•Statistically significant improvement is seen for mortality. 22 studies from 20 independent teams in 8 different countries show statistically significant
improvements in isolation (17 for the most serious outcome).
•Studies to date do not show a significant benefit for mechanical ventilation and ICU admission.
Benefit may be more likely without coadministered anticoagulants. The RECOVERY RCT shows
4% [-4‑11%]
lower mortality for all patients, however when restricting to non-LMWH
patients there was 17% [-4‑34%] improvement,
consistent with the mortality results of
all studies,
13% [7‑20%],
and the 16% improvement in the REMAP-CAP RCT.
•While many treatments have some level
of efficacy, they do not replace vaccines and other measures to avoid
infection.
Only 4% of aspirin
studies show zero events in the treatment arm.
Multiple treatments are typically used
in combination, and other treatments
are significantly more effective.
•No treatment, vaccine, or intervention is 100%
available and effective for all variants. All practical, effective, and safe
means should be used.
Denying the efficacy of treatments increases mortality, morbidity, collateral
damage, and endemic risk.
•All data to reproduce this paper and
sources are in the appendix.
[Banaser] present another meta analysis for aspirin, showing significant improvements for mortality and mechanical ventilation.
Highlights
Aspirin reduces
risk for COVID-19 with very high confidence for mortality and in pooled analysis, low confidence for recovery and viral clearance, and very low confidence for cases.
Benefit may be more likely without coadministered anticoagulants.
We show traditional outcome specific analyses and combined
evidence from all studies, incorporating treatment delay, a primary
confounding factor in COVID-19 studies.
Figure 1.A. Random effects
meta-analysis. This plot shows pooled effects, discussion can be found in the heterogeneity section,
and results for specific outcomes can be found in the individual outcome analyses.
Effect extraction is pre-specified, using the most serious outcome reported.
For details of effect extraction see the appendix.
B. Scatter plot showing the
distribution of effects reported in studies. C. History of all reported
effects (chronological within treatment stages).
We analyze all significant studies
concerning the use of
aspirin
for COVID-19.
Search methods, inclusion criteria, effect
extraction criteria (more serious outcomes have priority), all individual
study data, PRISMA answers, and statistical methods are detailed in
Appendix 1. We present random effects meta-analysis results for all
studies, for studies within each treatment stage, for individual outcomes, for
peer-reviewed studies, for Randomized Controlled Trials (RCTs), and after
exclusions.
Figure 2 shows stages of possible treatment for
COVID-19. Prophylaxis refers to regularly taking medication before
becoming sick, in order to prevent or minimize infection. Early
Treatment refers to treatment immediately or soon after symptoms appear,
while Late Treatment refers to more delayed treatment.
Figure 3 shows a visual overview of the results, with details in
Table 1 and Table 2.
Figure 4, 5, 6, 7, 8, 9, 10, 11, 12, and 13
show forest plots for a random effects meta-analysis of
all studies with pooled effects, mortality results, ventilation, ICU admission, hospitalization, progression, recovery, cases, viral clearance, and peer reviewed studies.
Figure 4. Random effects meta-analysis for all studies with pooled effects.
This plot shows pooled effects, discussion can be found in the heterogeneity section,
and results for specific outcomes can be found in the individual outcome analyses.
Effect extraction is pre-specified, using the most serious outcome reported.
For details of effect extraction see the appendix.
