Dexamethasone doses in patients with <scp>COVID</scp>‐19 and hypoxia: <scp>A</scp> systematic review and meta‐analysis
Bibliographic record
Abstract
BACKGROUND: The optimal dose of dexamethasone for severe/critical COVID-19 is uncertain. We compared higher versus standard doses of dexamethasone in adults with COVID-19 and hypoxia. METHODS: We searched PubMed and trial registers until 23 June 2023 for randomised clinical trials comparing higher (>6 mg) versus standard doses (6 mg) of dexamethasone in adults with COVID-19 and hypoxia. The primary outcome was mortality at 1 month. Secondary outcomes were mortality closest to 90 days; days alive without life support; and the occurrence of serious adverse events/reactions (SAEs/SARs) closest to 1 month. We assessed the risk of bias using the Cochrane RoB2 tool, risk of random errors using trial sequential analysis, and certainty of evidence using Grading of Recommendations Assessment, Development and Evaluation (GRADE). RESULTS: We included eight trials (2478 participants), of which four (1293 participants) had low risk of bias. Higher doses of dexamethasone probably resulted in little to no difference in mortality at 1 month (relative risk [RR] 0.97, 95% CI: 0.79-1.19), mortality closest to Day 90 (RR 1.01, 95% CI: 0.86-1.20), and SAEs/SARs (RR 1.00, 95% CI: 0.97-1.02). Higher doses of dexamethasone probably increased the number of days alive without invasive mechanical ventilation and circulatory support but had no effect on days alive without renal replacement therapy. CONCLUSIONS: Based on low to moderate certainty evidence, higher versus standard doses of dexamethasone probably result in little to no difference in mortality, SAEs/SARs, and days alive without renal replacement therapy, but probably increase the number of days alive without invasive mechanical ventilation and circulatory support.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.022 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".