Identification of invasive aspergillosis in electronic health records

Clicks: 21
ID: 324407
2026
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #221 of 326 articles by views in Open forum infectious diseases

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 326 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Abstract Background Consensus definitions for clinical identification of invasive aspergillosis (IA) are lacking, likely owed to difficulties in diagnosis. While the European Organization for Research and Treatment of Cancer-Mycoses Study Group (EORTC/MSG) has provided benchmark guidelines to define IA, the criteria are highly restrictive. In this study, we constructed alternative definitions of IA using structured data from electronic health records (EHR). Methods From 01 October 2015 to 31 March 2022, we identified patients with IA from EHR at Kaiser Permanente Southern California using definitions comprised of combinations of diagnosis codes, antifungal prescriptions, and/or positive mycological findings. Here, we report patient characteristics, including demographic information, underlying comorbidities and immunosuppression, diagnostic measures, as well as morbidity and mortality after diagnosis for the population comprising each IA definition. Results Between 86 and 4580 individuals were identified as possible IA cases across seven definitions. All IA definitions that except for that only required positive mycology had similar patient characteristics and outcomes to those meeting 2008 EORTC/MSG criteria. The largest of these cohorts was comprised of 1067 patients compared to the 86 that met EORTC/MSG criteria. Across IA definitions, all-cause mortality ranged from 11.7-33.1% within 6 months following diagnosis. The number of IA cases began trending upwards between 2019 and 2020 and continued steadily through the COVID-19 pandemic. Conclusions IA definitions based on structured data vastly increase efficiency and identify clinically significant IA cases that might otherwise go unrepresented. Variability in the number of patients identified between definitions also highlights critical deficits in current IA diagnostics.
Reference Key
openalex_W7201961866 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Emily Rayens, Jessica Skela, Bradley K. Ackerson, Magdalena E Pomichowski, Lance B. Price, Sara Y. Tartof
Are you one of these authors? Claim your profile
Journal Open forum infectious diseases
Year 2026
DOI
10.1093/ofid/ofag478
URL
https://doi.org/10.1093/ofid/ofag478
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.