A Predictive Model for Developing Long Term Opioid Use After Neurosurgery and Orthopedic Surgery

Area of Science:

• Medical research
• Surgical outcomes
• Pain management

Background:

• Post-surgical pain management often involves opioid prescriptions.
• Identifying predictors of long-term opioid use is essential for preventing opioid abuse.
• Orthopedic and neurosurgery patients represent a significant cohort for opioid use studies.

Purpose of the Study:

• To identify patient characteristics predicting long-term opioid use (≥90 days) after orthopedic or neurosurgery.
• To inform clinical practice and develop strategies for opioid abuse prevention.
• To analyze demographic and clinical factors associated with prolonged postoperative opioid consumption.

Main Methods:

• Retrospective analysis of 12,301 orthopedic and neurosurgery patients (≥18 years) from 2011-2017.
• Utilized multiple logistic regression to model predictors of long-term opioid use.
• Examined variables including age, sex, race, BMI, hospital stay, and pre-existing opioid use.

Main Results:

• 32.0% of patients experienced long-term opioid use post-surgery.
• Predictive factors for long-term opioid use included Caucasian race, age groups 18-25 and >45, and obesity.
• African American/Black race, age 25-45, underweight status, and prior opioid use were associated with decreased long-term use.

Conclusions:

• Specific patient characteristics significantly predict long-term opioid use after surgery.
• Awareness of these predictors can guide interventions to mitigate opioid abuse risk.
• Targeted strategies are needed for vulnerable patient groups to optimize pain management and reduce long-term opioid dependence.