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. 2011 Jul 15;210(1-3):149-53.
doi: 10.1016/j.forsciint.2011.02.028. Epub 2011 Mar 25.

Postmortem measurement of caffeine in bone marrow: influence of sample location and correlation with blood concentration

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Postmortem measurement of caffeine in bone marrow: influence of sample location and correlation with blood concentration

N Cartiser et al. Forensic Sci Int. .

Abstract

Bone marrow (BM) analysis is of forensic interest in postmortem toxicological investigation in case of limited, unavailable or unusable blood samples. However, it remains difficult to determine whether a drug BM concentration is therapeutic or represents overdose, due to the lack of studies on this alternative matrix. Given the variations in BM composition in the body, sample location was suggested to be a relevant factor in assessing BM concentration. The aim of the present study was to compare postmortem caffeine concentrations in various BM sample locations and secondly to consider the correlation between BM and blood concentrations. Six BM samples (right and left side: proximal and medial femur and 5th rib) and a blood sample were collected from 21 forensic autopsies. Gas chromatography coupled to tandem mass spectrometry was performed. Blood caffeine concentrations ranged from 60 to 7591ng/mL. Femoral and rib BM concentrations ranged from 51 to 6171ng/g and 66 to 7280ng/g, respectively. Blood concentrations were always higher than BM concentrations. As a good correlation was demonstrated between blood and rib BM and between blood and the average of the four femoral BM concentrations, blood caffeine concentrations could be correctly extrapolated from BM concentrations. BM caffeine concentration was found to depend on sample location. Rib BM caffeine concentrations appeared to be systematically greater than averaged femur values and concentrations were much more variable between the 4 femur BM samples than between the 2 ribs. From a practical point of view, for caffeine analysis, rib BM appeared more relevant than femoral BM, which requires multisampling to overcome the concentration variability problem.

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