Evidence map›Paper›PMID 38937368›Full record

Observational studyJournal of general internal medicine2024

Analysis of Clinical Criteria for Discharge Among Patients Hospitalized for COVID-19: Development and Validation of a Risk Prediction Model.

Jeffrey L Schnipper, Sandra Oreper, Colin C Hubbard, Dax Kurbegov, Shanna A Arnold Egloff, Nader Najafi, Gilmer Valdes, Zishan Siddiqui, Kevin J O 'Leary, Leora I Horwitz and 2 more

Abstract readObservational StudyMulticenter StudyValidation Study
In one paragraph

Observational study in Journal of general internal medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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.

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

1 citing paper in PubMed.

  1. 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.

Jeffrey L SchnipperHospital Medicine Unit, Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, MA, USA. jschnipper@bwh.harvard.edu.ORCID 0000-0001-7072-0781
Sandra OreperDivision of Hospital Medicine, University of California, San Francisco, San Francisco, CA, USA.
Colin C HubbardDivision of Hospital Medicine, University of California, San Francisco, San Francisco, CA, USA.
Dax KurbegovCOVID-19 Consortium of HCA Healthcare and Academia for Research Generation (CHARGE), Nashville, TN, USA.
Shanna A Arnold EgloffCOVID-19 Consortium of HCA Healthcare and Academia for Research Generation (CHARGE), Nashville, TN, USA.
Nader NajafiDivision of Hospital Medicine, University of California, San Francisco, San Francisco, CA, USA.
Gilmer ValdesDivision of Hospital Medicine, University of California, San Francisco, San Francisco, CA, USA.
Zishan SiddiquiDivision of Hospital Medicine, John Hopkins University School of Medicine, Baltimore, MD, USA.
Kevin J O 'LearyDivision of Hospital Medicine, Northwestern University, Feinberg School of Medicine, Chicago, IL, USA.
Leora I HorwitzDepartment of Population Health, Department of Medicine, NYU Grossman School of Medicine; Center for Healthcare Innovation and Delivery Science, NYU Langone Health, New York City, NY, USA.
Tiffany LeeDivision of Hospital Medicine, University of California, San Francisco, San Francisco, CA, USA.
Andrew D AuerbachDivision of Hospital Medicine, University of California, San Francisco, San Francisco, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatients hospitalized with COVID-19 can clinically deteriorate after a period of initial stability, making optimal timing of discharge a clinical and operational challenge.

objectiveTo determine risks for post-discharge readmission and death among patients hospitalized with COVID-19.

designMulticenter retrospective observational cohort study, 2020-2021, with 30-day follow-up.

participantsAdults admitted for care of COVID-19 respiratory disease between March 2, 2020, and February 11, 2021, to one of 180 US hospitals affiliated with the HCA Healthcare system. MAIN MEASURES: Readmission to or death at an HCA hospital within 30 days of discharge was assessed. The area under the receiver operating characteristic curve (AUC) was calculated using an internal validation set (33% of the HCA cohort), and external validation was performed using similar data from six academic centers associated with a hospital medicine research network (HOMERuN). KEY

resultsThe final HCA cohort included 62,195 patients (mean age 61.9 years, 51.9% male), of whom 4704 (7.6%) were readmitted or died within 30 days of discharge. Independent risk factors for death or readmission included fever within 72 h of discharge; tachypnea, tachycardia, or lack of improvement in oxygen requirement in the last 24 h; lymphopenia or thrombocytopenia at the time of discharge; being ≤ 7 days since first positive test for SARS-CoV-2; HOSPITAL readmission risk score ≥ 5; and several comorbidities. Inpatient treatment with remdesivir or anticoagulation were associated with lower odds. The model's AUC for the internal validation set was 0.73 (95% CI 0.71-0.74) and 0.66 (95% CI 0.64 to 0.67) for the external validation set.

conclusionsThis large retrospective study identified several factors associated with post-discharge readmission or death in models which performed with good discrimination. Patients 7 or fewer days since test positivity and who demonstrate potentially reversible risk factors may benefit from delaying discharge until those risk factors resolve.

Indexed as

COVID-19Patient DischargePatient ReadmissionAdultAgedCohort StudiesFemaleHospitalizationHumansMaleMiddle AgedRetrospective StudiesRisk AssessmentRisk FactorsSARS-CoV-2COVID-19hospital readmissionrisk assessment

Identifiers

PMID38937368
PMCPMC11534938

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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.