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Record W4403150837 · doi:10.1186/s13613-024-01385-0

Heterogeneous impact of Sighs on mortality in patients with acute hypoxemic respiratory failure: insights from the PROTECTION study

2024· article· en· W4403150837 on OpenAlexaff
Emanuele Rezoagli, Carla Fornari, Roberto Fumagalli, Giacomo Grasselli, Carlo Alberto Volta, Paolo Navalesi, Rihard Knafelj, Laurent Brochard, Antonio Pesenti, Tommaso Mauri, Giuseppe Foti

Bibliographic record

VenueAnnals of Intensive Care · 2024
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
FundersEuropean Society of Intensive Care MedicineMinistero della Salute
KeywordsMedicineAnesthesiologyVentilation (architecture)Mechanical ventilationRandomized controlled trialTidal volumeAnesthesiaInternal medicinePositive end-expiratory pressureRespiratory systemCardiology

Abstract

fetched live from OpenAlex

Sigh breaths may impact outcomes in acute hypoxemic respiratory failure (AHRF) during assisted mechanical ventilation. We investigated whether sigh breaths may impact mortality in predefined subgroups of patients enrolled in the PROTECTION multicenter clinical trial according to: 1.the physiological response in oxygenation to Sigh (responders versus non-responders) and 2.the set levels of positive end-expiratory pressure (PEEP) (High vs. Low-PEEP). If mortality differed between Sigh and No Sigh, we explored physiological daily differences at 7-days. Patients were randomized to pressure support ventilation (PSV) with Sigh (Sigh group) versus PSV with no sigh (No Sigh group). (1) Sighs were not associated with differences in 28-day mortality in responders to baseline sigh-test. Contrarily-in non-responders-56 patients were randomized to Sigh (55%) and 28-day mortality was lower with sighs (17%vs.36%, log-rank p = 0.031). (2) In patients with PEEP > 8cmH 2 O no difference in mortality was observed with sighs. With Low-PEEP, 54 patients were randomized to Sigh (48%). Mortality at 28-day was reduced in patients randomised to sighs (13%vs.31%, log-rank p = 0.021). These findings were robust to multivariable adjustments. Tidal volume, respiratory rate and ventilatory ratio decreased with Sigh as compared with No Sigh at 7-days. Ventilatory ratio was associated with mortality and successful extubation in both non-responders and Low-PEEP. Addition of Sigh to PSV could reduce mortality in AHRF non-responder to Sigh and exposed to Low-PEEP. Results in non-responders were not expected. Findings in the low PEEP group may indicate that insufficient PEEP was used or that Low PEEP may be used with Sigh. Sigh may reduce mortality by decreasing physiologic dead space and ventilation intensity and/or optimizing ventilation/perfusion mismatch. Clinical Trial Registration : ClinicalTrials.gov; Identifier: NCT03201263.

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)0.006
metaresearch head score (Gemma)0.009
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 score0.006
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.058
GPT teacher head0.342
Teacher spread0.284 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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