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Updated: Jul 16, 2026
Biobanking of Human Aqueous and Vitreous Liquid Biopsies for Molecular Analyses
Published on: September 11, 2023
A Step Forward in Post-Mortem Interval Estimation: Multivariate Analysis of Ammonium, Albumin, and Potassium Levels
Martina Focardi1, Beatrice Defraia1, Ilenia Bianchi2
1Forensic Medical Sciences, Department of Health Sciences, University of Florence, Largo Brambilla 3, 50134 Florence, Italy.
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Background/Objectives: Accurate post-mortem interval (PMI) estimation remains challenging in forensic pathology. Although potassium (K+) is the most well-validated single biomarker in vitreous humor (VH), multivariate approaches may enhance precision by capturing the complex cascade of post-mortem biochemical changes. This study aimed to develop and validate a multivariate PMI estimation model incorporating three biochemical markers-potassium, ammonium (NH4+), and albumin (ALB)-in vitreous humor using automated clinical chemistry platforms for practical forensic application. Methods: Vitreous humor samples from 38 autopsy cases with documented PMIs (39.5-285 h; mean, 105.5 h) were analyzed for K+ (Cobas C8000), NH4+ (Cobas C8000), and ALB (Immage 800 nephelometry). Univariate and multivariate regression analyses were performed, with the residual standard error (RSE) as the primary measure of accuracy. Model validation was conducted by back-calculating PMI in four samples completely distinct from the training cohort. Results: All three analytes demonstrated strong individual correlations with PMI (R2: K+ = 0.88, ALB = 0.78, NH4+ = 0.69; all p < 0.001). The multivariate regression model [PMI = 40.25[Alb] + 0.01573[NH4+] + 5.339[K+] - 53.032] yielded an RMSE of ±15.5 h (MSE = 240.25 h2), outperforming potassium-only models (RMSE = ±22.6 h). Although NH4+ showed limited statistical significance in the multivariate model (p = 0.128), its inclusion improved overall predictive accuracy. External validation in an independent cohort of four subjects (distinct from the 38 subjects in the training set) demonstrated a mean absolute error (MAE) of 20.4 h. Conclusions: The multivariate approach combining K+, NH4+, and ALB in VH improves PMI estimation accuracy compared with single-marker methods. The use of automated clinical chemistry platforms enhances reproducibility and facilitates practical implementation in forensic laboratories.
