A contingency management approach for treatment of methamphetamine use disorder and human immunodeficiency virus antiretroviral treatment adherence in pregnancy to prevent mother-to-child transmission: a case report
Bibliographic record
Abstract
INTRODUCTION: This review highlights the rising prevalence of methamphetamine use in pregnancy in North American and the difficulty of managing active human immunodeficiency virus infection in a pregnant woman while actively using methamphetamines. Multidisciplinary medical teams with knowledge of addiction medicine, infectious disease management, and pregnancy are needed to provide combined expert care to reduce the harms associated with substance use and improve adherence to antiretroviral treatment. We report the case of a treatment-naïve pregnant patient with human immunodeficiency virus who was actively using methamphetamines. The patient was able to initiate and adhere to antiretroviral treatment while taking a prescription stimulant in a contingency management paradigm. To the best of our knowledge, this is the first documented case of prescription stimulants being used in pregnancy to improve adherence to antiretroviral medications. CASE PRESENTATION: A 32-year-old white woman with untreated human immunodeficiency virus, a newly diagnosed pregnancy, and actively using methamphetamines presented to a drop-in combined prenatal care and addiction medicine clinic. After initiating a prescription amphetamine in a contingency management paradigm, she was adherent to human immunodeficiency antiretroviral treatment and had a fully suppressed viral load throughout the remainder of her pregnancy. CONCLUSION: Active treatment of methamphetamine use disorders with prescription stimulants, coupled with contingency management, may represent a mechanism to engage patients in care and improve adherence to antiretroviral treatment (and prevent mother-to-child-transmission of human immunodeficiency virus).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".