Remdesivir for COVID-19: real-time meta analysis of 60 studies
@CovidAnalysis, October 2023
https://c19early.org/smeta.html
•Meta analysis shows
11% [3‑18%] lower mortality,
and pooled analysis using the most serious outcome reported shows
10% [3‑16%] lower risk.
•While studies to date show a small mortality improvement, meta regression with
followup duration shows that this efficacy disappears with longer followup.
There is also no benefit seen for mechanical ventilation, ICU admission,
hospitalization, or progression. This may reflect antiviral efficacy being
offset by side effects of treatment.
•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.
•All data to reproduce this paper and
sources are in the appendix.
Highlights
Remdesivir shows a small mortality improvement, however this is primarily from
studies with short followup duration, and efficacy declines with extended followup.
We show traditional outcome specific analyses and combined
evidence from all studies, incorporating treatment delay, a primary
confounding factor in COVID-19 studies.
Real-time updates and corrections,
transparent analysis with all results in the same format, consistent protocol
for 56
treatments.
B
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C
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Figure 1.
A. Random effects
meta-analysis. This plot shows pooled effects, see the specific outcome analyses for individual
outcomes, and the heterogeneity section for discussion.
Effect extraction is pre-specified, using the most serious outcome reported.
For details of effect extraction see the
appendix.
B. 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.
C. Results within the context of multiple COVID-19 treatments.
0.7% of 5,680 proposed treatments show efficacy
c19early.org.
D. Timeline of results in remdesivir studies.
We analyze all significant studies
concerning the use of
remdesivir
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 after exclusions.
Figure 2 shows stages of possible treatment for
COVID-19. Prophylaxis refers to regularly taking medication before
becoming sick, in order to prevent or minimize infection. Early
Treatment refers to treatment immediately or soon after symptoms appear,
while Late Treatment refers to more delayed treatment.
Figure 2. Treatment stages.
An In Vivo animal study supports the efficacy of remdesivir Vermillion.
Vermillion investigate a novel formulation of remdesivir that may
be more effective for COVID-19.
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, with different exclusions, and for specific outcomes.
Table 2 shows results by treatment stage.
Figure 3, 4, 5, 6, 7, 8, 9, 10, and 11
show forest plots for random effects meta-analysis of
all studies with pooled effects, mortality results, ventilation, ICU admission, hospitalization, progression, recovery, viral clearance, and peer reviewed studies.
| Improvement | Studies | Patients | Authors | |
|---|---|---|---|---|
| All studies | 10% [3‑16%] ** | 61 | 156,800 | 981 |
| After exclusions | 11% [4‑17%] ** | 45 | 136,496 | 797 |
| Peer-reviewed studiesPeer-reviewed | 7% [-0‑14%] | 54 | 146,776 | 865 |
| Randomized Controlled TrialsRCTs | 12% [-2‑23%] | 10 | 10,313 | 321 |
| Mortality | 11% [3‑18%] ** | 52 | 154,591 | 795 |
| VentilationVent. | -10% [-54‑22%] | 8 | 33,882 | 153 |
| ICU admissionICU | -33% [-62‑-10%] ** | 3 | 3,403 | 18 |
| HospitalizationHosp. | -5% [-33‑17%] | 8 | 5,979 | 195 |
| Recovery | 21% [12‑29%] **** | 4 | 2,487 | 139 |
| Viral | 10% [-14‑29%] | 5 | 776 | 78 |
| RCT mortality | 9% [-1‑18%] | 8 | 9,615 | 249 |
| RCT hospitalizationRCT hosp. | 42% [-87‑82%] | 3 | 1,979 | 157 |
| Early treatment | Late treatment | |
|---|---|---|
| All studies | 41% [-20‑71%] | 9% [3‑15%] ** |
| After exclusions | 33% [-57‑71%] | 10% [4‑16%] ** |
| Peer-reviewed studiesPeer-reviewed | 33% [-57‑71%] | 7% [-1‑13%] |
| Randomized Controlled TrialsRCTs | 85% [42‑96%] ** | 9% [-1‑18%] |
| Mortality | 66% [9‑87%] * | 11% [3‑18%] ** |
| VentilationVent. | -10% [-54‑22%] | |
| ICU admissionICU | -33% [-62‑-10%] ** |
|
| HospitalizationHosp. | 34% [-57‑72%] | -13% [-42‑10%] |
| Recovery | 28% [10‑43%] ** | 18% [5‑29%] ** |
| Viral | -1% [-122‑54%] | 4% [-11‑17%] |
| RCT mortality | 9% [-1‑18%] | |
| RCT hospitalizationRCT hosp. | 71% [27‑89%] ** | -11% [-23‑-1%] * |
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Figure 3. Random effects meta-analysis for all studies with pooled effects.
This plot shows pooled effects, see the specific outcome analyses for individual
outcomes, and the heterogeneity section for discussion.
Effect extraction is pre-specified, using the most serious outcome reported.
For details of effect extraction see the
appendix.
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Figure 4. Random effects meta-analysis for mortality results.
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Figure 5. Random effects meta-analysis for ventilation.
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Figure 6. Random effects meta-analysis for ICU admission.
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Figure 7. Random effects meta-analysis for hospitalization.
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Figure 8. Random effects meta-analysis for progression.
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Figure 9. Random effects meta-analysis for recovery.
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Figure 10. Random effects meta-analysis for viral clearance.
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Figure 11. Random effects meta-analysis for peer reviewed studies.
Zeraatkar 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.
Effect extraction is pre-specified, using the most serious outcome reported,
see the appendix for details.
Figure 12 shows a comparison of results for RCTs and non-RCT studies.
The median effect size for
RCTs is 9% improvement,
compared to 8% for other studies.
Figure 13, 14, and 15
show forest plots for random effects meta-analysis of
all Randomized Controlled Trials, RCT mortality results, and RCT hospitalization results.
RCT results are included in Table 1 and Table 2.
Bias in clinical research may be defined as something that tends to make
conclusions differ systematically from the truth. RCTs help to make study
groups more similar and can provide a higher level of evidence, however they
are subject to many biases Jadad, and analysis of double-blind RCTs
has identified extreme levels of bias Gøtzsche.
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, 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.
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 56 treatments we have analyzed,
64% 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).
Evidence shows that non-RCT trials can also
provide reliable results. Concato find that well-designed
observational studies do not systematically overestimate the magnitude of the
effects of treatment compared to RCTs. Anglemyer summarized reviews
comparing RCTs to observational studies and found little evidence for
significant differences in effect estimates. Lee shows 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 Internet survey bias could
have a greater effect on results. Ethical issues may also prevent running RCTs
for known effective treatments. For more on issues with RCTs see
Deaton, Nichol.
Currently, 38 of the treatments we analyze show statistically significant efficacy or harm, defined as ≥10% decreased risk or >0% increased risk from ≥3 studies. Of the 38 treatments with statistically significant efficacy/harm, 24 have been confirmed in RCTs, with a mean delay of 5.7 months. For the 14 unconfirmed treatments, 4 have zero RCTs to date. The point estimates for the remaining 10 are all consistent with the overall results (benefit or harm), with 8 showing >20%. The only treatments showing >10% efficacy for all studies, but <10% for RCTs are sotrovimab and aspirin.
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.
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Figure 12. Results for RCTs and non-RCT studies.
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Figure 13. Random effects meta-analysis for all Randomized Controlled Trials.
This plot shows pooled effects, see the specific outcome analyses for individual
outcomes, and the heterogeneity section for discussion.
Effect extraction is pre-specified, using the most serious outcome reported.
For details of effect extraction see the
appendix.
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Figure 14. Random effects meta-analysis for RCT mortality results.
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Figure 15. Random effects meta-analysis for RCT hospitalization results.
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 may underemphasize serious issues not captured in the checklists,
overemphasize issues unlikely to alter outcomes in specific cases (for
example, lack of blinding for an objective mortality outcome, or certain
specifics of randomization with a very large effect size), or be easily
influenced by potential bias. However, they can also be very high
quality.
The studies excluded are as below.
Figure 16 shows a forest plot for random
effects meta-analysis of all studies after exclusions.
Arfijanto, unadjusted results with no group details.
El-Solh, very late stage, >50% on oxygen/ventilation at baseline; substantial unadjusted confounding by indication likely; significant confounding by contraindications possible.
Elec, substantial confounding by time possible due to significant changes in SOC and treatment propensity during the study period.
Elhadi, unadjusted results with no group details.
Fried, excessive unadjusted differences between groups; substantial unadjusted confounding by indication likely.
Kurniyanto, unadjusted results with no group details; substantial unadjusted confounding by indication likely.
Madan, unadjusted results with no group details.
Madan (B), excessive unadjusted differences between groups.
Malundo, unadjusted results with no group details.
Mulhem, substantial unadjusted confounding by indication likely; substantial confounding by time possible due to significant changes in SOC and treatment propensity during the study period.
Mustafa, unadjusted results with no group details.
Nadeem, unadjusted results with no group details.
Oku, unadjusted results with no group details.
Salehi, unadjusted results with no group details.
Schmidt, confounding by indication is likely and adjustments do not consider COVID-19 severity at baseline.
Shamsi, unadjusted results with no group details.
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Figure 16. Random effects meta-analysis for all studies after exclusions.
This plot shows pooled effects, see the specific outcome analyses for individual
outcomes, and the heterogeneity section for discussion.
Effect extraction is pre-specified, using the most serious outcome reported.
For details of effect extraction 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 hours McLean, Treanor.
Baloxavir studies for influenza also show that treatment delay is critical
— Ikematsu report an 86% reduction in cases for post-exposure
prophylaxis, Hayden 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 report only 2.5
hours improvement for inpatient treatment.
| Treatment delay | Result |
| Post exposure prophylaxis | 86% fewer cases Ikematsu |
| <24 hours | -33 hours symptoms Hayden |
| 24-48 hours | -13 hours symptoms Hayden |
| Inpatients | -2.5 hours to improvement Kumar |
Figure 17 shows a mixed-effects meta-regression for efficacy
as a function of treatment delay in COVID-19 studies from 56 treatments, showing
that efficacy declines rapidly with treatment delay. Early treatment is
critical for COVID-19.
Figure 17. Early treatment is more effective. Meta-regression showing efficacy as a function of treatment delay in COVID-19 studies from 56 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 (as in
López-Medina).
Efficacy may
differ significantly depending on the effect measured, for example a treatment
may be very effective at reducing mortality, but less effective at minimizing
cases or hospitalization. Or a treatment may have no effect on viral clearance
while still being effective at reducing mortality.
There are many
different variants of SARS-CoV-2 and efficacy may depend critically on the
distribution of variants encountered by the patients in a study. For example,
the Gamma variant shows significantly different characteristics
Faria, Karita, Nonaka, Zavascki. Different mechanisms of action may be
more or less effective depending on variants, for example the viral entry
process for the omicron variant has moved towards TMPRSS2-independent fusion,
suggesting that TMPRSS2 inhibitors may be less effective
Peacock, Willett.
Effectiveness may depend strongly on the dosage and treatment regimen.
The use of other
treatments may significantly affect outcomes, including anything from
supplements, other medications, or other kinds of treatment such as prone
positioning.
The
quality of medications may vary significantly between manufacturers and
production batches, which may significantly affect efficacy and safety.
Williams analyze ivermectin from 11 different sources, showing
highly variable antiparasitic efficacy across different manufacturers.
Xu analyze a treatment from two different manufacturers, showing 9
different impurities, with significantly different concentrations for each
manufacturer.
We present both pooled analyses and specific outcome analyses. Notably, pooled
analysis often results in earlier detection of efficacy as shown in
Figure 18. For many COVID-19 treatments, a reduction in mortality
logically follows from a reduction in hospitalization, which follows from a
reduction in symptomatic cases, etc. An antiviral tested with a low-risk
population may report zero mortality in both arms, however a reduction in
severity and improved viral clearance may translate into lower mortality among
a high-risk population, and including these results in pooled analysis allows
faster detection of efficacy. Trials with high-risk patients may also be
restricted due to ethical concerns for treatments that are known or expected
to be effective.
Pooled analysis enables using more of the available
information. While there is much more information available, for example
dose-response relationships, the advantage of the method used here is
simplicity and transparency. Note that pooled analysis could hide efficacy,
for example a treatment that is beneficial for late stage patients but has no
effect on viral replication or early stage disease could show no efficacy in
pooled analysis if most studies only examine viral clearance.
While we present pooled results, we also present individual
outcome analyses, which may be more informative for specific use cases.
Currently, 38 of the treatments we analyze show statistically significant efficacy or harm, defined as ≥10% decreased risk or >0% increased risk from ≥3 studies. 91% of treatments showing statistically significant efficacy/harm with pooled effects have been confirmed with one or more specific outcomes, with a mean delay of 3.3 months. When restricting to RCTs only, 57% of treatments showing statistically significant efficacy/harm with pooled effects have been confirmed with one or more specific outcomes, with a mean delay of 3.9 months.
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Figure 18. 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.
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. This may have a greater effect than
pooling different outcomes such as mortality and hospitalization. For example
a treatment may have 50% efficacy for mortality but only 40% for
hospitalization when used within 48 hours. However efficacy could be 0% when
used late.
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.
Figure 19 shows a mixed-effects meta-regression of
efficacy as a function of followup duration, which shows decreasing efficacy
with longer followup. This may reflect antiviral efficacy being offset by side
effects of treatment.
Figure 19. Efficacy decreases with longer followup. Meta-regression showing mortality efficacy as a function of followup duration in COVID-19 remdesivir studies.
Publishing is often biased
towards positive results. Trials with patented drugs may have a financial conflict of interest that
results in positive studies being more likely to be published, or bias towards more positive results. For example with molnupiravir, trials with negative results remain unpublished to
date (CTRI/2021/05/033864 and CTRI/2021/08/0354242).
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 20 shows a scatter plot of
results for prospective and retrospective studies.
36% of retrospective studies
report a statistically significant positive effect for
one or more outcomes, compared to
36% of prospective studies, showing similar results.
The median effect size for
retrospective studies is 9% improvement,
compared to 6% for prospective
studies, showing similar results.
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Figure 20. 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 21 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 < 0.05
Egger, Harbord, Macaskill, Moreno, Peters, Rothstein, Rücker, Stanley.
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 21. Example funnel plot analysis for simulated perfect trials.
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 by 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 affiliated with special interests 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 alone
Alsaidi, Andreani, Biancatelli, De Forni (B), Gasmi, Jeffreys (B), Jitobaom, Jitobaom (B), Ostrov, Thairu.
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, vaccine, 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.
Meta analysis shows
11% [3‑18%] lower mortality,
and pooled analysis using the most serious outcome reported shows
10% [3‑16%] lower risk.
While studies to date show a small mortality improvement, meta regression with
followup duration shows that this efficacy disappears with longer followup.
There is also no benefit seen for mechanical ventilation, ICU admission,
hospitalization, or progression. This may reflect antiviral efficacy being
offset by side effects of treatment.
Ader:
RCT 857 hospitalized patients, showing no significant differences with remdesivir treatment. EudraCT2020-000936-23.
Aghajani:
Retrospective 991 hospitalized patients in Iran focusing on aspirin use but also showing results for HCQ, remdesivir, and favipiravir.
Ali:
RCT 1,282 hospitalized patients in Canada showing lower mechanical ventilation with remdesivir treatment, but no significant difference for mortality.
Alshamrani:
PSM retrospective 29 hospitals in Saudi Arabia, showing lower mortality with remdesivir treatment.
Arch:
Prospective PSM analysis of remdesivir use in the UK showing statistically significantly lower mortality at 28 days. For unspecified reasons, the study prioritized short-term outcomes. Mortality at 14 days was also lower but not statistically significant. Confounding by indication is likely and may only be partially addressed by the variables included in the PSM.
Arfijanto:
Retrospective 162 hospitalized COVID-19 patients in Indonesia, showing no significant difference in delayed viral clearance with remdesivir treatment in unadjusted results.
Aweimer:
Retrospective 149 patients under invasive mechanical ventilation in Germany showing no significant difference in mortality with remdesivir in unadjusted results.
Barrat-Due:
Small RCT in Norway with 52 HCQ and 42 remdesivir patients, showing no significant differences with treatment. Add-on trial to WHO Solidarity. NCT04321616.
Bavaro:
Retrospective 331 hospitalized COVID-19 patients in Italy, showing lower progression with remdesivir. Combination therapy with mAbs was more effective, and improved results were seen for immunocompromised patients.
Behboodikhah:
Retrospective 2,174 hospitalized patients showing no significant differences with remdesivir treatment.
Beigel:
RCT 1,062 hospitalized patients showing faster recovery time with treatment, median 10 days vs. 15 days for placebo, rate ratio for recovery 1.29, p<0.001. Day 29 mortality was 11.4% with remdesivir and 15.2% with placebo, hazard ratio HR 0.73 [0.52-1.03].
Bowen:
Retrospective 4,631 hospitalized patients in New York, showing higher mortality with remdesivir, and lower mortality with HCQ. Authors suggest that increased mortality during the first epidemic wave was partly due to strain on hospital resources.
Burhan:
Retrospective 559 COVID-19 ICU patients in Indonesia, showing higher mortality with remdesivir in unadjusted results, without statistical significance. Note that confounding by indication should be less significant for ICU studies compared to studies of all hospitalized patients, because all patients are in critical condition.
Chew:
Retrospective 163 COVID-19 patients in Singapore, showing increased risk of liver injury (abnormal ALT) with acetaminophen in a dose-dependent manner, and with remdesivir, without statistical significance in both cases.
Diaz:
Retrospective 1138 hospitalized patients in the USA, 286 treated with remdesivir, showing lower mortality with treatment.
Age was not included in the adjustments (authors excluded variables that contributed to another score, in this case age is in Pneumonia Severity Index).
Age was not included in the adjustments (authors excluded variables that contributed to another score, in this case age is in Pneumonia Severity Index).
El-Solh:
Retrospective 7,816 Veterans Affairs hospitalized patients showing lower mortality with remdesivir.
Elec:
Retrospective 165 hospitalized COVID-19+ kidney transplant patients, 38 treated with remdesivir, showing no significant difference in mortality, higher ICU admission, and lower ICU mortality. Subject to confounding by time with significant changes to SOC and treatment propensity during the study period.
Elhadi:
Prospective study of 465 COVID-19 ICU patients in Libya showing no significant differences with treatment.
Flisiak:
Retrospective study comparing 122 remdesivir patients and 211 lopinavir/ritonavir patients, showing higher rates of clinical improvement with remdesivir and lower mortality (not statistically significant).
Fried:
Database analysis of 11,721 hospitalized patients, 48 treated with remdesivir.
Data inconsistencies have been found in this study, for example 99.4% of patients treated with HCQ were treated in urban hospitals, compared to 65% of untreated patients (Supplemental Table 3), while patients are distributed in a more balanced manner between teaching or not-teaching hospitals, as well as in the most urbanized (Northeast) and less urbanized (Midwest) regions of the United States academic.oup.com.
Data inconsistencies have been found in this study, for example 99.4% of patients treated with HCQ were treated in urban hospitals, compared to 65% of untreated patients (Supplemental Table 3), while patients are distributed in a more balanced manner between teaching or not-teaching hospitals, as well as in the most urbanized (Northeast) and less urbanized (Midwest) regions of the United States academic.oup.com.
Garibaldi:
Retrospective 303 remdesivir patients and 303 matched controls showing significantly faster clinical improvement, and lower (but not statistically significant) mortality.
Goldberg:
Retrospective 29 remdesivir patients and 113 controls, not finding a significant difference in nasopharyngeal viral load or hospitalization time. Hospitalization time was lower with treatment, with a larger reduction for non-intubated patients, although not statistically significant in both cases.
Gottlieb:
RCT high-risk outpatients, 279 treated with remdesivir and 283 control patients, median 5 days from symptoms, showing significantly lower hospitalization with treatment.
Hagman:
Retrospective 318 hospitalized COVID-19 patients in Sweden, showing improvements in viral clearance but no improvement for mortality with remdesivir treatment.
Hartantri:
Retrospective 689 hospitalized patients in Indonesia, showing no significant difference in mortality with remdesivir treatment.
Jamir:
Retrospective 266 COVID-19 ICU patients in India, showing significantly lower mortality with PVP-I oral gargling and topical nasal use, and non-statistically significant higher mortality with ivermectin and lower mortality with remdesivir.
Jittamala:
High conflict of interest RCT with very low risk patients with high existing immunity, showing faster viral clearance with remdesivir. The viral clearance half-life was very short in both arms. With rapid viral clearance and very low risk patients, the trial favors detecting an effect with intravenous treatments that have rapid onset of action.
Kim:
Retrospective 167 nosocomial COVID-19 patients in South Korea, showing higher mortality with remdesivir treatment, without statistical significance.
Kneidinger:
Retrospective 218 COVID+ lung transplant patients in Germany, showing no significant difference in severe cases with early remdesivir use.
Kuno:
PSM retrospective 3,372 hospitalized patients in the USA treated with steroids, showing no significant difference in mortality with remdesivir, but a lower risk of acute kidney injury.
Kurniyanto:
Retrospective 477 hospitalized patients in Indonesia, showing higher mortality with remdesivir in unadjusted results.
Madan (B):
Retrospective 1,262 hospitalized patients, 398 treated with remdesivir, showing unadjusted lower mortality with treatment, and a treatment delay-response relationship.
Mahajan:
Small RCT with 34 remdesivir patients and 36 controls finding no significant difference in clinical outcomes.
Malundo:
Retrospective 1,215 hospitalized patients in the Phillipines, showing no significant difference in outcomes with remdesivir or HCQ use in unadjusted results subject to confounding by indication.
Mitsushima:
Retrospective 18,566 hospitalized patients in Japan, showing higher mortality with remdesivir treatment.
Mozaffari:
Retrospective 19,184 immunocompromised patients treated with remdesivir and matched controls, showing lower mortality with treatment. Several authors work at Gilead and the study was funded by Gilead.
The majority of patients were treated with remdesivir. A significant fraction of non-remdesivir patients may have contraindications that also increase risk. Authors provide serum creatine for 26% of the cohort, but notably provide only median and IQR, not allowing comparison of the number of patients with high values. Authors state that "renal function was not significantly different" between remdesivir and non-remdesivir patients, but this does not seem realistic given the prevalence of renal impairment and the contraindictions for remdesivir.
The majority of patients were treated with remdesivir. A significant fraction of non-remdesivir patients may have contraindications that also increase risk. Authors provide serum creatine for 26% of the cohort, but notably provide only median and IQR, not allowing comparison of the number of patients with high values. Authors state that "renal function was not significantly different" between remdesivir and non-remdesivir patients, but this does not seem realistic given the prevalence of renal impairment and the contraindictions for remdesivir.
Mozaffari (B):
Retrospective 28,855 remdesivir patients with PSM matched controls, showing lower mortality with treatment.
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.
Mustafa:
Retrospective 444 hospitalized patients in Pakistan, showing lower mortality with remdesivir treatment in unadjusted results, not reaching statistical significance.
Nadeem:
Retrospective 132 hospitalized COVID-19 patients in the USA, showing no significant difference in mortality with remdesivir in unadjusted results.
Ohl:
Retrospective 5,898 hospitalized patients in the USA, 2,374 receiving remdesivir treatment, showing no significant difference in mortality, and a longer time to hospital discharge with treatment.
Oku:
Retrospective 220 COVID-19 patients with rheumatic disease in Japan, showing no significant difference in mortality with remdesivir treatment.
Olender:
Comparative analysis between remdesivir trial GS-US-540–5773 and a retrospective SOC cohort with similar inclusion criteria, showing lower mortality and higher recovery at day 14 with remdesivir.
Ong:
Retrospective 18 immunocompromised pediatric COVID-19 patients in Singapore, showing slower viral clearance with remdesivir, without statistical significance.
Pasquini:
Retrospective 51 ICU patients under mechanical ventilation, 25 treated with remdesivir, showing lower mortality with treatment.
Piccicacco:
Retrospective high-risk outpatients in the USA, 82 treated with remdesivir, 88 with sotrovimab, and 90 control patients, showing significantly lower combined hospitalization/ER visits with both treatments in unadjusted results. The dominant variant was omicron B.1.1.529.
Pourhoseingholi:
Prospective study of 2,468 hospitalized COVID-19 patients in Iran, showing no significant difference with remdesivir treatment. IR.MUQ.REC.1399.013.
Punzalan:
Prospective study of 400 hospitalized patients in the Philippines, showing higher progression with remdesivir in unadjusted results, without statistical significance.
Raad:
Retrospective 3,966 COVID-19 patients, 1,115 with cancer, showing lower mortality with remdesivir and higher mortality with convalescent plasma.
Salehi:
Retrospective 125 mechanically ventilated ICU patients in Iran, showing lower mortality with remdesivir treatment in unadjusted results.
Schmidt:
Retrospective 1,106 prostate cancer patients, showing higher mortality with remdesivir treatment.
Shamsi:
Retrospective 183 hospitalized pediatric COVID-19 patients in Iran, showing no significant difference in mortality with remdesivir in unadjusted results.
Siraj:
Retrospective 1,000 COVID+ hospitalized patients in India, showing lower mortality with famotidine and remdesivir in multivariable logistic regression.
SOLIDARITY:
WHO SOLIDARITY open-label RCT with 2,750 very late stage (76% on oxygen/ventilation) remdesivir patients, mortality relative risk RR 0.95 [0.81-1.11], p=0.50. Non-ventilated patients show a greater benefit, RR 0.86 [0.72-1.04], p = 0.13.
Spinner:
Late stage (median 8 days from symptom onset) RCT 584 patients with moderate COVID-19 showing (non-statistically significant) lower mortality.
5-day remdesivir had significantly higher odds of a better clinical status distribution on the 7-point ordinal scale, odds ratio OR 1.65, p = 0.02. The difference for 10-day remdesivir was not statistically significant, p=0.18.
5-day remdesivir had significantly higher odds of a better clinical status distribution on the 7-point ordinal scale, odds ratio OR 1.65, p = 0.02. The difference for 10-day remdesivir was not statistically significant, p=0.18.
Tsuzuki:
Retrospective database analysis of 12,487 hospitalized patients in Japan, showing lower risk of oxygen requirement, but no significant difference in mortality or ventilation/ECMO.
Ullah:
Small late stage (hospitalized, <12 days symptoms) remdesivir study showing non-statistically significant higher mortality with treatment.
No adjustments were made for differences in the groups. Remdesivir mean age was 49 vs. control 57. Baseline oxygen requirement was 13.4 liters treatment vs. 10.8 control. Potential confounding by indication.
No adjustments were made for differences in the groups. Remdesivir mean age was 49 vs. control 57. Baseline oxygen requirement was 13.4 liters treatment vs. 10.8 control. Potential confounding by indication.
Wang:
Small RCT with 237 hospitalized patients in China with severe COVID-19, not showing statistically significant benefits. 158 treatment patients and 79 control patients.
While too small for significance, the subgroup treated within 10 days showed reduced mortality RR 0.76, p = 0.58, and reduced median time to clinical improvement of 18 days vs. 23 days, hazard ratio 1.52 [0.95-2.43].
While too small for significance, the subgroup treated within 10 days showed reduced mortality RR 0.76, p = 0.58, and reduced median time to clinical improvement of 18 days vs. 23 days, hazard ratio 1.52 [0.95-2.43].
Yeramaneni:
Retrospective 7,158 hospitalized COVID-19 patients in the USA analyzing famotidine treatment, showing no significant difference in mortality with associated remdesivir treatment.
Zangeneh:
Retrospective 193 ICU patients in Iran, showing lower mortality with remdesivir treatment, not reaching statistical significance.
We performed ongoing searches of PubMed, medRxiv,
ClinicalTrials.gov, The Cochrane Library, Google Scholar, Collabovid, Research
Square, ScienceDirect, Oxford University Press, the reference lists of other
studies and meta-analyses, and submissions to the site c19early.org.
Search terms were remdesivir, filtered for papers containing the terms COVID-19 or SARS-CoV-2. Automated searches are performed
every few hours with notification of new matches.
All studies regarding the use of remdesivir 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 are used. Mortality alone is preferred over combined outcomes.
Outcomes with zero events in both arms were not used (the next most serious
outcome is used — no studies were excluded). 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 outcome is considered more important than PCR testing 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 no room
for an effective treatment to do better).
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 computed the relative risk when
possible, or converted to a relative risk according to Zhang.
Reported confidence intervals and p-values were used when available,
using adjusted values when provided. If multiple types of adjustments are
reported including propensity score matching (PSM), the PSM results are used.
Adjusted primary outcome 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 1 Sweeting.
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
(3.11.5) with
scipy (1.11.1), pythonmeta (1.26), numpy (1.25.0), statsmodels (0.14.0), and plotly (5.15.0).
Forest plots are computed using PythonMeta Deng
with the DerSimonian and Laird random effects model (the fixed effect
assumption is not plausible in this case) and inverse variance weighting.
Mixed-effects meta-regression results are computed with R (4.1.2) using the metafor
(3.0-2) and rms (6.2-0) packages, and using the most serious sufficiently powered outcome.
We received no funding, this research is done in our spare
time. We have no affiliations with any pharmaceutical companies or political
parties.
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 effective
McLean, Treanor.
A summary of study results is below. Please submit
updates and corrections at https://c19early.org/smeta.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.
| Chew, 3/16/2023, retrospective, Singapore, peer-reviewed, median age 56.0, 7 authors, study period 23 January, 2020 - 15 April, 2020. | abnormal ALT, 68.0% higher, OR 1.68, p = 0.40, treatment 12, control 151, adjusted per study, multivariable, RR approximated with OR. |
| Gottlieb, 12/22/2021, Double Blind Randomized Controlled Trial, multiple countries, peer-reviewed, 30 authors, study period 18 September, 2020 - 8 April, 2021, average treatment delay 5.0 days, trial NCT04501952 (history) (PINETREE). | risk of death/hospitalization, 87.0% lower, RR 0.13, p = 0.008, treatment 2 of 279 (0.7%), control 15 of 283 (5.3%), NNT 22, adjusted per study, COVID-19 related hospitalization or death from any cause @day 28, primary outcome. |
| risk of hospitalization, 71.8% lower, RR 0.28, p = 0.009, treatment 5 of 279 (1.8%), control 18 of 283 (6.4%), NNT 22. | |
| risk of no recovery, 29.1% lower, RR 0.71, p = 0.31, treatment 43 of 66 (65.2%), control 45 of 60 (75.0%), adjusted per study, inverted to make RR<1 favor treatment, alleviation of symptoms @day 14. | |
| risk of no recovery, 47.9% lower, RR 0.52, p = 0.003, treatment 108 of 169 (63.9%), control 132 of 165 (80.0%), NNT 6.2, adjusted per study, inverted to make RR<1 favor treatment, post-hoc alleviation of symptoms @day 14. | |
| Jittamala, 7/20/2023, Randomized Controlled Trial, multiple countries, peer-reviewed, median age 30.1, 42 authors, study period 30 September, 2021 - 10 June, 2022, trial NCT05041907 (history) (PLATCOV). | risk of hospitalization, 66.3% lower, RR 0.34, p = 1.00, treatment 0 of 67 (0.0%), control 1 of 69 (1.4%), NNT 69, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm). |
| relative clearance half-life, 28.9% better, RR 0.71, p < 0.001, treatment median 12.8 IQR 8.0 n=67, control median 18.0 IQR 10.5 n=69, primary outcome. | |
| Kneidinger, 9/9/2022, retrospective, Germany, peer-reviewed, 11 authors, study period 1 January, 2022 - 20 March, 2022, lung transplant patients. | risk of severe case, 19.9% lower, RR 0.80, p = 0.71, treatment 6 of 46 (13.0%), control 28 of 172 (16.3%), NNT 31. |
| Madan, 7/19/2021, retrospective, India, preprint, 22 authors, early treatment subset, excluded in exclusion analyses: unadjusted results with no group details. | risk of death, 65.6% lower, RR 0.34, p = 0.04, treatment 4 of 112 (3.6%), control 27 of 260 (10.4%), NNT 15, unadjusted, <5 days from onset. |
| Ong, 1/20/2023, retrospective, Singapore, peer-reviewed, 12 authors. | recovery time, 75.0% higher, relative time 1.75, p = 0.60, treatment 4, control 14, defervescence. |
| hospitalization time, 55.6% higher, relative time 1.56, p = 0.31, treatment 4, control 14. | |
| time to viral-, 60.7% higher, relative time 1.61, p = 0.14, treatment 4, control 14. | |
| Piccicacco, 8/1/2022, retrospective, USA, peer-reviewed, 7 authors, study period 27 December, 2021 - 4 February, 2022, average treatment delay 4.0 days, ER visit. | risk of death, 65.6% lower, RR 0.34, p = 1.00, treatment 0 of 82 (0.0%), control 1 of 90 (1.1%), NNT 90, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), day 29. |
| risk of hospitalization, 30.2% lower, RR 0.70, p = 0.47, treatment 7 of 82 (8.5%), control 11 of 90 (12.2%), NNT 27, day 29. | |
| risk of hospitalization/ER, 52.5% lower, RR 0.48, p = 0.05, treatment 9 of 82 (11.0%), control 21 of 90 (23.3%), NNT 8.1, odds ratio converted to relative risk, day 29. | |
| risk of progression, 78.0% lower, RR 0.22, p = 0.03, treatment 2 of 82 (2.4%), control 10 of 90 (11.1%), NNT 12, day 29. |
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.
| Ader, 9/14/2021, Randomized Controlled Trial, multiple countries, peer-reviewed, 17 authors, study period 22 March, 2020 - 21 January, 2021, average treatment delay 9.0 days, trial NCT04315948 (history) (DISCOVERY). | risk of death, 6.4% lower, RR 0.94, p = 0.77, treatment 34 of 414 (8.2%), control 37 of 418 (8.9%), NNT 156, adjusted per study, odds ratio converted to relative risk, day 28. |
| risk of death, 11.7% lower, RR 0.88, p = 0.76, treatment 21 of 414 (5.1%), control 24 of 418 (5.7%), NNT 149, day 15. | |
| risk of 7-point scale, 9.9% lower, OR 0.90, p = 0.39, treatment 414, control 418, inverted to make OR<1 favor treatment, 28 days, RR approximated with OR. | |
| risk of 7-point scale, 2.0% higher, OR 1.02, p = 0.85, treatment 414, control 418, inverted to make OR<1 favor treatment, 15 days, RR approximated with OR. | |
| Aghajani, 4/29/2021, retrospective, Iran, peer-reviewed, 7 authors. | risk of death, 18.6% lower, HR 0.81, p = 0.49, treatment 46, control 945, univariate Cox proportional regression. |
| Ali, 1/19/2022, Randomized Controlled Trial, Canada, peer-reviewed, 85 authors, average treatment delay 8.0 days, trial NCT04330690 (history) (CATCO). | risk of death, 12.0% lower, RR 0.88, p = 0.21, treatment 127 of 634 (20.0%), control 152 of 647 (23.5%), NNT 29, day 60. |
| risk of death, 17.0% lower, RR 0.83, p = 0.09, treatment 117 of 634 (18.5%), control 145 of 647 (22.4%), NNT 25, in hospital. | |
| risk of death, 20.6% lower, RR 0.79, p = 0.59, treatment 14 of 634 (2.2%), control 18 of 647 (2.8%), NNT 174, day 15. | |
| risk of mechanical ventilation, 47.0% lower, RR 0.53, p < 0.001, treatment 46 of 634 (7.3%), control 89 of 647 (13.8%), NNT 15, day 60. | |
| risk of no recovery, 9.0% lower, RR 0.91, p = 0.41, treatment 634, control 647, clinical status, day 60. | |
| hospitalization time, 11.1% higher, relative time 1.11, p = 0.04, treatment median 10.0 IQR 12.0 n=634, control median 9.0 IQR 11.0 n=647. | |
| Alshamrani, 2/15/2023, retrospective, Saudi Arabia, peer-reviewed, 3 authors, study period March 2020 - January 2021. | risk of death, 17.3% lower, RR 0.83, p = 0.003, treatment 137 of 246 (55.7%), control 725 of 1,078 (67.3%), NNT 8.6, adjusted per study, odds ratio converted to relative risk, propensity score matching, multivariable. |
| risk of progression, 4.3% lower, RR 0.96, p = 0.12, treatment 215 of 246 (87.4%), control 984 of 1,078 (91.3%), NNT 26, adjusted per study, odds ratio converted to relative risk, AKI, ARDS, multi-organ failure, or mortality, propensity score matching, multivariable. | |
| ICU time, 42.6% higher, relative time 1.43, p = 0.003, treatment 245, control 995, propensity score matching. | |
| hospitalization time, 7.4% lower, relative time 0.93, p = 0.25, treatment 246, control 1,078, propensity score matching. | |
| Arch, 6/21/2021, prospective, propensity score matching, United Kingdom, preprint, 10 authors, average treatment delay 6.0 days. | risk of death, 19.9% lower, RR 0.80, p = 0.03, treatment 203 of 1,491 (13.6%), control 777 of 4,676 (16.6%), NNT 33, odds ratio converted to relative risk, PSM, day 28. |
| risk of death, 18.0% lower, RR 0.82, p = 0.12, treatment 140 of 1,502 (9.3%), control 565 of 4,728 (12.0%), NNT 38, odds ratio converted to relative risk, PSM, day 14. | |
| risk of mechanical ventilation, 68.0% higher, RR 1.68, p = 0.003, treatment 106 of 1,498 (7.1%), control 153 of 4,602 (3.3%), odds ratio converted to relative risk, PSM, day 28. | |
| Arfijanto, 5/4/2023, retrospective, Indonesia, peer-reviewed, 8 authors, study period June 2021 - December 2021, excluded in exclusion analyses: unadjusted results with no group details. | delayed viral clearance, 0.9% lower, RR 0.99, p = 1.00, treatment 17 of 44 (38.6%), control 46 of 118 (39.0%), NNT 288. |
| Aweimer, 3/29/2023, retrospective, Germany, peer-reviewed, median age 67.0, 19 authors, study period 1 March, 2020 - 31 August, 2021. | risk of death, 13.0% higher, RR 1.13, p = 0.33, treatment 40 of 51 (78.4%), control 68 of 98 (69.4%), day 100. |
| Barrat-Due, 7/13/2021, Double Blind Randomized Controlled Trial, Norway, peer-reviewed, 41 authors, average treatment delay 8.0 days, trial NCT04321616 (history). | risk of death, no change, RR 1.00, p = 1.00, treatment 3 of 42 (7.1%), control 4 of 57 (7.0%), adjusted per study. |
| risk of death, 35.7% higher, RR 1.36, p = 0.70, treatment 3 of 42 (7.1%), control 3 of 57 (5.3%), day 60. | |
| risk of death, 54.8% lower, RR 0.45, p = 0.63, treatment 1 of 42 (2.4%), control 3 of 57 (5.3%), NNT 35, day 28. | |
| Bavaro, 5/19/2023, retrospective, Italy, peer-reviewed, median age 75.0, 27 authors, study period 1 July, 2021 - 15 March, 2022. | risk of severe case, 7.0% lower, RR 0.93, p < 0.001, treatment 120, control 211, propensity score weighting. |
| Behboodikhah, 9/15/2022, retrospective, Iran, peer-reviewed, 8 authors. | risk of death, 37.5% lower, OR 0.62, p = 0.21, treatment 1,214, control 960, adjusted per study, multivariable, RR approximated with OR. |
| Beigel, 10/8/2020, Randomized Controlled Trial, USA, peer-reviewed, 12 authors, average treatment delay 9.0 days. | risk of death, 27.0% lower, HR 0.73, p = 0.07, treatment 541, control 521, day 29. |
| risk of death, 45.0% lower, HR 0.55, p = 0.005, treatment 541, control 521, day 15. | |
| risk of no recovery, 22.5% lower, RR 0.78, p < 0.001, treatment 541, control 521, inverted to make RR<1 favor treatment. | |
| Bowen, 8/25/2022, retrospective, USA, peer-reviewed, 10 authors, study period 1 March, 2020 - 31 March, 2021. | risk of death, 57.0% higher, HR 1.57, p < 0.001, treatment 817, control 3,814, Table S2, Cox proportional hazards, day 30. |
| Burhan, 9/25/2023, retrospective, Indonesia, peer-reviewed, 26 authors, study period January 2020 - March 2021. | risk of death, 14.8% higher, RR 1.15, p = 0.23, treatment 33 of 43 (76.7%), control 345 of 516 (66.9%). |
| Diaz, 8/19/2021, retrospective, USA, peer-reviewed, 45 authors. | risk of death, 34.7% lower, HR 0.65, p = 0.01, treatment 33 of 286 (11.5%), control 173 of 852 (20.3%), NNT 11, adjusted per study, odds ratio converted to relative risk, multivariable, Cox proportional hazards, day 60. |
| risk of death, 44.0% lower, HR 0.56, p = 0.04, treatment 286, control 852, adjusted per study, multivariable, Cox proportional hazards, day 30, RR approximated with OR. | |
| El-Solh, 10/20/2020, retrospective, database analysis, USA, peer-reviewed, 5 authors, excluded in exclusion analyses: very late stage, >50% on oxygen/ventilation at baseline; substantial unadjusted confounding by indication likely; significant confounding by contraindications possible. | risk of death, 29.0% lower, HR 0.71, p = 0.03, treatment 63 of 219 (28.8%), control 202 of 424 (47.6%), NNT 5.3, adjusted per study, multivariable. |
| Elec, 3/14/2022, retrospective, Romania, peer-reviewed, 9 authors, study period 1 March, 2020 - 31 May, 2021, excluded in exclusion analyses: substantial confounding by time possible due to significant changes in SOC and treatment propensity during the study period. | risk of death, 19.3% lower, RR 0.81, p = 0.66, treatment 7 of 38 (18.4%), control 29 of 127 (22.8%), NNT 23. |
| risk of mechanical ventilation, 10.9% lower, RR 0.89, p = 0.73, treatment 8 of 38 (21.1%), control 30 of 127 (23.6%), NNT 39. | |
| risk of ICU admission, 71.9% higher, RR 1.72, p = 0.01, treatment 18 of 38 (47.4%), control 35 of 127 (27.6%). | |
| 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, 10.9% higher, RR 1.11, p = 0.65, treatment 14 of 21 (66.7%), control 267 of 444 (60.1%), day 60. |
| Flisiak, 11/3/2020, retrospective, Poland, peer-reviewed, 23 authors, study period 1 March, 2020 - 31 August, 2020, SARSTer trial. | risk of death, 48.9% lower, RR 0.51, p = 0.18, treatment 5 of 122 (4.1%), control 17 of 211 (8.1%), NNT 25, odds ratio converted to relative risk, all patients, day 28. |
| no clinical improvement, 56.5% lower, RR 0.44, p = 0.01, treatment 9 of 122 (7.4%), control 36 of 211 (17.1%), NNT 10, odds ratio converted to relative risk. | |
| Fried, 8/28/2020, retrospective, database analysis, USA, peer-reviewed, 11 authors, excluded in exclusion analyses: excessive unadjusted differences between groups; substantial unadjusted confounding by indication likely. | risk of death, 61.2% lower, RR 0.39, p = 0.02, treatment 4 of 48 (8.3%), control 2,510 of 11,673 (21.5%), NNT 7.6, remdesivir vs. non-remdesivir. |
| risk of mechanical ventilation, 36.8% higher, RR 1.37, p = 0.25, treatment 11 of 48 (22.9%), control 1,956 of 11,673 (16.8%), remdesivir vs. non-remdesivir. | |
| Garibaldi, 11/20/2020, retrospective, USA, preprint, 10 authors. | risk of death, 20.0% lower, HR 0.80, p = 0.44, treatment 23 of 303 (7.6%), control 45 of 303 (14.9%), adjusted per study, day 28. |
| risk of no improvement, 35.0% better, RR 0.65, p < 0.001, treatment 52 of 303 (17.2%), control 80 of 303 (26.4%), NNT 11, adjusted per study, day 28. | |
| Goldberg, 3/9/2021, retrospective, Israel, peer-reviewed, 7 authors. | hospitalization time, 9.2% lower, relative time 0.91, p = 0.77, treatment 29, control 113. |
| risk of no viral clearance, 0.1% lower, RR 1.00, p = 0.98, treatment 29, control 113, relative change in Ct values. | |
| Hagman, 9/26/2023, retrospective, Sweden, peer-reviewed, 9 authors, average treatment delay 6.0 days. | risk of death, no change, HR 1.00, p = 0.97, treatment 105, control 213, adjusted per study, multivariable, day 60. |
| risk of death, no change, HR 1.00, p = 0.99, treatment 105, control 213, adjusted per study, multivariable, day 28. | |
| risk of death, 20.0% lower, HR 0.80, p = 0.74, treatment 105, control 213, adjusted per study, multivariable, day 7. | |
| risk of progression, 40.0% higher, OR 1.40, p = 0.31, treatment 105, control 213, adjusted per study, multivariable, Table S7, RR approximated with OR. | |
| risk of no viral clearance, 28.6% lower, HR 0.71, p = 0.11, treatment 105, control 213, adjusted per study, inverted to make HR<1 favor treatment, multivariable. | |
| Hartantri, 2/9/2023, retrospective, Indonesia, peer-reviewed, 10 authors, study period 1 March, 2020 - 31 December, 2020. | risk of death, 11.0% lower, HR 0.89, p = 0.84, adjusted per study, mild/moderate, multivariable, Cox proportional hazards. |
| risk of death, 24.0% lower, HR 0.76, p = 0.53, adjusted per study, severe, multivariable, Cox proportional hazards. | |
| Jamir, 12/13/2021, retrospective, India, peer-reviewed, 6 authors, study period June 2020 - October 2020. | risk of death, 8.0% lower, HR 0.92, p = 0.77, treatment 60 of 181 (33.1%), control 41 of 85 (48.2%), NNT 6.6, adjusted per study, multivariable, Cox proportional hazards. |
| Kim, 3/15/2023, retrospective, South Korea, peer-reviewed, 5 authors, study period 1 November, 2021 - 30 April, 2022. | risk of death, 1612.4% higher, RR 17.12, p = 0.22, treatment 14 of 145 (9.7%), control 0 of 22 (0.0%), continuity correction due to zero event (with reciprocal of the contrasting arm). |
| Kuno, 8/9/2021, retrospective, propensity score matching, USA, peer-reviewed, 6 authors. | risk of death, 0.9% lower, RR 0.99, p = 0.96, treatment 214 of 999 (21.4%), control 216 of 999 (21.6%), NNT 499, PSM. |
| risk of mechanical ventilation, no change, RR 1.00, p = 1.00, treatment 140 of 999 (14.0%), control 140 of 999 (14.0%), PSM. | |
| risk of ICU admission, 17.1% higher, RR 1.17, p = 0.05, treatment 260 of 999 (26.0%), control 222 of 999 (22.2%), PSM. | |
| Kurniyanto, 2/28/2022, retrospective, Indonesia, peer-reviewed, 11 authors, excluded in exclusion analyses: unadjusted results with no group details; substantial unadjusted confounding by indication likely. | risk of death, 460.0% higher, RR 5.60, p < 0.001, treatment 7 of 45 (15.6%), control 12 of 432 (2.8%). |
| Madan (B), 7/19/2021, retrospective, India, preprint, 22 authors, excluded in exclusion analyses: excessive unadjusted differences between groups. | risk of death, 44.4% lower, RR 0.56, p = 0.03, treatment 23 of 398 (5.8%), control 27 of 260 (10.4%), NNT 22, unadjusted. |
| risk of death, 65.6% lower, RR 0.34, p = 0.04, treatment 4 of 112 (3.6%), control 27 of 260 (10.4%), NNT 15, unadjusted, <5 days from onset. | |
| risk of death, 61.7% lower, RR 0.38, p = 0.009, treatment 9 of 226 (4.0%), control 27 of 260 (10.4%), NNT 16, unadjusted, 5-10 days from onset. | |
| risk of death, 60.5% higher, RR 1.60, p = 0.18, treatment 10 of 60 (16.7%), control 27 of 260 (10.4%), unadjusted, >10 days from onset. | |
| risk of death, 31.0% lower, RR 0.69, p = 0.30, treatment 19 of 398 (4.8%), control 18 of 260 (6.9%), NNT 47, day 14. | |
| risk of death, 34.7% lower, RR 0.65, p = 0.32, treatment 14 of 398 (3.5%), control 14 of 260 (5.4%), NNT 54, day 10. | |
| risk of death, 47.7% lower, RR 0.52, p = 0.22, treatment 8 of 398 (2.0%), control 10 of 260 (3.8%), NNT 54, day 7. | |
| risk of death, 34.7% lower, RR 0.65, p = 0.53, treatment 5 of 398 (1.3%), control 5 of 260 (1.9%), NNT 150, day 5. | |
| risk of death, 12.9% lower, RR 0.87, p = 1.00, treatment 4 of 398 (1.0%), control 3 of 260 (1.2%), NNT 672, day 3. | |
| Mahajan, 3/20/2021, Randomized Controlled Trial, India, peer-reviewed, 3 authors, study period June 2020 - December 2020, average treatment delay 6.84 days. | risk of death, 76.5% higher, RR 1.76, p = 0.47, treatment 5 of 34 (14.7%), control 3 of 36 (8.3%). |
| risk of mechanical ventilation, 111.8% higher, RR 2.12, p = 0.42, treatment 4 of 34 (11.8%), control 2 of 36 (5.6%). | |
| Malundo, 7/14/2022, retrospective, Philippines, peer-reviewed, 16 authors, study period 12 March, 2021 - 9 September, 2021, excluded in exclusion analyses: unadjusted results with no group details. | risk of death, 16.5% higher, RR 1.17, p = 0.45, treatment 24 of 115 (20.9%), control 197 of 1,100 (17.9%). |
| Mitsushima, 2/21/2023, retrospective, Japan, peer-reviewed, 3 authors. | risk of death, 44.0% higher, OR 1.44, p < 0.01, adjusted per study, multivariable, RR approximated with OR. |
| Mozaffari, 8/9/2023, retrospective, USA, peer-reviewed, 11 authors, study period 1 December, 2020 - 30 April, 2022. | risk of death, 25.0% lower, HR 0.75, p < 0.001, treatment 14,169, control 5,341, adjusted per study, propensity score matching, Cox proportional hazards, day 28. |
| risk of death, 30.0% lower, HR 0.70, p < 0.001, treatment 14,169, control 5,341, adjusted per study, propensity score matching, Cox proportional hazards, day 14. | |
| Mozaffari (B), 10/1/2021, retrospective, USA, peer-reviewed, 12 authors. | risk of death, 12.0% lower, HR 0.88, p = 0.003, treatment 4,441 of 28,855 (15.4%), control 5,499 of 28,855 (19.1%), NNT 27, adjusted per study, PSM, Cox proportional hazards, day 28. |
| risk of death, 24.0% lower, HR 0.76, p < 0.001, treatment 3,057 of 28,855 (10.6%), control 4,437 of 28,855 (15.4%), NNT 21, adjusted per study, PSM, Cox proportional hazards, day 14. | |
| 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 possible due to significant changes in SOC and treatment propensity during the study period. | risk of death, 85.7% higher, RR 1.86, p = 0.54, treatment 1 of 8 (12.5%), control 515 of 3,211 (16.0%), adjusted per study, odds ratio converted to relative risk, logistic regression. |
| Mustafa, 12/29/2021, retrospective, Pakistan, peer-reviewed, 7 authors, excluded in exclusion analyses: unadjusted results with no group details. | risk of death, 32.7% lower, RR 0.67, p = 0.21, treatment 16 of 200 (8.0%), control 29 of 244 (11.9%), NNT 26. |
| Nadeem, 8/12/2023, retrospective, USA, peer-reviewed, mean age 59.0, 6 authors, study period 1 March, 2020 - 28 February, 2022, excluded in exclusion analyses: unadjusted results with no group details. | risk of death, 12.5% higher, RR 1.12, p = 1.00, treatment 12 of 96 (12.5%), control 4 of 36 (11.1%). |
| Ohl, 7/15/2021, retrospective, propensity score matching, USA, peer-reviewed, 9 authors. | risk of death, 6.0% higher, HR 1.06, p = 0.66, treatment 143 of 1,172 (12.2%), control 124 of 1,172 (10.6%), adjusted per study, PSM, Cox proportional hazards regression, day 30. |
| hospitalization time, 100% higher, relative time 2.00, p < 0.001, treatment 1,172, control 1,172, PSM, Cox proportional hazards regression. | |
| Oku, 9/6/2022, retrospective, Japan, peer-reviewed, 8 authors, study period 3 June, 2020 - 30 June, 2021, excluded in exclusion analyses: unadjusted results with no group details. | risk of death, 40.2% higher, RR 1.40, p = 0.59, treatment 3 of 46 (6.5%), control 8 of 172 (4.7%), unadjusted, odds ratio converted to relative risk. |
| Olender, 7/24/2020, retrospective, USA, peer-reviewed, 33 authors. | risk of death, 58.8% lower, RR 0.41, p = 0.001, treatment 24 of 312 (7.7%), control 102 of 818 (12.5%), odds ratio converted to relative risk, weighted multivariable logistic regression, day 14. |
| Pasquini, 8/23/2020, retrospective, Italy, peer-reviewed, 9 authors. | risk of death, 16.2% lower, RR 0.84, p = 0.03, treatment 14 of 25 (56.0%), control 24 of 26 (92.3%), NNT 2.8, adjusted per study, inverted to make RR<1 favor treatment, odds ratio converted to relative risk, multivariate. |
| 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, 2.0% higher, HR 1.02, p = 0.92, treatment 42 of 123 (34.1%), control 297 of 2,345 (12.7%), adjusted per study, multivariable, Cox proportional hazards. |
| Punzalan, 2/28/2023, prospective, Philippines, peer-reviewed, mean age 56.0, 17 authors, study period October 2020 - September 2021. | risk of death, 42.0% higher, RR 1.42, p = 0.12, treatment 47 of 224 (21.0%), control 26 of 176 (14.8%). |
| risk of progression, 58.9% higher, RR 1.59, p = 0.001, treatment 93 of 224 (41.5%), control 46 of 176 (26.1%). | |
| Raad, 8/26/2022, retrospective, multiple countries, preprint, 52 authors, study period January 2020 - November 2020. | risk of death, 42.0% lower, OR 0.58, p = 0.009, adjusted per study, multivariable, day 30, RR approximated with OR. |
| Salehi, 3/11/2022, retrospective, Iran, preprint, mean age 62.0, 11 authors, study period April 2021 - September 2021, excluded in exclusion analyses: unadjusted results with no group details. | risk of death, 36.6% lower, RR 0.63, p = 0.01, treatment 17 of 40 (42.5%), control 57 of 85 (67.1%), NNT 4.1. |
| Schmidt, 11/12/2021, retrospective, USA, peer-reviewed, 42 authors, study period 17 March, 2020 - 11 February, 2021, excluded in exclusion analyses: confounding by indication is likely and adjustments do not consider COVID-19 severity at baseline. | risk of severe case, 509.0% higher, OR 6.09, p < 0.001, treatment 43, control 434, adjusted per study, propensity score matching, multivariable, RR approximated with OR. |
| 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, 22.6% higher, RR 1.23, p = 0.63, treatment 8 of 53 (15.1%), control 16 of 130 (12.3%). |
| Siraj, 2/28/2022, retrospective, India, peer-reviewed, median age 56.0, 13 authors, study period March 2020 - December 2020. | risk of death, 52.9% lower, RR 0.47, p < 0.001, treatment 108 of 413 (26.2%), control 197 of 587 (33.6%), adjusted per study, inverted to make RR<1 favor treatment, odds ratio converted to relative risk, multivariable. |
| SOLIDARITY, 10/15/2020, Randomized Controlled Trial, multiple countries, peer-reviewed, 15 authors, trial NCT04315948 (history) (SOLIDARITY). | risk of death, 5.0% lower, RR 0.95, p = 0.53, treatment 301 of 2,743 (11.0%), control 303 of 2,708 (11.2%), NNT 464, day 28. |
| Spinner, 8/21/2020, Randomized Controlled Trial, multiple countries, peer-reviewed, 30 authors, study period 15 March, 2020 - 18 April, 2020, average treatment delay 8.0 days. | 5 or 10 day remdesivir vs. control 28 day mortality, 34.9% lower, RR 0.65, p = 0.50, treatment 5 of 384 (1.3%), control 4 of 200 (2.0%), NNT 143, day 28. |
| Tsuzuki, 3/10/2021, retrospective, Japan, peer-reviewed, 21 authors, average treatment delay 6.0 days. | risk of death, 4.0% higher, HR 1.04, p = 0.21, treatment 69 of 824 (8.4%), control 285 of 11,663 (2.4%), adjusted per study, day 30. |
| risk of mechanical ventilation or ECMO, 1.7% lower, HR 0.98, p = 0.68, treatment 48 of 824 (5.8%), control 98 of 11,663 (0.8%), adjusted per study. | |
| risk of progression, 15.0% lower, HR 0.85, p = 0.68, treatment 559 of 824 (67.8%), control 1,784 of 11,663 (15.3%), adjusted per study. | |
| Ullah, 11/29/2020, retrospective, Pakistan, peer-reviewed, 8 authors. | risk of death, 100% higher, RR 2.00, p = 0.33, treatment 8 of 30 (26.7%), control 4 of 30 (13.3%). |
| risk of mechanical ventilation, 250.0% higher, RR 3.50, p = 0.15, treatment 7 of 30 (23.3%), control 2 of 30 (6.7%). | |
| Wang, 4/29/2020, Randomized Controlled Trial, China, peer-reviewed, 46 authors, study period 6 February, 2020 - 12 March, 2020, average treatment delay 11.0 days. | all patients, 8.6% higher, RR 1.09, p = 1.00, treatment 22 of 158 (13.9%), control 10 of 78 (12.8%), day 28. |
| <10 days from symptoms, 24.3% lower, RR 0.76, p = 0.58, treatment 8 of 71 (11.3%), control 7 of 47 (14.9%), NNT 28, day 28. | |
| >10 days from symptoms, 47.6% higher, RR 1.48, p = 0.76, treatment 12 of 84 (14.3%), control 3 of 31 (9.7%), day 28. | |
| Yeramaneni, 2/28/2021, retrospective, USA, peer-reviewed, 6 authors, study period 11 February, 2020 - 8 May, 2020. | risk of death, 24.0% higher, OR 1.24, p = 0.87, treatment 32, control 7,126, adjusted per study, multivariable, day 30, RR approximated with OR. |
| Zangeneh, 5/13/2022, retrospective, Iran, peer-reviewed, 3 authors. | risk of death, 32.0% lower, HR 0.68, p = 0.06, Cox proportional hazards. |
Ader et al., Remdesivir plus standard of care versus standard of care alone for the treatment of patients admitted to hospital with COVID-19 (DisCoVeRy): a phase 3, randomised, controlled, open-label trial, Lancet Infectious Diseases, doi:10.1016/S1473-3099(21)00485-0.
Aghajani et al., Decreased In-Hospital Mortality Associated with Aspirin Administration in Hospitalized Patients Due to Severe COVID-19, Journal of Medical Virology, doi:10.1002/jmv.27053.
Ali et al., Remdesivir for the treatment of patients in hospital with COVID-19 in Canada: a randomized controlled trial, Canadian Medical Association Journal, doi:10.1503/cmaj.211698.
Alsaidi et al., Griffithsin and Carrageenan Combination Results in Antiviral Synergy against SARS-CoV-1 and 2 in a Pseudoviral Model, Marine Drugs, doi:10.3390/md19080418.
Alshamrani et al., Comprehensive evaluation of six interventions for hospitalized patients with COVID-19: A propensity score matching study, Saudi Pharmaceutical Journal, doi:10.1016/j.jsps.2023.02.004.
Altman (B) et al., How to obtain the confidence interval from a P value, BMJ, doi:10.1136/bmj.d2090.
Andreani et al., In vitro testing of combined hydroxychloroquine and azithromycin on SARS-CoV-2 shows synergistic effect, Microbial Pathogenesis, doi:/10.1016/j.micpath.2020.104228.
Anglemyer et al., Healthcare outcomes assessed with observational study designs compared with those assessed in randomized trials, Cochrane Database of Systematic Reviews 2014, Issue 4, doi:10.1002/14651858.MR000034.pub2.
Arch et al., Evaluation of the effectiveness of remdesivir in treating severe COVID-19 using data from the ISARIC WHO Clinical Characterisation Protocol UK: a prospective, national cohort study, medRxiv, doi:10.1101/2021.06.18.21259072.
Arfijanto et al., Duration of SARS-CoV-2 RNA Shedding Is Significantly Influenced by Disease Severity, Bilateral Pulmonary Infiltrates, Antibiotic Treatment, and Diabetic Status: Consideration for Isolation Period, Pathophysiology, doi:10.3390/pathophysiology30020016.
Aweimer et al., Mortality rates of severe COVID-19-related respiratory failure with and without extracorporeal membrane oxygenation in the Middle Ruhr Region of Germany, Scientific Reports, doi:10.1038/s41598-023-31944-7.
Barrat-Due et al., Evaluation of the Effects of Remdesivir and Hydroxychloroquine on Viral Clearance in COVID-19, Annals of Internal Medicine, doi:10.7326/M21-0653.
Bavaro et al., Efficacy of Remdesivir and Neutralizing Monoclonal Antibodies in Monotherapy or Combination Therapy in Reducing the Risk of Disease Progression in Elderly or Immunocompromised Hosts Hospitalized for COVID-19: A Single Center Retrospective Study, Viruses, doi:10.3390/v15051199.
Behboodikhah et al., Evaluation of the Costs and Outcomes of COVID-19 Therapeutic Regimens in Hospitalized Patients in Shiraz, Iranian Journal of Science and Technology, Transactions A: Science, doi:10.1007/s40995-022-01351-0.
Beigel et al., Remdesivir for the Treatment of Covid-19 — Final Report, NEJM, doi:10.1056/NEJMoa2007764.
Biancatelli et al., Quercetin and Vitamin C: An Experimental, Synergistic Therapy for the Prevention and Treatment of SARS-CoV-2 Related Disease (COVID-19), Frontiers in Immunology, doi:10.3389/fimmu.2020.01451.
Bowen et al., Reduction in risk of death among patients admitted with COVID-19 between first and second epidemic waves in New York City, Open Forum Infectious Diseases, doi:10.1093/ofid/ofac436.
Burhan et al., Characteristics and outcomes of patients with severe COVID-19 in Indonesia: Lessons from the first wave, PLOS ONE, doi:10.1371/journal.pone.0290964.
Chew et al., Clinical Predictors for Abnormal ALT in Patients Infected with COVID-19—A Retrospective Single Centre Study, Pathogens, doi:10.3390/pathogens12030473.
De Forni et al., Synergistic drug combinations designed to fully suppress SARS-CoV-2 in the lung of COVID-19 patients, PLoS ONE, doi:10.1371/journal.pone.0276751.
De Forni (B) et al., Synergistic drug combinations designed to fully suppress SARS-CoV-2 in the lung of COVID-19 patients, PLoS ONE, doi:10.1371/journal.pone.0276751.
Deaton et al., Understanding and misunderstanding randomized controlled trials, Social Science & Medicine, 210, doi:10.1016/j.socscimed.2017.12.005.
Delandre et al., Antiviral Activity of Repurposing Ivermectin against a Panel of 30 Clinical SARS-CoV-2 Strains Belonging to 14 Variants, Pharmaceuticals, doi:10.3390/ph15040445.
Diaz et al., Remdesivir and Mortality in Patients with COVID-19, Clinical Infectious Diseases, doi:10.1093/cid/ciab698.
Egger et al., Bias in meta-analysis detected by a simple, graphical test, BMJ, doi:10.1136/bmj.315.7109.629.
El-Solh et al., Clinical Course and Outcome of COVID-19 Acute Respiratory Distress Syndrome: Data From a National Repository, Journal of Intensive Care Medicine, doi:10.1177/0885066621994476.
Elec et al., COVID-19 and Kidney Transplantation: The impact of remdesivir on renal function and outcome - a retrospective cohort study, International Journal of Infectious Diseases, doi:10.1016/j.ijid.2022.03.015.
Elhadi et al., Epidemiology, outcomes, and utilization of intensive care unit resources for critically ill COVID-19 patients in Libya: A prospective multi-center cohort study, PLOS ONE, doi:10.1371/journal.pone.0251085.
Faria et al., Genomics and epidemiology of the P.1 SARS-CoV-2 lineage in Manaus, Brazil, Science, doi:10.1126/science.abh2644.
Flisiak et al., Remdesivir-based therapy improved recovery of patients with COVID-19 in the SARSTer multicentre, real-world study, Polish Archives of Internal Medicine, doi:10.20452/pamw.15735.
Fried et al., Patient Characteristics and Outcomes of 11,721 Patients with COVID19 Hospitalized Across the United States, Clinical Infectious Disease, doi:10.1093/cid/ciaa1268.
Garibaldi et al., Effectiveness of remdesivir with and without dexamethasone in hospitalized patients with COVID-19, medRxiv, doi:10.1101/2020.11.19.20234153.
Gasmi et al., Quercetin in the Prevention and Treatment of Coronavirus Infections: A Focus on SARS-CoV-2, Pharmaceuticals, doi:10.3390/ph15091049.
Gérard et al., Remdesivir and Acute Renal Failure: A Potential Safety Signal From Disproportionality Analysis of the WHO Safety Database, Clinical Pharmacology & Therapeutics, doi:10.1002/cpt.2145.
Goldberg et al., A real-life setting evaluation of the effect of remdesivir on viral load in COVID-19 patients admitted to a large tertiary center in Israel, Clinical Microbiology and Infection, doi:10.1016/j.cmi.2021.02.029.
Gottlieb et al., Early Remdesivir to Prevent Progression to Severe Covid-19 in Outpatients, New England Journal of Medicine, doi:10.1056/NEJMoa2116846.
Gøtzsche, P., Bias in double-blind trials, Doctoral Thesis, University of Copenhagen, www.scientificfreedom.dk/2023/05/16/bias-in-double-blind-trials-doctoral-thesis/.
Hagman et al., Effects of remdesivir on SARS-CoV-2 viral dynamics and mortality in viraemic patients hospitalized for COVID-19, Journal of Antimicrobial Chemotherapy, doi:10.1093/jac/dkad295.
Harbord et al., A modified test for small-study effects in meta-analyses of controlled trials with binary endpoints, Statistics in Medicine, doi:10.1002/sim.2380.
Hartantri et al., Clinical and treatment factors associated with the mortality of COVID-19 patients admitted to a referral hospital in Indonesia, The Lancet Regional Health - Southeast Asia, doi:10.1016/j.lansea.2023.100167.
Hayden et al., Baloxavir Marboxil for Uncomplicated Influenza in Adults and Adolescents, New England Journal of Medicine, doi:10.1056/NEJMoa1716197.
Ikematsu et al., Baloxavir Marboxil for Prophylaxis against Influenza in Household Contacts, New England Journal of Medicine, doi:10.1056/NEJMoa1915341.
Jadad et al., Randomized Controlled Trials: Questions, Answers, and Musings, Second Edition, doi:10.1002/9780470691922.
Jamir et al., Determinants of Outcome Among Critically Ill Police Personnel With COVID-19: A Retrospective Observational Study From Andhra Pradesh, India, Cureus, doi:10.7759/cureus.20394.
Jeffreys et al., Remdesivir-ivermectin combination displays synergistic interaction with improved in vitro activity against SARS-CoV-2, International Journal of Antimicrobial Agents, doi:10.1016/j.ijantimicag.2022.106542.
Jeffreys (B) et al., Remdesivir-ivermectin combination displays synergistic interaction with improved in vitro activity against SARS-CoV-2, International Journal of Antimicrobial Agents, doi:10.1016/j.ijantimicag.2022.106542.
Jitobaom et al., Favipiravir and Ivermectin Showed in Vitro Synergistic Antiviral Activity against SARS-CoV-2, Research Square, doi:10.21203/rs.3.rs-941811/v1.
Jitobaom (B) et al., Synergistic anti-SARS-CoV-2 activity of repurposed anti-parasitic drug combinations, BMC Pharmacology and Toxicology, doi:10.1186/s40360-022-00580-8.
Jittamala et al., Clinical antiviral efficacy of remdesivir in COVID-19: an open label, randomized, controlled adaptive platform trial (PLATCOV), The Journal of Infectious Diseases, doi:10.1093/infdis/jiad275.
Karita et al., Trajectory of viral load in a prospective population-based cohort with incident SARS-CoV-2 G614 infection, medRxiv, doi:10.1101/2021.08.27.21262754.
Kim et al., Clinical Outcome and Prognosis of a Nosocomial Outbreak of COVID-19, Journal of Clinical Medicine, doi:10.3390/jcm12062279.
Kneidinger et al., Outcome of lung transplant recipients infected with SARS-CoV-2/Omicron/B.1.1.529: a Nationwide German study, Infection, doi:10.1007/s15010-022-01914-8.
Kumar et al., Combining baloxavir marboxil with standard-of-care neuraminidase inhibitor in patients hospitalised with severe influenza (FLAGSTONE): a randomised, parallel-group, double-blind, placebo-controlled, superiority trial, The Lancet Infectious Diseases, doi:10.1016/S1473-3099(21)00469-2.
Kuno et al., The association of remdesivir and in-hospital outcomes for COVID-19 patients treated with steroids, Journal of Antimicrobial Chemotherapy, doi:10.1093/jac/dkab256.
Kurniyanto et al., Factors Associated with Death and ICU Referral among COVID-19 Patients Hospitalized in the Secondary Referral Academic Hospital in East Jakarta, Indonesia, Journal of Clinical Virology Plus, doi:10.1016/j.jcvp.2022.100068.
Lee et al., Analysis of Overall Level of Evidence Behind Infectious Diseases Society of America Practice Guidelines, Arch Intern Med., 2011, 171:1, 18-22, doi:10.1001/archinternmed.2010.482.
López-Medina et al., Effect of Ivermectin on Time to Resolution of Symptoms Among Adults With Mild COVID-19: A Randomized Clinical Trial, JAMA, doi:10.1001/jama.2021.3071.
Macaskill et al., A comparison of methods to detect publication bias in meta-analysis, Statistics in Medicine, doi:10.1002/sim.698.
Madan et al., Remdesivir for the treatment of COVID-19 disease: A retrospective comparative study of patients treated with and without Remdesivir, medRxiv, doi:10.1101/2021.07.15.21260600.
Madan (B) et al., Remdesivir for the treatment of COVID-19 disease: A retrospective comparative study of patients treated with and without Remdesivir, medRxiv, doi:10.1101/2021.07.15.21260600.
Mahajan et al., Clinical outcomes of using remdesivir in patients with moderate to severe COVID-19: A prospective randomised study, Indian Journal of Anasthesia, doi:10.4103/ija.IJA_149_21.
Malundo et al., Predictors of Mortality among inpatients with COVID-19 Infection in a Tertiary Referral Center in the Philippines, IJID Regions, doi:10.1016/j.ijregi.2022.07.009.
McLean et al., Impact of Late Oseltamivir Treatment on Influenza Symptoms in the Outpatient Setting: Results of a Randomized Trial, Open Forum Infect. Dis. September 2015, 2:3, doi:10.1093/ofid/ofv100.
Mitsushima et al., Risk of Underlying Diseases and Effectiveness of Drugs on COVID-19 Inpatients Assessed Using Medical Claims in Japan: Retrospective Observational Study, International Journal of General Medicine, doi:10.2147/IJGM.S394413.
Moreno et al., Assessment of regression-based methods to adjust for publication bias through a comprehensive simulation study, BMC Medical Research Methodology, doi:10.1186/1471-2288-9-2.
Mozaffari et al., Remdesivir reduced mortality in immunocompromised patients hospitalized for COVID-19 across variant waves: Findings from routine clinical practice., Clinical Infectious Diseases, doi:10.1093/cid/ciad460.
Mozaffari (B) et al., Remdesivir treatment in hospitalized patients with COVID-19: a comparative analysis of in-hospital all-cause mortality in a large multi-center observational cohort, Clinical Infectious Diseases, doi:10.1093/cid/ciab875.
Mulhem et al., 3219 hospitalised patients with COVID-19 in Southeast Michigan: a retrospective case cohort study, BMJ Open, doi:10.1136/bmjopen-2020-042042.
Mustafa et al., Pattern of medication utilization in hospitalized patients with COVID-19 in three District Headquarters Hospitals in the Punjab province of Pakistan, Exploratory Research in Clinical and Social Pharmacy, doi:10.1016/j.rcsop.2021.100101.
Nadeem et al., Effects of Different Anticoagulation Doses on Moderate-to-Severe COVID-19 Pneumonia With Hypoxemia, Cureus, doi:10.7759/cureus.43389.
Nichol et al., Challenging issues in randomised controlled trials, Injury, 2010, doi: 10.1016/j.injury.2010.03.033, www.injuryjournal.com/article/S0020-1383(10)00233-0/fulltext.
Nonaka et al., SARS-CoV-2 variant of concern P.1 (Gamma) infection in young and middle-aged patients admitted to the intensive care units of a single hospital in Salvador, Northeast Brazil, February 2021, International Journal of Infectious Diseases, doi:10.1016/j.ijid.2021.08.003.
Ohl et al., Association of Remdesivir Treatment With Survival and Length of Hospital Stay Among US Veterans Hospitalized With COVID-19, JAMA Network Open, doi:10.1001/jamanetworkopen.2021.14741.
Oku et al., Risk factors for hospitalization or mortality for COVID-19 in patients with rheumatic diseases: Results of a nation-wide JCR COVID-19 registry in Japan, Modern Rheumatology, doi:10.1093/mr/roac104.
Olender et al., Remdesivir for Severe Coronavirus Disease 2019 (COVID-19) Versus a Cohort Receiving Standard of Care, Clinical Infectious Diseases, doi:10.1093/cid/ciaa1041.
Ong et al., A cohort study of COVID-19 infection in pediatric oncology patients plus the utility and safety of remdesivir treatment, Acta Oncologica, doi:10.1080/0284186X.2023.2169079.
Ostrov et al., Highly Specific Sigma Receptor Ligands Exhibit Anti-Viral Properties in SARS-CoV-2 Infected Cells, Pathogens, doi:10.3390/pathogens10111514.
Pasquini et al., Effectiveness of remdesivir in patients with COVID-19 under mechanical ventilation in an Italian ICU, Journal of Antimicrobial Chemotherapy, doi:10.1093/jac/dkaa321.
Peacock et al., The SARS-CoV-2 variant, Omicron, shows rapid replication in human primary nasal epithelial cultures and efficiently uses the endosomal route of entry, bioRxiv, doi:10.1101/2021.12.31.474653.
Peters, J., Comparison of Two Methods to Detect Publication Bias in Meta-analysis, JAMA, doi:10.1001/jama.295.6.676.
Piccicacco et al., Real-world effectiveness of early remdesivir and sotrovimab in the highest-risk COVID-19 outpatients during the Omicron surge, Journal of Antimicrobial Chemotherapy, doi:10.1093/jac/dkac256.
Pourhoseingholi et al., Case Characteristics, Clinical Data, And Outcomes of Hospitalized COVID-19 Patients In Qom Province, Iran: A Prospective Cohort Study, Research Square, doi:10.21203/rs.3.rs-365321/v2.
Punzalan et al., Utility of laboratory and immune biomarkers in predicting disease progression and mortality among patients with moderate to severe COVID-19 disease at a Philippine tertiary hospital, Frontiers in Immunology, doi:10.3389/fimmu.2023.1123497.
Raad et al., International Multicenter Study Comparing Cancer to Non-Cancer Patients with COVID-19: Impact of Risk Factors and Treatment Modalities on Survivorship, medRxiv, doi:10.1101/2022.08.25.22279181.
Rothstein, H., Publication Bias in Meta-Analysis: Prevention, Assessment and Adjustments, www.wiley.com/en-ae/Publication+Bias+in+Meta+Analysis:+Prevention,+Assessment+and+Adjustments-p-9780470870143.
Rücker et al., Arcsine test for publication bias in meta-analyses with binary outcomes, Statistics in Medicine, doi:10.1002/sim.2971.
Salehi et al., Risk factors of death in mechanically ventilated COVID-19 patients: a retrospective multi-center study, Research Square, doi:10.21203/rs.3.rs-1362678/v1.
Schmidt et al., Association Between Androgen Deprivation Therapy and Mortality Among Patients With Prostate Cancer and COVID-19, JAMA Network Open, doi:10.1001/jamanetworkopen.2021.34330.
Shamsi et al., Survival and Mortality in Hospitalized Children with COVID-19: A Referral Center Experience in Yazd, Iran, Canadian Journal of Infectious Diseases and Medical Microbiology, doi:10.1155/2023/5205188.
Siraj et al., Efficacy of Various Treatment Modalities on Patient-related Outcome in Hospitalized COVID-19 Patients – A Retrospective Study, Indian Journal of Clinical Practice, 32:9, ijcp.in/Admin/CMS/PDF/6.%20OriginalResearch_IJCP_Feb2022.pdf.
SOLIDARITY, Repurposed antiviral drugs for COVID-19; interim WHO SOLIDARITY trial results Trial Consortium, NEJM, doi:10.1056/NEJMoa2023184.
Spinner et al., Effect of Remdesivir vs Standard Care on Clinical Status at 11 Days in Patients With Moderate COVID-19A Randomized Clinical Trial, JAMA, doi:10.1001/jama.2020.16349.
Stanley et al., Meta-regression approximations to reduce publication selection bias, Research Synthesis Methods, doi:10.1002/jrsm.1095.
Sweeting et al., What to add to nothing? Use and avoidance of continuity corrections in meta-analysis of sparse data, Statistics in Medicine, doi:10.1002/sim.1761.
Thairu et al., A Comparison of Ivermectin and Non Ivermectin Based Regimen for COVID-19 in Abuja: Effects on Virus Clearance, Days-to-discharge and Mortality, Journal of Pharmaceutical Research International, doi:10.9734/jpri/2022/v34i44A36328.
Treanor et al., Efficacy and Safety of the Oral Neuraminidase Inhibitor Oseltamivir in Treating Acute Influenza: A Randomized Controlled Trial, JAMA, 2000, 283:8, 1016-1024, doi:10.1001/jama.283.8.1016.
Tsuzuki et al., Efficacy of remdesivir in hospitalized nonsevere COVID-19 patients in Japan: A large observational study using the COVID-19 Registry Japan, International Journal of Infectious Diseases, doi:10.1016/j.ijid.2022.02.039.
Ullah et al., Efficacy of Remdesivir in Covid-19 Patients; Multicenter Study in Lahore, International Journal of Sciences, doi:10.18483/ijSci.2417.
Vermillion et al., Inhaled remdesivir reduces viral burden in a nonhuman primate model of SARS-CoV-2 infection, Science Translational Medicine, doi:10.1126/scitranslmed.abl8282.
Wang et al., Remdesivir in adults with severe COVID-19: a randomised, double-blind, placebo-controlled, multicentre trial, Lancet, doi:10.1016/S0140-6736(20)31022-9.
Willett et al., The hyper-transmissible SARS-CoV-2 Omicron variant exhibits significant antigenic change, vaccine escape and a switch in cell entry mechanism, medRxiv, doi:10.1101/2022.01.03.21268111.
Williams, T., Not All Ivermectin Is Created Equal: Comparing The Quality of 11 Different Ivermectin Sources, Do Your Own Research, doyourownresearch.substack.com/p/not-all-ivermectin-is-created-equal.
Wu et al., Acute Kidney Injury Associated With Remdesivir: A Comprehensive Pharmacovigilance Analysis of COVID-19 Reports in FAERS, Frontiers in Pharmacology, doi:10.3389/fphar.2022.692828.
Xu et al., A study of impurities in the repurposed COVID-19 drug hydroxychloroquine sulfate by UHPLC-Q/TOF-MS and LC-SPE-NMR, Rapid Communications in Mass Spectrometry, doi:10.1002/rcm.9358.
Yeramaneni et al., Famotidine Use Is Not Associated With 30-day Mortality: A Coarsened Exact Match Study in 7158 Hospitalized Patients With Coronavirus Disease 2019 From a Large Healthcare System, Gastroenterology, doi:10.1053/j.gastro.2020.10.011.
Zangeneh et al., Survival analysis based on body mass index in patients with Covid-19 admitted to the intensive care unit of Amir Al-Momenin Hospital in Arak – 2021, Obesity Medicine, doi:10.1016/j.obmed.2022.100420.
Zavascki et al., Advanced ventilatory support and mortality in hospitalized patients with COVID-19 caused by Gamma (P.1) variant of concern compared to other lineages: cohort study at a reference center in Brazil, Research Square, doi:10.21203/rs.3.rs-910467/v1.
Zeraatkar et al., Consistency of covid-19 trial preprints with published reports and impact for decision making: retrospective review, BMJ Medicine, doi:10.1136/bmjmed-2022-0003091.
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