Evidence map›Paper›PMID 35986059›Full record

ArticleNPJ digital medicine2022

Early-stage COVID-19 pandemic observations on pulmonary embolism using nationwide multi-institutional data harvesting.

Axel Wismüller, Adora M DSouza, Anas Z Abidin, M Ali Vosoughi, Christopher Gange, Isabel O Cortopassi, Gracijela Bozovic, Alexander A Bankier, Kiran Batra, Yosef Chodakiewitz and 18 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NPJ digital medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.7field-weighted citation impact, top 14% of its field
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

7 citing papers in PubMed, 18 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

28 authors at 15 institutions in 2 countries.

Axel WismüllerDepartment of Imaging Sciences, University of Rochester Medical Center, Rochester, NY, USA.
Adora M DSouzaDepartment of Electrical and Computer Engineering, University of Rochester, Rochester, NY, USA.
Anas Z AbidinDepartment of Biomedical Engineering, University of Rochester Medical Center, Rochester, NY, USA.
M Ali VosoughiDepartment of Electrical and Computer Engineering, University of Rochester, Rochester, NY, USA.
Christopher GangeDepartment of Radiology & Biomedical Sciences, Yale University School of Medicine, New Haven, CT, USA.ORCID http://orcid.org/0000-0002-1224-4665
Isabel O CortopassiDepartment of Radiology, Mayo Clinic College of Medicine and Science, Jacksonville, FL, USA.
Gracijela BozovicDepartment of Radiology, University of Massachusetts Chan Medical School, Worcester, MA, USA.
Alexander A BankierDepartment of Radiology, University of Massachusetts Chan Medical School, Worcester, MA, USA.
Kiran BatraDepartment of Radiology, University of Texas, Southwestern Medical Center, Dallas, TX, USA.
Yosef ChodakiewitzDepartment of Imaging, S. Mark Taper Foundation Imaging Center, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Yin XiDepartment of Radiology, University of Texas, Southwestern Medical Center, Dallas, TX, USA.
Christopher T WhitlowDepartment of Radiology, Wake Forest School of Medicine, Winston-Salem, NC, USA.
Janardhana PonnatapuraDepartment of Radiology, Wake Forest School of Medicine, Winston-Salem, NC, USA.ORCID http://orcid.org/0000-0002-7459-0854
Gary J WendtDepartment of Radiology, University of Wisconsin, Madison, WI, USA.
Eric P WeinbergDepartment of Imaging Sciences, University of Rochester Medical Center, Rochester, NY, USA.
Larry StockmasterDepartment of Imaging Sciences, University of Rochester Medical Center, Rochester, NY, USA.ORCID http://orcid.org/0000-0002-3596-0787
David A ShrierDepartment of Imaging Sciences, University of Rochester Medical Center, Rochester, NY, USA.
Min Chul ShinDepartment of Radiology, Christiana Care Health System, Newark, DE, USA.
Roshan ModiDepartment of Radiology, Christiana Care Health System, Newark, DE, USA.
Hao Steven LoDepartment of Radiology, University of Massachusetts Chan Medical School, Worcester, MA, USA.ORCID http://orcid.org/0000-0002-2790-8946
Seth KligermanDepartment of Radiology, University of California, San Diego, San Diego, CA, USA.
Aws HamidEmory University School of Medicine, Department of Radiology and Imaging Sciences, Atlanta, GA, USA.ORCID http://orcid.org/0000-0002-0029-8906
Lewis D HahnDepartment of Radiology, University of California, San Diego, San Diego, CA, USA.
Glenn M GarciaUniversity of Texas, Medical Branch, Galveston, TX, USA.
Jonathan H ChungDepartment of Radiology, University of Chicago, Chicago, IL, USA.
Talissa AltesUniversity of Missouri-Columbia, Columbia, SC, USA.
Suhny AbbaraDepartment of Radiology, University of Texas, Southwestern Medical Center, Dallas, TX, USA.ORCID http://orcid.org/0000-0003-2552-7362
Anna S BaderDepartment of Radiology & Biomedical Sciences, Yale University School of Medicine, New Haven, CT, USA. ashlionsky@gmail.com.ORCID http://orcid.org/0000-0002-3807-0261
University of Rochester Medical Center · USThe University of Texas Southwestern Medical Center · USUniversity of Massachusetts Chan Medical School · USChristiana Care Health System · USUniversity of California San Diego · USUniversity of Rochester · USWake Forest University · USYale University · USCedars-Sinai Medical Center · USEmory University · USJacksonville College · USThe University of Texas Medical Branch at Galveston · USUniversity of Chicago · USUniversity of Missouri · USUniversity of Wisconsin–Madison · US

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
CRCNS: Large Scale Brain Connectivity in HIV-Related Cognitive ImpairmentR01DA034977 · NIDA · UNIVERSITY OF ROCHESTER · PI WISMUELLER, AXEL W.E. · 2012 to 2014
$599k
NCATS NIH HHS UL1 TR001863NIDA NIH HHS R01 DA034977
6 · The paper itself

Abstract

We introduce a multi-institutional data harvesting (MIDH) method for longitudinal observation of medical imaging utilization and reporting. By tracking both large-scale utilization and clinical imaging results data, the MIDH approach is targeted at measuring surrogates for important disease-related observational quantities over time. To quantitatively investigate its clinical applicability, we performed a retrospective multi-institutional study encompassing 13 healthcare systems throughout the United States before and after the 2020 COVID-19 pandemic. Using repurposed software infrastructure of a commercial AI-based image analysis service, we harvested data on medical imaging service requests and radiology reports for 40,037 computed tomography pulmonary angiograms (CTPA) to evaluate for pulmonary embolism (PE). Specifically, we compared two 70-day observational periods, namely (i) a pre-pandemic control period from 11/25/2019 through 2/2/2020, and (ii) a period during the early COVID-19 pandemic from 3/8/2020 through 5/16/2020. Natural language processing (NLP) on final radiology reports served as the ground truth for identifying positive PE cases, where we found an NLP accuracy of 98% for classifying radiology reports as positive or negative for PE based on a manual review of 2,400 radiology reports. Fewer CTPA exams were performed during the early COVID-19 pandemic than during the pre-pandemic period (9806 vs. 12,106). However, the PE positivity rate was significantly higher (11.6 vs. 9.9%, p < 10

Identifiers

PMID35986059
PMCPMC9388980
OpenAlexW4292332655

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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.