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News — CHICAGO – Breaking research shows that rates of cannabis use during pregnancy are far higher than previously thought, a finding that could improve efforts to identify pregnant cannabis users and inform them of potential risks. This study will be presented today at ADLM 2024 (formerly the AACC Annual Scientific Meeting & Clinical Lab Expo), along with a second study on a machine learning model that predicts the duration of opioid use after surgery.

Cannabis use during pregnancy

Cannabis is rapidly becoming legalized in more and more states across the U.S. and its recreational use is skyrocketing, but its effects on the developing fetus are not fully understood. Current recommendations advise against cannabis use and exposure during pregnancy due to its association with negative outcomes, such as preterm birth, fetal growth restriction, low birth weight, and developmental deficits.

A research team from NMS Labs led by Dr. Alexandria Reinhart sought to investigate the prevalence of cannabinoid exposure in utero during 2019-2023 by analyzing umbilical cord samples submitted for testing. Of the 90,384 samples tested, 44% were positive for at least one of approximately 60 analytes included in the testing panel, and cannabinoids accounted for 59%-63% of all positive results, making them the most common drug found.

“The sheer amount of cannabinoid positivity we found in comparison to all the drugs that we run on our umbilical cord toxicity testing was pretty astounding,” Dr. Reinhart said.

As the effects of cannabinoids on health continue to be studied, the clinical laboratory should be vigilant in testing for them in pregnant individuals, according to Dr. Reinhart. This, in turn, will enable clinicians to educate these patients about the potential harm that cannabis can do to a fetus.

Predicting duration of opioid use

Hydrocodone is the most commonly prescribed opioid in the U.S. and is often used for pain management following surgery. It is a known potential drug of abuse and can result in dependence and addiction. There is significant variability in patients’ response to hydrocodone therapy, though, including how long after surgery they require the drug to manage their pain.

Dr. Hunter Miller along with colleagues from the University of Louisville and a researcher from ARUP Institute for Clinical and Experimental Pathology, evaluated whether machine learning models could predict postoperative hydrocodone use duration in patients who had undergone orthopedic surgery. They developed two different models — a fast and frugal tree (FFTree) and a second that used an extreme gradient boosting approach (xgBoost) — that incorporated patient demographics, genetic test results, concurrently prescribed medications, and other clinical laboratory test results.

The researchers evaluated the two models by using them to predict the duration of hydrocodone use for 79 patients for whom they already had hydrocodone use duration information. Both models demonstrated good to excellent performance when classifying patients as either “short” or “long” duration users. Specifically, the FFTree model classified patients with 0.80 sensitivity and 0.76 specificity, while the xgBoost model achieved a sensitivity and specificity of 0.87 and 0.63, respectively.

“Currently, when it comes to pain management, most clinicians are kind of just taking a shot in the dark, because they don’t really know how a patient is going to respond to a drug,” Dr. Miller said. In the future, “a physician could theoretically put a patient’s information into the model, estimate a probability for how long a patient is going to be on hydrocodone, and potentially switch them to a different therapeutic strategy if they have a high risk of prolonged use.”   

Session information

ADLM 2024 registration is free for members of the media. Reporters can register online here:

will be presented during:

Scientific poster session

Wednesday, July 31

9:30 a.m. – 5 p.m. (presenting authors in attendance from 1:30 – 2:30 p.m.)

Poster Hall on the Expo show floor

will be presented during the following two sessions:

Session 33109 Academy Distinguished Abstracts: Innovations in bedside-to-bench and back again

Tuesday, July 30

10:30 a.m. – 12 p.m.

Room S504abc

Scientific poster session

Wednesday, July 31

9:30 a.m. – 5 p.m. (presenting authors in attendance from 1:30 – 2:30 p.m.)

Poster Hall on the Expo show floor

All sessions will take place at McCormick Place, Chicago.

About ADLM 2024

ADLM 2024 (formerly the AACC Annual Scientific Meeting & Clinical Lab Expo) offers 5 days packed with opportunities to learn about exciting science from July 28-August 1 in Chicago. Plenary sessions will explore the projected consequences of ending abortion protection, new HIV prevention options, lymphoma biomarkers and therapeutic targets, pharmacogenetic testing in precision health, and the need for clinical trials of laboratory tests.

At the ADLM 2024 Clinical Lab Expo, more than 900 exhibitors will fill the show floor of the McCormick Place Convention Center in Chicago, with displays of the latest diagnostic technology, including but not limited to artificial intelligence, point-of-care, and automation.

About the Association for Diagnostics & Laboratory Medicine (ADLM)

Dedicated to achieving better health through laboratory medicine, ADLM (formerly AACC) brings together more than 70,000 clinical laboratory professionals, physicians, research scientists, and business leaders from around the world focused on clinical chemistry, molecular diagnostics, mass spectrometry, translational medicine, lab management, and other areas of progressing laboratory science. Since 1948, ADLM has worked to advance the common interests of the field, providing programs that advance scientific collaboration, knowledge, expertise, and innovation. For more information, visit .