J Korean Med Sci. 2023 Apr 03;38(13):e99. English.
Published online Mar 21, 2023.
© 2023 The Korean Academy of Medical Sciences.
Original Article

Histamine-2 Receptor Antagonists and Proton Pump Inhibitors Are Associated With Reduced Risk of SARS-CoV-2 Infection Without Comorbidities Including Diabetes, Hypertension, and Dyslipidemia: A Propensity Score-Matched Nationwide Cohort Study

Bokyung Kim,1 Jin-Hyung Jung,2 Kyungdo Han,3 Seungkyung Kang,1 Eunwoo Lee,1 Hyunsoo Chung,1 Sang Gyun Kim,1 and Soo-Jeong Cho1
    • 1Department of Internal Medicine and Liver Research Institute, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.
    • 2Department of Biostatistics, The Catholic University College of Medicine, Seoul, Korea.
    • 3Department of Statistics and Actuarial Science, Soongsil University, Seoul, Korea.
Received July 19, 2022; Accepted December 27, 2022.

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background

This study aimed to identify the effect of histamine-2 receptor antagonist (H2RA) and proton pump inhibitor (PPI) use on the positivity rate and clinical outcomes of coronavirus disease 2019 (COVID-19).

Methods

We performed a nationwide cohort study with propensity score matching using medical claims data and general health examination results from the Korean National Health Insurance Service. Individuals aged ≥ 20 years who were tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) between 1 January and 4 June 2020 were included. Patients who were prescribed H2RA or PPI within 1 year of the test date were defined as H2RA and PPI users, respectively. The primary outcome was SARS-CoV-2 test positivity, and the secondary outcome was the instance of severe clinical outcomes of COVID-19, including death, intensive care unit admission, and mechanical ventilation administration.

Results

Among 59,094 patients tested for SARS-CoV-2, 21,711 were H2RA users, 12,426 were PPI users, and 24,957 were non-users. After propensity score matching, risk of SARS-CoV-2 infection was significantly lower in H2RA users (odds ratio [OR], 0.85; 95% confidence interval [CI], 0.74–0.98) and PPI users (OR, 0.62; 95% CI, 0.52–0.74) compared to non-users. In patients with comorbidities including diabetes, dyslipidemia, and hypertension, the effect of H2RA and PPI against SARS-CoV-2 infection was not significant, whereas the protective effect was maintained in patients without such comorbidities. Risk of severe clinical outcomes in COVID-19 patients showed no difference between users and non-users after propensity score matching either in H2RA users (OR, 0.89; 95% CI, 0.52–1.54) or PPI users (OR, 1.22; 95% CI, 0.60–2.51).

Conclusion

H2RA and PPI use is associated with a decreased risk for SARS-CoV-2 infection but does not affect clinical outcome. Comorbidities including diabetes, hypertension, and dyslipidemia seem to offset the protective effect of H2RA and PPI.

Graphical Abstract

Keywords
COVID-19; SARS-CoV-2; Proton Pump Inhibitors; Histamine H2 Antagonists

INTRODUCTION

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly contagious and pathogenic virus first discovered in December 2019 that caused a global pandemic of respiratory disease named coronavirus disease 2019 (COVID-19).1, 2 Risk factors including old age, diabetes mellitus, chronic pulmonary disease, cardiovascular disease, chronic kidney disease, hypertension, obesity, metabolic disease, and smoking have been linked to higher risk of COVID-19.2, 3, 4, 5, 6, 7 Fortunately, several drugs have been proposed to have potential effects against COVID-19.8

Histamine-2 receptor antagonists (H2RA) and proton pump inhibitors (PPI) are acid suppressants most widely used for the management of gastrointestinal disorders. Gastric acid is a major defense mechanism against diverse pathogens including SARS-CoV-1. The activity of the SARS-CoV-1 spike protein, which enables the virus to attach and fuse into human cells, is sensitive to differences in pH conditions.9 Darnell et al. reports that highly acidic conditions of pH 1 and 3 inactivates SARS-CoV-1.9 In contrast, Jimenez et al. reports that acidic pH may increase susceptibility to SARS-CoV-2 infection. Lower pH associated with Barrett’s esophagus can drive increased expression of angiotensin-converting enzyme 2 (ACE2), the functional receptor through which SARS-CoV-2 enters the host cell. In addition, human monocytes cultured in acidic pH show increased expression of ACE2 and higher viral load of SARS-CoV-2.10

To date, the impact of acid suppressants on the risk of SARS-CoV-2 infection and severity of COVID-19 is not clearly understood. Previous studies identifying the association between the use of H2RA or PPI and the incidence11, 12, 13, 14, 15, 16 and clinical outcomes7, 12, 13, 15, 17, 18, 19, 20, 21, 22 of COVID-19 report inconsistent results and vary widely in study design including study population, definition of acid suppressant use, adjusted covariates, and study period. Evaluating the potential impact of acid suppressants on COVID-19 would have substantial benefits considering the popular use of the drugs and the global health burden of COVID-19.

In this study, we used a population based, large-scale nationwide cohort in South Korea with propensity score matching to identify the effect of acid suppressants PPI and H2RA on susceptibility to SARS-CoV-2 infection and clinical outcomes of COVID-19. This study included data from the Korean National Health Insurance Service (NHIS) claims database and general health examination results.

METHODS

Data source

We performed a large-scale, population based nationwide cohort study using the Korean NHIS claims database, which is linked to the Korea Centers for Disease Control and Prevention data. During the COVID-19 pandemic, the South Korean government provided a claims database that included all individuals who underwent tests for SARS-CoV-2 between 1 January and 4 June 2020 in South Korea. The database includes inpatient and outpatient healthcare records (healthcare visits, prescriptions, diagnoses, procedures, and surgeries), pharmaceutical visits, insurance eligibility data, and general health examination results within the past 3 years.23, 24

Study population

The study population consisted of individuals aged 20 years or older who underwent testing for SARS-CoV-2 during the study period (1 January 2020 to 4 June 2020). SARS-CoV-2 infection was confirmed by a positive result from a real-time reverse transcriptase-polymerase chain reaction (RT-PCR) assay of pharyngeal and nasal swabs. The date of the first test for SARS-CoV-2 in each patient was defined as the index date.12, 25 H2RA and PPI users were defined as patients prescribed H2RA (famotidine, cimetidine, nizatidine, and ranitidine) or PPI (dexlansoprazole, esomeprazole, ilaprazole, lansoprazole, omeprazole, pantoprazole, and rabeprazole) within 1 year of the index date. Non-users were defined as individuals who were not prescribed either H2RA or PPI within 1 year of the index date. Individuals who were prescribed non-steroidal anti-inflammatory drugs (NSAIDs) within 30 days of the index date were excluded. This was because H2RA or PPI may have been initiated with NSAIDs in patients with early pneumonia symptoms,12, 26 Patients prescribed both H2RA and PPI within 1 year prior to the index date were excluded. Patients who tested negative for SARS-CoV-2 during the study period but were found to be positive in tests performed after the study period were also excluded.

Study outcome

The primary outcome was SARS-CoV-2 test positivity among individuals who underwent testing for SARS-CoV-2. Clinical outcomes of COVID-19, including death, intensive care unit (ICU) admission, and mechanical ventilation administration, in patients who tested positive for SARS-CoV-2 within 2 months of diagnosis were also evaluated.4, 12

Data collection

We identified the claims data from the NHIS and combined them with the demographic data and general health examination results. Underlying comorbidities such as diabetes mellitus, hypertension, chronic pulmonary disease, chronic heart disease, cerebrovascular disease, renal disease, peripheral vascular disease, dementia, rheumatic disease, liver disease, malignancy, and dyslipidemia were identified by the presence of two or more claims within a year prior to the index date using International Classification of Diseases, 10th Revision (ICD-10) code.12 The Charlson Comorbidity Index (CCI) was calculated as a proxy of underlying disease burden using the ICD-10 codes as previously described,12 and the study population was classified into four groups according to CCI score: 0, 1, 2, and ≥ 3.12, 27 For type 2 diabetes mellitus, hypertension, and dyslipidemia, general health examination records were also used to define the comorbidities: E11–14 with antidiabetic medications or fasting blood glucose ≥ 126 for type 2 diabetes mellitus; I10–13 or I15 with antihypertensive medications, systolic blood pressure (SBP) ≥ 140, or diastolic blood pressure (DBP) ≥ 90 for hypertension; and E78 with antihyperlipidemic medications or total cholesterol ≥ 240 for dyslipidemia.

Demographic data and general health examination results included age, sex, region of residence, height, weight, waist circumference, smoking history, alcohol intake, physical activity, SBP, DBP, fasting plasma glucose (FPG), and blood lipid profile (including cholesterol, high-density lipoprotein [HDL], low-density lipoprotein [LDL], and triglyceride [TG] levels).28, 29, 30, 31 We calculated body mass index (BMI) as weight in kilograms divided by the square of height in meters (kg/m2) and classified the study population into two groups: non-obese (BMI < 25 kg/m2) and obese (BMI ≥ 25 kg/m2) according to the definition of obesity for Asians.32 Metabolic syndrome was defined by the revised National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) criteria with the combination of 1) central obesity, 2) hypertension or use of anti-hypertensives, 3) elevated TG levels or use of lipid-lowering drugs, 4) elevated FPG or use of diabetes medications, and 5) low HDL-cholesterol levels.33, 34 The region of residence was classified into two groups: Daegu and Gyeongbuk province, where large-scale outbreaks occurred during the study period, and other regions.25 Alcohol consumption was categorized as non-drinker and drinker (≥ 1 drink a month), and smoking was categorized as non-smoker and ever-smoker. Physical activity was defined as performing either > 30 minutes of moderate physical activity ≥ 5 times a week or > 20 minutes of strenuous physical activity ≥ 5 times per week. Previous medication history within 1 year prior to the test date were obtained and included aspirin, metformin, steroids, and immunosuppressive drugs other than steroids.12, 35

We identified clinical outcomes of COVID-19 patients using claim codes. The clinical outcomes included ICU admission (AJ code), mechanical ventilator administration (M5850, M5857, M5858, M5859, M5860), conventional oxygen therapy (M0040), high flow nasal cannula (M0046), extracorporeal membrane oxygenation (ECMO) (O1901, O1902, O1903, O1904), and continuous renal replacement therapy (CRRT) (O7031, O7032, O7033, O7034, O7035, O7051, O7052, O7053, O7054, O7055).35 We defined severe clinical outcome of COVID-19 as a composite of death, ICU admission, and mechanical ventilator administration. Death was identified by the classification code of treatment result. Use of inotropes and vasopressors, antiviral agents, and hydroxychloroquine after COVID-19 diagnosis were also evaluated. Drug codes (Anatomical Therapeutic Chemical [ATC] classification system) and diagnostic codes (ICD-10 code) used in this study are summarized in Supplementary Tables 1 and 2.

Statistical analysis

Descriptive statistics are shown as means and standard deviations for continuous variables, and numbers and proportions for categorical variables. Baseline characteristics were compared using the t-test and χ2 test. To evaluate the effect of H2RA and PPI use on the risk of COVID-19, 1:1 nearest neighbor propensity score matching method was applied.36 We selected variables that could potentially affect the study outcomes, including demographic characteristics, height, weight, BMI, waist circumference, systolic and diastolic blood pressure, FBG, lipid profiles, smoking history, alcohol intake, physical activity, comorbidities, CCI, and previous medications.28, 29, 30, 31, 37 We evaluated the adequacy of matching between the user and non-user groups using standardized mean difference (SMD), and a value of < 0.1 was considered to indicate no major imbalance.38 To analyze the association between the use of H2RA or PPI and the study outcome, multivariate logistic regression analyses were performed using three models: 1) Model 1, unadjusted; 2) Model 2, adjusted for age, sex, region of residence, medication history, and comorbidities; and 3) Model 3, adjusted for age, sex, region of residence, medication history, comorbidities, smoking history, alcohol intake, physical activity, obesity, and metabolic syndrome. Statistical significance was defined as a P value of < 0.05. Statistical analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC, USA).

Ethics statement

The requirement for written consent from patients was waived by the Institutional Review Board of Seoul National University Hospital (IRB No. 2102-004-1192) based on the observational nature of the study. All patient-related identifiers were anonymized for confidentiality.

RESULTS

Study population and baseline characteristics

A total of 222,164 patients underwent testing for SARS-CoV-2 in South Korea between 1 January and 4 June 2020. Of these patients, 111,251 patients were excluded, including patients younger than 20 years old (n = 17,626), patients diagnosed with COVID-19 after the study period (n = 4), patients prescribed NSAIDs within 1 month prior to the index date (n = 18,948), and patients prescribed both H2RA and PPI within 1 year prior to the index date (n = 74,678). This left 110,913 patients in the base cohort, of which 40,810 were H2RA users, 21,509 were PPI users, and 48,594 were non-users (Fig. 1). Among the patients in the base cohort, 59,094 patients had general health examination records, including 21,711 H2RA users, 12,425 PPI users, and 24,957 non-users (Fig. 1).

Fig. 1
Flowchart of population selection.
SARS-CoV-2 = severe acute respiratory syndrome coronavirus 2, COVID-19 = coronavirus disease 2019, NSAID = non-steroidal anti-inflammatory drug, H2RA = histamine 2 receptor antagonist, PPI = proton pump inhibitor.

The most common type of H2RA prescribed was ranitidine (50.27%), followed by famotidine (40.14%), cimetidine (34.85%), and nizatidine (10.35%). The most common type of PPI prescribed was esomeprazole (51.10%), followed by rabeprazole (31.44%), pantoprazole (17.98%), lansoprazole (16.73%), dexlansoprazole (7.87%), omeprazole (6.40%), and ilaprazole (4.28%).

Baseline characteristics of H2RA users, PPI users, and non-users who underwent testing for SARS-CoV-2 are shown in Table 1. Compared to non-users, H2RA users and PPI users were more likely to be older, have more comorbidities with higher CCI, take more medications (metformin, aspirin, steroids, and other immunosuppressants), and have larger waist circumference, higher blood pressure, higher FBG level, and lower HDL level. They also tended to smoke less, drink less alcohol, and have metabolic syndrome.

Table 1
Baseline characteristics of individuals tested for SARS-CoV-2

SARS-CoV-2 test positivity in H2RA and PPI users

H2RA users (n = 32,287) and PPI users (n = 17,560) were matched individually to an equal number of non-users in each propensity score-matched cohort (Table 2). No major imbalance was noticed in the demographic and clinical characteristics between the user and non-user groups (SMD < 0.1 for all covariates) for either H2RA or PPI. The odds ratio (OR) of testing positive for SARS-CoV-2 associated with H2RA or PPI use is shown in Table 3. In H2RA users, SARS-CoV-2 test positivity was 2.59%, which was significantly lower than SARS-CoV-2 test positivity in the matched non-users (3.11%), with an adjusted OR (aOR) of 0.85 (95% confidence interval [CI], 0.74–98). In PPI users, SARS-CoV-2 test positivity was 2.28%, which was significantly lower than SARS-CoV-2 test positivity in the matched non-users (3.44%), with an aOR of 0.62 (95% CI, 0.52–0.74) (Table 3).

Table 2
Propensity score-matched baseline characteristics and SARS-CoV-2 test positivity in H2RA users, PPI users, and non-users

Table 3
Propensity score-matched association of H2RA and PPI use with SARS-CoV-19 test positivity

In subgroup analysis, risk of SARS-CoV-2 infection in H2RA or PPI users was significantly lower in patients without comorbidities such as diabetes mellitus (H2RA: OR, 0.85; 95% CI, 0.73–0.98 and PPI: OR, 0.61; 95% CI, 0.51–0.74), hypertension (H2RA: OR, 0.80; 95% CI, 0.69–0.93 and PPI: OR, 0.62; 95% CI, 0.51–0.75), or dyslipidemia (H2RA: OR, 0.85; 95% CI, 0.73–0.98 and PPI: OR, 0.62; 95% CI, 0.51–0.75) in the propensity score-matched cohort. However, the protective effects of H2RA and PPI were not significant in individuals with such comorbidities (Table 3, Figs. 2 and 3). In addition, SARS-CoV-2 test positivity in H2RA users was significantly lower compared to non-users in individuals aged < 60 years and individuals without metabolic syndrome, while H2RA users aged ≥ 60 years and H2RA users with metabolic syndrome did not show such an association.

Fig. 2
Propensity score-matched association of H2RA use with SARS-COV-2 test positivity.
H2RA = histamine 2 receptor antagonist, SARS-CoV-2 = severe acute respiratory syndrome coronavirus 2, BMI = body mass index, aOR = adjusted odds ratio, CI = confidence interval.

Fig. 3
Propensity score-matched association of PPI use with SARS-COV-2 test positivity.
PPI = proton pump inhibitor, SARS-CoV-2 = severe acute respiratory syndrome coronavirus 2, BMI = body mass index, aOR = adjusted odds ratio, CI = confidence interval.

Subgroup analysis by type of H2RA or PPI used is shown in Figs. 2, 3, and Supplementary Table 3. Among the 4 types of H2RAs evaluated, famotidine (aOR, 0.63; 95% CI, 0.50–79) and cimetidine (aOR, 0.71; 95% CI, 0.57–0.89) use were each associated with significantly lower SARS-CoV-2 test positivity compared to non-users. Among the 7 types of PPIs evaluated, use of dexlansoprazole (aOR, 0.34; 95% CI, 0.16–0.74), esomeprazole (aOR, 0.55; 95% CI, 0.43–0.69), ilaprazole (aOR, 0.14; 95% CI, 0.02–0.99), lansoprazole (aOR, 0.50; 95% CI, 0.33–0.75), pantoprazole (aOR, 0.44; 95% CI, 0.29–0.68), and rabeprazole (aOR, 0.64; 95% CI, 0.50–0.83) were each associated with significantly lower SARS-CoV-2 test positivity. Nizatidine, ranitidine, and omeprazole use were not significantly associated with risk of SARS-CoV-2 infection.

The baseline characteristics, propensity score-matched characteristics, and SARS-CoV-2 test positivity of the base cohort, which includes individuals with and without health examination records, are described in Supplementary Tables 4 and 5. The OR for SARS-CoV-2 test positivity was 0.87 (95% CI, 0.80–0.95) and 0.65 (95% CI, 0.57–0.73) for H2RA users and PPI users compared to non-users, respectively.

Clinical outcomes of patients diagnosed with COVID-19

In the base cohort, the overall SARS-CoV-2 positivity rate was 3.67% (4,072/110,913). Among 4,072 patients diagnosed with COVID-19, 1,416 were H2RA users, 479 were PPI users, and 2,177 were non-users (Supplementary Fig. 1, Supplementary Table 6). After propensity score matching, 1,100 H2RA users and 437 PPI users were matched individually to an equal number of non-users. No major imbalance was noticed between the user and non-user groups (SMD < 0.1 for all covariates) for either H2RA or PPI (Supplementary Tables 7 and 8). Propensity score-matched association of H2RA and PPI use with clinical outcomes of COVID-19 are shown in Table 4. After propensity score matching, risk of death, ICU admission, mechanical ventilator administration, and severe clinical outcome, a composite of the previous three outcomes, did not show significant association with the use of H2RA or PPI. Other outcomes such as oxygen demand and use of ECMO, CRRT, inotropes, vasopressors, antiviral agents, and hydroxychloroquine were not significantly associated with H2RA or PPI use either.

Table 4
Propensity score-Matched association of H2RA or PPI use with clinical outcomes of COVID-19 patients

DISCUSSION

In this nationwide population-based cohort study, use of either H2RA or PPI was associated with decreased risk of SARS-CoV-2 infection and was not associated with severe COVID-19 outcomes. However, the protective effect of acid suppression against SARS-CoV-2 infection seems to be null in the presence of comorbidities including diabetes, hypertension, and dyslipidemia.

The incidence of COVID-19 infection in this study was 3.67% which was similar to other population-based studies (3.61–6.4%).11, 12 Previous studies that evaluate the association of H2RA and PPI with the susceptibility to SARS-CoV-2 and clinical outcome of COVID-19 show inconsistent results. These studies vary widely in the study population, type of study, definition of antacids use, covariate adjustments, and study period. Supplementary Table 9 shows difference in methods and results of previous studies regarding the association of acid suppressants and risk of SARS-CoV-2 infection and clinical outcome of COVID-19 and this study.

Almario et al.11 conducted an online survey of 53,130 participants and report that people who use PPI have increased risk of SARS-CoV-2 infection, while people who use H2RA have decreased risk SARS-CoV-2 infection. Fan et al.13 used the UK Biobank data of 9,469 participants and report that neither H2RA nor PPI is associated with SARS-CoV-2 infection. However, both studies are based on self-reported data of drug intake, either online surveys or verbal interviews. In addition, the use of H2RA and PPI is defined as current use at the time of the survey, which includes past H2RA and PPI users in the reference group and makes assessing the effect of past H2RA and PPI use difficult. Most other studies evaluate the association of either H2RA or PPI use, not both, with the risk of SARS-CoV-2 infection and report inconsistent results.12, 14, 16 Lee et al.12 conducted a nationwide cohort study in South Korea using NHIS data, which is similar to our study. They report that PPI use is not associated with positive SARS-CoV-2 test results but is related to increased risk of severe clinical outcomes of COVID-19.12 The main differences between the two studies are that our study evaluated both H2RA and PPI, included general health examination results for covariate adjustment such as BMI and presence of metabolic syndrome, smoking history, alcohol intake, physical activity, and laboratory findings, and excluded more types of recently used NSAIDs. Considering previous studies that reported obesity and metabolic disease as risk factors for SARS-CoV-2 infection,39, 40 adjusting such covariates may have contributed to the different results of the two studies.

In terms of the clinical outcomes of COVID-19 patients, several multicenter retrospective cohort studies have reported similar results to our study.7, 13, 19, 21 In contrast, Freedberg et al.18 reports that H2RA use is associated with reduced risk of severe clinical outcomes of COVID-19 and PPI use is associated with increased risk, while Zhou et al.22 reports that both H2RA and PPI are associated with an increased risk. Interestingly, a recent meta-analysis suggests that the association of PPI and increased risk of pneumonia might have been overestimated due to protopathic bias and reverse causality.26 Although several studies have reported the association of acid suppressant use and increased risk of COVID-19, when the studies that adjusted for NSAID use, BMI, and smoking history were analyzed separately, the significant association disappeared.15 Notably, the majority of previous studies that reported elevated risk of COVID-19 outcomes were those that did not include BMI for covariate adjustment.12, 41, 42, 43, 44, 45, 46 Previous studies suggest that acid suppressants may be associated with immune system impairment, resulting in increased susceptibility to infections such as pneumonia.26 However, in our study, both H2RA and PPI were associated with reduced risk of SARS-CoV-2 infection. Recently, a study using computational methods reported that famotidine likely inhibits the 3-chymotrypsin-like protease, which acts on proteins essential for virus replication.8 The protective effect of famotidine on SARS-CoV-2 infection can be explained by on-target histamine receptor-H2 activity, receptor mediated immunomodulatory effects on mast cell activation, and histamine–cytokine cross talk.47 which may also explain the effect of other H2RAs. PPIs have shown antiviral effects in various in vitro and in vivo studies.48 Possible mechanisms of PPI against SARS-CoV-2 include exerting anti-fibrotic and anti-inflammatory effects, targeting endosomal complexes, and raising endolysosomal pH via vacuolar ATPase pumps.48 However, caution is warranted in interpreting in vitro experimental results, as many drugs that were reported to be effective in vitro, such as hydroxychloroquine, did not show such effect in clinical studies.49, 50

In subgroup analysis, the protective effect of H2RA and PPI against SARS-CoV-2 infection was not significant in patients with diabetes mellitus, hypertension, or dyslipidemia. This may be due to the many direct links between COVID-19 and the metabolic system. Patients with metabolic syndrome and its components are highly susceptible to SARS-CoV-2 infection51 and are at increased risk of developing severe COVID-19.52 Metabolic dysfunction leads to a state of chronic inflammation, and in metabolic syndrome patients, inflammatory cytokines such as tumor necrosis factor-α, interleukin (IL)-1β, and IL-6 are upregulated in the adipose tissue.52 The chronic systemic inflammation and dysregulated immunometabolism provoked by metabolic associated preconditions may intensify inflammation associated with SARS-CoV-2 infection.3, 4 In addition, expression of ACE2, the entry receptor of SARS-CoV-2, is increased following inflammatory stress and metabolic syndrome.51 Enhanced expression of ACE2, combined with endothelial dysfunction and dysregulation of adipocytokines in metabolic syndrome and associated preconditions, may play a crucial role in the susceptibility to SARS-CoV-2 infection and development of COVID-19.51 In subgroup analysis, individuals with obesity, diabetes mellitus, hypertension, metabolic syndrome, as well as old age and female sex showed higher SARS-CoV-2 test positivity rates both in non-users and acid suppressant users, compared to individuals without comorbidities, young age, and male sex (Supplementary Table 3). Considering the possible effect of H2RA and PPI on immunomodulation and anti-inflammation, the comorbidity of diabetes mellitus, hypertension, or dyslipidemia may have offset the protective effect of acid suppressants against SARS-CoV-2 infection.

With respect to the types of drugs used, notable exceptions were found with omeprazole, nizatidine, and ranitidine, which did not show a significant association with risk of SARS-CoV-2 infection. One previous study that evaluated the effect of acid suppressants on the risk of COVID-19 shows a similar trend, reporting that omeprazole users are more likely to have positive SARS-CoV-2 test results compared to users of other PPI.13 Another study identifying the effect of famotidine on cytokine storm reported that while famotidine activates the vagal inflammatory reflex to attenuate cytokine storm, ranitidine did not show such effect even at high doses.53 However, the mechanism behind these tendency is yet to be discovered.

Individuals who were prescribed NSAIDs within 1 month the index date were excluded in the consideration that acid suppressants may have been initiated with NSAIDs in COVID-19 patients with early pneumonia symptoms who are not yet diagnosed.12, 26 The period of 1 month seems reasonable since previous studies reported the time from symptom onset to diagnosis to be as long as 4 weeks.54, 55

This study has several limitations. First, the study was based on NHIS claims data, which may not accurately reflect patients’ drug intake. Although the patients’ exposure to H2RA and PPI is highly accurate because a prescription is required to obtain H2RA and PPI in South Korea, drug compliance could not be screened by this study. Second, as with all retrospective studies, the possibility of unmeasured confounders cannot be excluded. Although we have adjusted most of the confounders, including demographic characteristics, various underlying diseases, medication history, and general health examination data, other variables that may affect outcomes, such as socioeconomic status or education level, were not included. Third, underlying disease and general health examination data were assessed from past ICD codes and health check-up data, which may not reflect the individuals’ exact status on the index date. Fourth, the period of one year could be insufficient to explain the biologic plausibility of the drugs. Also, this study did not differentiate between current and past user group. However, a previous study reported that majority of patients who are prescribed with acid suppressants have a tendency to take the drugs in intermittent or on-demand basis in a long-term period.56 This suggests that patients who are prescribed acid suppressants months before diagnosis could still take medications long after the date of prescription, which could contribute to biological plausibility. This tendency can make it difficult to differentiate current users from past users when using claims data, since patients who are prescribed acid suppressants long ago but take the drug on demand or intermittently until test date could be defined as past users by study definition, but actually be current users.56 Also, a previous study that compared the time window of PPI prescription and diagnosis of COVID-19 reported a decreasing, but still significant tendency in the protective effect of PPI on COVID-19 infection as the window period changed from 6 months, 1 year, to 2 years.57 We believe this results could indicate the possibility of the biologic effect of acid suppressants in a long term period although the mechanism should be further identified. Lastly, cumulative exposure and dose dependent risk could not be evaluated. In the future, prospective, well-matched, long-term studies are warranted to overcome these limitations.

The strengths of this study include a large sample size from a well-characterized national cohort that included the whole population that underwent testing for SARS-CoV-2. Vigorous adjustment for potential confounders, which included not only demographics, comorbidities, and medications but also anthropometry and laboratory data, was performed. We also applied strict exclusion criteria for individuals who received new prescriptions of NSAIDs or prescriptions of both H2RA and PPI within 1 year prior to the index date, to minimize bias. We believe the results of this study could provide additional knowledge to the effect of acid suppressant in the process of infection of SARS-CoV-2, especially in relation with metabolic preconditions.

In this large-scale propensity-matched nationwide study, H2RA and PPI use was associated with a lower risk of SARS-CoV-2 infection but did not show significant association with clinical outcomes of COVID-19 patients. Comorbidities including diabetes, hypertension, and dyslipidemia seem to offset the protective effect of the medications. Our results provide improved insight into the association between acid suppressants and risk of COVID-19.

SUPPLEMENTARY MATERIALS

Supplementary Table 1

ICD-10 codes

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Supplementary Table 2

Drug codes

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Supplementary Table 3

Propensity score-matched association of H2RA and PPI use with SARS-CoV-19 test positivity with subgroup analysis according to age, sex, BMI, and underlying disease

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Supplementary Table 4

Propensity score-matched association of H2RA and PPI use with SARS-CoV-19 test positivity according to type of H2RA and PPI used

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Supplementary Table 5

Baseline characteristics of individuals tested for SARS-CoV-2 of H2RA user, PPI user, and non-user groups in the entire cohort (including individuals with and without health examination records)

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Supplementary Table 6

Propensity score matched baseline characteristics and SARS-CoV-2 test positivity in H2RA user, PPI user, and non-user groups in the entire cohort (including individuals with and without health examination records)

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Supplementary Table 7

Baseline characteristics of patients diagnosed with COVID-19 according to previous use of H2RA and PPI

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Supplementary Table 8

Propensity score matched baseline characteristics and clinical outcomes of COVID-19 patients in H2RA user, PPI user, and non-user groups

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Supplementary Table 9

Comparison of previous studies that evaluated the effect of H2RA and PPI on the risk of SARS-CoV-2 infection and clinical outcomes of COVID-19

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Supplementary Fig. 1

Flowchart of population selection for clinical outcomes in COVID-19 patients.

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Notes

Funding:This study was supported by the National Research Foundation of Korea (grant No. NRF-2019R1A2C1009923 and NRF-2022R1A2B5B01001430), the Korean College of Helicobacter and Upper Gastrointestinal Research Foundation (grant No. KCHUGR – 202002001), and Clinical Research Institute, Seoul National University Hospital (grant No. 0620211010) from Dong-A Pharmaceutical Co. Korea. The funding source of the study had no role in the study design, data collection, data analysis, data interpretation, writing of the manuscript, or decision of submission for publication.

Disclosure:The authors have no potential conflicts of interest to disclose.

Author Contributions:

  • Conceptualization: Kim B, Jung JH, Han K, Kang S, Lee E, Chung HS, Kim SG, Cho SJ.

  • Data curation: Kim B, Jung JH, Han K, Cho SJ.

  • Formal analysis: Kim B, Jung JH, Han K, Cho SJ.

  • Funding acquisition: Cho SJ.

  • Investigation: Kim B, Jung JH, Han K, Cho SJ.

  • Methodology: Kim B, Jung JH, Han K, Cho SJ.

  • Project administration: Cho SJ, Han K.

  • Software: Jung JH, Han K.

  • Supervision: Cho SJ, Han K.

  • Validation: Kim B, Jung JH, Han K, Cho SJ.

  • Visualization: Kim B, Jung JH, Han K.

  • Writing - original draft: Kim B, Cho SJ.

  • Writing - review & editing: Kim B, Jung JH, Han K, Kang S, Lee E, Chung HS, Kim SG, Cho SJ.

References

    1. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 2020;395(10223):497–506.
    1. Grasselli G, Zangrillo A, Zanella A, Antonelli M, Cabrini L, Castelli A, et al. Baseline characteristics and outcomes of 1591 patients infected with SARS-CoV-2 admitted to ICUs of the Lombardy region, Italy. JAMA 2020;323(16):1574–1581.
    1. Mauvais-Jarvis F. Aging, male sex, obesity, and metabolic inflammation create the perfect storm for COVID-19. Diabetes 2020;69(9):1857–1863.
    1. Guan WJ, Liang WH, Zhao Y, Liang HR, Chen ZS, Li YM, et al. Comorbidity and its impact on 1590 patients with COVID-19 in China: a nationwide analysis. Eur Respir J 2020;55(5):2000547
    1. Moon SS, Lee K, Park J, Yun S, Lee YS, Lee DS. Clinical characteristics and mortality predictors of COVID-19 patients hospitalized at nationally-designated treatment hospitals. J Korean Med Sci 2020;35(36):e328
    1. Kim DW, Byeon KH, Kim J, Cho KD, Lee N. The correlation of comorbidities on the mortality in patients with COVID-19: an observational study based on the Korean National Health Insurance big data. J Korean Med Sci 2020;35(26):e243
    1. Shupp B, Mehta SV, Chirayath S, Patel N, Aiad M, Sapin J, et al. Proton pump inhibitor therapy usage and associated hospitalization rates and critical care outcomes of COVID-19 patients. Sci Rep 2022;12(1):7596.
    1. Wu C, Liu Y, Yang Y, Zhang P, Zhong W, Wang Y, et al. Analysis of therapeutic targets for SARS-CoV-2 and discovery of potential drugs by computational methods. Acta Pharm Sin B 2020;10(5):766–788.
    1. Darnell ME, Subbarao K, Feinstone SM, Taylor DR. Inactivation of the coronavirus that induces severe acute respiratory syndrome, SARS-CoV. J Virol Methods 2004;121(1):85–91.
    1. Jimenez L, Campos Codo A, Sampaio VS, Oliveira AE, Ferreira LK, Davanzo GG, et al. Acid pH increases SARS-CoV-2 infection and the risk of death by COVID-19. Front Med (Lausanne) 2021;8:637885
    1. Almario CV, Chey WD, Spiegel BM. Increased risk of COVID-19 among users of proton pump inhibitors. Am J Gastroenterol 2020;115(10):1707–1715.
    1. Lee SW, Ha EK, Yeniova AO, Moon SY, Kim SY, Koh HY, et al. Severe clinical outcomes of COVID-19 associated with proton pump inhibitors: a nationwide cohort study with propensity score matching. Gut 2021;70(1):76–84.
    1. Fan X, Liu Z, Miyata T, Dasarathy S, Rotroff DM, Wu X, et al. Effect of acid suppressants on the risk of COVID-19: a propensity score-matched study using UK Biobank. Gastroenterology 2021;160(1):455–458.e5.
    1. Blanc F, Waechter C, Vogel T, Schorr B, Demuynck C, Hunyadi CM, et al. Therapeutic prevention of COVID-19 in elderly: a case-control study. Geroscience 2021;43(5):2333–2343.
    1. Kim HB, Kim JH, Wolf BJ. Acid suppressant use in association with incidence and severe outcomes of COVID-19: a systematic review and meta-analysis. Eur J Clin Pharmacol 2022;78(3):383–391.
    1. Vila-Corcoles A, Satue-Gracia E, Ochoa-Gondar O, Torrente-Fraga C, Gomez-Bertomeu F, Vila-Rovira A, et al. Use of distinct anti-hypertensive drugs and risk for COVID-19 among hypertensive people: a population-based cohort study in Southern Catalonia, Spain. J Clin Hypertens (Greenwich) 2020;22(8):1379–1388.
    1. Shoaibi A, Fortin SP, Weinstein R, Berlin JA, Ryan P. Comparative effectiveness of famotidine in hospitalized COVID-19 patients. Am J Gastroenterol 2021;116(4):692–699.
    1. Freedberg DE, Conigliaro J, Wang TC, Tracey KJ, Callahan MV, Abrams JA, et al. Famotidine use is associated with improved clinical outcomes in hospitalized COVID-19 patients: a propensity score matched retrospective cohort study. Gastroenterology 2020;159(3):1129–1131.e3.
    1. Yeramaneni S, Doshi P, Sands K, Cooper M, Kurbegov D, Fromell G. Famotidine use is not associated with 30-day mortality: a coarsened exact match study in 7158 hospitalized patients with coronavirus disease 2019 from a large healthcare system. Gastroenterology 2021;160(3):919–921.e3.
    1. Ramachandran P, Perisetti A, Gajendran M, Jean-Louis F, Bansal P, Dwivedi AK, et al. Pre-hospitalization proton pump inhibitor use and clinical outcomes in COVID-19. Eur J Gastroenterol Hepatol 2022;34(2):137–141.
    1. Elmunzer BJ, Wolf BJ, Scheiman JM, Tierney WM, Taylor JR. North American Alliance for the Study of Digestive Manifestations of COVID-19. Association between preadmission acid suppressive medication exposure and severity of illness in patients hospitalized with COVID-19. Gastroenterology 2021;160(4):1417–1422.e14.
    1. Zhou J, Wang X, Lee S, Wu WK, Cheung BM, Zhang Q, et al. Proton pump inhibitor or famotidine use and severe COVID-19 disease: a propensity score-matched territory-wide study. Gut 2021;70(10):2012–2013.
    1. Song SO, Jung CH, Song YD, Park CY, Kwon HS, Cha BS, et al. Background and data configuration process of a nationwide population-based study using the Korean National Health Insurance System. Diabetes Metab J 2014;38(5):395–403.
    1. Park S, Choi GJ, Ko H. Information technology-based tracing strategy in response to COVID-19 in South Korea-Privacy Controversies. JAMA 2020;323(21):2129–2130.
    1. Bae S, Ghang B, Kim YJ, Lim JS, Yun SC, Kim YG, et al. Recent hydroxychloroquine use is not significantly associated with positive PCR results for SARS-CoV-2: a nationwide observational study in South Korea. Viruses 2021;13(2):329.
    1. Wang CH, Li CH, Hsieh R, Fan CY, Hsu TC, Chang WC, et al. Proton pump inhibitors therapy and the risk of pneumonia: a systematic review and meta-analysis of randomized controlled trials and observational studies. Expert Opin Drug Saf 2019;18(3):163–172.
    1. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 1987;40(5):373–383.
    1. Ghoneim S, Butt MU, Hamid O, Shah A, Asaad I. The incidence of COVID-19 in patients with metabolic syndrome and non-alcoholic steatohepatitis: a population-based study. Metabol Open 2020;8:100057
    1. Scalsky RJ, Chen YJ, Desai K, O’Connell JR, Perry JA, Hong CC. Baseline cardiometabolic profiles and SARS-CoV-2 infection in the UK Biobank. PLoS One 2021;16(4):e0248602
    1. Sallis R, Young DR, Tartof SY, Sallis JF, Sall J, Li Q, et al. Physical inactivity is associated with a higher risk for severe COVID-19 outcomes: a study in 48 440 adult patients. Br J Sports Med 2021;55(19):1099–1105.
    1. Dai M, Tao L, Chen Z, Tian Z, Guo X, Allen-Gipson DS, et al. Influence of cigarettes and alcohol on the severity and death of COVID-19: a multicenter retrospective study in Wuhan, China. Front Physiol 2020;11:588553
    1. WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 2004;363(9403):157–163.
    1. Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 2009;120(16):1640–1645.
    1. Lee SY, Park HS, Kim DJ, Han JH, Kim SM, Cho GJ, et al. Appropriate waist circumference cutoff points for central obesity in Korean adults. Diabetes Res Clin Pract 2007;75(1):72–80.
    1. Jung SY, Choi JC, You SH, Kim WY. Association of renin-angiotensin-aldosterone system inhibitors with coronavirus disease 2019 (COVID-19)-related outcomes in Korea: a nationwide population-based cohort study. Clin Infect Dis 2020;71(16):2121–2128.
    1. Parsons LS. Reducing bias in a propensity score matched-pair sample using greedy matching techniques; Proceedings of the 26th Annual SAS Users Group International Conference; April 22-25, 2001; Long Beach, CA, USA. Cary, NC, USA: SAS Institute Inc.; 2001. pp. 214-226.
    1. Tuty Kuswardhani RA, Henrina J, Pranata R, Anthonius Lim M, Lawrensia S, Suastika K. Charlson comorbidity index and a composite of poor outcomes in COVID-19 patients: a systematic review and meta-analysis. Diabetes Metab Syndr 2020;14(6):2103–2109.
    1. Austin PC. Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples. Stat Med 2009;28(25):3083–3107.
    1. Cho DH, Choi J, Gwon JG. Metabolic syndrome and the risk of COVID-19 infection: a nationwide population-based case-control study. Nutr Metab Cardiovasc Dis 2021;31(9):2596–2604.
    1. Muscogiuri G, Bettini S, Boschetti M, Barrea L, Savastano S, Colao A, et al. Low-grade inflammation, COVID-19, and obesity: clinical aspect and molecular insights in childhood and adulthood. Int J Obes 2022;46(7):1254–1261.
    1. Luxenburger H, Sturm L, Biever P, Rieg S, Duerschmied D, Schultheiss M, et al. Treatment with proton pump inhibitors increases the risk of secondary infections and ARDS in hospitalized patients with COVID-19: coincidence or underestimated risk factor? J Intern Med 2021;289(1):121–124.
    1. Israelsen SB, Ernst MT, Lundh A, Lundbo LF, Sandholdt H, Hallas J, et al. Proton pump inhibitor use is not strongly associated with SARS-CoV-2 related outcomes: a nationwide study and meta-analysis. Clin Gastroenterol Hepatol 2021;19(9):1845–1854.e6.
    1. Liu JJ, Sloan ME, Owings AH, Figgins E, Gauthier J, Gharaibeh R, et al. Increased ACE2 levels and mortality risk of patients with COVID-19 on proton pump inhibitor therapy. Am J Gastroenterol 2021;116(8):1638–1645.
    1. Oddy C, McCaul J, Keeling P, Allington J, Senn D, Soni N, et al. Pharmacological predictors of morbidity and mortality in COVID-19. J Clin Pharmacol 2021;61(10):1286–1300.
    1. Yozgat A, Kasapoğlu B, Can G, Tanoğlu A, Sakin YS, Yalçın KS, et al. Long-term proton pump inhibitor use is a risk factor for mortality in patients hospitalized for COVID-19. Turk J Med Sci 2021;51(3):1675–1681.
    1. Yan C, Chen Y, Sun C, Ahmed MA, Bhan C, Guo Z, et al. Does proton pump inhibitor use lead to a higher risk of coronavirus disease 2019 infection and progression to severe disease? A meta-analysis. Jpn J Infect Dis 2022;75(1):10–15.
    1. Malone RW, Tisdall P, Fremont-Smith P, Liu Y, Huang XP, White KM, et al. COVID-19: famotidine, histamine, mast cells, and mechanisms. Front Pharmacol 2021;12:633680
    1. Ray A, Sharma S, Sadasivam B. The potential therapeutic role of proton pump inhibitors in COVID-19: hypotheses based on existing evidences. Drug Res (Stuttg) 2020;70(10):484–488.
    1. Bartoszko JJ, Siemieniuk RA, Kum E, Qasim A, Zeraatkar D, Ge L, et al. Prophylaxis against COVID-19: living systematic review and network meta-analysis. BMJ 2021;373(949):n949.
    1. Yao X, Ye F, Zhang M, Cui C, Huang B, Niu P, et al. In vitro antiviral activity and projection of optimized dosing design of hydroxychloroquine for the treatment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Clin Infect Dis 2020;71(15):732–739.
    1. Yanai H. Metabolic syndrome and COVID-19. Cardiol Rev 2020;11(6):360–365.
    1. Steenblock C, Schwarz PE, Ludwig B, Linkermann A, Zimmet P, Kulebyakin K, et al. COVID-19 and metabolic disease: mechanisms and clinical management. Lancet Diabetes Endocrinol 2021;9(11):786–798.
    1. Yang H, George SJ, Thompson DA, Silverman HA, Tsaava T, Tynan A, et al. Famotidine activates the vagus nerve inflammatory reflex to attenuate cytokine storm. Mol Med 2022;28(1):57.
    1. Zheng W, Kämpfen F, Huang Z. Health-seeking and diagnosis delay and its associated factors: a case study on COVID-19 infections in Shaanxi Province, China. Sci Rep 2021;11(1):17331.
    1. Li M, Zhu D, Yang J, Yan L, Xiong Z, Lu J, et al. Clinical treatment experience in severe and critical COVID-19. Mediators Inflamm 2021;2021:9924542
    1. Van Soest EM, Siersema PD, Dieleman JP, Sturkenboom MC, Kuipers EJ. Persistence and adherence to proton pump inhibitors in daily clinical practice. Aliment Pharmacol Ther 2006;24(2):377–385.
    1. Xiang Y, Wong KC, So HC. Exploring drugs and vaccines associated with altered risks and severity of COVID-19: a UK Biobank cohort study of all ATC level-4 drug categories reveals repositioning opportunities. Pharmaceutics 2021;13(9):1514.

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