Interpolation function estimates post mortem interval under ambient temperature correlating with blood ATP level

Objective: We developed a mathematical model using interpolation function, to characterize the correlation between blood ATP levels in the right ventricle of rabbit and post mortem interval (PMI) at different ambient temperatures.

Methods: Forty-eight healthy rabbits were randomly divided into 6 groups of 8 each. The sacrificed rabbits were maintained in calorstats at 10°C, 15°C, 20°C, 25°C, 30°C and 35°C, respectively. Blood from the right ventricle was sampled every 4h until 72h after death. At different time points, ATP concentrations in the blood samples were measured using an ATP fluorescence rapid detector, and then displayed on the detector screen in the form of relative light units (RLU). Relationship between PMI and ATP degradation levels was investigated statistically by SPSS 17.0 and MATLAB 10.0 software.

Results: We obtained six regression equations (Ra(2)=0.887-0.929) with RLU values at PMIs of 72h (10°C), 60h (15°C), 56h (20°C), 52h (25°C), 40h (30°C) and 32h (35°C), and an interpolation function (Ra(2)=0.930) was established with PMI as the dependent variable (z), RLU value as independent variable (x) and temperature as independent variable (y).

Conclusion: Interpolation function is an appropriate choice for PMI estimation by weakening influence of ambient temperature.