Back Pain

Prediction of sustained opioid use in children and adolescents using machine learning.

BACKGROUND: Opioid misuse in the paediatric population is understudied. This study aimed to develop a machine learning classifier to differentiate between occasional and sustained opioid users among children and adolescents in outpatient settings.

Opioid Nonadherence Risk Prediction of Patients with Cancer-Related Pain Based on Five Machine Learning Algorithms.

OBJECTIVES: Opioid nonadherence represents a significant barrier to cancer pain treatment efficacy. However, there is currently no effective prediction method for opioid adherence in patients with cancer pain. We aimed to develop and validate a machine learning (ML) model and evaluate its feasibility to predict opioid nonadherence in patients with cancer pain.

Deep learning predicts postoperative opioids refills in a multi-institutional cohort of surgical patients.

BACKGROUND: To combat the opioid epidemic, several strategies were implemented to limit the unnecessary prescription of opioids in the postoperative p...

Machine Learning-Driven Analysis of Individualized Treatment Effects Comparing Buprenorphine and Naltrexone in Opioid Use Disorder Relapse Prevention.

OBJECTIVE: A trial comparing extended-release naltrexone and sublingual buprenorphine-naloxone demonstrated higher relapse rates in individuals random...

Prediction of naloxone dose in opioids toxicity based on machine learning techniques (artificial intelligence).

BACKGROUND: Treatment management for opioid poisoning is critical and, at the same time, requires specialized knowledge and skills. This study was des...

Machine learning identifies risk factors associated with long-term opioid use in fibromyalgia patients newly initiated on an opioid.

OBJECTIVES: Fibromyalgia is frequently treated with opioids due to limited therapeutic options. Long-term opioid use is associated with several advers...

Predicting Postoperative Pain and Opioid Use with Machine Learning Applied to Longitudinal Electronic Health Record and Wearable Data.

BACKGROUND:  Managing acute postoperative pain and minimizing chronic opioid use are crucial for patient recovery and long-term well-being.

Fetal bladder rupture after high-dose maternal opioid treatment: a case report.

OBJECTIVES: Fetal bladder rupture is rare and mainly caused by lower urinary tract obstruction (LUTO). Our case report describes a rupture at a gestat...

Machine Learning Discrimination and Ultrasensitive Detection of Fentanyl Using Gold Nanoparticle-Decorated Carbon Nanotube-Based Field-Effect Transistor Sensors.

The opioid overdose crisis is a global health challenge. Fentanyl, an exceedingly potent synthetic opioid, has emerged as a leading contributor to the...

An explainable machine learning framework for predicting the risk of buprenorphine treatment discontinuation for opioid use disorder among commercially insured individuals.

OBJECTIVES: Buprenorphine is an effective evidence-based medication for opioid use disorder (OUD). Yet premature discontinuation undermines treatment ...

Robot-assisted laparoscopic nephrectomy: early outcome measures with the implementation of multimodal analgesia and intrathecal morphine via the acute pain service.

PURPOSE: The objective of this study was to perform a retrospective cohort analysis, in which we measured the association of an acute pain service (AP...

Improving the quality of counseling and clinical supervision in opioid treatment programs: how can technology help?

BACKGROUND: The opioid epidemic has resulted in expanded substance use treatment services and strained the clinical workforce serving people with opio...

Optimizing methadone dose adjustment in patients with opioid use disorder.

INTRODUCTION: Opioid use disorder is a cause for concern globally. This study aimed to optimize methadone dose adjustments using mixed modeling and ma...

Evaluation of Gabapentin and Pregabalin Use in Hospitalized Patients With Decreased Kidney Function.

Gabapentin and pregabalin are well-tolerated medications primarily cleared by the kidney. Patients receiving higher gabapentinoid doses with decrease...

Enhancing Opioid Bioactivity Predictions through Integration of Ligand-Based and Structure-Based Drug Discovery Strategies with Transfer and Deep Learning Techniques.

The opioid epidemic has cast a shadow over public health, necessitating immediate action to address its devastating consequences. To effectively comba...

Stauntonia chinensis injection relieves neuropathic pain by increasing the expression of PSD-95 and reducing the proliferation of phagocytic microglia.

Neuroinflammation induced by engulfment of synapses by phagocytic microglia plays a crucial role in neuropathic pain. Stauntonia chinensis is extracte...

Robotic retroperitoneal lymph node dissection for paratesticular rhabdomyosarcoma in adolescents: a case series.

Robotic assisted (RA) retroperitoneal lymph node dissection (RPLND) has grown in popularity as it offers decreased morbidity and faster recovery compa...

Outcome prediction of methadone poisoning in the United States: implications of machine learning in the National Poison Data System (NPDS).

Methadone is an opioid receptor agonist with a high potential for abuse. The current study aimed to compare different machine learning models to predi...

Predicting Persistent Opioid Use after Hand Surgery: A Machine Learning Approach.

BACKGROUND: The aim of this study was to evaluate the use of machine learning to predict persistent opioid use after hand surgery.

Machine Learning Algorithms Predict Long-Term Postoperative Opioid Misuse: A Systematic Review.

INTRODUCTION: A steadily rising opioid pandemic has left the US suffering significant social, economic, and health crises. Machine learning (ML) domai...