Traditional Chinese medicine syndrome patterns and associated factors in adults with type 2 diabetes and metabolic syndrome: a data-driven analysis - Report - MDSpire
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Traditional Chinese medicine syndrome patterns and associated factors in adults with type 2 diabetes and metabolic syndrome: a data-driven analysis
Clinical Report: Analysis of TCM Syndrome Classifications in Type 2 Diabetes
Overview
This study identifies distinct Traditional Chinese Medicine (TCM) syndrome subgroups in adults with type 2 diabetes mellitus (T2DM) and metabolic syndrome (MetS) using data-driven methods. It highlights the association of these syndromes with various sociodemographic and clinical factors.
Background
The co-occurrence of T2DM and MetS presents significant health risks, necessitating effective management strategies. Traditional Chinese Medicine offers a holistic approach to treatment, yet its syndrome classifications require empirical validation. Understanding these syndromes can enhance personalized treatment and improve patient outcomes.
Data Highlights
TCM Syndrome
Prevalence (%)
Spleen and Kidney Yang Deficiency
17.62
Qi and Yin Deficiency
22.97
Kidney Essence Deficiency
10.89
Yin and Yang Deficiency
22.97
Phlegm and Blood Stasis
25.54
Key Findings
Five symptom-based syndromes were identified: Phlegm and Blood Stasis (25.54%), Qi and Yin Deficiency (22.97%), and others.
Latent class analysis revealed five patient subgroups, with Liver and Kidney Yin Deficiency being the most prevalent (36.24%).
Syndrome patterns were significantly associated with sociodemographic factors such as age and income.
Clinical parameters like hypertension and triglyceride levels correlated with specific TCM syndromes.
Patient-reported outcomes, including fatigue severity and sleep quality, were linked to deficiency syndromes.
Clinical Implications
The findings support the integration of TCM syndrome classifications into clinical practice for managing T2DM and MetS. Healthcare providers may consider these syndromic patterns when developing personalized treatment plans to address the unique needs of patients.
Conclusion
This study underscores the utility of data-driven methods in refining TCM syndrome classifications, paving the way for improved patient stratification and management strategies in T2DM and MetS.
