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We read the recent articles published in Gut on the relationship between proton pump inhibitor (PPI) use and outcomes in COVID-19 with great interest.1 2 In the meta-analysis, the authors found that current or regular PPI users were more likely to have severe outcomes of COVID-19 than non-users, but no significant association was observed for previous PPI use.2 The reason may be reduced secretion of gastric acid that can neutralise the SARS-CoV-2. By contrast, the use of famotidine, another medication for gastric ulcers or gastro-oesophageal reflux disease, was associated with better clinical outcomes in some studies,3 4 but not others.5 6
Given these conflicting findings, we conducted this territory-wide study to investigate whether PPI or famotidine use was associated with a higher risk of severe disease using propensity score matching. The detailed methodology of the present analyses is shown in the online supplemental appendix. A total of 4445 patients (median age 44.8 years old, 95% CI: (28.9 to 60.8)); 50% male) were diagnosed with the COVID-19 infection between 1 January 2020 and 22 August 2020 in Hong Kong public hospitals or their associated ambulatory/outpatient facilities. On follow-up until 8 September 2020, a total of 212 patients (4.8%) met the primary outcome of need for intensive care unit (ICU) admission or intubation, or death (online supplemental figure 1). The median duration between hospitalisation admission and ICU admission, intubation or death were 35 (95% CI: 24.5 to 50.5), 33 (95% CI: 21.0 to 140.0) and 15 days (95% CI: 7.5 to 24.5), respectively. The baseline clinical characteristics of patients with or without PPI/famotidine use during the inpatient stay are shown in online supplemental table 4. Those for the cohort stratified by PPI or famotidine use before and after propensity score matching for baseline demographics, medical comorbidities and medication history are shown in online supplemental tables 5 and 6, respectively.
The percentage of COVID-19 patients meeting the primary outcome was significantly higher in PPI users than in non-users, both before (n=151/524, 28.8% vs n=61/3921, 1.6%; p<0.0001) and after 1:5 propensity score matching for age, sex, medical comorbidities and medication history (n=151/524, 28.8% vs n=173/2620, 6.6%; p<0.0001). Similarly, famotidine users also showed a higher percentage compared with non-users before (n=72/519, 13.9% vs n=140/3926, 3.6%; p<0.0001) and after matching (n=72/519, 13.9% vs n=198/2595, 7.6%; p<0.0001). Kaplan-Meier curves stratified by PPI or famotidine use are shown in figures 1 and 2. Based on the matched cohorts, univariable Cox regression showed that the use of PPI (HR: 6.32, 95% CI: (5.02 to 7.95); p<0.0001) or famotidine (HR: 1.98, 95% CI: (1.47 to 2.66); p<0.0001) was associated with a higher risk of the primary outcome (online supplemental table 7). On multivariable Cox regression adjusting for age, cardiovascular disease, renal disease, stroke, Kaletra, diuretics for heart failure, other anti-hypertensives, PPI/famotidine, neutrophils, lymphocytes, platelets, urea, creatinine, albumin and glucose, the associations remained significant for both PPI (HR: 2.73, 95% CI: (2.05 to 3.64), p<0.0001) and famotidine (HR: 1.81, 95% CI: (1.28 to 2.58), p<0.0001). The Cox analyses were repeated on separate cohorts generated by 1:1 propensity score matching, demonstrating similarly increased risks with PPI (HR: 11.76, 95% CI: (7.77 to 17.79); p<0.0001) or famotidine (HR: 1.81, 95% CI: (1.35 to 2.43); p<0.0001) use. Similarly, on multivariate Cox regression, the associations remained significant for both PPI (HR: 2.65, 95% CI: (1.75 to 4.00), p<0.0001) and famotidine (HR: 1.84, 95% CI: (1.16 to 2.92), p<0.0001).
Our data indicate that the use of PPIs or famotidine is associated with a higher risk of severe COVID-19 disease after propensity score matching in a Chinese cohort. Our findings should be validated in future studies.
JZ and XW are joint first authors.
QZ and GT are joint senior authors.
Twitter @sharen212, @QPCN, @garytse1
Contributors JZ and XW: data analysis, data interpretation, statistical analysis, manuscript drafting and critical revision of manuscript. SL, WKKW and BC: project planning, data acquisition, data interpretation and critical revision of manuscript. QZ and GT: study conception, study supervision, project planning, data interpretation, statistical analysis, manuscript drafting and critical revision of manuscript.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Patient consent for publication Not required.
Ethics approval This study was approved by the Institutional Review Board of the University of Hong Kong/Hospital Authority Hong Kong West Cluster.
Provenance and peer review Not commissioned; internally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.
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