Long-Term Opioid Use and Dementia Risk in Patients With Chronic Pain

Predictive Scores for Identifying Chronic Opioid Dependence After General Anesthesia Surgery

Purpose

To address the prevalence and risk factors of postoperative chronic opioid dependence, focusing on the development of a predictive scoring system to identify high-risk populations.

Methods

We analyzed data from the Taiwan Health Insurance Research Database spanning January 2016 to December 2018, encompassing adults undergoing major elective surgeries with general anesthesia. Patient demographics, surgical details, comorbidities, and preoperative medication use were scrutinized. Wu and Zhang's scores, a predictive system, were developed through a stepwise multivariate model, incorporating factors significantly linked to chronic opioid dependence. Internal validation was executed using bootstrap sampling.

Results

Among 111,069 patients, 1.6% developed chronic opioid dependence postoperatively. Significant risk factors included age, gender, surgical type, anesthesia duration, preoperative opioid use, and comorbidities. Wu and Zhang's scores demonstrated good predictive accuracy (AUC=0.83), with risk categories (low, moderate, high) showing varying susceptibility (0.7%, 1.4%, 3.5%, respectively). Internal validation confirmed the model's stability and potential applicability to external populations.

Conclusion

This study provides a comprehensive understanding of postoperative chronic opioid dependence and introduces an effective predictive scoring system. The identified risk factors and risk stratification allow for early detection and targeted interventions, aligning with the broader initiative to enhance patient outcomes, minimize societal burdens, and contribute to the nuanced management of postoperative pain.

Correlates of neurocognitive performance in older adults with chronic pain and negative emotions: baseline data from the problem adaptation therapy for pain (PATH-pain) randomized controlled trial

Chronic pain is highly prevalent among older adults, is associated with cognitive deficits, and is commonly treated in primary care. We sought to document the extent of impairment across specific neurocognitive domains and its correlates among older adults with chronic pain in primary care. We analyzed baseline data from the Problem Adaptation Therapy for Pain trial, which examined a psychosocial intervention to improve emotion regulation in 100 adults ≥ 60 years with comorbid chronic pain and negative emotions, who did not have evidence of moderate-to-severe cognitive impairment. Questionnaires on comorbidities, depressive symptoms, pain intensity, and pain-related disability were administered along with the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and the Montreal Cognitive Assessment (MoCA). Multiple regression assessed the relationship between demographic and clinical characteristics with specific neurocognitive domains. Over half of participants (56%) had mild-to-moderate cognitive impairment (<26 on the MoCA). Across domains, participants scored the lowest in visuospatial/constructional (M = 86.2; SD = 15.7), and 15%-23% scored at least one standard deviation below the mean for immediate and delayed memory, visuospatial/constructional, and attention. In adjusted models, greater medical comorbidities were associated with poorer performance on the total RBANS, immediate memory, and attention. Cognitive deficits in older adults with chronic pain in primary care are substantial, with varying levels of deficits by neurocognitive domain. Future research should examine synergistic effects of chronic pain and comorbidities on cognition, and the impact of cognitive deficits on older adults' ability to engage in pain interventions and self-management behaviors.

Opioids and Dementia in the Danish Population

Importance

Opioids have been studied as a potential risk factor for dementia, but evidence concerning long-term noncancer opioid use and exclusive use of weak opioids and associated dementia risk is sparse.

Objective

To assess the association between cumulative noncancer use of opioids and risk of age-related all-cause dementia.

Design, Setting, and Participants

This nested case-control study within a population-based cohort included 1 872 854 individuals without previous dementia, cancer, opioid addiction, or opioid use in terminal illness. Data were obtained from national Danish registers. Each individual who developed dementia during follow-up was incidence-density matched to 5 dementia-free controls. Statistical analysis was performed from August 2023 to March 2024.

Exposure

Cumulative opioid exposure was based on filled prescriptions available from 1995 through 2020.

Main Outcomes and Measures

Conditional logistic regression provided adjusted incidence rate ratios (IRRs) for associations between opioids and dementia.

Results

Among 1 872 854 individuals without previous dementia, cancer, opioid addiction, or opioid use in terminal illness included in the study, 93 638 (5.0%) developed all-cause dementia during follow-up (51 469 [55.0%] female; median [IQR] age, 78.1 [73.0-82.8] years) and were matched to 468 190 control individuals (257 345 [55.0%] female; median [IQR] age, 78.0 [73.0-82.8] years). Opioid use up to 90 total standardized doses (TSDs) was not consistently associated with dementia risk. Opioid exposure above 90 TSDs yielded increased IRRs of dementia occurring before age 90 years ranging from 1.29 (95% CI, 1.17-1.42) for 91 to 200 TSDs to 1.59 (95% CI, 1.44-1.76) for greater than 500 TSDs for age-band 60 to 69 years at dementia diagnosis. Corresponding IRRs were 1.16 (95% CI, 1.11-1.22) to 1.49 (95% CI, 1.42-1.57) for age-band 70 to 79 years and 1.08 (95% CI, 1.03-1.14) to 1.21 (95% CI, 1.16-1.27) for 80 to 89 years. Sensitivity analyses corroborated associations in individuals with chronic noncancer pain and with use of weak opioids.

Conclusions and Relevance

This study found that opioid use of less than 90 TSDs was not significantly associated with increased dementia risk. Above 90 TSDs of opioid use was associated with an elevated dementia risk before age 90 years, which persisted in individuals with chronic noncancer pain and in individuals solely exposed to weak opioids. Further research should ascertain whether the findings denote causality between opioids and dementia risk.

Tramadol use and incident dementia in older adults with musculoskeletal pain: a population-based retrospective cohort study

We aimed to assess the association of tramadol use with the risk of dementia. This population-based retrospective cohort study using the Korean National Health Insurance Service database included a total of 1,865,827 older adult patients aged 60 years or older with common musculoskeletal pain between January 1, 2003, and December 31, 2007. Individuals who were newly dispensed tramadol (N = 41,963) were identified and propensity score-matched with those who were not (N = 41,963). Over a maximum of 14-year follow-up, the incidence rates (events per 1000 person-years) of all-cause dementia were 6.1 for nonusers, 6.2 for those with cumulative tramadol use of 1-14 days, 7.7 for those with 15-90 days of use, and 8.0 for those with > 90 days of use. Longer cumulative duration of tramadol use was associated with an increased risk of all-cause dementia compared with nonuse (1 to 14 days: aHR 1.06, 95% CI 0.96-1.17; 15 to 90 days: aHR 1.14, 95% CI 1.10-1.35; and more than 90 days: aHR 1.18, 95% CI 1.00-1.39; test for trend: P < 0.001). The results showed a similar pattern for Alzheimer's disease and were robust across subgroup and sensitivity analyses, but not for vascular dementia. This study found that exposure to tramadol was associated with an increased risk of dementia. Taking this potential risk into consideration, clinicians should carefully weigh potential benefits and risks when prescribing tramadol to older adults with musculoskeletal pain.

Association of Regular Opioid Use With Incident Dementia and Neuroimaging Markers of Brain Health in Chronic Pain Patients: Analysis of UK Biobank

OBJECTIVES

We aimed to investigate the association of regular opioid use, compared with non-opioid analgesics, with incident dementia and neuroimaging outcomes among chronic pain patients.

DESIGN

The primary design is a prospective cohort study. To triangulate evidence, we also conducted a nested case-control study analyzing opioid prescriptions and a cross-sectional study analyzing neuroimaging outcomes.

SETTING AND PARTICIPANTS

Dementia-free UK Biobank participants with chronic pain and regular analgesic use.

MEASUREMENTS

Chronic pain status and regular analgesic use were captured using self-reported questionnaires and verbal interviews. Opioid prescription data were obtained from primary care records. Dementia cases were ascertained using primary care, hospital, and death registry records. Propensity score-matched Cox proportional hazards analysis, conditional logistic regression, and linear regression were applied to the data in the prospective cohort, nested case-control, and cross-sectional studies, respectively.

RESULTS

Prospective analyses revealed that regular opioid use, compared with non-opioid analgesics, was associated with an increased dementia risk over the 15-year follow-up (Hazard ratio [HR], 1.18 [95% confidence interval (CI): 1.08-1.30]; Absolute rate difference [ARD], 0.44 [95% CI: 0.19-0.71] per 1000 person-years; Wald χ2 = 3.65; df = 1; p <0.001). The nested case-control study suggested that a higher number of opioid prescriptions was associated with an increased risk of dementia (1 to 5 prescriptions: OR = 1.21, 95% CI: 1.07-1.37, Wald χ2 = 3.02, df = 1, p = 0.003; 6 to 20: OR = 1.27, 95% CI: 1.08-1.50, Wald χ2 = 2.93, df = 1, p = 0.003; more than 20: OR = 1.43, 95% CI: 1.23-1.67, Wald χ2 = 4.57, df = 1, p < 0.001). Finally, neuroimaging analyses revealed that regular opioid use was associated with lower total grey matter and hippocampal volumes, and higher white matter hyperintensities volumes.

CONCLUSION

Regular opioid use in chronic pain patients was associated with an increased risk of dementia and poorer brain health when compared to non-opioid analgesic use. These findings imply a need for re-evaluation of opioid prescription practices for chronic pain patients and, if further evidence supports causality, provide insights into strategies to mitigate the burden of dementia.

Lifetime Psychotropic Medication Use Among Service Members and Veterans With and Without History of Mild Traumatic Brain Injury: A Pilot Study

INTRODUCTION

Military Service Members, Veterans, and other patient populations who experience traumatic brain injury (TBI) may have increased risk of early neurodegenerative diseases relative to those without TBI history. Some evidence suggests that exposure to psychotropic medications may play a role in this association. The Long-term Impact of Military-relevant Brain Injury Consortium-Chronic Effects of Neurotrauma Consortium (LIMBIC-CENC) prospective longitudinal study provides an ideal setting to examine the effects of psychotropic medication exposure on long-term neurological health of those with and without mild TBI history. In this study, we sought to develop and pilot test a self-report electronic survey instrument to measure participants' psychotropic medication histories for use across LIMBIC-CENC study sites.

MATERIALS AND METHODS

We developed a new survey instrument measuring psychotropic medication history and fielded it among Service Members and Veterans enrolled in a single site of the LIMBIC-CENC study to evaluate response rates and patterns, and to compare survey responses to prescription data extracted from participants' Veterans Affair (VA) records. Descriptive statistics estimated survey respondents' lifetime psychotropic medication exposures by their TBI history and other demographic and clinical characteristics of interest. We also compared survey responses to participants' VA outpatient prescription records to estimate sensitivity and negative predictive values (NPVs) for participants' self-reported medication exposures relative to this single prescription data source.

RESULTS

Among 310 Veterans enrolled at the study site, 249 completed the survey (response rate = 80%), of whom 248 also had VA health records and were included in the analysis. Most (69%) had a history of mild TBI. Over three-fourths of survey respondents (78%) reported ever having used prescription opioids, 26% reported benzodiazepines, 50% reported muscle relaxants, 42% reported antidepressants, 13% reported non-benzodiazepine sedative-hypnotics, 15% reported stimulants, 7% reported mood stabilizers, and 6% reported antipsychotics. Veterans with, versus without, a history of mild TBI were more likely to self-report psychotropic medication history as well as have confirmed receipt of VA prescriptions for each medication class. Using VA records as a criterion standard, the sensitivity of the survey for detecting VA prescriptions ranged from 19% to 84%, while the NPVs ranged from 64% to 97%. Sensitivity and NPVs were similar for participants with, versus without, mild TBI history.

CONCLUSIONS

Service Members and Veterans may receive psychotropic medications from multiple sources over their lifetimes. Valid methods to examine and quantify these exposures among those with a history of TBI are important, particularly as we evaluate causes of neurodegenerative disorders in this population over time. The measurement of Veterans' lifetime psychotropic medication exposures using a self-report survey, in combination with health care records, holds promise as a valid approach, but further testing and refinement are needed.

Prediction of conversion from mild cognitive impairment to Alzheimer's disease and simultaneous feature selection and grouping using Medicaid claim data

BACKGROUND

Due to the heterogeneity among patients with Mild Cognitive Impairment (MCI), it is critical to predict their risk of converting to Alzheimer's disease (AD) early using routinely collected real-world data such as the electronic health record data or administrative claim data.

METHODS

The study used MarketScan Multi-State Medicaid data to construct a cohort of MCI patients. Logistic regression with tree-guided lasso regularization (TGL) was proposed to select important features and predict the risk of converting to AD. A subsampling-based technique was used to extract robust groups of predictive features. Predictive models including logistic regression, generalized random forest, and artificial neural network were trained using the extracted features.

RESULTS

The proposed TGL workflow selected feature groups that were robust, highly interpretable, and consistent with existing literature. The predictive models using TGL selected features demonstrated higher prediction accuracy than the models using all features or features selected using other methods.

CONCLUSIONS

The identified feature groups provide insights into the progression from MCI to AD and can potentially improve risk prediction in clinical practice and trial recruitment.

Estimation of cognitive impairment in chronic pain patients and characteristics of estimated mild cognitive impairment

Background

Patients with chronic pain suffer from psychological effects such as anxiety due to the pain itself. Pain can not only impair activities of daily living (ADL) and quality of life (QOL), but also impair cognitive function. Therefore, in this study, we aimed to estimate the cognitive function of chronic pain patients using a deep neural network (DNN) model that has already been implemented in society. We investigated the characteristics of patients presumed to have mild cognitive impairment (MCI) and, at the same time, verified the relationship with the questionnaire commonly used in chronic pain research, which is administered by 43 university affiliated hospitals and medical institutions participating in the chronic pain research group of the Ministry of Health, Labor and Welfare in Japan (assessment batteries).

Method

The study included 114 outpatients from a multidisciplinary pain clinic, and we estimated their Mini-Mental State Examination (MMSE) scores based on age and basic blood test data (23 items). Furthermore, we classified the estimated MMSE scores of chronic pain patients into two groups based on a cutoff score of 27, which indicates MCI, and compared the blood data and assessment batteries. Additionally, we used a control group of 252 healthy adults aged 45 years or older who visited a dementia prevention outpatient clinic for comparison with the MMSE scores of chronic pain patients.

Result

The MMSE scores in chronic pain patients were below the cutoff for MCI. When classified into two groups based on the estimated MMSE score of 27 points, WBC, RBC, Hb, Hct, PLT, UA, BUN, creatinine, Triglyceride, and γ-GT were significantly higher in the blood data. In the MCI group, PDAS values were significantly lower. Furthermore, only in the non-MCI group, a significant correlation was found between the estimated MMSE value and BPI, PDAS, and Locomo. The estimated MMSE scores were significantly lower in chronic pain patients than in healthy adults (p = 0.04).

Conclusion

Patients with chronic pain may exhibit cognitive impairment due to systemic metabolic disturbances. This suggests that chronic pain affects activities of daily living, resulting in systemic metabolic disorders.

Impact of prescribed opioid use on development of dementia among patients with chronic non-cancer pain

We aimed to examine the association between opioid use and the development of dementia in patients with chronic non-cancer pain in South Korea. Data were extracted from the National Health Insurance Service database in South Korea. Adult patients diagnosed with musculoskeletal diseases with chronic non-cancer pain between 2010 and 2015 were included in the analysis. Patients who were prescribed opioids regularly and continuously for ≥ 90 days were classified as opioid users. In total, 1,261,682 patients with chronic non-cancer pain were included in the final analysis, of whom 21,800 (1.7%) were opioid users. From January 1, 2016 to December 31, 2020, 35,239 (2.8%) patients with chronic non-cancer pain were newly diagnosed with dementia. In the multivariable model, opioid users showed a 15% higher risk of developing dementia than the control group. Additionally, opioid users showed a 15% and 16% higher risk of developing Alzheimer's disease and unspecified dementia, respectively, than the control group, but did not show any significant differences for vascular dementia. Among adult patients with chronic non-cancer pain, opioid users were at a higher risk of developing dementia than the control group; the risk was significantly higher for Alzheimer's disease but not for vascular dementia in this study. Our results suggest that in patients with CNCP, public health strategies should target opioid users for early dementia detection and intervention.