Emerging therapies for treatment of acute lung injury and acute respiratory distress syndrome
Bibliographic record
Abstract
Acute lung injury/acute respiratory distress syndrome (ALI/ARDS) is a life-threatening form of respiratory failure that affects a heterogeneous population of critically ill patients. Although overall mortality appears to be decreasing in recent years due to improvements in supportive care, there are presently no proven, effective pharmacological therapies to treat ARDS and prevent its associated complications. The most common cause of death in ARDS is not hypoxemia or pulmonary failure, but rather multiple organ dysfunction syndrome (MODS), suggesting that improving survival in patients with ARDS may be linked to decreasing the incidence or severity of MODS. The key to developing novel treatments depends, in part, on identifying and understanding the mechanisms by which ARDS leads to MODS, although the heterogeneity and complexity of this disorder certainly poses a challenge to investigators. Novel therapies in development for treatment of ALI/ARDS include exogenous surfactant, therapies aimed at modulating neutrophil activity, such as prostaglandin and complement inhibitors, and treatments targeting earlier resolution of ARDS, such as beta-agonists and granulocyte macrophage colony-stimulating factor. From a clinical perspective, identifying subpopulations of patients most likely to benefit from a particular therapy and recognising the appropriate stage of illness in which to initiate treatment could potentially lead to better outcomes in the short term.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".