Evidence map›Paper›PMID 34740527›Full record

ArticleAcademic radiology2021

Using Lung Base Covid-19 Findings to Predict Future Disease Trends and New Variant Outbreaks: Study of First New York City (NYC) Outbreak.

Paul Smereka, Rebecca Anthopolos, Larry A Latson, Polly Kirsch, Bari Dane

Open access · bronzeAbstract read
In one paragraph

Article in Academic radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 57% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
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

5 authors at 1 institution in 1 country.

Paul SmerekaDepartment of Radiology (P.S., R.A., L.L., P.K., B.D.), NYU Langone Health, 660 1(st) Avenue, New York, NY 10016. Electronic address: paul.smereka@nyulangone.org.
Rebecca AnthopolosDepartment of Radiology (P.S., R.A., L.L., P.K., B.D.), NYU Langone Health, 660 1(st) Avenue, New York, NY 10016.
Larry A LatsonDepartment of Radiology (P.S., R.A., L.L., P.K., B.D.), NYU Langone Health, 660 1(st) Avenue, New York, NY 10016.
Polly KirschDepartment of Radiology (P.S., R.A., L.L., P.K., B.D.), NYU Langone Health, 660 1(st) Avenue, New York, NY 10016.
Bari DaneDepartment of Radiology (P.S., R.A., L.L., P.K., B.D.), NYU Langone Health, 660 1(st) Avenue, New York, NY 10016.
NYU Langone Health · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

RATIONALE AND

objectivesAsymptomatic COVID-19 carriers and insufficient testing make containment of the virus difficult. The purpose of this study was to determine if unexpected lung base findings on abdominopelvic CTs concerning for COVID-19 infection could serve as a surrogate for the diagnosis of COVID-19 in the community. MATERIALS AND

methodsA database search of abdominopelvic CT reports from March 1,2020 to May 2,2020 was performed for keywords suggesting COVID-19 infection by lung base findings. COVID-19 status, respiratory symptoms, laboratory parameters and patient outcomes (hospitalization, ICU admission and/or intubation, and death) were recorded. The trend in cases of unexpected concerning lung base findings on abdominopelvic CT at our institution was compared to the total number of confirmed new cases in NYC over the same time period.

resultsThe trend in abnormal lung base findings on abdominopelvic CT at our institution correlated with the citywide number of confirmed new cases, including rise and subsequent fall in total cases. The trend was not mediated by COVID-19 testing status or number of tests performed. Patients with respiratory symptoms had significantly higher ferritin (median = 995ng/ml vs 500ng/ml, p = 0.027) and death rate (8/24, 33% vs 4/54, 9%, p = 0.018) compared to those without.

conclusionThe rise and fall of unexpected lung base findings suggestive of COVID-19 infection on abdominopelvic CT in patients without COVID-19 symptoms correlated with the number of confirmed new cases throughout NYC from the same time period. A model using abdominopelvic CT lung base findings can serve as a surrogate for future COVID-19 outbreaks.

Indexed as

COVID-19COVID-19 TestingDisease OutbreaksHumansLungNew York CitySARS-CoV-2

Identifiers

PMID34740527
PMCPMC8484077
OpenAlexW3202236256

What OpenQuestion holds

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Registered trials

None linked

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.