Evidence map›Paper›PMID 38347927›Full record

ArticleFrontiers in public health2024

COVID-19 waves in an urban setting 2020-2022: an electronic medical record analysis.

Yi-Shuan Elaine Chen, Susan H Gawel, Pankaja Desai, Juan Rojas, Hannah J Barbian, Nagarjuna Tippireddy, Rajkamal Gopinath, Sharon Schneider, Anthony Orzechowski, Gavin Cloherty and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2024. 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
0.3field-weighted citation impact, top 42% 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

11 authors at 3 institutions in 1 country.

Yi-Shuan Elaine ChenAbbott Diagnostics Division, Abbott Laboratories, Abbott Park, IL, United States.
Susan H GawelAbbott Diagnostics Division, Abbott Laboratories, Abbott Park, IL, United States.
Pankaja DesaiRush University Medical Center, Chicago, IL, United States.
Juan RojasRush University Medical Center, Chicago, IL, United States.
Hannah J BarbianRush University Medical Center, Chicago, IL, United States.
Nagarjuna TippireddyRush University Medical Center, Chicago, IL, United States.
Rajkamal GopinathAbbott Diagnostics Division, Abbott Laboratories, Abbott Park, IL, United States.
Sharon SchneiderAbbott Diagnostics Division, Abbott Laboratories, Abbott Park, IL, United States.
Anthony OrzechowskiAbbott Diagnostics Division, Abbott Laboratories, Abbott Park, IL, United States.
Gavin ClohertyAbbott Diagnostics Division, Abbott Laboratories, Abbott Park, IL, United States.
Alan LandayRush University Medical Center, Chicago, IL, United States.
Rush University Medical Center · USAbbott Fund · USAbbott (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Global and national surveillance efforts have tracked COVID-19 incidence and clinical outcomes, but few studies have compared comorbid conditions and clinical outcomes across each wave of the pandemic. We analyzed data from the COVID-19 registry of a large urban healthcare system to determine the associations between presenting comorbidities and clinical outcomes during the pandemic. Methods: We analyzed registry data for all inpatients and outpatients with COVID-19 from March 2020 through September 2022 ( Results: Waves 2 and 3 (Alpha and Delta variants) were associated with greater hospitalizations, ICU admissions, and mortality than other variants. Chronic pulmonary disease was the most common comorbid condition across all age groups and waves. Mortality rates were higher in older patients but decreased across all age groups in later waves. In every wave, mortality was associated with renal disease, congestive heart failure, cerebrovascular disease, diabetes, and chronic pulmonary disease. Multivariable analysis found that liver disease and renal disease were significantly associated with mortality, hospitalization, and ICU admission, and diabetes was significantly associated with hospitalization and ICU admission. Conclusion: The COVID-19 registry is a valuable resource to identify risk factors for clinical outcomes. Our findings may inform risk stratification and care planning for patients with COVID-19 based on age and comorbid conditions.

Indexed as

COVID-19Diabetes MellitusKidney DiseasesAgedElectronic Health RecordsHumansSARS-CoV-2COVID-19electronic health recordsmortalitySARS-CoV-2surveillance

Identifiers

PMID38347927
PMCPMC10859858
OpenAlexW4391317256

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.