Literature Collection

Medications such as buprenorphine-naloxone are among the most effective treatments for opioid use disorder, but limited retention in treatment limits long-term outcomes. In this study, we assess the feasibility of a machine learning model to predict retention vs. attrition in medication for opioid use disorder (MOUD) treatment using electronic medical record data including concepts extracted from clinical notes. A logistic regression classifier was trained on 374 MOUD treatments with 68% resulting in potential attrition. On a held-out test set of 157 events, the full model achieved an area under the receiver operating characteristic curve (AUROC) of 0.77 (95% CI: 0.64-0.90) and AUROC of 0.74 (95% CI: 0.62-0.87) with a limited model using only structured EMR data. Risk prediction for opioid MOUD retention vs. attrition is feasible given electronic medical record data, even without necessarily incorporating concepts extracted from clinical notes.

BACKGROUND: The Integrated Care for Older People (ICOPE) approach was developed by the World Health Organization (WHO) aiming to shift the traditional focus of care based on diseases to a function- and person-centered approach, focused on maintaining and monitoring intrinsic capacity (IC). This study aimed to investigate the ability of the ICOPE screening tool to identify older people with clinically meaningful impairments in IC domains. METHODS: This cross-sectional analysis included 603 older adults, participants (mean age 74.7 [SD = 8.8] years, women 59.0%) of the INSPIRE Translational (INSPIRE-T) cohort. Responses at screening were compared to results of the subsequent in-depth assessment (ie, Mini-Mental State Examination, Mini Nutritional Assessment, Short Physical Performance Battery, Patient Health Questionnaire-9, and clinical investigation of vision problems) to determine its predictive capacity for impairments at the IC domains (ie, cognition, psychological, sensory (vision), vitality, and locomotion). RESULTS: The ICOPE screening items provided very high sensitivity for identifying abnormality in vision (97.2%) and varied from 42.0% to 69.6% for the other domains. High specificity (>70%) was observed for all the IC domains, except for vision (2.7%). CONCLUSIONS: The ICOPE screening tool can be a useful instrument enabling the identification of older people with impairments in IC domains, but studies with different populations are needed. It should be considered as a low-cost and simple screening tool in clinical care.

OBJECTIVE:  Our objective was to examine the biomedical and sociodemographic factors associated with the prescription of naloxone among pregnant people with opioid-use disorder (OUD) who were admitted for initiation of medications for OUD (i.e., buprenorphine-containing medications or methadone) following the implementation of a statewide initiative focused on reducing adverse perinatal health outcomes. STUDY DESIGN:  This is a single-site, retrospective cohort study of pregnant people admitted for the management of OUD at an urban, tertiary care center between 2013 and 2020. The primary outcome is evidence of a prescription of naloxone, ascertained from the electronic medical record. Bivariate and multivariable logistic regression modeling was performed to evaluate biomedical and sociodemographic variables associated with a prescription for naloxone. Covariates for inclusion in the multivariate logistic regression model were selected based on a p < 0.05 on bivariate analysis. Statistical significance was set at p < 0.05. RESULTS:  One hundred and thirty-nine participants met the inclusion criteria. On bivariate analysis, people who received naloxone were more likely to be admitted after the initiation of a statewide initiative focused on reducing adverse perinatal outcomes associated with perinatal OUD. Those individuals reporting intravenous drug use (IVDU) were less likely to receive naloxone. On multivariate logistic regression, after controlling for IVDU and epoch of admission, both IVDU (adjusted odds ratio [aOR]: 0.27, 95% confidence interval [CI]: 0.11-0.70) and epoch of admission (aOR: 3.48, 95% CI: 1.28-9.50) were independently associated with receipt of prescription of take-home naloxone. CONCLUSION:  Naloxone prescription was independently associated with the epoch of admission and route of drug administration. These data can be useful in the evaluation and development of clinical practices to increase rates of naloxone prescription in pregnant people with OUD admitted for inpatient management. KEY POINTS: · Thirty four percent of individuals with perinatal OUD were prescribed take-home naloxone (THN).. · Epoch of admission and route of drug administration were independently associated with THN.. · These data can be used to guide public health and clinical programming for pregnant people..