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Record W2921470843 · doi:10.29390/cjrt-2018-016

Fluid management in Acute Respiratory Distress Syndrome: A narrative review

2019· review· en· W2921470843 on OpenAlexvenueno aff
Jean I. Keddissi, Houssein Youness, Kellie Jones, Gary T. Kinasewitz

Bibliographic record

VenueCanadian Journal of Respiratory Therapy · 2019
Typereview
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsIntensive care medicineMedicineAcute respiratory distressNarrative reviewRespiratory distressIntensive care unitConservative managementLungSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Acute Respiratory Distress Syndrome remains a major source of morbidity and mortality in the modern intensive care unit (ICU). Major advances in the understanding and management of this condition were made in the last two decades. The use of low tidal ventilation is a well-established therapy. Conservative fluid management is now another cornerstone of management. However, much remains to be understood in this arena. Assessing volume status in these patients may be challenging and the tools available to do so are far from perfect. Several dynamic measures including pulse pressures variation are used. Ultrasound of the lungs and the vascular system may also have a role. In addition, the type of fluid to administer when needed is still open to debate. Finally, supportive measures in these patients, early during their ICU stay and later after discharge continue to be crucial for survival and adequate recovery.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.078
GPT teacher head0.362
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 designNot applicable
Domainnot available
GenreReview

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

Citations35
Published2019
Admission routes1
Has abstractyes

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