Corticosteroids for Acute Respiratory Distress Syndrome
Bibliographic record
Abstract
Acute respiratory distress syndrome (ARDS) remains a heterogeneous and a major challenge disease process despite five decades of study. Emerging translational data delineate three overlapping phases: exudative, proliferative, and fibroproliferative, each driven by distinct immune-mechanical pathways and potentially modifiable by glucocorticosteroids (GC) modulation. Contemporary clinical randomized trials and meta-analyses indicate that early (≤72 hours) administration of systemic GCs at receptor-saturating doses (e.g., dexamethasone from 20 to 10 mg/day, or methylprednisolone 1-2 mg/kg/day) accelerates resolution of pulmonary edema, shortens mechanical ventilation duration, and improves intensive care survival, while prolonged tapering regimens are required once fibroproliferation is established. Conversely, delayed initiation (>14 days), viral pneumonitis with high viral load, recent surgical anastomosis, or uncontrolled fungal coinfection constitute "red flags" in which GCs might increase mortality. Latent-class analyses-a statistical modeling approach in which multivariable data are reduced to indirectly observed (latent) variables-identified two (hyper- and hypoinflammatory) ARDS phenotypes that likely might respond differentially to GC exposure, although we lack validation studies. Therefore, it seems that biomarker-guided precision therapy is poised to replace the historical one-size-fits-all approach. This narrative review integrates epidemiology, pathobiology, pharmacology, and clinical evidence to provide a phase-specific, phenotype-directed framework for GC use in ARDS and outlines future research priorities aimed at harmonizing molecular endotyping with dose, timing, and tapering strategies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 0.010 |
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 source (direct Gemma or distilled Codex), 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".