Evidence map›Paper›PMID 32511595›Full record

ArticlemedRxiv : the preprint server for health sciences2020

Covid-19 Testing, Hospital Admission, and Intensive Care Among 2,026,227 United States Veterans Aged 54-75 Years.

Christopher T Rentsch, Farah Kidwai-Khan, Janet P Tate, Lesley S Park, Joseph T King, Melissa Skanderson, Ronald G Hauser, Anna Schultze, Christopher I Jarvis, Mark Holodniy and 6 more

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 3 pooled it
–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.

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

6 citing papers in PubMed, 3 syntheses or guidelines pooled it, 154 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Article
  6. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors at 5 institutions in 2 countries.

Christopher T RentschVA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516.
Farah Kidwai-KhanVA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516.
Janet P TateVA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516.
Lesley S ParkStanford Center for Population Health Sciences, Stanford University School of Medicine, Stanford, CA, US, 94305.
Joseph T KingVA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516.
Melissa SkandersonVA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516.
Ronald G HauserVA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516.
Anna SchultzeFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK, WC1E 7HT.
Christopher I JarvisFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK, WC1E 7HT.
Mark HolodniyVA Palo Alto Healthcare System, US Department of Veterans Affairs, Palo Alto, CA, US, 94304.
Vincent Lo ReDivision of Infectious Diseases, Department of Medicine and Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, US, 19104.
Kathleen M AkgünVA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516.
Kristina CrothersVA Puget Sound Health Care System and Department of Medicine, University of Washington School of Medicine, Seattle, WA, US, 98104.
Tamar H TaddeiVA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516.
Matthew S FreibergGeriatric Research Education and Clinical Center (GRECC), US Department of Veterans Affairs, Tennessee Valley Health Care System, Nashville, TN, US 37212.
Amy C JusticeVA Connecticut Healthcare System, US Department of Veterans Affairs, West Haven, CT, US, 06516.
United States Department of Veterans Affairs · USUniversity of London · GBStanford Health Care · USUniversity of Pennsylvania · USUniversity of Washington · US

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Alcohol Associated Outcomes Among HIV+/- Aging VeteransU10AA013566 · NIAAA · YALE UNIVERSITY · PI JUSTICE, AMY CAROLINE · 2006 to 2010
$12.7M
Alcohol and Multisubstance Use in the Veterans Aging Cohort StudyU01AA020790 · NIAAA · YALE UNIVERSITY · PI JUSTICE, AMY CAROLINE · 2011 to 2020
$7.7M
Sex Disparities in Overall Response to ART Among HIV Infected IndividualsU24AA020794 · NIAAA · YALE UNIVERSITY · PI JUSTICE, AMY CAROLINE · 2011 to 2020
$5.5M
3/3 COMpAAAS Tripartite: ART-CC, KP, and VAU01AA026224 · NIAAA · YALE UNIVERSITY · PI JUSTICE, AMY CAROLINE · 2017 to 2021
$2.9M
NCATS NIH HHS UL1 TR001863NIAAA NIH HHS U01 AA020790NIAAA NIH HHS U01 AA026224NIAAA NIH HHS U10 AA013566NIAAA NIH HHS U24 AA020794
6 · The paper itself

Abstract

importanceSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causes coronavirus disease 2019 (Covid-19), an evolving pandemic. Limited data are available characterizing SARS-Cov-2 infection in the United States.

objectiveTo determine associations between demographic and clinical factors and testing positive for coronavirus 2019 (Covid-19+), and among Covid-19+ subsequent hospitalization and intensive care. DESIGN, SETTING, AND

participantsRetrospective cohort study including all patients tested for Covid-19 between February 8 and March 30, 2020, inclusive. We extracted electronic health record data from the national Veterans Affairs Healthcare System, the largest integrated healthcare system in the United States, on 2,026,227 patients born between 1945 and 1965 and active in care. Exposures: Demographic data, comorbidities, medication history, substance use, vital signs, and laboratory measures. Laboratory tests were analyzed first individually and then grouped into a validated summary measure of physiologic injury (VACS Index). Main Outcomes and Measures: We evaluated which factors were associated with Covid-19+ among all who tested. Among Covid-19+ we identified factors associated with hospitalization or intensive care. We identified independent associations using multivariable and conditional multivariable logistic regression with multiple imputation of missing values.

resultsAmong Veterans aged 54-75 years, 585/3,789 (15.4%) tested Covid-19+. In adjusted analysis (C-statistic=0.806) black race was associated with Covid-19+ (OR 4.68, 95% CI 3.79-5.78) and the association remained in analyses conditional on site (OR 2.56, 95% CI 1.89-3.46). In adjusted models, laboratory abnormalities (especially fibrosis-4 score [FIB-4] >3.25 OR 8.73, 95% CI 4.11-18.56), and VACS Index (per 5-point increase OR 1.62, 95% CI 1.43-1.84) were strongly associated with hospitalization. Associations were similar for intensive care. Although significant in unadjusted analyses, associations with comorbid conditions and medications were substantially reduced and, in most cases, no longer significant after adjustment. CONCLUSIONS AND RELEVANCE: Black race was strongly associated with Covid-19+, but not with hospitalization or intensive care. Among Covid-19+, risk of hospitalization and intensive care may be better characterized by laboratory measures and vital signs than by comorbid conditions or prior medication exposure.

Identifiers

PMID32511595
PMCPMC7276022
OpenAlexW3016553045

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.