RESUMO
BACKGROUND: Estimating an accurate postmortem interval (PMI) is essential for death investigators to confirm the offence timing and suspects' alibis. Compared to traditional methods, the Nomogram-based method is claimed to estimate nearly accurate PMI, but most of such studies are based on the Western population. Adequate data for bodies exposed to tropical climate of India and the Indian subcontinent are not available. AIM: To assess the accuracy and goodness-of-fit of Nomogram based PMI estimation in bodies exposed to Indian climatic conditions after death. MATERIAL AND METHODS: This is a 3-year-long study on 200 bodies with known death times. The exact PMI was recorded from direct sources: family members, police and hospital records. Before autopsy, the ambient temperature, body weight, length, and rectal temperature were measured, and the details of clothing, sex, and age, were used on a nomogram to calculate the PMI (tN). One-way ANOVA correlation and Mann-Whitney U test were used to compare the variables. Linear regression analysis was used to establish the relationship between the rectal temperature (Tr) and nomogram estimated PMI (tN) and the known PMI(t). The consistency and agreement between the tN and t were measured using Intra-class correlation coefficient (ICC). Bland-Altman (BA) plot was used to compare the level of agreement between direct(t) and nomograms method PMIs. RESULTS: Nomogram-based PMI estimation showed a statistically significant strong relationship with rectal temperature (R 0.77, R2 0.74, adjusted R2 0.76, t-stat 25.83 p < 0.000) and exhibited a relatively consistent agreement with the known death interval (ICC 0.935). Regressing the tN over t showed that the nomogram method can predict PMI with 95 % accuracy. The BA plot between Direct and Nomogram methods exhibited a consistent agreement in PMI estimation though the limits of agreement (LoA) were wide: range 39.09-121.18 min. CONCLUSION: The accuracy and reliability of the Nomogram method in PMI estimation is high and recommended for the South Indian population. However, the presence of systematic differences between tN and t can't be ruled out due to wider LoA in BA plot. Hence, these findings highlight the need for further investigation and potential refinement of the PMI estimation methods to enhance accuracy and reduce discrepancies.