Automatic identification of methotrexate-induced liver toxicity in patients with rheumatoid arthritis from the electronic medical record

Lin, Chen; Karlson, Elizabeth W.; Dligach, Dmitriy; Ramirez, Monica P.; Miller, Timothy A.; Mo, Huan; Braggs, Natalie S.; Cagan, Andrew; Gainer, Vivian S.; Denny, Joshua C.; Savova, Guergana

doi:10.1136/amiajnl-2014-002642

Cited by 64 publications

(55 citation statements)

References 27 publications

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“…Studies from Asia or Australia were published in more recent years. Majority of the studies included adult populations (62%), two studies (7%) included children aged 18 years and below, eight studies (28%) included a mixed adult and children population, while age limit was not reported in one study . Apart from two prospective studies with shorter study periods, the rest of the studies were conducted retrospectively.…”

Section: Resultsmentioning

confidence: 99%

Systematic review and meta‐analysis of algorithms used to identify drug‐induced liver injury (DILI) in health record databases

Tan

Low

Dan

et al. 2017

Liver International

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Section: Resultsmentioning

confidence: 99%

Systematic review and meta‐analysis of algorithms used to identify drug‐induced liver injury (DILI) in health record databases

Tan

Low

Dan

et al. 2017

Liver International

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“…Second, as per our motivating use cases, we are working to integrate this annotation data with timeline visualization tools and to use these annotations in quality-of-care research. For example, we are using temporal reasoning built on this work to investigate the liver toxicity of methotrexate across a large corpus of EHRs (Lin et al, under review)]. Finally, we plan to explore the application of our notion of an event (anything that should be visible on a domain-appropriate timeline) to other domains.…”

Section: Discussionmentioning

confidence: 99%

Temporal Annotation in the Clinical Domain

Styler¹,

Bethard

Finan

et al. 2014

TACL

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149

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This article discusses the requirements of a formal specification for the annotation of temporal information in clinical narratives. We discuss the implementation and extension of ISO-TimeML for annotating a corpus of clinical notes, known as the THYME corpus. To reflect the information task and the heavily inference-based reasoning demands in the domain, a new annotation guideline has been developed, “the THYME Guidelines to ISO-TimeML (THYME-TimeML)”. To clarify what relations merit annotation, we distinguish between linguistically-derived and inferentially-derived temporal orderings in the text. We also apply a top performing TempEval 2013 system against this new resource to measure the difficulty of adapting systems to the clinical domain. The corpus is available to the community and has been proposed for use in a SemEval 2015 task.

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“…For the present analyses, only data from their initial diagnosis was utilized. cTAKES/ytex have been utilized in clinical research in a variety of areas to identify phenotypes [Oellrich, Collier, Smedley, Groza, ], from studies of drug toxicity [Lin et al, ] to research in epilepsy [Cui, Bozorgi, Lhatoo, Zhang, Sahoo, ; Hamid et al, ].…”

Section: Methodsmentioning

confidence: 99%

Maternal metabolic risk factors for autism spectrum disorder—An analysis of electronic medical records and linked birth data

et al. 2016

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Past studies have suggested that conditions experienced by women during pregnancy (e.g. obesity and gestational diabetes mellitus (GDM)) may be associated with having a child with autism spectrum disorder (ASD). Our objective was to compare mothers who had a child diagnosed with ASD to mothers of children with a non-ASD developmental disorder (DD) or without any reported DD (controls). To accomplish the objective we collected medical record data from patients who resided in the Cincinnati Children's Hospital Medical Center's (CCHMC) primary catchment area and linked those data to data from birth certificates (to identify risk factors). Two comparison groups were analyzed; one with DD; and the other, controls without a reported ASD or DD. Descriptive statistics and regression analyses evaluated differences. Differences were greater comparing mothers of ASD to controls than comparing ASD to DD. Maternal obesity and GDM were associated with a statistically significant approximately 1.5-fold increased odds of having a child with an ASD. For mothers with both GDM and obesity, the association was twofold for having a child with ASD compared with controls. Maternal obesity and GDM might be associated with an increased risk of ASD in the offspring; however, no difference in risk of ASD according to BMI and GDM was seen when comparing to DD. Autism Res 2016, 9: 829-837,. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

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Automatic identification of methotrexate-induced liver toxicity in patients with rheumatoid arthritis from the electronic medical record

Abstract: Automated methotrexate-induced liver toxicity phenotype discovery for patients with RA based on structured and unstructured information in the EMR shows accurate results. Our work demonstrates that adding temporal features significantly improved classification results.

Cited by 64 publications

References 27 publications

Systematic review and meta‐analysis of algorithms used to identify drug‐induced liver injury (DILI) in health record databases

Systematic review and meta‐analysis of algorithms used to identify drug‐induced liver injury (DILI) in health record databases

Temporal Annotation in the Clinical Domain

Maternal metabolic risk factors for autism spectrum disorder—An analysis of electronic medical records and linked birth data

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