Identification of key metabolic indicators associated with the comorbidity of ischemic stroke and diabetes mellitus using an optimal interpretable clinlabomics model - Scorecard - MDSpire
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Identification of key metabolic indicators associated with the comorbidity of ischemic stroke and diabetes mellitus using an optimal interpretable clinlabomics model
Clinical Scorecard: Discovery of significant metabolic markers linked to the coexistence of ischemic stroke and diabetes mellitus through an optimal interpretable clinlabomics approach
At a Glance
Category
Detail
Condition
Ischemic Stroke with Diabetes Mellitus Comorbidity
Key Mechanisms
Metabolic dysregulation linked to systemic inflammation and endothelial dysfunction
Target Population
Patients with ischemic stroke and diabetes mellitus
Care Setting
Clinical laboratory evaluation and machine learning analysis
Key Highlights
12 metabolic indicators significantly associated with IS-DM comorbidity identified.
TyG index and AIP showed the highest odds ratios for increased risk.
The rpart algorithm model achieved an AUC of 0.910 in training set.
Nine candidate metabolic biomarkers for IS-DM comorbidity were identified.
SHAP analysis highlighted HbA1c/HDL-C as the most important feature.
Guideline-Based Recommendations
Diagnosis
Utilize metabolic indicators for risk stratification in IS-DM patients.
Management
Implement individualized interventions based on identified biomarkers.
Monitoring & Follow-up
Regularly assess metabolic parameters to evaluate comorbidity status.
Risks
Higher stroke-related mortality and recurrent stroke risk in IS-DM patients.
Patient & Prescribing Data
Patients with ischemic stroke and diabetes mellitus comorbidity.
Focus on metabolic management to improve outcomes.
Clinical Best Practices
Incorporate machine learning models for predicting outcomes in IS-DM patients.
Standardize laboratory evaluations for metabolic indicators.
