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An organized coronary thrombus and cannabis-positive toxicology in the same autopsy do not, by themselves, establish that cannabis caused the thrombosis. A 2025 case report documented both findings in a 34-year-old man, while expressly concluding that a definitive causal relationship could not be established from the available postmortem evidence.

What the autopsy actually demonstrated

Aravind and colleagues described a man found unresponsive at home. The case presentation reported obesity and occasional marijuana and alcohol use. A complete autopsy found a 500 g heart with left-ventricular dilation and, microscopically, complete focal occlusion of the proximal left anterior descending coronary artery by an organized thrombus.

Trichrome staining showed fibroblastic growth within the thrombus. Elastic staining showed focal disruption of the internal elastic lamina. The authors interpreted the organization as supporting development during life, rather than a clot that appeared only after death.

That is evidence about the thrombus’s development, not specific evidence that THC initiated it. The remaining coronary arteries showed no atherosclerosis, thrombus or inflammatory infiltrates. No histological evidence of acute myocardial infarction was identified, although focal cardiac scarring was described.

What toxicology reported, and what it did not separate

Blood and vitreous were collected and analyzed by LC–MS. Table 1 reports 11-hydroxy-delta-9-THC at 3.3 ng/mL and delta-9-THC at 28 ng/mL. It also contains a combined label for delta-9-carboxy-THC and delta-9-THC with a value of 50 mg/mL, while its reference column uses ng/mL.

The abstract likewise prints 50 mg/mL. That figure and analyte label conflict with the table’s separate THC entry and surrounding unit convention. The publication does not provide enough clarification to silently change mg/mL to ng/mL or assign the 50 value to one specific analyte. Such a change would be a substantive correction, not ordinary formatting.

The table does not identify separate concentrations for blood and vitreous. It therefore cannot establish that each reported concentration was independently measured in both matrices, or supply a paired vitreous/blood ratio. The report also does not give an anatomical blood collection site, postmortem interval, detailed preservation history, calibration range, detection and quantitation limits or numerical assay precision.

Why two collected matrices do not resolve every uncertainty

The authors considered collection of blood and vitreous supportive of reliability. However, collecting two specimen types is not the same as publishing two matrix-specific, validated quantitative results. Without the missing details, the reader cannot determine how their values compared or which analytical uncertainties were assessed.

The table’s reference values likewise should not be treated as established thresholds for coronary thrombosis, impairment or death. This single case did not validate a diagnostic concentration for any of those outcomes.

Proposed mechanisms were not observed mechanisms

The discussion considered arteritis, vasospasm and platelet aggregation as possible pathways linking cannabis with cardiovascular injury. The authors explicitly distinguished those literature-based hypotheses from mechanisms demonstrated in this person. Vasospasm and cannabinoid-induced platelet activation were not directly measured.

Obesity, cardiomegaly and cardiac scarring also complicate attributing the outcome to one exposure. The report’s title uses causal language, but its discussion and conclusion retain uncertainty. An interpretation should preserve that qualification rather than citing the title as if causation had been experimentally established.

What conclusion can travel to another investigation?

The case illustrates the value of detailed histology when gross coronary examination lacks obvious atherosclerosis. It also illustrates why a measured exposure and a plausible biological mechanism are not sufficient to determine an individual’s causal pathway.

It cannot estimate the population risk of cannabis-related thrombosis, reconstruct dose or timing, establish behavioral impairment or distinguish how much a concentration changed after death. Those questions require evidence the case did not supply. The useful statement keeps the documented pathology, the cannabis findings, unresolved reporting details and the authors’ causal limitation together.

For another concentration-to-effect distinction, see THC in postmortem brain and impairment interpretation. Analytical uncertainty also differs from a negative result, as discussed in unquantifiable postmortem THC findings.

Primary source

Aravind A, Kyle PB, Subramony C. A Fatal Case of Coronary Thrombosis in a Young Male Triggered by Marijuana Use. Cureus. 2025;17(11):e98083. doi:10.7759/cureus.98083.

A clonazepam metabolite-to-parent ratio measured in muscle should not be read as though it came from blood. In a 109-case autopsy study, median 7-aminoclonazepam/clonazepam ratios were 31 in peripheral blood, nine in psoas muscle and four in lateral vastus muscle. The matrix itself materially changed the observed relationship.

What did those denominators represent?

Øiestad and colleagues included 109 benzodiazepine- or z-hypnotic-positive cases from a larger 183-case specimen project. Not every case contained clonazepam, and not every parent finding had a paired quantifiable metabolite finding.

The metabolite/parent ratio summaries used 54 paired peripheral-blood results, 37 psoas-muscle pairs and 43 lateral-vastus pairs. These are compound- and matrix-specific subsets. The study’s total of 109 must not be presented as the denominator for every ratio.

The muscle and blood measurements had different units

Peripheral-blood clonazepam had a median concentration of 0.0060 mg/L, while the psoas and lateral-vastus medians were 0.016 and 0.028 mg/kg. For 7-aminoclonazepam, the corresponding medians were 0.15 mg/L in blood and 0.13 mg/kg in each muscle.

Those concentration medians describe the reported positive findings, whose counts differed. Dividing group medians does not reproduce the median of the individual parent/metabolite pairs. Within one matrix, the metabolite/parent ratio uses matching units and is dimensionless; a muscle-to-blood comparison instead combines mg/kg with mg/L and must retain that distinction.

Table III reported median parent clonazepam muscle/blood concentration ratios of 2.1 for psoas and 4.6 for lateral vastus, compared with 0.80 and 0.78 for the metabolite. Thus, the parent was relatively enriched in muscle compared with its metabolite. A general statement that both compounds distribute identically would miss the observed pattern.

Collection and preparation shaped the comparison

Samples were collected during autopsies from June 2013 through November 2016, generally within a week of death. Peripheral blood was femoral blood expressed after iliac-vein transection and cessation of initial flow, using thigh and groin compression. It was not an unspecified cardiac specimen.

After laboratory arrival, samples were refrigerated at 4°C, typically for one to two weeks. Muscle homogenates used approximately 3.5 g tissue with 14 mL water. Results were corrected for dilution only after the homogenate result exceeded the method’s quantitation limit. That preparation could reduce detection of low muscle concentrations.

Most cases had no or slight putrefaction; four had moderate putrefaction. The investigators did not validate the same relationships in severe decomposition, burns or severely injured bodies lacking peripheral blood.

Why the ratio was not a validated ingestion clock

The authors considered both metabolism during life and possible postcollection conversion of nitrobenzodiazepines to 7-amino metabolites as explanations for higher metabolite concentrations. They lacked antemortem concentrations and could not determine which matrix best reflected the concentration at death.

The data therefore do not establish a time-since-ingestion equation. A lower muscle ratio does not independently prove more recent use than a higher blood ratio, nor does a high metabolite ratio establish that every change occurred during life. Postmortem and analytical processes remain possible influences.

What supported the reported measurements?

Screening and confirmation used distinct UHPLC–MS/MS procedures. Confirmation quantitation limits were 0.00079 mg/L for clonazepam and 0.0057 mg/L for 7-aminoclonazepam. Results below the relevant limits were omitted from evaluation. Alternative matrices used whole-blood calibration, with separate checks of recovery and matrix effects; matrix-specific calibration would have been preferred.

These limits and preparation steps belong with the results. They are not thresholds for impairment or cause of death. Interpretation should preserve the parent and metabolite identities, exact muscle, units, pair count and specimen history. For a different attribution issue, see whether clonazepam-related findings establish clonazafone exposure.

Primary source

Øiestad EL, Øiestad ÅML, Middelkoop G, Brochmann GW, Thaulow CH, Vindenes V. Comparative Study of Postmortem Concentrations of Benzodiazepines and Z-Hypnotics in Several Different Matrices. Journal of Analytical Toxicology. 2023;47:287–298. doi:10.1093/jat/bkac106.

Zopiclone behaved differently from most benzodiazepines in a six-matrix autopsy study: its vitreous-to-peripheral-blood ratio had a median close to one. That result supports vitreous as a potentially useful specimen for this drug. It does not make vitreous and blood interchangeable in an individual death investigation; the 16 paired ratios ranged from 0.13 to 3.7.

The study selected cases through blood findings

Øiestad and colleagues collected specimens during medicolegal autopsies from June 2013 to November 2016. Of 183 project cases, 109 had one or more benzodiazepines or z-hypnotics detected and were included. The 109 were not all zopiclone cases: 16 had zopiclone findings in peripheral blood and vitreous.

Routine peripheral-blood screening triggered analysis of the project matrices. This design did not establish the frequency with which vitreous would detect zopiclone when blood screening was negative. It also did not measure population prevalence or diagnostic sensitivity across every autopsy.

How were the specimens collected and handled?

Autopsy generally occurred within one week after death. Peripheral blood was obtained by transecting the iliac vein, allowing the initial flow to stop, and collecting femoral blood expressed by thigh and groin compression. Collection from both sides was often needed to obtain 40–50 mL. The procedure was designed to avoid collecting blood from the superior vessels.

Cardiac blood, pericardial fluid, psoas and lateral vastus muscle, and vitreous were also collected. After laboratory receipt, specimens were refrigerated at 4°C, typically for one to two weeks while routine screening was completed. Matrices from the same case were analyzed together as far as possible.

Most included bodies had no or slight putrefaction: 77 and 24 cases, respectively. Four had moderate putrefaction and four lacked that information. The study did not establish equivalent performance in severe decomposition.

What did the 16 zopiclone pairs show?

Peripheral-blood zopiclone had a median of 0.097 mg/L and range of 0.0038–8.1 mg/L. Vitreous had a median of 0.16 mg/L and range of 0.011–1.73 mg/L. The median of individual vitreous/blood ratios was 0.97, with a range of 0.13–3.7.

The ratio of the two group medians is a different calculation from the median of individual paired ratios. Consequently, 0.16 divided by 0.097 should not be substituted for the reported 0.97 paired-ratio median.

The vitreous–blood Spearman correlation was 0.90 and significant at the 0.01 level. Correlation indicates ordering across the available observations, not equality or a narrow prediction interval for a new case.

Why the finding should not be generalized to every sedative

For diazepam, the study reported a median vitreous/blood ratio of 0.084 in 14 pairs; for alprazolam it was 0.35 in 15 pairs. The authors considered zopiclone’s lower protein binding a relevant explanation for its different pattern. This was an interpretation of the observed drug-specific distributions, rather than proof that protein binding alone determined every ratio.

The authors also considered greater zopiclone stability in alternative matrices a possible explanation for some higher concentrations. The casework comparison was not a controlled stability time course and could not quantify how much storage changed each result.

Screening, confirmation and reporting limits

Routine screening used UHPLC–MS/MS, followed by separate confirmatory methods. The confirmation-method quantitation limit for zopiclone was 0.00029 mg/L. Values below quantitation limits were excluded from evaluation. The findings therefore concern reported quantifiable results, not every possible low-level detection.

All matrices used whole-blood calibration, a limitation acknowledged by the authors. They separately evaluated recovery, matrix effects, accuracy and precision in the alternative matrices. Limited vitreous volume also prevented some analyses for other drugs. This was not a guarantee that every available vitreous specimen would support every assay.

No antemortem concentrations were available to identify which postmortem matrix best represented the concentration during life. A positive zopiclone result did not establish impairment or causal contribution. For the broader specimen question, see vitreous versus blood for postmortem drug screening.

Primary source

Øiestad EL, Øiestad ÅML, Middelkoop G, Brochmann GW, Thaulow CH, Vindenes V. Comparative Study of Postmortem Concentrations of Benzodiazepines and Z-Hypnotics in Several Different Matrices. Journal of Analytical Toxicology. 2023;47:287–298. doi:10.1093/jat/bkac106.

A satisfactory internal-standard signal does not guarantee accurate drug quantification in lipid-rich postmortem blood. A 2023 experiment found substantial losses of certain benzodiazepine metabolites and sedative drugs even when internal-standard responses were comparatively preserved. The investigators found evidence pointing primarily to extraction-related losses rather than ion suppression in the compounds specifically examined.

Why postmortem lipemia deserved investigation

Elenstål and colleagues reviewed approximately 28,000 autopsy cases analyzed in Sweden during 2017–2021; 1,070 were classified visually as hyperlipidemic. Severe putrefaction was recorded in 32% of the lipemic cases versus 5% overall. No putrefaction was recorded in 9% versus 61%, respectively.

This association did not prove that decomposition caused every lipid-rich specimen or that the person had high blood lipids during life. The classification depended on visible layering, turbidity or a milky appearance. The experimental work addressed the effect of that matrix on testing, not diagnosis of a living lipid disorder.

What was experimentally added?

The investigators spiked citrated bovine whole blood with 19 benzodiazepine-related, sedative and antianxiety analytes at 35, 84 or 140 ng/g, depending on the compound’s calibration range. In duplicate preparations, they added Intralipid at 0, 2.4, 5.6, 12, 24 and 64 mg/g.

A second additive pooled upper lipid layers from seven postmortem cases with negative toxicological screening. Those pooled lipids were added at 0, 8 and 52 mg/g, also in duplicate. These were matrix experiments, not measurements of drug concentrations in 19 independent human fatalities. The report did not assign a uniform collection site or postmortem interval to the seven source cases.

Samples equilibrated for five to ten minutes, then remained at 8°C for at least 24 hours before analysis. Internal standards were added during analytical preparation, after storage, followed by ethyl-acetate extraction and UHPLC–mass spectrometry.

Analyte and internal standard did not always behave alike

At 5.6 mg/g Intralipid, a level the investigators could not identify visually as hyperlipidemic, recoveries were below 50% for 7-aminonitrazepam, 7-aminoclonazepam, 7-aminoflunitrazepam, propiomazine and dihydropropiomazine. By contrast, internal-standard responses were 79–101% of the reference responses at that lipid level.

Several parent benzodiazepines retained responses above 75%, while zopiclone, zolpidem and hydroxyzine fell between 50% and 75%. Lipemia did not produce one uniform loss across all related drugs. For most analytes, standards compensated more successfully; the important limitation concerned the compounds and conditions for which they did not.

The study calculated its recovery measure by comparing absolute peak area in lipid-containing samples with a concurrent reference without added lipid. These relative responses are not a direct measurement of biological drug elimination or postmortem redistribution within the body.

Why ion suppression was not the whole explanation

Post-column infusion experiments examined alprazolam, 7-aminoclonazepam and propiomazine. No apparent ion suppression was observed for those three compounds under the tested conditions, despite major losses for two of them in the preparation experiment.

The authors proposed pre-ionization effects, including partitioning into lipid particles, incomplete homogenization or insufficient equilibration of the standards. Those are plausible explanations, not experimentally established mechanisms for every analyte. The result should not be generalized to mean that ion suppression never occurs in postmortem blood.

A surrogate revealed the problem without exactly reproducing authentic lipids

Both additives produced the same broad pattern, but Intralipid generally caused larger losses. The discussion gives approximate propiomazine recoveries of 2% with Intralipid versus 20% with pooled postmortem lipids. Intralipid was useful as a controlled challenge matrix, while not being numerically interchangeable with every authentic sample.

These findings support analyte-specific investigation of lipemia and internal-standard performance. They do not justify multiplying a case result by a universal correction, declaring every low result erroneous or inferring impairment or cause of death from the matrix appearance. For a related validation issue, see why authentic specimens can reveal assay interference.

Primary source

Elenstål E, Green H, Kronstrand R, Elmsjö A. Intralipid as a matrix additive for evaluating hyperlipidemic postmortem blood. Journal of Analytical Toxicology. 2023;47:529–534. doi:10.1093/jat/bkad025.

Storage at 0°C did not stop every postmortem MDMA concentration change in a rat experiment. Some concentration peaks occurred later under that condition than at 20°C. Because humidity also differed, the comparison tested two storage environments rather than isolating temperature alone. It cannot supply a correction factor for a human autopsy result.

The animals and exposure model

Liang and colleagues randomly assigned 720 male Sprague–Dawley rats, weighing approximately 200 ± 10 g, to four groups of 180. Two groups received 20% ethanol–water as their only drinking liquid for four weeks; the others received water. One ethanol-exposed group and one water group then received intragastric MDMA at 150 mg/kg. The other groups received saline.

The rats were killed by neck concussion 30 minutes after dosing. Thus, the experiment did not establish that MDMA alone, or an MDMA–ethanol interaction, caused their deaths. Despite the paper’s discussion of acute combined use, its alcohol history included four weeks of exposure; it was not simply a single simultaneous drink-and-MDMA challenge.

Body storage and specimen storage were different steps

Each exposure group was divided between 20°C with 70% humidity and 0°C with 50% humidity, with 90 rats per environment. The paper calls the latter “freeze” storage, but the specified temperature was 0°C. It should not be relabeled as a −20°C laboratory-freezer experiment.

At 15 postmortem times from zero through ten days, six rats per exposure group and storage condition supplied specimens. Collected matrices included heart blood, vitreous, urine, brain, heart, lung, liver, spleen, kidney, testicles and biceps femoris muscle. After collection, samples were kept at −70°C until analysis. That later specimen-storage temperature was not the temperature at which the bodies decomposed.

The time course therefore compared animals sampled at different times. It was not repeated blood collection from the same living or deceased rat.

Later peaks show that change continued

Table 5 places the heart-blood MDMA peak at day three under 20°C storage and day four under 0°C storage, both with and without the ethanol-exposure history. In the combined-exposure group, the vitreous peak shifted from day four to day six, and the urine peak from 24 hours to day two.

The changes were specimen-dependent. For example, the combined group’s lung and femoral-muscle peaks did not show the same delay. The authors described an overall pattern of increasing concentrations followed by decreases, with some late results becoming undetectable. They reported significant variation in concentrations over the ten-day period by MANOVA, p < 0.01; that does not make every separate numerical contrast statistically significant.

Why the result is not a pure temperature effect

The colder bodies also had lower environmental humidity. Without comparing temperature while holding humidity constant, the design cannot allocate every observed difference to cooling alone. Tissue water changes, diffusion, degradation and the short dose-to-death interval further complicate interpretation.

Peak concentrations also do not all describe the same moment. Comparing two groups’ maxima can compare different postmortem days. Nor is an area under a postmortem concentration–time curve a measurement of antemortem impairment or absorbed human dose.

The analytical procedure had a defined scope

MDMA quantification used extraction, derivatization and gas chromatography with electron-capture detection, rather than mass-spectrometric confirmation. For heart blood, the reported calibration range was 0.5–100 µg/mL and detection limit 8 ng/mL. Tissue calibration was generally 0.5–50 µg/g. Blood validation in Table 4 reported intra-day imprecision of 1.9–3.4% and inter-day imprecision of 2.3–5.1% at the tested levels.

The report also contains conflicting summaries of the ethanol measurements: the Results state no significant difference between the two alcohol-exposed groups, while the Conclusion describes a significant difference. That discrepancy should not be turned into a demonstrated alcohol effect.

For forensic use, retain the species, high experimental dose, exposure history, anatomical matrix, both storage variables and sampling time. Cold storage reduced or delayed some changes under this protocol; it did not establish preservation of an individual’s concentration during life. See also why a postmortem tissue ratio is not an exact blood reconstruction.

Primary source

Liang M, Zhang J, Zheng N, Liu L. How Postmortem Redistribution of MDMA in Acute Alcohol-MDMA Combined-Use Rats Change under Effects of Alcohol. Scientific Reports. 2017;7:4038. doi:10.1038/s41598-017-04416-y.

A study containing 166 autopsies did not provide 166 paired observations for every ethanol comparison. Issa and Khattab’s 2024 report used 125 cases for comparisons involving vitreous and 127 for the blood–urine correlation. Keeping those denominators attached to the findings is essential when evaluating specimen coverage and claims about alternative matrices.

Which comparisons were actually available?

The overall series contained 649 alcohol-positive cases: 166 deceased and 483 living people. For postmortem blood versus vitreous, Table 4 reports 125 cases, Pearson r = 0.831 and p = 0.001. For postmortem urine versus vitreous, it reports 125 cases, r = 0.973 and p = 0.0001. The blood–urine comparison used 127 cases, r = 0.819 and p = 0.001.

The living blood–urine comparison used 483 cases, with r = 0.489 and p = 0.01. These are four distinct comparisons. Neither 649 nor 166 should be substituted as the denominator for all the reported correlations.

The paper does not fully explain the missing-specimen pattern or demonstrate that people with available paired samples were representative of those without them. Consequently, the results should not be presented as complete three-matrix measurements from every autopsy or as proof that missing specimens were random.

Who and what did the autopsy findings cover?

The records spanned 2017–2020. The study included positive alcohol cases and generally collected autopsy specimens within 24 hours of death. It excluded putrefied bodies, collection beyond 24 hours, environmental contamination, harsh environmental conditions and open wounds that could hasten bacterial invasion.

Postmortem blood was femoral venous blood. Bladder urine was extracted suprapubically, and approximately 2 mL clear vitreous was sufficient for testing under the described procedure. Blood was collected with 1% sodium fluoride, vitreous into dry tubes and urine into sterile containers. The stated storage conditions were 2–8°C, with prompt vitreous analysis or refrigeration if delayed until the next day.

These conditions constrain generalization. A correlation in relatively early, selected autopsies does not validate substitution in advanced decomposition or establish performance in specimens contaminated by trauma.

A strong correlation is not an individual prediction interval

The particularly high urine–vitreous correlation indicates that concentrations tended to vary together in the available paired cases. It does not mean the measurements were equal. Pearson r does not, by itself, specify a slope, intercept, systematic difference or uncertainty for predicting one new person’s blood concentration.

Statistical significance also does not establish which matrix best reflects the concentration during life. No independent antemortem reference concentration was supplied for each of these autopsy comparisons. The correlation cannot identify what proportion of a positive finding arose from drinking or from a postmortem process.

The living and deceased blood–urine correlations differed numerically. That does not make the stronger postmortem correlation a validated conversion rule. Different selection criteria, histories and collection circumstances remain relevant.

Analytical scope and reporting limits

Ethanol was measured by headspace GC–FID, with a reported calibration span of 10–400 mg/dL and a reporting cutoff of 10 mg/dL. Values above 400 mg/dL were diluted and reanalyzed, with the dilution factor applied. Other drug screening and confirmatory procedures described in the paper should not be confused with this ethanol assay.

The methods call the calibration six-point but elsewhere list eight concentrations. They also define detection and quantitation limits without giving clear numerical values for both in each matrix. Those limits cannot simply be inferred from the reporting cutoff. The main case counts total 649, whereas the discussion once states 549; the specimen-specific counts in Table 4 are the relevant reported counts for its correlations.

How should a reviewer use the study?

Keep the total case count, available pair count, exact matrices, collection interval and statistical measure together. Ask whether a proposed clinical or forensic inference was actually tested, and whether missingness could affect the comparison. Detection, correlation, quantitative prediction and attribution of impairment are separate claims.

For another alternative-matrix question, see urine-to-blood ethanol interpretation in 378 autopsies. For individual uncertainty, see vitreous ethanol prediction intervals.

Primary source

Issa SY, Khattab A. Ethanol concentrations in various biological specimens: Living and postmortem forensic toxicology analysis and comprehensive literature review. Journal of Forensic and Legal Medicine. 2024;106:102737. doi:10.1016/j.jflm.2024.102737.

Higher mean ethanol concentrations in an autopsy group do not, by themselves, demonstrate that ethanol increased after death. A 2024 study compared 166 deceased people with 483 living cases. These were different groups, rather than paired measurements collected before and after death from the same people.

What population did the study describe?

Issa and Khattab included 649 alcohol-positive cases: 483 living cases and 166 autopsies. Records covered 2017–2020. Living cases included people seeking emergency care and people referred following legal or traffic-related events. Inclusion required positive alcohol findings, so this was not a prevalence survey of all hospital patients or all deaths.

Autopsy generally occurred within 24 hours of death. The methods excluded putrefied bodies, environmental contamination, open wounds that might hasten bacterial invasion, delayed collection beyond 24 hours and harsh environmental exposure. These restrictions matter: the dataset was not designed to measure ethanol production in advanced decomposition.

The measurements had different collection contexts

Living blood and urine were collected on hospital arrival. Autopsy blood came from the femoral vein; urine was obtained from the bladder by suprapubic needle extraction. Blood tubes contained a reported 1% sodium fluoride preservative. Vitreous was collected into dry tubes and urine into sterile containers. The paper describes refrigeration at 2–8°C and prompt vitreous analysis, with refrigeration if postponed until the next day.

Ethanol quantification used headspace gas chromatography with flame-ionization detection. This procedure was separate from screening and other instrumental drug testing described in the study. Identification or quantification of ethanol in a collected specimen cannot independently establish its origin.

What differences were statistically significant?

Table 5 reports a blood comparison of 166 postmortem and 483 living cases, with t = 2.465, df = 69.443 and p = 0.008. The urine comparison used 127 postmortem and 483 living cases, with t = 2.460, df = 35.640 and p = 0.009. Both met the study’s stated significance threshold of p ≤ 0.01, and the reported mean was higher in the postmortem group.

These tests address group differences under the analysis used. They do not identify why the groups differed. Drinking history, selection into hospital or autopsy casework, elapsed time and other characteristics could differ between groups. No paired within-person predeath/postmortem ethanol series was supplied for this comparison.

Nor does a significant p value quantify a microbial ethanol increment. It cannot be used to calculate a universal amount or multiplier to remove from an individual autopsy result.

Reporting inconsistencies limit numerical reuse

The main methods and group counts total 649 cases, but the discussion calls the sample size 549. Table 1’s printed age-group counts also exceed its stated postmortem denominator of 166. These inconsistencies should not be silently repaired by inventing a different population.

Table 5 does not label the units beside its concentration means, while other sections use percentage BAC and mg/dL. Assigning a unit to those unlabeled means, converting them or deriving a concentration ratio for practical correction requires clarification. The statistical comparison can be described without presenting those numbers as a validated correction factor.

What did the analytical reporting establish?

The assay section reports calibration spanning 10–400 mg/dL, a 10 mg/dL cutoff and dilution followed by reanalysis for results above 400 mg/dL. Elsewhere it lists eight calibration concentrations despite describing a six-point curve. The paper defines detection and quantitation limits conceptually without supplying unambiguous matrix-specific numerical values for both. Its reporting cutoff should not be relabeled as either limit.

These analytical qualifications are distinct from the study-design issue. Even flawless measurement would not transform two different groups into a longitudinal redistribution or microbial-production experiment.

What conclusion is justified?

The study reported higher means in selected alcohol-positive autopsy cases than in selected living cases. It did not measure the amount by which a particular person’s ethanol changed after death. An opinion about drinking, impairment or causal contribution requires the actual case evidence.

For a study that did observe repeated measurements in one specimen, see serial postmortem ethanol testing. That addresses a different question from a between-group comparison.

Primary source

Issa SY, Khattab A. Ethanol concentrations in various biological specimens: Living and postmortem forensic toxicology analysis and comprehensive literature review. Journal of Forensic and Legal Medicine. 2024;106:102737. doi:10.1016/j.jflm.2024.102737.

A fermentation experiment using blood-bank material cannot automatically establish the maximum ethanol that could form in an ordinary forensic specimen. Chang and Kollman’s 1989 study found ethanol formation after inoculation with Candida albicans, but the blood contained added dextrose. The authors specifically acknowledged that this prevented assessment of their proposed glucose-based maximum yield.

What was in the experimental blood?

The researchers obtained four blood-bank collection bags of 450-mL capacity. Each contained 2.0 g dextrose, along with citrate, citric acid, phosphate and adenine. The blood was pooled; half was inoculated with C. albicans ATCC 14056 to approximately 10,000 organisms/mL.

They divided the material among 112 tubes of 10-mL capacity. Half contained 100 mg sodium fluoride and 20 mg potassium oxalate; half had no tube additives. Four conditions combined inoculated or uninoculated blood with preserved or unpreserved tubes. Filling occurred under nonsterile conditions, with uninoculated specimens serving as controls.

These were prepared aliquots from pooled material, not 112 people, 112 autopsies or a survey of naturally contaminated forensic specimens. No postmortem anatomical collection site or body decomposition interval applied to this laboratory design.

The proposed ceiling did not survive the substrate check

The discussion calculated an approximate ethanol yield of 0.05% w/v from a starting glucose concentration of 95 mg/100 mL, assuming complete conversion of one mole of glucose to two moles of ethanol. The experiment produced ethanol exceeding that estimate.

The authors then recognized the blood-bank addition of 2.0 g glucose per unit and stated that their maximum-yield hypothesis could not be assessed. The appropriate conclusion is not that fermentation violated the proposed chemical stoichiometry. The assumed substrate concentration did not describe the experimental material.

Neither the calculated 0.05% w/v nor an observed plateau near 0.08% w/v is therefore a demonstrated universal ceiling for postmortem ethanol. A yield depends on the material and conditions tested; the paper did not validate a fixed allowance to subtract from human autopsy blood.

Preservation and temperature still produced informative findings

At 37°C after about 69 hours, the four inoculated, unpreserved specimens contained 0.019–0.053% w/v ethanol. The preserved specimens, whether inoculated or not, had no detectable ethanol at that time. At 22°C, inoculated specimens developed ethanol after several days even with sodium fluoride. A short warm experiment therefore did not predict the longer room-temperature outcome.

At 6°C, no fermentation was detected during the first 35 days. After 182 days, two of four inoculated, unpreserved specimens contained 0.008 and 0.015% w/v, and one uninoculated, unpreserved specimen contained 0.004% w/v. Preserved specimens remained without detected ethanol at 182 days.

Those negative findings are conditional on the experiment and detection threshold. They do not establish that preservatives or refrigeration guarantee stability for every microbial strain, specimen and storage period.

The analytical units and detection threshold matter

Testing used direct-injection gas chromatography with flame-ionization detection, not headspace GC–MS. Methyl ethyl ketone was the internal standard. Calibration used ethanol standards of 0.122, 0.220 and 0.340% w/v, with 0.177% w/v controls at the beginning, middle and end of runs. The minimum detectable ethanol concentration was 0.003% w/v.

The reported concentrations were percentages by weight per volume: 0.05% w/v corresponds to 0.5 g/L. That conversion does not convert a detection threshold into a quantitation limit; the paper did not provide a separate fully characterized numerical quantitation limit or modern validation dataset for every condition.

What can the experiment support in case review?

It supports asking about substrate composition, organism, preservative, temperature and duration together. It demonstrates formation after experimental contamination and preserves important negative control findings. It does not measure how often forensic specimens are contaminated, establish an individual’s alcohol consumption or assign a cause of death.

A complementary human case concerns ethanol increasing during serial testing of preserved postmortem blood. The designs should remain separate.

Primary source

Chang J, Kollman SE. The Effect of Temperature on the Formation of Ethanol by Candida Albicans in Blood. Journal of Forensic Sciences. 1989;34(1):105–109. doi:10.1520/JFS12616J.

Increasing incubation temperature from 25°C to 37°C did not uniformly increase ethanol production in a three-species bacterial experiment. The response depended on the organism and on which alcohol was measured. Those results limit any simple rule that a warmer postmortem specimen must contain a proportionately larger microbial ethanol contribution.

The experimental environment was defined

Velivasi and colleagues studied individual reference strains of Klebsiella pneumoniae ATCC 13883, Staphylococcus aureus ATCC 25923 and Enterococcus faecalis ATCC 29212. Each was inoculated separately into Brain Heart Infusion broth at approximately 10⁶ colony-forming units/mL.

The main 25°C cultures were followed for 23 days. One arrangement was strictly anaerobic. The other began aerobically for five days, then used a paraffin overlay and anaerobic jars. Parallel controls were incubated at 37°C for 48 hours and 4°C for 23 days. Two tubes per sampling point from each culture set were removed for alcohol measurement. These repeated culture specimens were not independent human deaths.

Temperature effects differed by species

K. pneumoniae produced the most ethanol under the main experimental conditions, followed by S. aureus and E. faecalis. Ethanol generally rose rapidly during the first two days at 25°C and then plateaued or, for S. aureus, declined slowly.

The maximum ethanol concentrations for K. pneumoniae and E. faecalis at 37°C were comparable to those at 25°C. In contrast, S. aureus produced lower ethanol concentrations at 37°C than at 25°C. The paper describes these patterns but does not provide a formal statistical demonstration of equivalence between the temperature conditions.

The other alcohols did not all move with ethanol. At 37°C, K. pneumoniae produced more 1-butanol but less 1-propanol, isobutanol and methyl-butanol than at 25°C, while its ethanol maximum was similar. A temperature effect on one congener therefore cannot be substituted automatically for an effect on ethanol itself.

Oxygen history was another experimental variable

Strictly anaerobic incubation yielded slightly higher ethanol concentrations than the aerobic-to-anaerobic arrangement for all three species. The transition was intended to approximate declining oxygen availability after death. It did not reproduce the complete microbial community, nutrient changes or temperature history of a human body.

The species also differed in their dominant non-ethanol alcohol. At 25°C, 1-propanol predominated for K. pneumoniae and S. aureus, whereas 1-butanol predominated for E. faecalis. This matters when interpreting a congener pattern: identical ethanol origins need not produce one fixed companion-alcohol ratio across all organisms and conditions.

What did the refrigerated controls show?

No ethanol or other studied volatiles were produced in the 4°C broth controls during the 23-day incubation under either aeration arrangement. That is useful evidence for the tested strains, medium, inoculum and duration. It does not establish that every refrigerated autopsy specimen is unchanged or that refrigeration removes ethanol already formed before collection.

The study separately inoculated pooled human blood heated at 50°C for about two hours to denature proteins. The resulting alcohol patterns differed from broth, and E. faecalis produced negligible alcohols in that medium. Even this substitute for postmortem blood was not equivalent to an intact decomposing body.

What was measured, and what remains unknown?

Headspace GC–FID measured ethanol and five other alcohols. Table 1 reports ethanol calibration of 0.005–4.0 g/L, a detection limit of 0.001 g/L and a quantitation limit of 0.005 g/L. Its ethanol quantitation limit differs from a figure in the prose, an internal reporting issue relevant to method reproduction. Analytical performance does not supply a human postmortem production rate.

The 25°C and 37°C experiments also had different observation periods. They should not be used to invent a universal temperature coefficient, hourly production rate or amount to subtract from a person’s result. The findings establish neither drinking, impairment nor ethanol’s role in death.

For evidence from a different design, see serial changes in a preserved human postmortem specimen.

Primary source

Velivasi G, Kourkoumelis N, Sakkas H, Boumba VA. Modeling microbial ethanol production by S. aureus, K. pneumoniae, and E. faecalis under aerobic/anaerobic conditions — applicability to laboratory cultures and real postmortem cases. International Journal of Legal Medicine. 2021;135:2555–2565. doi:10.1007/s00414-021-02638-4.

A microbial ethanol model that approximated measured blood ethanol in 35 of 93 selected autopsy cases did not establish that 38% of deaths involved postmortem ethanol production. The study measured agreement between a calculation and the observed ethanol concentration. It did not independently determine the microbial fraction in each specimen.

How were the models developed?

Velivasi and colleagues cultured three reference bacterial strains separately: Klebsiella pneumoniae, Staphylococcus aureus and Enterococcus faecalis. Brain Heart Infusion broth was inoculated to approximately 10⁶ colony-forming units/mL. The main cultures were incubated at 25°C for 23 days, either anaerobically throughout or aerobically for five days followed by anaerobic conditions.

Stepwise linear regression related measured ethanol to the concentrations of other alcohols. The investigators measured 1-propanol, isobutanol, 1-butanol and two methyl-butanol isomers; the last two were combined for model reporting. These were culture-derived equations, rather than equations derived from people with known drinking doses and known amounts of postmortem production.

What counted as a successful application?

The authors set an error criterion of less than ±40% when comparing calculated ethanol with measured ethanol. Thus, their term “successful” allowed a substantial difference. It did not mean exact agreement, correct identification of the organism or validated reconstruction of blood alcohol during life.

For the autopsy application, the investigators retrospectively selected 93 blood chromatograms with ethanol above 0.10 g/L and detected higher alcohols and 1-butanol. This selected set was enriched for findings relevant to the proposed models. It was not a random sample of all deaths or all ethanol-positive autopsies. The paper did not provide one uniform blood collection site, death-to-collection interval or storage history for those 93 specimens.

The denominator and a numerical inconsistency

Table 3 reports that at least one K. pneumoniae model met the error criterion in 35 of 93 cases, approximately 38%. The corresponding totals were 18 of 93 for S. aureus and 25 of 93 for E. faecalis. These sets should not be added as if they were mutually exclusive diagnoses of three infections.

The higher-ethanol subgroup contained 54 cases. Table 3 gives 25 successful K. pneumoniae applications in that subgroup, about 46%; the lower subgroup had 10 of 39, about 26%. The discussion instead prints “35/54” beside 46%. That fraction is inconsistent with both the percentage and table. Using the table’s 25/54 preserves the distinction between the subgroup result and the overall 35/93.

Agreement with total ethanol does not isolate its source

In an authentic case, measured ethanol could contain antemortem ethanol, microbial ethanol or both. A model’s proximity to the total does not independently establish that the total was all microbial. Conversely, failure to match does not establish that no microbial production occurred.

The laboratory findings themselves showed dependence on organism, temperature and medium. Denatured blood did not reproduce every higher-alcohol pattern observed in broth. The authors also acknowledged variable microbial succession in real bodies and called for further work on applicability. The study supports investigation of these models, with limits on causal interpretation.

Analytical identification and model validation are separate

Alcohols were measured by headspace GC with flame-ionization detection. Table 1 lists ethanol detection and quantitation limits of 0.1 and 0.5 mg/dL, equivalent to 0.001 and 0.005 g/L, with calibration up to 4.0 g/L. The prose gives a different ethanol quantitation-limit figure, so that discrepancy should be resolved before reproducing the assay. None of those analytical limits establishes biological specificity for microbial ethanol.

A case review should state the selection criteria, model used, error tolerance and independent evidence of origin. The model-match percentage is not a prevalence estimate, an impairment measure or a cause-of-death determination. For another transfer problem, see ethanol models across broth, blood and plasma.

Primary source

Velivasi G, Kourkoumelis N, Sakkas H, Boumba VA. Modeling microbial ethanol production by S. aureus, K. pneumoniae, and E. faecalis under aerobic/anaerobic conditions — applicability to laboratory cultures and real postmortem cases. International Journal of Legal Medicine. 2021;135:2555–2565. doi:10.1007/s00414-021-02638-4.