Back Pain

Tegmental kappa-opioid receptor neurons modulate opioid withdrawal via the periaqueductal gray.

Opioid withdrawal is a common and distressing manifestation of opioid dependence which, if left untreated, frequently results in relapse, accidental overdose, and suicide. While much is known about the role of mesolimbic and mesocortical dopaminergic neurons in mu opioid receptor-mediated reward, much less is understood about the impact of chronic opioid use on parallel aversive pathways mediated ...

Performance of Machine Learning Models in Predicting Outcomes After ACDF: A Systematic Review and Meta-Analysis of 443 000 Patients.

Study DesignSystematic review and meta-analysis.ObjectiveDirect head-to-head comparison of machine learning models aiming to predict outcomes in Anterior Cervical Discectomy and Fusion (ACDF) is necessary because existing studies typically evaluate algorithms in isolation, using heterogeneous datasets, features, and performance metrics, which limits interpretability and prevents meaningful compari...

Machine Learning Prediction of Pharmacogenetic Testing Uptake Among Opioid-Prescribed Patients Using Electronic Health Records: Retrospective Cohort Study.

BACKGROUND: Opioids are a widely prescribed class of medication for pain management. However, they have variable efficacy and adverse effects among pa...

Development of prediction models for perioperative opioid needs in laparoscopic cholecystectomy patients: A machine-learning approach.

BACKGROUND: Changes in opioid prescribing practices have evolved, including perioperative settings. However, computerized clinical decision support sy...

Nalmefene and naltrexone reduce alcohol intake via selective efficacy in subpopulations distinguished by behavioral and blood-based biomarkers.

BACKGROUND: The relative efficacies of nalmefene versus naltrexone for alcohol use disorder is the subject of intense and ongoing debate. The two pan-...

Elucidating hydrogen bonding and synergistic adsorption mechanisms of morphine on deep eutectic solvent-functionalized biochar through machine learning and density functional theory.

Adsorbent materials effectively separated psychoactive substances from the ambient medium through adsorption, serving as a sustainable removal strateg...

Integrated metabolomics and transcriptomics reveal biomarkers for detecting fentanyl analog abuse through machine learning.

Fentanyl analogs' (FA) rampant proliferation causes widespread abuse, fatalities, and severe social issues globally. Their high toxicity, rapid metabo...

Literature-informed ensemble machine learning for three-year diabetic kidney disease risk prediction in type 2 diabetes: Development, validation, and deployment of the PSMMC NephraRisk model.

INTRODUCTION: Diabetic kidney disease (DKD) and diabetic nephropathy (DN) affect around 40% of diabetic patients but lack accurate risk prediction too...

Artificial intelligence and machine learning applications in ambulatory surgery - A systematic review.

BACKGROUND: We aimed to systematically review applications of artificial intelligence (AI) technologies for ambulatory surgical patients. METHODS: We ...

Integrating administrative health data and machine learning to predict ALS onset.

BACKGROUND: This study aims to develop a Machine Learning (ML) model to predict the initial diagnosis of Amyotrophic Lateral Sclerosis (ALS). METHODS:...

Applying machine learning in predicting medication treatment outcomes for opioid use disorder.

BACKGROUND: While medication for opioid use disorder (MOUD) is effective for a significant proportion of patients, many return to using opioids during...

Pharmacoepidemiologic characterization of cannabis use and symptomatology in rheumatology using natural language processing of electronic health record clinic notes.

Up to 70% of patients with autoimmune rheumatic diseases (ARDs), including rheumatoid arthritis, psoriatic arthritis, and systemic lupus erythematosus...

Design and optimization of indomethacin-loaded solid dispersion orally dissolving films: Machine learning and molecular dynamics study.

Indomethacin (IND) is a nonsteroidal anti-inflammatory drug (NSAID) with anti-inflammatory, analgesic, and antipyretic properties, and is widely used ...

Multidimensional quantification of pain responses using novel rat pain scale reveals the absence of opioid induced hyperalgesia following chronic contingent and non-contingent morphine exposure in rats.

Opioids are often prescribed to treat chronic and post-operative pain, but there is data to suggest that opioid exposure can lead to hyperalgesia or a...

Robotic thoracic surgery: what is different in anesthesia?

PURPOSE OF REVIEW: Robotic-assisted thoracic surgery (RATS) has emerged as a transformative approach in thoracic surgery, enabling enhanced precision ...

A novel machine learning-based method to quantify the effect of transcranial direct current stimulation on opioid users.

BACKGROUND: Opioid addiction is a major public health concern, associated with numerous health and social problems. Conventional diagnostic methods fo...

Prediction of Response to Spinal Cord Stimulation Using Machine Learning Based on Radiomics and Patient-Reported Outcomes.

BACKGROUND AND OBJECTIVES: Chronic pain affects more patients than cancer, diabetes, and heart disease combined, resulting in high morbidity and signi...

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

BACKGROUND: The opioid crisis poses a significant health challenge in the United States, with increasing overdoses and death rates due to opioids mixe...

Patterns in Mental Health Symptoms, Substance Use, and Viral Suppression in People with HIV: A Clustering Analysis.

Mental health conditions and substance use are prevalent among people with HIV (PWH), are correlated with one another, and associate with viral non-su...

The future of target-controlled infusion and new pharmacokinetic models.

PURPOSE OF REVIEW: To summarize recent developments in the understanding of the pharmacology of the hypnotic and opioid drugs, with relevance to targe...