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Record W1994001314 · doi:10.1097/mcc.0b013e3283427295

Acute respiratory distress syndrome and multiple organ failure

2010· article· en· W1994001314 on OpenAlexaff
Lorenzo Del Sorbo, Arthur S. Slutsky

Bibliographic record

VenueCurrent Opinion in Critical Care · 2010
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsSt. Michael's HospitalUniversity of Toronto
Fundersnot available
KeywordsARDSMedicineIntensive care medicineHypoxemiaAcute respiratory distressSepsisPathophysiologyRespiratory failureRespiratory distressVentilation (architecture)LungCardiologyInternal medicineSurgery

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Despite improvements in outcome due to lung protective ventilation strategies using low tidal volumes, the mortality rate from acute respiratory distress syndrome (ARDS) remains unacceptably high, ranging from 34 to 64%. The predominant cause of death in ARDS is not severe hypoxemia, which is one of the defining criteria of ARDS, but multiple organ failure (MOF). RECENT FINDINGS: In view of the relationship between ARDS and MOF, two different but complementary pathophysiological perspectives will be developed in this article: ARDS as a consequence of MOF, and ARDS as the cause of MOF. This framework may be useful in guiding the development of novel therapeutic strategies that ultimately improve the outcome of ARDS and sepsis patients. SUMMARY: ARDS is a severe lung disease characterized by a very complex pathophysiology, involving not only the respiratory system but also nonpulmonary distal organs. Elucidation of the pathophysiological mechanisms bi-directionally linking MOF to ARDS appears to be a promising area of research that hopefully will lead to improved outcomes for these devastating conditions.

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)0.002
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 score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.004

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 head0.082
GPT teacher head0.407
Teacher spread0.325 · 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

Citations134
Published2010
Admission routes1
Has abstractyes

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