A Step Forward in Post-Mortem Interval Estimation: Multivariate Analysis of Ammonium, Albumin, and Potassium Levels in Vitreous Humor
Year: 2026
Type: article
Abstract: 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.
Source: Diagnostics
Language: English
Subfield: Insect Science
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,137
Funder: Regione Toscana
OpenAlex ID: W7165780499
FWCI:
Cites:
Cited by:
Related to:
