Evidence map›Paper›PMID 38832632›Full record

ArticleHuman vaccines & immunotherapeutics2024

Vaccination status and disease severity of COVID-19 in different phases of the pandemic.

Xueying Yang, Fanghui Shi, Jiajia Zhang, Haoyuan Gao, Shujie Chen, Bankole Olatosi, Sharon Weissman, Xiaoming Li

Abstract read
In one paragraph

Article in Human vaccines & immunotherapeutics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Predicting the severity of COVID-19 using machine learning methods.BMC medical informatics and decision making · 2026
    Article
  2. Review
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.

Xueying YangSouth Carolina SmartState Center for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA.
Fanghui ShiSouth Carolina SmartState Center for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA.ORCID 0000-0002-5603-5398
Jiajia ZhangSouth Carolina SmartState Center for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA.
Haoyuan GaoSouth Carolina SmartState Center for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA.
Shujie ChenSouth Carolina SmartState Center for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA.
Bankole OlatosiSouth Carolina SmartState Center for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA.
Sharon WeissmanSouth Carolina SmartState Center for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA.
Xiaoming LiSouth Carolina SmartState Center for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA.

Funding

Multilevel Determinants of Racial and Ethnic Disparities in Maternal Morbidity and Mortality in the Context of COVID-19 PandemicR01AI127203 · NIAID · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI LI, XIAOMING, LIU, JIHONG · 2017 to 2021
$5.2M
The COVID-19 vaccine efficacy among people living with and without HIV: a real-world data approachR21AI170159 · NIAID · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI YANG, XUEYING · 2022 to 2023
$398k
NIAID NIH HHS R01 AI127203NIAID NIH HHS R21 AI170159
6 · The paper itself

Abstract

This study aimed to explore the clinical profile and the impact of vaccination status on various health outcomes among COVID-19 patients diagnosed in different phases of the pandemic, during which several variants of concern (VOCs) circulated in South Carolina (SC). The current study included 861,526 adult COVID-19 patients diagnosed between January 2021 and April 2022. We extracted their information about demographic characteristics, vaccination, and clinical outcomes from a statewide electronic health record database. Multiple logistic regression models were used to compare clinical outcomes by vaccination status in different pandemic phases, accounting for key covariates (e.g. historical comorbidities). A reduction in mortality was observed among COVID-19 patients during the whole study period, although there were fluctuations during the Delta and Omicron dominant periods. Compared to non-vaccinated patients, full-vaccinated COVID-19 patients had lower mortality in all dominant variants, including Pre-alpha (adjusted odds ratio [aOR]: 0.33; 95%CI: 0.15-0.72), Alpha (aOR: 0.58; 95%CI: 0.42-0.82), Delta (aOR: 0.28; 95%CI: 0.25-0.31), and Omicron (aOR: 0.29; 95%CI: 0.26-0.33) phases. Regarding hospitalization, full-vaccinated parties showed lower risk of hospitalization than non-vaccinated patients in Delta (aOR: 0.44; 95%CI: 0.41-0.47) and Omicron (aOR: 0.53; 95%CI: 0.50-0.57) dominant periods. The findings demonstrated the protection effect of the COVID-19 vaccines against all VOCs, although some of the full-vaccinated population still have symptoms to varying degrees from COVID-19 disease at different phases of the pandemic.

Indexed as

COVID-19COVID-19 VaccinesSARS-CoV-2AdultAgedAged, 80 and overFemaleHospitalizationHumansMaleMiddle AgedPandemicsSeverity of Illness IndexSouth CarolinaVaccinationYoung AdultCOVID-19 VaccinesCOVID-19disease severitySouth Carolinavaccinevariants of concern

Identifiers

PMID38832632
PMCPMC11152109

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.