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Phrenic Nerve Stimulation Decreases Biomarkers for Brain Injury in Deeply Sedated Mechanically Ventilated Moderate ARDS Patients

2025· article· en· W4410268745 on OpenAlexaff
Thiago Bassi, Elizabeth Rohrs, Steven Reynolds, Maxens Decavèle, Alexandre Demoule, Thomas Similowski, Martin Dres

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsFraser HealthRoyal Columbian HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineARDSAnesthesiaPhrenic nerveStimulationRespiratory systemLungInternal medicine

Abstract

fetched live from OpenAlex

Abstract INTRODUCTION: Preclinical studies have shown that mechanical ventilation (MV) is associated with increased serum concentration of biomarkers for brain injury. Restoring the respiratory drive by phrenic nerve stimulation in deeply sedated pigs led to a reduction in biomarkers for brain injury. This study investigated whether the preclinical findings of reduced biomarkers for brain injury were also observed in a clinical scenario by applying phrenic nerve stimulation in critically ill acute respiratory distress syndrome (ARDS) patients undergoing MV. METHODS: Twelve deeply sedated ARDS patients receiving invasive MV were included (ClinTrials.gov: NCT04844892). A central-line catheter embedded with electrodes was inserted via the left subclavian vein to stimulate the phrenic nerves bilaterally, in synchrony with MV. The study protocol was comprised of two hours without diaphragm neurostimulation (unpaced sessions), and two hours with diaphragm neurostimulation on every breath (paced sessions). All ventilator settings and administered medications remained unchanged during the study. Sedation infusions were also kept unchanged during the sessions. Blood samples for brain biomarkers (S100b, GFAP, UCHL-1, NSE, NfL and tau) were collected at baseline and the end of each session. We conducted an analysis comparing serum concentration at baseline versus at the study end (i.e., session 1 vs. session 4) using a paired Wilcoxon test due to the half-life of biomarkers for brain injury studied (between 30 minutes and 72 hours). P-values <0.05 were considered statistically significant. RESULTS: Serum concentrations of biomarkers of astrocyte injury, S100b (0.11 pg/ml vs 0.07 pg/ml, p<0.0001) and GFAP (169 pg/ml vs 130 pg/ml, p=0.0498) were statistically significantly reduced at the end of the study when compared to baseline serum concentrations (Figure). There was no significant change in the serum concentration of biomarkers for neuronal injury, tau (2 pg/ml vs 2 pg/ml, p=0.41), UCHL-1 (45 ng/ml vs 44ng/ml, p=0.35), NSE 14 pg/ml vs 11 pg/ml, p=0.15) and NfL (95 pg/ml vs 80 pg/ml, p=0.31) between the baseline and the end of the study. The median interquartile range for the Richmond Agitation-Sedation Scale was -5 (-4, -5). CONCLUSIONS: In deeply sedated MV moderate ARDS patients, diaphragm neurostimulation reduced biomarkers for brain injury. While promising and preliminary in nature, the results presented here may indicate the importance of phrenic nerve stimulation in brain protection in critically ill patients.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

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)0.0020.000

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 head0.015
GPT teacher head0.337
Teacher spread0.322 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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