Dynamic suprahyoid muscle ultrasound in acute stroke: a prospective observational study for developing a dysphagia severity score.

BACKGROUND

Early identification and appropriate management of dysphagia are critical for improving outcomes of acute ischemic stroke.

AIM: To develop a simple and reliable scoring system to predict the severity of dysphagia in patients with acute ischemic stroke by integrating ultrasound (US) parameters with clinical variables.

DESIGN

Prospective, cross-sectional observational study.

SETTING

Inpatient neurology department of a university-affiliated hospital.

POPULATION: A total of 212 patients with acute ischemic stroke were prospectively enrolled in this study. The mild dysphagia group and severe dysphagia group comprised 146 patients and 66 patients, respectively. Group assignment was based on the need for dietary modifications confirmed via retrospective review of dietary status, videofluoroscopic swallowing study results, and the occurrence of aspiration pneumonia during hospitalization.

METHODS

Dynamic M-mode US of the suprahyoid muscle (SHM) was performed during swallowing. The following six SHM parameters were obtained: SHM thickness (baseline thickness of the SHM); SHM displacement (peak-to-peak amplitude of SHM movement); SHM difference (SHM displacement - SHM thickness); SHM ratio (SHM displacement/SHM thickness); peak-to-peak time; and total duration. The study population was randomly split into training (70%) and test (30%) sets. Least absolute shrinkage and selection operator and logistic regression analyses were performed to identify significant predictors of severe dysphagia. These predictors were used to develop and validate a simple scoring system.

RESULTS

Brainstem lesion, bilateral lesion, National Institutes of Health Stroke Scale (NIHSS) score, SHM difference, and total duration were identified as key predictors of severe dysphagia. A simple scoring system based on these variables showed excellent discriminative performance. Areas under the receiver-operating characteristic curves (AUCs) of the training set and the test set were 0.963 and 0.935, respectively. A cutoff of ≥3 points yielded sensitivity of 97.9% and specificity of 86.4% for the training set as well as sensitivity of 78.9% and specificity of 95.3% for the test set.

CONCLUSIONS

This simple scoring system combining US and clinical parameters enabled early identification of patients at increased risk for severe dysphagia.

CLINICAL REHABILITATION IMPACT: The dysphagia severity prediction score can facilitate timely management of patients with acute ischemic stroke, thus potentially reducing complications and enhancing dysphagia rehabilitation.