Adverse effects of remdesivir, hydroxychloroquine, and lopinavir/ritonavir when used for COVID-19: systematic review and meta-analysis of randomized trials
Bibliographic record
Abstract
Abstract Introduction In an attempt to improve outcomes for patients with coronavirus disease 19 (COVID-19), several drugs, such as remdesivir, hydroxychloroquine (with or without azithromycin), and lopinavir/ritonavir, have been evaluated for treatment. While much attention focuses on potential benefits of these drugs, this must be weighed against their adverse effects. Methods We searched 32 databases in multiple languages from 1 December 2019 to 27 October 2020. We included randomized trials if they compared any of the drugs of interest to placebo or standard care, or against each other. A related world health organization (WHO) guideline panel selected the interventions to address and identified possible adverse effects that might be important to patients. Pairs of reviewers independently extracted data and assessed risk of bias. We analyzed data using a fixed-effects pairwise meta-analysis and assessed the certainty of evidence using the GRADE approach. Results We included 16 randomized trials which enrolled 8226 patients. Compared to standard care or placebo, low certainty evidence suggests that remdesivir may not have an important effect on acute kidney injury (risk difference [RD] 8 fewer per 1000, 95% confidence interval (CI): 27 fewer to 21 more) or cognitive dysfunction/delirium (RD 3 more per 1000, 95% CI: 12 fewer to 19 more). Low certainty evidence suggests that hydroxychloroquine may increase the risk of serious cardiac toxicity (RD 10 more per 1000, 95% CI: 0 more to 30 more) and cognitive dysfunction/delirium (RD 33 more per 1000, 95% CI: 18 fewer to 84 more), whereas moderate certainty evidence suggests hydroxychloroquine probably increases the risk of diarrhoea (RD 106 more per 1000, 95% CI: 48 more to 175 more) and nausea and/or vomiting (RD 62 more per 1000, 95% CI: 23 more to 110 more) compared to standard care or placebo. Low certainty evidence suggests lopinavir/ritonavir may increase the risk of diarrhoea (RD 168 more per 1000, 95% CI: 58 more to 330 more) and nausea and/or vomiting (RD 160 more per 1000, 95% CI: 100 more to 210 more) compared to standard care or placebo. Conclusion Hydroxychloroquine probably increases the risk of diarrhoea and nausea and/or vomiting and may increase the risk of cardiac toxicity and cognitive dysfunction/delirium. Remdesivir may have no effect on risk of acute kidney injury or cognitive dysfunction/delirium. Lopinavir/ritonavir may increase the risk of diarrhoea and nausea and/or vomiting. These findings provide important information to support the development of evidence-based management strategies for patients with COVID-19.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.030 | 0.683 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.036 | 0.007 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".