Regression Models for Postmortem Interval Estimation by using Accumulated Degree Hours and Potassium in Vitreous and Blood
Keywords:Ambient temperature; Accumulated degree hours; Postmortem interval; Potassium.
The biochemical changes of corpse are using forthe postmortem interval (PMI) estimation, but decomposition is
varied due to many factors. Ambient temperature is believed to be the most important factor which is related to
biochemical change in the human corpse by using accumulated degree hours (ADH). The aim of this research
was to develop exponential formula to estimate the PMI based on a potassium and ADH as the parameters. The
secondary data analysis is conducted on 3 articles published in Thailand. The correlation data were analyzed by
potassium, ADH, and time of death in each experiment. The temperature data was provided by the Thailand
Meteorology Department (TMD). These results suggested that this developed method can use for PMI estimation.
The additional step, namely to calculate the ADH from the finding date back until the predicted day of death from
case reported and TMD. The regression analysis had a high reliability. The potassium level significantly estimates
the PMI (R2 = 0.9183, 0.8296 and 0.7142 for pig vitreous, corpse vitreous and corpse blood, respectively). When
using the ADH in pig vitreous, the R2 increased to 0.9931. The developed potassium regression models are a
practical method to measure PMI. The PMI can be estimated using this method, but caution is advised in case with
a long PMI. It can be used to estimate the mortality time of the fresh-early decomposition stage, up to 48 hours.
Due to the longer mortality, there may be a gradual rate of change and samples cannot be collected.
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