MétaCan
Menu
Back to cohort

Temporal change, reproducibility, and interobserver variability in pressure-volume curves in adults with acute lung injury and acute respiratory distress syndrome

2003· article· en· W2074484212 on OpenAlexaff
Sangeeta Mehta, Thomas E. Stewart, Rod MacDonald, David Hallett, David Banayan, Stephen E. Lapinsky, Arthur S. Slutsky

Bibliographic record

VenueCritical Care Medicine · 2003
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsToronto Public HealthMount Sinai Hospital
Fundersnot available
KeywordsMedicineARDSLung volumesAnesthesiaReproducibilityIntensive careLungInternal medicineIntensive care medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: To assess the reproducibility of the static pressure-volume curve of the respiratory system by using a "mini-syringe" technique; to assess the temporal change in upper (UIP) and lower inflection points (LIP) measured from pressure-volume curves of the respiratory system; to assess the inter- and intraobserver variability in detection of the UIP and LIP in patients with acute lung injury (ALI)/acute respiratory distress syndrome (ARDS); and to compare the syringe and multiple occlusion techniques for determining LIP and UIP. DESIGN: Prospective observational study. SETTING: Academic medical-surgical critical care unit. PATIENTS: Consecutive patients with ALI or ARDS. INTERVENTIONS: Static inspiratory pressure-volume curves of the respiratory system were determined twice on day 1 of diagnosis of ALI/ARDS and then once daily for up to 6 days by using the syringe technique. Pressure-volume curves were determined from zero positive end-expiratory pressure. At each time point, three separate measurements of the pressure-volume curve were made to determine reproducibility. A 100-mL graduated syringe was used to inflate patients' lungs with 50- to 100-mL increments up to an airway pressure of 45 cm H2O or a total volume of 2 L; each volume step was maintained for 2-3 secs until a plateau airway pressure was recorded. On day 1, the static pressure-volume curve also was determined by using the multiple occlusion technique. In a random and blinded sequence, the pressure-volume curves were examined visually by three critical care physicians on three different occasions, to determine the intra- and interobserver variability in visual detection of the LIP and UIP. Observers were given objective instructions to visually identify LIP and UIP. MEASUREMENTS AND MAIN RESULTS: Eleven patients were enrolled, with a total of 134 pressure-volume curves generated. LIP and UIP could be detected in 90-94% and 61-68% of curves, respectively. When the three successive pressure-volume curves were compared, both the LIP and UIP were within 3 cm H2O in >65% of curves. The index of reliability (intraclass correlation coefficient) in LIP and UIP was 0.92 and 0.89 for interobserver variability and 0.90 and 0.88 for intraobserver variability. Daily variability was as high as 7 cm H2O for LIP and 5 cm H2O for UIP. When pressure-volume curves obtained by using the multiple occlusion and syringe techniques were compared, LIP was within 2 cm H2O, and UIP was within 4 cm H2O with the two techniques. CONCLUSIONS: The static pressure-volume curve of the respiratory system is reasonably reproducible, thus avoiding the need for multiple measurements at a single time. We found excellent interobserver and intraobserver correlation in manual identification of the LIP and UIP. Both LIP and UIP show appreciable daily variability in patients with ALI/ARDS. The multiple occlusion and syringe techniques generate similar values for LIP and UIP.

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)0.008
metaresearch head score (Gemma)0.038
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 score0.008
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.038
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.025
GPT teacher head0.319
Teacher spread0.294 · 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

Citations31
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueCritical Care MedicineSame topicRespiratory Support and MechanismsFrench-language works237,207