The association between the C-reactive protein-triglyceride glucose index and myocardial injury after acute ischemic stroke: a machine learning analysis of the brain-heart axis - Summary - MDSpire
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The association between the C-reactive protein-triglyceride glucose index and myocardial injury after acute ischemic stroke: a machine learning analysis of the brain-heart axis
To investigate the association between the C-reactive protein-triglyceride glucose index (CTI) and myocardial injury following acute ischemic stroke (AIS) using machine learning, highlighting its potential clinical significance.
Key Findings:
34.2% of patients experienced myocardial injury.
CTI was significantly higher in the myocardial injury group (P < 0.01).
CTI was identified as the top predictor of myocardial injury by ML models.
CTI showed an independent association with myocardial injury (OR = 2.61, 95% CI: 1.99–3.42).
CTI demonstrated moderate discriminative ability (AUC = 0.713) compared to TyG index (AUC = 0.596) and Hs-CRP (AUC = 0.689).
Interpretation:
The CTI integrates inflammatory and insulin resistance markers, suggesting its potential as a risk stratification tool for myocardial injury post-AIS, which could enhance clinical decision-making.
Limitations:
Retrospective design may introduce selection bias.
Single-center study limits generalizability.
Potential confounding factors not fully accounted for.
The retrospective nature may affect the reliability of the findings.
Conclusion:
CTI is significantly associated with myocardial injury after AIS and may serve as a useful indicator for risk assessment.
Over two days, specialists across neurology, neurosurgery and related subspecialties came together to discuss advances in stroke care, epilepsy, movement disorders, neurodegenerative disease, neuro-oncology, brain and spine surgery, interventional pain management and emerging technologies.
