Evidence map›Paper›PMID 35119680›Full record

ArticleJournal of racial and ethnic health disparities2023

Critical Care Among Disadvantaged Minority Groups Made Equitable: Trends Throughout the COVID-19 Pandemic.

Diana Cristina Lopez, Georgina Whelan, Lisa Kojima, Samyukta Dore, Saloni Lad, Dominique Tucker, Emily Abramczyk, Omar Mehkri, Xiaozhen Han, Xiaofeng Wang and 2 more

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

Article in Journal of racial and ethnic health disparities, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 32% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. Article
  3. 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

12 authors at 2 institutions in 1 country.

Diana Cristina Lopez *Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH, USA.
Georgina Whelan *Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH, USA.
Lisa KojimaCleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH, USA.
Samyukta DoreCleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH, USA.
Saloni LadCleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH, USA.
Dominique TuckerCleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH, USA.
Emily AbramczykCleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH, USA.
Omar MehkriDepartment of Critical Care, Respiratory Institute, Cleveland Clinic, 9500 Euclid Avenue, OH, 44195, Cleveland, USA.
Xiaozhen HanDepartment of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, USA.
Xiaofeng WangDepartment of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, USA.
Ana Monica Yepes-RiosDepartment of Internal Medicine, Cleveland Clinic, Cleveland, OH, USA.
Abhijit DuggalDepartment of Critical Care, Respiratory Institute, Cleveland Clinic, 9500 Euclid Avenue, OH, 44195, Cleveland, USA. duggala2@ccf.org.ORCID 0000-0003-4220-2359
Cleveland Clinic Lerner College of Medicine · USCleveland Clinic · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUS racial and ethnic minorities have well-established elevated rates of comorbidities, which, compounded with healthcare access inequity, often lead to worse health outcomes. In the current COVID-19 pandemic, it is important to understand existing disparities in minority groups' critical care outcomes and mechanisms behind these-topics that have yet to be well-explored.

objectiveAssess for disparities in racial and ethnic minority groups' COVID-19 critical care outcomes.

designRetrospective cohort study.

participantsA total of 2125 adult patients who tested positive for COVID-19 via RT-PCR between March and December 2020 and required ICU admission at the Cleveland Clinic Hospital Systems were included. MAIN MEASURES: Primary outcomes were mortality and hospital length of stay. Cohort-wide analysis and subgroup analyses by pandemic wave were performed. Multivariable logistic regression models were built to study the associations between mortality and covariates. KEY

resultsWhile crude mortality was increased in White as compared to Black patients (37.5% vs. 30.5%, respectively; p = 0.002), no significant differences were appraised after adjustment or across pandemic waves. Although median hospital length of stay was comparable between these groups, ICU stay was significantly different (4.4 vs. 3.4, p = 0.003). Mortality and median hospital and ICU length of stay did not differ significantly between Hispanic and non-Hispanic patients. Neither race nor ethnicity was associated with mortality due to COVID-19, although APACHE score, CKD, malignant neoplasms, antibiotic use, vasopressor requirement, and age were.

conclusionsWe found no significant differences in mortality or hospital length of stay between different races and ethnicities. In a pandemic-influenced critical care setting that operated outside conditions of ICU strain and implemented standardized protocol enabling equitable resource distribution, disparities in outcomes often seen among racial and ethnic minority groups were successfully mitigated.

Indexed as

COVID-19Minority GroupsAdultCritical CareEthnicityHumansPandemicsRetrospective StudiesCOVID-19Critical careICU strainRacial and ethnic inequalitySocial disparities of health

Identifiers

PMID35119680
PMCPMC8815384
OpenAlexW4210703874

What OpenQuestion holds

Textmetadata
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.