ArticleJMIR formative research2022
Automated Pulmonary Embolism Risk Assessment Using the Wells Criteria: Validation Study.
Article in JMIR formative research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 15 citations in OpenAlex.
- Nudging provider adoption of clinical decision support: study protocol for a stepped-wedge cluster randomized, hybrid type III trial of an electronic health record-agnostic pulmonary embolism risk tool.Implementation science : IS · 2026Article
- Artificial Intelligence in Venous Thromboembolism Prevention: A Narrative Review of Machine Learning, Deep Learning, and Natural Language Processing.Journal of cardiovascular development and disease · 2026Review
- Evaluation of CTPA Ordering for Pulmonary Embolisms by Patient Race and Ethnicity.Academic emergency medicine : official journal of the Society for Academic Emergency Medicine · 2026Article
- Finding a constrained number of predictor phenotypes for multiple outcome prediction.BMJ health & care informatics · 2025Article
- Apelin-13 as a novel diagnostic laboratory biomarker in thromboembolic disorders: a review of literature with prospective insights.International journal of emergency medicine · 2024Review
- Efficient management of pulmonary embolism diagnosis using a two-step interconnected machine learning model based on electronic health records data.Health information science and systems · 2024Article
- From Calculation to Communication: Using Risk Score Calculators to Inform Clinical Decision Making and Facilitate Patient Engagement.Medical decision making : an international journal of the Society for Medical Decision Making · 2024Article
- Article
- Nudging Health Care Providers' Adoption of Clinical Decision Support: Protocol for the User-Centered Development of a Behavioral Economics-Inspired Electronic Health Record Tool.JMIR research protocols · 2023Article
- Determining the diagnostic value of three clinical criteria Wells', YEARS and modified Geneva in pregnant women with suspected pulmonary thromboembolism.American journal of cardiovascular disease · 2022Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundComputed tomography pulmonary angiography (CTPA) is frequently used in the emergency department (ED) for the diagnosis of pulmonary embolism (PE), while posing risk for contrast-induced nephropathy and radiation-induced malignancy.
objectiveWe aimed to create an automated process to calculate the Wells score for pulmonary embolism for patients in the ED, which could potentially reduce unnecessary CTPA testing.
methodsWe designed an automated process using electronic health records data elements, including using a combinatorial keyword search method to query free-text fields, and calculated automated Wells scores for a sample of all adult ED encounters that resulted in a CTPA study for PE at 2 tertiary care hospitals in New York, over a 2-month period. To validate the automated process, the scores were compared to those derived from a 2-clinician chart review.
resultsA total of 202 ED encounters resulted in a completed CTPA to form the retrospective study cohort. Patients classified as "PE likely" by the automated process (126/202, 62%) had a PE prevalence of 15.9%, whereas those classified as "PE unlikely" (76/202, 38%; Wells score >4) had a PE prevalence of 7.9%. With respect to classification of the patient as "PE likely," the automated process achieved an accuracy of 92.1% when compared with the chart review, with sensitivity, specificity, positive predictive value, and negative predictive value of 93%, 90.5%, 94.4%, and 88.2%, respectively.
conclusionsThis was a successful development and validation of an automated process using electronic health records data elements, including free-text fields, to classify risk for PE in ED visits.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.