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Record W4399126278 · doi:10.14740/jocmr5145

Updated Bivalent COVID-19 Vaccines Reduce Risk of Hospitalization and Severe Outcomes in Adults: An Observational Cohort Study

2024· article· en· W4399126278 on OpenAlexvenueno aff
Nicholas Mielke, Steven Johnson, Charlotte O’Sullivan, Mohammad Usama Toseef, Amit Bahl

Bibliographic record

VenueJournal of Clinical Medicine Research · 2024
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineObservational studyCoronavirus disease 2019 (COVID-19)CohortBivalent (engine)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakCohort studyIntensive care medicinePediatricsVirologyInternal medicineInfectious disease (medical specialty)DiseaseOutbreak

Abstract

fetched live from OpenAlex

Background: This study evaluates the real-world effectiveness of updated bivalent coronavirus disease 2019 (COVID-19) vaccines in adults, as the virus evolves and the need for new vaccinations increases. Methods: In this observational, retrospective, multi-center, cohort analysis, we examined emergency care encounters with COVID-19 in metro Detroit, Michigan, from January 1, 2022, to March 9, 2023. Patients were categorized by vaccination status: unvaccinated, fully vaccinated, fully vaccinated and boosted (FV&B), or fully vaccinated and bivalent boosted (FV&BB). The primary outcome was to assess the impact of bivalent COVID-19 vaccinations on the risk of composite severe outcomes (intensive care unit (ICU) admission, mechanical ventilation, or death) among patients presenting to a hospital with a primary diagnosis of COVID-19. Results: A total of 21,439 encounters met inclusion criteria: 9,630 (44.9%) unvaccinated, 9,223 (43.0%) vaccinated, 2,180 (10.2%) FV&B, and 406 (1.9%) FV&BB. The average age was 48.8, with 59.6% female; 61.1% were White, 32.8% Black, and 6.0% other races. Severe disease affected 5.5% overall: 5.0% unvaccinated, 5.7% vaccinated, 7.0% FV&B, and 4.7% FV&BB (P = 0.001). Severe disease rates among admitted patients were 13.3% unvaccinated, 11.9% vaccinated, 12.2% boosted, and 8.1% FV&BB (P = 0.052). The FV&BB group showed a 4.0% (P = 0.0369) lower risk of severe disease compared to FV&B and a 5.1% (P = 0.0203) lower probability of hospitalization. Conclusions: As the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to mutate and evolve, updated vaccines are necessary to better combat COVID-19. In a real-world hospital-based population, this investigation demonstrates the incremental benefit of the bivalent booster vaccine in reducing the risk of hospitalization and severe outcomes in those diagnosed with COVID-19 compared to all other forms of vaccination.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.275
GPT teacher head0.573
Teacher spread0.297 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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