Effectiveness of Ivermectin/Doxycycline combination in COVID-19: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract BackgroundThis systematic review and meta-analysis aimed to assess the efficacy of the Ivermectin/Doxycycline combination for the treatment of coronavirus disease 2019 (COVID-19).MethodsWe searched PubMed, Web of Science, Scopus, ClinicalTrials.gov, and Google Scholar from database inception to August 26, 2021 for relevant studies. We included studies reporting at least one of the outcomes of interest: all-cause mortality; time to clinical recovery; hospital stay and viral clearance. The logarithm of risk ratios or mean differences and their corresponding standard errors for each outcome were pooled using a random-effects model. The risk of bias was assessed using the Cochrane Collaboration's tool for randomized clinical trials and the Newcastle-Ottawa Scale for cohort studies.ResultsFour randomized clinical trials and one prospective study involving 789 patients, including 399 in the Ivermectin/Doxycycline group and 390 in the control group, were enrolled. The all-cause mortality rate of patients with COVID-19 in the Ivermectin/Doxycycline group was 0.79% (2/253), which was lower than in the control group (3.6%; 9/250). However, the difference was not statistically significant (Log risk ratio=-1.288; 95% CI:-2.671, 0.096; P = 0.068; I2 = 0%). The effect of Ivermectin/Doxycycline on time to clinical recovery was found to be significant (Difference in means =-2.427 days; 95% CI:-4.033, -0.820; P = 0.003, I2 = 91.475%). There is no significant effect of Ivermectin/Doxycycline on hospital stay (Difference in means =-0.379 days; 95% CI:-1.965, 1.208; P = 0.640, I2 = 91.95%) and time to negative PCR or viral clearance (Difference in means =-0.768 days; 95% CI:-1.550, 0.013; P = 0.054, I2 = 91.48%).DiscussionBased on low-quality evidence, this meta-analysis showed that Ivermectin/Doxycycline combination is accompanied with shorter time of clinical recovery in COVID-19 patients. However, it did not reduce all-cause mortality, viral clearance, and hospital stay significantly. Not only the number of the studies are limited but also they ranked methodologically medium to low with limited participants. To assess the exact effective dose and efficacy of this combination therapy, high-quality and large-scale randomized clinical trials are needed.OtherThis study was registered in Prospero (registration number: CRD42021272400). The authors declare they have no competing financial interests.
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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 | 0.018 | 0.038 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.028 | 0.045 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 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".