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Record W3158685742 · doi:10.1097/ccm.0000000000005049

Design of Clinical Trials Evaluating Sedation in Critically Ill Adults Undergoing Mechanical Ventilation: Recommendations From Sedation Consortium on Endpoints and Procedures for Treatment, Education, and Research (SCEPTER) Recommendation III

2021· article· en· W3158685742 on OpenAlexafffund
Denham S. Ward, Anthony Absalom, Leanne M. Aitken, Michele C. Balas, David Brown, Lisa Burry, Elizabeth Colantuoni, Douglas B. Coursin, John W. Devlin, Franklin Dexter, Robert H. Dworkin, Talmage D. Egan, Doug Elliott, Ingrid Egerod, Pamela Flood, Gilles L. Fraser, Timothy D. Girard, David Gozal, Ramona O. Hopkins, John P. Kress, Mervyn Maze, Dale M. Needham, Pratik P. Pandharipande, Richard R. Riker, Daniel I. Sessler, Steven L. Shafer, Yahya Shehabi, Claudia Spies, Lena S. Sun, Avery Tung, Richard D. Urman

Bibliographic record

VenueCritical Care Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsMount Sinai Hospital
FundersDaiichi Sankyo EuropeNational Heart, Lung, and Blood InstituteOffice of the President, University of CaliforniaMedical Center, University of RochesterGlenmark PharmaceuticalsNovartis PharmaU.S. Food and Drug AdministrationNational Institutes of HealthAstellas PharmaMcGill UniversityBaxter Healthcare CorporationUniversity of CambridgeBoston Scientific CorporationEVER Neuro PharmaPfizerBiogenUniversity of RochesterMedicines CompanyAcelRx PharmaceuticalsTeva Pharmaceutical IndustriesCelgeneGlaxoSmithKlineJohns Hopkins UniversityUniversité de MontréalAstraZenecaEli Lilly and CompanyAbbott Laboratories
KeywordsMedicineSedationMechanical ventilationCritically illIntensive care medicineClinical trialAnesthesiaInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: Clinical trials evaluating the safety and effectiveness of sedative medication use in critically ill adults undergoing mechanical ventilation differ considerably in their methodological approach. This heterogeneity impedes the ability to compare results across studies. The Sedation Consortium on Endpoints and Procedures for Treatment, Education, and Research Recommendations convened a meeting of multidisciplinary experts to develop recommendations for key methodologic elements of sedation trials in the ICU to help guide academic and industry clinical investigators. DESIGN: A 2-day in-person meeting was held in Washington, DC, on March 28-29, 2019, followed by a three-round, online modified Delphi consensus process. PARTICIPANTS: Thirty-six participants from academia, industry, and the Food and Drug Administration with expertise in relevant content areas, including two former ICU patients attended the in-person meeting, and the majority completed an online follow-up survey and participated in the modified Delphi process. MEASUREMENTS AND MAIN RESULTS: The final recommendations were iteratively refined based on the survey results, participants' reactions to those results, summaries written by panel moderators, and a review of the meeting transcripts made from audio recordings. Fifteen recommendations were developed for study design and conduct, subject enrollment, outcomes, and measurement instruments. Consensus recommendations included obtaining input from ICU survivors and/or their families, ensuring adequate training for personnel using validated instruments for assessments of sedation, pain, and delirium in the ICU environment, and the need for methodological standardization. CONCLUSIONS: These recommendations are intended to assist researchers in the design, conduct, selection of endpoints, and reporting of clinical trials involving sedative medications and/or sedation protocols for adult ICU patients who require mechanical ventilation. These recommendations should be viewed as a starting point to improve clinical trials and help reduce methodological heterogeneity in future clinical 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 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)0.004
metaresearch head score (Gemma)0.390
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.942
Threshold uncertainty score0.771

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.390
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.302
GPT teacher head0.554
Teacher spread0.252 · 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.

Study designOther design
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

Citations26
Published2021
Admission routes2
Has abstractyes

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