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Low Tidal Volume versus Non–Volume-Limited Strategies for Patients with Acute Respiratory Distress Syndrome. A Systematic Review and Meta-Analysis

2017· review· en· W2749127765 on OpenAlexaff
Allan J. Walkey, Ewan C. Goligher, Lorenzo Del Sorbo, Carol Hodgson, Neill K. J. Adhikari, Hannah Wunsch, Maureen O. Meade, Elizabeth Uleryk, Dean Hess, Daniel Talmor, Bruce Thompson, Roy G. Brower, Eddy Fan

Bibliographic record

VenueAnnals of the American Thoracic Society · 2017
Typereview
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsHospital for Sick ChildrenMcMaster UniversityUniversity Health NetworkToronto General HospitalUniversity of TorontoSunnybrook Health Science CentreHealth Sciences Centre
Fundersnot available
KeywordsMedicineMeta-analysisTidal volumeConfidence intervalMechanical ventilationRandomized controlled trialARDSClinical trialInternal medicineIntensive care medicineRespiratory systemLung

Abstract

fetched live from OpenAlex

Abstract Rationale Trials investigating use of lower tidal volumes and inspiratory pressures for patients with acute respiratory distress syndrome (ARDS) have shown mixed results. Objectives To compare clinical outcomes of mechanical ventilation strategies that limit tidal volumes and inspiratory pressures (LTV) to strategies with tidal volumes of 10 to 15 ml/kg among patients with ARDS. Methods This is a systematic review and meta-analysis of clinical trials investigating LTV mechanical ventilation strategies. We used random effects models to evaluate the effect of LTV on 28-day mortality, organ failure, ventilator-free days, barotrauma, oxygenation, and ventilation. Our primary analysis excluded trials for which the LTV strategy was combined with the additional strategy of higher positive end-expiratory pressure (PEEP), but these trials were included in a stratified sensitivity analysis. We performed metaregression of tidal volume gradient achieved between intervention and control groups on mortality effect estimates. We used Grading of Recommendations Assessment, Development, and Evaluation methodology to determine the quality of evidence. Results Seven randomized trials involving 1,481 patients met eligibility criteria for this review. Mortality was not significantly lower for patients receiving an LTV strategy (33.6%) as compared with control strategies (40.4%) (relative risk [RR], 0.87; 95% confidence interval [CI], 0.70–1.08; heterogeneity statistic I 2 = 46%), nor did an LTV strategy significantly decrease barotrauma or ventilator-free days when compared with a lower PEEP strategy. Quality of evidence for clinical outcomes was downgraded for imprecision. Metaregression showed a significant inverse association between larger tidal volume gradient between LTV and control groups and log odds ratios for mortality (β, −0.1587; P = 0.0022). Sensitivity analysis including trials that protocolized an LTV/high PEEP cointervention showed lower mortality associated with LTV (nine trials and 1,629 patients; RR, 0.80; 95% CI, 0.66–0.98; I 2 = 46%). Compared with trials not using a high PEEP cointervention, trials using a strategy of LTV combined with high PEEP showed a greater mortality benefit (RR, 0.58; 95% CI, 0.41–0.82; P for interaction = 0.05). Conclusions The trend toward lower mortality with LTV ventilation in the primary analysis and the significant relationship between the degree of tidal volume reduction and the mortality effect together suggest, but do not prove, that LTV ventilation improves mortality among critically ill adults with ARDS.

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)0.013
metaresearch head score (Gemma)0.027
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: Review · Consensus signal: Review
Teacher disagreement score0.024
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.027
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0240.039
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
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 head0.211
GPT teacher head0.446
Teacher spread0.235 · 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
GenreReview

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

Citations121
Published2017
Admission routes1
Has abstractyes

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