AIMC Topic: Analgesics, Opioid

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Support Vector Machine Classification of Adulterated Illicit Opioids Using Paper-Spray Mass Spectrometry.

Analytical chemistry
The complexity and potency of the illicit opioid supply in North America has become increasingly concerning for people who use drugs. Drug checking efforts aim to keep up with the evolving psychoactive components present in the illicit drug supply. W...

Leading predictors and their associations with combination opioid pain therapy in older adults with cancer: Application of machine learning approaches.

PloS one
Combined use of opioids and other pharmacological therapies used for pain management, such as non-steroidal anti-inflammatory drugs (NSAIDs), benzodiazepines, gabapentinoids, and/or skeletal muscle relaxants (SMRs), in older adult cancer survivors ca...

Explainable machine learning to predict prolonged post-operative opioid use in rotator cuff patients.

BMC musculoskeletal disorders
BACKGROUND: Opioid overuse is a costly and significant problem in the United States. Medical specialties including surgery are a contributor to opioid prescriptions while having few clear prescribing guidelines. Machine learning predictive tools can ...

Monitoring Opioid-Related Social Media Chatter Using Natural Language Processing and Large Language Models: Temporal Analysis.

JMIR infodemiology
BACKGROUND: Opioid overdose is a global public health emergency, with the United States experiencing high rates of morbidity and mortality due to prescription and illicit opioid use. Traditional public health monitoring systems often fail to provide ...

Development and In Vivo evaluation of liposomal fentanyl nanocarriers using thin-film hydration and AI-based characterization for enhanced analgesic efficacy in anesthesia.

Scientific reports
The aim of this study was to develop and evaluate a liposomal formulation of fentanyl to improve its analgesic efficacy and safety profile in anesthesia, using artificial intelligence (AI) techniques to characterize and optimize the formulation. The ...

Relative importance of socioecological domains to predicting opioid-involved mortality.

PloS one
BACKGROUND: The opioid crisis in the United States is a complex issue with interconnected factors that lead to opioid misuse and opioid-involved mortality. This study assessed the relative importance of different risk factor domains in predicting fat...

Mitigating Opioid Dependence in Orthopaedic Surgery: Current Strategies and Future Directions.

British journal of hospital medicine (London, England : 2005)
The opioid crisis presents a significant burden to patients and healthcare systems. Orthopaedic surgery involves treating patients with significant pain demands, therefore opioid stewardship in this specialty is an important area in targeting the opi...

Sentiment Analysis Using a Large Language Model-Based Approach to Detect Opioids Mixed With Other Substances Via Social Media: Method Development and Validation.

JMIR infodemiology
BACKGROUND: The opioid crisis poses a significant health challenge in the United States, with increasing overdoses and death rates due to opioids mixed with other illicit substances. Various strategies have been developed by federal and local governm...

Population-level individualized prospective prediction of opioid overdose using machine learning.

Molecular psychiatry
The opioid overdose epidemic has rapidly expanded in North America, with rates accelerating during the COVID-19 pandemic. No existing study has demonstrated prospective opioid overdose at a population level. This study aimed to develop and validate a...