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Effectiveness of Conventional Swallowing Therapy in Acute Stroke Patients with Dysphagia.

ABSTRACT: Background:Dysphagia is a common problem in acute stroke patient. Aspiration pneumonia increases in this group. Swallowing therapy is immediately conducted in a stable stroke patient. An effectiveness of our program has not been determined. Objective:To determine an effectiveness of conventional swallowing therapy in acute stroke patients with dysphagia. Methods:We retrospectively reviewed data from medical records of acute stroke patients with dysphagia who participated a swallowing therapy from January 2017 to June 2017. Fifty-seven acute stroke patients with dysphagia (26 males and 31 females) were participating in a conventional swallowing therapy (50 minutes a day for 3 days per week). A functional oral intake scale (FOIS) and swallow function scoring system (SFSS) were used to determine an effectiveness of the swallowing therapy. FOIS and SFSS scores before the first therapy session and after the last therapy session were compared using a paired t-test. Results:The mean age of the patient was 69.5 ± 15.35 years. The period from stroke onset to the first swallowing therapy session was 7.5 ± 6.69 days. The number of therapy was 5.6 ± 2.83 sessions. Participants showed a significant improvement of the FOIS (mean score increased from 1.74 to 3.30 points, P = 0.001) and SFSS (mean score increased from 2.51 to 3.68 points, P = 0.001). Forty-two percent of patients with tube dependent change to total oral intake. Conclusion:Conventional swallowing therapy is an effective treatment in acute stroke with dysphagia.

SUBMITTER: Jongprasitkul H

PROVIDER: S-EPMC7556095 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Effectiveness of Conventional Swallowing Therapy in Acute Stroke Patients with Dysphagia.

Jongprasitkul Hathaya H Kitisomprayoonkul Wasuwat W

Rehabilitation research and practice 20201005

<h4>Background</h4>Dysphagia is a common problem in acute stroke patient. Aspiration pneumonia increases in this group. Swallowing therapy is immediately conducted in a stable stroke patient. An effectiveness of our program has not been determined.<h4>Objective</h4>To determine an effectiveness of conventional swallowing therapy in acute stroke patients with dysphagia.<h4>Methods</h4>We retrospectively reviewed data from medical records of acute stroke patients with dysphagia who participated a ...[more]

PMID: 33083059

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Project description:IntroductionPost-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.MethodsIn 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.ResultsThe 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]).DiscussionThis 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.

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Effectiveness of Conventional Swallowing Therapy in Acute Stroke Patients with Dysphagia.

Publications

Effectiveness of Conventional Swallowing Therapy in Acute Stroke Patients with Dysphagia.

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