Effectiveness of pulse dose methyl prednisolone in management of COVID 19: A systematic review and meta-analysis of observational studies.
Bibliographic record
Abstract
PURPOSE: Till date, only systemic corticosteroids have demonstrated definite mortality benefit in management of COVID 19 in various studies. Still certain questions regarding the appropriate dose, duration and timing of corticosteroids remain unanswered. For this reason, the study was planned to determine the efficacy and safety of the pulse dose methyl prednisolone in management of COVID 19 from the publicly available evidence. METHODS: PubMed, the Cochrane library, ClinicalTrials.gov and medRxiv were searched for articles reporting the use of pulse dose methyl prednisolone in COVID 19 from inception till 31st May, 2021. Odds ratios (ORs) were calculated for estimation of pooled effect by using random effect model and heterogeneity was checked by using I2 statistics. RESULTS: Twelve studies (11 observational and 1 RCT) were included in the systematic review. A total of 3110 patients from 9 studies were included in the meta-analysis. Though the use of pulse dose methyl prednisolone demonstrated statistically significant mortality benefit in comparison to usual care (OR=0.71, 95% CI: 0.51 to 0.97, [P=0.03]), (I2= 21%) with calculated Number needed to treat (NNT) of 23.5, there was no statistically significant difference between the use of pulse dose and low dose corticosteroid (OR=0.66, 95% CI: 0.44 to 1.01, [(P=0.05]), (I2= 25%) and the NNT is 23.5. Incidence of adverse events were similar across all the groups. The grade of evidence for primary outcome was of moderate certainty. CONCLUSION: This meta-analysis concurs with the previous reports regarding the use of corticosteroid in COVID 19 in comparison to usual care. However, for both the primary and secondary outcome, the study did not find any statistically significant difference between the use of pulse dose methyl prednisolone and low dose corticosteroid to treat COVID 19 patients.
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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 | 0.016 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.047 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".