Evidence map›Paper›PMID 38646211›Full record

ArticleCureus2024

Defining Incidental Versus Non-incidental COVID-19 Hospitalizations.

Dhimitri A Nikolla, Jonathan J Oskvarek, Mark S Zocchi, Nishad A Rahman, Andrew Leubitz, Ali Moghtaderi, Bernard S Black, Jesse M Pines

Open access · diamondAbstract read
In one paragraph

Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
4.2field-weighted citation impact, top 7% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. 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

8 authors at 5 institutions in 2 countries.

Dhimitri A NikollaDepartment of Internal Medicine / Emergency Medicine, Lake Erie College of Osteopathic Medicine, Erie, USA.
Jonathan J OskvarekDepartment of Emergency Medicine, Summa Health System, Akron, USA.
Mark S ZocchiHeller School for Social Policy and Management, Brandeis University, Waltham, USA.
Nishad A RahmanDepartment of Emergency Medicine, LifeBridge Health - Sinai Hospital, Baltimore, USA.
Andrew LeubitzDepartment of Emergency Medicine, Adventist HealthCare - Shady Grove Medical Center, Rockville, USA.
Ali MoghtaderiMilken Institute School of Public Health, George Washington University, Washington, DC, USA.
Bernard S BlackPritzker School of Law and Kellogg School of Management, Northwestern University, Chicago, USA.
Jesse M PinesDepartment of Emergency Medicine, Allegheny Health Network, Pittsburgh, USA.
Adventist HealthCare Shady Grove Medical Center · USBrandeis University · USACS Solutions (United States) · USKellogg's (Canada) · CAMilken Institute · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background Rates of COVID-19 hospitalization are an important measure of the health system burden of severe COVID-19 disease and have been closely followed throughout the pandemic. The highly transmittable, but often less severe, Omicron COVID-19 variant has led to an increase in hospitalizations with incidental COVID-19 diagnoses where COVID-19 is not the primary reason for admission. There is a strong public health need for a measure that is implementable at low cost with standard electronic health record (EHR) datasets that can separate these incidental hospitalizations from non-incidental hospitalizations where COVID-19 is the primary cause or an important contributor. Two crude metrics are in common use. The first uses in-hospital administration of dexamethasone as a marker of non-incidental COVID-19 hospitalizations. The second, used by the United States (US) CDC, relies on a limited set of COVID-19-related diagnoses (i.e., respiratory failure, pneumonia). Both measures likely undercount non-incidental COVID-19 hospitalizations. We therefore developed an improved EHR-based measure that is better able to capture the full range of COVID-19 hospitalizations. Methods We conducted a retrospective study of ED visit data from a national emergency medicine group from April 2020 to August 2023. We assessed the CDC approach, the dexamethasone-based measure, and alternative approaches that rely on co-diagnoses likely to be related to COVID-19, to determine the proportion of non-incidental COVID-19 hospitalizations. Results Of the 153,325 patients diagnosed with COVID-19 at 112 general EDs in 17 US states, and admitted or transferred, our preferred measure classified 108,243 (70.6%) as non-incidental, compared to 71,066 (46.3%) using the dexamethasone measure and 77,399 (50.5%) using the CDC measure. Conclusions Identifying non-incidental COVID-19 hospitalizations using ED administration of dexamethasone or the CDC measure provides substantially lower estimates than our preferred measure.

Indexed as

coronavirus disease 2019dexamethasoneemergency medicinehealth policyhospital admissioninternal medicinepandemicpublic health

Identifiers

PMID38646211
PMCPMC11027788
OpenAlexW4392992010

What OpenQuestion 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 OpenQuestion graph.