Back Pain

From molecular mechanisms to digital surveillance: the 2010-2025 evolution of benzodiazepine and Z-drug misuse research.

The misuse of benzodiazepines (BZDs) and Z-drugs poses significant global public health challenges. This study maps the scientific evolution and paradigm shifts in this field from 2010 to 2025. A bibliometric analysis of 6,311 publications from the Web of Science Core Collection was performed using VOSviewer and CiteSpace to identify collaboration networks, research hotspots, and emerging frontier...

Predicting persistent pain after total knee arthroplasty using different machine learning algorithms.

BACKGROUND AND PURPOSE:  After total knee arthroplasty (TKA), 10-20% of patients remain unsatisfied. Well-performing clinical prediction models can provide individualized risk estimates and stratification in terms of poor outcomes, resulting in unnecessary surgeries being avoided and patients being counseled preoperatively. We aimed to create a precise, well-performing prediction model for clinica...

Nanoelectronic Detection of Opioids: Machine Learning-Powered Screening With Carbon Nanotube Field-Effect Transistor Sensor Array.

The development of inexpensive, portable, and rapid opioid screening techniques is urgently needed because of the ongoing opioid crisis in the United ...

Integrating machine learning and pathway modelling to explore factors associated with chronic post-surgical pain and quality of life: a secondary observational analysis of the ENIGMA-II trial.

BACKGROUND: Chronic post-surgical pain (CPSP) is a common long-term complication with multifactorial contributors, and improved risk stratification re...

A Novel Machine Learning Signature Incorporating Lipid and Inflammatory Biomarkers to Predict Pulsed Radiofrequency Efficacy in Zoster-Associated Pain.

INTRODUCTION: Pulsed radiofrequency (PRF) is a pivotal neuromodulation strategy for zoster-associated pain (ZAP); however, clinical outcomes exhibit s...

Fusion prediction model for post-ERCP pancreatitis under NSAIDs prophylaxis.

BACKGROUND: Endoscopic retrograde cholangiopancreatography (ERCP) is a common procedure for treating biliary and pancreatic disorders; however, it is ...

Spontaneous oxycodone withdrawal alters behavior and oligodendrocyte-related gene expression in mice.

Negative affective signs are induced during withdrawal from acute opioid injection and increase in magnitude over repeated injections. Recent evidence...

TRPV1, Endocannabinoid, and Opioid Systems in Analgesia: Molecular Mechanisms and Drug Development Strategies.

Pain modulation relies on complex molecular interactions among ion channels, G protein-coupled receptors, and intracellular signaling cascades. The Tr...

Advances in Ultrasound-Guided Fascial Plane Blocks for Perioperative Acute Pain Management.

INTRODUCTION: Perioperative acute pain remains a major challenge because conventional analgesic strategies are often limited by inadequate efficacy an...

Identifying communities at elevated risk of hepatitis C infection in Los Angeles County: an ecological study using machine learning.

BACKGROUND: Identifying communities disproportionately affected by hepatitis C infection is essential for targeted prevention and resource allocation....

Auricular Point Acupressure Self-Management (APA-SM) program for chronic musculoskeletal pain among rural populations: a protocol for a pragmatic, randomized controlled trial.

INTRODUCTION: Chronic musculoskeletal pain (CMP) is a leading cause of incurred personal healthcare costs and disability in the USA. It disproportiona...

TASC: a time-aware sequence clustering framework with uncertainty quantification for electronic health record trajectories.

Longitudinal electronic health record (EHR) trajectories are highly heterogeneous, sparse, and irregular, making unsupervised temporal pattern discove...

Carfentanil in the illicit drug supply: A machine learning approach for trace detection using surface-enhanced Raman spectroscopy.

BACKGROUND: Carfentanil is an extremely potent synthetic fentanyl analogue often present at trace levels alongside other fentanyl analogues and long-a...

Imaging Primary Chronic Pain Syndromes: Current Evidence, Clinical Relevance, and Advances in MRI and PET/CT.

Primary chronic pain syndromes are increasingly understood through advanced neuroimaging techniques, which reveal consistent structural, functional, a...

Precision pharmacology of CNS GPCRs: From biased signaling to translational therapeutics.

G protein-coupled receptors (GPCRs) represent one of the most extensively targeted receptor families in central nervous system (CNS) pharmacology. Rec...

Impact of COVID-19-related data drift on machine-learning prognostic models predicting 30-day opioid-related emergency department visits, hospitalisation or mortality: a population-level administrative data study in Alberta, Canada.

OBJECTIVE: To develop machine-learning (ML) models during the COVID-19 pandemic and adjacent time periods to evaluate the impact of data drift on mode...

Spectral clustering identifies patterns of chiropractic care in a national longitudinal cohort.

OBJECTIVE: Characterise longitudinal patterns of chiropractic visits for neck pain or low back pain by using machine learning (ML) methods and explain...

Prediction of postoperative desaturation and bradycardia in neonates undergoing laparoscopic inguinal hernia repair: a retrospective cohort study.

BACKGROUND: Ex-premature infants have a high risk of postoperative apnea and bradycardia. This study aimed to develop a predictive model for postopera...

Reader comment regarding machine learning models to detect opioid misuse in emergency department patients at triage.

The authors respond to reader comment regarding machine learning models to detect opioid misuse in emergency department patients at triage.