Evidence map›Paper›PMID 40666327›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Epidemiology of Aspergillosis Diagnoses in the U.S. using a National EHR Database, 2013-2023.

Brittany L Morgan Bustamante, Elijah G Martinez, Aidan Lee, Natalie J Kane, Simon K Camponuri, Rose M Reynolds, Theo T Snow, Juliana G E Bartels, Mark Hoffman, Theodore C White and 1 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Brittany L Morgan BustamanteDivision of Environmental Health Sciences, University of California, Berkeley, Berkeley, CA 94720.ORCID 0000-0002-0280-0904
Elijah G MartinezDivision of Environmental Health Sciences, University of California, Berkeley, Berkeley, CA 94720.
Aidan LeeCollege of Letters and Sciences, University of California, Berkeley, Berkeley, CA 94720.
Natalie J KaneChildren's Mercy Research Institute, Kansas City, MO 64108.
Simon K CamponuriDivision of Environmental Health Sciences, University of California, Berkeley, Berkeley, CA 94720.ORCID 0000-0003-3787-170X
Rose M ReynoldsChildren's Mercy Research Institute, Kansas City, MO 64108.
Theo T SnowDivision of Environmental Health Sciences, University of California, Berkeley, Berkeley, CA 94720.
Juliana G E BartelsDivision of Environmental Health Sciences, University of California, Berkeley, Berkeley, CA 94720.
Mark HoffmanChildren's Mercy Research Institute, Kansas City, MO 64108.
Theodore C WhiteSchool of Science and Engineering, University of Missouri-Kansas City, Kansas City, MO 64110.ORCID 0000-0003-3229-1378
Justin V RemaisDivision of Environmental Health Sciences, University of California, Berkeley, Berkeley, CA 94720.ORCID 0000-0002-0223-4615

Funding

Using massive, multi-regional EHR data to estimate the impacts of environmental and other risk factors on fungal disease epidemiology in the U.S.R01AI176770 · NIAID · UNIVERSITY OF MISSOURI KANSAS CITY · PI Mark Hoffman, Justin V Remais · 2023 to 2026
$3.2M
NIAID NIH HHS R01 AI176770
6 · The paper itself

Abstract

Importance: Aspergillosis is an under-recognized fungal infection associated with rising hospitalizations, concerns about antifungal resistance, and substantial morbidity and mortality in the U.S. Yet, national data on aspergillosis remain fragmented due to absence of centralized surveillance. Objective: To examine demographic and geographic variation and temporal trends in aspergillosis prevalence in the U.S. from 2013 to 2023; to assess how the COVID-19 pandemic influenced prevalence across population subgroups. Design: Retrospective cohort study using a large, national electronic health record (EHR) database. Setting: 142 healthcare systems in the U.S. using Oracle Health EHR systems, encompassing disparate care settings. Participants: Adults aged 18 years and older who received care between January 1, 2013, and December 31, 2023. The cohort included over 76 million patients, and over 127 million person-years, with 20,764 aspergillosis diagnoses. Exposures: Calendar year, patient characteristics (age, sex, race, ethnicity, residence type), and state of residence. COVID-19 was treated as a time-varying exposure. Main Outcomes and Measures: Annual and overall prevalence of aspergillosis per 100,000 person-years; adjusted prevalence ratios (aPRs) by demographic group and state, estimated using quasi-Poisson and Bayesian spatiotemporal regression. COVID-19-related shifts in prevalence were assessed using estimated marginal means. Results: Between 2013 and 2023, aspergillosis prevalence increased 5% annually, peaking in 2022. Rhode Island had the highest aPR across all years; Utah the lowest. Prevalence was higher in males (aPR: 1.37), older adults (aPR for ≥65 vs. 18 to 34: 4.95), and urban residents (rural aPR: 0.86). Post-COVID-19, prevalence increased disproportionately among Hispanic or Latino patients and several racial minority groups. Suggestive trends of increasing prevalence were also observed among rural residents. Conclusions and Relevance: This study provides the most comprehensive national assessment to date of aspergillosis patterns in the U.S., revealing evidence of rising prevalence and emerging disparities shaped by the COVID-19 pandemic. Clinicians should consider regional and demographic risk patterns to support earlier diagnosis, guide antifungal treatment, and improve outcomes-especially among older adults and populations disproportionately affected by COVID-19. Clinicians practicing in rural or underserved areas should be particularly mindful of shifting risk profiles and advocate for improved diagnostic resources to reduce delays in care.

Identifiers

PMID40666327
PMCPMC12262757

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.