Article

A methodology to generate longitudinally updated ACLF prognostication scores from electronic health record data

2020-11-24

Abstract excerpt

<h4>Background and Aims</h4> Queries of electronic health record (EHR) data repositories allow for automated data collection. These techniques have not been utilized in hepatology due to previous inability to capture hepatic encephalopathy (HE) grades, which are inputs for acute-on-chronic liver failure (ACLF) models. Here, we describe a methodology to utilizing EHR data to calculate rolling ACLF scores. <h4>Metho...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 08ff2073-3e00-50b4-a342-2477f9093249
DOI: 10.1101/2020.11.23.20237081

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

A methodology to generate longitudinally updated ACLF prognostication scores from electronic health record dataDOI 10.1101/2020.11.23.20237081Read

Predicting Post-Liver Transplant Outcomes in Patients with Acute-on-Chronic Liver Failure using Expert-Augmented Machine LearningSemantic proximity Read

A Comparison of Diagnostic Models and Prognostic Scores of ACLF: Towards Global HarmonizationSemantic proximity Read

Data from an electronic health informatics pipeline to describe clearance dynamics of Hepatitis B surface antigen (HBsAg) and e-Antigen (HBeAg) in chronic HBV infectionSemantic proximity Read

Assessment and Prediction of Clinical Outcomes for ICU-Admitted Patients Diagnosed with Hepatitis: Integrating Sociodemographic and Comorbidity DataSemantic proximity Read

Predicting Wilson’s Disease Progression using Machine Learning with Real-World Electronic Health RecordsSemantic proximity Read

HEV‐LFS: A novel scoring model for patients with hepatitis E virus‐related liver failureSemantic proximity Read

Single time-point multi-dimensional biomarker models can predict acute organ injury trajectorySemantic proximity Read

Development and validation of personalised risk prediction models for early detection and diagnosis of primary liver cancer among the English primary care population using the QResearch<sup>®</sup> database: research protocol and statistical analysis planSemantic proximity Read

Enhancing Cause of Death Prediction: Development and Validation of ML Models Using Multimodal Data Across Multiple Healthcare SitesSemantic proximity Read

International Electronic Health Record-Derived COVID-19 Clinical Course Profiles: The 4CE ConsortiumSemantic proximity Read

Time-to-event modeling with multimodal clinical and genetic features improves risk stratification of liver complications in chronic hepatitis CSemantic proximity Read

Development of an automated phenotyping algorithm for hepatorenal syndrome.Semantic proximity Read