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A racemic methamphetamine dose contains equal amounts of its two enantiomers. That does not mean urine will contain equal amounts of their corresponding metabolites. Li and colleagues’ 2010 controlled experiment showed substantial stereoselectivity, particularly in the urinary recovery of amphetamine formed after methamphetamine administration.

What was the experimental design?

Twelve healthy male intravenous methamphetamine users participated in a six-session, double-blind, placebo-controlled crossover study. They were not methamphetamine-dependent under the study criteria. Each person received S-(+)-methamphetamine at 0.25 and 0.5 mg/kg, R-(−)-methamphetamine at those doses, racemic methamphetamine at 0.5 mg/kg total, and placebo on separate occasions.

The racemic condition supplied 0.25 mg/kg of each enantiomer, rather than 0.5 mg/kg of each. Infusions were intravenous over one minute, with sessions approximately one week apart. These conditions must remain attached to the findings; they are not oral-dose or inhaler experiments.

Which specimens and quantities were analyzed?

The study collected urine over intervals ending at 4, 8, 12, 24 and 48 hours, recording each interval’s volume. Chiral gas chromatography–mass spectrometry separated and measured the enantiomers and metabolites. Serial blood sampling supported the related plasma pharmacokinetic analyses.

Urinary recovery expresses the amount measured over collection intervals relative to the administered dose. It is not the same quantity as the concentration in a single spot urine, which also depends on urine volume. Nor is recovered metabolite necessarily the entire amount formed throughout the body.

What showed the strongest stereoselectivity?

Approximately 6–7% of the S-(+)-methamphetamine dose was recovered as corresponding amphetamine, compared with approximately 2% of the R-(−) dose. The difference was significant (p<0.001). Hydroxylated methamphetamine showed a smaller enantiomer difference.

More unchanged R-(−)-methamphetamine than S-(+)-methamphetamine was recovered in urine. Thus, the parent drug and different metabolites did not all share one common enantiomer pattern. A generic “amphetamine-type stimulant ratio” would obscure what was actually measured.

Did the proportions stay constant over time?

After the racemic dose, the average S/R ratio of cumulative amphetamine recovery was approximately 6:1 at four hours and approximately 3:1 at forty-eight hours. The corresponding parent-methamphetamine ratio changed from approximately 1:1 to 0.7:1.

These were ratios of cumulative recovered amounts in a controlled protocol. They should not be silently substituted for ratios from one forensic spot sample. The differing patterns show why metabolite stereochemistry cannot simply be copied back onto the original consumed material.

What uncertainty limits individual interpretation?

The study found substantial between-person variation, including one participant with unusually low metabolite formation. The authors considered a possible CYP2D6 explanation, but did not genotype participants. An interesting outlier therefore did not establish that individual’s genotype.

Urine pH was not measured, despite its known relevance to urinary elimination discussed by the authors. The sample contained only twelve men and tested specific single intravenous regimens. Repeated use, other substances and different exposure routes require additional evidence.

This experiment supports stereoselective metabolism and recovery under its tested conditions. It does not validate an exact last-use clock, a universal source-composition correction or an impairment estimate. The practical question for a disputed ratio is which analyte, specimen, collection interval and calculation produced it—not merely whether the original drug was racemic.

Source

Li L, Everhart T, Jacob P III, Jones R, Mendelson J. Stereoselectivity in the human metabolism of methamphetamine. British Journal of Clinical Pharmacology. 2010;69(2):187–192. doi:10.1111/j.1365-2125.2009.03576.x.

Wastewater monitoring can reveal community drug patterns without identifying how many individuals used methamphetamine. A large international study measured amphetamine and methamphetamine residues across 120 cities during 2011–2017. Its basic result was a mass load normalized to population, not a count of drug-positive residents.

How extensive was the sampling?

González-Mariño and colleagues included catchments served by 143 wastewater treatment plants in 120 cities across 37 countries. More than 60 million people were represented at least once. Those cumulative coverage figures do not mean that every city was sampled in every year.

Sampling typically covered seven consecutive days in March or April each year, targeting a normal week without major festivals or holidays. Twenty-six European cities supplied at least five years of data. Short annual snapshots can support comparisons, but they are not continuous year-round surveillance.

What did the laboratory actually measure?

Laboratories used liquid chromatography–tandem mass spectrometry to quantify parent amphetamine and methamphetamine in raw wastewater, alongside markers of other drugs. Concentrations in ng/L were combined with wastewater flow and estimated catchment population to calculate loads in mg per 1,000 people per day.

The denominator was the estimated population contributing to that sewer system. It was not the number of people consuming the drug. The numerator was measured mass passing through the sampled wastewater, subject to collection, analytical and sewer-process uncertainties.

Why can a larger load have several explanations?

A higher drug mass can be compatible with more people using the drug, greater consumption by the same number of people, different purity, or differences in excretion and sewer conditions. The chemical measurement alone does not distinguish those possibilities.

Direct disposal can also contribute. The study excluded some unusually affected locations from certain summary calculations because drug-manufacturing discharges could overwhelm the consumption signal. A quantity entering a sewer is not automatically a quantity that passed through a human body.

Why is amphetamine especially difficult to attribute?

Amphetamine can enter wastewater after amphetamine consumption, prescribed use, methamphetamine metabolism or disposal. The study estimated amphetamine consumption from the full amphetamine load without subtracting every potential non-illicit or metabolite contribution.

Consequently, a map labeled amphetamine cannot automatically be interpreted as a map of illicit amphetamine use. The authors specifically discussed this limitation in areas with high methamphetamine consumption or substantial prescription amphetamine use. Analytical separation of amphetamine from methamphetamine is necessary but does not by itself resolve each compound’s source.

What about the estimated number of doses?

The researchers applied average excretion factors and assumed drug doses to estimate consumption. They also summed estimated doses across several stimulants. These calculations add assumptions about dose, purity and administration patterns to the underlying mass measurements.

An estimated dose count is not a count of unique consumers: one person may account for multiple doses, and different substances in the combined total need not have been taken by the same individuals. Combined-dose estimates also excluded cannabis because of additional measurement uncertainty.

What conclusions remain useful?

The study found geographically distinct stimulant patterns and described wastewater data as complementary to surveys and seizure information. Comparisons were qualitative where indicators measured different things. Few sampled cities within a country could not establish a representative national rate.

For careful reporting, retain the collection week, catchment, analyte, mass unit and population estimate. Distinguish a measured load from a modeled consumption estimate. This historical dataset cannot establish present-day local prevalence, identify an individual consumer, or provide evidence of anyone’s impairment.

Source

González-Mariño I, Baz-Lomba JA, Alygizakis NA, et al. Spatio-temporal assessment of illicit drug use at large scale: evidence from 7 years of international wastewater monitoring. Addiction. 2020;115(1):109–120; online 2019. doi:10.1111/add.14767.

Improvement in mood does not necessarily mean that craving has ended. Zorick and colleagues’ 2010 study followed methamphetamine-dependent volunteers during monitored abstinence for up to five weeks. Average psychiatric symptoms declined substantially, while craving persisted at a reduced level later in the observation period.

Who participated, and under what conditions?

The research included 56 methamphetamine-dependent participants and 89 healthy comparisons. The methamphetamine group was not seeking treatment and lived in a research hospital; comparisons were assessed as outpatients. Participants with several major medical or psychiatric conditions were excluded.

Daily urine testing and alcohol breath testing monitored inpatient abstinence. Staff restricted drug-related cues and media, and participants had individual rooms. Those controlled conditions differ from everyday environments where people encounter stress, access to drugs and familiar cues.

The researchers did not administer a standardized methamphetamine regimen before cessation. Last-use timing combined self-report with screening information. Participants entered related research protocols lasting either two or five weeks, so the initial 56 did not all supply every five-week assessment.

What did “symptoms resolved” mean?

The paper’s abstract summarized depressive and psychotic symptoms as largely resolving within a week. The detailed results require a more qualified account. Beck Depression Inventory scores declined substantially over the first two weeks, but remained higher than comparison scores during the first three weeks.

By the end of week four, the between-group depression comparison was not statistically significant at the conventional threshold (p=0.07). That does not prove every participant was symptom-free or that the two populations were equivalent. A mean decline and the disappearance of a significant group contrast are different findings.

How did craving differ?

Craving remained elevated through the first week, fell significantly after more than two weeks relative to entry, and continued at a lower level through week five. Five weeks was the end of observation, not a demonstrated universal endpoint of craving.

At entry, craving and depression scores were not significantly correlated. Associations appeared at the first and second weeks, but not at later assessed points. The relationship between the measures therefore depended on when it was examined.

Neither a craving score nor a depression score measured the amount of methamphetamine remaining in blood. Persistent craving after monitored abstinence does not establish continued consumption, just as reduced craving does not establish absence of exposure in an unmonitored setting.

Why did the assessment method matter?

The researchers used an investigator-rated withdrawal questionnaire and self-report psychiatric scales. These did not always produce the same impression of symptom severity. The investigator-rated instrument tended to indicate lower severity than self-report measures.

Those differences could reflect what each instrument measured or how comfortable participants were disclosing symptoms. They are reasons to retain the instrument’s identity rather than combine every rating into one interchangeable “withdrawal score.”

Can the averages determine an individual recovery date?

No. The selected, medically screened, non-treatment-seeking cohort and inpatient setting limit generalization. The study did not follow participants beyond five weeks or validate its symptom pattern as a prediction rule for relapse or day-to-day functioning.

The authors discussed possible implications for relapse, but this symptom-course study did not prove that one particular day range causes the highest relapse risk. Its strongest direct evidence concerns the observed trajectories. Those trajectories show why improving psychiatric symptoms and ongoing craving can coexist, without prescribing a deadline for any individual’s recovery.

Source

Zorick T, Nestor L, Miotto K, et al. Withdrawal symptoms in abstinent methamphetamine-dependent subjects. Addiction. 2010;105(10):1809–1818. doi:10.1111/j.1360-0443.2010.03066.x.

A research label such as “persistent psychotic symptoms” needs its operational definition. In McKetin and colleagues’ 2016 study, it meant symptoms reported during at least one observed month of methamphetamine use and at least one observed month of abstinence. It did not mean that researchers continuously documented psychosis throughout the intervening years.

How was the cohort observed?

The prospective Australian study analyzed 278 people with methamphetamine dependence who did not meet lifetime DSM-IV criteria for schizophrenia or mania. Interviews occurred at baseline, three months, one year and three years. Each interview assessed the preceding month.

These were four noncontiguous observation windows, not thirty-six months of continuous symptom surveillance. The dataset contained 1,064 observed person-months because not everyone contributed the final interview. Most participants had injected methamphetamine, and the selected cohort should not be treated as representative of all people using the drug.

Why were only 232 people classified?

The symptom grouping excluded 35 participants who reported methamphetamine use at every observed follow-up, because symptom status during abstinence could not be evaluated. Eleven more had symptoms only during abstinent months and were excluded from these three groups.

The remaining 232 comprised 110 with no observed psychotic symptoms, 85 with symptoms only during use months and 37 with symptoms during both use and abstinent months. The reported 16% persistent-symptom figure was 37/232. It was not 16% of a community sample or a lifetime risk estimate for everyone who uses methamphetamine.

What counted as a psychotic symptom?

Trained interviewers used the Brief Psychiatric Rating Scale. The research threshold was a score of at least four on suspiciousness, unusual thought content or hallucinations. That criterion identifies clinically significant symptoms under the instrument’s rules; it does not independently establish a particular psychotic-disorder diagnosis.

Use and abstinence were largely assessed by report, with validation of abstinence in a subset of the larger cohort. No standardized methamphetamine dose or purity was assigned. A month classified as abstinent is also not equivalent to an experimentally controlled drug-free period for every participant.

Which associations distinguished the groups?

Conduct disorder and anxiety disorders were associated with both transient and persistent categories relative to the no-symptom group. Persistent symptoms were additionally associated with family history of primary psychotic disorder and major depression.

After adjustment for dependence severity, the reported odds ratios for persistent symptoms were 2.7 for family history (95% confidence interval 1.1–6.4) and 2.8 for depression (1.2–6.8). These describe group associations. They are not validated probabilities that classify an individual or prove which factor caused symptoms.

What could the observation windows miss?

Someone could have experienced symptoms between interviews and been classified as having no observed symptoms. Someone labeled transient could have experienced symptoms during an unobserved abstinent period. The authors specifically identified these possible misclassifications.

Only 37 people occupied the persistent group, limiting more detailed modeling. Depression could precede symptoms, accompany them or follow their consequences; the design did not resolve every temporal pathway. Several apparently predictive characteristics could also reflect related comorbidities.

The study is useful for distinguishing observed symptom patterns and identifying research questions. It cannot determine a particular person’s mental state at an unobserved incident, attribute every symptom to methamphetamine, or establish uninterrupted illness from four sampled months.

Source

McKetin R, Gardner J, Baker AL, et al. Correlates of transient versus persistent psychotic symptoms among dependent methamphetamine users. Psychiatry Research. 2016;166–171. doi:10.1016/j.psychres.2016.02.038.

Finding a metabolite in hair can add information, but its biological origin does not automatically establish how it entered the hair. A study of 63 deceased people examined para-hydroxy-methylamphetamine alongside methylamphetamine and amphetamine. The authors described the hydroxylated metabolite as a potential marker with reservations, rather than a validated answer to postmortem contamination.

What material was studied?

Mantinieks and colleagues analyzed hair from coronial cases with methylamphetamine detected in femoral blood. The paper appeared online in 2024 and in the 2025 volume of Drug Testing and Analysis. This was an analytical validation and selected autopsy-case application, not controlled dosing of living volunteers.

Hair segments nearest the root were standardized to no more than three centimeters, washed sequentially with dichloromethane and water, then extracted for liquid chromatography–tandem mass spectrometry. Of the 63 cases, 23 involved decomposition, 39 had normal body condition and one involved trauma. Washes were separately classified as clean or visibly soiled.

What did the assay add?

The lower quantification limits were 0.01 ng/mg for methylamphetamine and amphetamine and 0.001 ng/mg for para-hydroxy-methylamphetamine. These are hair-mass units. They should not be compared directly with a blood result reported per milliliter.

Para-hydroxy-methylamphetamine was quantified in 62 hair samples, with a median of 0.020 ng/mg and range of 0.0012–0.38 ng/mg. The very low concentrations explain why analytical sensitivity matters. Detection establishes what the assay measured; it does not, by itself, establish the route of incorporation.

The table’s denominators also varied by analyte and concentration range. Twelve methylamphetamine hair results exceeded the upper quantification limit. Its reported median among quantifiable values should not silently be treated as though all 63 results fell within the validated numerical range.

Why does postmortem contamination remain possible?

Hair collected after death may contact blood, sweat or decomposition fluids containing parent drugs and metabolites. Material coming from the person’s own body can be external to the hair shaft. It may reflect exposure somewhere in the organism without proving incorporation into growing hair over a particular earlier period.

The study found wash-to-hair patterns consistent with contamination, especially among visibly soiled samples. Hair concentrations of the hydroxylated metabolite were higher in the soiled group. Strong correlations among analytes did not establish that every analyte entered exclusively during hair growth.

Did bleaching settle the question?

The researchers also examined a limited bleaching experiment involving three case samples and fortified hair. Parent methamphetamine and amphetamine declined in the treated case hair. Small increases in the hydroxylated metabolite in two cases could have reflected analytical variation.

The methamphetamine-fortified hair did not produce detectable amphetamine or para-hydroxy-methylamphetamine under the tested bleaching conditions. That null finding matters: the paper should not be cited as proving that routine bleaching always creates the metabolite. The authors called for further work under realistic conditions.

What remains unvalidated?

The wash-residue analysis was not itself part of the method validation, and the authors acknowledged uncertainty about decontamination effectiveness. The cohort consisted of selected drug-related deaths, so its concentration distribution was not representative of living users.

For case review, the metabolite result belongs beside specimen condition, wash appearance, analytical limits, treatment history and other toxicology. This study did not establish a standalone hair threshold that distinguishes ingestion from every source of contamination, reconstructs a dose, or proves tolerance or impairment.

Source

Mantinieks D, Drummer OH, Schumann J, Gerostamoulos D. The analysis of methylamphetamine and para-hydroxy-methylamphetamine in post-mortem hair samples using liquid chromatography–tandem mass spectrometry. Drug Testing and Analysis. 2025;17:544–554; online 2024. doi:10.1002/dta.3765.

A hair methamphetamine concentration is not a simple dose meter. In a controlled human experiment, higher administered doses generally produced higher hair concentrations within the same person, but concentrations differed substantially between people receiving the same regimen. Those findings answer different questions and should be reported together.

What was controlled in this experiment?

Polettini and colleagues’ 2012 paper studied seven volunteers with stimulant-use histories in an inpatient unit. After a washout period, participants received four oral 10 mg doses of sustained-release S-(+)-methamphetamine hydrochloride within one week. Four participants later completed a higher regimen of four 20 mg doses after a three-week interval.

The administered totals were therefore 40 mg and 80 mg of the specified hydrochloride preparation, spread across dosing occasions. They were not single 40 mg or 80 mg doses. Timing sometimes departed from consecutive-day administration because of clinical or scheduling considerations.

Controlled access reduced the possibility of additional drug use and environmental drug-smoke exposure during the experiment. It did not eliminate drug reaching hair through participants’ own sweat or sebum.

How was hair collected and measured?

Investigators repeatedly shaved newly available scalp hair, usually in approximately weekly collections, with actual intervals ranging from five to twelve days. The main analysis used posterior-vertex hair. Methamphetamine and amphetamine were quantified by liquid chromatography–tandem mass spectrometry after washing; the lower quantification limit was 0.005 ng/mg for each analyte.

This collection method followed successive newly emerging hair samples. It differs from cutting one long strand into segments after several months. The resulting timeline should not be transferred unchanged to routine segmental testing.

How much did concentrations vary?

Peak methamphetamine concentrations ranged from 0.6–3.5 ng/mg after the lower regimen and 1.2–5.3 ng/mg after the higher regimen. The corresponding amphetamine ranges were 0.1–0.3 and 0.2–0.5 ng/mg. These ranges overlap across dose conditions.

Within individuals, the higher regimen generally produced greater incorporation. Across individuals, however, someone receiving the lower regimen could have a higher hair result than someone receiving the higher regimen. A within-person dose relationship does not establish a universal between-person conversion equation.

Why did pigmentation matter?

The study measured total hair melanin and found positive associations with methamphetamine and amphetamine incorporation. Some of the strongest reported relationships used body-weight adjustment and logarithmic transformation. They should not be described as a simple unadjusted correlation applying equally to every sample.

The finding supplies a biological reason for caution when ranking people by hair concentration. It does not establish an individually validated “melanin correction” that allows an analyst to calculate an unknown consumed dose. The small cohort and only four higher-regimen completers limit that possibility.

Can the peak date identify the exact day of use?

Drugs were first detected in the first scheduled postdose hair samples, collected six to eight days after the initial dose. That is the earliest sampled detection, not proof that hair was negative at every earlier moment. Methamphetamine peaks occurred in the first or second weekly sample, even among participants with similar dosing schedules.

Growth variability, specimen location, washing and collection intervals all affect interpretation. The study also found that washing removed different amounts over time. A wash result therefore needs the actual collection and preparation protocol rather than a generic label of “decontaminated.”

The defensible historical conclusion is that controlled dosing supports a dose-related incorporation process, while substantial biological and sampling variation prevents straightforward dose reconstruction from another person’s hair concentration. A hair result also does not supply a contemporaneous blood concentration or establish functional impairment on a particular date.

Source

Polettini A, Cone EJ, Gorelick DA, Huestis MA. Incorporation of methamphetamine and amphetamine in human hair following controlled oral methamphetamine administration. Analytica Chimica Acta. 2012;726:35–43. doi:10.1016/j.aca.2012.01.042.

Two drugs detected in the same body need not share the same postmortem distribution. Pounder and Jones documented differing blood-site and tissue patterns in four detailed overdose cases. Their observations support interpreting each analyte separately rather than using one co-detected drug as a correction for another.

A case series with anatomically controlled sampling

The 1990 study selected suspected overdose cases before medicolegal autopsy. Investigators collected multiple tissues and fluids and took blood by needle puncture after ligating or cross-clamping the relevant vessels. This approach helped preserve the distinction between sampling sites.

The four cases involved different drug combinations and different intervals. Autopsy occurred 17 hours after discovery in case 1, an estimated 36 hours after death in case 2, approximately 24–48 hours after death in case 3, and 7.25 hours after death in case 4. These were descriptive individual investigations, not a randomized experiment or a prevalence survey. The methods do not provide a uniform specimen storage or preservative protocol.

Clomipramine and flurazepam peaked at different blood sites

Case 3 concerned a 24-year-old woman reported to have taken chloral hydrate, clomipramine and flurazepam. Across blood sites, clomipramine ranged from 4.0 to 21.5 mg/L and its metabolite desmethylclomipramine from 1.7 to 8.1 mg/L. The highest concentrations were in pulmonary arterial and venous blood, and the lowest in femoral veins.

Flurazepam ranged from 0.15 to 0.99 mg/L. Its highest reported blood concentration was in the infrarenal inferior vena cava, with the lowest in subclavian and femoral veins. Mixed cardiac blood contained clomipramine 15.3 mg/L, desmethylclomipramine 4.1 mg/L and flurazepam 0.51 mg/L. “Cardiac blood” therefore did not represent the maximum for every compound.

Tissue concentrations also differed by drug

In that same case, liver contained clomipramine 298 mg/kg and desmethylclomipramine 58 mg/kg; lung contained 107 and 54 mg/kg, respectively. Flurazepam concentrations were 1.1 mg/kg in liver and 0.42 mg/kg in lung, with 1.5 mg/kg in renal cortex and 4.9 mg/kg in perirenal fat.

These findings describe different tissue distributions. Tissue values in mg/kg should not be treated as numerically interchangeable with blood values in mg/L or used to infer equivalent pharmacological effects across drugs. The measured amount of unabsorbed drug in gastrointestinal contents likewise is a different quantity from a tissue concentration.

A second case provided an informative contrast

Case 4 involved imipramine overdose followed by hospital treatment that included intravenous lidocaine. Imipramine concentrations across postmortem blood sites ranged from 4.1 to 18.1 mg/L, whereas lidocaine ranged from 0.9 to 1.4 mg/L. Liver and lung imipramine were 136 and 100 mg/kg, compared with lidocaine at 1.0 and 0.9 mg/kg.

The contrast illustrates different distributions within one body, but it does not isolate an intrinsic drug effect: dose, route, treatment timing and time available for distribution differed. It cannot establish that lidocaine never redistributes or that every imipramine case follows this pattern.

Mechanistic evidence and analytical limits

The authors proposed diffusion from drug-rich organs, particularly liver and lung, as a major explanation for site differences. They also considered incomplete distribution during life, variable blood composition and postmortem changes. Their case data supported a mechanism; they did not directly measure drug movement over time or prove a single cause.

Tricyclic compounds were quantified by gas chromatography with nitrogen–phosphorus detection, barbiturates by HPLC–UV, and flurazepam-related compounds by gas chromatography with electron-capture detection. Assays used internal standards, five-point calibration, duplicate case analyses and independently prepared controls. Full numerical detection limits, precision and recovery validation were not reported. These were targeted quantitative procedures, not one comprehensive screening method.

Interpret each analyte on its own evidence

The series supplies no universal redistribution factor and no statistical estimate of how often these patterns occur. A drug’s detection, a tissue reservoir and a high autopsy blood concentration are separate findings; none alone establishes the dose, impairment or cause of death.

Review the exact vessel, analyte, method and timing for each result. Our discussion of subclavian versus femoral sampling addresses the additional problem of treating different peripheral sites as equivalent.

Primary source

Pounder DJ, Jones GR. Post-mortem drug redistribution—A toxicological nightmare. Forensic Science International. 1990;45:253–263. doi:10.1016/0379-0738(90)90182-X.

Blood THC accompanied by negative urine THCCOOH does not, by itself, establish cannabis use immediately before death. Tascon and colleagues found that combination substantially more often in selected postmortem cases than in separate living-person cases. They identified redistribution as a possible explanation, rather than validating the pattern as a clock for last use.

The comparison used separate case populations

The Quebec laboratory database covered 2018–2019 and included 276 postmortem cases and 351 antemortem cases with THC or its metabolites detected in blood. The living-person cases comprised 196 sexual-assault investigations and 155 driving-under-the-influence-of-drugs investigations. They were not earlier samples from the same people later examined at autopsy.

For autopsies, cardiac blood was pooled from both ventricles. Femoral blood was obtained from the exposed, unclamped femoral vein, with a maximum collection of 7 mL. Blood received sodium fluoride and potassium oxalate, and specimens were kept at 4°C during analysis. Urine was collected when available. The paper does not provide a uniform urine preservative protocol or a case-specific collection interval for every urine–blood pair.

Keep the paired-specimen denominators separate

Among 221 postmortem cases with femoral blood and urine analyzed, 39 had blood THC with no detected urinary THCCOOH—reported as 18%. Femoral blood THC in those cases ranged from 0.5 to 82 ng/mL.

In the antemortem comparison, the pattern occurred in four of 191 sexual-assault cases and two of 11 driving cases with both matrices analyzed: six of 202, approximately 3% overall. Blood THC in those six cases ranged from 1.1 to 1.8 ng/mL.

The relevant denominators are 221 and 202, not all 276 and 351 cases in the database. These selected populations and their different investigation contexts also prevent treating the percentages as general rates among all deceased or living cannabis users.

What “negative urine” meant analytically

The laboratory used protein precipitation followed by LC–MS/MS, with two monitored transitions per analyte. Blood quantification ranges were 0.5–100 ng/mL for THC, 2–400 ng/mL for 11-OH-THC and 5–1000 ng/mL for THCCOOH. Urine was assessed qualitatively with cutoffs of 1.5, 6 and 15 ng/mL, respectively.

No hydrolysis of glucuronides was performed. The urinary THCCOOH result therefore should not be relabeled as a hydrolyzed total-metabolite concentration. Nor should a negative classification at the 15 ng/mL urinary cutoff be equated with proof that no THCCOOH molecules or conjugates were present.

The study reports method validation including accuracy, precision, matrix effects, interference and dilution integrity, but does not supply full numerical performance results for every parameter in the article. Its urine result was a method-specific qualitative finding, separate from quantitative blood measurement and from a broad immunoassay screen.

Why postmortem redistribution changes the inference

In the authors’ interpretation, absent urinary metabolite can accompany very recent exposure, but postmortem release of THC into blood provides another possible explanation. Their broader database showed substantial blood-site variability. It did not directly establish the last-use time or amount of redistribution in each of the 39 discordant cases.

Without matched predeath specimens, the study cannot assign each case to recent use or redistribution with a known error rate. It also did not test whether every negative urine result arose from the same mechanism. A distribution pattern can raise an interpretive question without answering it.

What a defensible report should retain

Describe the actual blood site and THC concentration, the urine analyte, the cutoff and whether hydrolysis was performed. Review both central and peripheral blood where available, specimen histories and independent case information. A urine result measured after death should not be turned into an unsupported number of minutes since cannabis use.

These findings do not establish impairment or a causal role in death. They also do not make the negative urine result uninformative; they define the limits of the timing inference. For the distinct analytical consequences of deconjugation, see our discussion of hydrolyzed postmortem urine and bile cannabinoid results.

Primary source

Tascon I, Côté C, Garneau B, Desharnais B, Gosselin V, Mireault P. Postmortem redistribution of cannabinoids: Statistical analysis of a novel dataset and meta-analysis. Forensic Science International. 2023;353:111873. doi:10.1016/j.forsciint.2023.111873.

Ethanol can decrease during blood putrefaction as well as increase. In a 24-specimen experiment, Chen and colleagues observed different trajectories depending on the specimen and its starting condition. The results undermine a one-direction assumption that microbial activity always adds a predictable amount of ethanol.

What was incubated, and under which conditions?

The investigators selected 12 blood specimens from well-preserved deceased people and 12 from living people suspected of drunk driving. Each source contributed six classified as ethanol-negative and six classified as ethanol-positive, creating four groups of six specimens.

Autopsy blood came from the right cardiac chamber; living specimens were venous whole blood collected in sodium-citrate tubes. These differences in source and collection conditions were part of the design, rather than factors held identical between groups. The authors considered sterility during living-person collection a possible explanation for some observed differences.

Blood was incubated in closed tubes at 37°C without agitation and sampled on days 0, 1, 3, 5 and 7. The study’s initial casework handling involved immediate analysis or no more than eight hours at 4°C before testing, followed by −20°C storage. The seven-day incubation was a separate experimental condition. It did not simulate continuous refrigeration of routine preserved casework.

Initially negative blood could develop ethanol

In the ethanol-negative deceased group, three specimens showed continued ethanol increases across the seven-day experiment; the other three increased and then declined slightly. In the ethanol-negative living group, ethanol appeared by day 3 in five specimens, while specimen 14 remained at the reported 0.000 mg/mL throughout.

These different curves show why “ethanol formed in an incubated specimen” is more precise than assigning one production rate to every specimen. They also show that a final value can conceal an earlier peak.

Initially positive specimens often lost ethanol

The six ethanol-positive living specimens began between 0.379 and 1.041 mg/mL. The authors described an overall downward trend with fluctuations, except for specimen 23, whose ethanol was almost constant. In the ethanol-positive deceased group, starting concentrations and subsequent patterns were heterogeneous; the authors described decreases among higher-starting specimens but could not draw a uniform conclusion for low-starting specimens.

The report does not provide a validated rate of loss, a uniform percentage decrease or a statistical comparison establishing that every positive specimen must decline. Its individual curves should not be converted into a back-calculation formula for an unrelated death investigation.

A changing concentration is a net result

The authors discussed ethanol–acetaldehyde conversion and microbial production or degradation as explanations. They did not identify the microbial species in each experimental specimen or separately measure the amount produced and the amount consumed. A falling ethanol concentration therefore does not prove that no ethanol formation occurred at the same time.

That distinction also prevents the reverse error: an ethanol increase does not prove that no ethanol was lost. The measured concentration reflects the balance of processes in that particular specimen and incubation history.

Other markers did not supply a correction

Dual-column headspace GC–FID measured ethanol, acetaldehyde and n-propanol. Their stated detection limit was 0.002 mg/mL and quantification limit 0.005 mg/mL; ethanol calibration extended to 3.0 mg/mL. EtG and EtS were measured separately by LC–MS/MS, with limits of 10 and 15 ng/mL for detection and quantification.

Acetaldehyde changed during incubation, but the investigators could not fit a satisfactory quantitative relationship to ethanol. N-propanol was undetected in many specimens. Neither result justified a case-specific correction for the ethanol change.

What this means for serial testing

Retain the complete sequence of results and the time–temperature history, rather than selecting one measurement as necessarily representative of the original specimen. Reanalysis can document disagreement, but its direction alone cannot reconstruct ethanol at collection or during life.

The small groups, unequal starting concentrations, absent microbial identification and single warm-incubation temperature limit generalization. The study neither establishes impairment nor assigns a causal role in death. Compare this controlled incubation with the distinct evidence from a preserved autopsy specimen whose ethanol increased during serial testing.

Primary source

Chen X, Dong X, Zhu R, et al. Abnormally High Blood Acetaldehyde Concentrations Suggest Potential Postmortem Ethanol Generation. Journal of Analytical Toxicology. 2021;45:748–755. doi:10.1093/jat/bkaa173.

Blood acetaldehyde above 0.14 mg/mL can support suspicion of postmortem change, but it does not prove that all detected ethanol formed after death. Chen and colleagues proposed that threshold from selected forensic samples and laboratory incubation experiments. Their study did not validate a case-specific calculation of the amount of ethanol produced.

The threshold came from three selected groups

The investigators initially collected 177 venous whole-blood samples from living people suspected of drunk driving and 250 right-cardiac-chamber blood samples from deceased people. Living specimens were collected into sodium-citrate tubes. Autopsy specimens were collected into glass tubes for prompt analysis without the preservation treatment that could interfere with the later putrefaction experiment.

Samples were analyzed immediately or refrigerated at 4°C for no more than eight hours before testing, then stored at −20°C. The deceased group included traffic fatalities and other causes of death. Some case-specific death times and postmortem intervals were unavailable.

For the cross-sectional comparison, blood with ethanol below 0.05 mg/mL was excluded: 12 living samples and 138 autopsy samples. The resulting groups were 165 living people, 90 deceased people whose bodies were well preserved, and 22 with heavy putrefaction. The well-preserved bodies had been deeply frozen at approximately −20°C; that body history is distinct from laboratory storage of a collected tube.

Higher group concentrations did not create a diagnostic test

Mean acetaldehyde concentrations were 0.101 ± 0.101 mg/mL in the living group, 0.117 ± 0.093 mg/mL in the well-preserved deceased group and 0.506 ± 0.429 mg/mL in the heavily putrefied group. Values are reported as mean ± standard deviation.

The living and well-preserved deceased groups did not differ significantly (P = 0.062). The well-preserved and heavily putrefied groups did differ significantly. Those findings support an association with specimen or body condition in this selected dataset; they do not establish that acetaldehyde has only one source.

The authors selected 0.14 mg/mL—equivalent to 0.014 g/dL—slightly above the approximately 0.134 mg/mL upper confidence bound reported for the well-preserved group. A confidence interval for a group mean is not a reference interval covering individual people. The paper did not establish sensitivity and specificity for that threshold against independently known amounts of postmortem ethanol.

Why a numerical subtraction is unsupported

The study also incubated 24 blood specimens at 37°C for seven days: six each from ethanol-negative deceased people, ethanol-positive deceased people, ethanol-negative living people and ethanol-positive living people. Acetaldehyde and ethanol changed over time, but attempts to fit a quantitative relationship between them were unsuccessful.

The cross-sectional analysis likewise found no significant correlation between acetaldehyde and ethanol concentrations in the three groups. A high acetaldehyde result therefore cannot be converted into a validated quantity of ethanol to subtract from the reported blood concentration.

Measurement limits and preservation remain relevant

Acetaldehyde, ethanol and n-propanol were measured by dual-column headspace GC–FID. The stated detection and quantification limits for all three were 0.002 and 0.005 mg/mL. Calibration extended from 0.005 to 0.5 mg/mL for acetaldehyde and n-propanol, and to 3.0 mg/mL for ethanol. These are analytical limits, not boundaries separating ingestion from microbial activity.

EtG and EtS were measured separately by LC–MS/MS, with detection and quantification limits of 10 and 15 ng/mL. Their presence can contribute evidence about antemortem exposure, but does not establish that every ethanol molecule in the collected specimen came from drinking.

Use the result as one part of the investigation

The study lacked other-matrix measurements, identification of the microbes involved and complete timing information for every case. Initial concentrations also varied substantially between experimental specimens. Its proposed threshold warrants contextual interpretation, not automatic classification.

Review collection site, body condition, preservation, storage, paired specimens and biomarkers together. The distinction between analytical uncertainty and possible formation is developed in our discussion of ethanol assay uncertainty. Acetaldehyde detection alone establishes neither impairment nor ethanol as a cause of death.

Primary source

Chen X, Dong X, Zhu R, et al. Abnormally High Blood Acetaldehyde Concentrations Suggest Potential Postmortem Ethanol Generation. Journal of Analytical Toxicology. 2021;45:748–755. doi:10.1093/jat/bkaa173.