Using natural language processing to identify opioid use disorder in electronic health record data

Background: As opioid prescriptions have risen, there has also been an increase in opioid use disorder (OUD) and its adverse outcomes. Accurate and complete epidemiologic surveillance of OUD, to inform prevention strategies, presents challenges. The objective of this study was to ascertain prevalence of OUD using two methods to identify OUD in electronic health records (EHR): applying natural language processing (NLP) for text mining of unstructured clinical notes and using ICD-10-CM diagnostic codes. Methods: Data were drawn from EHR records for hospital and emergency department patient visits to a large regional academic medical center from 2017 to 2019. International Classification of Disease, 10th Edition, Clinic Modification (ICD-10-CM) discharge codes were extracted for each visit. To develop the rule-based NLP algorithm, a stepwise process was used. First, a small sample of visits from 2017 was used to develop initial dictionaries. Next, EHR corresponding to 30,124 visits from 2018 were used to develop and evaluate the rule-based algorithm. A random sample of the results were manually reviewed to identify and address shortcomings in the algorithm, and to estimate sensitivity and specificity of the two methods of ascertainment. Last, the final algorithm was then applied to 29,212 visits from 2019 to estimate OUD prevalence. Results: While there was substantial overlap in the identified records (n = 1,381 [59.2 %]), overall n = 2,332 unique visits were identified. Of the total unique visits, 430 (18.4 %) were identified only by ICD-10-CM codes, and 521 (22.3 %) were identified only by NLP. The prevalence of visits with evidence of an OUD diagnosis in this sample, ascertained using only ICD-10-CM codes, was 1,811/29,212 (6.1 %). Including the additional 521 visits identified only by NLP, the estimated prevalence of OUD is 2,332/29,212 (7.9 %), an increase of 29.5 % compared to the use of ICD-10-CM codes alone. The estimated sensitivity and specificity of the NLP-based OUD classification were 81.8 % and 97.5 %, respectively, relative to gold-standard manual review by an expert addiction medicine physician. Conclusion: NLP-based algorithms can automate data extraction and identify evidence of opioid use disorder from unstructured electronic healthcare records. The most complete ascertainment of OUD in EHR was combined NLP with ICD-10-CM codes. NLP should be considered for epidemiological studies involving EHR data

Denial of long-term issues with agriculture on tropical peatlands will have devastating consequences

Non peer reviewe

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Síntese de trans-resveratrol e controle de podridão em maçãs com uso de elicitores em pós-colheita Synthesis of trans-resveratrol and rotting control in apples with use of elicitors in post-harvest

O objetivo deste trabalho foi avaliar o efeito da aplicação de elicitores abióticos na biossíntese de resveratrol e na indução de resistência à podridão póscolheita de maçãs 'Gala' e 'Fuji'. Foram realizados os tratamentos: radiação ultravioleta, fosfito e acibenzolar-Smetil - aplicados antes do armazenamento - e ozônio - aplicado intermitente durante o armazenamento. As condições de armazenamento foram: 'Gala', 1,5 kPa de O2 e 2,5 kPa de CO2, a 0,5±0,1ºC, por oito meses, e 'Fuji', 1,0 kPa de O2 e <0,5 kPa de CO2, a 0,5±0,1ºC, por sete meses. O delineamento experimental foi inteiramente ao acaso, com oito repetições de 25 frutos. Na casca dos frutos, determinou-se: trans-resveratrol, polifenóis totais, antocianinas totais e diâmetro de lesão, após inoculação de Penicillium sp. no ferimento. Analisou-se na polpa: firmeza de polpa, acidez titulável, sólidos solúveis totais, açúcares redutores e nãoredutores. Os elicitores não alteram a concentração de polifenóis totais e antocianinas, com exceção do acibenzolar-Smetil que reduz o conteúdo de antocianinas na maçã 'Gala'. Os elicitores induzem, na 'Fuji', mas não na maçã 'Gala', a síntese de trans-resveratrol na seqüência: acibenzolar-Smetil> fosfito> irradiação UV-C> ozônio. Na maçã 'Gala', o fosfito reduz a ocorrência de podridão, porém, em ambas as cultivares, não há correlação entre síntese de trans-resveratrol e controle de podridão.<br>The objective of this study was evaluate the effect of the application of abiotic elicitors of resveratrol in 'Gala' and 'Fuji' apples, and rotting control. The treatment was with ultraviolet irradiation, phosphite and acibenzolar-Smethyl, applied before controlled atmosphere storage and ozone, applied so intermittently during storage. The storage conditions were: 'Gala' (1.5 kPa O2 and 2.5 kPa CO2, at 0.5±0.1°C by eight months) and 'Fuji' (1.0 kPa O2 and <0.5 kPa CO2, at 0.5±0.1°C for seven months). The experimental design was a completely randomized with eight repetitions of 25 fruits. In the skin of fruit trans-resveratrol were analyzed by high performance liquid chromatography; total polyphenols and anthocyanins by spectrophotometry and diameter of injury after inoculation by Penicillium sp. Firmness, acidity, total soluble solids, and reducing and nonreducing sugars were analyzed in the flesh. The elicitores do not change the concentration of phenols and anthocyanins, with the exception of the loss of total anthocyanins with acibenzolar-Smethyl in 'Gala' apple. The elicitors induce in 'Fuji' apples the synthesis of trans-resveratrol in the sequence: acibenzolar-Smethyl>phosphite>UV-C irradiation>ozone. There isn't correlation between synthesis of trans-resveratrol and rotting control, but the phosphite controlled rot in 'Gala'