Regression Models for Postmortem Interval Estimation by using Accumulated Degree Hours and Potassium in Vitreous and Blood

Abstract

The biochemical changes of corpse are using forthe postmortem interval (PMI) estimation, but decomposition isvaried due to many factors. Ambient temperature is believed to be the most important factor which is related tobiochemical change in the human corpse by using accumulated degree hours (ADH). The aim of this researchwas to develop exponential formula to estimate the PMI based on a potassium and ADH as the parameters. Thesecondary data analysis is conducted on 3 articles published in Thailand. The correlation data were analyzed bypotassium, ADH, and time of death in each experiment. The temperature data was provided by the ThailandMeteorology 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 fromcase reported and TMD. The regression analysis had a high reliability. The potassium level significantly estimatesthe PMI (R2 = 0.9183, 0.8296 and 0.7142 for pig vitreous, corpse vitreous and corpse blood, respectively). Whenusing the ADH in pig vitreous, the R2 increased to 0.9931. The developed potassium regression models are apractical method to measure PMI. The PMI can be estimated using this method, but caution is advised in case witha 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.