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Record W3101454149 · doi:10.1016/j.chest.2020.10.079

Sigh in Patients With Acute Hypoxemic Respiratory Failure and ARDS

2020· article· en· W3101454149 on OpenAlexaff
Tommaso Mauri, Giuseppe Foti, Carla Fornari, Giacomo Grasselli, Riccardo Pinciroli, Federica Lovisari, Daniela Tubiolo, Carlo Alberto Volta, Savino Spadaro, Roberto Rona, Egle Rondelli, Paolo Navalesi, Eugenio Garofalo, Rihard Knafelj, Vojka Gorjup, Riccardo Colombo, Andrea Cortegiani, Zhou Jian-xin, Rocco D’Andrea, Italo Calamai, Ánxela Vidal González, Oriol Roca, Domenico Luca Grieco, Tomas Jovaiša, Dimitrios Bampalis, Tobias Becher, Denise Battaglini, Huiqing Ge, Mariana Luz, Jean‐Michel Constantin, Marco Ranieri, Claude Guérin, Jordi Mancebo, Paolo Pelosi, Roberto Fumagalli, Laurent Brochard, Antonio Pesenti, Plug working group of ESICM, Alessandra Papoff, Raffaele Di Fenza, Stefano Gianni, Elena Spinelli, Alfredo Lissoni, Chiara Abbruzzese, Alfio Bronco, Silvia Villa, Vincenzo Russotto, Arianna Iachi, Lorenzo Ball, Nicolò Patroniti, Rosario Spina, Romano Giuntini, Simone Peruzzi, Luca S. Menga, Tommaso Fossali, Antonio Castelli, Davide Ottolina, Marina García-de-Acilu, Manel M. Santafé, Dirk Schädler, Norbert Weiler, Emilia Rosas Carvajal, César Calvo, Evangelia Neou, Yumei Wang, Yimin Zhou, Federico Longhini, Andrea Bruni, Mariacristina Leonardi, Cesare Gregoretti, Mariachiara Ippolito, Zelia Milazzo, Lorenzo Querci, Serena Ranieri, Giulia Insom, Jernej Berden, Marko Noč, Urša Mikuž, Matteo Arzenton, Marta Lazzeri, Arianna Villa, Bruna Brandão Barreto, Marcos Nogueira Oliveira Rios, Dimitri Gusmao-Flores, Mandeep Phull, Tom Barnes, Hussain Musarat, Sara Conti

Bibliographic record

VenueCHEST Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsUniversity of Toronto
FundersEuropean Society of Intensive Care Medicine
KeywordsMedicineARDSVentilation (architecture)RandomizationClinical endpointTidal volumePressure support ventilationRandomized controlled trialOxygenationMechanical ventilationAnesthesiaAdverse effectPositive end-expiratory pressureMean airway pressureInternal medicineRespiratory systemLung

Abstract

fetched live from OpenAlex

BACKGROUND: Sigh is a cyclic brief recruitment maneuver: previous physiologic studies showed that its use could be an interesting addition to pressure support ventilation to improve lung elastance, decrease regional heterogeneity, and increase release of surfactant. RESEARCH QUESTION: Is the clinical application of sigh during pressure support ventilation (PSV) feasible? STUDY DESIGN AND METHODS: O for 3 s once per minute) until day 28 or death or successful spontaneous breathing trial. The primary end point of the study was feasibility, assessed as noninferiority (5% tolerance) in the proportion of patients failing assisted ventilation. Secondary outcomes included safety, physiologic parameters in the first week from randomization, 28-day mortality, and ventilator-free days. RESULTS: Two-hundred and fifty-eight patients (31% women; median age, 65 [54-75] years) were enrolled. In the sigh group, 23% of patients failed to remain on assisted ventilation vs 30% in the no-sigh group (absolute difference, -7%; 95% CI, -18% to 4%; P = .015 for noninferiority). Adverse events occurred in 12% vs 13% in the sigh vs no-sigh group (P = .852). Oxygenation was improved whereas tidal volume, respiratory rate, and corrected minute ventilation were lower over the first 7 days from randomization in the sigh vs no-sigh group. There was no significant difference in terms of mortality (16% vs 21%; P = .337) and ventilator-free days (22 [7-26] vs 22 [3-25] days; P = .300) for the sigh vs no-sigh group. INTERPRETATION: Among hypoxemic intubated ICU patients, application of sigh was feasible and without increased risk. TRIAL REGISTRY: ClinicalTrials.gov; No.: NCT03201263; URL: www.clinicaltrials.gov.

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)0.000
metaresearch head score (Gemma)0.003
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 score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.230
Teacher spread0.214 · 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".

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Citations34
Published2020
Admission routes1
Has abstractno

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