Evidence map›Paper›PMID 34400452›Full record

Observational studyBMJ open2021

Temporal trends of COVID-19 mortality and hospitalisation rates: an observational cohort study from the US Department of Veterans Affairs.

Miao Cai, Benjamin Bowe, Yan Xie, Ziyad Al-Aly

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in BMJ open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
3.6field-weighted citation impact, top 5% 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

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 46 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. The impact of COVID-19 and COVID vaccination on cardiovascular outcomes.European heart journal supplements : journal of the European Society of Cardiology · 2023
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

4 authors at 2 institutions in 1 country.

Miao CaiClinical Epidemiology Center, VA Saint Louis Health Care System, Saint Louis, Missouri, USA.ORCID 0000-0003-0170-6905
Benjamin BoweClinical Epidemiology Center, VA Saint Louis Health Care System, Saint Louis, Missouri, USA.
Yan XieClinical Epidemiology Center, VA Saint Louis Health Care System, Saint Louis, Missouri, USA.ORCID 0000-0002-2457-9382
Ziyad Al-AlyClinical Epidemiology Center, VA Saint Louis Health Care System, Saint Louis, Missouri, USA zalaly@gmail.com.ORCID 0000-0002-2600-0434
VA St. Louis Health Care System · USWashington University in St. Louis · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo investigate the temporal trends of 30-day mortality and hospitalisation in US Veterans with COVID-19 and 30-day mortality in hospitalised veterans with COVID-19 and to decompose the contribution of changes in the underlying characteristics of affected populations to these temporal changes.

designObservational cohort study.

settingUS Department of Veterans Affairs.

participants49 238 US veterans with a positive COVID-19 test between 20 March 2020 and 19 September 2020; and 9428 US veterans hospitalised with a positive COVID-19 test during the same period. OUTCOME MEASURES: 30-day mortality rate and hospitalisation rate.

resultsBetween 20 March 2020 and 19 September 2020 and in COVID-19 positive individuals, 30-day mortality rate dropped by 9.2% from 13.6% to 4.4%; hospitalisation rate dropped by 16.8% from 33.8% to 17.0%. In hospitalised COVID-19 individuals, 30-day mortality rate dropped by 12.7% from 23.5% to 10.8%. Among COVID-19 positive individuals, decomposition analyses suggested that changes in demographic, health and contextual characteristics, COVID-19 testing capacity, and hospital occupancy rates accounted for 40.2% and 33.3% of the decline in 30-day mortality and hospitalisation, respectively. Changes in the underlying characteristics of hospitalised COVID-19 individuals accounted for 29.9% of the decline in 30-day mortality.

conclusionBetween March and September 2020, changes in demographic and health characteristics of people infected with COVID-19 contributed measurably to the substantial decline in 30-day mortality and hospitalisation.

Indexed as

COVID-19VeteransCohort StudiesCOVID-19 TestingHospitalizationHumansSARS-CoV-2United StatesCOVID-19epidemiologygeneral medicine (see internal medicine)

Identifiers

PMID34400452
PMCPMC8370839
OpenAlexW3194103068

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.