Evidence map›Paper›PMID 38914601›Full record

Observational studyScientific reports2024

Re-thinking all-cause COVID-19 hospitalizations as a surrogate measure for severe illness in observational surveillance studies.

J Daniel Kelly, Samuel Leonard, W John Boscardin, Katherine J Hoggatt, Emily N Lum, Charles C Austin, Amy L Byers, Phyllis C Tien, Dawn M Bravata, Salomeh Keyhani

Abstract readObservational Study
In one paragraph

Observational study in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

J Daniel KellySan Francisco VA Medical Center, 4150 Clement Street 111A1, San Francisco, CA, 94121, USA. Dan.Kelly@ucsf.edu.
Samuel LeonardSan Francisco VA Medical Center, 4150 Clement Street 111A1, San Francisco, CA, 94121, USA.
W John BoscardinDepartment of Epidemiology and Biostatistics, UCSF, San Francisco, CA, USA.
Katherine J HoggattSan Francisco VA Medical Center, 4150 Clement Street 111A1, San Francisco, CA, 94121, USA.
Emily N LumSan Francisco VA Medical Center, 4150 Clement Street 111A1, San Francisco, CA, 94121, USA.
Charles C AustinDepartment of Veterans Affairs (VA) Health Services and Development (HSR&D) Center for Health Information and Communication (CHIC), Department of Medicine, Richard L. Roudebush VA Medical Center, Indianapolis, IN, USA.
Amy L ByersSan Francisco VA Medical Center, 4150 Clement Street 111A1, San Francisco, CA, 94121, USA.
Phyllis C TienSan Francisco VA Medical Center, 4150 Clement Street 111A1, San Francisco, CA, 94121, USA.
Dawn M BravataDepartment of Veterans Affairs (VA) Health Services and Development (HSR&D) Center for Health Information and Communication (CHIC), Department of Medicine, Richard L. Roudebush VA Medical Center, Indianapolis, IN, USA.
Salomeh KeyhaniSan Francisco VA Medical Center, 4150 Clement Street 111A1, San Francisco, CA, 94121, USA. Salomeh.Keyhani@ucsf.edu.

Funding

VAccine failure: natural history and determinants of post-vaccination Covid-19I01CX002417 · VA · VETERANS AFFAIRS MED CTR SAN FRANCISCO · PI John Daniel Kelly, Salomeh Keyhani · 2022 to 2026
–
Risks of Cannabis Use Among Veterans on Long-term Opioid TherapyI01HX002737 · VA · VETERANS AFFAIRS MED CTR SAN FRANCISCO · PI KEYHANI, SALOMEH · 2020 to 2024
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Gaps in Identification, Referral and Treatment of Cannabis Use in VA Primary CareI01HX003522 · VA · VETERANS AFFAIRS MED CTR SAN FRANCISCO · PI Carolyn Gibson, Salomeh Keyhani · 2023 to 2026
–
CSRD VA I01 CX002417HSRD VA I01 HX002737HSRD VA I01 HX003522
6 · The paper itself

Abstract

All-cause COVID-19 hospitalization ≤ 30 days of infection is a common outcome for severe illness in observational/surveillance studies. Milder COVID-19 disease and COVID-19-specific measurements calls for an evaluation of this endpoint. This was a descriptive, retrospective cohort study of adults ≥ 18 who were established in primary care at Veteran Health Administration (VHA) facilities. The outcome was hospitalization within 30 days of a laboratory-confirmed, symptomatic SARS-CoV-2 infection. Between December 15, 2021 and May 1, 2022, a simple random sample of all VA facilities, excluding Puerto Rico or Philippines, was drawn to identify these hospitalized cases and determine whether hospitalization was due to COVID-19-specific causes. A chart review was conducted to record the inpatient clinical team's diagnosis and whether the inpatient team classified the diagnosis as COVID-19 related or not. These data were used to classify hospitalizations as either due to COVID-19-specific causes (direct manifestations of SARS-CoV-2 infection) or non-COVID-19-specific hospitalizations (incidental SARS-CoV-2 infection), A simple random sample of 9966 (12.3%) all-cause hospitalizations (95% CI: 12.1%, 12.5%) was used to select 300 representative patients. Of these, 226/300 (75.3%) were determined to be COVID-19-specific. COVID-19 pneumonia was most common (147/226, 65.0%). The highest proportion of COVID-19-specific hospitalizations occurred among unvaccinated (85.0%), followed by vaccinated but not boosted (73.7%) and boosted (59.4%) (p < 0.001). The proportion of non-COVID-19-specific hospitalizations was higher in the later period (15-30 days: 55.0%) than the early (0-15 days: 22.5%) (p = 0.003). This study supports the outcome of COVID-19-specific hospitalization instead of all-cause hospitalization in observational studies. The earlier outcome period (0-15 days) was less susceptible to potential measurement bias.

Indexed as

COVID-19HospitalizationSARS-CoV-2AdultAgedFemaleHumansMaleMiddle AgedRetrospective StudiesSeverity of Illness IndexUnited States

Identifiers

PMID38914601
PMCPMC11196634

What OpenQuestion holds

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LicenceCC BY
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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.