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Nonnutritional Ergogenic Aids
Published in Luke Bucci, Nutrients as Ergogenic Aids for Sports and Exercise, 2020
Another concern is the identification of naturally-occurring compounds in certain herbs which are not commonly considered as substances banned for athletic competition. Examples include caffeine in guarana, coffee, tea, and “energy” nutritional supplements or ephedrines in Ma Huang (Chinese Ephedra). Consumption of large amounts of dietary supplements containing these herbs may result in a positive drug test when U.S. Olympic Committee (USOC) drug testing methods are used, which then could lead to accidental disbarment at athletic events. While it is difficult to predict accurately just how much of an herbal product will cause illegal levels of banned substances, the following crude guidelines may be used: (1) caffeine — more than five to six cups of fresh-brewed coffee or more than five to six caffeine tablets; (2) ephedrine — any amount of over-the-counter decongestant or herbal product containing Ma Huang (Chinese Ephedra). The ergogenic effects of these compounds found in foodstuffs will be examined later in this section.
Bioequivalence Studies
Published in Nusrat Rabbee, Biomarker Analysis in Clinical Trials with R, 2020
R output $AUClast $AUClast$`Analysis of Variance (log scale)` SS DF MS F p SUBJECT 2.875497e+00 32 8.985928e-02 3.183942248 0.0008742828 GROUP 1.024607e-01 1 1.024607e-01 1.145416548 0.2927731856 SUBJECT(GROUP) 2.773036e+00 31 8.945279e-02 3.169539016 0.0009544080 PERIOD 3.027399e-05 1 3.027399e-05 0.001072684 0.9740824428 DRUG 3.643467e-02 1 3.643467e-02 1.290972690 0.2645764201 ERROR 8.749021e-01 31 2.822265e-02 TOTAL 3.786834e+00 65 $AUClast$`Between and Within Subject Variability` Between Subject Within Subject Variance Estimate 0.03061507 0.02822265 Coefficient of Variation, CV(%) 17.63193968 16.91883011 $AUClast$`Least Square Means (geometric mean)` Reference Drug Test Drug Geometric Means 5092.098 4858.245 $AUClast$`90% Confidence Interval of Geometric Mean Ratio (T/R)` Lower Limit Point Estimate Upper Limit 90% CI for Ratio 0.889436 0.9540753 1.023412 $AUClast$`Sample Size` True Ratio=1 True Ratio=Point Estimate 80% Power Sample Size 6 7
Cannabis for Pets
Published in Betty Wedman-St Louis, Cannabis as Medicine, 2019
Occasionally, pets may ingest cannabis edibles that contain THC, the psychoactive cannabinoid in cannabis, but human urine drug tests are not an effective way to screen a pet for cannabis toxicity. Intoxication in pets is similar to that in humans and starts 30–60 minutes after ingestion. Unfortunately, it may last longer in a cat or dog than a human—up to 18–36 hours after ingestion. The usual signs of intoxication are depression, dilated pupils, vomiting, and possible agitation or excitement. Death from toxicity is not common but tremors and seizures should be assessed by a veterinarian [3].
Blood cannabinoid molar metabolite ratios are superior to blood THC as an indicator of recent cannabis smoking
Published in Clinical Toxicology, 2023
Michael J. Kosnett, Ming Ma, Gregory Dooley, George Sam Wang, Kyle Friedman, Timothy Brown, Thomas K. Henthorn, Ashley Brooks-Russell
These post-incident testing approaches have well-established limitations in their ability to accurately assess either recent cannabis use or cannabis-induced impairment. Acute cannabis-induced decrements in psychomotor or neurocognitive performance, which may occur in some but not all users, typically resolve within 6 h of cannabis smoking or vaping or within 8 h of cannabis ingestion [3]. By comparison, urine drug tests, which rely on the detection of the inactive THC metabolite, 11-nor-9-carboxy-Δ9-tetrahydrocannabinol, may be positive for days to weeks after last cannabis use, particularly in frequent users [4]. Blood concentrations of THC, a highly lipophilic drug that partitions into adipose tissue and equilibrates with the bloodstream, may also remain elevated for days to weeks after the last consumption in daily or near-daily users [5].
Using measured cannabidiol and tetrahydrocannabinol metabolites in urine to differentiate marijuana use from consumption of commercial cannabidiol products
Published in Clinical Toxicology, 2021
Melissa M. Goggin, Gregory C. Janis
At the other extreme, a clustering of metabolic profiles is highly likely to be indicative of CBD use with little or no THC exposure. These samples had a metabolic ratio (CBD/THC) of greater than 10 and comprised 43% of the pain management samples. A majority of these samples possessed undetectable concentrations of THC metabolites (74% of the group). However, the remaining samples falling within this group as defined by the metabolic ratio contained measurable THC metabolites. Twenty-five percent of the samples in this group possessed 11-COOH-THC concentrations in excess of 3 ng/mL; and 10% of them possessed 11-COOH-THC concentrations in excess of 15 ng/mL which is commonly used as a pre-employment confirmation cutoff indicating marijuana use [17]. Thus, these samples would be indicated as marijuana/THC positive in standard urine drug test procedures. Carboxy-THC concentrations within this group reached concentrations as high as 109 ng/mL but within the same sample, the sum of CBD metabolites exceeded 2990 ng/mL.
Tackling deceptive responding during eligibility via content-knowledge questionnaires
Published in The American Journal of Drug and Alcohol Abuse, 2020
Ricardo Marcos Pautassi, Angelina Pilatti
The CKQ showed good internal consistency and, most importantly, the likelihood of positively answering the questions largely and significantly increased as a function of self-reported drug use. Moreover, in the laboratory study, the number of correct responses to the questionnaire was significantly higher in those that tested positive for cannabis in the urine drug test, compared to those that tested negative. It seems, therefore, that the inclusion of knowledge-based questionnaires is a valuable, simple, and economical tool to detect, and therefore reduce, deceptive responding in addiction research. The study adds to prior work (10) indicating that “two-step” procedures are effective to reduce eligibility problems and response inconsistencies. It is important to remark that, to further facilitate the use of CKQ, the authors provide the instrument as supplementary material of the paper, and describe specificity, sensitivity and predictive values for its individual questions and cutoff points.