An Evidence-Based Approach to Acute Respiratory Distress Syndrome
Bibliographic record
Abstract
We provide an evidence-based approach to managing patients with acute lung injury and acute respiratory distress syndrome (ARDS). We searched MEDLINE and the Cumulative Index to Nursing and Allied Health for randomized trials evaluating lung-protective ventilation strategies, inhaled nitric oxide, prone positioning, and late-phase corticosteroids for managing these patients, and for additional literature related to long-term follow-up of ARDS survivors. The results of our review suggest that pressure- and volume-limited ventilation, according to the ARDS Network protocol, can reduce mortality for patients with acute lung injury, and so may an "open lung" approach to mechanical ventilation. Those 2 strategies are currently being compared in 2 multicenter randomized trials. Although both inhaled nitric oxide therapy and prone positioning can produce dramatic acute improvements in oxygenation for some patients, there is no evidence that these interventions can benefit patients with respect to patient-important outcomes. Therefore it is unreasonable to be dogmatic about the role of inhaled nitric oxide and prone positioning in ARDS. The role of corticosteroids in the late phase of ARDS is unclear and remains a very important unanswered question. With respect to long-term follow-up, we found that pulmonary dysfunction is probably not a major source of morbidity for ARDS survivors, whereas neuropsychological dysfunction is prominent. Ongoing research may suggest interventions to improve the outcome of ARDS and of critical illness in general.
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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 | 0.046 | 0.085 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.030 | 0.014 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.013 | 0.013 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".