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Record W4381429298 · doi:10.1111/irv.13167

Clinical symptoms of SARS‐CoV‐2 breakthrough infection during the Omicron period in relation to baseline immune status and booster vaccination—A prospective multicentre cohort of health professionals (SURPRISE study)

2023· article· en· W4381429298 on OpenAlexaff
Philipp Köhler, Baharak Babouee Flury, Sabine Güsewell, Thomas Egger, Onício Leal Neto, Angela Brucher, Eva Lemmenmeier, Dorette Meier Kleeb, Jens Carsten Möller, Manuela Ortner, Philip Rieder, Markus Ruetti, H. H. Schmid, Reto Stocker, Danielle Vuichard‐Gysin, Oliver Speer, Benedikt Wiggli, Ulrike Besold, Allison McGeer, Lorenz Risch, Andrée Friedl, Matthias Schlegel, Pietro Vernazza, Christian R. Kahlert, Stefan P. Kuster

Bibliographic record

VenueInfluenza and Other Respiratory Viruses · 2023
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsSinai Health System
FundersBundesamt für Gesundheit
KeywordsMedicineVaccinationImmunityBooster (rocketry)Prospective cohort studyBooster doseClinical trialCohortImmune systemInternal medicinePhysical therapyImmunologyImmunization

Abstract

fetched live from OpenAlex

The effects of different types of pre-existing immunity on the frequency of clinical symptoms caused by the SARS-CoV-2 breakthrough infection were prospectively assessed in healthcare workers during the Omicron period. Among 518 participants, hybrid immunity was associated with symptom reduction for dizziness, muscle or limb pain and headache as compared to vaccination only. Moreover, the frequencies of dizziness, cough and muscle or limb pain were lower in participants who had received a booster vaccine dose. Thus, hybrid immunity appeared to be superior in preventing specific symptoms during breakthrough infection compared to vaccination alone. A booster vaccine dose conferred additional symptom reduction.

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)0.001
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.108
GPT teacher head0.465
Teacher spread0.357 · 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

Citations7
Published2023
Admission routes1
Has abstractyes

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