features report respectively the strength, the unpredictability (turbulence noise due to the air jet) and the impulsive quality (burst) of the signal. The second method of analysis consists of a spectral decomposition of the relative cough signal energy into several frequency bands (0-400 Hz, 400-800 Hz, 800-1600 Hz, 1600-3200 Hz, > 3200 Hz). The primary outcome of this exploratory research project is the identification of a set of descriptive acoustic cough features in healthy subjects as reference data (ACCOUGH). The secondary outcome of this research in head and neck cancer patients with radiation-associated dysphagia includes the identification of (1) a set of descriptive acoustic cough features as biomarkers of penetration-aspiration (ACCOUGH-P/A), (2) swallowing scores, (3) voice features and (4) aerodynamic cough features.

DISCUSSION

This study is expected to develop methods of acoustic cough analysis to enhance the assessment of radiation-associated dysphagia in head and neck cancer patients following (chemo)radiation.

TRIAL REGISTRATION

International Standard Randomized Controlled Trials Number (ISRCTN) registry ISRCTN16540497. Accepted on 23 June 2023.

Establishment of a Multi-parameter Evaluation Model for Risk of Aspiration in Dysphagia: A Pilot Study

It's difficult for clinical bedside evaluations to accurately determine the occurrence of aspiration in patients. Although VFSS and FEES are the gold standards for clinical diagnosis of dysphagia, which are mainly used to evaluate people at high risk of dysphagia found by bedside screening, the operation is complicated and time-consuming. The aim of this pilot study was to present an objective measure based on a multi-parameter approach to screen for aspiration risk in patients with dysphagia. Objective evaluation techniques based on speech parameters were used to assess the oral motor function, vocal cord function, and voice changes before and after swallowing in 32 patients with dysphagia (16 low-risk aspiration group, 16 high-risk aspiration group). Student's t test combined with stepwise logistic regression were used to determine the optimal index. The best model consists of three parameters, and the equation is: logit(P) = - 3.824 - (0.504 × maximum phonation time) + (0.008 × second formant frequency of /u/) - 0.085 × (fundamental frequency difference before and after swallowing). An additional eight patients with dysphagia were randomly selected as the validation group of the model. When applied to validation, this model can accurately identify the risk of aspiration in 87.5% of patients, and the sensitivity is as high as 100%. Therefore, it has certain clinical practical value that may help clinicians to assess the risk of aspiration in patients with dysphagia, especially for silent aspiration.

Post-stroke respiratory complications using machine learning with voice features from mobile devices

Abnormal voice may identify those at risk of post-stroke aspiration. This study was aimed to determine whether machine learning algorithms with voice recorded via a mobile device can accurately classify those with dysphagia at risk of tube feeding and post-stroke aspiration pneumonia and be used as digital biomarkers. Voice samples from patients referred for swallowing disturbance in a university-affiliated hospital were collected prospectively using a mobile device. Subjects that required tube feeding were further classified to high risk of respiratory complication, based on the voluntary cough strength and abnormal chest x-ray images. A total of 449 samples were obtained, with 234 requiring tube feeding and 113 showing high risk of respiratory complications. The eXtreme gradient boosting multimodal models that included abnormal acoustic features and clinical variables showed high sensitivity levels of 88.7% (95% CI 82.6–94.7) and 84.5% (95% CI 76.9–92.1) in the classification of those at risk of tube feeding and at high risk of respiratory complications; respectively. In both cases, voice features proved to be the strongest contributing factors in these models. Voice features may be considered as viable digital biomarkers in those at risk of respiratory complications related to post-stroke dysphagia.

Listening for Dysphagia: Voice Quality Sequelae of Material in the Airway

PURPOSE

Postswallow voice abnormality is often assumed to indicate the presence of material in the laryngeal airway (MIA), but prior research has not shown definitive evidence of a causal relationship. This study investigated if endoscopically confirmed MIA (prandial material or secretions) generates specific voice quality attributes that can be perceptually identified by experienced listeners.

METHOD

Forty-four dysphagic adults underwent endoscopic evaluation of swallowing. Time-linked audiovisual recordings of pre- and postswallow phonation were analyzed to determine the presence, amount, and location of prandial material or secretions in the larynx during phonation. Expert listeners completed auditory-perceptual ratings of phonation samples.

RESULTS

Voice quality ratings did not differ significantly when there was MIA during postswallow phonation. However, judgments of voice quality abnormality for MIA samples were elevated when analyses controlled for effects of baseline dysphonia. Listeners were most likely to perceive voice quality abnormality when larger amounts of secretions were present, as compared to prandial material. Interrater reliability was variable and ranged from low to moderate across perceptual parameters.

CONCLUSIONS

MIA during phonation occurred for many participants, but perception of voice quality abnormality was variable when MIA was present. Baseline dysphonia is common among individuals with dysphagia and may limit perception of voice quality abnormalities generated by MIA. Secretions in the laryngeal airway may have a greater impact on voice quality parameters.

Machine learning based analysis of speech dimensions in functional oropharyngeal dysphagia

BACKGROUND AND OBJECTIVE

The normal swallowing process requires a complex coordination of anatomical structures driven by sensory and cranial nerves. Alterations in such coordination cause swallowing malfunctions, namely dysphagia. The dysphagia screening methods are quite subjective and experience dependent. Bearing in mind that the swallowing process and speech production share some anatomical structures and mechanisms of neurological control, this work aims to evaluate the suitability of automatic speech processing and machine learning techniques for screening of functional dysphagia.

METHODS

Speech recordings were collected from 46 patients with functional oropharyngeal dysphagia produced by neurological causes, and 46 healthy controls. The dimensions of speech including phonation, articulation, and prosody were considered through different speech tasks. Specific features per dimension were extracted and analyzed using statistical tests. Machine learning models were applied per dimension via nested cross-validation. Hyperparameters were selected using the AUC - ROC as optimization criterion.

RESULTS

The Random Forest in the articulation related speech tasks retrieved the highest performance measures (AUC=0.86±0.10, sensitivity=0.91±0.12) for individual analysis of dimensions. In addition, the combination of speech dimensions with a voting ensemble improved the results, which suggests a contribution of information from different feature sets extracted from speech signals in dysphagia conditions.

CONCLUSIONS

The proposed approach based on speech related models is suitable for the automatic discrimination between dysphagic and healthy individuals. These findings seem to have potential use in the screening of functional oropharyngeal dysphagia in a non-invasive and inexpensive way.

Using Voice Change as an Indicator of Dysphagia: A Systematic Review

Voice change post-swallow, observed during a clinical swallow examination, is often used as a clinical indicator of dysphagia risk. However, there has been limited research that evaluated the level of agreement between voice change and swallow dysfunction reported to date. This systematic review aims to investigate existing evidence relating to the relationship between vocal change post-swallow and swallow deficits identified on a Videofluoroscopic Swallow Study (VFSS). The studies were selected by two independent evaluators for inclusion, without restriction on language or date of publication and the methodological quality and the risk of bias were assessed using QUADAS-2. Following the PRISMA recommendation, 271 articles were analyzed, of which 17 were included in the study. Of these, the methodology described in five studies employed voice analyses using only acoustic methods, seven others conducted only auditory-perceptual analyses, and five other studies used both. Across the studies there was no homogeneity in the voice quality parameters assessed, analytic methods used, and results obtained. Forty seven per cent of the studies presented a high risk of bias in the analysis of vocal quality due to lack of clarity and blinding of VFSS. There was no homogeneity in the choice of consistencies evaluated during swallowing, as well as standardization of the outcome investigated in VFSS without a vocal parameter attributable to accurate detection in each outcome. It is not possible to obtain a consensus regarding the recommendation of the use of vocal evaluation as an accurate method for identifying swallowing alterations due to heterogeneity of the vocal evaluation methods, the outcomes evaluated in the VFSS examination, heterogeneity in food and liquid consistencies, and the methodological quality of the studies.

Noninvasive Respiratory Management of Spinal Cord Injury

Intubated ventilator-dependent patients with high-level spinal cord injury can be managed without tracheostomy tubes provided that they have sufficient cognition to cooperate and that any required surgical procedures are completed and they are medically stable. Intubation for a month or more than extubation to continuous noninvasive ventilatory support (NVS) can be safer long term than resort to tracheotomy. Noninvasive ventilation (NIV) is not conventionally being used for ventilatory support. Noninvasive interfaces include mouthpieces, nasal and oronasal interfaces, and intermittent abdominal pressure ventilators. NIV/NVS should never been used without consideration of mechanical insufflation-exsufflation for airway secretion clearance.

Respiratory muscle training in stroke patients with respiratory muscle weakness, dysphagia, and dysarthria - a prospective randomized trial

OBJECTIVE

To examine the efficacy of combined inspiratory and expiratory respiratory muscle training (RMT) with respect to the swallowing function, pulmonary function, functional performance, and dysarthria in patients with stroke.

DESIGN

Prospective, randomized controlled trial.

SETTING

Tertiary hospital.

PARTICIPANTS

The trial included 21 subjects (12 men, 9 women) aged 35 to 80 years presenting with 6 months history of unilateral stroke, respiratory muscle weakness (≥70% predicted maximal inspiratory pressure (MIP) and/or ≤70% maximal expiratory pressure (MEP)), dysphagia, or dysarthria. These subjects were randomly assigned to the control (n = 10, rehabilitation) and experimental (n = 11, rehabilitation with RMT) groups.

INTERVENTION

Inspiratory RMT starting from 30% to 60% of MIP and expiratory RMT starting from 15% to 75% of MEP for 5 days/week for 6 weeks.

MAIN OUTCOME MEASURES

MIP, MEP, pulmonary function, peak cough flow, perception of dyspnea, Fatigue Assessment Scale, Modified Rankin Scale, Brunnstrom stage, Barthel index, Functional Oral Intake Scale (FOIS), and parameters of voice analysis.

RESULTS

Significant differences were observed between both groups in terms of MIP, forced vital capacity (FVC), and forced expiratory volume per second (FEV1) of the percentage predicted. Significant difference was found with respect to the change in fatigue, shimmer percent, amplitude perturbation quotient, and voice turbulence index (VTI) according to the acoustic analysis in the RMT group. The FEV1/FVC ratio was negatively correlated with jitter percent, relative average perturbation, pitch perturbation quotient, and VTI; the maximum mid-expiratory flow (MMEF) and MMEF% were also negatively correlated with VTI. Significant differences among participants of the same group were observed while comparing the Brunnstrom stage before and after training of the affected limbs and the Barthel scale and FOIS scores in both the groups.

CONCLUSIONS

Altogether, 6-week combined inspiratory and expiratory RMT is feasible as adjuvant therapy for stroke patients to improve fatigue level, respiratory muscle strength, lung volume, respiratory flow, and dysarthria.Clinical trial registration number (Clinical Trial Identifier): NCT03491111.

Oropharyngeal Dysphagia Evaluation Tools in Adults with Solid Malignancies Outside the Head and Neck and Upper GI Tract: A Systematic Review

Dysphagia is often associated with head and neck and upper gastrointestinal (GI) tract cancers. Evidence suggests that those with solid malignancies in other primary sites may also have swallowing difficulties. Timely and accurate identification of dysphagia is important given the impact it has on hydration, medical treatment, nutrition, prognosis, and quality of life. A systematic review was conducted to identify swallow screening, evaluation, and quality of life tools for those with solid malignancies outside the head and neck and upper GI tract. Ten electronic databases, one journal and two published conference proceedings were searched. Following deduplication, 7435 studies were examined for relevance. No tools were validated solely in this cancer population, though some included this group in larger cohorts. Comments are provided on the diagnostic properties and applicability of these tools. In the absence of appropriate diagnostic instruments, the exact prevalence of dysphagia and its impact on clinical and psychosocial well-being remain unknown. Accurate and adequate measurement of therapeutic intervention is also compromised. This review establishes the need for validated dysphagia evaluation tools for this clinical population.

Independent exercise for glottal incompetence to improve vocal problems and prevent aspiration pneumonia in the elderly: a randomized controlled trial

Objectives:

To evaluate the effect of a self-controlled vocal exercise in elderly people with glottal closure insufficiency.

Design:

Parallel-arm, individual randomized controlled trial.

Methods:

Patients who visited one of 10 medical centers under the National Hospital Organization group in Japan for the first time, aged 60 years or older, complaining of aspiration or hoarseness, and endoscopically confirmed to have glottal closure insufficiency owing to vocal cord atrophy, were enrolled in this study. They were randomly assigned to an intervention or a control group. The patients of the intervention group were given guidance and a DVD about a self-controlled vocal exercise. The maximum phonation time which is a measure of glottal closure was evaluated, and the number of patients who developed pneumonia during the six months was compared between the two groups.

Results:

Of the 543 patients enrolled in this trial, 259 were allocated into the intervention group and 284 into the control; 60 of the intervention group and 75 of the control were not able to continue the trial. A total of 199 patients (age 73.9 ±7.25 years) in the intervention group and 209 (73.3 ±6.68 years) in the control completed the six-month trial. Intervention of the self-controlled vocal exercise extended the maximum phonation time significantly (p < 0.001). There were two hospitalizations for pneumonia in the intervention group and 18 in the control group, representing a significant difference (p < 0.001).

Conclusion:

The self-controlled vocal exercise allowed patients to achieve vocal cord adduction and improve glottal closure insufficiency, which reduced the rate of hospitalization for pneumonia significantly.

ClinicalTrial.govIdentifier-UMIN000015567

Bedside diagnosis of dysphagia: a systematic review

Dysphagia is associated with aspiration, pneumonia, and malnutrition, but remains challenging to identify at the bedside. A variety of exam protocols and maneuvers are commonly used, but the efficacy of these maneuvers is highly variable. We conducted a comprehensive search of 7 databases, including MEDLINE, Embase, and Scopus, from each database's earliest inception through June 9, 2014. Studies reporting diagnostic performance of a bedside examination maneuver compared to a reference gold standard (videofluoroscopic swallow study or flexible endoscopic evaluation of swallowing with sensory testing) were included for analysis. From each study, data were abstracted based on the type of diagnostic method and reference standard study population and inclusion/exclusion characteristics, design, and prediction of aspiration. The search strategy identified 38 articles meeting inclusion criteria. Overall, most bedside examinations lacked sufficient sensitivity to be used for screening purposes across all patient populations examined. Individual studies found dysphonia assessments, abnormal pharyngeal sensation assessments, dual axis accelerometry, and 1 description of water swallow testing to be sensitive tools, but none were reported as consistently sensitive. A preponderance of identified studies was in poststroke adults, limiting the generalizability of results. No bedside screening protocol has been shown to provide adequate predictive value for presence of aspiration. Several individual exam maneuvers demonstrated reasonable sensitivity, but reproducibility and consistency of these protocols was not established. More research is needed to design an optimal protocol for dysphagia detection.

Vocal Variability Post Swallowing in Individuals with and without Oropharyngeal Dysphagia

Introduction Voice modification after swallowing may indicate changes in the transit of the bolus.

Objective The aim of this study is to verify the use of perceptual voice analysis to detect oropharyngeal dysphagia.

Study Design Case series.

Methods Twenty-seven patients with dysphagia as diagnosed by videofluoroscopy and 25 without were evaluated. The sustained vowel /a/ was recorded before this exam and after swallowing different consistencies (pasty, liquid and solid). For the voice evaluation, the GRBAS scale (grade, roughness, breathiness, asthenia and strain) and the parameter “wet voice” were used. Three judges blinded to study group and time of emission performed voice analysis.

Results Individuals with dysphagia showed significant decrease in grade of voice and asthenia and increase in strain after swallowing pasty substances, differing from individuals without dysphagia who showed no modification of the parameters after swallowing. The wet voice parameter showed no difference after swallowing in both study groups.

Conclusion The decrease in grade and asthenia and increased strain are indicative of a swallowing disorder, indicating increased vocal strain to clean the vocal tract of food. The modification of vocal production after swallowing proved to be a trusted resource for detection of swallowing disorders.

Tracheal decannulation protocol in patients affected by traumatic brain injury

Introduction The frequency of tracheostomy in patients with traumatic brain injury (TBI) contrasts with the lack of objective criteria for its management. The study arose from the need for a protocol in the decision to remove the tracheal tube.

Objective To evaluate the applicability of a protocol for tracheal decannulation.

Methods A prospective study with 20 patients, ranging between 21 and 85 years of age (average 33.55), 4 of whom were women (20%) and 16 were men (80%). All patients had been diagnosed by a neurologist as having TBI, and the anatomical region of the lesion was known. Patients were evaluated following criteria for tracheal decannulation through a clinical evaluation protocol developed by the authors.

Results Decannulation was performed in 12 (60%) patients. Fourteen (70%) had a score greater than 8 on the Glasgow Coma Scale and only 2 (14%) of these were not able to undergo decannulation. Twelve (60%) patients maintained the breathing pattern with occlusion of the tube and were successfully decannulated. Of the 20 patients evaluated, 11 (55%) showed no signs suggestive of tracheal aspiration, and of these, 9 (82%) began training on occlusion of the cannula. The protocol was relevant to establish the beginning of the decannulation process. The clinical assessment should focus on the patient's condition to achieve early tracheal decannulation.

Conclusion This study allowed, with the protocol, to establish six criteria for tracheal decannulation: level of consciousness, respiration, tracheal secretion, phonation, swallowing, and coughing.

Acoustic characteristics of phonation in "wet voice" conditions

A perceptible change in phonation characteristics after a swallow has long been considered evidence that food and/or drink material has entered the laryngeal vestibule and is on the surface of the vocal folds as they vibrate. The current paper investigates the acoustic characteristics of phonation when liquid material is present on the vocal folds, using ex vivo porcine larynges as a model. Consistent with instrumental examinations of swallowing disorders or dysphagia in humans, three liquids of different Varibar viscosity ("thin liquid," "nectar," and "honey") were studied at constant volume. The presence of materials on the folds during phonation was generally found to suppress the higher frequency harmonics and generate intermittent additional frequencies in the low and high end of the acoustic spectrum. Perturbation measures showed a higher percentage of jitter and shimmer when liquid material was present on the folds during phonation, but they were unable to differentiate statistically between the three fluid conditions. The finite correlation dimension and positive Lyapunov exponent measures indicated that the presence of materials on the vocal folds excited a chaotic system. Further, these measures were able to reliably differentiate between the baseline and different types of liquid on the vocal folds.

Interdisciplinary evaluation of dysphagia: clinical swallowing evaluation and videoendoscopy of swallowing

Patients with dysphagia have impairments in many aspects, and an interdisciplinary approach is fundamental to define diagnosis and treatment. A joint approach in the clinical and videoendoscopy evaluation is paramount.

Aim

To study the correlation between the clinical assessment (ACD) and the videoendoscopic (VED) assessment of swallowing by classifying the degree of severity and the qualitative/descriptive analyses of the procedures.

Study design

cross-sectional, descriptive and comparative.

Materials and methods

held from March to December of 2006, at the Otolaryngology/Dysphagia ward of a hospital in the country side of São Paulo. 30 dysphagic patients with different disorders were assessed by ACD and VED. The data was classified by means of severity scales and qualitative/descriptive analysis.

Results

the correlation between severity ACD and VED scales pointed to a statistically significant low agreement (KAPA = 0.4) (p=0,006). The correlation between the qualitative/descriptive analysis pointed to an excellent and statistically significant agreement (KAPA=0.962) (p<0.001) concerning the entire sample.

Conclusion

the low agreement between the severity scales point to a need to perform both procedures, reinforcing VED as a doable procedure. The descriptive qualitative analysis pointed to an excellent agreement, and such data reinforces our need to understand swallowing as a process.