# Integrative Vitamin D-Inflammatory-Coagulation Biomarker Index Predicts COVID-19 Severity: Development and Validation of the Vitamin D Inflammatory Burden Score (VDIBS)

## TL;DR

A new score combining vitamin D levels, inflammation, and coagulation biomarkers helps predict severe outcomes in hospitalized COVID-19 patients.

## Contribution

A novel integrative biomarker index (VDIBS-Core) that combines vitamin D status with inflammation and coagulation markers to predict disease severity in hospitalized COVID-19 patients.

## Key findings

- VDIBS-Core predicted severe disease with an AUC of 0.78 and showed strong risk stratification across low, moderate, and high-risk groups.
- The vitamin D component added significant predictive value beyond inflammation and coagulation biomarkers alone (LR test p = 0.004).
- VDIBS-Core is a simple, rapid bedside tool that offers equivalent performance to complex multivariate models.

## Abstract

Vitamin D deficiency is common in hospitalized COVID-19 patients and is associated with increased severity. However, single-biomarker approaches provide insufficient prognostic precision. We developed an integrative inflammatory-metabolic risk index combining vitamin D status, systemic inflammation, and coagulation activation. This is a prospective cohort study of 512 hospitalized COVID-19 patients (September 2022–December 2023) with serum 25(OH)D3 measurement at admission. The primary analysis (N = 301) included patients with complete data for VDIBS-Core components (CRP, ferritin, D-dimer, LDH). The Vitamin D Inflammatory Burden Score-Core (VDIBS-Core; range 0–7) integrated the following: (1) vitamin D tier (deficient < 30 nmol/L: 3 points; insufficient 30–50: 2; non-optimal 50–75: 1; sufficient > 75: 0), (2) inflammation score (CRP ≥ 100, ferritin ≥ 1000 each +1 point; 0–2 total), and (3) coagulation score (D-dimer ≥ 1000, LDH ≥ 3–6 or ≥ 6 each +0–2 points; 0–2 total). The IL-6 measurement (N = 48, 9.4%) was explored separately as VDIBS-Plus in the secondary analysis. The outcomes were severe COVID-19 (defined as the worst severity classification during hospitalization per WHO criteria), ICU admission, and mortality. The mean vitamin D was 63.4 ± 33.2 nmol/L (68.1% deficient). Among N = 301 with complete VDIBS-Core data, severe disease occurred in 221 (73.4%), ICU admission in 15 (5.0%), and mortality in 8 (2.7%). VDIBS-Core risk stratification showed the following: low-risk (VDIBS 0–2, n = 178) 8.4% severe; moderate-risk (VDIBS 3–5, n = 245) 45.7% severe; and high-risk (VDIBS 6–7, n = 89) 78.6% severe; χ2 = 142.3, p < 0.001. VDIBS-Core predicted severe disease with AUC 0.78 (95% CI 0.74–0.82), with excellent calibration (Hosmer–Lemeshow p = 0.40). When compared to complex multivariate models incorporating all seven individual biomarkers, VDIBS-Core demonstrated equivalent discrimination (AUC 0.82, Δ = 0.04, p = 0.08, not statistically significant) with superior clinical simplicity. Bootstrap internal validation confirmed modest optimism (optimism-corrected AUC 0.76). An incremental value analysis demonstrated that the vitamin D component contributes a significant additional predictive value compared to inflammation/coagulation biomarkers alone (LR test p = 0.004). VDIBS-Core provides bedside-implementable risk stratification using three simple components measurable in <5 min, integrating vitamin D-dependent immune regulation with systemic inflammation and coagulation activation. This composite approach offers a practical tool for treatment intensity escalation and monitoring frequency assignment in hospitalized COVID-19 patients. External validation in geographically diverse cohorts is required before widespread clinical implementation.