Back Pain

Effectiveness of Thoracic Paravertebral Block in Minimally Invasive Vertebroplasty: A Retrospective Cohort Study Focusing on Pain Trajectories and Sagittal Spinal Alignment.

PURPOSE: To evaluate the effectiveness of ultrasound-guided thoracic paravertebral block (TPVB) combined with general anesthesia (GA) versus GA alone in improving postoperative pain trajectories, reducing opioid consumption, and enhancing sagittal spinal alignment in patients undergoing minimally invasive vertebroplasty (MIVP) for osteoporotic vertebral compression fractures. DESIGN: Retrospective...

Spatiotemporal clustering of state-level opioid, opioid-stimulant, and opioid-benzodiazepine polysubstance deaths across the U.S.: Hierarchical agglomerative clustering analysis.

BACKGROUND: Polysubstance use continues to complicate the US overdose landscape, with over 107,000 lives lost to drug overdoses in 2022. The present study uses hierarchical agglomerative clustering to identify distinct spatiotemporal profiles of opioid-only, opioid-stimulant, and opioid-benzodiazepine overdose deaths. METHODS: We used de-identified data sourced from the CDC's WONDER Multiple Cause...

Random forest models accurately classify synthetic opioids using high-dimensionality mass spectrometry datasets.

Detection of novel threat agents presents several challenges, a principle one being the development of untargeted methods to screen an increasing numb...

Neural Network-Based Detection of Adulterants in Opioid Samples Using IR Absorption Spectroscopy.

Community-based drug checking services are challenged in their ability to reliably detect low concentration adulterants that are increasingly present ...

Neurophysiological signatures of rumination's impact on opioid withdrawal severity.

Opioid withdrawal symptoms (OWS) represent a major clinical challenge during abstinence, imposing physiological distress and increasing psychological ...

LLMs show bias in opioid prescribing.

Machine learning models to detect opioid misuse in emergency department patients at triage.

OBJECTIVE: Emergency department (ED) encounters represent valuable opportunities to initiate evidence-based treatments for patients with opioid misuse...

Integrating Clinical Modeling and Machine Learning for Risk Assessment of Paracetamol and Other Nonsteroidal Anti-Inflammatory Drug Hypersensitivity in Children.

BACKGROUND: Nonsteroidal anti-inflammatory drug (NSAID) hypersensitivity is a common cause of drug-related reactions in children. Pre-test risk strati...

Predicting the Course of High-Impact Chronic Pain Using Machine Learning Algorithms.

High-impact chronic pain (HICP) affects over 17 million U.S. adults and follows highly variable courses. To date, the relative importance of biopsycho...

Automated Risk Assessment of Opioid Use: Analysis Using Pre-Trained Transformers on Social Media Data.

BACKGROUND: The illegal use of opioids has emerged as a major global public health concern, contributing to widespread addiction and a growing number ...

Temporal and regional associations between fentanyl concentrations in the unregulated drug supply and drug-related mortality in British Columbia, Canada.

BACKGROUND: British Columbia (BC), Canada, continues to experience persistently high rates of unregulated drug toxicity. While the presence of fentany...

Identifying the 'gray zone': Developing scalable methods to detect opioid misuse in veterans on long-term opioid therapy for pain.

BACKGROUND: Patients prescribed opioids who are at high risk for misuse but don't meet diagnostic criteria for opioid use disorder (OUD) fall into a c...

Chronic Pain Management: From Ancient Healing Practices to Advanced Medical Innovation.

Chronic pain is one of the most prevalent global health issues, significantly impacting physical and psychological health and resulting in reduced qua...

Machine Learning Model Development and Validation in Individuals With Suggestive Hypersensitivity to Nonsteroidal Anti-inflammatory Drugs.

BACKGROUND AND OBJECTIVES: Nonsteroidal anti-inflammatory drugs (NSAIDs) are the main triggers of drug hypersensitivity reactions (HSRs). NSAID-induce...

Development and validation of a fentanyl quantification model for drug checking services.

BACKGROUND: Drug checking services are becoming increasingly popular. Despite the significant variability in fentanyl concentrations observed in the u...

Protocol for Personalised Prediction of Persistent Postsurgical Pain.

INTRODUCTION: Persistent postsurgical pain (PPSP) affects up to 15% of patients after major surgery, impairing physical function, quality of life and ...

Machine Learning Approach to Predict Pain Outcomes Following Primary and Secondary Targeted Muscle Reinnervation in Amputees.

INTRODUCTION: Targeted Muscle Reinnervation (TMR) can prevent and treat neuropathic pain in amputees, but the degree of success varies. This study dev...

Investigation of Bias Using ChatGPT-4 in Pain Management and Patient Profiling.

BACKGROUND: Large language models, such as ChatGPT (cGPT), are being integrated increasingly into clinical workflows and medical education. However, c...

Discussion of Toward Opioid-Free Ambulatory Surgery: A Prospective Study Using Machine Learning to Predict Postoperative Opioid Use.

Neuroimmune Cross-Talk and Multilevel Cascades in Fentanyl Toxicity: Interplay of Hypoxic Stress, Glial Activation, and Synaptic Dysregulation in Systems-Level Neurodegeneration.

Fentanyl, an ultra-potent synthetic opioid, has traditionally been characterized by its acute toxic effects, particularly respiratory depression. Howe...