Poly-Drug Use of Prescription Medicine among People with Opioid Use Disorder in China: A Systematic Review and Meta-Analysis

<p><i>Background</i>: Opioid use disorder (OUD) causes substantial public health and social problems worldwide. Poly-drug use is common in people with OUD and increases morbidity and mortality. Investigation of the patterns and characteristics of poly-drug use of prescription medicine among opioid users is needed to develop appropriate prevention and intervention strategies. <i>Objectives</i>: To estimate the prevalence of poly-drug use of prescription medicine among people with OUD in China using meta-analysis. <i>Methods</i>: We searched relevant epidemiological studies published before February 2017 in English and Chinese databases. The quality of included studies was assessed using the Agency for Healthcare Research and Quality scale. The pooled prevalences of prescription medicine use among people with OUD were estimated. <i>Results</i>: We included 80 eligible studies in the meta-analysis. The main prescription medicines were benzodiazepines (BZDs) and prescription opioid analgesics. The pooled prevalence of unclassified BZDs and prescription opioids was 40.6% and 23.2%, respectively. Diazepam was the most frequently co-used BZD (32.6%), followed by triazolam (32.1%), and estazolam (9.2%). Tramadol was the most commonly used prescription opioid (27.3%), followed by methadone (16.8%), buprenorphine (12.6%), pethidine (8.9%), morphine (6.5%), dihydroetorphine (3.9%), and codeine-containing cough syrup (3.7%). BZDs were mainly used for self-medication (56.1%), whereas prescription opioids were primarily coused for nonmedical purposes (69.4%). <i>Conclusions</i>: The results demonstrate that prescription medicine use is widespread among opioid users in China. There needs to be more consideration of poly-drug use, and early interventions and management strategies are needed to prevent poly-drug use among opioid users in China.</p

sj-docx-1-wso-10.1177_17474930231205221 – Supplemental material for The frequency of imaging markers adjusted for time since symptom onset in intracerebral hemorrhage: A novel predictor for hematoma expansion

Supplemental material, sj-docx-1-wso-10.1177_17474930231205221 for The frequency of imaging markers adjusted for time since symptom onset in intracerebral hemorrhage: A novel predictor for hematoma expansion by Lei Song, Jun Cheng, Cun Zhang, Hang Zhou, Wenmin Guo, Yu Ye, Rujia Wang, Hui Xiong, Ji Zhang, Ren Ke, Dongfang Tang, Yufei Fu, Zhibing He, Liwei Zou, Longsheng Wang, Lianghong Kuang, Xiaoming Qiu, Tingting Guo and Yongqiang Yu in International Journal of Stroke</p

DataSheet_1_Prediction model for the pretreatment evaluation of mortality risk in anti-melanoma differentiation-associated gene 5 antibody-positive dermatomyositis with interstitial lung disease.docx

BackgroundAnti-melanoma differentiation-associated gene 5 antibody-positive dermatomyositis with interstitial lung disease (anti-MDA5 DM-ILD) is a disease with high mortality. We sought to develop an effective and convenient prediction tool to estimate mortality risk in patients with anti-MDA5 DM-ILD and inform clinical decision-making early.MethodsThis prognostic study included Asian patients with anti-MDA5 DM-ILD hospitalized at the Nanjing Drum Hospital from December 2016 to December 2020. Candidate laboratory indicators were retrospectively collected. Patients hospitalized from 2016 to 2018 were used as the discovery cohort and applied to identify the optimal predictive features using a least absolute shrinkage and selection operator (LASSO) logistic regression model. A risk score was determined based on these features and used to construct the mortality risk prediction model in combination with clinical characteristics. Results were verified in a temporal validation comprising patients treated between 2019 and 2020. The primary outcome was mortality risk within one year. The secondary outcome was overall survival. The prediction model’s performance was assessed in terms of discrimination, calibration, and clinical usefulness.ResultsThis study included 127 patients, (72 men [56.7%]; median age, 54 years [interquartile range, 48-63 years], split into discovery (n = 87, 70%) and temporal validation (n=37, 30%) cohorts. Five optimal features were selected by LASSO logistic regression in the discovery cohort (n = 87) and used to construct a risk score, including lymphocyte counts, CD3+CD4+ T-cell counts, cytokeratin 19 fragment (CYFRA21-1), oxygenation index, and anti-Ro52 antibody. The retained predictive variables in the final prediction model were age, Heliotrope, fever, and risk score, and the most predictive factor was the risk score. The prediction model showed good discrimination (AUC: 0.915, 95% CI: 0.846–0.957), good calibration (Hosmer–Lemeshow test, P = 0.506; Brier score, 0.12), and fair clinical usefulness in the discovery cohort. The results were verified among patients in the temporal validation cohort (n = 38). We successfully divided patients into three risk groups with very different mortality rates according to the predictive score in both the discovery and validation cohorts (Cochran-Armitage test for trend, P ConclusionsWe developed and validated a mortality risk prediction tool with good discrimination and calibration for Asian patients with anti-MDA5 DM-ILD. This tool can offer individualized mortality risk estimation and inform clinical decision-making.</p