Aspirin for COVID-19: real-time meta analysis of 76 studies
Abstract
Statistically significant lower risk is seen for mortality and progression. 28 studies from 26 independent teams in 11 countries show significant
improvements.
Meta analysis using the most serious outcome reported shows
9% [3‑15%] lower risk. Early treatment is more effective than late treatment.
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,
comparable with the mortality results of
all studies,
10% [4‑16%],
and the 16% improvement in the REMAP-CAP RCT.
No treatment or intervention
is 100% effective. All practical, effective, and safe means should be used
based on risk/benefit analysis.
Multiple treatments are typically used
in combination, and other treatments
are significantly more effective.
Aspirin for COVID-19 — Highlights
Aspirin reduces
risk with very high confidence for mortality, progression, and in pooled analysis, and low confidence for recovery and viral clearance.
Benefit may be more likely without coadministered anticoagulants.
Outcome specific analyses and combined evidence from all
studies, incorporating treatment delay, a primary confounding factor.
Real-time updates and corrections,
transparent analysis with all results in the same format, consistent protocol
for 109
treatments.
Figure 1.
A. Random effects
meta-analysis. This plot shows pooled effects,
see the specific outcome analyses for individual outcomes.
Analysis validating pooled outcomes for
COVID-19 can be found below.
Effect extraction is pre-specified, using the most serious outcome reported.
For details see the appendix.
B. Timeline of results in aspirin studies.
SARS-CoV-2 infection primarily begins in the upper respiratory
tract and may progress to the lower respiratory tract, other tissues, and the
nervous and cardiovascular systems, which may lead to cytokine storm,
pneumonia, ARDS, neurological injury5-15 and
cognitive deficits7,12, cardiovascular
complications16-18, organ failure, and death.
Minimizing replication as early as possible is recommended.
SARS-CoV-2 infection and replication involves the complex interplay of 50+
host and viral proteins and other factorsA,19-24, providing many
therapeutic targets for which many existing compounds have known activity.
Scientists have predicted that over 8,000 compounds may
reduce COVID-19 risk25, either by
directly minimizing infection or replication, by supporting immune system
function, or by minimizing secondary complications.
We analyze all significant
controlled studies 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, studies within each treatment stage, individual outcomes, peer-reviewed studies, Randomized Controlled Trials (RCTs), and higher quality studies.
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 2. Treatment stages.
Preclinical research is an important part of the development of
treatments, however results may be very different in clinical trials.
Preclinical results are not used in this paper.
Table 1 summarizes the results for all stages combined, for Randomized Controlled Trials, for peer-reviewed studies, after exclusions, and for specific outcomes.
Table 2 shows results by treatment stage.
Figure 3 plots individual results by treatment stage.
Figure 4, 5, 6, 7, 8, 9, 10, 11, 12, and 13
show forest plots for 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.
| Improvement | Studies | Patients | Authors | |
|---|---|---|---|---|
| All studies | 9% [3‑15%] ** | 76 | 187,919 | 1,096 |
| After exclusions | 13% [6‑18%] *** | 66 | 180,765 | 1,004 |
| Peer-reviewed studiesPeer-reviewed | 9% [3‑15%] ** | 68 | 171,966 | 985 |
| Randomized Controlled TrialsRCTs | 5% [-2‑11%] | 7 | 23,015 | 235 |
| Mortality | 10% [4‑16%] ** | 65 | 161,240 | 969 |
| VentilationVent. | 5% [-5‑15%] | 15 | 54,773 | 222 |
| ICU admissionICU | 3% [-11‑16%] | 15 | 35,339 | 225 |
| HospitalizationHosp. | -1% [-6‑4%] | 10 | 12,578 | 128 |
| Recovery | 9% [-1‑18%] | 3 | 16,018 | 112 |
| Cases | 5% [-5‑14%] | 7 | 10,749 | 65 |
| Viral | 9% [-0‑17%] | 2 | 710 | 16 |
| RCT mortality | 5% [-2‑11%] | 6 | 22,735 | 208 |
| Early treatment | Late treatment | Prophylaxis | |
|---|---|---|---|
| All studies | 67% [-696‑99%] | 15% [8‑22%] **** | 5% [-5‑14%] |
| After exclusions | 67% [-696‑99%] | 20% [14‑25%] **** | 7% [-3‑16%] |
| Peer-reviewed studiesPeer-reviewed | 67% [-696‑99%] | 16% [9‑23%] **** | 4% [-5‑12%] |
| Randomized Controlled TrialsRCTs | 67% [-696‑99%] | 5% [-2‑11%] | |
| Mortality | 15% [8‑22%] **** | 5% [-6‑15%] | |
| VentilationVent. | 8% [-14‑25%] | 2% [-2‑7%] | |
| ICU admissionICU | 3% [-35‑30%] | 2% [-16‑17%] | |
| HospitalizationHosp. | 67% [-696‑99%] | 17% [-19‑42%] | -1% [-7‑4%] |
| Recovery | 9% [-1‑18%] | ||
| Cases | 5% [-5‑14%] | ||
| Viral | -2% [-61‑36%] | 10% [0‑18%] * |
|
| RCT mortality | 5% [-2‑11%] |
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Figure 3. Scatter plot showing the most serious outcome in all studies, and for studies within each stage. Diamonds shows the results of random effects meta-analysis.
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Figure 4. Random effects meta-analysis for all studies.
This plot shows pooled effects,
see the specific outcome analyses for individual outcomes.
Analysis validating pooled outcomes for
COVID-19 can be found below.
Effect extraction is pre-specified, using the most serious outcome reported.
For details see the appendix.
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Figure 5. Random effects meta-analysis for mortality results.
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Figure 6. Random effects meta-analysis for ventilation.
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Figure 7. Random effects meta-analysis for ICU admission.
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Figure 8. Random effects meta-analysis for hospitalization.
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Figure 9. Random effects meta-analysis for progression.
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Figure 10. Random effects meta-analysis for recovery.
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Figure 11. Random effects meta-analysis for cases.
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Figure 12. Random effects meta-analysis for viral clearance.
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Figure 13. Random effects meta-analysis for peer reviewed studies.
Effect extraction is pre-specified, using the most serious outcome reported,
see the appendix for details.
Analysis validating pooled outcomes for
COVID-19 can be found below.
Zeraatkar et al. analyze 356 COVID-19 trials, finding no significant
evidence that preprint results are inconsistent with peer-reviewed studies.
They also show extremely long peer-review delays, with a median of 6 months to
journal publication. A six month delay was equivalent to around 1.5 million
deaths during the first two years of the pandemic. Authors recommend using
preprint evidence, with appropriate checks for potential falsified data, which
provides higher certainty much earlier. Davidson et al. also showed no
important difference between meta analysis results of preprints and
peer-reviewed publications for COVID-19, based on 37 meta analyses including
114 trials.
Figure 14 shows a comparison of results for RCTs and non-RCT studies.
Figure 15 and 16
show forest plots for random effects meta-analysis of
all Randomized Controlled Trials and RCT mortality results.
RCT results are included in Table 1 and Table 2.
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Figure 14. Results for RCTs and non-RCT studies.
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Figure 15. Random effects meta-analysis for all Randomized Controlled Trials.
This plot shows pooled effects,
see the specific outcome analyses for individual outcomes.
Analysis validating pooled outcomes for
COVID-19 can be found below.
Effect extraction is pre-specified, using the most serious outcome reported.
For details see the appendix.
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Figure 16. Random effects meta-analysis for RCT mortality results.
RCTs help to make study groups more similar and can provide a higher level of
evidence, however they are subject to many biases30, and
analysis of double-blind RCTs has identified extreme levels of bias31.
For COVID-19, the overhead may delay treatment, dramatically compromising
efficacy; they may encourage monotherapy for simplicity at the cost of
efficacy which may rely on combined or synergistic effects; the participants
that sign up may not reflect real world usage or the population that benefits
most in terms of age, comorbidities, severity of illness, or other factors;
standard of care may be compromised and unable to evolve quickly based on
emerging research for new diseases; errors may be made in randomization and
medication delivery; and investigators may have hidden agendas or vested
interests influencing design, operation, analysis, reporting, and the
potential for fraud. All of these biases have been observed with COVID-19
RCTs. There is no guarantee that a specific RCT provides a higher level of
evidence.
RCTs are expensive and many RCTs are funded
by pharmaceutical companies or interests closely aligned with pharmaceutical
companies. For COVID-19, this creates an incentive to show efficacy for
patented commercial products, and an incentive to show a lack of efficacy for
inexpensive treatments. The bias is expected to be significant, for example
Als-Nielsen et al. analyzed 370 RCTs from Cochrane reviews, showing that
trials funded by for-profit organizations were 5 times more likely to
recommend the experimental drug compared with those funded by nonprofit
organizations. For COVID-19, some major philanthropic organizations are
largely funded by investments with extreme conflicts of interest for and
against specific COVID-19 interventions.
High quality RCTs for novel acute diseases are more challenging, with
increased ethical issues due to the urgency of treatment, increased risk due
to enrollment delays, and more difficult design with a rapidly evolving
evidence base. For COVID-19, the most common site of initial infection is the
upper respiratory tract. Immediate treatment is likely to be most successful
and may prevent or slow progression to other parts of the body. For a
non-prophylaxis RCT, it makes sense to provide treatment in advance and
instruct patients to use it immediately on symptoms, just as some governments
have done by providing medication kits in advance. Unfortunately, no RCTs have
been done in this way. Every treatment RCT to date involves delayed treatment.
Among the 109 treatments we have analyzed,
65% of RCTs involve very late treatment 5+ days after
onset. No non-prophylaxis COVID-19 RCTs match the potential real-world use of
early treatments. They may more accurately represent results for treatments
that require visiting a medical facility, e.g., those requiring intravenous
administration.
RCTs have a bias against finding an
effect for interventions that are widely available — patients that
believe they need the intervention are more likely to decline participation
and take the intervention. RCTs for aspirin are more likely to
enroll low-risk participants that do not need treatment to recover, making the
results less applicable to clinical practice. This bias is likely to be
greater for widely known treatments, and may be greater when the risk of a
serious outcome is overstated. This bias does not apply to the typical
pharmaceutical trial of a new drug that is otherwise unavailable.
For COVID-19, observational study results do not systematically
differ from RCTs, RR 1.00 [0.92‑1.08]
across 109 treatments33.
Evidence shows that observational studies
can also provide reliable results. Concato et al. found that well-designed
observational studies do not systematically overestimate the magnitude of the
effects of treatment compared to RCTs. Anglemyer et al. analyzed reviews
comparing RCTs to observational studies and found little evidence for
significant differences in effect estimates.
We performed a similar analysis across the 109 treatments
we cover, showing no significant difference in the results of RCTs compared to
observational studies, RR 1.00 [0.92‑1.08]. Similar results are found for all low-cost treatments, RR
1.02 [0.92‑1.12]. High-cost treatments
show a non-significant trend towards RCTs showing greater efficacy,
RR 0.92 [0.82‑1.03].
Details can be found in the
supplementary data.
Lee et al. showed that only 14% of the guidelines of the Infectious
Diseases Society of America were based on RCTs. Evaluation of studies relies
on an understanding of the study and potential biases. Limitations in an RCT
can outweigh the benefits, for example excessive dosages, excessive treatment
delays, or remote survey bias may have a greater effect on results. Ethical
issues may also prevent running RCTs for known effective treatments. For more
on issues with RCTs see37,38.
Currently, 48 of the treatments we analyze show statistically significant efficacy or harm, defined as ≥10% decreased risk or >0% increased risk from ≥3 studies. Of these, 60% have been confirmed in RCTs, with a mean delay of 7.1 months (68% with 8.2 months delay for low-cost treatments). The remaining treatments either have no RCTs, or the point estimate is consistent.
We need to
evaluate each trial on its own merits. RCTs for a given medication and disease
may be more reliable, however they may also be less reliable. For off-patent
medications, very high conflict of interest trials may be more likely to be
RCTs, and more likely to be large trials that dominate meta analyses.
To avoid bias in the selection of studies, we analyze all
non-retracted studies. Here we show the results after excluding
studies with major issues likely to alter results, non-standard studies, and
studies where very minimal detail is currently available. Our bias evaluation
is based on analysis of each study and identifying when there is a significant
chance that limitations will substantially change the outcome of the study. We
believe this can be more valuable than checklist-based approaches such as
Cochrane GRADE, which can be easily influenced by potential bias, may ignore
or underemphasize serious issues not captured in the checklists, and may
overemphasize issues unlikely to alter outcomes in specific cases (for example
certain specifics of randomization with a very large effect size and
well-matched baseline characteristics).
The studies excluded are as below.
Figure 17 shows a forest plot for random
effects meta-analysis of all studies after exclusions.
Alamdari, substantial unadjusted confounding by indication likely.
Aweimer, unadjusted results with no group details.
Azimi Pirsaraei, unadjusted results with no group details.
Azizi, age matching based on only two categories, matching may be very poor given the relationship between age and COVID-19 risk; inconsistent data.
Elhadi, unadjusted results with no group details.
Holt, unadjusted results with no group details.
Karimpour-Razkenari, substantial unadjusted confounding by indication likely.
Mulhem, substantial unadjusted confounding by indication likely; substantial confounding by time likely due to declining usage over the early stages of the pandemic when overall treatment protocols improved dramatically.
Mustafa, unadjusted results with no group details.
Shamsi, unadjusted results with no group details.
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Figure 17. Random effects meta-analysis for all studies after exclusions.
This plot shows pooled effects,
see the specific outcome analyses for individual outcomes.
Analysis validating pooled outcomes for
COVID-19 can be found below.
Effect extraction is pre-specified, using the most serious outcome reported.
For details see the appendix.
Heterogeneity in COVID-19 studies arises from many factors including:
The time
between infection or the onset of symptoms and treatment may critically affect
how well a treatment works. For example an antiviral may be very effective
when used early but may not be effective in late stage disease, and may even
be harmful. Oseltamivir, for example, is generally only considered effective
for influenza when used within 0-36 or 0-48 hours49,50.
Baloxavir marboxil studies for influenza also show that treatment delay is critical
— Ikematsu et al. report an 86% reduction in cases for post-exposure
prophylaxis, Hayden et al. show a 33 hour reduction in the time to
alleviation of symptoms for treatment within 24 hours and a reduction of 13
hours for treatment within 24-48 hours, and Kumar et al. report only 2.5
hours improvement for inpatient treatment.
| Treatment delay | Result |
| Post-exposure prophylaxis | 86% fewer cases51 |
| <24 hours | -33 hours symptoms52 |
| 24-48 hours | -13 hours symptoms52 |
| Inpatients | -2.5 hours to improvement53 |
Figure 18 shows a mixed-effects meta-regression for efficacy
as a function of treatment delay in COVID-19 studies from 109 treatments, showing
that efficacy declines rapidly with treatment delay. Early treatment is
critical for COVID-19.
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Figure 18. Early treatment is more effective. Meta-regression showing efficacy as a function of treatment delay in COVID-19 studies from 109 treatments.
Details of the patient population including age and comorbidities may
critically affect how well a treatment works. For example, many COVID-19
studies with relatively young low-comorbidity patients show all patients
recovering quickly with or without treatment. In such cases, there is little
room for an effective treatment to improve results, for example as in
López-Medina et al.
Efficacy may
depend critically on the distribution of SARS-CoV-2 variants encountered by
patients. Risk varies significantly across variants55, for
example the Gamma variant shows significantly different characteristics56-59. Different mechanisms of action may be
more or less effective depending on variants, for example the degree to which
TMPRSS2 contributes to viral entry can differ across variants60,61.
Effectiveness may depend strongly on the dosage and treatment regimen.
The use
of other treatments may significantly affect outcomes, including supplements,
other medications, or other interventions such as prone positioning.
Treatments may be synergistic62-73, therefore
efficacy may depend strongly on combined treatments.
The
quality of medications may vary significantly between manufacturers and
production batches, which may significantly affect efficacy and safety.
Williams et al. analyze ivermectin from 11 different sources, showing
highly variable antiparasitic efficacy across different manufacturers.
Xu et al. analyze a treatment from two different manufacturers, showing 9
different impurities, with significantly different concentrations for each
manufacturer.
Across all
studies there is a strong association between different outcomes, for example
improved recovery is strongly associated with lower mortality. However,
efficacy may differ depending on the effect measured, for example a treatment
may be more effective against secondary complications and have minimal effect
on viral clearance.
The
distribution of studies will alter the outcome of a meta analysis. Consider a
simplified example where everything is equal except for the treatment delay,
and effectiveness decreases to zero or below with increasing delay. If there
are many studies using very late treatment, the outcome may be negative, even
though early treatment is very effective.
All meta analyses combine heterogeneous studies, varying in population,
variants, and potentially all factors above, and therefore may obscure
efficacy by including studies where treatment is less effective. Generally, we
expect the estimated effect size from meta analysis to be less than that for
the optimal case.
Looking at all studies is valuable for providing an overview of all research,
important to avoid cherry-picking, and informative when a positive result is
found despite combining less-optimal situations. However, the resulting
estimate does not apply to specific cases such as
early treatment in high-risk populations.
While we present results for all studies, we also present treatment time and
individual outcome analyses, which may be more informative for specific use
cases.
For COVID-19, delay in clinical results translates into
additional death and morbidity, as well as additional economic and societal
damage. Combining the results of studies reporting different outcomes is
required.
There may be no mortality in a trial with low-risk patients,
however a reduction in severity or improved viral clearance may translate
into lower mortality in a high-risk population.
Different studies may report lower severity, improved recovery, and lower mortality,
and the significance may be very high when combining the results.
"The studies reported different outcomes"
is not a good reason for disregarding results.
We present both specific outcome and pooled analyses.
In order to combine the results of studies reporting different outcomes we use
the most serious outcome reported in each study, based on the thesis that
improvement in the most serious outcome provides comparable measures of
efficacy for a treatment. A critical advantage of this approach is
simplicity and transparency.
There are many other ways to combine evidence for different outcomes, along
with additional evidence such as dose-response relationships, however these
increase complexity.
Another way to view pooled analysis is that we are using more of
the available information. Logically we should, and do, use additional
information. For example dose-response and
treatment delay-response relationships provide significant additional evidence
of efficacy that is considered when reviewing the evidence for a
treatment.
Trials with high-risk patients may be restricted due to ethics for treatments
that are known or expected to be effective, and they increase difficulty for
recruiting. Using less severe outcomes as a proxy for more serious outcomes
allows faster collection of evidence.
For many COVID-19 treatments, a reduction in mortality logically
follows from a reduction in hospitalization, which follows from a reduction in
symptomatic cases, which follows from a reduction in PCR positivity. We can
directly test this for COVID-19.
Analysis of the the association between different outcomes across studies from
all 109
treatments we cover confirms the validity of pooled outcome analysis for COVID-19.
Figure 19 shows that lower hospitalization is very strongly associated
with lower mortality (p < 0.000000000001).
Similarly, Figure 20 shows that improved recovery is very strongly associated
with lower mortality (p < 0.000000000001).
Considering the extremes, Singh et al. show an association between viral clearance and
hospitalization or death, with p = 0.003 after excluding one large
outlier from a mutagenic treatment, and based on 44 RCTs including 52,384
patients.
Figure 21 shows that improved viral clearance is strongly associated
with fewer serious outcomes. The association is very similar to
Singh et al., with higher confidence due to the larger number of
studies. As with Singh et al., the confidence increases
when excluding the outlier treatment, from p = 0.00000042 to p = 0.00000002.
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Figure 19. Lower hospitalization is associated with lower mortality, supporting pooled outcome analysis.
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Figure 20. Improved recovery is associated with lower mortality, supporting pooled outcome analysis.
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Figure 19. Improved viral clearance is associated with fewer serious outcomes, supporting pooled outcome analysis.
Currently, 48 of the treatments we analyze show statistically significant efficacy or harm, defined as ≥10% decreased risk or >0% increased risk from ≥3 studies. 89% of these have been confirmed with one or more specific outcomes, with a mean delay of 5.1 months. When restricting to RCTs only, 56% of treatments showing statistically significant efficacy/harm with pooled effects have been confirmed with one or more specific outcomes, with a mean delay of 6.4 months.
Figure 22 shows when treatments were found effective during the
pandemic. Pooled outcomes often resulted in earlier detection of efficacy.
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Figure 22. The time when studies showed that
treatments were effective, defined as statistically significant improvement of
≥10% from ≥3 studies.
Pooled results typically show efficacy earlier than specific
outcome results. Results from all studies often shows efficacy much earlier
than when restricting to RCTs.
Results reflect conditions as used in trials to date, these depend on the
population treated, treatment delay, and treatment regimen.
Pooled analysis could hide efficacy, for example a treatment that is
beneficial for late stage patients but has no effect on viral clearance may
show no efficacy if most studies only examine viral clearance. In practice, it
is rare for a non-antiviral treatment to report viral clearance and to not
report clinical outcomes; and in practice other sources of heterogeneity such
as difference in treatment delay is more likely to hide efficacy.
Analysis validates the use of pooled effects and shows significantly faster
detection of efficacy on average.
However, as with all meta analyses, it is important to review the different
studies included. We also present individual outcome analyses, which may be
more informative for specific use cases.
Publishing is often biased
towards positive results, however evidence suggests that there may be a negative bias for
inexpensive treatments for COVID-19. Both negative and positive results are
very important for COVID-19, media in many countries prioritizes negative
results for inexpensive treatments (inverting the typical incentive for
scientists that value media recognition), and there are many reports of
difficulty publishing positive results77-80.
One method to evaluate bias is to compare prospective vs.
retrospective studies. Prospective studies are more likely to be published
regardless of the result, while retrospective studies are more likely to
exhibit bias. For example, researchers may perform preliminary analysis with
minimal effort and the results may influence their decision to continue.
Retrospective studies also provide more opportunities for the specifics of
data extraction and adjustments to influence results.
Figure 23 shows a scatter plot of
results for prospective and retrospective studies.
38% of retrospective studies
report a statistically significant positive effect for
one or more outcomes, compared to
30% of prospective studies, consistent with a bias toward publishing positive results.
The median effect size for
retrospective studies is 12% improvement,
compared to 13% for prospective
studies, showing similar results.
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Figure 23. Prospective vs. retrospective studies.
The diamonds show the results of random effects meta-analysis.
Funnel
plots have traditionally been used for analyzing publication bias. This is
invalid for COVID-19 acute treatment trials — the underlying assumptions
are invalid, which we can demonstrate with a simple example. Consider a set of
hypothetical perfect trials with no bias. Figure 24 plot A
shows a funnel plot for a simulation of 80 perfect trials, with random group
sizes, and each patient's outcome randomly sampled (10% control event
probability, and a 30% effect size for treatment). Analysis shows no asymmetry
(p > 0.05). In plot B, we add a single typical variation in COVID-19 treatment
trials — treatment delay. Consider that efficacy varies from 90% for
treatment within 24 hours, reducing to 10% when treatment is delayed 3 days.
In plot B, each trial's treatment delay is randomly selected. Analysis now
shows highly significant asymmetry, p < 0.0001, with six variants of
Egger's test all showing p < 0.0581-88.
Note that these tests fail even though treatment delay is uniformly
distributed. In reality treatment delay is more complex — each trial has
a different distribution of delays across patients, and the distribution
across trials may be biased (e.g., late treatment trials may be more common).
Similarly, many other variations in trials may produce asymmetry, including
dose, administration, duration of treatment, differences in SOC,
comorbidities, age, variants, and bias in design, implementation, analysis,
and reporting.
Figure 24. Example funnel plot analysis for simulated perfect trials.
Pharmaceutical drug
trials often have conflicts of interest whereby sponsors or trial staff have a
financial interest in the outcome being positive. Aspirin for COVID-19
lacks this because it is off-patent, has multiple manufacturers, and is very low cost.
In contrast, most COVID-19 aspirin trials have been run by
physicians on the front lines with the primary goal of finding the best
methods to save human lives and minimize the collateral damage caused by
COVID-19. While pharmaceutical companies are careful to run trials under
optimal conditions (for example, restricting patients to those most likely to
benefit, only including patients that can be treated soon after onset when
necessary, and ensuring accurate dosing), not all aspirin trials
represent the optimal conditions for efficacy.
Summary statistics from
meta analysis necessarily lose information. As with all meta analyses, studies
are heterogeneous, with differences
in treatment delay, treatment regimen, patient demographics, variants,
conflicts of interest, standard of care, and other factors. We provide analyses for specific
outcomes and by treatment delay, and we aim to identify key characteristics in
the forest plots and summaries. Results should be viewed in the context of
study characteristics.
Some analyses classify treatment based on early or late
administration, as done here, while others distinguish between mild, moderate,
and severe cases. Viral load does not indicate degree of symptoms — for
example patients may have a high viral load while being asymptomatic. With
regard to treatments that have antiviral properties, timing of treatment is
critical — late administration may be less helpful regardless of
severity.
Details of treatment delay per patient is often not available.
For example, a study may treat 90% of patients relatively early, but the
events driving the outcome may come from 10% of patients treated very late.
Our 5 day cutoff for early treatment may be too conservative, 5 days may be too late in many cases.
Comparison across treatments is confounded by differences in
the studies performed, for example dose, variants, and conflicts of interest.
Trials with conflicts of interest may use designs better suited to the
preferred outcome.
In some cases, the most serious outcome has very few events,
resulting in lower confidence results being used in pooled analysis, however
the method is simpler and more transparent. This is less critical as the
number of studies increases. Restriction to outcomes with sufficient power may
be beneficial in pooled analysis and improve accuracy when there are few
studies, however we maintain our pre-specified method to avoid any
retrospective changes.
Studies show that combinations of treatments can be highly
synergistic and may result in many times greater efficacy than individual
treatments alone62-73.
Therefore standard of care may be critical and benefits may diminish or
disappear if standard of care does not include certain treatments.
This real-time analysis is constantly updated based on
submissions. Accuracy benefits from widespread review and submission of
updates and corrections from reviewers. Less popular treatments may receive
fewer reviews.
No treatment or intervention is 100% available and
effective for all current and future variants. Efficacy may vary significantly
with different variants and within different populations. All treatments have
potential side effects. Propensity to experience side effects may be predicted
in advance by qualified physicians. We do not provide medical advice. Before
taking any medication, consult a qualified physician who can compare all
options, provide personalized advice, and provide details of risks and
benefits based on individual medical history and situations.
SARS-CoV-2 infection and replication involves a complex interplay of 50+ host
and viral proteins and other factors19-24,
providing many therapeutic targets.
Over 8,000 compounds have been predicted to reduce COVID-19
risk25, either by directly
minimizing infection or replication, by supporting immune system function, or
by minimizing secondary complications.
Figure 25 shows an overview of the results for aspirin
in the context of multiple COVID-19 treatments, and Figure 26 shows a plot
of efficacy vs. cost for COVID-19 treatments.
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Figure 25.
Scatter plot showing results within the context of multiple COVID-19 treatments.
Diamonds shows the results of random effects meta-analysis.
0.6% of 8,000+ proposed treatments show efficacy89.
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Figure 26. Efficacy vs. cost for COVID-19 treatments.
Statistically significant lower risk is seen for mortality and progression. 28 studies from 26 independent teams in 11 countries show significant
improvements.
Meta analysis using the most serious outcome reported shows
9% [3‑15%] lower risk. Early treatment is more effective than late treatment.
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,
comparable with the mortality results of
all studies,
10% [4‑16%],
and the 16% improvement in the REMAP-CAP RCT.
Abdelwahab:
Retrospective 225 hospitalized patients in Egypt, showing significantly lower thromboembolic events with aspirin treatment, but no significant difference in the need for mechanical ventilation.
Abul:
Retrospective 1,687 nursing home residents in the USA, showing significantly lower risk of mortality with chronic low-dose aspirin use. Low dose 81mg aspirin users had treatment ≥10 of 14 days prior to the positive COVID date, control patients had no aspirin use in the prior 14 days.
Aidouni:
Prospective study of 1,124 COVID-19 ICU patients, showing lower mortality with aspirin treatment.
Al Harthi:
Retrospective 1,033 critical condition patients, showing lower in-hospital mortality with aspirin in PSM analysis. Patients receiving aspirin also had a higher risk of significant bleeding, although not reaching statistical significance. Authors note that the use of aspirin during an ICU stay should be tailored to each patient.
Alamdari:
Retrospective 459 patients in Iran, 53 treated with aspirin, showing no significant difference with treatment.
Ali:
Retrospective 1,645 hospitalized patients in the USA, showing lower mortality with aspirin use, without statistical significance.
Ali (B):
Retrospective 1,190 ICU patients in Egypt, showing lower mortality with aspirin treatment. 150mg daily.
Aweimer:
Retrospective 149 patients under invasive mechanical ventilation in Germany showing no significant difference in mortality with aspirin prophylaxis in unadjusted results.
Azimi Pirsaraei:
Retrospective 831 hospitalized COVID-19 patients showing higher mortality with aspirin treatment in unadjusted results.
Azizi:
Retrospective 131 COVID-19 patients with aspirin use and 131 matched controls in Iran, showing no significant difference in outcomes, however age matching used only two categories, 40-60 and 60+, therefore matching may be very poor given the relationship between age and COVID-19 risk. The percentages given for the control group death/recovery outcomes do not match the reported counts.
Basheer:
Retrospective 390 hospitalized patients in Israel, showing higher risk of mortality with prior aspirin use. Details of the analysis are not provided.
Bejan:
Retrospective 9,748 COVID-19 patients in the USA showing no signficant difference with aspirin use.
Botton:
Retrospective 31 million people without cardiovascular disease in France, showing no significant difference in hospitalization or combined intubation/death with low dose aspirin prophylaxis.
Bradbury:
RCT 1,557 critical patients, showing significantly lower mortality with aspirin, with 97.5% posterior probability of efficacy.
Campbell:
Retrospective 28,856 COVID-19 patients in the USA, showing no significant difference in mortality for chronic aspirin use vs. sporadic NSAID use. Since aspirin is available OTC and authors only tracked prescriptions, many patients classified as sporadic users may have been chronic users.
Chow:
PSM retrospective 6,781 hospitalized patients ≥50 years old in the USA who were on pre-hospital antiplatelet therapy (84% aspirin), and 10,566 matched controls, showing lower mortality with treatment.
Chow (B):
Retrospective 112,269 hospitalized COVID-19 patients in the USA, showing lower mortality with aspirin treatment.
Chow (C):
Retrospective 412 hospitalized patients, 98 treated with aspirin, showing lower mortality, ventilation, and ICU admission with treatment.
Connors:
Early terminated RCT with 164 aspirin and 164 control patients in the USA with very few events, showing no significant difference with aspirin treatment for the combined endpoint of all-cause mortality, symptomatic venous or arterial thromboembolism, myocardial infarction, stroke, and hospitalization for cardiovascular or pulmonary indication. There was no mortality and no major bleeding events among participants that started treatment (there was one ITT placebo death).
Drew:
Retrospective 2,736,091 individuals in the U.S., U.K., and Sweden, showing lower risk of hospital/clinic visits with aspirin use.
Eikelboom:
Late (5.4 days) outpatient RCT showing no significant difference in outcomes with aspirin treatment.
Eikelboom (B):
RCT very late stage (baseline SpO2 77%) patients, showing no significant differences with rivaroxaban and aspirin treatment.
Elhadi:
Prospective study of 465 COVID-19 ICU patients in Libya showing no significant differences with treatment.
Formiga:
Retrospective 20,641 hospitalized patients in Spain, showing no significant difference in outcomes with existing aspirin use.
Ghati:
RCT hospitalized patients in India, 224 treated with atorvastatin, 225 with aspirin, and 225 with both, showing lower serum interleukin-6 levels with aspirin, but no statistically significant changes in other outcomes. Low dose aspirin 75mg daily for 10 days.
Gogtay:
Retrospective 125 COVID+ hospitalized patients in the USA, showing no significant differences with aspirin prophylaxis.
Goshua:
PSM retrospective 2,785 hospitalized patients in the USA, showing lower mortality and higher ventilation and ICU admission with aspirin treatment.
Haji Aghajani:
Retrospective 991 hospitalized patients in Iran, showing lower mortality with aspirin treatment.
Holt:
Retrospective 689 hospitalized COVID-19 patients in Denmark, showing higher risk of ICU/death with aspirin use in unadjusted results subject to confounding by indication.
Husain:
Retrospective 42 patients in Bangladesh, 11 treated with aspirin, showing fewer complications with treatment.
Karimpour-Razkenari:
Retrospective 478 moderate to severe hospitalized patients in Iran, showing higher mortality with aspirin treatment. Authors note confounding by indication for aspirin treatment.
Karruli:
Retrospective 32 ICU patients showing lower mortality with aspirin treatment, without statistical significance.
Kim:
Retrospective database analysis of 22,660 patients tested for COVID-19 in South Korea. There was no significant difference in cases according to aspirin use. Aspirin use before COVID-19 was related to an increased death rate and aspirin use after COVID-19 was related to a higher risk of oxygen therapy.
Kim (B):
Retrospective database analysis of 22,660 patients tested for COVID-19 in South Korea. There was no significant difference in cases according to aspirin use. Aspirin use before COVID-19 was related to an increased death rate and aspirin use after COVID-19 was related to a higher risk of oxygen therapy.
Lal:
Retrospective 21,579 hospitalized COVID-19 patients mostly in the USA, showing lower risk of mortality and severity with existing aspirin use.
Levy:
Retrospective 849 COVID-19+ patients in skilled nursing homes, showing lower risk of combined hospitalization/death with aspirin prophylaxis, not reaching statistical significance.
Lewandowski:
Retrospective 430 hospitalized COVID-19 patients with type 2 diabetes in Poland showing lower mortality with metformin and higher mortality with remdesivir, convalescent plasma, and aspirin in univariable analysis. These results were not statistically significant except for aspirin, and no baseline information per treatment is provided to assess confounding.
Liu:
Retrospective PSM analysis of 232 hospitalized patients, 28 treated with aspirin, showing lower mortality with treatment. There was no significant difference in viral clearance.
Lodigiani:
Retrospective 388 hospitalized COVID-19 patients in Italy showing higher use of aspirin in ICU patients, without statistical significance.
Loucera:
Retrospective 15,968 COVID-19 hospitalized patients in Spain, showing lower mortality with existing use of several medications including metformin, HCQ, azithromycin, aspirin, vitamin D, vitamin C, and budesonide. Since only hospitalized patients are included, results do not reflect different probabilities of hospitalization across treatments.
Ma (B):
UK Biobank retrospective 77,271 patients aged 50-86, showing no significant differences with aspirin use. Matching lead to different results for the gender vs. overall analysis, for example the overall result for cases was OR 1.07, however both gender results are lower OR 0.97 and 1.02.
Malik:
Retrospective 539 patients in the USA, showing lower mortality, ICU admission, and ARDS with aspirin treatment, without statistical significance.
Mehrizi:
Retrospective study of 917,198 hospitalized COVID-19 cases covered by the Iran Health Insurance Organization over 26 months showing that antithrombotics, corticosteroids, and antivirals reduced mortality while diuretics, antibiotics, and antidiabetics increased it. Confounding makes some results very unreliable. For example, diuretics like furosemide are often used to treat fluid overload, which is more likely in ICU or advanced disease requiring aggressive fluid resuscitation. Hospitalization length has increased risk of significant confounding, for example longer hospitalization increases the chance of receiving a medication, and death may result in shorter hospitalization. Mortality results may be more reliable.
Confounding by indication is likely to be significant for many medications. Authors adjustments have very limited severity information (admission type refers to ward vs. ER department on initial arrival). We can estimate the impact of confounding from typical usage patterns, the prescription frequency, and attenuation or increase of risk for ICU vs. all patients.
Confounding by indication is likely to be significant for many medications. Authors adjustments have very limited severity information (admission type refers to ward vs. ER department on initial arrival). We can estimate the impact of confounding from typical usage patterns, the prescription frequency, and attenuation or increase of risk for ICU vs. all patients.
Meizlish:
Retrospective 638 matched hospitalized patients in the USA, 319 treated with aspirin, showing lower mortality with treatment.
Merzon:
Retrospective 10,477 patients in Israel, showing lower risk of COVID-19 cases with existing aspiring use.
Monserrat Villatoro:
PSM retrospective 3,712 hospitalized patients in Spain, showing lower mortality with existing use of azithromycin, bemiparine, budesonide-formoterol fumarate, cefuroxime, colchicine, enoxaparin, ipratropium bromide, loratadine, mepyramine theophylline acetate, oral rehydration salts, and salbutamol sulphate, and higher mortality with acetylsalicylic acid, digoxin, folic acid, mirtazapine, linagliptin, enalapril, atorvastatin, and allopurinol.
Morrison:
Retrospective 13,585 COVID+ patients in the USA, showing higher hospitalization with aspirin use, and no significant difference for mortality, ventilation, and ICU admission.
Mulhem:
Retrospective database analysis of 3,219 hospitalized patients in the USA. Very different results in the time period analysis (Table S2), and results significantly different to other studies for the same medications (e.g., heparin OR 3.06 [2.44-3.83]) suggest significant confounding by indication and confounding by time.
Mura:
PSM retrospective TriNetX database analysis of 1,379 severe COVID-19 patients requiring respiratory support, showing lower mortality with aspirin (not reaching statistical significance) and famotidine, and improved results from the combination of both.
Mustafa:
Retrospective 444 hospitalized patients in Pakistan, showing lower mortality with aspirin treatment in unadjusted results, not reaching statistical significance.
Nimer:
Retrospective 2,148 COVID-19 recovered patients in Jordan, showing no significant differences in the risk of severity and hospitalization with aspirin prophylaxis.
Oh:
Retrospective database analysis of 328,374 adults in South Korea, showing lower risk of COVID-19 cases with aspirin use, but no difference in mortality for COVID-19 patients.
Osborne:
Retrospective PSM analysis of pre-existing aspirin use in the USA, showing lower mortality with treatment.
Pan:
Retrospective 762 COVID+ hospitalized patients in the USA, 239 on antiplatelet medication (199 aspirin), showing no significant differences in outcomes.
For more discussion see135.
For more discussion see135.
Pourhoseingholi:
Prospective study of 2,468 hospitalized COVID-19 patients in Iran, showing higher mortality with aspirin treatment. IR.MUQ.REC.1399.013.
Prieto-Campo:
Population-based case-control study of 86,602 people in Spain, shower lower risk of COVID-19 cases with low-dose aspirin, but no significant difference for severity, hospitalization, or mortality.
Pérez-Segura:
Retrospective 770 COVID-19 patients with cancer, showing increased mortality with aspirin use in unadjusted results.
Ramos-Rincón:
Retrospective 790 hospitalized type 2 diabetes patients ≥80 years old in Spain, showing higher mortality with existing aspirin use.
RECOVERY Collaborative Group:
RCT 14,892 late stage patients, 7,351 treated with aspirin, showing slightly improved discharge and hospitalization time, and no significant difference for mortality.
Results are limited due to low dose (150mg daily), very late treatment (9 days post symptom onset), and 96% concurrent use of low molecular weight heparin. Greater benefits were seen for non-LMWH patients, and for very late (<= 7 days from onset) vs. extremely late (>7 days) treatment. For more discussion see141.
Results are limited due to low dose (150mg daily), very late treatment (9 days post symptom onset), and 96% concurrent use of low molecular weight heparin. Greater benefits were seen for non-LMWH patients, and for very late (<= 7 days from onset) vs. extremely late (>7 days) treatment. For more discussion see141.
Reese:
N3C retrospective 250,533 patients showing significantly higher mortality with aspirin use. Note that aspirin results were not included in the journal version or v2 of this preprint.
Sahai:
PSM retrospective 1,994 PCR+ patients in the USA, not showing a significant difference in mortality with aspirin treatment.
Sakamaki:
Retrospective 650,317 COVID-19 patients in Japan showing higher risk of severe COVID-19 with low-dose apirin use. Although cardiovascular disease should have been adjusted for (details of adjustments are not provided), there may be significant residual confounding because aspirin use might indicate more severe or complex cardiovascular issues not fully captured by the adjustment.
Santoro:
HOPE-COVID-19 PSM retrospective 7,824 patients, comparing prophylactic anticoagulation with and without additional treatment with aspirin in hospitalized patients, showing lower mortality with aspirin treatment.
Shamsi:
Retrospective 183 hospitalized pediatric COVID-19 patients in Iran, showing no significant difference in mortality with aspirin in unadjusted results.
Singla:
RCT 98 hospitalized patients in the USA, 49 treated with aspirin and dipyridamole, showing improved results with treatment, but without statistical significance.
Sisinni:
Retrospective 984 COVID-19 patients, 253 taking aspirin prior to admission, showing lower risk of respiratory support upgrade with treatment.
Son:
PSM retrospective case control study in South Korea, showing a trend towards lower mortality, but no significant differences with aspirin use.
Sullerot:
Retrospective 1,047 pneumonia patients in 5 COVID-19 geriatric units in France and Switzerland, significantly higher ICU admission and longer hospital stays with existing aspirin treatment. Numbers in this study appear to be inconsistent, for example the abstract says 147 of 301 aspirin patients died, shown as 34.3%, while Table 1 shows 104 of 301 (34.6%).
Tse:
PSM retrospective 2,664 COVID-19 hospitalized patients receiving steroids/antiviral therapy in Hong Kong, showing lower risk of combined death/intubation with aspirin use.
Vahedian-Azimi:
Retrospective 587 COVID+ hospitalized patients in Iran, showing no significant differences in outcomes with aspirin treatment.
Vinod:
Retrospective 376 hospitalized COVID-19 patients in the United States showing no significant differences with aspirin. Mortality, mechanical ventilation, and hypoxia were lower with treatment, without statistical significance.
Wang:
Retrospective 58 multiple myeloma COVID-19 patients in the USA, showing no significant difference with aspirin treatment.
Ware:
PSM retrospective 334,374 COVID-19 patients showing decreased risk of venous thromboembolism, including pulmonary embolism and deep vein thrombosis, but increased risk of arterial thromboembolic disorders, including ischemic stroke and acute ischemic heart disease, with aspirin use prior to COVID-19 diagnosis. The increased risk of arterial disease may be associated with preexisting cardiovascular disease for which aspirin was already prescribed. All cause mortality was lower in the aspirin group, however authors do not discuss this result.
Yuan:
Retrospective 183 hospitalized patients in China, 52 taking low-dose aspirin prior to hospitalization, showing no significant difference with treatment.
Zadeh:
Retrospective 4,017 coronary artery disease patients hospitalized for COVID-19 in the USA, showing no significant difference in outcomes with low dose aspirin use.
Zhao:
Retrospective 2,070 hospitalized patients in the USA, showing lower mortality with aspirin treatment.
We perform ongoing searches of PubMed, medRxiv, Europe PMC,
ClinicalTrials.gov, The Cochrane Library, Google Scholar, Research
Square, ScienceDirect, Oxford University Press, the reference lists of other
studies and meta-analyses, and submissions to the site c19early.org.
Search terms are aspirin and COVID-19 or SARS-CoV-2. Automated searches are performed twice daily, with all matches reviewed for inclusion.
All studies regarding the use of aspirin for COVID-19 that report
a comparison with a control group are included in the main analysis.
Sensitivity analysis is performed, excluding studies with major issues,
epidemiological studies, and studies with minimal available information.
This is a living analysis and is updated regularly.
We extracted effect sizes and associated data from all studies.
If studies report multiple kinds of effects then the most serious
outcome is used in pooled analysis, while other outcomes are included in the
outcome specific analyses. For example, if effects for mortality and cases are
both reported, the effect for mortality is used, this may be different to the
effect that a study focused on.
If symptomatic
results are reported at multiple times, we used the latest time, for example
if mortality results are provided at 14 days and 28 days, the results at 28
days have preference. Mortality alone is preferred over combined outcomes.
Outcomes with zero events in both arms are not used, the next most serious
outcome with one or more events is used. For example, in low-risk populations
with no mortality, a reduction in mortality with treatment is not possible,
however a reduction in hospitalization, for example, is still valuable.
Clinical outcomes are considered more important than viral test status. When
basically all patients recover in both treatment and control groups,
preference for viral clearance and recovery is given to results mid-recovery
where available. After most or all patients have recovered there is little or
no room for an effective treatment to do better, however faster recovery is
valuable.
If only individual symptom data is available, the most serious symptom has
priority, for example difficulty breathing or low SpO2 is more
important than cough.
When results provide an odds ratio, we compute the relative risk when
possible, or convert to a relative risk according to158.
Reported confidence intervals and p-values were used when available,
using adjusted values when provided. If multiple types of adjustments are
reported propensity score matching and multivariable regression has preference
over propensity score matching or weighting, which has preference over
multivariable regression. Adjusted results have preference over unadjusted
results for a more serious outcome when the adjustments significantly alter
results. When needed, conversion between reported p-values and
confidence intervals followed Altman, Altman (B), and Fisher's exact
test was used to calculate p-values for event data. If continuity
correction for zero values is required, we use the reciprocal of the opposite
arm with the sum of the correction factors equal to 1161.
Results are expressed with RR < 1.0 favoring treatment, and using the risk of
a negative outcome when applicable (for example, the risk of death rather than
the risk of survival). If studies only report relative continuous values such
as relative times, the ratio of the time for the treatment group versus the
time for the control group is used. Calculations are done in Python
(3.13.0) with
scipy (1.14.1), pythonmeta (1.26), numpy (1.26.4), statsmodels (0.14.4), and plotly (5.24.1).
Forest plots are computed using PythonMeta162
with the DerSimonian and Laird random effects model (the fixed effect
assumption is not plausible in this case) and inverse variance weighting.
Results are presented with 95% confidence intervals. Heterogeneity among studies was
assessed using the I2 statistic.
Mixed-effects meta-regression results are computed with R (4.4.0) using the metafor
(4.6-0) and rms (6.8-0) packages, and using the most serious sufficiently powered outcome.
For all statistical tests, a p-value less than 0.05 was considered statistically significant.
Grobid 0.8.0 is used to parse PDF documents.
We have classified studies as early treatment if most patients
are not already at a severe stage at the time of treatment (for example based
on oxygen status or lung involvement), and treatment started within 5 days of
the onset of symptoms. If studies contain a mix of early treatment and late
treatment patients, we consider the treatment time of patients contributing
most to the events (for example, consider a study where most patients are
treated early but late treatment patients are included, and all mortality
events were observed with late treatment patients).
We note that a shorter time may be preferable. Antivirals are typically only
considered effective when used within a shorter timeframe, for example 0-36 or
0-48 hours for oseltamivir, with longer delays not being effective49,50.
We received no funding, this research is done in our spare
time. We have no affiliations with any pharmaceutical companies or political
parties.
A summary of study results is below. Please submit
updates and corrections at https://c19early.org/emeta.html.
Effect extraction follows pre-specified rules as detailed above
and gives priority to more serious outcomes.
For pooled analyses, the first (most serious) outcome is used, which may
differ from the effect a paper focuses on.
Other outcomes are used in outcome specific analyses.
| Connors, 10/11/2021, Double Blind Randomized Controlled Trial, placebo-controlled, USA, peer-reviewed, 27 authors, study period September 2020 - June 2021, trial NCT04498273 (history) (ACTIV-4B). | risk of hospitalization, 67.3% lower, RR 0.33, p = 0.49, treatment 0 of 144 (0.0%), control 1 of 136 (0.7%), NNT 136, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), hospitalization for cardiovascular or pulmonary indication, suspected, started treatment. |
| risk of progression, 19.0% lower, RR 0.81, p = 0.78, treatment 6 of 144 (4.2%), control 7 of 136 (5.1%), NNT 102, acute medical event, suspected, started treatment. | |
| risk of progression, 5.6% lower, RR 0.94, p = 1.00, treatment 1 of 144 (0.7%), control 1 of 136 (0.7%), NNT 2448, combined endpoint of all-cause mortality, symptomatic venous or arterial thromboembolism, myocardial infarction, stroke, and hospitalization for cardiovascular or pulmonary indication, suspected, started treatment, primary outcome. |
Effect extraction follows pre-specified rules as detailed above
and gives priority to more serious outcomes.
For pooled analyses, the first (most serious) outcome is used, which may
differ from the effect a paper focuses on.
Other outcomes are used in outcome specific analyses.
| Abdelwahab, 7/30/2021, retrospective, Egypt, peer-reviewed, 17 authors. | risk of mechanical ventilation, 7.8% higher, RR 1.08, p = 0.93, treatment 11 of 31 (35.5%), control 6 of 36 (16.7%), adjusted per study, odds ratio converted to relative risk. |
| Aidouni, 11/30/2022, prospective, Morocco, preprint, mean age 64.0, 6 authors, study period March 2020 - March 2022. | risk of death, 30.9% lower, HR 0.69, p = 0.003, treatment 202 of 712 (28.4%), control 165 of 412 (40.0%), NNT 8.6, adjusted per study, multivariable, Cox proportional hazards. |
| risk of mechanical ventilation, 9.6% lower, RR 0.90, p = 0.33, treatment 189 of 712 (26.5%), control 121 of 412 (29.4%), NNT 35. | |
| Al Harthi, 9/3/2021, retrospective, propensity score matching, Saudi Arabia, peer-reviewed, 21 authors. | risk of death, 27.0% lower, HR 0.73, p = 0.03, treatment 98 of 176 (55.7%), control 107 of 173 (61.8%), adjusted per study, in-hospital mortality, multivariable Cox proportional hazards. |
| risk of death, 14.0% lower, HR 0.86, p = 0.30, treatment 95 of 176 (54.0%), control 97 of 175 (55.4%), adjusted per study, day 30, multivariable Cox proportional hazards. | |
| ICU time, 5.3% lower, relative time 0.95, p = 0.54, treatment median 9.0 IQR 11.0 n=176, control median 9.5 IQR 11.0 n=175. | |
| Alamdari, 9/9/2020, retrospective, Iran, peer-reviewed, 14 authors, average treatment delay 5.72 days, excluded in exclusion analyses: substantial unadjusted confounding by indication likely. | risk of death, 27.7% higher, RR 1.28, p = 0.52, treatment 9 of 53 (17.0%), control 54 of 406 (13.3%). |
| Ali (B), 10/31/2022, retrospective, Egypt, peer-reviewed, 3 authors. | risk of death, 39.6% lower, RR 0.60, p < 0.001, treatment 152 of 660 (23.0%), control 202 of 530 (38.1%), NNT 6.6. |
| risk of ARDS, 37.4% lower, RR 0.63, p = 0.001, treatment 74 of 660 (11.2%), control 95 of 530 (17.9%), NNT 15. | |
| Azimi Pirsaraei, 8/13/2024, retrospective, Iran, peer-reviewed, mean age 57.2, 5 authors, study period 20 March, 2020 - 20 June, 2020, excluded in exclusion analyses: unadjusted results with no group details. | risk of death, 96.9% higher, RR 1.97, p = 0.002, treatment 28 of 184 (15.2%), control 50 of 647 (7.7%). |
| Bradbury, 3/22/2022, Randomized Controlled Trial, multiple countries, peer-reviewed, 73 authors, study period 30 October, 2020 - 23 June, 2021, trial NCT02735707 (history) (REMAP-CAP). | risk of death, 16.0% lower, HR 0.84, p = 0.05, treatment 165 of 563 (29.3%), control 170 of 521 (32.6%), NNT 30, inverted to make HR<1 favor treatment, Kaplan–Meier, day 90. |
| risk of no hospital discharge, 16.9% lower, RR 0.83, p = 0.08, treatment 161 of 563 (28.6%), control 167 of 521 (32.1%), NNT 29, adjusted per study, inverted to make RR<1 favor treatment, odds ratio converted to relative risk. | |
| risk of progression, 21.0% lower, RR 0.79, p = 0.02, treatment 204 of 563 (36.2%), control 212 of 521 (40.7%), adjusted per study, odds ratio converted to relative risk, combined death/thrombosis. | |
| risk of progression, 4.8% lower, OR 0.95, p = 0.67, treatment 563, control 521, adjusted per study, inverted to make OR<1 favor treatment, support-free days, primary outcome, RR approximated with OR. | |
| Chow (B), 3/24/2022, retrospective, USA, peer-reviewed, median age 63.0, 89 authors. | risk of death, 13.5% lower, RR 0.87, p < 0.001, treatment 1,410 of 13,795 (10.2%), control 11,577 of 98,275 (11.8%), NNT 64, adjusted per study, odds ratio converted to relative risk, propensity score weighting. |
| Chow (C), 4/1/2021, retrospective, USA, peer-reviewed, 38 authors. | risk of death, 47.0% lower, HR 0.53, p = 0.02, treatment 26 of 98 (26.5%), control 73 of 314 (23.2%), adjusted per study, Cox proportional hazards. |
| risk of mechanical ventilation, 44.0% lower, HR 0.56, p = 0.007, treatment 35 of 98 (35.7%), control 152 of 314 (48.4%), NNT 7.9, adjusted per study, Cox proportional hazards. | |
| risk of ICU admission, 43.0% lower, HR 0.57, p = 0.007, treatment 38 of 98 (38.8%), control 160 of 314 (51.0%), NNT 8.2, adjusted per study, Cox proportional hazards. | |
| Eikelboom, 10/10/2022, Randomized Controlled Trial, Canada, peer-reviewed, mean age 45.0, 31 authors, study period 27 August, 2020 - 10 February, 2022, average treatment delay 5.4 days, trial NCT04324463 (history) (ACT outpatient). | risk of death, 9.0% higher, HR 1.09, p = 0.84, treatment 12 of 1,945 (0.6%), control 11 of 1,936 (0.6%). |
| risk of progression, 20.0% lower, HR 0.80, p = 0.21, treatment 59 of 1,945 (3.0%), control 73 of 1,936 (3.8%), NNT 136, major thrombosis, hospitalisation, or death, primary outcome. | |
| risk of hospitalization, 17.0% lower, HR 0.83, p = 0.31, treatment 56 of 1,945 (2.9%), control 67 of 1,936 (3.5%), NNT 172. | |
| Eikelboom (B), 10/10/2022, Randomized Controlled Trial, multiple countries, peer-reviewed, mean age 56.0, 29 authors, study period 2 October, 2020 - 10 February, 2022, average treatment delay 7.0 days, this trial uses multiple treatments in the treatment arm (combined with rivaroxaban) - results of individual treatments may vary, trial NCT04324463 (history) (ACT inpatient). | risk of death, 5.0% higher, HR 1.05, p = 0.66, treatment 193 of 1,063 (18.2%), control 186 of 1,056 (17.6%). |
| risk of progression, 8.0% lower, HR 0.92, p = 0.32, treatment 281 of 1,063 (26.4%), control 300 of 1,056 (28.4%), NNT 51, major thrombosis, high-flow oxygen, ventilation, or death. | |
| risk of progression, 11.0% lower, HR 0.89, p = 0.27, treatment 191 of 1,063 (18.0%), control 210 of 1,056 (19.9%), NNT 52, high-flow oxygen or ventilation. | |
| Elhadi, 4/30/2021, prospective, Libya, peer-reviewed, 21 authors, study period 29 May, 2020 - 30 December, 2020, excluded in exclusion analyses: unadjusted results with no group details. | risk of death, 9.7% lower, RR 0.90, p = 0.50, treatment 22 of 40 (55.0%), control 259 of 425 (60.9%), NNT 17. |
| Ghati, 7/9/2022, Randomized Controlled Trial, India, peer-reviewed, 14 authors, study period 28 July, 2020 - 27 January, 2021, average treatment delay 6.0 days, trial CTRI/2020/07/026791 (RESIST). | risk of death, 22.1% lower, RR 0.78, p = 0.62, treatment 11 of 442 (2.5%), control 7 of 219 (3.2%), NNT 141, aspirin and aspirin/atorvastatin vs. control, modified intention-to-treat. |
| risk of death, 57.5% lower, RR 0.42, p = 0.22, treatment 3 of 221 (1.4%), control 7 of 219 (3.2%), NNT 54, aspirin vs. control, modified intention-to-treat. | |
| risk of mechanical ventilation, 9.2% lower, RR 0.91, p = 0.80, treatment 11 of 442 (2.5%), control 6 of 219 (2.7%), NNT 398, aspirin and aspirin/atorvastatin vs. control, modified intention-to-treat. | |
| risk of mechanical ventilation, 50.5% lower, RR 0.50, p = 0.34, treatment 3 of 221 (1.4%), control 6 of 219 (2.7%), NNT 72, aspirin vs. control, modified intention-to-treat. | |
| risk of progression, 30.0% lower, HR 0.70, p = 0.46, treatment 11 of 442 (2.5%), control 7 of 219 (3.2%), NNT 141, aspirin and aspirin/atorvastatin vs. control, Cox proportional hazards, modified intention-to-treat, primary outcome. | |
| risk of progression, 60.0% lower, HR 0.40, p = 0.18, treatment 3 of 221 (1.4%), control 7 of 219 (3.2%), NNT 54, aspirin vs. control, Cox proportional hazards, modified intention-to-treat, primary outcome. | |
| Goshua, 11/5/2020, retrospective, USA, peer-reviewed, 15 authors. | risk of death, 35.0% lower, OR 0.65, p = 0.04, treatment 319, control 319, propensity score matching, RR approximated with OR. |
| risk of mechanical ventilation, 49.0% higher, OR 1.49, p = 0.04, treatment 319, control 319, propensity score matching, RR approximated with OR. | |
| risk of ICU admission, 45.0% higher, OR 1.45, p = 0.02, treatment 319, control 319, propensity score matching, RR approximated with OR. | |
| Haji Aghajani, 4/29/2021, retrospective, Iran, peer-reviewed, 7 authors. | risk of death, 24.7% lower, HR 0.75, p = 0.04, treatment 336, control 655, adjusted per study, Cox proportional hazards, RR approximated with OR. |
| Husain, 10/31/2020, retrospective, Bangladesh, preprint, 4 authors. | risk of death, 80.3% lower, RR 0.20, p = 0.55, treatment 0 of 11 (0.0%), control 3 of 31 (9.7%), NNT 10, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm). |
| risk of no recovery, 64.8% lower, RR 0.35, p = 0.40, treatment 1 of 11 (9.1%), control 8 of 31 (25.8%), NNT 6.0. | |
| complications, 95.8% lower, RR 0.04, p = 0.001, treatment 0 of 11 (0.0%), control 17 of 31 (54.8%), NNT 1.8, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm). | |
| Karimpour-Razkenari, 10/3/2022, retrospective, Iran, peer-reviewed, median age 58.5, 9 authors, study period 23 February, 2020 - 23 May, 2020, excluded in exclusion analyses: substantial unadjusted confounding by indication likely. | risk of death, 123.2% higher, RR 2.23, p = 0.008, treatment 39 of 90 (43.3%), control 64 of 363 (17.6%), adjusted per study, inverted to make RR<1 favor treatment, odds ratio converted to relative risk, multivariable. |
| Karruli, 9/1/2021, retrospective, Italy, peer-reviewed, 13 authors, study period March 2020 - May 2020. | risk of death, 46.3% lower, RR 0.54, p = 0.63, treatment 1 of 5 (20.0%), control 22 of 27 (81.5%), NNT 1.6, adjusted per study, odds ratio converted to relative risk, multivariable. |
| Kim (B), 9/4/2021, retrospective, propensity score matching, South Korea, peer-reviewed, 7 authors. | risk of death, 33.7% lower, RR 0.66, p = 0.22, treatment 14 of 124 (11.3%), control 23 of 135 (17.0%), NNT 17, PSM. |
| risk of mechanical ventilation, 102.2% higher, RR 2.02, p = 0.16, treatment 13 of 124 (10.5%), control 7 of 135 (5.2%), PSM. | |
| risk of ICU admission, 90.5% higher, RR 1.91, p = 0.36, treatment 7 of 124 (5.6%), control 4 of 135 (3.0%), PSM. | |
| Lewandowski, 3/7/2024, retrospective, Poland, peer-reviewed, 15 authors. | risk of death, 70.3% higher, OR 1.70, p = 0.02, RR approximated with OR. |
| Liu, 2/12/2021, retrospective, propensity score matching, China, peer-reviewed, 8 authors. | risk of death, 75.0% lower, HR 0.25, p = 0.03, treatment 2 of 28 (7.1%), control 11 of 204 (5.4%), adjusted per study, 60 days, KM, PSM. |
| risk of death, 81.0% lower, HR 0.19, p = 0.02, treatment 1 of 28 (3.6%), control 9 of 204 (4.4%), adjusted per study, 30 days, KM, PSM. | |
| time to viral-, 1.9% higher, relative time 1.02, p = 0.94, treatment 24, control 24, PSM. | |
| Mehrizi, 12/18/2023, retrospective, Iran, peer-reviewed, 10 authors, study period 1 February, 2020 - 20 March, 2022. | risk of death, 16.0% lower, OR 0.84, p < 0.001, RR approximated with OR. |
| Meizlish, 1/21/2021, retrospective, propensity score matching, USA, peer-reviewed, 22 authors. | risk of death, 47.8% lower, HR 0.52, p = 0.004, treatment 319, control 319, PSM. |
| Mura, 3/31/2021, retrospective, database analysis, multiple countries, peer-reviewed, 6 authors. | risk of death, 15.4% lower, RR 0.85, p = 0.08, treatment 527, control 527, odds ratio converted to relative risk, aspirin only, control prevalence approximated with treatment prevalence, propensity score matching. |
| risk of death, 37.3% lower, RR 0.63, p = 0.001, treatment 305, control 305, odds ratio converted to relative risk, famotidine and aspirin, control prevalence approximated with treatment prevalence, propensity score matching. | |
| Mustafa, 12/29/2021, retrospective, Pakistan, peer-reviewed, 7 authors, excluded in exclusion analyses: unadjusted results with no group details. | risk of death, 44.1% lower, RR 0.56, p = 0.28, treatment 4 of 66 (6.1%), control 41 of 378 (10.8%), NNT 21. |
| Pourhoseingholi, 5/26/2021, prospective, Iran, preprint, mean age 57.9, 11 authors, study period 2 February, 2020 - 20 July, 2020, average treatment delay 7.4 days. | risk of death, 32.0% higher, HR 1.32, p = 0.04, treatment 71 of 290 (24.5%), control 268 of 2,178 (12.3%), adjusted per study, multivariable, Cox proportional hazards. |
| RECOVERY Collaborative Group, 11/18/2021, Randomized Controlled Trial, multiple countries, peer-reviewed, 35 authors, study period 1 November, 2020 - 21 March, 2021, average treatment delay 9.0 days, RECOVERY trial. | risk of death, 4.0% lower, RR 0.96, p = 0.35, treatment 7,351, control 7,541. |
| risk of death, 17.0% lower, RR 0.83, p = 0.35, treatment 7,351, control 7,541, non-LMWH. | |
| risk of mechanical ventilation, 5.0% lower, RR 0.95, p = 0.32, treatment 7,351, control 7,541. | |
| risk of no hospital discharge, 5.7% lower, RR 0.94, p = 0.006, treatment 7,351, control 7,541, inverted to make RR<1 favor treatment. | |
| risk of no hospital discharge, 16.0% lower, RR 0.84, p = 0.04, treatment 7,351, control 7,541, inverted to make RR<1 favor treatment, non-LMWH. | |
| Sahai, 5/19/2021, retrospective, propensity score matching, USA, peer-reviewed, 18 authors. | risk of death, 13.2% lower, RR 0.87, p = 0.53, treatment 33 of 248 (13.3%), control 38 of 248 (15.3%), NNT 50. |
| Santoro, 6/22/2022, retrospective, propensity score matching, multivariable, multiple countries, peer-reviewed, 31 authors, study period 16 January, 2020 - 30 May, 2020. | risk of death, 38.0% lower, HR 0.62, p = 0.02, treatment 360, control 2,949. |
| Shamsi, 7/17/2023, retrospective, Iran, peer-reviewed, 4 authors, study period 1 March, 2020 - 1 August, 2021, excluded in exclusion analyses: unadjusted results with no group details. | risk of death, 96.3% lower, RR 0.04, p = 0.22, treatment 0 of 13 (0.0%), control 24 of 170 (14.1%), NNT 7.1, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm). |
| Singla, 1/30/2023, Randomized Controlled Trial, USA, peer-reviewed, 26 authors, study period 1 October, 2020 - 30 April, 2021, this trial uses multiple treatments in the treatment arm (combined with dipyridamole) - results of individual treatments may vary, trial NCT04410328 (history). | risk of death, 57.4% lower, RR 0.43, p = 0.44, treatment 3 of 49 (6.1%), control 5 of 49 (10.2%), adjusted per study, odds ratio converted to relative risk, multivariable, day 28. |
| risk of death, 15.0% lower, OR 0.85, p = 0.87, treatment 49, control 49, adjusted per study, multivariable, day 14, RR approximated with OR. | |
| risk of mechanical ventilation, 20.0% lower, RR 0.80, p = 1.00, treatment 4 of 49 (8.2%), control 5 of 49 (10.2%), NNT 49. | |
| risk of ICU admission, 28.6% lower, RR 0.71, p = 0.76, treatment 5 of 49 (10.2%), control 7 of 49 (14.3%), NNT 25. | |
| risk of progression, 33.3% lower, RR 0.67, p = 0.74, treatment 4 of 49 (8.2%), control 6 of 49 (12.2%), NNT 24, day 28. | |
| risk of progression, 76.3% lower, RR 0.24, p = 0.22, treatment 4 of 49 (8.2%), control 7 of 49 (14.3%), odds ratio converted to relative risk, respiratory failure, day 28. | |
| risk of progression, 44.4% lower, RR 0.56, p = 0.39, treatment 5 of 49 (10.2%), control 9 of 49 (18.4%), NNT 12, AKI. | |
| risk of progression, 85.7% lower, RR 0.14, p = 0.24, treatment 0 of 49 (0.0%), control 3 of 49 (6.1%), NNT 16, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), DIC. | |
| risk of progression, 25.0% lower, RR 0.75, p = 0.62, treatment 9 of 49 (18.4%), control 12 of 49 (24.5%), NNT 16, liver dysfunction. | |
| Vahedian-Azimi, 7/20/2021, retrospective, Iran, peer-reviewed, 9 authors. | risk of death, 21.9% lower, RR 0.78, p = 0.56, treatment 13 of 337 (3.9%), control 28 of 250 (11.2%), adjusted per study, odds ratio converted to relative risk, multivariable, primary outcome. |
| risk of ICU admission, 10.5% higher, RR 1.10, p = 0.67, treatment 36 of 337 (10.7%), control 44 of 250 (17.6%), adjusted per study, odds ratio converted to relative risk, multivariable. | |
| Vinod, 6/24/2024, retrospective, USA, peer-reviewed, mean age 66.8, 8 authors, study period March 2020 - October 2020. | risk of death, 14.4% lower, OR 0.86, p = 0.61, treatment 128, control 248, adjusted per study, multivariable, RR approximated with OR. |
| risk of mechanical ventilation, 30.3% lower, OR 0.70, p = 0.24, treatment 128, control 248, adjusted per study, multivariable, RR approximated with OR. | |
| hypoxia, 39.6% lower, OR 0.60, p = 0.0497, treatment 128, control 248, adjusted per study, multivariable, RR approximated with OR. | |
| readmisson, 5.8% higher, OR 1.06, p = 0.88, treatment 128, control 248, adjusted per study, multivariable, RR approximated with OR. | |
| DVT/PE, 17.7% lower, OR 0.82, p = 0.77, treatment 128, control 248, adjusted per study, multivariable, RR approximated with OR. | |
| Zhao, 10/1/2021, retrospective, USA, peer-reviewed, 6 authors. | risk of death, 43.0% lower, HR 0.57, p < 0.001, treatment 121 of 473 (25.6%), control 140 of 473 (29.6%), adjusted per study, PSM. |
| risk of death, 28.0% lower, HR 0.72, p = 0.03, treatment 473, control 1,597, adjusted per study, multivariable. |
Effect extraction follows pre-specified rules as detailed above
and gives priority to more serious outcomes.
For pooled analyses, the first (most serious) outcome is used, which may
differ from the effect a paper focuses on.
Other outcomes are used in outcome specific analyses.
| Abul, 8/4/2022, retrospective, USA, preprint, mean age 72.3, 10 authors, study period 13 December, 2020 - 18 September, 2021. | risk of death, 33.0% lower, HR 0.67, p = 0.03, treatment 46 of 511 (9.0%), control 201 of 1,176 (17.1%), Cox proportional hazards, day 56. |
| risk of death, 40.0% lower, HR 0.60, p = 0.01, treatment 33 of 511 (6.5%), control 154 of 1,176 (13.1%), Cox proportional hazards, day 30. | |
| risk of hospitalization, 20.0% lower, HR 0.80, p = 0.13, treatment 103 of 511 (20.2%), control 352 of 1,176 (29.9%), Cox proportional hazards. | |
| Ali, 11/19/2022, retrospective, USA, peer-reviewed, 8 authors. | risk of death, 28.0% lower, HR 0.72, p = 0.07, treatment 481, control 1,164, Cox proportional hazards. |
| Aweimer, 3/29/2023, retrospective, Germany, peer-reviewed, median age 67.0, 19 authors, study period 1 March, 2020 - 31 August, 2021, excluded in exclusion analyses: unadjusted results with no group details. | risk of death, 9.6% higher, RR 1.10, p = 0.43, treatment 34 of 44 (77.3%), control 74 of 105 (70.5%). |
| Azizi, 2/17/2023, retrospective, Iran, peer-reviewed, 6 authors, excluded in exclusion analyses: age matching based on only two categories, matching may be very poor given the relationship between age and COVID-19 risk; inconsistent data. | risk of death, no change, RR 1.00, p = 1.00, treatment 17 of 131 (13.0%), control 17 of 131 (13.0%). |
| Basheer, 10/2/2021, retrospective, Israel, peer-reviewed, 4 authors. | risk of death, 13.0% higher, RR 1.13, p < 0.001, treatment 45 of 140 (32.1%), control 29 of 250 (11.6%), adjusted per study, odds ratio converted to relative risk, group sizes approximated (only percentages provided). |
| Bejan, 2/28/2021, retrospective, USA, peer-reviewed, mean age 42.0, 6 authors. | risk of mechanical ventilation, 1.0% lower, OR 0.99, p = 0.97, treatment 1,899, control 7,330, adjusted per study, RR approximated with OR. |
| Botton, 6/17/2022, retrospective, France, peer-reviewed, 7 authors. | risk of death/intubation, 4.0% higher, HR 1.04, p = 0.18, Cox proportional hazards. |
| risk of hospitalization, 3.0% higher, HR 1.03, p = 0.046, Cox proportional hazards. | |
| Campbell, 5/5/2022, retrospective, USA, peer-reviewed, 4 authors, study period 2 March, 2020 - 14 December, 2020. | risk of death, 3.0% lower, OR 0.97, p = 0.06, treatment 419, control 20,311, adjusted per study, propensity score weighting, multivariable, day 60, RR approximated with OR. |
| risk of death, 2.0% lower, OR 0.98, p = 0.10, treatment 419, control 20,311, adjusted per study, propensity score weighting, multivariable, day 30, RR approximated with OR. | |
| Chow, 8/29/2021, retrospective, propensity score matching, USA, peer-reviewed, 12 authors. | risk of death, 19.0% lower, HR 0.81, p < 0.005, treatment 1,280 of 6,781 (18.9%), control 2,271 of 10,566 (21.5%), NNT 38, adjusted per study, Kaplan Meier. |
| risk of mechanical ventilation, 2.8% lower, HR 0.97, p = 0.21, treatment 2,122 of 6,781 (31.3%), control 3,403 of 10,566 (32.2%), NNT 109. | |
| Drew, 5/2/2021, retrospective, multiple countries, preprint, 25 authors, study period 24 March, 2020 - 8 May, 2020. | risk of progression, 22.0% lower, HR 0.78, p = 0.30, adjusted per study, seen in hospital/clinic, comorbidity and symptom adjusted, multivariable. |
| risk of case, 3.0% higher, HR 1.03, p = 0.80, adjusted per study, comorbidity and symptom adjusted, multivariable. | |
| Formiga, 11/29/2021, retrospective, USA, peer-reviewed, 24 authors, study period 1 March, 2020 - 1 May, 2021. | risk of death, 3.4% higher, RR 1.03, p = 0.48, treatment 1,000 of 3,291 (30.4%), control 874 of 2,885 (30.3%), odds ratio converted to relative risk, propensity score matching. |
| risk of mechanical ventilation, 3.2% higher, RR 1.03, p = 0.75, treatment 213 of 3,291 (6.5%), control 181 of 2,885 (6.3%), propensity score matching. | |
| risk of ICU admission, 4.2% higher, RR 1.04, p = 0.65, treatment 283 of 3,291 (8.6%), control 238 of 2,885 (8.2%), propensity score matching. | |
| Gogtay, 3/9/2022, retrospective, USA, peer-reviewed, 4 authors, study period March 2020 - April 2020. | risk of death, 5.9% higher, RR 1.06, p = 0.87, treatment 12 of 38 (31.6%), control 21 of 87 (24.1%), adjusted per study, inverted to make RR<1 favor treatment, odds ratio converted to relative risk, multivariable. |
| risk of mechanical ventilation, 49.8% lower, RR 0.50, p = 0.16, treatment 5 of 38 (13.2%), control 21 of 87 (24.1%), NNT 9.1, adjusted per study, odds ratio converted to relative risk, multivariable. | |
| risk of ICU admission, 49.2% lower, RR 0.51, p = 0.41, treatment 9 of 38 (23.7%), control 38 of 87 (43.7%), NNT 5.0, adjusted per study, odds ratio converted to relative risk, multivariable. | |
| Holt, 5/7/2020, retrospective, Denmark, peer-reviewed, median age 70.0, 4 authors, study period 1 March, 2020 - 1 April, 2020, excluded in exclusion analyses: unadjusted results with no group details. | risk of death/ICU, 34.0% higher, RR 1.34, p = 0.09, treatment 35 of 116 (30.2%), control 129 of 573 (22.5%). |
| Kim, 9/4/2021, retrospective, propensity score matching, South Korea, peer-reviewed, 7 authors. | risk of death, 700.0% higher, RR 8.00, p = 0.03, treatment 6 of 15 (40.0%), control 1 of 20 (5.0%), PSM, prior aspirin use. |
| risk of mechanical ventilation, 433.3% higher, RR 5.33, p = 0.14, treatment 4 of 15 (26.7%), control 1 of 20 (5.0%), PSM, prior aspirin use. | |
| risk of ICU admission, 433.3% higher, RR 5.33, p = 0.14, treatment 4 of 15 (26.7%), control 1 of 20 (5.0%), PSM, prior aspirin use. | |
| risk of case, 33.4% lower, RR 0.67, p = 0.29, treatment 15 of 136 (11.0%), control 20 of 136 (14.7%), NNT 27, adjusted per study, odds ratio converted to relative risk, PSM, logistic regression, prior aspirin use. | |
| risk of death, 33.7% lower, RR 0.66, p = 0.22, treatment 14 of 124 (11.3%), control 23 of 135 (17.0%), NNT 17, PSM, aspirin treatment after diagnosis. | |
| risk of mechanical ventilation, 102.2% higher, RR 2.02, p = 0.16, treatment 13 of 124 (10.5%), control 7 of 135 (5.2%), PSM, aspirin treatment after diagnosis. | |
| risk of ICU admission, 90.5% higher, RR 1.91, p = 0.36, treatment 7 of 124 (5.6%), control 4 of 135 (3.0%), PSM, aspirin treatment after diagnosis. | |
| Lal, 5/5/2022, retrospective, USA, peer-reviewed, 20 authors, study period 15 February, 2020 - 30 September, 2021, trial NCT04323787 (history). | risk of death, 11.0% lower, HR 0.89, p = 0.01, treatment 4,691, control 16,888, adjusted per study, multivariable. |
| risk of ICU admission, 22.0% lower, HR 0.78, p < 0.001, treatment 4,691, control 16,888, adjusted per study, multivariable. | |
| risk of progression, 9.0% lower, HR 0.91, p = 0.02, treatment 4,691, control 16,888, adjusted per study, multivariable. | |
| Levy, 1/31/2022, retrospective, Israel, peer-reviewed, 10 authors. | risk of death/hospitalization, 26.0% lower, HR 0.74, p = 0.13, treatment 29 of 159 (18.2%), control 178 of 690 (25.8%), NNT 13, adjusted per study, multivariable, Cox proportional hazards, day 40. |
| Lodigiani, 7/31/2020, retrospective, Italy, peer-reviewed, median age 66.0, 12 authors, study period 13 February, 2020 - 10 April, 2020. | risk of ICU admission, 20.8% higher, RR 1.21, p = 0.52, treatment 17 of 94 (18.1%), control 44 of 294 (15.0%). |
| Loucera, 8/16/2022, retrospective, Spain, peer-reviewed, 8 authors, study period January 2020 - November 2020. | risk of death, 17.7% lower, HR 0.82, p < 0.001, treatment 2,127, control 13,841, Cox proportional hazards, day 30. |
| Ma (B), 8/18/2021, retrospective, propensity score matching, United Kingdom, peer-reviewed, 9 authors. | risk of death, 9.0% lower, OR 0.91, p = 0.12, treatment 12,471, control 64,750, RR approximated with OR. |
| risk of hospitalization, 2.0% lower, OR 0.98, p = 0.47, treatment 12,471, control 64,750, RR approximated with OR. | |
| risk of symptomatic case, 9.0% higher, OR 1.09, p = 0.18, treatment 12,471, control 64,750, RR approximated with OR. | |
| risk of case, 7.0% higher, OR 1.07, p = 0.09, treatment 12,471, control 64,750, RR approximated with OR. | |
| Malik, 7/11/2022, retrospective, USA, peer-reviewed, 16 authors, study period 1 March, 2020 - 1 December, 2020. | risk of death, 13.6% lower, RR 0.86, p = 0.72, treatment 15 of 87 (17.2%), control 24 of 223 (10.8%), adjusted per study, odds ratio converted to relative risk, multivariable. |
| risk of ICU admission, 27.8% lower, RR 0.72, p = 0.17, treatment 28 of 87 (32.2%), control 77 of 223 (34.5%), adjusted per study, odds ratio converted to relative risk, multivariable. | |
| risk of ARDS, 25.1% lower, RR 0.75, p = 0.39, treatment 13 of 87 (14.9%), control 40 of 223 (17.9%), NNT 33, adjusted per study, odds ratio converted to relative risk, multivariable. | |
| risk of hospitalization, 2.4% lower, OR 0.98, p = 0.94, treatment 25, control 176, adjusted per study, multivariable, RR approximated with OR. | |
| Merzon, 2/23/2021, retrospective, Israel, peer-reviewed, 8 authors. | risk of case, 27.6% lower, RR 0.72, p = 0.04, treatment 73 of 1,621 (4.5%), control 589 of 8,856 (6.7%), NNT 47, adjusted per study, odds ratio converted to relative risk. |
| risk of death, 62.4% lower, RR 0.38, p = 0.51, treatment 1 of 21 (4.8%), control 6 of 91 (6.6%), adjusted per study, odds ratio converted to relative risk. | |
| time to viral-, 9.6% lower, relative time 0.90, p = 0.045, treatment 73, control 589, time to 2nd negative test. | |
| time to viral-, 14.8% lower, relative time 0.85, p = 0.005, treatment 73, control 589, time to 1st negative test. | |
| Monserrat Villatoro, 1/8/2022, retrospective, propensity score matching, Spain, peer-reviewed, 18 authors. | risk of death, 31.0% higher, OR 1.31, p = 0.04, RR approximated with OR. |
| Morrison, 10/10/2022, retrospective, USA, peer-reviewed, mean age 62.5, 3 authors, study period March 2020 - March 2021. | risk of death, 7.7% lower, OR 0.92, p = 0.52, treatment 1,667, control 1,667, propensity score matching, RR approximated with OR. |
| risk of mechanical ventilation, 0.9% higher, OR 1.01, p = 0.96, treatment 1,667, control 1,667, propensity score matching, RR approximated with OR. | |
| risk of ICU admission, 12.2% higher, OR 1.12, p = 0.36, treatment 1,667, control 1,667, propensity score matching, RR approximated with OR. | |
| risk of hospitalization, 18.3% higher, OR 1.18, p = 0.04, treatment 1,667, control 1,667, propensity score matching, RR approximated with OR. | |
| Mulhem, 4/7/2021, retrospective, database analysis, USA, peer-reviewed, 3 authors, excluded in exclusion analyses: substantial unadjusted confounding by indication likely; substantial confounding by time likely due to declining usage over the early stages of the pandemic when overall treatment protocols improved dramatically. | risk of death, 13.9% higher, RR 1.14, p = 0.21, treatment 300 of 1,354 (22.2%), control 216 of 1,865 (11.6%), adjusted per study, odds ratio converted to relative risk, Table S1, logistic regression. |
| Nimer, 2/28/2022, retrospective, Jordan, peer-reviewed, survey, 4 authors, study period March 2021 - July 2021. | risk of hospitalization, 3.7% lower, RR 0.96, p = 0.08, treatment 83 of 427 (19.4%), control 136 of 1,721 (7.9%), adjusted per study, odds ratio converted to relative risk, multivariable. |
| risk of severe case, 17.8% higher, RR 1.18, p = 0.28, treatment 98 of 427 (23.0%), control 162 of 1,721 (9.4%), adjusted per study, odds ratio converted to relative risk, multivariable. | |
| Oh, 6/17/2021, retrospective, database analysis, South Korea, peer-reviewed, 4 authors. | risk of death, 1.0% lower, OR 0.99, p = 0.95, adjusted per study, multivariable, RR approximated with OR. |
| risk of case, 12.0% lower, RR 0.88, p = 0.04, adjusted per study, odds ratio converted to relative risk, multivariable, control prevalance approximated with overall prevalence. | |
| Osborne, 2/11/2021, retrospective, propensity score matching, USA, peer-reviewed, 6 authors. | risk of death, 59.4% lower, RR 0.41, p < 0.001, treatment 272 of 6,300 (4.3%), control 661 of 6,300 (10.5%), NNT 16, odds ratio converted to relative risk, 30 days, PSM. |
| risk of death, 60.5% lower, RR 0.40, p < 0.001, treatment 170 of 6,814 (2.5%), control 427 of 6,814 (6.3%), NNT 27, odds ratio converted to relative risk, 14 days, PSM. | |
| Pan, 5/26/2021, retrospective, USA, peer-reviewed, 11 authors, study period 1 March, 2020 - 9 April, 2020. | risk of death, 13.0% higher, OR 1.13, p = 0.63, treatment 239, control 523, adjusted per study, MOS 6 vs. <6, multivariable, RR approximated with OR. |
| risk of death/intubation, 2.0% higher, OR 1.02, p = 0.93, treatment 239, control 523, adjusted per study, MOS 5+ vs. <5, multivariable, RR approximated with OR. | |
| Prieto-Campo, 1/6/2024, retrospective, Spain, peer-reviewed, 6 authors. | risk of death, 13.0% higher, OR 1.13, p = 0.38, adjusted per study, case control OR. |
| risk of hospitalization, 3.0% lower, OR 0.97, p = 0.64, adjusted per study, case control OR. | |
| risk of progression, no change, OR 1.00, p = 0.98, adjusted per study, case control OR. | |
| risk of case, 8.0% lower, OR 0.92, p = 0.02, adjusted per study, case control OR. | |
| Pérez-Segura, 10/4/2021, retrospective, multiple countries, peer-reviewed, 23 authors. | risk of death, 49.1% higher, RR 1.49, p < 0.001, treatment 66 of 155 (42.6%), control 183 of 608 (30.1%), odds ratio converted to relative risk. |
| Ramos-Rincón, 12/28/2020, retrospective, Spain, preprint, 25 authors, study period 1 March, 2020 - 29 May, 2020. | risk of death, 28.9% higher, RR 1.29, p = 0.02, treatment 132 of 264 (50.0%), control 253 of 526 (48.1%), adjusted per study, odds ratio converted to relative risk, multivariable. |
| Reese, 4/20/2021, retrospective, USA, preprint, 23 authors. | risk of death, 61.0% higher, HR 1.61, p < 0.001, treatment 4,921, control 4,921, propensity score matching, Cox proportional hazards, Table S55. |
| risk of severe case, 309.0% higher, OR 4.09, p < 0.001, treatment 4,921, control 4,921, propensity score matching, Table S47, RR approximated with OR. | |
| Sakamaki, 9/27/2024, retrospective, Japan, peer-reviewed, mean age 52.1, 3 authors, study period 15 January, 2020 - 31 December, 2022. | risk of severe case, 37.0% higher, OR 1.37, p < 0.001, adjusted per study, multivariable, RR approximated with OR. |
| Sisinni, 10/4/2021, retrospective, Italy, peer-reviewed, 18 authors. | risk of death, 7.1% higher, RR 1.07, p = 0.65, treatment 93 of 253 (36.8%), control 251 of 731 (34.3%). |
| risk of death or respiratory support upgrade, 30.3% lower, RR 0.70, p = 0.01, treatment 253, control 731, multivariate. | |
| Son, 7/30/2021, retrospective, propensity score matching, South Korea, peer-reviewed, 6 authors. | risk of death, 11.0% lower, OR 0.89, p = 0.67, treatment 58 of 210 (27.6%) cases, 54 of 210 (25.7%) controls, adjusted per study, case control OR, group 2, model 1, multivariable. |
| risk of death, 24.0% lower, OR 0.76, p = 0.52, treatment 37 of 128 (28.9%) cases, 31 of 128 (24.2%) controls, adjusted per study, case control OR, group 1, model 2, multivariable. | |
| risk of progression, 7.0% higher, OR 1.07, p = 0.80, treatment 77 of 339 (22.7%) cases, 58 of 339 (17.1%) controls, adjusted per study, case control OR, complications, group 1, model 2, multivariable. | |
| risk of progression, 9.0% lower, OR 0.91, p = 0.61, treatment 77 of 339 (22.7%) cases, 58 of 339 (17.1%) controls, adjusted per study, case control OR, complications, group 2, model 1, multivariable. | |
| risk of case, 11.0% higher, OR 1.11, p = 0.21, treatment 313 of 3,825 (8.2%) cases, 531 of 7,650 (6.9%) controls, adjusted per study, case control OR, group 1, PSM 1, model 2, multivariable. | |
| risk of case, 1.0% higher, OR 1.01, p = 0.90, treatment 431 of 7,223 (6.0%) cases, 752 of 14,446 (5.2%) controls, adjusted per study, case control OR, group 2, PSM 1, model 1, multivariable. | |
| Sullerot, 1/7/2022, retrospective, propensity score weighting, multiple countries, peer-reviewed, 15 authors, study period 1 March, 2020 - 31 December, 2020. | risk of death, 10.0% higher, RR 1.10, p = 0.52, treatment 101 of 301 (33.6%), control 224 of 746 (30.0%). |
| risk of ICU admission, 109.7% higher, RR 2.10, p = 0.007, treatment 22 of 301 (7.3%), control 26 of 746 (3.5%). | |
| hospitalization time, 10.0% higher, relative time 1.10, p = 0.02, treatment 301, control 746. | |
| Tse, 6/2/2023, retrospective, China, peer-reviewed, 12 authors, study period 1 January, 2020 - 8 December, 2020. | risk of death/intubation, 67.0% lower, OR 0.33, p < 0.001, adjusted per study, propensity score matching, multivariable, day 30, RR approximated with OR. |
| Wang, 7/14/2020, retrospective, USA, peer-reviewed, 13 authors. | risk of death, 57.7% lower, RR 0.42, p = 0.43, treatment 1 of 9 (11.1%), control 13 of 49 (26.5%), NNT 6.5, odds ratio converted to relative risk. |
| Ware, 4/12/2024, retrospective, propensity score matching, USA, preprint, 7 authors, study period 2 March, 2020 - 13 June, 2022. | risk of death, 45.8% lower, RR 0.54, p = 0.001, treatment 7,531 of 81,830 (9.2%), control 13,890 of 81,830 (17.0%), NNT 13, propensity score matching, day 365. |
| Yuan, 12/18/2020, retrospective, China, peer-reviewed, 6 authors. | risk of death, 4.4% lower, RR 0.96, p = 0.89, treatment 11 of 52 (21.2%), control 29 of 131 (22.1%), NNT 102, odds ratio converted to relative risk, mutivariate. |
| Zadeh, 12/20/2022, retrospective, USA, peer-reviewed, mean age 62.2, 8 authors. | risk of death, 37.0% lower, RR 0.63, p = 0.28. |
| risk of ICU admission, 1.0% higher, RR 1.01, p = 0.79. |
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Treatments and other interventions are complementary.
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means should be used based on risk/benefit analysis.
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and future variants.
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