Characterizing Long COVID: Deep Phenotype of a Complex Condition.

BACKGROUND: Numerous publications describe the clinical manifestations of post-acute sequelae of SARS-CoV-2 (PASC or "long COVID"), but they are difficult to integrate because of heterogeneous methods and the lack of a standard for denoting the many phenotypic manifestations. Patient-led studies are of particular importance for understanding the natural history of COVID-19, but integration is hampered because they often use different terms to describe the same symptom or condition. This significant disparity in patient versus clinical characterization motivated the proposed ontological approach to specifying manifestations, which will improve capture and integration of future long COVID studies. METHODS: The Human Phenotype Ontology (HPO) is a widely used standard for exchange and analysis of phenotypic abnormalities in human disease but has not yet been applied to the analysis of COVID-19. FUNDING: We identified 303 articles published before April 29, 2021, curated 59 relevant manuscripts that described clinical manifestations in 81 cohorts three weeks or more following acute COVID-19, and mapped 287 unique clinical findings to HPO terms. We present layperson synonyms and definitions that can be used to link patient self-report questionnaires to standard medical terminology. Long COVID clinical manifestations are not assessed consistently across studies, and most manifestations have been reported with a wide range of synonyms by different authors. Across at least 10 cohorts, authors reported 31 unique clinical features corresponding to HPO terms; the most commonly reported feature was Fatigue (median 45.1%) and the least commonly reported was Nausea (median 3.9%), but the reported percentages varied widely between studies. INTERPRETATION: Translating long COVID manifestations into computable HPO terms will improve analysis, data capture, and classification of long COVID patients. If researchers, clinicians, and patients share a common language, then studies can be compared/pooled more effectively. Furthermore, mapping lay terminology to HPO will help patients assist clinicians and researchers in creating phenotypic characterizations that are computationally accessible, thereby improving the stratification, diagnosis, and treatment of long COVID. FUNDING: U24TR002306; UL1TR001439; P30AG024832; GBMF4552; R01HG010067; UL1TR002535; K23HL128909; UL1TR002389; K99GM145411.

High prevalence of co-occurring substance use in individuals with opioid use disorder.

OBJECTIVE: Funding to address the current opioid epidemic has focused on treatment of opioid use disorder (OUD); however, rates of other substance use disorders (SUDs) remain high and non-opioid related overdoses account for nearly 30% of overdoses. This study assesses the prevalence of co-occurring substance use in West Virginia (WV) to inform treatment strategies. The objective of this study was to assess the prevalence of, and demographic and clinical characteristics (including age, gender, hepatitis C virus (HCV) status) associated with, co-occurring substance use among patients with OUD in WV. METHODS: This retrospective study utilized the West Virginia Clinical and Translation Science Institute Integrated Data Repository, comprised of Electronic Medical Record (EMR) data from West Virginia University Medicine. Deidentified data were extracted from inpatient psychiatric admissions and emergency department (ED) healthcare encounters between 2009 and 2018. Eligible patients were those with OUD who had a positive urine toxicology screen for opioids at the time of their initial encounter with the healthcare system. Extracted data included results of comprehensive urine toxicology testing during the study timeframe. RESULTS: 3,127 patients met the inclusion criteria of whom 72.8% had co-occurring substance use. Of those who were positive for opioids and at least one additional substance, benzodiazepines were the most common co-occurring substances (57.4% of patients yielded a positive urine toxicology screen for both substances), followed by cannabis (53.1%), cocaine (24.5%) and amphetamine (21.6%). Individuals who used co-occurring substances were younger than those who were positive for opioids alone (P < 0.001). There was a higher prevalence of individuals who used co-occurring substances that were HCV positive in comparison to those who used opioids alone (P < 0.001). There were limited gender differences noted between individuals who used co-occurring substances and those who used opioids alone. Among ED admissions who were positive for opioids, 264 were diagnosed with substance toxicity/overdose, 78.4% of whom had co-occurring substance use (benzodiazepines: 65.2%; cannabis: 44.4%; cocaine: 28.5%; amphetamine: 15.5%). Across the 10-year timespan, the greatest increase for the entire sample was in the rate of co-occurring amphetamine and opioid use (from 12.6% in 2014 to 47.8% in 2018). CONCLUSIONS: These data demonstrate that the current substance use epidemic extends well beyond opioids, suggesting that comprehensive SUD prevention and treatment strategies are needed, especially for those substances which do not yet have any evidence-based and/or medication treatments available.