Evidence map›Paper›PMID 33891529›Full record

ArticleAmerican journal of respiratory and critical care medicine2021

Hospital-Level Variation in Death for Critically Ill Patients with COVID-19.

Matthew M Churpek, Shruti Gupta, Alexandra B Spicer, William F Parker, John Fahrenbach, Samantha K Brenner, David E Leaf, STOP-COVID Investigators

2 registry-linked trialsAbstract readMulticenter Study
In one paragraph

Article in American journal of respiratory and critical care medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
–field-weighted citation impact
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.

NCT04343898 completednot on this map

Study of the Treatment and Outcomes in Critically Ill Patients With COVID-19

TypeobservationalSponsorBrigham and Women's HospitalRan2020 to 2023Enrolled5,154ConditionsCoronavirus InfectionArmsNo intervention
NCT04706533 completednot on this map

Prospective Observational Study Examining Clinical Characteristics, Inflammatory Markers, Treatments and Outcomes of Patients Hospitalized for COVID-19 at the University of Michigan Healthcare System in Ann Arbor

TypeobservationalSponsorUniversity of MichiganRan2020 to 2022Enrolled3,402ConditionsCovid19, Kidney Diseases, Inflammation, SARS-CoV InfectionArmsBiomarkers of inflammation
3 · Its place in the literature

Who cites it

32 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. World Pneumonia Day 2024: Fighting Pneumonia and Antimicrobial Resistance.American journal of respiratory and critical care medicine · 2024
    Article
  7. Review
  8. Article
  9. Observational
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Care of the Seriously Ill Patient with SARS-CoV-2.The Medical clinics of North America · 2022
    Review
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Matthew M ChurpekUniversity of Wisconsin Madison, 5228, Medicine; Division of Pulmonary and Critical Care, Madison, Wisconsin, United States; mchurpek@medicine.wisc.edu.
Shruti GuptaBrigham and Women's Hospital Department of Medicine, 370908, Division of Renal Medicine, Boston, Massachusetts, United States.ORCID 0000-0002-5747-2151
Alexandra B SpicerUniversity of Wisconsin-Madison, 5228, Medicine; Division of Pulmonary and Critical Care, Madison, Wisconsin, United States.
William F ParkerThe University of Chicago, 2462, Department of Medicine, Chicago, Illinois, United States.
John FahrenbachThe University of Chicago, 2462, Department of Medicine, Chicago, Illinois, United States.
Samantha K BrennerHackensack University Medical Center, 3673, Internal Medicine, Hackensack, New Jersey, United States.
David E LeafBrigham and Women's Hospital, 1861, Division of Renal Medicine, Boston, Massachusetts, United States.
STOP-COVID Investigators

Funding

TRAINING IN METABOLISM, DIABETES AND ENDOCRINOLOGYT32DK007169 · NIDDK · NORTHWESTERN UNIVERSITY AT CHICAGO · PI Joseph Bass · 1988 to 2026
$6.6M
Deferoxamine for the Prevention of Acute Kidney InjuryR01DK125786 · NIDDK · BRIGHAM AND WOMEN'S HOSPITAL · PI LEAF, DAVID EVAN · 2020 to 2024
$3.5M
Sepsis Early Prediction and Subphenotype Illumination Study (SEPSIS)R01GM123193 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI CHURPEK, MATTHEW MICHAEL · 2017 to 2021
$1.9M
Precision Medicine Approach to Vitamin D3 Administration in Critical IllnessR01HL144566 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI LEAF, DAVID EVAN · 2019 to 2022
$1.8M
Oxygen Saturation Targets during Mechanical Ventilation of Critically Ill Adults: A Clinical TrialK23HL143053 · NHLBI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI SEMLER, MATTHEW WALL · 2018 to 2022
$854k
Diet Related Inflammation and Kidney Function Decline in Racial/Ethnic MinoritiesK23DK124644 · NIDDK · ALBERT EINSTEIN COLLEGE OF MEDICINE · PI JOHNS, TANYA · 2021 to 2023
$752k
Mending a Broken Heart Allocation System with Machine LearningK08HL150291 · NHLBI · UNIVERSITY OF CHICAGO · PI PARKER, WILLIAM F · 2020 to 2024
$713k
NHLBI NIH HHS K08 HL150291NHLBI NIH HHS K23 HL143053NHLBI NIH HHS R01 HL144566NIDDK NIH HHS K23 DK124644NIDDK NIH HHS R01 DK125786NIDDK NIH HHS T32 DK007169NIGMS NIH HHS R01 GM123193
6 · The paper itself

Abstract

rationaleVariation in hospital mortality has been described for coronavirus disease 2019 (COVID-19), but the factors that explain these differences remain unclear.

objectiveOur objective was to utilize a large, nationally representative dataset of critically ill adults with COVID-19 to determine which factors explain mortality variability.

methodsIn this multicenter cohort study, we examined adults hospitalized in intensive care units with COVID-19 at 70 United States hospitals between March and June 2020. The primary outcome was 28-day mortality. We examined patient-level and hospital-level variables. Mixed-effects logistic regression was used to identify factors associated with interhospital variation. The median odds ratio (OR) was calculated to compare outcomes in higher- vs. lower-mortality hospitals. A gradient boosted machine algorithm was developed for individual-level mortality models. MEASUREMENTS AND MAIN

resultsA total of 4,019 patients were included, 1537 (38%) of whom died by 28 days. Mortality varied considerably across hospitals (0-82%). After adjustment for patient- and hospital-level domains, interhospital variation was attenuated (OR decline from 2.06 [95% CI, 1.73-2.37] to 1.22 [95% CI, 1.00-1.38]), with the greatest changes occurring with adjustment for acute physiology, socioeconomic status, and strain. For individual patients, the relative contribution of each domain to mortality risk was: acute physiology (49%), demographics and comorbidities (20%), socioeconomic status (12%), strain (9%), hospital quality (8%), and treatments (3%).

conclusionThere is considerable interhospital variation in mortality for critically ill patients with COVID-19, which is mostly explained by hospital-level socioeconomic status, strain, and acute physiologic differences. Individual mortality is driven mostly by patient-level factors. This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Indexed as

AlgorithmsAgedComorbidityCOVID-19Critical IllnessFemaleFollow-Up StudiesHospital MortalityHumansIncidenceIntensive Care UnitsMaleMiddle AgedPrognosisRetrospective StudiesRisk FactorsCOVID-19Critical CareHealth DisparitiesIntensive Care Unit

Identifiers

PMID33891529
PMCPMC8480242

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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.