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Table 1.

Full Biomarker panel.

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Table 1 Expand

Fig 1.

Workflow for biomarker-based clustering and recursive feature addition to characterise cardiovascular phenotypes in HIV.

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Table 2.

Sequential addition of biomarkers (25–55) used in Model 1 to the initial 24-marker model, ordered by functional relevance to biological pathways identified in initial clustering.

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Table 2 Expand

Table 3.

Baseline demographics of combined cohorts.

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Table 3 Expand

Table 4.

Comparison of Baseline and RFA Models: Key Biomarkers and CVP associations and regression outcomes by Cluster.

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Table 4 Expand

Fig 2.

Heatmap showing biomarker contribution to cluster formation in the initial model.

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Fig 2 Expand

Fig 3.

Baseline 24-biomarker model: associations with CVP.

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Fig 3 Expand

Table 5.

Biomarker selection criteria scores model 1.

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Table 5 Expand

Fig 4.

Heatmap showing biomarker contribution to cluster formation in RFA model 1.

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Table 6.

Median ASCVD 10-year risk and fold-change associations with CVP across models and clusters.

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Fig 5.

Unadjusted and adjusted odd ratios (95% CI) for CVP in all three RFA models, using cluster 1 as the reference group.

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Fig 5 Expand

Table 7.

Biomarker selection criteria scores model 2.

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Table 7 Expand

Fig 6.

Heatmap showing biomarker contribution to cluster formation in model 2.

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Fig 6 Expand

Table 8.

Model 3 (Greedy forward - backward) biomarker selection path and resampling stability.

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Table 8 Expand

Fig 7.

Correlation Heatmap showing biomarker contribution to cluster formation in model 3.

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Fig 8.

Overlap of Biomarkers Across the Three Predictive Models.

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Table 9.

Comparison of biomarker selection robustness, cluster stability, and bootstrap regression results across models.

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Table 9 Expand

Table 10.

Distribution of study cohorts across clusters for each clustering model.

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Table 10 Expand