Evidence map›Paper›PMID 32960645›Full record

ArticleAnnals of internal medicine2021

Patient Trajectories Among Persons Hospitalized for COVID-19 : A Cohort Study.

Brian T Garibaldi, Jacob Fiksel, John Muschelli, Matthew L Robinson, Masoud Rouhizadeh, Jamie Perin, Grant Schumock, Paul Nagy, Josh H Gray, Harsha Malapati and 18 more

Erratum issuedAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Annals of internal medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 128 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
128citing papers in PubMed, 7 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

128 citing papers in PubMed, 7 syntheses or guidelines pooled it.

  1. Pooled it
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  6. Asthma in patients with coronavirus disease 2019: A systematic review and meta-analysis.Annals of allergy, asthma & immunology : official publication of the American College of Allergy, Asthma, & Immunology · 2021
    Pooled it
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  8. Trial
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68 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

28 authors.

Brian T GaribaldiJohns Hopkins University School of Medicine, Baltimore, Maryland (B.T.G., M.L.R., P.N., J.H.G., H.M., T.M.N., B.S.K., P.M.H., R.B., D.R.T., M.G.B., A.R., A.G.).ORCID 0000-0001-8632-5567
Jacob FikselJohns Hopkins Bloomberg School of Public Health, Baltimore, Maryland (J.F., J.M., J.P., G.S., M.W., K.B., S.L.Z.).ORCID 0000-0001-7067-1334
John MuschelliJohns Hopkins Bloomberg School of Public Health, Baltimore, Maryland (J.F., J.M., J.P., G.S., M.W., K.B., S.L.Z.).ORCID 0000-0001-6469-1750
Matthew L RobinsonJohns Hopkins University School of Medicine, Baltimore, Maryland (B.T.G., M.L.R., P.N., J.H.G., H.M., T.M.N., B.S.K., P.M.H., R.B., D.R.T., M.G.B., A.R., A.G.).ORCID 0000-0003-0376-8560
Masoud RouhizadehInstitute for Clinical and Translational Research, Johns Hopkins University School of Medicine, Baltimore, Maryland (M.R., B.W.).ORCID 0000-0002-9006-6112
Jamie PerinJohns Hopkins Bloomberg School of Public Health, Baltimore, Maryland (J.F., J.M., J.P., G.S., M.W., K.B., S.L.Z.).ORCID 0000-0002-5482-6620
Grant SchumockJohns Hopkins Bloomberg School of Public Health, Baltimore, Maryland (J.F., J.M., J.P., G.S., M.W., K.B., S.L.Z.).ORCID 0000-0003-2361-9896
Paul NagyJohns Hopkins University School of Medicine, Baltimore, Maryland (B.T.G., M.L.R., P.N., J.H.G., H.M., T.M.N., B.S.K., P.M.H., R.B., D.R.T., M.G.B., A.R., A.G.).ORCID 0000-0001-5108-7749
Josh H GrayJohns Hopkins University School of Medicine, Baltimore, Maryland (B.T.G., M.L.R., P.N., J.H.G., H.M., T.M.N., B.S.K., P.M.H., R.B., D.R.T., M.G.B., A.R., A.G.).ORCID 0000-0002-3388-5867
Harsha MalapatiJohns Hopkins University School of Medicine, Baltimore, Maryland (B.T.G., M.L.R., P.N., J.H.G., H.M., T.M.N., B.S.K., P.M.H., R.B., D.R.T., M.G.B., A.R., A.G.).ORCID 0000-0002-6710-0239
Mariam Ghobadi-KruegerInformation Technology, Johns Hopkins Medicine, Baltimore, Maryland (M.G., K.H.).
Timothy M NiessenJohns Hopkins University School of Medicine, Baltimore, Maryland (B.T.G., M.L.R., P.N., J.H.G., H.M., T.M.N., B.S.K., P.M.H., R.B., D.R.T., M.G.B., A.R., A.G.).
Bo Soo KimJohns Hopkins University School of Medicine, Baltimore, Maryland (B.T.G., M.L.R., P.N., J.H.G., H.M., T.M.N., B.S.K., P.M.H., R.B., D.R.T., M.G.B., A.R., A.G.).
Peter M HillJohns Hopkins University School of Medicine, Baltimore, Maryland (B.T.G., M.L.R., P.N., J.H.G., H.M., T.M.N., B.S.K., P.M.H., R.B., D.R.T., M.G.B., A.R., A.G.).
M Shafeeq AhmedHoward Country General Hospital, Johns Hopkins University School of Medicine, Baltimore, Maryland (M.S.A.).
Eric D DobkinSuburban Hospital, Johns Hopkins Medicine, Bethesda, Maryland (E.D.D.).
Renee BlandingJohns Hopkins University School of Medicine, Baltimore, Maryland (B.T.G., M.L.R., P.N., J.H.G., H.M., T.M.N., B.S.K., P.M.H., R.B., D.R.T., M.G.B., A.R., A.G.).
Jennifer AbeleSibley Memorial Hospital, Johns Hopkins Medicine, Washington, DC (J.A.).
Bonnie WoodsInstitute for Clinical and Translational Research, Johns Hopkins University School of Medicine, Baltimore, Maryland (M.R., B.W.).
Kenneth HarknessInformation Technology, Johns Hopkins Medicine, Baltimore, Maryland (M.G., K.H.).
David R ThiemannJohns Hopkins University School of Medicine, Baltimore, Maryland (B.T.G., M.L.R., P.N., J.H.G., H.M., T.M.N., B.S.K., P.M.H., R.B., D.R.T., M.G.B., A.R., A.G.).
Mary G BowringJohns Hopkins University School of Medicine, Baltimore, Maryland (B.T.G., M.L.R., P.N., J.H.G., H.M., T.M.N., B.S.K., P.M.H., R.B., D.R.T., M.G.B., A.R., A.G.).ORCID 0000-0002-7299-7730
Aalok B ShahTechnology Innovation Center, Johns Hopkins University School of Medicine, Baltimore, Maryland (A.B.S.).
Mei-Cheng WangJohns Hopkins Bloomberg School of Public Health, Baltimore, Maryland (J.F., J.M., J.P., G.S., M.W., K.B., S.L.Z.).
Karen Bandeen-RocheJohns Hopkins Bloomberg School of Public Health, Baltimore, Maryland (J.F., J.M., J.P., G.S., M.W., K.B., S.L.Z.).
Antony RosenJohns Hopkins University School of Medicine, Baltimore, Maryland (B.T.G., M.L.R., P.N., J.H.G., H.M., T.M.N., B.S.K., P.M.H., R.B., D.R.T., M.G.B., A.R., A.G.).ORCID 0000-0002-8374-4763
Scott L ZegerJohns Hopkins Bloomberg School of Public Health, Baltimore, Maryland (J.F., J.M., J.P., G.S., M.W., K.B., S.L.Z.).
Amita GuptaJohns Hopkins University School of Medicine, Baltimore, Maryland (B.T.G., M.L.R., P.N., J.H.G., H.M., T.M.N., B.S.K., P.M.H., R.B., D.R.T., M.G.B., A.R., A.G.).

Funding

Medical Scientist Training ProgramT32GM136577 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI ANDREA L COX · 2020 to 2026
$13.4M
EPIDEMIOLOGY AND BIOSTATISTICS OF AGINGT32AG000247 · NIA · JOHNS HOPKINS UNIVERSITY · PI Karen J. Bandeen-Roche · 1996 to 2026
$13.2M
NIA NIH HHS T32 AG000247NIGMS NIH HHS T32 GM136577
6 · The paper itself

Abstract

backgroundRisk factors for progression of coronavirus disease 2019 (COVID-19) to severe disease or death are underexplored in U.S. cohorts.

objectiveTo determine the factors on hospital admission that are predictive of severe disease or death from COVID-19.

designRetrospective cohort analysis.

settingFive hospitals in the Maryland and Washington, DC, area. PATIENTS: 832 consecutive COVID-19 admissions from 4 March to 24 April 2020, with follow-up through 27 June 2020. MEASUREMENTS: Patient trajectories and outcomes, categorized by using the World Health Organization COVID-19 disease severity scale. Primary outcomes were death and a composite of severe disease or death.

resultsMedian patient age was 64 years (range, 1 to 108 years); 47% were women, 40% were Black, 16% were Latinx, and 21% were nursing home residents. Among all patients, 131 (16%) died and 694 (83%) were discharged (523 [63%] had mild to moderate disease and 171 [20%] had severe disease). Of deaths, 66 (50%) were nursing home residents. Of 787 patients admitted with mild to moderate disease, 302 (38%) progressed to severe disease or death: 181 (60%) by day 2 and 238 (79%) by day 4. Patients had markedly different probabilities of disease progression on the basis of age, nursing home residence, comorbid conditions, obesity, respiratory symptoms, respiratory rate, fever, absolute lymphocyte count, hypoalbuminemia, troponin level, and C-reactive protein level and the interactions among these factors. Using only factors present on admission, a model to predict in-hospital disease progression had an area under the curve of 0.85, 0.79, and 0.79 at days 2, 4, and 7, respectively. LIMITATION: The study was done in a single health care system.

conclusionA combination of demographic and clinical variables is strongly associated with severe COVID-19 disease or death and their early onset. The COVID-19 Inpatient Risk Calculator (CIRC), using factors present on admission, can inform clinical and resource allocation decisions. PRIMARY FUNDING SOURCE: Hopkins inHealth and COVID-19 Administrative Supplement for the HHS Region 3 Treatment Center from the Office of the Assistant Secretary for Preparedness and Response.

Indexed as

HospitalizationHospital MortalitySeverity of Illness IndexAdolescentAdultAgedAged, 80 and overChildChild, PreschoolCOVID-19Disease ProgressionFemaleHumansInfantMaleMiddle Aged

Identifiers

PMID32960645
PMCPMC7530643

What OpenQuestion holds

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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.