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Record W2096503141 · doi:10.1164/rccm.200207-782oc

Treatment of Acute Respiratory Distress Syndrome with Recombinant Surfactant Protein C Surfactant

2003· article· en· W2096503141 on OpenAlexaff
Roger G. Spragg, James F. Lewis, W Wurst, Dietrich Häfner, Robert P. Baughman, Mark D. Wewers, James J. Marsh

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2003
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsSt Joseph's Health CentreLawson Health Research InstituteWestern University
FundersNational Heart, Lung, and Blood Institute
KeywordsPulmonary surfactantMedicineBronchoalveolar lavageRespiratory distressSurfactant therapyAnesthesiaGastroenterologyInternal medicineLungBiochemistry

Abstract

fetched live from OpenAlex

We performed a phase I/II trial in North America of a recombinant surfactant protein C-based surfactant (Venticute) as treatment for the acute respiratory distress syndrome. Patients were prospectively randomized to receive either standard therapy or standard therapy plus one of two doses of exogenous surfactant given four times over 24 hours. Surfactant administration was well tolerated. No significant treatment benefit was associated with surfactant treatment. Bronchoalveolar lavage of treated patients at 48 hours reflected the presence of exogenous surfactant components, did not show evidence of improved surface tension lowering function, and had interleukin-6 concentrations that were significantly lower than control group values, consistent with an antiinflammatory treatment effect. The presence of exogenous surfactant was not detected in lavage fluid obtained at 120 hours. Future studies might rationally employ larger surfactant doses and a more prolonged dosing schedule.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.034
GPT teacher head0.363
Teacher spread0.329 · 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 designBench or experimental
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

Citations175
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of Respiratory and Critical Care MedicineSame topicNeonatal Respiratory Health ResearchFrench-language works237,207