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Dynamic Risk Estimation of Adverse Events in Ambulatory LVAD Patients: A MOMENTUM 3 Analysis
Palak Shah1, Gabriel Sayer2, Shashank S Sinha1
1Inova Schar Heart and Vascular, Falls Church, Virginia, USA.
A new dynamic risk model accurately predicts 30-day risks of gastrointestinal bleeding, stroke, or death in patients with a left ventricular assist device (LVAD). This tool aids clinical decisions by stratifying patient risk as new data emerges.
Area of Science:
- Cardiovascular Medicine and Surgery
- Biomedical Engineering
- Clinical Risk Prediction
Background:
- Adverse events related to hemocompatibility are common after left ventricular assist device (LVAD) implantation.
- Predicting these adverse events in LVAD patients remains a significant clinical challenge.
Purpose of the Study:
- To develop and validate a dynamic risk modeling approach using a multistate model.
- To predict the risk of gastrointestinal bleeding (GIB), stroke, or death in ambulatory LVAD patients.
Main Methods:
- Secondary analysis of the MOMENTUM 3 trial involving HeartMate 3 LVAD recipients followed for up to 2 years post-hospital discharge.
- A multistate model incorporating 145 initial variables was developed using multivariate logistic regression.
- Model performance was evaluated using the area under the curve (AUC) in a validation cohort, and a risk stratification tool was created.
Main Results:
- The final multistate model included 39 variables to predict GIB (16 variables), stroke (10 variables), and death (19 variables).
- At 2 years post-implantation, the incidence rates were 25.6% for GIB, 6.0% for stroke, and 12.3% for death.
- The model demonstrated strong predictive performance with AUCs of 0.70 for GIB, 0.69 for stroke, and 0.86 for death in predicting 30-day event risks.
Conclusions:
- The developed multistate model effectively informs 30-day risk assessment in ambulatory LVAD recipients.
- The model allows for dynamic risk recalculation as new patient-specific data become available.
- This tool facilitates accurate risk stratification, potentially guiding clinical decision-making for adverse event prevention.
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