Evidence map›Paper›PMID 35547844›Full record

ArticlemedRxiv : the preprint server for health sciences2022

Trends in non-COVID-19 hospitalizations prior to and during the COVID-19 pandemic period, United States, 2017 – 2021.

Kelsie Cassell, Casey M Zipfel, Shweta Bansal, Daniel M Weinberger

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2022. 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, 7 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Kelsie CassellDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven CT, USA.
Casey M ZipfelDepartment of Biology, Georgetown University, Washington DC, USA.
Shweta BansalDepartment of Biology, Georgetown University, Washington DC, USA.
Daniel M WeinbergerDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven CT, USA.
Georgetown University · USYale University · US

Funding

Vaccine hesitancy and erosion of herd immunity: harnessing big data to forecast disease re-emergenceR01GM123007 · NIGMS · GEORGETOWN UNIVERSITY · PI BANSAL, SHWETA · 2017 to 2021
$2.1M
Estimating the association between TNF inhibitors and Legionnaires' diseaseF31AI161971 · NIAID · YALE UNIVERSITY · PI CASSELL, KELSIE · 2022 to 2023
$84k
NIAID NIH HHS F31 AI161971NIGMS NIH HHS R01 GM123007
6 · The paper itself

Abstract

COVID-19 pandemic-related shifts in healthcare utilization, in combination with trends in non-COVID-19 disease transmission and NPI use, had clear impacts on infectious and chronic disease hospitalization rates. Using a national healthcare billing database (C19RDB), we estimated the monthly incidence rate ratio of hospitalizations between March 2020 and June 2021 according to 19 ICD-10 diagnostic chapters and 189 subchapters. The majority of hospitalization causes showed an immediate decline in incidence during March 2020. Hospitalizations for diagnoses such as reproductive neoplasms, hypertension, and diabetes returned to pre-pandemic norms in incidence during late 2020 and early 2021, while others, like those for infectious respiratory disease, never returned to pre-pandemic norms. These results are crucial for contextualizing future research, particularly time series analyses, utilizing surveillance and hospitalization data for non-COVID-19 disease. Our assessment of subchapter level primary hospitalization codes offers new insight into trends among less frequent causes of hospitalization during the COVID-19 pandemic.

Identifiers

PMID35547844
PMCPMC9094108
OpenAlexW4225146126

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.