BACKGROUND: Opioid overuse is a costly and significant problem in the United States. Medical specialties including surgery are a contributor to opioid prescriptions while having few clear prescribing guidelines. Machine learning predictive tools can ...
BACKGROUND AND PURPOSE: We aimed to externally validate machine learning models developed in Norway by evaluating their predictive outcome of disability and pain 12 months after lumbar disc herniation surgery in a Swedish and Danish cohort.
British journal of hospital medicine (London, England : 2005)
Jul 4, 2025
The opioid crisis presents a significant burden to patients and healthcare systems. Orthopaedic surgery involves treating patients with significant pain demands, therefore opioid stewardship in this specialty is an important area in targeting the opi...
BACKGROUND: Chronic postoperative inguinal pain (CPIP) is a major complication of inguinal hernia repair and significantly affects patients' quality of life. Despite the widespread use of transabdominal preperitoneal repair (TAPP), CPIP still occurs....
BACKGROUND: Effective management of postoperative pain remains a significant challenge in obstetric care due to the variability in pain perception and response influenced by physical, medical, and psychosocial factors. Current standardized pain manag...
International journal of surgery (London, England)
Apr 3, 2025
BACKGROUND: Early identification of high-risk factors for inadequate analgesia and adverse reactions in obstetric patients is critical for improving outcomes. This study developed a machine learning model to predict these factors and optimize anesthe...
The spine journal : official journal of the North American Spine Society
Mar 28, 2025
BACKGROUND CONTEXT: Anterior cervical discectomy and fusion (ACDF) is widely performed for cervical spine disorders, with opioids commonly prescribed postoperatively for pain management. However, prolonged opioid use carries significant risks such as...
Machine learning (ML) has been extensively utilized to predict complications associated with various diseases. This study aimed to develop ML-based classifiers employing a stacking ensemble strategy to forecast the intensity of postoperative axial pa...
The use of machine learning to predict postoperative pain and opioid use has likely been catalyzed by the availability of complex patient-level data, computational and statistical advancements, the prevalence and impact of chronic postsurgical pain, ...
BACKGROUND: Acute pain management is critical in postoperative care, especially in vulnerable patient populations that may be unable to self-report pain levels effectively. Current methods of pain assessment often rely on subjective patient reports o...
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