The Relationship Between Patient Perceived Pain and the Numerical Rating System: A Prospective Validation Using Electronic Health Record Data.

We developed a method of using the Clinically Aligned Pain Assessment (CAPA) measures to reconstruct the Numeric Rating System (NRS). We used an observational retrospective cohort study design with prospective validation using de-identified adult patient data derived from a major health system. Data between 2011-2017 were used for development and 2018-2020 for validation. All included patients had at least one NRS and CAPA measurement at the same time. An ordinal regression model was built with CAPA components to predict NRS scores. We identified 6,414 and 3,543 simultaneous NRS-CAPA pairs in the development and validation dataset, respectively. All CAPA components were significantly related to NRS, with RMSE of 1.938 and Somers' D of 0.803 on the development dataset, and RMSE of 2.1 and Somers' D of 0.74 when prospectively validated. Our model was capable of accurately reconstructing NRS based on CAPA and was exact when the NRS was [0,7].

Psychosocial problems and high amount of opioid administration are associated with opioid dependence and abuse after first exposure for chronic pain patients.

Controversy surrounding the use of opioids for the treatment and the unique characteristics of chronic pain heighten the risks for abuse and dependence; however, it's unclear if higher doses of opioids and first exposure are associated with dependence and abuse. This study aimed to identify patients who developed dependence or opioid abuse after exposed to opioids for the first time and what were the risks factors associated with the outcome. A retrospective observational cohort study analyzed 2,411 patients between 2011 and 2017 who had a diagnosis of chronic pain and received opioids for the first time. A logistic regression model was used to estimate the likelihood of opioid dependence/abuse after the first exposure based on their mental health conditions, prior substance abuse disorders, demographics, and the amount of MME per day patients received. From 2,411 patients, 5.5 % of the patients had a diagnosis of dependence or abuse after the first exposure. Patients who were depressed (OR = 2.09), previous non-opioid substance dependence or abuse (OR = 1.59) or received greater than 50 MME per day (OR = 1.03) showed statistically significant relationship with developing opioid dependence or abuse, while age (OR = -1.03) showed to be a protective factor. Further studies should stratify chronic pain patients into groups who is in higher risk in developing opioid dependence or abuse and develop alternative strategies for pain management and treatments beyond opioids. This study reinforces the psychosocial problems as determinants of opioid dependence or abuse and risk factors, and the need for safer opioid prescribing practices.

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

This study aimed to identify patient characteristics that predict long-term opioid use after an orthopedic or neurosurgery procedure. Long-term opioid use was defined as opioid use for 90 or more days following the surgical procedure. A retrospective analysis was conducted of orthopedic and neurosurgery patients 18 years and older from 01/01/2011 through 12/31/2017 (n = 12,301). Characteristics included age, sex, race, length of hospital stay, body mass index, surgical procedure specialty, presence of opioid use before and after surgery, and opioid use 90 days or more after surgery. A multiple logistic regression model was used to model characteristics predictive of long-term use of opioids. In this cohort, 32.0% of patients had prescriptions for opioids 90 or more days after surgery. Statistically significant risk factors for long-term opioid use were being Caucasian, younger (18-25 years age group) or older than age 45 and being obese. People who were African American or Black, in the 25-45 years age group, underweight, and used opioids before surgery were less likely to use opioids 90 days after surgery. Nurse anesthetist awareness of predictive characteristics of long-term opioid use can lead to alternative options to prevent opioid abuse.