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Povidone-Iodine for COVID-19: real-time meta analysis of 20 studies
Covid Analysis, May 2023
https://c19early.org/pmeta.html
 
0 0.5 1 1.5+ All studies 50% 20 3,226 Improvement, Studies, Patients Relative Risk Mortality 72% 2 872 Hospitalization 76% 3 885 Recovery 25% 3 286 Cases 45% 1 1,354 Viral clearance 65% 17 1,517 RCTs 53% 17 2,865 RCT mortality 88% 1 606 Peer-reviewed 48% 17 3,132 Prophylaxis 45% 1 1,354 Early 64% 14 1,536 Late 42% 5 336 Povidone-Iodine for COVID-19 c19early.org/p May 2023 Favorspovidone-iodine Favorscontrol after exclusions
Statistically significant improvements are seen for mortality, cases, and viral clearance. 11 studies from 11 independent teams in 9 different countries show statistically significant improvements in isolation (7 for the most serious outcome).
Meta analysis using the most serious outcome reported shows 50% [37‑61%] improvement. Results are similar for Randomized Controlled Trials, similar after exclusions, and similar for peer-reviewed studies. Early treatment is more effective than late treatment.
Results are robust — in exclusion sensitivity analysis 15 of 20 studies must be excluded to avoid finding statistically significant efficacy in pooled analysis.
0 0.5 1 1.5+ All studies 50% 20 3,226 Improvement, Studies, Patients Relative Risk Mortality 72% 2 872 Hospitalization 76% 3 885 Recovery 25% 3 286 Cases 45% 1 1,354 Viral clearance 65% 17 1,517 RCTs 53% 17 2,865 RCT mortality 88% 1 606 Peer-reviewed 48% 17 3,132 Prophylaxis 45% 1 1,354 Early 64% 14 1,536 Late 42% 5 336 Povidone-Iodine for COVID-19 c19early.org/p May 2023 Favorspovidone-iodine Favorscontrol after exclusions
Some studies only test short term viral load after a single application. Excessive use of PVP-I could affect thyroid function.
No treatment, vaccine, or intervention is 100% effective and available. All practical, effective, and safe means should be used based on risk/benefit analysis. Multiple treatments are typically used in combination, and other treatments may be more effective. Only 10% of povidone-iodine studies show zero events with treatment.
All data to reproduce this paper and sources are in the appendix. Other meta analyses for povidone-iodine can be found in [Hasan, Idrees], showing significant improvements for viral load and viral clearance.
Evolution of COVID-19 clinical evidence Povidone-Iodine p=0.000000037 Acetaminophen p=0.0000018 2020 2021 2022 2023 Effective Harmful c19early.org May 2023 meta analysis results (pooled effects) 100% 50% 0% -50%
Percentage improvement with povidone-iodine (more)
Early treatment All studies Prophylaxis Studies Patients Authors
All studies64% [43‑78%]
****
50% [37‑61%]
****
45% [20‑62%]
**
20 3,226 194
Randomized Controlled TrialsRCTs71% [50‑84%]
****
53% [35‑66%]
****
45% [20‑62%]
**
17 2,865 178
Mortality88% [50‑97%]
**
72% [8‑92%]
*
- 2 872 12
HospitalizationHosp.76% [-14‑95%]76% [-14‑95%]- 3 885 26
Highlights
PVP-I reduces risk for COVID-19 with very high confidence for viral clearance and in pooled analysis, low confidence for mortality, hospitalization, and cases, and very low confidence for recovery.
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 51 treatments.
A
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Mohamed (RCT) 86% 0.14 [0.01-2.21] viral+ 0/5 3/5 Improvement, RR [CI] Treatment Control Choudhury (RCT) 88% 0.12 [0.03-0.50] death 2/303 17/303 Guenezan (RCT) 63% 0.37 [0.06-1.63] viral load 12 (n) 12 (n) Elzein (DB RCT) 89% 0.11 [0.01-1.00] viral load 25 (n) 9 (n) Short term viral Arefin (RCT) 79% 0.21 [0.08-0.54] viral+ 4/27 19/27 Short term viral Baxter (RCT) -214% 3.14 [0.13-74.7] hosp. 1/37 0/42 OT​1 Pablo-Marcos 29% 0.71 [0.32-1.56] viral load 31 (n) 40 (n) Sulistyani (SB RCT) 6% 0.94 [0.45-1.96] viral load 15 (n) 15 (n) Elsersy (DB RCT) 91% 0.09 [0.01-1.62] hosp. 0/100 5/100 CT​2 Sevinç Gül (RCT) 99% 0.01 [0.00-439] viral load 21 (n) 20 (n) Short term viral OT​1 Natto (RCT) 74% 0.26 [0.02-2.80] viral load 12 (n) 12 (n) Short term viral OT​1 Sirijatuphat 33% 0.67 [0.17-2.67] viral load 12 (n) 12 (n) Short term viral Karaaltin (RCT) 83% 0.17 [0.05-0.62] viral load 30 (n) 30 (n) Matsuyama (RCT) 69% 0.31 [0.10-0.93] viral+ 4/139 13/140 Tau​2 = 0.23, I​2 = 32.3%, p < 0.0001 Early treatment 64% 0.36 [0.22-0.57] 11/769 57/767 64% improvement Seneviratne (RCT) 33% 0.67 [0.50-0.91] viral load 4 (n) 2 (n) Short term viral Improvement, RR [CI] Treatment Control Zarabanda (RCT) -27% 1.27 [0.26-6.28] no recov. 3/13 2/11 OT​1 Jamir (ICU) 57% 0.43 [0.27-0.69] death 39/163 62/103 ICU patients Ferrer (RCT) 34% 0.66 [0.02-19.0] viral load 9 (n) 12 (n) Short term viral Fantozzi (RCT) 31% 0.69 [0.39-1.21] viral+ 5/8 10/11 Short term viral OT​1 Tau​2 = 0.03, I​2 = 28.0%, p = 0.00014 Late treatment 42% 0.58 [0.44-0.76] 47/197 74/139 42% improvement Seet (CLUS. RCT) 45% 0.55 [0.38-0.80] symp. case 42/735 64/619 OT​1 Improvement, RR [CI] Treatment Control Tau​2 = 0.00, I​2 = 0.0%, p = 0.002 Prophylaxis 45% 0.55 [0.38-0.80] 42/735 64/619 45% improvement All studies 50% 0.50 [0.39-0.63] 100/1,701 195/1,525 50% improvement 20 povidone-iodine COVID-19 studies c19early.org/p May 2023 Tau​2 = 0.07, I​2 = 30.4%, p < 0.0001 Effect extraction pre-specified(most serious outcome, see appendix) 1 OT: comparison with other treatment2 CT: study uses combined treatment Favors povidone-iodine Favors control
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Mohamed (RCT) 86% viral- Relative Risk [CI] Choudhury (RCT) 88% death Guenezan (RCT) 63% viral load Elzein (DB RCT) 89% viral- Short term viral Arefin (RCT) 79% viral- Short term viral Baxter (RCT) -214% hospitalization OT​1 Pablo-Marcos 29% viral- Sulisty.. (SB RCT) 6% viral- Elsersy (DB RCT) 91% hospitalization CT​2 Sevinç Gül (RCT) 99% viral load Short term viral OT​1 Natto (RCT) 74% viral load Short term viral OT​1 Sirijatuphat 33% viral load Short term viral Karaaltin (RCT) 83% viral load Matsuyama (RCT) 69% viral- Tau​2 = 0.23, I​2 = 32.3%, p < 0.0001 Early treatment 64% 64% improvement Seneviratne (RCT) 33% viral load Short term viral Zarabanda (RCT) -27% recovery OT​1 Jamir (ICU) 57% death ICU patients Ferrer (RCT) 34% viral load Short term viral Fantozzi (RCT) 31% viral- Short term viral OT​1 Tau​2 = 0.03, I​2 = 28.0%, p = 0.00014 Late treatment 42% 42% improvement Seet (CLUS. RCT) 45% symp. case OT​1 Tau​2 = 0.00, I​2 = 0.0%, p = 0.002 Prophylaxis 45% 45% improvement All studies 50% 50% improvement 20 povidone-iodine COVID-19 studies c19early.org/p May 2023 Tau​2 = 0.07, I​2 = 30.4%, p < 0.0001 Effect extraction pre-specifiedRotate device for footnotes/details Favors povidone-iodine Favors control
B
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C
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D
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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. 0.9% of 3,817 proposed treatments show efficacy [c19early.org]. D. Timeline of results in povidone-iodine studies. The marked dates indicate the time when efficacy was known with a statistically significant improvement of ≥10% from ≥3 studies for pooled outcomes, one or more specific outcome, and pooled outcomes in RCTs. Efficacy based on specific outcomes was delayed by 1.3 months, compared to using pooled outcomes.
We analyze all significant studies concerning the use of povidone-iodine 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.
Several in vitro studies show that PVP-I is effective for SARS-CoV-2 at clinically relevant concentrations [Anderson, Bidra, Frank, Hassandarvish, Pelletier, Tucker, Xu].
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, and 9 show forest plots for random effects meta-analysis of all studies with pooled effects, mortality results, hospitalization, recovery, cases, viral clearance, and peer reviewed studies.
Table 1. Random effects meta-analysis for all stages combined, with different exclusions, and for specific outcomes. Results show the percentage improvement with treatment and the 95% confidence interval. ** p<0.01  *** p<0.001  **** p<0.0001.
Improvement Studies Patients Authors
All studies50% [37‑61%]
****
20 3,226 194
After exclusions52% [38‑63%]
****
19 3,155 188
Peer-reviewed studiesPeer-reviewed48% [34‑60%]
****
17 3,132 158
Randomized Controlled TrialsRCTs53% [35‑66%]
****
17 2,865 178
Mortality72% [8‑92%]
*
2 872 12
HospitalizationHosp.76% [-14‑95%]3 885 26
Recovery25% [-18‑53%]3 286 33
Viral65% [42‑79%]
****
17 1,517 161
RCT hospitalizationRCT hosp.76% [-14‑95%]3 885 26
Table 2. Random effects meta-analysis results by treatment stage. Results show the percentage improvement with treatment, the 95% confidence interval, and the number of studies for the stage.treatment and the 95% confidence interval. ** p<0.01  *** p<0.001  **** p<0.0001.
Early treatment Late treatment Prophylaxis
All studies64% [43‑78%]
****
42% [24‑56%]
***
45% [20‑62%]
**
After exclusions69% [47‑81%]
****
42% [24‑56%]
***
45% [20‑62%]
**
Peer-reviewed studiesPeer-reviewed63% [36‑79%]
***
42% [24‑56%]
***
45% [20‑62%]
**
Randomized Controlled TrialsRCTs71% [50‑84%]
****
31% [11‑47%]
**
45% [20‑62%]
**
Mortality88% [50‑97%]
**
57% [31‑73%]
***
-
HospitalizationHosp.76% [-14‑95%]--
Recovery32% [-28‑64%]-27% [-528‑74%]-
Viral73% [49‑86%]
****
32% [11‑48%]
**
-
RCT hospitalizationRCT hosp.76% [-14‑95%]--
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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 hospitalization.
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Figure 6. Random effects meta-analysis for recovery.
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Figure 7. Random effects meta-analysis for cases.
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Figure 8. Random effects meta-analysis for viral clearance.
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Figure 9. 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 10 shows a comparison of results for RCTs and non-RCT studies. The median effect size for RCTs is 69% improvement, compared to 33% for other studies. Figure 11, 12, and 13 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 51 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, 36 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 36 treatments with statistically significant efficacy/harm, 23 have been confirmed in RCTs, with a mean delay of 4.4 months. For the 13 unconfirmed treatments, 4 have zero RCTs to date. The point estimates for the remaining 9 are all consistent with the overall results (benefit or harm), with 8 showing >20%. The only treatment showing >10% efficacy for all studies, but <10% for RCTs is 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 10. Results for RCTs and non-RCT studies.
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Figure 11. 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 12. Random effects meta-analysis for RCT mortality results.
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Figure 13. 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 14 shows a forest plot for random effects meta-analysis of all studies after exclusions.
[Pablo-Marcos], unadjusted results with no group details.
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Figure 14. 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.
Table 3. Studies of baloxavir for influenza show that early treatment is more effective.
Treatment delayResult
Post exposure prophylaxis86% fewer cases [Ikematsu]
<24 hours-33 hours symptoms [Hayden]
24-48 hours-13 hours symptoms [Hayden]
Inpatients-2.5 hours to improvement [Kumar]
Figure 15 shows a mixed-effects meta-regression for efficacy as a function of treatment delay in COVID-19 studies from 51 treatments, showing that efficacy declines rapidly with treatment delay. Early treatment is critical for COVID-19.
Figure 15. Early treatment is more effective. Meta-regression showing efficacy as a function of treatment delay in COVID-19 studies from 51 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 (B)] 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 16. 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, 36 of the treatments we analyze show statistically significant efficacy or harm, defined as ≥10% decreased risk or >0% increased risk from ≥3 studies. 97% of treatments showing statistically significant efficacy/harm with pooled effects have been confirmed with one or more specific outcomes, with a mean delay of 3.1 months. When restricting to RCTs only, 55% of treatments showing statistically significant efficacy/harm with pooled effects have been confirmed with one or more specific outcomes, with a mean delay of 2.9 months.
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Figure 16. 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.
Safety analysis can be found in [Frank (B), Frank (C), Khan]. [Frank (B)] conclude that PVP-I can safely be used in the nose at concentrations up to 1.25% and in the mouth at concentrations up to 2.5% for up to 5 months.
Publishing is often biased towards positive results, however evidence suggests that there may be a negative bias for inexpensive treatments for COVID-19. Both negative and positive results are very important for COVID-19, media in many countries prioritizes negative results for inexpensive treatments (inverting the typical incentive for scientists that value media recognition), and there are many reports of difficulty publishing positive results [Boulware, Meeus, Meneguesso]. For povidone-iodine, there is currently not enough data to evaluate publication bias with high confidence.
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 17 shows a scatter plot of results for prospective and retrospective studies. Prospective studies show 49% [33‑62%] improvement in meta analysis, compared to 57% [31‑73%] for retrospective studies, showing no significant difference. However, there has only been one retrospective study to date.
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Figure 17. 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 18 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 18. Example funnel plot analysis for simulated perfect trials.
Pharmaceutical drug trials often have conflicts of interest whereby sponsors or trial staff have a financial interest in the outcome being positive. PVP-I for COVID-19 lacks this because it is off-patent, has multiple manufacturers, and is very low cost. In contrast, most COVID-19 povidone-iodine trials have been run by physicians on the front lines with the primary goal of finding the best methods to save human lives and minimize the collateral damage caused by COVID-19. While pharmaceutical companies are careful to run trials under optimal conditions (for example, restricting patients to those most likely to benefit, only including patients that can be treated soon after onset when necessary, and ensuring accurate dosing), not all povidone-iodine trials represent the optimal conditions for efficacy.
Summary statistics from meta analysis necessarily lose information. As with all meta analyses, studies are heterogeneous, with differences in treatment delay, treatment regimen, patient demographics, variants, conflicts of interest, standard of care, and other factors. We provide analyses 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, Gasmi, Jeffreys, 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.
6 of the 20 studies compare against other treatments, which may reduce the effect seen. 1 of 20 studies combine treatments. The results of povidone-iodine alone may differ. 1 of 17 RCTs use combined treatment. Other meta analyses for povidone-iodine can be found in [Hasan, Idrees], showing significant improvements for one or more of viral load and viral clearance.
PVP-I is an effective treatment for COVID-19. Statistically significant improvements are seen for mortality, cases, and viral clearance. 11 studies from 11 independent teams in 9 different countries show statistically significant improvements in isolation (7 for the most serious outcome). Meta analysis using the most serious outcome reported shows 50% [37‑61%] improvement. Results are similar for Randomized Controlled Trials, similar after exclusions, and similar for peer-reviewed studies. Early treatment is more effective than late treatment. Results are robust — in exclusion sensitivity analysis 15 of 20 studies must be excluded to avoid finding statistically significant efficacy in pooled analysis.
Some studies only test short term viral load after a single application. Excessive use of PVP-I could affect thyroid function.
0 0.5 1 1.5 2+ Viral clearance 79% Improvement Relative Risk Viral clearance (b) 89% Viral clearance (c) 53% Viral clearance (d) 80% Viral clearance (e) 64% Viral clearance (f) 74% c19early.org/p Arefin et al. NCT04549376 Povidone-Iodine RCT EARLY Does povidone-iodine reduce short-term viral load for COVID-19? RCT 189 patients in Bangladesh Improved viral clearance with povidone-iodine (p=0.018) Arefin et al., Indian J. Otolaryngology and Head.., doi:10.1007/s12070-021-02616-7 Favors povidone-iodine Favors control
[Arefin] RCT with 189 patients showing significantly greater viral clearance with a single application of PVP-I. Authors recommend using PVP-I prophylactically in the nasopharynx and oropharynx. NCT04549376 [trialsjournal.biomedcentral.com].
0 0.5 1 1.5 2+ Hospitalization -214% Improvement Relative Risk Recovery 57% Transmission 14% Hospitalization, vs. CDC 94% c19early.org/p Baxter et al. NCT04559035 Povidone-Iodine RCT EARLY Is early treatment with povidone-iodine beneficial for COVID-19? RCT 79 patients in the USA (September - December 2020) Trial compares with sodium bicarbonate nasal irrigation Improved recovery with povidone-iodine (p=0.034) Baxter et al., Ear, Nose & Throat J., doi:10.1177/01455613221123737 Favors povidone-iodine Favors sodium bicar..
[Baxter] Small RCT 79 PCR+ patients 55+ comparing pressure-based nasal irrigation with povidone-iodine and sodium bicarbonate, showing improved recovery with povidone-iodine. Not all results comparing povidone-iodine and sodium bicarbonate are in the journal version, as authors focus on the comparison with CDC data. Earlier versions can be found at [medrxiv.org]. The reported hospitalization switched groups between the preprint and the journal version.
0 0.5 1 1.5 2+ Mortality 88% Improvement Relative Risk Hospitalization 84% Viral clearance 96% c19early.org/p Choudhury et al. Povidone-Iodine for COVID-19 RCT EARLY Is early treatment with povidone-iodine beneficial for COVID-19? RCT 606 patients in Bangladesh Lower mortality (p=0.00061) and hospitalization (p<0.0001) Choudhury et al., Bioresearch Communications, Volume 7, Issue 1, January 2021 Favors povidone-iodine Favors control
[Choudhury] RCT 606 patients in Bangladesh for povidone iodine mouthwash/gargle, nasal drops and eye drops showing significantly lower death, hospitalization, and PCR+ at day 7.
0 0.5 1 1.5 2+ Hospitalization 91% Improvement Relative Risk Recovery time 15% Recovery time, smell 49% Recovery time, taste 48% Viral clearance, day 7 68% Viral clearance, day 10 90% Viral clearance, day 4 29% Transmission 92% Transmission (b) 94% c19early.org/p Elsersy et al. PACTR202101875903773 Povidone-Iodine RCT EARLY Is early treatment with povidone-iodine+glycyrrhizic acid beneficial for COVID-19? Double-blind RCT 421 patients in Egypt (March - July 2021) Faster recovery (p=0.008) and improved viral clearance (p<0.0001) Elsersy et al., Frontiers in Medicine, doi:10.3389/fmed.2022.863917 Favors povidone-iodine Favors control
[Elsersy] RCT with 200 patients and 421 contacts in Egypt, with 100 patients and their contacts treated with nasal and oropharyngeal sprays containing povidone-iodine and glycyrrhizic acid, showing significantly faster viral clearance and recovery, and significantly lower transmission.

SOC included vitamin C and zinc. The spray active ingredients included a compound of glycyrrhizic acid in the form of ammonium glycyrrhizate 2.5 mg/ml plus PVI 0.5% for oropharyngeal and dipotassium glycyrrhizinate 2.5 mg/ml plus PVI 0.5% for nasal spray. Patients were advised to concomitantly use oropharyngeal and nasal sprays 6 times per day. They were instructed to abstain from food, drink, and smoke for 20min, particularly after oropharyngeal spray. The oropharyngeal spray bottle contains an atomizer that ends with a long arm applicator to insert inside the mouth cavity and can be directed up, down, right, or left to cover the entire pharyngeal area.
0 0.5 1 1.5 2+ Improvement in Ct value 89% Improvement Relative Risk c19early.org/p Elzein et al. Povidone-Iodine for COVID-19 RCT EARLY Does povidone-iodine reduce short-term viral load for COVID-19? Double-blind RCT 34 patients in Lebanon Improved viral clearance with povidone-iodine (not stat. sig., p=0.05) Elzein et al., J. Evidence Based Dental Practice, doi:10.1016/j.jebdp.2021.101584 Favors povidone-iodine Favors control
[Elzein] Small RCT comparing mouthwashing with PVP-I, Chlorhexidine, and water, showing significant efficacy for both PVP-I and Chlorhexidine, with PVP-I increasing Ct by a mean of 4.45 (p < 0.0001) and Chlorhexidine by a mean of 5.69 (p < 0.0001), compared to no significant difference for water.
0 0.5 1 1.5 2+ Viral load 57% no CI Improvement Relative Risk Viral load (b) 100% no CI Viral clearance 31% Viral clearance (b) 59% c19early.org/p Fantozzi et al. Povidone-Iodine for COVID-19 RCT LATE Does late treatment with povidone-iodine reduce short-term viral load? RCT 38 patients in Italy (December 2020 - May 2021) Trial compares with saline, results vs. placebo may differ Improved viral clearance with povidone-iodine (not stat. sig., p=0.26) Fantozzi et al., American J. Otolaryngology, doi:10.1016/j.amjoto.2022.103549 Favors povidone-iodine Favors saline
[Fantozzi] Mouthrinse RCT in Italy comparing short-term viral load after a single 60 second treatment with povidone-iodine, hydrogen peroxide, chlorhexidine, and saline. The greatest efficacy was seen with povidone-iodine, especially for patients with low viral load at baseline.
0 0.5 1 1.5 2+ Decrease in log viral load 34% Improvement Relative Risk c19early.org/p Ferrer et al. Povidone-Iodine for COVID-19 RCT LATE Does late treatment with povidone-iodine reduce short-term viral load? RCT 21 patients in Spain No significant difference in viral load Ferrer et al., Scientific Reports, doi:10.1038/s41598-021-03461-y Favors povidone-iodine Favors control
[Ferrer] Small very late (>50% 7+ days from symptom onset, 9 PVP-I patients) RCT testing mouthwashing with cetylpyridinium chloride, chlorhexidine, povidone-iodine, hydrogen peroxide, and distilled water, showing no significant differences. Over 30% of patients show >90% decrease in viral load @2 hrs with all 5. Authors note that a trend was observed for viral load decrease with PVP-I @2h for patients <6 days from onset (p=0.06, Wilcox test).
0 0.5 1 1.5 2+ Improvement in viral tite.. 63% Improvement Relative Risk c19early.org/p Guenezan et al. Povidone-Iodine for COVID-19 RCT EARLY Is early treatment with povidone-iodine beneficial for COVID-19? RCT 24 patients in France Improved viral load with povidone-iodine (not stat. sig., p=0.25) Guenezan et al., JAMA Otolaryngol Head Neck Surg., doi:10.1001/jamaoto.2020.5490 Favors povidone-iodine Favors control
[Guenezan] RCT of PCR+ patients with Ct<=20 with 12 treatment and 12 control patients, concluding that nasopharyngeal decolonization may reduce the carriage of infectious SARS-CoV-2 in adults with mild to moderate COVID-19. All patients but 1 had negative viral titer by day 3 (group not specified). There was no significant difference in viral RNA quantification over time. The mean relative difference in viral titers between baseline and day 1 was 75% [43%-95%] in the intervention group and 32% [10%-65%] in the control group. Thyroid dysfunction occurred in 42% of treated patients, with spontaneous resolution after the end of treatment. Patients in the treatment group were younger.
0 0.5 1 1.5 2+ Mortality 57% Improvement Relative Risk c19early.org/p Jamir et al. Povidone-Iodine for COVID-19 ICU Is very late treatment with povidone-iodine beneficial for COVID-19? Retrospective 266 patients in India (June - October 2020) Lower mortality with povidone-iodine (p=0.0004) Jamir et al., Cureus, doi:10.7759/cureus.20394 Favors povidone-iodine Favors control
[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.
0 0.5 1 1.5 2+ Viral load, day 5 83% Improvement Relative Risk Viral load, day 5 (b) 86% Viral load, day 3 82% Viral load, day 3 (b) 91% c19early.org/p Karaaltin et al. Povidone-Iodine for COVID-19 RCT EARLY Is early treatment with povidone-iodine beneficial for COVID-19? RCT 60 patients in Turkey (September - October 2021) Improved viral load with povidone-iodine (p=0.007) Karaaltin et al., Authorea, Inc., doi:10.22541/au.166675335.56566797/v1 Favors povidone-iodine Favors control
[Karaaltin] RCT 120 outpatients in Turkey, showing improved reduction in viral load with PVP-I nasal irrigation.

PVP-I prepared with hypertonic alkaline solution had better results. [Kreutzberger] show that SARS-CoV-2 requires acidic pH to infect cells, therefore alkalinization may add additional benefits.

All patients received favipiravir. PVP-I 1% 4 times per day.
0 0.5 1 1.5 2+ Viral infectivity, culture 69% Improvement Relative Risk Viral clearance, PCR 38% primary c19early.org/p Matsuyama et al. jRCT1051200078 Povidone-Iodine RCT EARLY Is early treatment with povidone-iodine beneficial for COVID-19? RCT 279 patients in Japan (November 2020 - March 2021) Improved viral clearance with povidone-iodine (p=0.025) Matsuyama et al., Scientific Reports, doi:10.1038/s41598-022-24683-8 Favors povidone-iodine Favors control
[Matsuyama] RCT 430 COVID+ patients in Japan, showing significantly lower viral infectivity from culture, and significantly faster PCR viral clearance with PVP-I.

For days 2-4 the study compares treatment with PVP-I vs. water (on day 5 both groups received PVP-I). Most patients were asymptomatic. 4 times per day mouthwashing and gargling with 20mL of 15-fold diluted PVP–I 7% or water.
0 0.5 1 1.5 2+ Viral clearance 86% Improvement Relative Risk c19early.org/p Mohamed et al. Povidone-Iodine for COVID-19 RCT EARLY Is early treatment with povidone-iodine beneficial for COVID-19? RCT 10 patients in Malaysia Improved viral clearance with povidone-iodine (not stat. sig., p=0.17) Mohamed et al., medRxiv, doi:10.1101/2020.09.07.20180448 Favors povidone-iodine Favors control
[Mohamed] Tiny RCT with 5 PVP-I patients, gargling 30 seconds, 3x per day, and 5 control patients (essential oils and tap water were also tested), showing improved viral clearance with PVP-I.
0 0.5 1 1.5 2+ Viral load, combined 74% Improvement Relative Risk Viral load, E 96% Viral load, S 44% c19early.org/p Natto et al. Povidone-Iodine for COVID-19 RCT EARLY Does povidone-iodine reduce short-term viral load for COVID-19? RCT 24 patients in Saudi Arabia Trial compares with saline, results vs. placebo may differ Improved viral load with povidone-iodine (not stat. sig., p=0.27) Natto et al., Medicine, doi:10.1097/MD.0000000000028925 Favors povidone-iodine Favors saline
[Natto] 60 patient RCT comparing chlorhexidine, PVP-I, and saline in Saudi Arabia with a single mouth rinse treatment and PCR testing 5 minutes later, showing statistically significant improvement in Ct value for PVP-I. PVP-I showed greater improvement than saline, without statistical significance.
0 0.5 1 1.5 2+ Viral load 29% Improvement Relative Risk Viral load (b) 9% c19early.org/p Pablo-Marcos et al. Povidone-Iodine for COVID-19 EARLY Is early treatment with povidone-iodine beneficial for COVID-19? Prospective study of 71 patients in Spain (May - November 2020) Improved viral clearance with povidone-iodine (not stat. sig., p=0.4) Pablo-Marcos et al., Enfermedades Infecciosas y .., doi:10.1016/j.eimc.2021.10.005 Favors povidone-iodine Favors control
[Pablo-Marcos] Small prospective study with 31 patients gargling povidone-iodine, 17 hydrogen peroxide, and 40 control patients, showing lower viral load mid-recovery with povidone-iodine, without reaching statistical significance. Oropharyngeal only, and only every 8 hours for two days. Results may be better with the addition of nasopharyngeal use, more frequent use, and without the two day limit.

Authors are not familiar with the literature, having found only one of the 7 previous trials for PVP-I and COVID-19. Non-randomized study with no adjustments or group details. Some results in Figure 1 appear to be switched compared to the text and the labels in the figure. The viral clearance figures do not match the group sizes - for example authors report 62% PCR- for PVP-I at the 3rd test, however there is no number of 31 patients that rounds to 62%.
0 0.5 1 1.5 2+ Symptomatic case 45% Improvement Relative Risk Case 31% c19early.org/p Seet et al. NCT04446104 Povidone-Iodine RCT Prophylaxis Is prophylaxis with povidone-iodine beneficial for COVID-19? RCT 1,354 patients in Singapore Trial compares with vitamin C, results vs. placebo may differ Fewer symptomatic cases (p=0.0022) and cases (p=0.012) Seet et al., Int. J. Infectious Diseases, doi:10.1016/j.ijid.2021.04.035 Favors povidone-iodine Favors vitamin C
[Seet] Prophylaxis RCT in Singapore with 3,037 low risk patients, showing lower serious cases, lower symptomatic cases, and lower confirmed cases of COVID-19 with all treatments (ivermectin, HCQ, PVP-I, and Zinc + vitamin C) compared to vitamin C.

Meta-analysis of vitamin C in 6 previous trials shows a benefit of 16%, so the actual benefit of ivermectin, HCQ, and PVP-I may be higher. Cluster RCT with 40 clusters.

There were no hospitalizations and no deaths. NCT04446104.
0 0.5 1 1.5 2+ Fold change 33% Improvement Relative Risk c19early.org/p Seneviratne et al. Povidone-Iodine for COVID-19 RCT LATE Does late treatment with povidone-iodine reduce short-term viral load? RCT 6 patients in Singapore Improved viral load with povidone-iodine (p=0.01) Seneviratne et al., Infection, doi:10.1007/s15010-020-01563-9 Favors povidone-iodine Favors control
[Seneviratne] Small mouthwash RCT with 4 PVP-I patients and 2 water patients concluding that PVP-I may have a sustained effect on reducing the salivary SARS-CoV-2 level in COVID-19 patients. ISRCTN95933274.
0 0.5 1 1.5 2+ Viral load 99% Improvement Relative Risk c19early.org/p Sevinç Gül et al. Povidone-Iodine for COVID-19 RCT EARLY Does povidone-iodine reduce short-term viral load for COVID-19? RCT 41 patients in Turkey Trial compares with saline, results vs. placebo may differ Improved viral load with povidone-iodine (not stat. sig., p=0.37) Sevinç Gül et al., Dental and Medical Problems, doi:10.17219/dmp/150831 Favors povidone-iodine Favors saline
[Sevinç Gül] RCT with 21 PVP-I and 20 saline patients gargling for 30 seconds and testing PCR Ct after 30 minutes, showing greater improvement with PVP-I, without statistical significance.

Ct values differ across testing platforms, however the reported Ct value difference can represent a large difference in viral load. For example, using the calibration included with the ct2vl converter, the reported difference in mean Ct values corresponds to a reduction in viral load of over 3x for PVP-I.
0 0.5 1 1.5 2+ Viral load, 3m left 33% Improvement Relative Risk Viral load, 3m right 88% Viral load, 4h right 83% c19early.org/p Sirijatuphat et al. TCTR20210125002 Povidone-Iodine EARLY Does povidone-iodine reduce short-term viral load for COVID-19? Prospective study of 12 patients in Thailand (Feb - Mar 2021) Improved viral load with povidone-iodine (not stat. sig., p=0.58) Sirijatuphat et al., medRxiv, doi:10.1101/2022.08.18.22278340 Favors povidone-iodine Favors control
[Sirijatuphat] Small single-arm trial testing short-term viral load change after a single administration of three puffs of 0.4% PVP-I, showing lower viral titer at 3 minutes and 4 hours, not reaching statistical significance. Authors note that one reason for the lower change compared to in vitro results is that the spray administration may be less effective.
0 0.5 1 1.5 2+ Improvement in Ct value 6% Improvement Relative Risk Improvement in Ct value (b) 11% c19early.org/p Sulistyani et al. Povidone-Iodine for COVID-19 RCT EARLY Is early treatment with povidone-iodine beneficial for COVID-19? RCT 30 patients in Indonesia (July - September 2021) No significant difference in viral clearance Sulistyani et al., F1000Research, doi:10.12688/f1000research.110843.1 Favors povidone-iodine Favors control
[Sulistyani] Small mouth rinsing and gargling RCT with 15 1% PVP-I, 12 0.5% PVP-I, 15 3% hydrogen peroxide, 12 1.5% hydrogen peroxide, and 15 water patients, showing rapid improvement in Ct value in all groups, and no significant differences between groups.
0 0.5 1 1.5 2+ Recovery -27% Improvement Relative Risk Recovery (b) -50% Viral clearance 0% c19early.org/p Zarabanda et al. Povidone-Iodine for COVID-19 RCT LATE Is late treatment with povidone-iodine beneficial for COVID-19? RCT 24 patients in the USA Trial compares with saline spray, results vs. placebo may differ Trial underpowered to detect differences Zarabanda et al., Laryngoscope, doi:10.1002/lary.29935 Favors povidone-iodine Favors saline spray
[Zarabanda] Very late treatment (7 days from onset) RCT comparing 11 & 13 PVP-I (0.5% and 2%), and 11 saline spray patients in the USA, showing no significant differences. There was no control group (saline is likely not a placebo, showing efficacy in other trials). There are large unadjusted differences between groups, e.g. 7.1 days from onset for PVP-I versus 4.8 for saline. Baseline Ct was higher for PVP-I, providing less room for improvement. Authors note that they cannot determine if earlier use is more beneficial.
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 povidone-iodine, 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 povidone-iodine 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 (3.11.3) with scipy (1.10.1), pythonmeta (1.26), numpy (1.24.3), statsmodels (0.14.0), and plotly (5.14.1).
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 the bottom of this page.
A summary of study results is below. Please submit updates and corrections at https://c19early.org/pmeta.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.
[Arefin], 5/18/2021, Randomized Controlled Trial, Bangladesh, peer-reviewed, 9 authors, trial NCT04549376 (history). risk of no viral clearance, 78.9% lower, RR 0.21, p = 0.02, treatment 4 of 27 (14.8%), control 19 of 27 (70.4%), NNT 1.8, 0.6% nasal irrigation.
risk of no viral clearance, 89.5% lower, RR 0.11, p < 0.001, treatment 2 of 27 (7.4%), control 19 of 27 (70.4%), NNT 1.6, 0.5% nasal irrigation.
risk of no viral clearance, 52.6% lower, RR 0.47, p = 0.006, treatment 9 of 27 (33.3%), control 19 of 27 (70.4%), NNT 2.7, 0.4% nasal irrigation.
risk of no viral clearance, 80.0% lower, RR 0.20, p < 0.001, treatment 5 of 27 (18.5%), control 25 of 27 (92.6%), NNT 1.4, 0.6% nasal spray.
risk of no viral clearance, 64.0% lower, RR 0.36, p < 0.001, treatment 9 of 27 (33.3%), control 25 of 27 (92.6%), NNT 1.7, 0.5% nasal spray.
risk of no viral clearance, 73.6% lower, RR 0.26, p < 0.001, treatment 29 of 135 (21.5%), control 44 of 54 (81.5%), NNT 1.7, all treatment vs. all control.
[Baxter], 8/17/2021, Randomized Controlled Trial, USA, peer-reviewed, 12 authors, study period 24 September, 2020 - 21 December, 2020, average treatment delay 4.0 days, this trial compares with another treatment - results may be better when compared to placebo, trial NCT04559035 (history). risk of hospitalization, 213.5% higher, RR 3.14, p = 0.47, treatment 1 of 37 (2.7%), control 0 of 42 (0.0%), continuity correction due to zero event (with reciprocal of the contrasting arm), preprint result reversed.
risk of no recovery, 56.8% lower, RR 0.43, p = 0.03, treatment 6 of 27 (22.2%), control 18 of 35 (51.4%), NNT 3.4, preprint V2.
risk of transmission, 13.6% lower, RR 0.86, p = 1.00, treatment 4 of 27 (14.8%), control 6 of 35 (17.1%), NNT 43, preprint V2.
[Choudhury], 12/3/2020, Randomized Controlled Trial, Bangladesh, peer-reviewed, 6 authors. risk of death, 88.2% lower, RR 0.12, p < 0.001, treatment 2 of 303 (0.7%), control 17 of 303 (5.6%), NNT 20.
risk of hospitalization, 84.4% lower, RR 0.16, p < 0.001, treatment 12 of 303 (4.0%), control 77 of 303 (25.4%), NNT 4.7.
risk of no viral clearance, 96.2% lower, RR 0.04, p < 0.001, treatment 8 of 303 (2.6%), control 213 of 303 (70.3%), NNT 1.5, day 7.
[Elsersy], 4/19/2022, Double Blind Randomized Controlled Trial, placebo-controlled, Egypt, peer-reviewed, 8 authors, study period March 2021 - July 2021, this trial uses multiple treatments in the treatment arm (combined with glycyrrhizic acid) - results of individual treatments may vary, trial PACTR202101875903773. risk of hospitalization, 90.9% lower, RR 0.09, p = 0.06, treatment 0 of 100 (0.0%), control 5 of 100 (5.0%), NNT 20, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm).
recovery time, 14.6% lower, relative time 0.85, p = 0.008, treatment mean 7.6 (±2.0) n=100, control mean 8.9 (±2.0) n=100.
recovery time, 49.1% lower, relative time 0.51, p < 0.001, treatment mean 5.6 (±1.3) n=100, control mean 11.0 (±3.4) n=100, smell.
recovery time, 48.2% lower, relative time 0.52, p < 0.001, treatment mean 5.7 (±1.0) n=100, control mean 11.0 (±4.0) n=100, taste.
risk of no viral clearance, 67.7% lower, RR 0.32, p < 0.001, treatment 21 of 100 (21.0%), control 65 of 100 (65.0%), NNT 2.3, mid-recovery, day 7.
risk of no viral clearance, 90.0% lower, RR 0.10, p = 0.010, treatment 1 of 100 (1.0%), control 10 of 100 (10.0%), NNT 11, day 10.
risk of no viral clearance, 29.3% lower, RR 0.71, p < 0.001, treatment 70 of 100 (70.0%), control 99 of 100 (99.0%), NNT 3.4, day 4.
risk of transmission, 91.9% lower, RR 0.08, p < 0.001, treatment 12 of 194 (6.2%), control 173 of 227 (76.2%), NNT 1.4, symptomatic.
risk of transmission, 94.0% lower, RR 0.06, p < 0.001, treatment 8 of 194 (4.1%), control 157 of 227 (69.2%), NNT 1.5, PCR+.
[Elzein], 3/17/2021, Double Blind Randomized Controlled Trial, Lebanon, peer-reviewed, 7 authors. relative improvement in Ct value, 88.8% better, RR 0.11, p < 0.05, treatment 25, control 9.
[Guenezan], 2/4/2021, Randomized Controlled Trial, France, peer-reviewed, 7 authors. relative improvement in viral titer reduction between baseline and day 1, 63.2% better, RR 0.37, p = 0.25, treatment 12, control 12.
[Karaaltin], 10/26/2022, Randomized Controlled Trial, Turkey, preprint, 16 authors, study period September 2021 - October 2021. viral load, 83.1% lower, relative load 0.17, p = 0.007, treatment 30, control 30, relative change in viral load, PVP-I vs. control, day 5.
viral load, 85.5% lower, relative load 0.14, p = 0.001, treatment 30, control 30, relative change in viral load, PVP-I + HANI vs. control, day 5.
viral load, 82.1% lower, relative load 0.18, p = 0.14, treatment 30, control 30, relative change in viral load, PVP-I vs. control, day 3.
viral load, 90.8% lower, relative load 0.09, p < 0.001, treatment 30, control 30, relative change in viral load, PVP-I + HANI vs. control, day 3.
[Matsuyama], 11/28/2022, Randomized Controlled Trial, Japan, peer-reviewed, mean age 45.1, 4 authors, study period 30 November, 2020 - 17 March, 2021, trial jRCT1051200078. viral infectivity, 69.0% lower, RR 0.31, p = 0.03, treatment 4 of 139 (2.9%), control 13 of 140 (9.3%), NNT 16, viral infectivity from culture, day 5.
risk of no viral clearance, 38.0% lower, HR 0.62, p = 0.01, treatment 139, control 140, inverted to make HR<1 favor treatment, day 5, primary outcome.
[Mohamed], 9/9/2020, Randomized Controlled Trial, Malaysia, preprint, 16 authors. risk of no viral clearance, 85.7% lower, RR 0.14, p = 0.17, treatment 0 of 5 (0.0%), control 3 of 5 (60.0%), NNT 1.7, relative risk is not 0 because of continuity correction due to zero events (with reciprocal of the contrasting arm), day 12.
[Natto], 7/29/2022, Randomized Controlled Trial, Saudi Arabia, peer-reviewed, 7 authors, this trial compares with another treatment - results may be better when compared to placebo. risk of viral load, 74.0% lower, RR 0.26, p = 0.27, treatment 12, control 12, relative improvement in Ct value, both genes combined.
risk of viral load, 96.2% lower, RR 0.04, p = 0.12, treatment mean 4.43 (±4.78) n=12, control mean 0.17 (±7.67) n=12, relative improvement in Ct value, E gene.
risk of viral load, 44.4% lower, RR 0.56, p = 0.60, treatment mean 3.33 (±5.6) n=12, control mean 1.85 (±7.68) n=12, relative improvement in Ct value, S gene.
[Pablo-Marcos], 10/25/2021, prospective, Spain, peer-reviewed, mean age 43.0, 6 authors, study period May 2020 - November 2020, excluded in exclusion analyses: unadjusted results with no group details. relative viral load, 29.2% better, RR 0.71, p = 0.40, treatment 31, control 40, 3rd PCR (mid-recovery).
relative viral load, 9.1% better, RR 0.91, p = 0.91, treatment 31, control 40, 4th PCR (most patients recovered).
[Sevinç Gül], 7/29/2022, Randomized Controlled Trial, Turkey, peer-reviewed, 4 authors, this trial compares with another treatment - results may be better when compared to placebo. risk of viral load, 99.5% lower, RR 0.005, p = 0.37, treatment mean 1.85 (±7.06) n=21, control mean 0.01 (±5.89) n=20, relative improvement in Ct value.
[Sirijatuphat], 8/22/2022, prospective, Thailand, preprint, median age 34.0, 4 authors, study period 15 February, 2021 - 15 March, 2021, trial TCTR20210125002. viral load, 33.3% lower, relative load 0.67, p = 0.58, after median 2560.0 IQR 17790.0 n=12, before median 3840.0 IQR 9600.0 n=12, before values 640.0 640.0 40960.0 2560.0 10240.0 10240.0 640.0 2560.0 10240.0 5120.0 40960.0 640.0, after values 10.0 40.0 2560.0 40960.0 5120.0 1280.0 160.0 2560.0 40960.0 40960.0 10240.0 40.0, relative median viral titer, 3 min, left vs. baseline, Mann-Whitney, Table 3.
viral load, 87.5% lower, relative load 0.12, p = 0.04, after median 480.0 IQR 4340.0 n=12, before median 3840.0 IQR 9600.0 n=12, before values 640.0 640.0 40960.0 2560.0 10240.0 10240.0 640.0 2560.0 10240.0 5120.0 40960.0 640.0, after values 80.0 160.0 10240.0 320.0 320.0 10240.0 40.0 640.0 640.0 40960.0 2560.0 0.0, relative median viral titer, 3 min, right vs. baseline, Mann-Whitney, Table 3.
viral load, 83.3% lower, relative load 0.17, p = 0.11, after median 640.0 IQR 6240.0 n=12, before median 3840.0 IQR 9600.0 n=12, before values 640.0 640.0 40960.0 2560.0 10240.0 10240.0 640.0 2560.0 10240.0 5120.0 40960.0 640.0, after values 160.0 10.0 10240.0 640.0 160.0 1280.0 320.0 640.0 5120.0 40960.0 20480.0 0.0, relative median viral titer, 4 hours, right vs. baseline, Mann-Whitney, Table 3.
[Sulistyani], 3/15/2022, Single Blind Randomized Controlled Trial, Indonesia, peer-reviewed, 9 authors, study period July 2021 - September 2021. relative improvement in Ct value, 6.3% better, RR 0.94, p = 0.74, treatment mean 12.905 (±5.96) n=15, control mean 12.088 (±7.38) n=15, 1% PVP-I vs. water, day 5.
relative improvement in Ct value, 11.3% better, RR 0.89, p = 0.54, treatment mean 13.628 (±6.28) n=15, control mean 12.088 (±7.38) n=15, 0.5% PVP-I vs. water, day 5.
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.
risk of no viral clearance, 31.2% lower, RR 0.69, p = 0.26, treatment 5 of 8 (62.5%), control 10 of 11 (90.9%), NNT 3.5, T2.
risk of no viral clearance, 58.7% lower, RR 0.41, p = 0.04, treatment 3 of 8 (37.5%), control 10 of 11 (90.9%), NNT 1.9, T1.
[Ferrer], 12/22/2021, Randomized Controlled Trial, Spain, peer-reviewed, 19 authors. relative decrease in log viral load, 34.0% better, RR 0.66, p = 0.82, treatment 9, control 12, calculated from Supplementary Table 1.
[Jamir], 12/13/2021, retrospective, India, peer-reviewed, 6 authors, study period June 2020 - October 2020. risk of death, 57.0% lower, HR 0.43, p < 0.001, treatment 39 of 163 (23.9%), control 62 of 103 (60.2%), NNT 2.8, adjusted per study, multivariable, Cox proportional hazards.
[Seneviratne], 12/14/2020, Randomized Controlled Trial, Singapore, peer-reviewed, 12 authors. relative fold change, 32.9% better, RR 0.67, p < 0.01, treatment 4, control 2, PVP-I vs. water, 6 hours.
[Zarabanda], 11/1/2021, Randomized Controlled Trial, USA, peer-reviewed, 13 authors, average treatment delay 7.0 days, this trial compares with another treatment - results may be better when compared to placebo. risk of no recovery, 26.9% higher, RR 1.27, p = 1.00, treatment 3 of 13 (23.1%), control 2 of 11 (18.2%), 2%.
risk of no recovery, 50.0% higher, RR 1.50, p = 1.00, treatment 3 of 11 (27.3%), control 2 of 11 (18.2%), 0.5%.
risk of no viral clearance, no change, RR 1.00, p = 1.00, treatment 2 of 7 (28.6%), control 2 of 7 (28.6%), day 5, minus strand PCR.
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.
[Seet], 4/14/2021, Cluster Randomized Controlled Trial, Singapore, peer-reviewed, 15 authors, this trial compares with another treatment - results may be better when compared to placebo, trial NCT04446104 (history). risk of symptomatic case, 44.7% lower, RR 0.55, p = 0.002, treatment 42 of 735 (5.7%), control 64 of 619 (10.3%), NNT 22.
risk of case, 31.1% lower, RR 0.69, p = 0.01, treatment 338 of 735 (46.0%), control 433 of 619 (70.0%), NNT 4.2, adjusted per study, odds ratio converted to relative risk, model 6.
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