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Record W6940028076 · doi:10.6084/m9.figshare.c.6090384

Effects of PEEP on regional ventilation-perfusion mismatch in the acute respiratory distress syndrome

2022· other· en· W6940028076 on OpenAlexaff

Bibliographic record

VenueFigshare · 2022
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsVentilation (architecture)Acute respiratory distressPositive end-expiratory pressureRespiratory distressMechanical ventilationPerfusion

Abstract

fetched live from OpenAlex

Abstract Purpose In the acute respiratory distress syndrome (ARDS), decreasing Ventilation-Perfusion $$\left( {{{\dot{V}} \mathord{\left/ {\vphantom {{\dot{V}} {\dot{Q}}}} \right. \kern-\nulldelimiterspace} {\dot{Q}}}} \right)$$ V ˙ / Q ˙ mismatch might enhance lung protection. We investigated the regional effects of higher Positive End Expiratory Pressure (PEEP) on $${{\dot{V}} \mathord{\left/ {\vphantom {{\dot{V}} {\dot{Q}}}} \right. \kern-\nulldelimiterspace} {\dot{Q}}}$$ V ˙ / Q ˙ mismatch and their correlation with recruitability. We aimed to verify whether PEEP improves regional $${{\dot{V}} \mathord{\left/ {\vphantom {{\dot{V}} {\dot{Q}}}} \right. \kern-\nulldelimiterspace} {\dot{Q}}}$$ V ˙ / Q ˙ mismatch, and to study the underlying mechanisms. Methods In fifteen patients with moderate and severe ARDS, two PEEP levels (5 and 15 cmH2O) were applied in random order. $${{\dot{V}} \mathord{\left/ {\vphantom {{\dot{V}} {\dot{Q}}}} \right. \kern-\nulldelimiterspace} {\dot{Q}}}$$ V ˙ / Q ˙ mismatch was assessed by Electrical Impedance Tomography at each PEEP. Percentage of ventilation and perfusion reaching different ranges of $${{\dot{V}} \mathord{\left/ {\vphantom {{\dot{V}} {\dot{Q}}}} \right. \kern-\nulldelimiterspace} {\dot{Q}}}$$ V ˙ / Q ˙ ratios were analyzed in 3 gravitational lung regions, leading to precise assessment of their distribution throughout different $${{\dot{V}} \mathord{\left/ {\vphantom {{\dot{V}} {\dot{Q}}}} \right. \kern-\nulldelimiterspace} {\dot{Q}}}$$ V ˙ / Q ˙ mismatch compartments. Recruitability between the two PEEP levels was measured by the recruitment-to-inflation ratio method. Results In the non-dependent region, at higher PEEP, ventilation reaching the normal $${{\dot{V}} \mathord{\left/ {\vphantom {{\dot{V}} {\dot{Q}}}} \right. \kern-\nulldelimiterspace} {\dot{Q}}}$$ V ˙ / Q ˙ compartment (p = 0.018) increased, while it decreased in the high $${{\dot{V}} \mathord{\left/ {\vphantom {{\dot{V}} {\dot{Q}}}} \right. \kern-\nulldelimiterspace} {\dot{Q}}}$$ V ˙ / Q ˙ one (p = 0.023). In the middle region, at PEEP 15 cmH2O, ventilation and perfusion to the low $${{\dot{V}} \mathord{\left/ {\vphantom {{\dot{V}} {\dot{Q}}}} \right. \kern-\nulldelimiterspace} {\dot{Q}}}$$ V ˙ / Q ˙ compartment decreased (p = 0.006 and p = 0.011) and perfusion to normal $${{\dot{V}} \mathord{\left/ {\vphantom {{\dot{V}} {\dot{Q}}}} \right. \kern-\nulldelimiterspace} {\dot{Q}}}$$ V ˙ / Q ˙ increased (p = 0.003). In the dependent lung, the percentage of blood flowing through the non-ventilated compartment decreased (p = 0.041). Regional $${{\dot{V}} \mathord{\left/ {\vphantom {{\dot{V}} {\dot{Q}}}} \right. \kern-\nulldelimiterspace} {\dot{Q}}}$$ V ˙ / Q ˙ mismatch improvement was correlated to lung recruitability and changes in regional tidal volume. Conclusions In patients with ARDS, higher PEEP optimizes the distribution of both ventilation (in the non-dependent areas) and perfusion (in the middle and dependent lung). Bedside measure of recruitability is associated with improved $${{\dot{V}} \mathord{\left/ {\vphantom {{\dot{V}} {\dot{Q}}}} \right. \kern-\nulldelimiterspace} {\dot{Q}}}$$ V ˙ / Q ˙ mismatch.

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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.018
GPT teacher head0.227
Teacher spread0.209 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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