Stroke diagnosis using tongue examination
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Tongue Examination in Stroke Diagnosis: Traditional and Modern Approaches
Tongue examination has long been used in traditional medicine as a non-invasive tool to help diagnose and monitor stroke. Recent research has explored both the traditional visual assessment of tongue features and the use of objective measurements and machine learning to improve accuracy and reliability.
Traditional Tongue Diagnosis for Stroke: Visual Features and Pattern Identification
Traditional Chinese and Korean medicine practitioners use tongue diagnosis to identify patterns and syndromes in stroke patients. Key tongue features assessed include tongue color, shape, fur (coating) color and thickness, dryness, and special signs like ecchymoses (bruising), fissures, teeth marks, and deviation angle. Studies have found that certain tongue features—such as pale or bluish color, ecchymoses, and tongue deviation—are significantly more common in patients with acute ischemic stroke compared to healthy individuals, suggesting these features are associated with increased stroke risk 24.
Pattern identification using tongue diagnosis can help differentiate between types of stroke syndromes, such as Qi deficiency, Dampness & Phlegm, Fire & Heat, Eum deficiency, and Blood Stasis, each with distinct tongue presentations . Reviews of multiple studies confirm that tongue diagnosis is valuable for pattern identification, prognosis evaluation, and assessing neurological deficits in stroke patients .
Reliability and Standardization of Tongue Diagnosis
Interobserver reliability in tongue diagnosis is generally moderate to high, especially for certain features like mirror, spotted, and bluish-purple tongues. However, agreement is lower for features such as pale tongue color and fur quality, highlighting the need for more objective and standardized criteria, as well as enhanced clinician training 35. Efforts are ongoing to standardize tongue diagnosis for stroke, including the development of detailed case report forms and multi-center data collection .
Objective Tongue Feature Analysis: Technology and Deep Learning
To address subjectivity in traditional tongue diagnosis, researchers have developed automatic tongue diagnosis systems and deep learning models. These systems use image analysis to objectively extract and classify tongue features, such as color, coating, and texture, from photographs. Deep learning models have shown improved accuracy in recognizing stroke-related tongue features compared to traditional single-task models, making them promising tools for real-time evaluation and diagnosis during stroke rehabilitation 26.
Tongue Pressure Measurement: Screening for Dysphagia and Aspiration Risk
Beyond visual assessment, measuring tongue pressure provides a quantitative method to evaluate swallowing function in stroke patients. Low tongue pressure is associated with a higher risk of aspiration and pneumonia, common complications after stroke. Studies show that tongue pressure measurement is a simple, noninvasive, and sensitive tool for predicting swallowing dysfunction and pneumonia risk in acute stroke patients 78910. While tongue pressure alone may not be sufficient for comprehensive screening, combining it with other bedside tests can improve diagnostic accuracy and help guide clinical decision-making 789.
Conclusion
Tongue examination, both visual and quantitative, plays a valuable role in stroke diagnosis and management. Traditional tongue diagnosis helps identify stroke patterns and assess prognosis, but its reliability can be improved with standardization and training. Objective methods, including image analysis and tongue pressure measurement, enhance the accuracy and reproducibility of tongue-based assessments. Combining traditional insights with modern technology offers a promising approach for non-invasive, accessible stroke diagnosis and monitoring.
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