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Record W4283121599 · doi:10.1093/cid/ciac476

The<i>Staphylococcus aureus</i>Network Adaptive Platform Trial Protocol: New Tools for an Old Foe

2022· article· en· W4283121599 on OpenAlexaff
Steven Y. C. Tong, Jocelyn Mora, Asha C Bowen, Matthew P. Cheng, Nick Daneman, Anna L. Goodman, George Heriot, Todd C. Lee, Roger Lewis, David Chien Lye, Robert K. Mahar, Julie Marsh, Anna McGlothlin, Zoe McQuilten, Susan C. Morpeth, David L. Paterson, David J. Price, Jason Roberts, James O. Robinson, Sebastiaan J. van Hal, Genevieve Walls, Steve Webb, Lyn Whiteway, Joshua S. Davis, Nick Anagnostou, Sophia Archuleta, Eugene Athan, Lauren Barina, Emma Best, Max Bloomfield, Jennifer Bostock, Carly L. Botheras, Philip N Britton, Hannah J. Burden, Anita J Campbell, Hannah Carter, Ka Lip Chew, Russel Lee Ming Chong, Geoffrey W. Coombs, Peter Daley, Jane C. Davies, Yael Dishon, Ravindra Dotel, Adrian Dunlop, Felicity Flack, Katie L. Flanagan, Hong Foo, Nesrin Ghanem‐Zoubi, Stefano Giulieri, Jennifer Grant, Dan Gregson, Stephen Guy, Amanda Gwee, Erica Hardy, Andrew Henderson, Benjamin P. Howden, Fleur Hudson, Jennie Johnstone, Shirin Kalimuddin, Dana de Kretser, Andrea Lay‐Hoon Kwa, Todd A. Lee, Amy Legg, Martin Llewelyn, Thomas Lumley, Derek R. MacFadden, Isabelle Malhamé, Michael Marks, Marianne Martinello, Gail Matthews, Colin McArthur, Genevieve McKew, Brendan McMullan, Eliza Milliken, Srinivas Murthy, Clare Nourse, Matthew O’Sullivan, Mical Paul, Neta Petersiel, Lina Petrella, Sarah Pett, Owen Robinson, Benedict D. Rogers, Benjamin R. Saville, Matthew Scarborough, Marc H. Scheetz, Oded Scheuerman, Kevin Schwartz, Simon Smith, Tom Snelling, Marta Soares, Christine Sommerville, Andrew J. Stewardson, Neil Stone, Archana Sud, Robert Tilley, R. Brigg Turner, Jonathan Underwood, Lesley Voss, Rachel Webb, Lynda Whiteway, Heather L. Wilson, Terence Wuerz

Bibliographic record

VenueClinical Infectious Diseases · 2022
Typearticle
Languageen
FieldMedicine
TopicAntifungal resistance and susceptibility
Canadian institutionsMcGill UniversityHealth Sciences CentreUniversity of TorontoSunnybrook Health Science CentreMcGill University Health Centre
FundersMedical Research Council
KeywordsMedicineStaphylococcus aureusProtocol (science)Staphylococcal infectionsMicrobiologyBacteriaBiologyGeneticsPathology

Abstract

fetched live from OpenAlex

Staphylococcus aureus bloodstream (SAB) infection is a common and severe infectious disease, with a 90-day mortality of 15%-30%. Despite this, <3000 people have been randomized into clinical trials of treatments for SAB infection. The limited evidence base partly results from clinical trials for SAB infections being difficult to complete at scale using traditional clinical trial methods. Here we provide the rationale and framework for an adaptive platform trial applied to SAB infections. We detail the design features of the Staphylococcus aureus Network Adaptive Platform (SNAP) trial that will enable multiple questions to be answered as efficiently as possible. The SNAP trial commenced enrolling patients across multiple countries in 2022 with an estimated target sample size of 7000 participants. This approach may serve as an exemplar to increase efficiency of clinical trials for other infectious disease syndromes.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.279
Threshold uncertainty score0.893

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.130
GPT teacher head0.421
Teacher spread0.291 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations101
Published2022
Admission routes1
Has abstractyes

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