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Record W4210990743 · doi:10.1186/s13613-022-00988-9

Sequential lateral positioning as a new lung recruitment maneuver: an exploratory study in early mechanically ventilated Covid-19 ARDS patients

2022· article· en· W4210990743 on OpenAlexaff
Rollin Roldán, Shalim Rodriguez, Fernando Barriga, Mauro R. Tucci, Marcus Victor, Glasiele Alcala, Renán Villamonte, Fernando Suárez-Sipmann, Marcelo B. P. Amato, Laurent Brochard, Gerardo Tusman

Bibliographic record

VenueAnnals of Intensive Care · 2022
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsMuscular Dystrophy CanadaSt. Michael's Hospital
FundersDirección General de Universidades e Investigación
KeywordsARDSAnesthesiologyCoronavirus disease 2019 (COVID-19)Medicine2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Intensive care medicinePain medicineEmergency medicinePandemicMechanical ventilationLungInternal medicineAnesthesiaVirologyOutbreakInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

A sequential change in body position from supine-to-both lateral positions under constant ventilatory settings could be used as a postural recruitment maneuver in case of acute respiratory distress syndrome (ARDS), provided that sufficient positive end-expiratory pressure (PEEP) prevents derecruitment. This study aims to evaluate the feasibility and physiological effects of a sequential postural recruitment maneuver in early mechanically ventilated COVID-19 ARDS patients. A cohort of 15 patients receiving lung-protective mechanical ventilation in volume-controlled with PEEP based on recruitability were prospectively enrolled and evaluated in five sequentially applied positions for 30 min each: Supine-baseline; Lateral-1st side; 2nd Supine; Lateral-2nd side; Supine-final. PEEP level was selected using the recruitment-to-inflation ratio (R/I ratio) based on which patients received PEEP 12 cmH2O for R/I ratio ≤ 0.5 or PEEP 15 cmH2O for R/I ratio > 0.5. At the end of each period, we measured respiratory mechanics, arterial blood gases, lung ultrasound aeration, end-expiratory lung impedance (EELI), and regional distribution of ventilation and perfusion using electric impedance tomography (EIT). Comparing supine baseline and final, respiratory compliance (29 ± 9 vs 32 ± 8 mL/cmH2O; p < 0.01) and PaO2/FIO2 ratio (138 ± 36 vs 164 ± 46 mmHg; p < 0.01) increased, while driving pressure (13 ± 2 vs 11 ± 2 cmH2O; p < 0.01) and lung ultrasound consolidation score decreased [5 (4–5) vs 2 (1–4); p < 0.01]. EELI decreased ventrally (218 ± 205 mL; p < 0.01) and increased dorsally (192 ± 475 mL; p = 0.02), while regional compliance increased in both ventral (11.5 ± 0.7 vs 12.9 ± 0.8 mL/cmH2O; p < 0.01) and dorsal regions (17.1 ± 1.8 vs 18.8 ± 1.8 mL/cmH2O; p < 0.01). Dorsal distribution of perfusion increased (64.8 ± 7.3% vs 66.3 ± 7.2%; p = 0.01). Without increasing airway pressure, a sequential postural recruitment maneuver improves global and regional respiratory mechanics and gas exchange along with a redistribution of EELI from ventral to dorsal lung areas and less consolidation. Trial registration ClinicalTrials.gov, NCT04475068. Registered 17 July 2020, https://clinicaltrials.gov/ct2/show/NCT04475068

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)0.001
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.156
GPT teacher head0.405
Teacher spread0.249 · 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".

Quick stats

Citations47
Published2022
Admission routes1
Has abstractyes

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