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Feasibility of Measuring Driving Pressure and Patient Effort in Assisted Modes of Ventilation: An Observational Study

2025· article· en· W4410268248 on OpenAlexaffabout
Maheen Farooqi, Michael Mikhaeil, J. Chen, Mohamed Althobity, Alisha Greer, Arya M. Sharma, Kathleen Lewis, Thomas Piraino, D.J. Cook, Bram Rochwerg

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineObservational studyIntensive care medicineMechanical ventilationVentilation (architecture)Emergency medicineMedical emergencyAnesthesiaInternal medicineMechanical engineeringEngineering

Abstract

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Abstract Rationale Driving pressure (DP) has established prognostic significance in patients receiving controlled modes of ventilation (CMV). During assisted ventilation, DP is influenced by negative pressure generated through patient effort and can be measured using an end-inspiratory hold maneuver. However, the feasibility of obtaining acceptable measurements in lightly sedated or awake patients is uncertain. We aimed to determine if measuring driving pressure and estimating patient effort was feasible in patients receiving pressure support ventilation (PSV). Methods We conducted a prospective observational cohort study in three adult intensive care units at McMaster University (Hamilton, Canada). We included adult patients who were mechanically ventilated on CMV and switched to PSV within 48 hours. End-inspiratory holds were conducted to obtain DP (plateau pressure – positive end-expiratory pressure) and pressure muscle index (PMI, peak airway pressure – plateau pressure) which is a marker of patient effort. The primary outcome was feasibility rate, determined by the percentage of acceptable inspiratory holds (duration of occlusion over 2 seconds, airflow equal to 0 ml/sec during the hold, absence of visible patient effort). Sedation was assessed using the Richmond Agitation Sedation Scale (RASS). We compared driving pressure, PMI and P0.1 between survivors and non-survivors using t-tests (p-value of 0.05 for statistical significance). Results In total, we enrolled 100 patients and performed 302 end-inspiratory holds. Of these, 29 were deemed unacceptable, resulting in a 90% feasibility rate. The most common reasons for an unacceptable measurement were tachypnea (respiratory rate >30) (11, 38%) or agitation (RASS ≥3+)(18, 62%). When comparing 30-day survivors (n=71) and non-survivors (n=26), there were no important differences in DP and PMI (Table). Average daily RASS was -1 [-2,0]. Conclusions Measuring driving pressure and patient effort using PMI in those receiving assisted ventilation is feasible and may provide insight into respiratory system compliance (as determined by driving pressure) and patient effort. Measurements are straightforward, easy to learn, take seconds and can be conducted at the bedside without complication, even in awake patients who are not agitated or tachypneic (respiratory rate >30). Further studies are needed to determine if this information can be used to guide clinical decision-making and weaning efforts. Funding source: Physician Services Incorporated (PSI)

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)0.002
metaresearch head score (Gemma)0.006
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.080
GPT teacher head0.381
Teacher spread0.301 · 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
Published2025
Admission routes2
Has abstractyes

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