Corticosteroids for patients with acute respiratory distress syndrome: a systematic review and meta-analysis of randomized trials
Bibliographic record
Abstract
INTRODUCTION: Acute respiratory distress syndrome (ARDS) is a rapidly progressing, inflammatory lung disease with a high mortality rate and no specific pharmacological treatment available. OBJECTIVES: We conducted a systematic review and meta‑analysis on corticosteroid use in ARDS. METHODS: We searched 4 medical literature databases and retained randomized controlled trials on the use of corticosteroids in hospitalized adults with ARDS, which could be found there until February 2020. Two reviewers identified eligible studies, independently extracted data, and evaluated the risk of bias. The authors assessed the certainty of evidence using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach. RESULTS: We included 7 randomized controlled trials involving 851 patients. They showed that corticosteroids reduced all‑cause mortality (risk ratio [RR], 0.75; 95% CI, 0.59-0.95; P = 0.02; moderate certainty) and the duration of mechanical ventilation (mean difference [MD], -4.93 days; 95% CI; -7.81 to -2.06; P <0.001; low certainty), and increased the number of ventilator‑free days (MD, 4.28 days; 95% CI, 2.67-5.88; P <0.001; moderate certainty), as compared with placebo. Corticosteroids also increased the risk of hyperglycemia (RR, 1.12%; 95% CI, 1.01-1.24; P = 0.03; moderate certainty), and the effect on neuromuscular weakness was unclear (RR, 1.3; 95% CI, 0.8-2.11; P = 0.28; low certainty). CONCLUSIONS: These results suggest that systemic corticosteroids may potentially improve mortality, shorten ventilation times, and increase the number of ventilator‑free days in patients with ARDS. However, the studies included different corticosteroid classes and initiated drug administration at different times, as well as used various dosing regimens. Thus, caution in the actual clinical application of these results is recommended.
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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 | 0.019 | 0.047 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.035 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".