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Record W4361238647 · doi:10.1093/ofid/ofad150

Antibody Response After Third Vaccination With mRNA-1273 or BNT162b2: Extension of a Randomized Controlled SARS-CoV-2 Noninferiority Vaccine Trial in Patients With Different Levels of Immunosuppression (COVERALL-2)

2023· article· en· W4361238647 on OpenAlexaff
Alexandra Griessbach, Frédérique Chammartin, Irène A. Abela, Patrizia Amico, Marcel Stoeckle, Anna Eichenberger, Barbara Hasse, Dominique L. Braun, Macé M. Schuurmans, Thomas F. Müller, Michael Tamm, Annette Audigé, Nicolas J. Mueller, Andri Rauch, Huldrych F. Günthard, Michael Koller, Alexandra Trkola, Selina Epp, Alain Amstutz, Christof Schönenberger, Ala Taji Heravi, Katharina Kusejko, Heiner C. Bucher, Matthias Briel, Benjamin Speich, Karoline Aebi‐Popp, A Anagnostopoulos, Manuel Battegay, Enos Bernasconi, Alexandra Calmy, Matthias Cavassini, Angela Ciuffi, G Dollenmaier, Matthias Egger, Luigia Elzi, Jan Fehr, Jacques Fellay, Hansjakob Furrer, Christoph A. Fux, Anna Hachfeld, D Haerry, Hans H. Hirsch, Matthias Hoffmann, Irène Hösli, Michael Huber, David Jackson‐Perry, Christian R. Kahlert, Laurent Kaiser, Olivia Keiser, Thomas Klimkait, Roger D. Kouyos, Helen Kovari, Niklaus Daniel Labhardt, Karoline Leuzinger, Begoña Martínez de Tejada, Catia Marzolini, Karin J. Metzner, N Müller, Johannes Nemeth, Dunja Nicca, Julia Notter, P Paioni, Giuseppe Pantaleo, Matthieu Perreau, Luisa Salazar‐Vizcaya, Patrick Schmid, R Speck, M Stöckle, Philip Tarr, Gilles Wandeler, Maja Weisser, Sabine Yerly, John‐David Aubert, Vanessa Banz, Sonja Beckmann, Guido Beldi, Christoph Berger, Ekaterine Berishvili, Annalisa Berzigotti, Isabelle Binet, Pierre–Yves Bochud, Sanda Branca, Anne Cairoli, Yves Chalandon, Sabina De Geest, Olivier de Rougemont, Sophie de Seigneux, Michael Dickenmann, Joëlle Lynn Dreifuss, Michel A. Duchosal, Thomas Fehr, Sylvie Ferrari-Lacraz, Christian Garzoni, Déla Golshayan, Nicolas Goossens, Fadi Haidar, Jörg Halter, Dominik Heim, Christoph Hess, Sven Hillinger, Patricia Hirt, Linard Hoessly, Günther F.L. Hofbauer, Uyen Huynh‐Do, Franz Immer, Bettina Laesser, Frédéric Lamoth, Roger Lehmann, Alexander Leichtle, Oriol Manuel, Hans‐Peter Marti, Michele Martinelli, Valérie A. McLin, Katell Mellac, Aurélia Merçay, Karin Mettler, Ulrike Müller-Arndt, Beat Müllhaupt, Mirjam Nägeli, Graziano Oldani, Manuel Pascual, Jakob Passweg, Rosemarie Pazeller, Klara M. Posfay‐Barbe, Juliane Rick, Anne Rosselet, Simona Rossi, Silvia Rothlin, Frank Ruschitzka, Stefan Schaub, Alexandra Scherrer, Aurelia Schnyder, Simon Schwab, Thierry Sengstag, Federico Simonetta, Susanne Stampf, Jürg Steiger, Guido Stirnimann, Ueli Stürzinger, Christian van Delden, Jean-Pierre Venetz, Jean Villard, Julien Vionnet, Madeleine Wick, Markus J. Wilhelm, Patrick Yerly

Bibliographic record

VenueOpen Forum Infectious Diseases · 2023
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsMcMaster UniversityImpact
FundersUZH FoundationPromedica StiftungModernaOPEC Fund for International DevelopmentViiV HealthcareUniversität BaselNational Institutes of HealthSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungGilead SciencesSanofiUniversität ZürichPfizerNational Science Foundation
KeywordsMedicineImmunosuppressionConfidence intervalAntibody responseVaccinationRandomized controlled trialSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Coronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakAntibodyImmunologyVirologyInternal medicineOutbreak

Abstract

fetched live from OpenAlex

Extension of the COVERALL (COrona VaccinE tRiAL pLatform) randomized trial showed noninferiority in antibody response of the third dose of Moderna mRNA-1273 vaccine (95.3% [95% confidence interval {CI}, 91.9%-98.7%]) compared to Pfizer-BioNTech BNT162b2 vaccine (98.1% [95% CI, 95.9%-100.0%]) in individuals with different levels of immunosuppression (difference, -2.8% [95% CI, -6.8% to 1.3%]).

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.022
GPT teacher head0.349
Teacher spread0.328 · 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 designRandomized trial
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

Citations9
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueOpen Forum Infectious Diseases→Same topicSARS-CoV-2 and COVID-19 Research→French-language works237,207→