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Record W3049140083 · doi:10.1097/ccm.0000000000004585

Core Outcomes Set for Trials in People With Coronavirus Disease 2019

2020· article· en· W3049140083 on OpenAlexaff
Allison Tong, Julian Elliott, Luciano César Pontes Azevedo, Amanda Baumgart, Andrew D. Bersten, Lilia Cervantes, Derek P. Chew, Yeoungjee Cho, Tess E Cooper, Sally Crowe, Ivor S. Douglas, Nicole Evangelidis, Ella Flemyng, Elyssa Hannan, Peter Horby, Martin Howell, Jaehee Lee, Emma Liu, Eduardo Lorca, Deena Lynch, John C. Marshall, Andrea Matus González, Anne McKenzie, Karine Manera, Charlie McLeod, Sangeeta Mehta, Mervyn Mer, Andrew Conway Morris, Saad Nseir, Pedro Póvoa, Mark Reid, Yasser Sakr, Alan R Smyth, Tom Snelling, Giovanni FM Strippoli, Armando Teixeira‐Pinto, Antoní Torres, Tari Turner, Andrea K. Viecelli, Steve Webb, Paula Williamson, Laila Woc-Colburn, Junhua Zhang, Jonathan C. Craig

Bibliographic record

VenueCritical Care Medicine · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsUniversity of Toronto
FundersGenentechNational Institutes of HealthNational Institute for Health and Care ResearchNational Institute of Diabetes and Digestive and Kidney DiseasesUniversity of SydneyEquity TrusteesDavid and Elaine Potter FoundationWellcome TrustPfizer
KeywordsMedicineCoronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakCore (optical fiber)CoronavirusPandemicSet (abstract data type)BetacoronavirusCoronavirus InfectionsIntensive care medicineMEDLINEDiseaseVirologyInternal medicineInfectious disease (medical specialty)Outbreak

Abstract

fetched live from OpenAlex

OBJECTIVES: The outcomes reported in trials in coronavirus disease 2019 are extremely heterogeneous and of uncertain patient relevance, limiting their applicability for clinical decision-making. The aim of this workshop was to establish a core outcomes set for trials in people with suspected or confirmed coronavirus disease 2019. DESIGN: Four international online multistakeholder consensus workshops were convened to discuss proposed core outcomes for trials in people with suspected or confirmed coronavirus disease 2019, informed by a survey involving 9,289 respondents from 111 countries. The transcripts were analyzed thematically. The workshop recommendations were used to finalize the core outcomes set. SETTING: International. SUBJECTS: Adults 18 years old and over with confirmed or suspected coronavirus disease 2019, their family members, members of the general public and health professionals (including clinicians, policy makers, regulators, funders, researchers). INTERVENTIONS: None. MEASUREMENTS: None. MAIN RESULTS: Six themes were identified. "Responding to the critical and acute health crisis" reflected the immediate focus on saving lives and preventing life-threatening complications that underpinned the high prioritization of mortality, respiratory failure, and multiple organ failure. "Capturing different settings of care" highlighted the need to minimize the burden on hospitals and to acknowledge outcomes in community settings. "Encompassing the full trajectory and severity of disease" was addressing longer term impacts and the full spectrum of illness (e.g. shortness of breath and recovery). "Distinguishing overlap, correlation and collinearity" meant recognizing that symptoms such as shortness of breath had distinct value and minimizing overlap (e.g. lung function and pneumonia were on the continuum toward respiratory failure). "Recognizing adverse events" refers to the potential harms of new and evolving interventions. "Being cognizant of family and psychosocial wellbeing" reflected the pervasive impacts of coronavirus disease 2019. CONCLUSIONS: Mortality, respiratory failure, multiple organ failure, shortness of breath, and recovery are critically important outcomes to be consistently reported in coronavirus disease 2019 trials.

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)0.566
metaresearch head score (Gemma)0.603
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.434
Threshold uncertainty score0.535

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.5660.603
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.007
Bibliometrics0.0060.003
Science and technology studies0.0050.005
Scholarly communication0.0100.009
Open science0.0050.021
Research integrity0.0060.014
Insufficient payload (model declined to judge)0.0060.002

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 head0.501
GPT teacher head0.589
Teacher spread0.088 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designQualitative
DomainMethods
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

Citations66
Published2020
Admission routes1
Has abstractyes

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