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Proton Pump Inhibitors for COVID-19: real-time meta analysis of 39 studies

@CovidAnalysis, December 2024, Version 26V26
 
0 0.5 1 1.5+ All studies -46% 39 222,688 Improvement, Studies, Patients Relative Risk Mortality -40% 20 56,361 Ventilation -14% 5 25,841 ICU admission -15% 7 25,417 Hospitalization -9% 10 143,458 Cases 2% 13 212,848 Viral clearance 12% 2 4,788 Peer-reviewed -47% 37 222,341 Prophylaxis -34% 36 216,155 Late -288% 3 6,533 Proton Pump Inhibitors for COVID-19 c19early.org December 2024 after exclusions FavorsPPIs Favorscontrol
Abstract
Meta analysis shows 40% [17‑67%] higher mortality, and pooled analysis using the most serious outcome reported shows 46% [27‑67%] higher risk.
0 0.5 1 1.5+ All studies -46% 39 222,688 Improvement, Studies, Patients Relative Risk Mortality -40% 20 56,361 Ventilation -14% 5 25,841 ICU admission -15% 7 25,417 Hospitalization -9% 10 143,458 Cases 2% 13 212,848 Viral clearance 12% 2 4,788 Peer-reviewed -47% 37 222,341 Prophylaxis -34% 36 216,155 Late -288% 3 6,533 Proton Pump Inhibitors for COVID-19 c19early.org December 2024 after exclusions FavorsPPIs Favorscontrol
Potential mechanisms of harm include increased expression of ACE2, impaired immune responses due to gut microbiome changes, reduced antibacterial activity of neutrophils, easier passage of SARS-CoV-2 through the gastrointestinal tract due to reduced stomach acid, increased risk of secondary bacterial infections, degraded cellular defense mechanisms due to impaired lysosomal function, reduced absorption of nutrients critical for the immune system, potential interactions with COVID-19 medications, lung microbiome alterations, increased oxidative stress, impact on vitamin C and iron levels, potential effects on interferon responses, changes in coagulation factors, hypochlorhydria-induced hypergastrinemia, potential increased vulnerability to gastrointestinal pathogens, and delayed gastric emptying which may impair pharmacokinetics of COVID-19 medications.
All data and sources to reproduce this analysis are in the appendix.
8 other meta analyses show significant harm with proton pump inhibitors for mortality1-3, severity1,2,4-8, and cases2.
Evolution of COVID-19 clinical evidence Meta analysis results over time Proton Pump Inhibitors p=0.00000012 Vitamin D p<0.0000000001 2020 2021 2022 2023 2024 Lowerrisk Higherrisk c19early.org December 2024 100% 50% 0% -50%
Proton Pump Inhibitors for COVID-19 — Highlights
1st treatment shown harmful in September 2020, now with p = 0.00000012 from 39 studies.
Real-time updates and corrections with a consistent protocol for 109 treatments. Outcome specific analysis and combined evidence from all studies including treatment delay, a primary confounding factor.
A
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Zhou (PSM) -165% 2.65 [1.75-4.00] severe case 151/524 173/2,620 Improvement, RR [CI] Treatment Control Yao -600% 7.00 [4.57-10.7] severe case 694 (n) 2,330 (n) Liwang -204% 3.04 [1.22-7.60] death 216 (n) 149 (n) LD​1 Tau​2 = 0.34, I​2 = 87.9%, p = 0.00029 Late treatment -288% 3.88 [1.87-8.04] 151/1,434 173/5,099 288% higher risk Yan -240% 3.40 [2.00-5.79] severe case 16/32 20/136 Improvement, RR [CI] Treatment Control Blanc 56% 0.44 [0.23-0.82] cases 63 (n) 116 (n) Freedberg (PSM) -34% 1.34 [1.06-1.69] death/int. 8/84 332/1,536 Argenziano 1% 0.99 [0.73-1.34] ICU 38/163 198/837 Vila‐Corcoles -9% 1.09 [0.80-1.50] cases 11,807 (n) 23,129 (n) Lee (PSM) -79% 1.79 [1.30-3.10] severe case 267 (n) 267 (n) Luxenburger -248% 3.48 [1.29-9.39] death 12/62 5/90 Almario -179% 2.79 [1.65-4.70] cases García-Menaya -228% 3.28 [1.22-9.94] death 15/54 5/59 Mas Romero 26% 0.74 [0.38-1.45] death 11/82 21/116 Fan (PSM) -17% 1.17 [0.65-2.90] death n/a n/a McKeigue -44% 1.44 [1.31-1.58] severe case case control Zhang (PSM) -11% 1.11 [0.92-1.33] hosp. time 29 (n) 29 (n) Elmunzer 13% 0.87 [0.66-1.14] death 417 (n) 1,429 (n) Morán Blanco 31% 0.69 [0.36-1.33] symp. case 12/48 13/36 Cheung 25% 0.75 [0.07-6.00] severe case 4 (n) 948 (n) Liu -127% 2.27 [1.64-3.13] death 68/227 53/459 Jimenez -124% 2.24 [1.80-2.80] death 1,357 (all patients) Israelsen (PSM) 5% 0.95 [0.74-1.22] death 166/3,955 189/3,955 Shah 3% 0.97 [0.85-1.10] death 6,262 (n) 8,696 (n) Ramachandran -92% 1.92 [1.11-2.99] death 16/46 40/249 Shafrir (PSM) -47% 1.47 [0.77-2.80] severe case 22/655 15/655 Wu (PSW) -197% 2.97 [1.63-5.42] death 1,046 (n) 3,588 (n) Shupp 19% 0.81 [0.54-1.22] death 448 (n) 2,048 (n) Kodvanj 7% 0.93 [0.85-1.02] death Kim (PSM) -28% 1.28 [0.48-3.37] death 9/437 7/437 Shokri -81% 1.81 [1.01-3.25] severe case 121 (n) 549 (n) Elkanzi -17% 1.17 [0.76-1.81] death 36/159 29/150 Patil -48% 1.48 [1.32-1.66] death 4,566 (n) 15,349 (n) Gramont (PSW) -59% 1.59 [1.18-2.14] severe case 424 (n) 410 (n) Cheung -49% 1.49 [1.13-1.98] death population-based cohort Hirsch 15% 0.85 [0.64-1.13] hosp. 116,209 (all patients) Al-Momani -100% 2.00 [0.46-8.71] death 3/69 4/184 Zeng -46% 1.46 [1.05-2.03] death population-based cohort Pinto -57% 1.57 [0.90-2.74] hosp. 15/104 38/414 Bianconi -37% 1.37 [0.95-1.97] death/ICU 447 (n) 640 (n) Tau​2 = 0.09, I​2 = 83.8%, p < 0.0001 Prophylaxis -34% 1.34 [1.18-1.51] 447/32,078 969/66,511 34% higher risk All studies -46% 1.46 [1.27-1.67] 598/33,512 1,142/71,610 46% higher risk 39 proton pump inhibitor COVID-19 studies c19early.org December 2024 Tau​2 = 0.13, I​2 = 88.7%, p < 0.0001 Effect extraction pre-specified(most serious outcome, see appendix) 1 LD: comparison with low dose treatment Favors PPIs Favors control
0 0.25 0.5 0.75 1 1.25 1.5 1.75 2+ Zhou (PSM) -165% severe case Improvement Relative Risk [CI] Yao -600% severe case Liwang -204% death LD​1 Tau​2 = 0.34, I​2 = 87.9%, p = 0.00029 Late treatment -288% 288% higher risk Yan -240% severe case Blanc 56% case Freedberg (PSM) -34% death/intubation Argenziano 1% ICU admission Vila‐Corcoles -9% case Lee (PSM) -79% severe case Luxenburger -248% death Almario -179% case García-Menaya -228% death Mas Romero 26% death Fan (PSM) -17% death McKeigue -44% severe case Zhang (PSM) -11% hospitalization Elmunzer 13% death Morán Blanco 31% symp. case Cheung 25% severe case Liu -127% death Jimenez -124% death Israelsen (PSM) 5% death Shah 3% death Ramachandran -92% death Shafrir (PSM) -47% severe case Wu (PSW) -197% death Shupp 19% death Kodvanj 7% death Kim (PSM) -28% death Shokri -81% severe case Elkanzi -17% death Patil -48% death Gramont (PSW) -59% severe case Cheung -49% death Hirsch 15% hospitalization Al-Momani -100% death Zeng -46% death Pinto -57% hospitalization Bianconi -37% death/ICU Tau​2 = 0.09, I​2 = 83.8%, p < 0.0001 Prophylaxis -34% 34% higher risk All studies -46% 46% higher risk 39 proton pump inhibitor C19 studies c19early.org December 2024 Tau​2 = 0.13, I​2 = 88.7%, p < 0.0001 Protocol pre-specified/rotate for details1 LD: comparison with low dose treatment Favors PPIs Favors control
B
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Figure 1. A. Random effects meta-analysis. This plot shows pooled effects, see the specific outcome analyses for individual outcomes. Analysis validating pooled outcomes for COVID-19 can be found below. Effect extraction is pre-specified, using the most serious outcome reported. For details see the appendix. B. Timeline of results in proton pump inhibitor studies. The marked dates indicate the time when a harmful effect was identified with statistical significance from ≥3 studies for pooled outcomes and one or more specific outcome. Harm based on specific outcomes was delayed by 11.1 months, compared to using pooled outcomes.
Potential mechanisms of harm include increased expression of ACE2, impaired immune responses due to gut microbiome changes, reduced antibacterial activity of neutrophils, easier passage of SARS-CoV-2 through the gastrointestinal tract due to reduced stomach acid, increased risk of secondary bacterial infections, degraded cellular defense mechanisms due to impaired lysosomal function, reduced absorption of nutrients critical for the immune system, potential interactions with COVID-19 medications, lung microbiome alterations, increased oxidative stress, impact on vitamin C and iron levels, potential effects on interferon responses, changes in coagulation factors, hypochlorhydria-induced hypergastrinemia, potential increased vulnerability to gastrointestinal pathogens, and delayed gastric emptying which may impair pharmacokinetics of COVID-19 medications.
Studies have shown increased risk with proton pump inhibitors for serious infections9, spontaneous bacterial peritonitis10, C. diff infection11,12, bacterial infections13, and influenza14.
We analyze all significant controlled studies of Proton Pump Inhibitors 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, and higher quality studies.
Figure 2 shows stages of possible treatment for COVID-19. Prophylaxis refers to regularly taking medication before becoming sick, in order to prevent or minimize infection. Early Treatment refers to treatment immediately or soon after symptoms appear, while Late Treatment refers to more delayed treatment.
regular treatment to prevent or minimize infectionstreat immediately on symptoms or shortly thereafterlate stage after disease progressionexposed to virusEarly TreatmentProphylaxisTreatment delayLate Treatment
Figure 2. Treatment stages.
Table 1 summarizes the results for all stages combined, for peer-reviewed studies, after exclusions, and for specific outcomes. Table 2 shows results by treatment stage. Figure 3 plots individual results by treatment stage. Figure 4, 5, 6, 7, 8, 9, 10, 11, 12, and 13 show forest plots for random effects meta-analysis of all studies with pooled effects, mortality results, ventilation, ICU admission, hospitalization, progression, recovery, cases, viral clearance, and peer reviewed studies.
Table 1. Random effects meta-analysis for all stages combined, for peer-reviewed studies, after exclusions, and for specific outcomes. Results show the percentage improvement with treatment and the 95% confidence interval. * p<0.05  ** p<0.01  *** p<0.001  **** p<0.0001.
Improvement Studies Patients Authors
All studies-46% [-67‑-27%]
****
39 222,688 541
After exclusions-44% [-66‑-25%]
****
37 221,500 531
Peer-reviewed studiesPeer-reviewed-47% [-68‑-28%]
****
37 222,341 502
Mortality-40% [-67‑-17%]
***
20 56,361 310
VentilationVent.-14% [-32‑1%]5 25,841 157
ICU admissionICU-15% [-30‑-1%]
*
7 25,417 94
HospitalizationHosp.-9% [-16‑-3%]
**
10 143,458 109
Cases2% [-6‑10%]13 212,848 134
Viral12% [-49‑48%]2 4,788 14
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<0.05  ** p<0.01  *** p<0.001  **** p<0.0001.
Late treatment Prophylaxis
All studies-288% [-704‑-87%]
***
-34% [-51‑-18%]
****
After exclusions-288% [-704‑-87%]
***
-32% [-49‑-16%]
****
Peer-reviewed studiesPeer-reviewed-288% [-704‑-87%]
***
-33% [-50‑-18%]
****
Mortality-204% [-660‑-22%]
*
-37% [-64‑-14%]
***
VentilationVent.-14% [-32‑1%]
ICU admissionICU-15% [-30‑-1%]
*
HospitalizationHosp.-9% [-16‑-3%]
**
Cases2% [-6‑10%]
Viral12% [-49‑48%]
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Figure 3. Scatter plot showing the most serious outcome in all studies, and for studies within each stage. Diamonds shows the results of random effects meta-analysis.
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Figure 4. Random effects meta-analysis for all studies. This plot shows pooled effects, see the specific outcome analyses for individual outcomes. Analysis validating pooled outcomes for COVID-19 can be found below. Effect extraction is pre-specified, using the most serious outcome reported. For details see the appendix.
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Figure 5. Random effects meta-analysis for mortality results.
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Figure 6. Random effects meta-analysis for ventilation.
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Figure 7. Random effects meta-analysis for ICU admission.
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Figure 8. Random effects meta-analysis for hospitalization.
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Figure 9. Random effects meta-analysis for progression.
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Figure 10. Random effects meta-analysis for recovery.
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Figure 11. Random effects meta-analysis for cases.
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Figure 12. Random effects meta-analysis for viral clearance.
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Figure 13. Random effects meta-analysis for peer reviewed studies. Effect extraction is pre-specified, using the most serious outcome reported, see the appendix for details. Analysis validating pooled outcomes for COVID-19 can be found below. Zeraatkar et al. analyze 356 COVID-19 trials, finding no significant evidence that preprint results are inconsistent with peer-reviewed studies. They also show extremely long peer-review delays, with a median of 6 months to journal publication. A six month delay was equivalent to around 1.5 million deaths during the first two years of the pandemic. Authors recommend using preprint evidence, with appropriate checks for potential falsified data, which provides higher certainty much earlier. Davidson et al. also showed no important difference between meta analysis results of preprints and peer-reviewed publications for COVID-19, based on 37 meta analyses including 114 trials.
To avoid bias in the selection of studies, we analyze all non-retracted studies. Here we show the results after excluding studies with major issues likely to alter results, non-standard studies, and studies where very minimal detail is currently available. Our bias evaluation is based on analysis of each study and identifying when there is a significant chance that limitations will substantially change the outcome of the study. We believe this can be more valuable than checklist-based approaches such as Cochrane GRADE, which can be easily influenced by potential bias, may ignore or underemphasize serious issues not captured in the checklists, and may overemphasize issues unlikely to alter outcomes in specific cases (for example certain specifics of randomization with a very large effect size and well-matched baseline characteristics).
The studies excluded are as below. Figure 14 shows a forest plot for random effects meta-analysis of all studies after exclusions.
Luxenburger, unadjusted differences between groups. Excluded results: death, ARDS.
Pinto, unadjusted results with significant baseline differences.
Shokri, potential data issue.
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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. Analysis validating pooled outcomes for COVID-19 can be found below. Effect extraction is pre-specified, using the most serious outcome reported. For details see the appendix.
Heterogeneity in COVID-19 studies arises from many factors including:
The time between infection or the onset of symptoms and treatment may critically affect how well a treatment works. For example an antiviral may be very effective when used early but may not be effective in late stage disease, and may even be harmful. Oseltamivir, for example, is generally only considered effective for influenza when used within 0-36 or 0-48 hours20,21. Baloxavir marboxil studies for influenza also show that treatment delay is critical — Ikematsu et al. report an 86% reduction in cases for post-exposure prophylaxis, Hayden et al. show a 33 hour reduction in the time to alleviation of symptoms for treatment within 24 hours and a reduction of 13 hours for treatment within 24-48 hours, and Kumar et al. report only 2.5 hours improvement for inpatient treatment.
Table 3. Studies of baloxavir marboxil for influenza show that early treatment is more effective.
Treatment delayResult
Post-exposure prophylaxis86% fewer cases22
<24 hours-33 hours symptoms23
24-48 hours-13 hours symptoms23
Inpatients-2.5 hours to improvement24
Figure 15 shows a mixed-effects meta-regression for efficacy as a function of treatment delay in COVID-19 studies from 109 treatments, showing that efficacy declines rapidly with treatment delay. Early treatment is critical for COVID-19.
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Figure 15. Early treatment is more effective. Meta-regression showing efficacy as a function of treatment delay in COVID-19 studies from 109 treatments.
Details of the patient population including age and comorbidities may critically affect how well a treatment works. For example, many COVID-19 studies with relatively young low-comorbidity patients show all patients recovering quickly with or without treatment. In such cases, there is little room for an effective treatment to improve results, for example as in López-Medina et al.
Efficacy may depend critically on the distribution of SARS-CoV-2 variants encountered by patients. Risk varies significantly across variants26, for example the Gamma variant shows significantly different characteristics27-30. Different mechanisms of action may be more or less effective depending on variants, for example the degree to which TMPRSS2 contributes to viral entry can differ across variants31,32.
Effectiveness may depend strongly on the dosage and treatment regimen.
The use of other treatments may significantly affect outcomes, including supplements, other medications, or other interventions such as prone positioning. Treatments may be synergistic33-44, therefore efficacy may depend strongly on combined treatments.
The quality of medications may vary significantly between manufacturers and production batches, which may significantly affect efficacy and safety. Williams et al. analyze ivermectin from 11 different sources, showing highly variable antiparasitic efficacy across different manufacturers. Xu (B) et al. analyze a treatment from two different manufacturers, showing 9 different impurities, with significantly different concentrations for each manufacturer.
Across all studies there is a strong association between different outcomes, for example improved recovery is strongly associated with lower mortality. However, efficacy may differ depending on the effect measured, for example a treatment may be more effective against secondary complications and have minimal effect on viral clearance.
The distribution of studies will alter the outcome of a meta analysis. Consider a simplified example where everything is equal except for the treatment delay, and effectiveness decreases to zero or below with increasing delay. If there are many studies using very late treatment, the outcome may be negative, even though early treatment is very effective. All meta analyses combine heterogeneous studies, varying in population, variants, and potentially all factors above, and therefore may obscure efficacy by including studies where treatment is less effective. Generally, we expect the estimated effect size from meta analysis to be less than that for the optimal case. Looking at all studies is valuable for providing an overview of all research, important to avoid cherry-picking, and informative when a positive result is found despite combining less-optimal situations. However, the resulting estimate does not apply to specific cases such as early treatment in high-risk populations. While we present results for all studies, we also present treatment time and individual outcome analyses, which may be more informative for specific use cases.
This section validates the use of pooled effects for COVID-19, which enables earlier detection of harm, however note that pooled effects are no longer required for proton pump inhibitors as of August 2021. Harm is now known based on specific outcomes. Harm based on specific outcomes was delayed by 11.1 months, compared to using pooled outcomes.
For COVID-19, delay in clinical results translates into additional death and morbidity, as well as additional economic and societal damage. Combining the results of studies reporting different outcomes is required. There may be no mortality in a trial with low-risk patients, however a reduction in severity or improved viral clearance may translate into lower mortality in a high-risk population. Different studies may report lower severity, improved recovery, and lower mortality, and the significance may be very high when combining the results. "The studies reported different outcomes" is not a good reason for disregarding results.
We present both specific outcome and pooled analyses. In order to combine the results of studies reporting different outcomes we use the most serious outcome reported in each study, based on the thesis that improvement in the most serious outcome provides comparable measures of efficacy for a treatment. A critical advantage of this approach is simplicity and transparency. There are many other ways to combine evidence for different outcomes, along with additional evidence such as dose-response relationships, however these increase complexity.
Another way to view pooled analysis is that we are using more of the available information. Logically we should, and do, use additional information. For example dose-response and treatment delay-response relationships provide significant additional evidence of efficacy that is considered when reviewing the evidence for a treatment.
Trials with high-risk patients may be restricted due to ethics for treatments that are known or expected to be effective, and they increase difficulty for recruiting. Using less severe outcomes as a proxy for more serious outcomes allows faster collection of evidence.
For many COVID-19 treatments, a reduction in mortality logically follows from a reduction in hospitalization, which follows from a reduction in symptomatic cases, which follows from a reduction in PCR positivity. We can directly test this for COVID-19.
Analysis of the the association between different outcomes across studies from all 109 treatments we cover confirms the validity of pooled outcome analysis for COVID-19. Figure 16 shows that lower hospitalization is very strongly associated with lower mortality (p < 0.000000000001). Similarly, Figure 17 shows that improved recovery is very strongly associated with lower mortality (p < 0.000000000001). Considering the extremes, Singh et al. show an association between viral clearance and hospitalization or death, with p = 0.003 after excluding one large outlier from a mutagenic treatment, and based on 44 RCTs including 52,384 patients. Figure 18 shows that improved viral clearance is strongly associated with fewer serious outcomes. The association is very similar to Singh et al., with higher confidence due to the larger number of studies. As with Singh et al., the confidence increases when excluding the outlier treatment, from p = 0.00000042 to p = 0.00000002.
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Figure 16. Lower hospitalization is associated with lower mortality, supporting pooled outcome analysis.
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Figure 17. Improved recovery is associated with lower mortality, supporting pooled outcome analysis.
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Figure 16. Improved viral clearance is associated with fewer serious outcomes, supporting pooled outcome analysis.
Currently, 48 of the treatments we analyze show statistically significant efficacy or harm, defined as ≥10% decreased risk or >0% increased risk from ≥3 studies. 89% of these have been confirmed with one or more specific outcomes, with a mean delay of 5.1 months. When restricting to RCTs only, 56% of treatments showing statistically significant efficacy/harm with pooled effects have been confirmed with one or more specific outcomes, with a mean delay of 6.4 months. Figure 19 shows when treatments were found effective during the pandemic. Pooled outcomes often resulted in earlier detection of efficacy.
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Figure 19. The time when studies showed that treatments were effective, defined as statistically significant improvement of ≥10% from ≥3 studies. Pooled results typically show efficacy earlier than specific outcome results. Results from all studies often shows efficacy much earlier than when restricting to RCTs. Results reflect conditions as used in trials to date, these depend on the population treated, treatment delay, and treatment regimen.
Pooled analysis could hide efficacy, for example a treatment that is beneficial for late stage patients but has no effect on viral clearance may show no efficacy if most studies only examine viral clearance. In practice, it is rare for a non-antiviral treatment to report viral clearance and to not report clinical outcomes; and in practice other sources of heterogeneity such as difference in treatment delay is more likely to hide efficacy.
Analysis validates the use of pooled effects and shows significantly faster detection of efficacy on average. However, as with all meta analyses, it is important to review the different studies included. We also present individual outcome analyses, which may be more informative for specific use cases.
Studies have also shown increased risk with proton pump inhibitors for serious infections9, spontaneous bacterial peritonitis10, C. diff infection11,12, bacterial infections13, and influenza14.
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 results48-51. For proton pump inhibitor, there is currently not enough data to evaluate publication bias with high confidence.
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 20 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 < 0.0552-59. 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.
Log Risk Ratio Standard Error 1.406 1.055 0.703 0.352 0 -3 -2 -1 0 1 2 A: Simulated perfect trials p > 0.05 Log Risk Ratio Standard Error 1.433 1.074 0.716 0.358 0 -4 -3 -2 -1 0 1 2 B: Simulated perfect trials with varying treatment delay p < 0.0001
Figure 20. 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. PPI for COVID-19 lack this because they are generally inexpensive and widely available.
Summary statistics from meta analysis necessarily lose information. As with all meta analyses, studies are heterogeneous, with differences in treatment delay, treatment regimen, patient demographics, variants, conflicts of interest, standard of care, and other factors. We provide analyses for specific outcomes and by treatment delay, and we aim to identify key characteristics in the forest plots and summaries. Results should be viewed in the context of study characteristics.
Some analyses classify treatment based on early or late administration, as done here, while others distinguish between mild, moderate, and severe cases. Viral load does not indicate degree of symptoms — for example patients may have a high viral load while being asymptomatic. With regard to treatments that have antiviral properties, timing of treatment is critical — late administration may be less helpful regardless of severity.
Details of treatment delay per patient is often not available. For example, a study may treat 90% of patients relatively early, but the events driving the outcome may come from 10% of patients treated very late. Our 5 day cutoff for early treatment may be too conservative, 5 days may be too late in many cases.
Comparison across treatments is confounded by differences in the studies performed, for example dose, variants, and conflicts of interest. Trials with conflicts of interest may use designs better suited to the preferred outcome.
In some cases, the most serious outcome has very few events, resulting in lower confidence results being used in pooled analysis, however the method is simpler and more transparent. This is less critical as the number of studies increases. Restriction to outcomes with sufficient power may be beneficial in pooled analysis and improve accuracy when there are few studies, however we maintain our pre-specified method to avoid any retrospective changes.
Studies show that combinations of treatments can be highly synergistic and may result in many times greater efficacy than individual treatments alone33-44. Therefore standard of care may be critical and benefits may diminish or disappear if standard of care does not include certain treatments.
This real-time analysis is constantly updated based on submissions. Accuracy benefits from widespread review and submission of updates and corrections from reviewers. Less popular treatments may receive fewer reviews.
No treatment or intervention is 100% available and effective for all current and future variants. Efficacy may vary significantly with different variants and within different populations. All treatments have potential side effects. Propensity to experience side effects may be predicted in advance by qualified physicians. We do not provide medical advice. Before taking any medication, consult a qualified physician who can compare all options, provide personalized advice, and provide details of risks and benefits based on individual medical history and situations.
8 other meta analyses show significant harm with proton pump inhibitors for mortality1-3, severity1,2,4-8, and cases2.
SARS-CoV-2 infection and replication involves a complex interplay of 50+ host and viral proteins and other factors60-65, providing many therapeutic targets. Over 8,000 compounds have been predicted to reduce COVID-19 risk66, either by directly minimizing infection or replication, by supporting immune system function, or by minimizing secondary complications. Figure 21 shows an overview of the results for proton pump inhibitors in the context of multiple COVID-19 treatments, and Figure 22 shows a plot of efficacy vs. cost for COVID-19 treatments.
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Figure 21. Scatter plot showing results within the context of multiple COVID-19 treatments. Diamonds shows the results of random effects meta-analysis. 0.6% of 8,000+ proposed treatments show efficacy67.
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Figure 22. Efficacy vs. cost for COVID-19 treatments.
Meta analysis shows 40% [17‑67%] higher mortality, and pooled analysis using the most serious outcome reported shows 46% [27‑67%] higher risk.
Potential mechanisms of harm include increased expression of ACE2, impaired immune responses due to gut microbiome changes, reduced antibacterial activity of neutrophils, easier passage of SARS-CoV-2 through the gastrointestinal tract due to reduced stomach acid, increased risk of secondary bacterial infections, degraded cellular defense mechanisms due to impaired lysosomal function, reduced absorption of nutrients critical for the immune system, potential interactions with COVID-19 medications, lung microbiome alterations, increased oxidative stress, impact on vitamin C and iron levels, potential effects on interferon responses, changes in coagulation factors, hypochlorhydria-induced hypergastrinemia, potential increased vulnerability to gastrointestinal pathogens, and delayed gastric emptying which may impair pharmacokinetics of COVID-19 medications.
8 other meta analyses show significant harm with proton pump inhibitors for mortality1-3, severity1,2,4-8, and cases2.
Studies have also shown increased risk with proton pump inhibitors for serious infections9, spontaneous bacterial peritonitis10, C. diff infection11,12, bacterial infections13, and influenza14.
Mortality -100% Improvement Relative Risk Ventilation -48% ICU admission -25% PPIs for COVID-19  Al-Momani et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? Retrospective 253 patients in Jordan (May - August 2022) Higher mortality (p=0.39) and ventilation (p=0.54), not sig. c19early.org Al-Momani et al., Annals of Medicine, Jun 2024 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Al-Momani: Retrospective 254 hospitalized COVID-19 patients in Jordan showing higher rates of gastrointestinal symptoms such as abdominal pain and diarrhea with proton pump inhibitor (PPI) use. There were no significant differences for mortality, ventilation, and ICU admission. Authors hypothesize that PPIs may facilitate SARS-CoV-2 survival and invasion in the gastrointestinal tract.
Case, combined -179% Improvement Relative Risk Case, twice daily or less -267% Case, once daily -115% PPIs for COVID-19  Almario et al.  Prophylaxis Do PPIs reduce COVID-19 infections? Retrospective 51,973 patients in the USA (May - June 2020) More cases with PPIs (p=0.00014) c19early.org Almario et al., American J. Gastroente.., Aug 2020 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Almario: Survey of 53,130 individuals with a history of GI symptoms showing increased risk of COVID-19 positivity with proton pump inhibitor (PPI) use, especially twice-daily PPI use. There was a dose-response relationship between PPI use and COVID-19 risk. Those taking PPIs twice daily had 3.67 times higher odds of testing positive compared to those not taking PPIs. The authors hypothesize that PPI-induced hypochlorhydria may impair the body's defense against ingested pathogens like SARS-CoV-2.
ICU admission 1% Improvement Relative Risk Hospitalization -9% PPIs for COVID-19  Argenziano et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? Retrospective 1,000 patients in the USA (March - April 2020) Higher hospitalization with PPIs (p=0.012) c19early.org Argenziano et al., BMJ, May 2020 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Argenziano: Retrospective 1,000 hospitalized COVID-19 patients in New York City showing high rates of acute kidney injury, inpatient dialysis, prolonged intubation times, and length of stay compared to previous cohorts.
Death/ICU -37% Improvement Relative Risk SBI -96% SBS -67% PPIs for COVID-19  Bianconi et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? Retrospective 1,087 patients in Italy Higher death/ICU with PPIs (not stat. sig., p=0.091) c19early.org Bianconi et al., Annals of Medicine, Oct 2024 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Bianconi: Retrospective 1,087 hospitalized COVID-19 patients showing significantly increased risk of secondary bacterial infections (SBIs) and secondary bacterial sepsis (SBS) sepsis with pre-admission proton pump inhibitor (PPI) use. Combined ICU admission/mortality was higher but without statistical significance.
Case 56% Improvement Relative Risk PPIs for COVID-19  Blanc et al.  Prophylaxis Do PPIs reduce COVID-19 infections? Retrospective 179 patients in France (March - April 2020) Fewer cases with PPIs (p=0.0053) c19early.org Blanc et al., Preprints, May 2020 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Blanc: Retrospective 179 elderly patients in France, showing higher risk of COVID-19 cases with acetaminophen use, without statistical significance.
Mortality, all patients -49% Improvement Relative Risk Mortality, 2 dose -54% Mortality, 3 dose 21% Severe case, all patients -36% Severe case, 2 dose -57% Severe case, 3 dose 21% Hospitalization, all patients -20% Hospitalization, 2 dose -20% Hospitalization, 3 dose -21% Case, all patients -9% Case, 2 dose -7% Case, 3 dose -11% PPIs for COVID-19  Cheung et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? Retrospective 439,154 patients in China (February 2021 - March 2022) Higher mortality (p=0.0054) and hospitalization (p=0.00028) c19early.org Cheung et al., J. Gastroenterology and.., May 2024 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Cheung: Retrospective 627,514 patients in Hong Kong showing slightly higher risk of COVID-19 with pre-vaccination proton pump inhibitor (PPI) use in two-dose or three-dose vaccine recipients, and higher risk of hospitalization and severe outcomes only in two-dose recipients.
Severe case 25% Improvement Relative Risk PPIs for COVID-19  Cheung et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? Retrospective 952 patients in China No significant difference in severe cases c19early.org Cheung et al., Gastroenterology, April 2021 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Cheung (B): Retrospective 952 COVID-19 patients in Hong Kong, showing no significant difference in severe disease with famotidine use or PPI use.
Mortality -17% Improvement Relative Risk ICU admission -25% ASA 4 -126% ASA ≥3 -33% Hospitalization time 19% PPIs for COVID-19  Elkanzi et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? Retrospective 309 patients in the United Kingdom Higher mortality (p=0.49) and ICU admission (p=0.053), not sig. c19early.org Elkanzi et al., Academic J. Gastroente.., Nov 2023 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Elkanzi: Retrospective 309 hospitalized patients showing higher risk of severe cases (ASA≥3) with PPI use.
Mortality 13% Improvement Relative Risk Ventilation -2% PPIs for COVID-19  Elmunzer et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? Retrospective 1,846 patients in multiple countries (Apr - Jun 2020) Lower mortality with PPIs (not stat. sig., p=0.31) c19early.org Elmunzer et al., Gastroenterology, Mar 2021 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Elmunzer: Retrospective 1,846 hospitalized COVID-19 patients in North America showing no significant association between preadmission proton pump inhibitor (PPI) use and mechanical ventilation or mortality. Results do not account for the risk of hospitalization based on PPI use.
Mortality, all UGI -17% Improvement Relative Risk Mortality, positive UGI 4% Mortality, all 14% Mortality, all positive 20% Case, UGI -22% Case, all -8% PPIs for COVID-19  Fan et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? PSM retrospective study in the United Kingdom (Mar - Jun 2020) More cases with PPIs (not stat. sig., p=0.15) c19early.org Fan et al., Gastroenterology, January 2021 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Fan: PSM retrospective 9,469 UK Biobank participants tested for COVID-19, showing no significant association between proton pump inhibitor (PPI) or histamine-2 receptor antagonist (H2RA) use and risk of SARS-CoV-2 infection or COVID-19 mortality. Omeprazole was associated with higher risk of cases in patients with upper gastrointestinal diseases. The results for patients with upper gastrointestinal diseases should be more accurate due to reduced confounding and more accurate ascertainment of current use.
Death/intubation -34% Improvement Relative Risk PPIs for COVID-19  Freedberg et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? PSM retrospective 1,620 patients in the USA Higher death/intubation with PPIs (p=0.014) c19early.org Freedberg et al., Gastroenterology, May 2020 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Freedberg: PSM retrospective 1,620 hospitalized patients in the USA, showing higher risk of combined death/intubation with PPI treatment.
Mortality -228% Improvement Relative Risk ICU admission -392% PPIs for COVID-19  García-Menaya et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? Retrospective 113 patients in Spain (March - April 2020) Higher mortality (p=0.008) and ICU admission (p=0.017) c19early.org García-Menaya et al., Frontiers in Pha.., Sep 2020 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
García-Menaya: Retrospective 113 hospitalized COVID-19 patients in Spain showing higher mortality and ICU admission with PPI use.
Severe case -59% Improvement Relative Risk PPIs for COVID-19  Gramont et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? Retrospective 834 patients in France (March 2020 - February 2021) Higher severe cases with PPIs (p=0.002) c19early.org Gramont et al., Age and Ageing, April 2024 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Gramont: Retrospective 834 elderly patients in France showing higher risk of severe COVID-19 with PPI use, and increasing risk with increasing dosage.
Hospitalization 15% Improvement Relative Risk Case 15% PPIs for COVID-19  Hirsch et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? Retrospective 116,209 patients in the USA Fewer cases with PPIs (p=0.002) c19early.org Hirsch et al., The J. Pediatrics, June 2024 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Hirsch: Retrospective 116,209 pediatric patients showing lower risk of COVID-19 with PPI use. There was no significant difference for hospitalization.
Mortality, all patients 5% Improvement Relative Risk Mortality, within cases 12% Ventilation, all patients -8% Ventilation, within cases 0% ICU admission, all patients -5% ICU admission, within c.. 3% Hospitalization, all patients -22% Hospitalization, within c.. -13% Case -8% PPIs for COVID-19  Israelsen et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? Retrospective 322,975 patients in Denmark (February - December 2020) Higher hospitalization (p=0.005) and more cases (p=0.0012) c19early.org Israelsen et al., Clinical Gastroenter.., Sep 2021 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Israelsen: Retrospective 83,224 SARS-CoV-2 cases and 332,799 controls in Denmark showing increased risk of infection and hospital admission with proton pump inhibitor (PPI) use, but no significant association with ICU admission or mortality.
Mortality, both regions co.. -124% Improvement Relative Risk Mortality, north region -118% Mortality, southeast region -133% PPIs for COVID-19  Jimenez et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? Retrospective 1,357 patients in Brazil Higher mortality with PPIs (p<0.000001) c19early.org Jimenez et al., Frontiers in Medicine, Aug 2021 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Jimenez: In Vitro study showing lower pH increased ACE2 expression and viral load on SARS-CoV-2 infection, and retrospective study showing proton pump inhibitor use, which is correlated with low gastric pH-related diseases, was associated with higher mortality.
Mortality -28% Improvement Relative Risk Ventilation -75% ICU admission -150% Progression -21% Case 37% PPIs for COVID-19  Kim et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? PSM retrospective 19,826 patients in South Korea (Jan - Jun 2020) Fewer cases with PPIs (p<0.000001) c19early.org Kim et al., J. Korean Medical Science, Mar 2023 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Kim: PSM retrospective in South Korea, showing lower risk of COVID-19 cases with H2RA (including famotidine) and PPI use, but no significant difference in severe outcomes (results provided for the combined groups only).
Mortality 7% Improvement Relative Risk Hospitalization -4% PPIs for COVID-19  Kodvanj et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? Retrospective 58,529 patients in Croatia (February 2020 - August 2021) No significant difference in outcomes seen c19early.org Kodvanj et al., British J. Clinical Ph.., Oct 2022 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Kodvanj: Retrospective 433,609 COVID-19 patients in Croatia showing no significant difference in mortality or hospitalization risk with proton-pump inhibitor (PPI) use before COVID-19 diagnosis compared to matched controls with PPI-requiring morbidities but no PPI prescriptions. There was significantly higher hospitalization for users with 1-3 prescriptions which authors do not comment on.

The classification of users and possible users may introduce confounding. Users required a PPI prescription, while possible users includes those with ≥3 NSAID prescriptions. Possible users may be OTC PPI users, and may differ significantly in NSAID use. NSAID use per group is not reported, and was not used in adjustments.
Severe case, ICU, mecha.. -79% Improvement Relative Risk Severe case, oxygen, ICU.. -63% Case 10% PPIs for COVID-19  Lee et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? PSM retrospective 27,746 patients in South Korea (Jan - May 2020) Higher severe cases with PPIs (p=0.0086) c19early.org Lee et al., Gut, July 2020 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Lee: PSM retrospective 132,316 patients in South Korea, showing significantly higher risk of severe COVID-19 with PPI use, but no significant difference in cases.
Mortality -127% Improvement Relative Risk PPIs for COVID-19  Liu et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? Retrospective 686 patients in the USA (March - August 2020) Higher mortality with PPIs (p=0.001) c19early.org Liu et al., American J. Gastroenterology, May 2021 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Liu: Prospective study showing COVID- PPI users had higher salivary ACE2 expression, and retrospective analysis of 694 hospitalized COVID-19 patients, showing higher mortality with PPI use.
Mortality -204% Improvement Relative Risk PPIs for COVID-19  Liwang et al.  LATE TREATMENT Is late treatment with PPIs beneficial for COVID-19? Retrospective 365 patients in Indonesia (June - September 2021) Higher mortality with PPIs (p=0.017) c19early.org Liwang et al., J. Of The Indonesian Me.., Aug 2022 Favorshigh dose Favorslow dose 0 0.5 1 1.5 2+
Liwang: Retrospective hospitalized COVID-19 patients in Indonesia showing higher mortality with high dose proton pump inhibitor (PPI) use compared to low dose.
Mortality -248% Improvement Relative Risk ARDS -124% Secondary infection -86% PPIs for COVID-19  Luxenburger et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? Retrospective 152 patients in Germany Higher mortality (p=0.016) and ARDS (p=0.02) with PPIs c19early.org Luxenburger et al., J. Internal Medicine, Jul 2020 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Luxenburger: Retrospective 152 hospitalized COVID-19 patients showing increased risk of secondary infections, ARDS, and mortality with proton pump inhibitor (PPI) use. Authors hypothesize that reduced gastric acid production from PPIs leads to bacterial overgrowth and microaspiration, increasing the risk of secondary lung infections. PPIs may also have immunomodulatory effects.
Mortality 26% Improvement Relative Risk Symp. case -8% PPIs for COVID-19  Mas Romero et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? Retrospective 198 patients in Spain (March - June 2020) Lower mortality with PPIs (not stat. sig., p=0.44) c19early.org Mas Romero et al., PLOS ONE, October 2020 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Mas Romero: Retrospective 1,084 residents from 6 long-term care facilities in Spain showing no signficant difference in cases and mortality with PPI use in unadjusted results.
Severe case -44% Improvement Relative Risk PPIs for COVID-19  McKeigue et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? Retrospective 36,160 patients in Scotland Higher severe cases with PPIs (p<0.000001) c19early.org McKeigue et al., BMC Medicine, February 2021 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
McKeigue: Retrospective 4,251 severe COVID-19 cases and 36,738 matched controls in Scotland showing increased risk of severe COVID-19 with PPI use and antihistamine H1RA use. Adjusted results are only provided for the patients not in care homes (2,357 cases and 33,803 controls).
Symp. case 31% Improvement Relative Risk PPIs for COVID-19  Morán Blanco et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? Retrospective 84 patients in Spain (March - April 2020) Fewer symptomatic cases with PPIs (not stat. sig., p=0.34) c19early.org Morán Blanco et al., Pulmonary Pharmac.., Apr 2021 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Morán Blanco: Retrospective 84 elderly nursing home residents in Spain showing no mortality, hospitalization, or ICU admission with early treatment with antihistamines alone or in combination with azithromycin.
Mortality -48% Improvement Relative Risk ARDS -119% Sepsis -88% Oxygen therapy -73% PPIs for COVID-19  Patil et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? Retrospective 19,915 patients in the USA Higher mortality (p<0.0001) and ARDS (p<0.0001) with PPIs c19early.org Patil et al., Gastro Hep Advances, Dec 2023 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Patil: Retrospective 19,915 hospitalized COVID-19 patients with gastrointestinal symptoms, showing that use of proton pump inhibitors or H2 receptor antagonists was associated with higher mortality, ARDS, sepsis, and ventilator or oxygen requirement among patients
Hospitalization -57% Improvement Relative Risk PPIs for COVID-19  Pinto et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? Retrospective 518 patients in Oman (March - November 2020) Higher hospitalization with PPIs (not stat. sig., p=0.15) c19early.org Pinto et al., Cureus, October 2024 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Pinto: Retrospective 506 outpatients in Oman showing no significant association between proton pump inhibitor (PPI) use and COVID-19 hospitalization in unadjusted results.
Mortality -92% Improvement Relative Risk ARDS -80% PPIs for COVID-19  Ramachandran et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? Retrospective 295 patients in the USA (March - April 2020) Higher mortality (p=0.022) and progression (p=0.015) c19early.org Ramachandran et al., European J. Gastr.., Nov 2021 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Ramachandran: Retrospective 295 hospitalized COVID-19 patients showing higher mortality and acute respiratory distress syndrome (ARDS) with pre-hospitalization proton pump inhibitor (PPI) use. Authors hypothesize that hypochlorhydria caused by PPIs may allow SARS-CoV-2 to more easily infect the gastrointestinal tract.
Severe case -47% Improvement Relative Risk Severe case (b) -16% Case 8% Case (b) 5% PPIs for COVID-19  Shafrir et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? Retrospective 250,655 patients in Israel (March - November 2020) Higher severe cases with PPIs (not stat. sig., p=0.32) c19early.org Shafrir et al., Frontiers in Pharmacol.., Feb 2022 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Shafrir: Retrospective 255,355 adults in Israel showing no significant association between proton pump inhibitor (PPI) use and SARS-CoV-2 positivity or COVID-19 severity.
Mortality 3% Improvement Relative Risk Ventilation -21% ICU admission -13% Hospitalization -5% PPIs for COVID-19  Shah et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? Retrospective 14,958 patients in the USA (January - May 2020) Higher ventilation with PPIs (not stat. sig., p=0.063) c19early.org Shah et al., Gut, October 2021 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Shah: Retrospective 14,958 US veterans who tested positive for SARS-CoV-2, showing no significant difference in severe COVID-19 outcomes (mechanical ventilation, death, ICU admission, or hospitalization) with proton pump inhibitor (PPI) use compared to non-use in a propensity score weighted analysis.
Severe case, all patients -81% Improvement Relative Risk Severe case, short-term -138% Severe case, long-term -30% Mortality -78% unadjusted PPIs for COVID-19  Shokri et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? Retrospective 670 patients in Iran (September 2021 - January 2022) Higher severe cases with PPIs (p=0.046) c19early.org Shokri et al., Annales Pharmaceutiques.., Mar 2023 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Shokri: Retrospective 670 COVID-19 patients in Iran showing significantly higher COVID-19 severity scores and more symptomatic presentation in patients with a history of proton pump inhibitor (PPI) use. Adjusted results are only provided for severity. Several values in Table 4 are likely misreported raising concern for the reliability of the main result.
Mortality 19% Improvement Relative Risk Hospitalization -10% PPIs for COVID-19  Shupp et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? Retrospective 2,496 patients in the USA (March - August 2020) Lower mortality with PPIs (not stat. sig., p=0.32) c19early.org Shupp et al., Scientific Reports, May 2022 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Shupp: Retrospective 2,594 COVID-19 patients in the United States showing no significant association between proton pump inhibitor (PPI) use and COVID-19 severity, including need for hospitalization or 30-day mortality.

There was increasing mortality with increasing PPI use with 14%, 20%, and 27% mortality for low, standard, and high use, without statistical significance.
Case -9% Improvement Relative Risk PPIs for COVID-19  Vila‐Corcoles et al.  Prophylaxis Do PPIs reduce COVID-19 infections? Retrospective 34,936 patients in Spain (March - April 2020) No significant difference in cases c19early.org Vila‐Corcoles et al., The J. Clinical .., Jul 2020 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Vila‐Corcoles: Retrospective 34,936 hypertensive outpatients in Spain showing no significant difference in COVID-19 cases with PPIs and antihistamine H1RAs.
Mortality -197% Improvement Relative Risk Viral clearance -10% PPIs for COVID-19  Wu et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? Retrospective 4,634 patients in China Higher mortality (p=0.0004) and worse viral clearance (p=0.024) c19early.org Wu et al., J. Global Health, February 2022 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Wu: Retrospective 4,634 hospitalized COVID-19 patients in China, showing higher mortality and slower viral clearance with proton pump inhibitor (PPI) use. Authors hypothesize that PPIs may increase susceptibility to COVID-19 by increasing ACE2 expression.
Severe case -240% Improvement Relative Risk PPIs for COVID-19  Yan et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? Retrospective 168 patients in China (January - March 2020) Higher severe cases with PPIs (p=0.000052) c19early.org Yan et al., medRxiv, March 2020 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Yan (B): Retrospective 168 hospitalized COVID-19 patients in China showing higher risk of severe cases with acid suppression drugs.
Severe case -600% Improvement Relative Risk Severe case, intravenous -2501% Severe case, oral -95% PPIs for COVID-19  Yao et al.  LATE TREATMENT Is late treatment with PPIs beneficial for COVID-19? Retrospective 3,024 patients in China (February - April 2020) Higher severe cases with PPIs (p<0.000001) c19early.org Yao et al., Therapeutic Advances in Ga.., Jan 2022 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Yao: Retrospective 3,024 hospitalized COVID-19 patients in China showing increased risk of the composite outcome of ICU admission, mechanical ventilation, or death with proton pump inhibitor (PPI) use. Intravenous administration was significantly worse than oral. Authors hypothesize that PPIs may lead to worse COVID-19 outcomes by increasing the risk of secondary infections, cardiac damage, renal damage, and liver complications.
Mortality -46% Improvement Relative Risk Severe case -33% Case -8% PPIs for COVID-19  Zeng et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? Retrospective 160,923 patients in the United Kingdom (Jan 2020 - Sep 2021) Higher mortality (p=0.024) and severe cases (p=0.004) c19early.org Zeng et al., eLife, July 2024 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Zeng: UK Biobank retrospective with 160,923 patients showing increased risks of influenza, pneumonia, COVID-19 severity, and COVID-19 mortality with proton pump inhibitor (PPI) use.
Hospitalization time -11% Improvement Relative Risk Discharge 6% Viral clearance 37% PPIs for COVID-19  Zhang et al.  Prophylaxis Is prophylaxis with PPIs beneficial for COVID-19? Retrospective 154 patients in China (January - March 2020) Improved viral clearance with PPIs (not stat. sig., p=0.053) c19early.org Zhang et al., J. Inflammation Research, Feb 2021 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Zhang: Retrospective 154 hospitalized moderate COVID-19 patients in China showing no significant difference in viral clearance time or hospital stay duration with proton pump inhibitor (PPI) use. There was no association between PPI use and viral clearance or hospital stay duration in univariate or multivariate analysis. The same results were obtained after propensity score matching.
Severe case -165% Improvement Relative Risk PPIs for COVID-19  Zhou et al.  LATE TREATMENT Is late treatment with PPIs beneficial for COVID-19? PSM retrospective 3,144 patients in China (January - August 2020) Higher severe cases with PPIs (p=0.0001) c19early.org Zhou et al., Gut, December 2020 FavorsPPI Favorscontrol 0 0.5 1 1.5 2+
Zhou: Retrospective 4,445 COVID+ patients in China, showing higher risk of combined death/intubation/ICU with famotidine and with PPIs.
We perform ongoing searches of PubMed, medRxiv, Europe PMC, ClinicalTrials.gov, The Cochrane Library, Google Scholar, Research Square, ScienceDirect, Oxford University Press, the reference lists of other studies and meta-analyses, and submissions to the site c19early.org. Search terms are proton pump inhibitor and COVID-19 or SARS-CoV-2. Automated searches are performed twice daily, with all matches reviewed for inclusion. All studies regarding the use of proton pump inhibitor for COVID-19 that report a comparison with a control group are included in the main analysis. Sensitivity analysis is performed, excluding studies with major issues, epidemiological studies, and studies with minimal available information. This is a living analysis and is updated regularly.
We extracted effect sizes and associated data from all studies. If studies report multiple kinds of effects then the most serious outcome is used in pooled analysis, while other outcomes are included in the outcome specific analyses. For example, if effects for mortality and cases are both reported, the effect for mortality is used, this may be different to the effect that a study focused on. If symptomatic results are reported at multiple times, we used the latest time, for example if mortality results are provided at 14 days and 28 days, the results at 28 days have preference. Mortality alone is preferred over combined outcomes. Outcomes with zero events in both arms are not used, the next most serious outcome with one or more events is used. For example, in low-risk populations with no mortality, a reduction in mortality with treatment is not possible, however a reduction in hospitalization, for example, is still valuable. Clinical outcomes are considered more important than viral test status. When basically all patients recover in both treatment and control groups, preference for viral clearance and recovery is given to results mid-recovery where available. After most or all patients have recovered there is little or no room for an effective treatment to do better, however faster recovery is valuable. If only individual symptom data is available, the most serious symptom has priority, for example difficulty breathing or low SpO2 is more important than cough. When results provide an odds ratio, we compute the relative risk when possible, or convert to a relative risk according to103. Reported confidence intervals and p-values were used when available, using adjusted values when provided. If multiple types of adjustments are reported propensity score matching and multivariable regression has preference over propensity score matching or weighting, which has preference over multivariable regression. Adjusted results have preference over unadjusted results for a more serious outcome when the adjustments significantly alter results. When needed, conversion between reported p-values and confidence intervals followed Altman, Altman (B), and Fisher's exact test was used to calculate p-values for event data. If continuity correction for zero values is required, we use the reciprocal of the opposite arm with the sum of the correction factors equal to 1106. Results are expressed with RR < 1.0 favoring treatment, and using the risk of a negative outcome when applicable (for example, the risk of death rather than the risk of survival). If studies only report relative continuous values such as relative times, the ratio of the time for the treatment group versus the time for the control group is used. Calculations are done in Python (3.13.0) with scipy (1.14.1), pythonmeta (1.26), numpy (1.26.4), statsmodels (0.14.4), and plotly (5.24.1).
Forest plots are computed using PythonMeta107 with the DerSimonian and Laird random effects model (the fixed effect assumption is not plausible in this case) and inverse variance weighting. Results are presented with 95% confidence intervals. Heterogeneity among studies was assessed using the I2 statistic. Mixed-effects meta-regression results are computed with R (4.4.0) using the metafor (4.6-0) and rms (6.8-0) packages, and using the most serious sufficiently powered outcome. For all statistical tests, a p-value less than 0.05 was considered statistically significant. Grobid 0.8.0 is used to parse PDF documents.
We have classified studies as early treatment if most patients are not already at a severe stage at the time of treatment (for example based on oxygen status or lung involvement), and treatment started within 5 days of the onset of symptoms. If studies contain a mix of early treatment and late treatment patients, we consider the treatment time of patients contributing most to the events (for example, consider a study where most patients are treated early but late treatment patients are included, and all mortality events were observed with late treatment patients). We note that a shorter time may be preferable. Antivirals are typically only considered effective when used within a shorter timeframe, for example 0-36 or 0-48 hours for oseltamivir, with longer delays not being effective20,21.
We received no funding, this research is done in our spare time. We have no affiliations with any pharmaceutical companies or political parties.
A summary of study results is below. Please submit updates and corrections at the bottom of this page.
A summary of study results is below. Please submit updates and corrections at https://c19early.org/ppimeta.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.
Liwang, 8/3/2022, retrospective, Indonesia, peer-reviewed, median age 55.0, 4 authors, study period June 2021 - September 2021. risk of death, 204.0% higher, OR 3.04, p = 0.02, treatment 216, control 149, adjusted per study, multivariable, RR approximated with OR.
Yao, 1/31/2022, retrospective, China, peer-reviewed, median age 60.0, 17 authors, study period February 2020 - April 2020. risk of severe case, 600.0% higher, OR 7.00, p < 0.001, treatment 694, control 2,330, adjusted per study, multivariable, RR approximated with OR.
risk of severe case, 2501.0% higher, OR 26.01, p < 0.001, treatment 82, control 2,330, adjusted per study, intravenous, multivariable, RR approximated with OR.
risk of severe case, 95.0% higher, OR 1.95, p = 0.02, treatment 537, control 2,330, oral, RR approximated with OR.
Zhou, 12/4/2020, retrospective, propensity score matching, China, peer-reviewed, 7 authors, study period 1 January, 2020 - 22 August, 2020. risk of severe case, 165.0% higher, HR 2.65, p < 0.001, treatment 151 of 524 (28.8%), control 173 of 2,620 (6.6%), adjusted per study, death/intubation/ICU, propensity score matching, multivariable, Cox proportional hazards.
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.
Al-Momani, 6/30/2024, retrospective, Jordan, peer-reviewed, mean age 59.7, 2 authors, study period 6 May, 2022 - 6 August, 2022. risk of death, 100% higher, RR 2.00, p = 0.39, treatment 3 of 69 (4.3%), control 4 of 184 (2.2%).
risk of mechanical ventilation, 48.1% higher, RR 1.48, p = 0.54, treatment 5 of 69 (7.2%), control 9 of 184 (4.9%).
risk of ICU admission, 25.5% higher, RR 1.25, p = 0.64, treatment 8 of 69 (11.6%), control 17 of 184 (9.2%).
Almario, 8/25/2020, retrospective, USA, peer-reviewed, 3 authors, study period 3 May, 2020 - 24 June, 2020. risk of case, 178.5% higher, RR 2.79, p < 0.001, treatment 7,387, control 44,586, adjusted per study, combined.
risk of case, 267.0% higher, OR 3.67, p < 0.001, treatment 1,157, control 44,586, adjusted per study, twice daily or less, multivariable, RR approximated with OR.
risk of case, 115.0% higher, OR 2.15, p < 0.001, treatment 7,387, control 44,586, adjusted per study, once daily, multivariable, RR approximated with OR.
Argenziano, 5/29/2020, retrospective, USA, peer-reviewed, median age 63.0, 48 authors, study period 1 March, 2020 - 5 April, 2020. risk of ICU admission, 1.5% lower, RR 0.99, p = 1.00, treatment 38 of 163 (23.3%), control 198 of 837 (23.7%), NNT 292.
risk of hospitalization, 9.1% higher, RR 1.09, p = 0.01, treatment 149 of 163 (91.4%), control 701 of 837 (83.8%).
Bianconi, 10/30/2024, retrospective, Italy, peer-reviewed, 11 authors. risk of death/ICU, 37.0% higher, OR 1.37, p = 0.09, treatment 447, control 640, adjusted per study, multivariable, model 5, RR approximated with OR.
risk of miscellaneous, 95.5% higher, OR 1.96, p < 0.001, treatment 447, control 640, adjusted per study, SBI, multivariable, model 5, RR approximated with OR.
risk of miscellaneous, 67.0% higher, OR 1.67, p = 0.002, treatment 447, control 640, adjusted per study, SBS, multivariable, model 5, RR approximated with OR.
Blanc, 5/2/2020, retrospective, France, preprint, mean age 84.1, 22 authors, study period 2 March, 2020 - 8 April, 2020. risk of case, 56.2% lower, OR 0.44, p = 0.005, treatment 63, control 116, RR approximated with OR.
Cheung, 5/5/2024, retrospective, China, peer-reviewed, mean age 65.6, 6 authors, study period 23 February, 2021 - 31 March, 2022. risk of death, 49.5% higher, RR 1.49, p = 0.005, adjusted per study, all patients.
risk of death, 54.5% higher, RR 1.54, p < 0.001, adjusted per study, 2 dose.
risk of death, 20.6% lower, RR 0.79, p = 0.73, treatment 6 of 94,180 (0.0%), control 7 of 95,180 (0.0%), NNT 101656, adjusted per study, 3 dose.
risk of severe case, 36.3% higher, RR 1.36, p = 0.27, adjusted per study, all patients.
risk of severe case, 56.9% higher, RR 1.57, p < 0.001, adjusted per study, 2 dose.
risk of severe case, 21.1% lower, RR 0.79, p = 0.67, treatment 7 of 94,180 (0.0%), control 11 of 95,180 (0.0%), adjusted per study, 3 dose.
risk of hospitalization, 19.7% higher, RR 1.20, p < 0.001, adjusted per study, all patients.
risk of hospitalization, 19.5% higher, RR 1.20, p < 0.001, adjusted per study, 2 dose.
risk of hospitalization, 21.3% higher, RR 1.21, p = 0.17, treatment 132 of 94,180 (0.1%), control 107 of 95,180 (0.1%), adjusted per study, 3 dose.
risk of case, 9.1% higher, RR 1.09, p < 0.001, adjusted per study, all patients.
risk of case, 7.5% higher, RR 1.07, p < 0.001, adjusted per study, 2 dose.
risk of case, 11.4% higher, RR 1.11, p < 0.001, treatment 6,625 of 94,180 (7.0%), control 6,082 of 95,180 (6.4%), adjusted per study, 3 dose.
Cheung (B), 4/30/2021, retrospective, China, peer-reviewed, 3 authors. risk of severe case, 25.0% lower, OR 0.75, p = 0.80, treatment 4, control 948, adjusted per study, multivariable, RR approximated with OR.
Elkanzi, 11/17/2023, retrospective, United Kingdom, peer-reviewed, 8 authors. risk of death, 17.1% higher, RR 1.17, p = 0.49, treatment 36 of 159 (22.6%), control 29 of 150 (19.3%).
risk of ICU admission, 24.9% higher, RR 1.25, p = 0.05, treatment 90 of 159 (56.6%), control 68 of 150 (45.3%).
ASA 4, 126.4% higher, RR 2.26, p = 0.14, treatment 12 of 159 (7.5%), control 5 of 150 (3.3%).
ASA ≥3, 32.6% higher, RR 1.33, p = 0.006, treatment 104 of 159 (65.4%), control 74 of 150 (49.3%).
hospitalization time, 19.0% lower, relative time 0.81, p = 0.18, treatment mean 9.8 (±13.1) n=159, control mean 12.1 (±16.6) n=150.
Elmunzer, 3/31/2021, retrospective, multiple countries, peer-reviewed, 124 authors, study period 15 April, 2020 - 5 June, 2020. risk of death, 13.0% lower, OR 0.87, p = 0.31, treatment 417, control 1,429, adjusted per study, multivariable, RR approximated with OR.
risk of mechanical ventilation, 2.0% higher, OR 1.02, p = 0.89, treatment 417, control 1,429, adjusted per study, multivariable, RR approximated with OR.
Fan, 1/31/2021, retrospective, United Kingdom, peer-reviewed, 8 authors, study period 16 March, 2020 - 29 June, 2020. risk of death, 17.1% higher, RR 1.17, p = 0.69, all upper gastrointestinal disease patients, propensity score matching.
risk of death, 4.0% lower, HR 0.96, p = 0.88, positive upper gastrointestinal disease patients only, propensity score matching.
risk of death, 13.6% lower, HR 0.86, p = 0.59, all patients, propensity score matching.
risk of death, 20.0% lower, HR 0.80, p = 0.18, all positive patients, propensity score matching.
risk of case, 22.0% higher, OR 1.22, p = 0.15, upper gastrointestinal disease patients, propensity score matching, RR approximated with OR.
risk of case, 8.0% higher, OR 1.08, p = 0.44, all patients, propensity score matching, RR approximated with OR.
Freedberg, 5/21/2020, retrospective, propensity score matching, USA, peer-reviewed, 15 authors. risk of death/intubation, 34.0% higher, HR 1.34, p = 0.01, treatment 8 of 84 (9.5%), control 332 of 1,536 (21.6%), NNT 8.3, adjusted per study, propensity score matching, multivariable, Cox proportional hazards.
García-Menaya, 9/16/2020, retrospective, Spain, peer-reviewed, mean age 67.6, 5 authors, study period 16 March, 2020 - 24 April, 2020. risk of death, 228.0% higher, RR 3.28, p = 0.008, treatment 15 of 54 (27.8%), control 5 of 59 (8.5%), adjusted per study, multivariable.
risk of ICU admission, 392.0% higher, RR 4.92, p = 0.02, treatment 9 of 54 (16.7%), control 2 of 59 (3.4%), adjusted per study, multivariable.
Gramont, 4/15/2024, retrospective, France, peer-reviewed, 13 authors, study period March 2020 - February 2021. risk of severe case, 59.0% higher, OR 1.59, p = 0.002, treatment 424, control 410, propensity score weighting, RR approximated with OR.
Hirsch, 6/27/2024, retrospective, USA, peer-reviewed, 3 authors. risk of hospitalization, 15.0% lower, RR 0.85, p = 0.27, adjusted per study, multivariable.
risk of case, 15.0% lower, RR 0.85, p = 0.002.
Israelsen, 9/30/2021, retrospective, Denmark, peer-reviewed, 7 authors, study period 27 February, 2020 - 1 December, 2020, trial EUPAS35835. risk of death, 5.0% lower, RR 0.95, p = 0.70, treatment 166 of 3,955 (4.2%), control 189 of 3,955 (4.8%), NNT 172, adjusted per study, all patients, propensity score matching, multivariable.
risk of death, 12.0% lower, RR 0.88, p = 0.22, treatment 166 of 3,955 (4.2%), control 189 of 3,955 (4.8%), NNT 172, adjusted per study, within cases, propensity score matching, multivariable.
risk of mechanical ventilation, 8.0% higher, RR 1.08, p = 0.73, treatment 55 of 3,955 (1.4%), control 55 of 3,955 (1.4%), adjusted per study, all patients, propensity score matching, multivariable.
risk of mechanical ventilation, no change, RR 1.00, p = 1.00, treatment 55 of 3,955 (1.4%), control 55 of 3,955 (1.4%), adjusted per study, within cases, propensity score matching, multivariable.
risk of ICU admission, 4.8% higher, RR 1.05, p = 0.80, treatment 92 of 3,955 (2.3%), control 95 of 3,955 (2.4%), NNT 1318, adjusted per study, all patients, propensity score matching, multivariable.
risk of ICU admission, 3.0% lower, RR 0.97, p = 0.84, treatment 92 of 3,955 (2.3%), control 95 of 3,955 (2.4%), NNT 1318, adjusted per study, within cases, propensity score matching, multivariable.
risk of hospitalization, 22.0% higher, RR 1.22, p = 0.005, treatment 734 of 3,955 (18.6%), control 650 of 3,955 (16.4%), adjusted per study, all patients, propensity score matching, multivariable.
risk of hospitalization, 13.0% higher, RR 1.13, p = 0.010, treatment 734 of 3,955 (18.6%), control 650 of 3,955 (16.4%), adjusted per study, within cases, propensity score matching, multivariable.
risk of case, 8.0% higher, OR 1.08, p = 0.001, treatment 4,473 of 63,886 (7.0%) cases, 17,553 of 259,089 (6.8%) controls, adjusted per study, case control OR, current vs. non-use, multivariable.
Jimenez, 8/20/2021, retrospective, Brazil, peer-reviewed, 21 authors, southeast region. risk of death, 124.4% higher, HR 2.24, p < 0.001, adjusted per study, both regions combined.
risk of death, 118.3% higher, HR 2.18, p < 0.001, adjusted per study, multivariable, Cox proportional hazards.
risk of death, 133.2% higher, HR 2.33, p < 0.001, adjusted per study, multivariable, Cox proportional hazards.
Kim, 3/21/2023, retrospective, South Korea, peer-reviewed, 8 authors, study period 1 January, 2020 - 4 June, 2020. risk of death, 28.4% higher, RR 1.28, p = 0.63, treatment 9 of 437 (2.1%), control 7 of 437 (1.6%), odds ratio converted to relative risk, propensity score matching, model 3.
risk of mechanical ventilation, 74.8% higher, RR 1.75, p = 0.37, treatment 7 of 437 (1.6%), control 4 of 437 (0.9%), odds ratio converted to relative risk, propensity score matching, model 3.
risk of ICU admission, 150.5% higher, RR 2.50, p = 0.11, treatment 10 of 437 (2.3%), control 4 of 437 (0.9%), odds ratio converted to relative risk, propensity score matching, model 3.
risk of progression, 21.1% higher, RR 1.21, p = 0.60, treatment 17 of 437 (3.9%), control 14 of 437 (3.2%), odds ratio converted to relative risk, propensity score matching, model 3.
risk of case, 37.2% lower, RR 0.63, p < 0.001, treatment 226 of 9,913 (2.3%), control 341 of 9,913 (3.4%), NNT 86, adjusted per study, odds ratio converted to relative risk, propensity score matching, multivariable, model 3.
Kodvanj, 10/5/2022, retrospective, Croatia, peer-reviewed, 3 authors, study period 25 February, 2020 - 15 August, 2021. risk of death, 7.0% lower, RR 0.93, p = 0.12, treatment 41,195, control 17,334.
risk of hospitalization, 4.0% higher, OR 1.04, p = 0.32, treatment 41,195, control 17,334, RR approximated with OR.
Lee, 7/30/2020, retrospective, South Korea, peer-reviewed, 12 authors, study period 1 January, 2020 - 15 May, 2020. risk of severe case, 79.0% higher, OR 1.79, p = 0.009, treatment 267, control 267, adjusted per study, ICU, mechanical ventilation, death, propensity score matching, multivariable, RR approximated with OR.
risk of severe case, 63.0% higher, OR 1.63, p = 0.03, treatment 267, control 267, adjusted per study, oxygen, ICU, mechanical ventilation, death, propensity score matching, multivariable, RR approximated with OR.
risk of case, 10.0% lower, OR 0.90, p = 0.11, treatment 13,873, control 13,873, adjusted per study, propensity score matching, multivariable, RR approximated with OR.
Liu, 5/27/2021, retrospective, USA, peer-reviewed, 20 authors, study period 15 March, 2020 - 15 August, 2020. risk of death, 126.9% higher, RR 2.27, p < 0.001, treatment 68 of 227 (30.0%), control 53 of 459 (11.5%), adjusted per study, odds ratio converted to relative risk, multivariable.
Luxenburger, 7/31/2020, retrospective, Germany, peer-reviewed, 9 authors. risk of death, 248.4% higher, RR 3.48, p = 0.02, treatment 12 of 62 (19.4%), control 5 of 90 (5.6%), adjusted per study, multivariable, excluded in exclusion analyses: unadjusted differences between groups.
risk of ARDS, 124.3% higher, RR 2.24, p = 0.02, treatment 17 of 62 (27.4%), control 11 of 90 (12.2%), adjusted per study, multivariable, excluded in exclusion analyses: unadjusted differences between groups.
secondary infection, 86.0% higher, RR 1.86, p = 0.03, treatment 30 of 62 (48.4%), control 18 of 90 (20.0%), adjusted per study, odds ratio converted to relative risk, multivariable.
Mas Romero, 10/27/2020, retrospective, Spain, peer-reviewed, 26 authors, study period 6 March, 2020 - 5 June, 2020. risk of death, 25.9% lower, RR 0.74, p = 0.44, treatment 11 of 82 (13.4%), control 21 of 116 (18.1%), NNT 21.
risk of symptomatic case, 8.0% higher, RR 1.08, p = 0.54, treatment 58 of 82 (70.7%), control 76 of 116 (65.5%).
McKeigue, 2/22/2021, retrospective, Scotland, peer-reviewed, 18 authors, trial EUPAS35558. risk of severe case, 44.0% higher, OR 1.44, p < 0.001, treatment 1,168 of 2,357 (49.6%) cases, 12,745 of 33,803 (37.7%) controls, adjusted per study, case control OR.
Morán Blanco, 4/30/2021, retrospective, Spain, peer-reviewed, mean age 85.0, 6 authors, study period March 2020 - April 2020. risk of symptomatic case, 30.8% lower, RR 0.69, p = 0.34, treatment 12 of 48 (25.0%), control 13 of 36 (36.1%), NNT 9.0.
Patil, 12/31/2023, retrospective, USA, peer-reviewed, mean age 52.0, 7 authors. risk of death, 48.0% higher, OR 1.48, p < 0.001, treatment 4,566, control 15,349, adjusted per study, multivariable, RR approximated with OR.
risk of ARDS, 119.0% higher, OR 2.19, p < 0.001, treatment 4,566, control 15,349, adjusted per study, multivariable, RR approximated with OR.
sepsis, 88.0% higher, OR 1.88, p < 0.001, treatment 4,566, control 15,349, adjusted per study, multivariable, RR approximated with OR.
risk of oxygen therapy, 73.0% higher, OR 1.73, p < 0.001, treatment 4,566, control 15,349, adjusted per study, multivariable, RR approximated with OR.
Pinto, 10/25/2024, retrospective, Oman, peer-reviewed, mean age 44.0, 4 authors, study period 15 March, 2020 - 15 November, 2020, excluded in exclusion analyses: unadjusted results with significant baseline differences. risk of hospitalization, 57.1% higher, RR 1.57, p = 0.15, treatment 15 of 104 (14.4%), control 38 of 414 (9.2%).
Ramachandran, 11/30/2021, retrospective, USA, peer-reviewed, 7 authors, study period 1 March, 2020 - 25 April, 2020. risk of death, 92.0% higher, RR 1.92, p = 0.02, treatment 16 of 46 (34.8%), control 40 of 249 (16.1%), adjusted per study, odds ratio converted to relative risk, multivariable.
ARDS, 80.1% higher, RR 1.80, p = 0.01, treatment 18 of 46 (39.1%), control 55 of 249 (22.1%), adjusted per study, odds ratio converted to relative risk, multivariable.
Shafrir, 2/4/2022, retrospective, Israel, peer-reviewed, 9 authors, study period March 2020 - November 2020. risk of severe case, 46.7% higher, RR 1.47, p = 0.32, treatment 22 of 655 (3.4%), control 15 of 655 (2.3%), propensity score matching.
risk of severe case, 15.7% higher, RR 1.16, p = 0.28, treatment 113 of 1,608 (7.0%), control 797 of 42,789 (1.9%), adjusted per study, odds ratio converted to relative risk, multivariable.
risk of case, 7.9% lower, RR 0.92, p = 0.06, treatment 880 of 6,835 (12.9%), control 956 of 6,835 (14.0%), NNT 90, propensity score matching.
risk of case, 4.8% lower, RR 0.95, p = 0.10, adjusted per study, odds ratio converted to relative risk, multivariable.
Shah, 10/18/2021, retrospective, USA, peer-reviewed, 16 authors, study period January 2020 - May 2020. risk of death, 3.0% lower, OR 0.97, p = 0.66, treatment 6,262, control 8,696, propensity score weighting, RR approximated with OR.
risk of mechanical ventilation, 21.0% higher, OR 1.21, p = 0.06, treatment 6,262, control 8,696, propensity score weighting, RR approximated with OR.
risk of ICU admission, 13.0% higher, OR 1.13, p = 0.06, treatment 6,262, control 8,696, propensity score weighting, RR approximated with OR.
risk of hospitalization, 5.0% higher, OR 1.05, p = 0.26, treatment 6,262, control 8,696, propensity score weighting, RR approximated with OR.
Shokri, 3/31/2023, retrospective, Iran, peer-reviewed, mean age 44.2, 6 authors, study period 10 September, 2021 - 18 January, 2022, excluded in exclusion analyses: potential data issue. risk of severe case, 81.0% higher, RR 1.81, p = 0.046, treatment 121, control 549, all patients.
risk of severe case, 137.6% higher, OR 2.38, p < 0.001, treatment 40, control 549, short-term, RR approximated with OR.
risk of severe case, 30.5% higher, OR 1.30, p = 0.36, treatment 81, control 549, long-term, RR approximated with OR.
Shupp, 5/9/2022, retrospective, USA, peer-reviewed, mean age 52.6, 8 authors, study period March 2020 - August 2020. risk of death, 19.0% lower, OR 0.81, p = 0.32, treatment 448, control 2,048, adjusted per study, multivariable, RR approximated with OR.
risk of hospitalization, 10.0% higher, OR 1.10, p = 0.51, treatment 448, control 2,048, adjusted per study, multivariable, RR approximated with OR.
Vila‐Corcoles, 7/25/2020, retrospective, Spain, peer-reviewed, mean age 70.9, 11 authors, study period 1 March, 2020 - 30 April, 2020. risk of case, 9.0% higher, HR 1.09, p = 0.58, treatment 11,807, control 23,129, adjusted per study, multivariable, Cox proportional hazards.
Wu, 2/19/2022, retrospective, China, peer-reviewed, 8 authors. risk of death, 197.0% higher, OR 2.97, p < 0.001, treatment 1,046, control 3,588, propensity score weighting, model 4, RR approximated with OR.
risk of no viral clearance, 9.9% higher, HR 1.10, p = 0.02, treatment 1,046, control 3,588, inverted to make HR<1 favor treatment, propensity score matching, Cox proportional hazards.
Yan (B), 3/23/2020, retrospective, China, preprint, median age 51.0, 17 authors, study period 22 January, 2020 - 13 March, 2020. risk of severe case, 240.0% higher, RR 3.40, p < 0.001, treatment 16 of 32 (50.0%), control 20 of 136 (14.7%).
Zeng, 7/16/2024, retrospective, United Kingdom, peer-reviewed, mean age 56.5, 13 authors, study period January 2020 - September 2021. risk of death, 46.0% higher, HR 1.46, p = 0.02, treatment 9,997, control 150,926, adjusted per study, multivariable, Cox proportional hazards.
risk of severe case, 33.0% higher, HR 1.33, p = 0.004, treatment 9,997, control 150,926, adjusted per study, multivariable, Cox proportional hazards.
risk of case, 8.0% higher, HR 1.08, p = 0.10, treatment 9,997, control 150,926, adjusted per study, multivariable, Cox proportional hazards.
Zhang, 2/28/2021, retrospective, China, peer-reviewed, median age 52.0, 6 authors, study period 20 January, 2020 - 16 March, 2020. hospitalization time, 10.5% higher, relative time 1.11, p = 0.29, treatment median 21.0 IQR 11.0 n=29, control median 19.0 IQR 8.0 n=29, propensity score matching.
risk of no hospital discharge, 6.0% lower, HR 0.94, p = 0.82, treatment 35, control 119, adjusted per study, inverted to make HR<1 favor treatment, multivariable.
risk of no viral clearance, 36.5% lower, HR 0.63, p = 0.05, treatment 35, control 119, adjusted per study, inverted to make HR<1 favor treatment, multivariable.
Please send us corrections, updates, or comments. c19early involves the extraction of 100,000+ datapoints from thousands of papers. Community updates help ensure high accuracy. Treatments and other interventions are complementary. All practical, effective, and safe means should be used based on risk/benefit analysis. No treatment or intervention is 100% available and effective for all current and future variants. We do not provide medical advice. Before taking any medication, consult a qualified physician who can provide personalized advice and details of risks and benefits based on your medical history and situation. FLCCC and WCH provide treatment protocols.
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