Back Pain

Development and mixed-methods evaluation of the Prehabilitation for Facial Feminization Surgery (PREFACE) Program.

BACKGROUND: To strengthen preoperative preparation and improve clinical outcomes, a multimedia prehabilitation program was created for patients undergoing facial feminization surgery (FFS). This study evaluates the program and its impact on clinical outcomes. METHODS: PREFACE includes five video modules, a guidebook, and a mobile application covering surgical information, preoperative preparation,...

Machine Learning Prediction and Reducing Overdoses With Electronic Health Record Nudges (mPROVEN) in the Primary Care Setting: Protocol for a Cluster Randomized Controlled Trial.

BACKGROUND: Opioid overdose remains a leading cause of preventable death in the United States. Existing approaches to identify individuals at elevated risk rely on imprecise rule-based criteria that misclassify patients' risk of this serious health outcome. Machine learning (ML) algorithms can help improve prediction performance and can be combined with electronic health record (EHR) interventions...

Interpretable LightGBM model for predicting postoperative gastrointestinal hemorrhage in elderly hip fracture patients: leveraging systemic inflammation and medication exposures for personalized risk stratification.

BACKGROUND: Postoperative gastrointestinal (GI) bleeding is a serious complication after hip fracture surgery in older adults, yet perioperative risk ...

Development and Internal Validation of a Machine Learning Model for Predicting Long-Term Opioid Therapy After Hip Fracture Surgery in Older, Opioid-Naïve Adults.

BACKGROUND: Long-term opioid therapy (LTOT) after hip fracture surgery is a common postoperative complication associated with adverse outcomes, yet to...

A prospective multimethod investigation of cancer-related pain integrating clinical data and machine learning: results from the RUGGI Study.

BACKGROUND: Cancer-related pain is a multidimensional phenomenon, and key determinants of pain intensity remain unclear. The aim of this study was to ...

Single-molecule localization and diffusivity microscopy reveals dynamic biomolecular organization in living cells.

Single-molecule tracking in living cells measures protein diffusivity but requires sparse imaging, limiting high-density mapping. Here we introduce si...

Evaluation and enhancement of suspected opioid overdose definitions in emergency medical services data using machine learning with natural language processing.

BACKGROUND: Fatal and non-fatal drug overdoses have evolved into a critical public health crisis, with over a 50% increase in the rate of fatal drug o...

AI-driven quantum chemical exploration of multi-target synthetic opioid analogs for enhanced therapeutic profiles.

In silico metabolite prediction and LC-HRMS confirmation for forensic analysis of a fatal case involving novel synthetic opioid N, N-dimethyl etonitazene.

Nitazenes are a class of new psychoactive substances (NPS) belonging to the synthetic opioids. It has potent μ-opioid receptor agonist activity. In th...

Addressing diagnostic code variability in intimate partner violence surveillance through natural language processing: Evidence from substance use disorder populations.

BACKGROUND: Intimate partner violence (IPV) and substance use disorders (SUDs) represent major public health challenges, yet identifying IPV cases in ...

Personalizing treatment of pancreatitis-associated chronic pain: the need for an integrated omics approach.

BACKGROUND: Chronic pancreatitis (CP) is a progressive inflammatory disorder characterized by debilitating chronic pain and substantial healthcare bur...

Classification and stratification of patient pain archetypes following total knee arthroplasty: a machine learning approach.

BACKGROUND: Up to 20% of total knee arthroplasty (TKA) patients experience significant postoperative pain that delays recovery and increases risk of c...

[Comparative observation of analgesic efficacy between liposomal bupivacaine and "cocktail" therapy following artificial intelligence-assisted direct anterior approach total hip arthroplasty: A prospective randomized controlled study].

OBJECTIVE: To compare the analgesic efficacy and safety of liposomal bupivacaine (LB) versus ropivacaine for surgical incision local anesthesia after ...

Identifying demographic predictors of increased non-fatal opioid overdose risk among New York State Medicaid enrollees following the COVID-19 pandemic: an analysis of heterogeneous treatment effects.

BACKGROUND: Overdose rates in the U.S. rose dramatically during the COVID-19 pandemic. Well-documented racial and sociodemographic inequities in the i...

Prediction of Relapse Using Digital Technology in People in Recovery From Substance Use Disorders: Early Economic Evaluation With a Case Study of the Subreal App.

BACKGROUND: Many people relapse after achieving abstinence in substance use disorders. Health care providers may scan the horizon for new technologies...

The impact of regional block presence on large language model-based postoperative analgesia recommendations in abdominal surgery: a comparative study using real-world patient data.

BACKGROUND: Postoperative pain management is a core component of anesthesiology practice, with regional anesthesia playing a key role in multimodal an...

Subgroup identification of disparities in buprenorphine discontinuation in opioid-use disorder: A Virtual Twins machine learning approach using nationwide United States claims data, 2006-2022.

Buprenorphine retention is crucial for effective treatment of opioid use disorder (OUD), yet disparities in treatment discontinuation persist. This st...

AI-derived therapeutic development of a serotonin receptor-targeting drug for the treatment of opioid use disorder.

The opioid epidemic has led to a devastating loss of life nationwide. Of those dependent on opioids, many individuals desire to quit or reduce use, bu...

Examining Ethnic and Racial Variations in Opioid-related Hospitalizations Using Western U.S. Electronic Health Records.

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

BACKGROUND: Postoperative opioid use has the risk of dependence and diversion. We developed an opioid-sparing regimen and identified factors associate...