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Record W3120183090 · doi:10.14740/jocmr4390

Optimal Upper Limits of Plateau Pressure for Patients With Acute Respiratory Distress Syndrome During the First Seven Days: A Meta-Regression Analysis

2021· article· en· W3120183090 on OpenAlexvenueno aff
Hideto Yasuda, Masamitsu Sanui, Tetsuro Nishimura, Tetsuro Kamo, Eishu Nango, Takayuki Abe, Rachel Roberts, Toru Takebayashi, Satoru Hashimoto, Alan Kawarai Lefor

Bibliographic record

VenueJournal of Clinical Medicine Research · 2021
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMechanical ventilationPlateau pressureConfidence intervalRelative riskMeta-analysisPlateau (mathematics)Internal medicineIntensive care unitRespiratory distressRandomized controlled trialHazard ratioSurgeryAcute respiratory distressLung

Abstract

fetched live from OpenAlex

Background: The effects of plateau pressure during the initial days of mechanical ventilation on outcomes for patients with acute respiratory distress syndrome have not been fully examined. We conducted meta-regression analysis of plateau pressure during the first 7 days using randomized control trials to investigate the optimal upper limits of plateau pressure on different days of mechanical ventilation. Methods: Randomized controlled trials comparing two mechanical ventilation strategies with lower and higher plateau pressures in patients with acute respiratory distress syndrome were included. Meta-regression analysis was performed to determine the association of plateau pressure with mortality on days 1, 3, and 7 of mechanical ventilation. Results: After evaluation of 2,975 citations from a comprehensive search across electronic databases, 14 studies were included in the final qualitative analysis. A total of 4,984 patients were included in the quantitative analysis. As a result of the pairwise comparison, overall short-term mortality was significantly higher for patients with plateau pressures over 32 cm H 2 O during the first 3 days after intensive care unit (ICU) admission (day 1: relative risk (RR), 0.77; 95% confidence interval (CI), 0.66 - 0.89; I 2 = 0%; day 3: RR, 0.76; 95% CI, 0.64 - 0.90; I 2 = 0%), but not on day 7 (RR, 0.82; 95% CI, 0.65 - 1.04; I 2 = 16%). Plateau pressures below 27 cm H 2 O and 30 cm H 2 O were not associated with an absolute risk reduction of short-term mortality. According to univariable meta-regression analysis, mortality was significantly associated with plateau pressure on day 1 (? = 0.01 (95% CI, 0.002 - 0.024), P = 0.02). On days 3 and 7, however, no significant difference was detected. When the cutoffs were set at 27, 30 and 32 cm H 2 O on day 1, which showed a significant difference, plateau pressure tended to be associated with increased mortality at pressures above the cut-off values, and there were no significant differences at pressures below the cut-off values, regardless of the cutoff used. Conclusions: This study suggests that the optimal cut-off value for plateau pressure may be 27 cm H 2 O especially during the initial period of mechanical ventilation, although this association may not continue during the latter period of mechanical ventilation. J Clin Med Res. 2021;13(1):48-63 doi: https://doi.org/10.14740/jocmr4390

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)0.027
metaresearch head score (Gemma)0.053
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.027
Threshold uncertainty score0.143

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.053
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0220.077
Bibliometrics0.0050.006
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0030.002
Research integrity0.0030.003
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 head0.162
GPT teacher head0.465
Teacher spread0.304 · 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 designMeta-analysis
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

Citations12
Published2021
Admission routes1
Has abstractyes

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