Evidence map›Paper›PMID 35391623›Full record

Observational studyJournal of general internal medicine2022

Factors Associated with Post-Acute Sequelae of SARS-CoV-2 (PASC) After Diagnosis of Symptomatic COVID-19 in the Inpatient and Outpatient Setting in a Diverse Cohort.

Sun M Yoo, Teresa C Liu, Yash Motwani, Myung S Sim, Nisha Viswanathan, Nathan Samras, Felicia Hsu, Neil S Wenger

Open access · hybridAbstract readObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in Journal of general internal medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
73citing papers in PubMed, 3 pooled it
15.4field-weighted citation impact, top 1% 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

73 citing papers in PubMed, 3 syntheses or guidelines pooled it, 125 citations in OpenAlex.

  1. Pooled it
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  4. Long COVID After Bamlanivimab Treatment.The Journal of infectious diseases · 2023
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13 more citing papers are in PubMed but not listed here.

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

8 authors at 1 institution in 1 country.

Sun M YooDepartment of Medicine, David Geffen School of Medicine, University of California, Los Angeles, 757 Westwood Plaza, Los Angeles, CA, 90095, USA. smyoo@mednet.ucla.edu.ORCID 0000-0001-8410-0639
Teresa C LiuDepartment of Medicine, David Geffen School of Medicine, University of California, Los Angeles, 757 Westwood Plaza, Los Angeles, CA, 90095, USA.
Yash MotwaniDepartment of Medicine, David Geffen School of Medicine, University of California, Los Angeles, 757 Westwood Plaza, Los Angeles, CA, 90095, USA.
Myung S SimDepartment of Medicine, David Geffen School of Medicine, University of California, Los Angeles, 757 Westwood Plaza, Los Angeles, CA, 90095, USA.
Nisha ViswanathanDepartment of Medicine, David Geffen School of Medicine, University of California, Los Angeles, 757 Westwood Plaza, Los Angeles, CA, 90095, USA.
Nathan SamrasDepartment of Medicine, David Geffen School of Medicine, University of California, Los Angeles, 757 Westwood Plaza, Los Angeles, CA, 90095, USA.
Felicia HsuDepartment of Medicine, David Geffen School of Medicine, University of California, Los Angeles, 757 Westwood Plaza, Los Angeles, CA, 90095, USA.
Neil S WengerDepartment of Medicine, David Geffen School of Medicine, University of California, Los Angeles, 757 Westwood Plaza, Los Angeles, CA, 90095, USA.
University of California, Los Angeles · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe incidence of persistent clinical symptoms and risk factors in Post-Acute Sequelae of SARS-CoV-2 (PASC) in diverse US cohorts is unclear. While there are a disproportionate share of COVID-19 deaths in older patients, ethnic minorities, and socially disadvantaged populations in the USA, little information is available on the association of these factors and PASC.

objectiveTo evaluate the association of demographic and clinical characteristics with development of PASC.

designProspective observational cohort of hospitalized and high-risk outpatients, April 2020 to February 2021.

participantsOne thousand thirty-eight adults with laboratory-confirmed symptomatic COVID-19 infection. MAIN MEASURES: Development of PASC determined by patient report of persistent symptoms on questionnaires conducted 60 or 90 days after COVID-19 infection or hospital discharge. Demographic and clinical factors associated with PASC. KEY

resultsOf 1,038 patients with longitudinal follow-up, 309 patients (29.8%) developed PASC. The most common persistent symptom was fatigue (31.4%) followed by shortness of breath (15.4%) in hospitalized patients and anosmia (15.9%) in outpatients. Hospitalization for COVID-19 (odds ratio [OR] 1.49, 95% [CI] 1.04-2.14), having diabetes (OR, 1.39; 95% CI 1.02-1.88), and higher BMI (OR, 1.02; 95% CI 1-1.04) were independently associated with PASC. Medicaid compared to commercial insurance (OR, 0.49; 95% CI 0.31-0.77) and having had an organ transplant (OR 0.44, 95% CI, 0.26-0.76) were inversely associated with PASC. Age, race/ethnicity, Social Vulnerability Index, and baseline functional status were not associated with developing PASC.

conclusionsThree in ten survivors with COVID-19 developed a subset of symptoms associated with PASC in our cohort. While ethnic minorities, older age, and social disadvantage are associated with worse acute COVID-19 infection and greater risk of death, our study found no association between these factors and PASC.

Indexed as

COVID-19SARS-CoV-2AdultAgedComorbidityHumansInpatientsOutpatientsUnited States

Identifiers

PMID35391623
PMCPMC8989256
OpenAlexW4223591870

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.