Postmortem redistribution of cannabinoids: Statistical analysis of a novel dataset and meta-analysis

The assessment of human postmortem concentrations of Δ9-THC (THC) and its metabolites, 11-nor-9-carboxy-THC (THCCOOH) and 11-hydroxy-THC (11-OH-THC), is routinely performed in forensic toxicology laboratories. However, the literature on cannabinoids postmortem redistribution (PMR) is scarce and highlights their complex postmortem changes. This study aims to investigate the postmortem behavior of THC and its metabolites in order to provide practitioners with potential indicators of PMR. To do so, antemortem and postmortem cases positive for cannabinoids were compiled in a database. Its analysis shows significantly higher THC concentrations in postmortem blood than in antemortem blood. Antemortem and postmortem blood also present significantly different profiles for their THC to THCCOOH ratios. Whereas antemortem blood generally shows THCCOOH concentrations higher or equal to THC, several postmortem cases show the opposite, with THC concentrations higher than THCCOOH. While occurrence of postmortem redistribution (PMR) is difficult to measure directly, an evaluation was performed using the central to peripheral (C/P) blood concentrations ratio as a proxy. With a C/P significantly lower than 1.0 for THC and significantly higher than 1.0 for THCCOOH, the PMR hypothesis is supported for both compounds, with redistribution towards peripheral blood for THC and towards central blood for THCCOOH. On the other hand, 11-OH-THC does not show a C/P significantly different than 1.0, suggesting the absence of PMR. Influence of body mass index, conservation state and postmortem interval on C/P was statistically analyzed and no significant impact was observed. To compare and contrast C/P observed in the database with those published in the literature, a meta-analysis was performed using a median of median (MM) model. THC PMR towards peripheral blood is supported by a global estimate of 0.81 (CI95%: 0.51 to 1.2). Redistribution towards femoral blood appears to be stronger than towards iliac blood; indeed, the median estimate of C/P decreases to 0.64 (CI95%: 0.40 to 1.1) when studies with iliac blood were removed from the meta-analysis. THCCOOH PMR towards central blood is supported by a C/P median estimate of 1.3 (CI95%: 0.97 to 1.6). THC PMR can be suspected when these indicators are observed (i) high THC blood concentration (>50 ng/mL), (ii) THC C/P lower than 1.0 (iii) blood THC/THCCOOH concentration ratios greater than 1.0 and (iv) non-detectability of THCCOOH in urine. In postmortem samples, many factors may contribute to the overestimation of THC concentration, therefore a careful interpretation is required, relying on both central and peripheral blood samples.

Conventional and alternative matrices for driving under the influence of cannabis: recent progress and remaining challenges

In the past decade much research concerning the impact of cannabis use on road safety has been conducted. More specifically, studies on effects of cannabis smoking on driving performance, as well as epidemiological studies and cannabis-detection techniques have been published. As a result, several countries have adopted driving under the influence of drugs (DUID) legislations, with varying approaches worldwide. A wide variety of bodily fluids have been utilized to determine the presence of cannabis. Urine and blood are the most widely used matrices for DUID legislations. However, more and more publications focus on the usability of oral fluid testing for this purpose. Each matrix provides different information about time and extent of use and likelihood of impairment. This review will focus on the practical aspects of implying a DUID legislation. The pros and cons of the different biological matrices used for Δ9-tetrahydrocannabinol screening and quantification will be discussed. In addition, a literature overview concerning (roadside) cannabinoid detection, as well as laboratory confirmation techniques is given. Finally, we will discuss important issues influencing interpretation of these data, such as oral fluid collection, choice of cut-offs, stability and proficiency testing.