AIMC Topic: Analgesics, Opioid

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How prevalent and severe is addiction on GABAmimetic drugs in an elderly German general hospital population? Focus on gabapentinoids, benzodiazepines, and z-hypnotic drugs.

Human psychopharmacology
OBJECTIVE: Gabapentinoids (GPT) are reported to be increasingly misused by opioid- and polydrug-users, but the addictive potential of GPT outside of these populations remains understudied. Investigations comparing GPT abuse and dependence liability t...

Single- versus multi-port robotic partial nephrectomy: a comparative analysis of perioperative outcomes and analgesic requirements.

Journal of robotic surgery
Evidence supporting the safe use of the single-port (SP) robot for partial nephrectomy is scarce. The purpose of this study was to compare perioperative outcomes for patients undergoing robotic assisted SP vs multi-port (MP) partial nephrectomy (PN) ...

Intraoperative multimodal analgesic bundle containing dexmedetomidine and ketorolac may improve analgesia after robot-assisted prostatectomy in patients receiving rectus sheath blocks.

Asian journal of surgery
BACKGROUND: Minimally invasive robot-assisted laparoscopic radical prostatectomy (RALP) has replaced open prostatectomy. However, RALP does not reduce postoperative pain compared to the open approach. We explored whether bundled intraoperative intrav...

Predicting postoperative opioid use with machine learning and insurance claims in opioid-naïve patients.

American journal of surgery
BACKGROUND: The clinical impact of postoperative opioid use requires accurate prediction strategies to identify at-risk patients. We utilize preoperative claims data to predict postoperative opioid refill and new persistent use in opioid-naïve patien...

Integrating human services and criminal justice data with claims data to predict risk of opioid overdose among Medicaid beneficiaries: A machine-learning approach.

PloS one
Health system data incompletely capture the social risk factors for drug overdose. This study aimed to improve the accuracy of a machine-learning algorithm to predict opioid overdose risk by integrating human services and criminal justice data with h...

Predicting opioid overdose risk of patients with opioid prescriptions using electronic health records based on temporal deep learning.

Journal of biomedical informatics
The US is experiencing an opioid epidemic, and opioid overdose is causing more than 100 deaths per day. Early identification of patients at high risk of Opioid Overdose (OD) can help to make targeted preventative interventions. We aim to build a deep...

Machine learning algorithms to predict seizure due to acute tramadol poisoning.

Human & experimental toxicology
INTRODUCTION: This study was designed to develop and evaluate machine learning algorithms for predicting seizure due to acute tramadol poisoning, identifying high-risk patients and facilitating appropriate clinical decision-making.