ABSTRACT
Introduction: Proton pump inhibitors (PPIs) play an indispensable role in the treatment of acid-secretion disorders and are one of the most widely used drugs. This study aimed to investigate the association between proton pump inhibitors (PPI) use and COVID-19-related mortality and hospitalizations. Aims & Methods: This population-based matched cohort study included all individuals diagnosed with the first episode of COVID-19 up to August 15, 2021, in Croatia. We classified patients based on exposure to PPIs and burden of PPI-requiring conditions as: 1. Non-users (patients without issued PPI prescriptions and treatmentrequiring conditions), 2. Possible users (patients without issued PPI prescriptions but with recorded treatment-requiring conditions), and;3. Users (patients with issued PPI prescriptions). Users were further divided into three groups based on the intensity of PPI prescriptions to investigate the dose effect of PPIs. In addition to the comparison of users to non-users, we compared: 1. Users to possible users to isolate the effect of PPIs and 2. Possible users to non-users to isolate the effect of comorbidities treated with PPIs on COVID-19-related mortality and hospitalization. Log-binomial regression with robust sandwich variance estimation was used to calculate relative risk and 95% confidence intervals after exact matching in respect to a range of pre-COVID-19 characteristics (in primary analysis: age (binned to 5 years), sex, vaccination status, time period in the course of the pandemic, Charlson comorbidity index, presence of ACE inhibitor therapy and comorbidities: atrial fibrillation, autoimmune diseases, cancer, chronic heart failure, chronic obstructive lung disease, ischemic or cerebrovascular diseases, chronic renal disease and immunocompromised state;in sensitivity analysis with an alternative set of covariates). Result(s): Among 433609 COVID-19 patients, 332389 were identified as nonusers, 18170 as possible users, and 55098 as users of PPIs. Users to non-users, users to possible users, and possible users to non-users were matched 48453 to 325005, 41195 to 17334, and 17466 to 316168 subjects per group, respectively. A small difference in COVID-19 related mortality and hospitalizations was observed after matching users to non-users [RRmortality = 1.23 (95%CI 1.16 - 1.30) and RRhospitalization = 1.46 (95%CI 1.38 - 1.54)] and possible users to non-users [RRmortality = 1.24 (95%CI 1.13 to 1.37) and RRhospitalization = 1.26 (95%CI 1.16 - 1.37)]. However, there was no relevant difference between users and possible users in COVID-19-related mortality [RR= 0.93 (95%CI 0.85 - 1.02)] or hospitalizations [RR = 1.04 (0.97 - 1.13)]. Dose effect was not observed in any comparison involving users. Sensitivity analysis yielded comparable results. Conclusion(s): The comparison of possible to non-users, and users to possible users indicates that the risk observed in the comparison of users and non-users of PPI is likely attributable to the burden of comorbidities treated with PPIs and not the effect of the PPIs.
ABSTRACT
The Pandemic of COVID-19, an infectious disease caused by SARS-CoV-2 motivated the scientific community to work together in order to gather, organize, process and distribute data on the novel biomedical hazard. Here, we analyzed how the scientific community responded to this challenge by quantifying distribution and availability patterns of the academic information related to COVID-19. The aim of this study was to assess the quality of the information flow and scientific collaboration, two factors we believe to be critical for finding new solutions for the ongoing pandemic. The RISmed R package, and a custom Python script were used to fetch metadata on articles indexed in PubMed and published on Rxiv preprint server. Scopus was manually searched and the metadata was exported in BibTex file. Publication rate and publication status, affiliation and author count per article, and submission-to-publication time were analysed in R. Biblioshiny application was used to create a world collaboration map. Preliminary data suggest that COVID-19 pandemic resulted in generation of a large amount of scientific data, and demonstrates potential problems regarding the information velocity, availability, and scientific collaboration in the early stages of the pandemic. More specifically, the results indicate precarious overload of the standard publication systems, significant problems with data availability and apparent deficient collaboration. In conclusion, we believe the scientific community could have used the data more efficiently in order to create proper foundations for finding new solutions for the COVID-19 pandemic. Moreover, we believe we can learn from this on the go and adopt open science principles and a more mindful approach to COVID-19-related data to accelerate the discovery of more efficient solutions. We take this opportunity to invite our colleagues to contribute to this global scientific collaboration by publishing their findings with maximal transparency.
ABSTRACT
While the coronavirus disease 2019 (COVID-19) pandemic advances, the scientific community continues to struggle in the search for treatments. Several improvements have been made, including discovery of the clinical efficacy of chloroquine (CQ) in patients with COVID-19, but effective treatment protocols remain elusive. In the search for novel treatment options, many scientists have used the in-silico approach to identify compounds that could interfere with the key molecules involved in entrance, replication or dissemination of severe acute respiratory syndrome coronavirus-2. However, most of the identified molecules are not available as pharmacological agents at present, and assessment of their safety and efficacy could take many months. This review took a different approach based on the proposed pharmacodynamic model of CQ in COVID-19. The main mechanism of action responsible for the favourable outcome of patients with COVID-19 treated with CQ seems to be related to a pH-modulation-mediated effect on endolysosomal trafficking, a characteristic of chemical compounds often called 'lysosomotropic agents' because of the physico-chemical properties that enable them to diffuse passively through the endosomal membrane and undergo protonation-based trapping in the lumen of the acidic vesicles. This review discusses lysosomotropic and lysosome targeting drugs that are already in clinical use and are characterized by good safety profiles, low cost and wide availability. Some of these drugs -particularly azithromycin and other macrolides, indomethacin and some other non-steroidal anti-inflammatory drugs, proton pump inhibitors and fluoxetine - could provide additional therapeutic benefits in addition to the potential antiviral effect that is still to be confirmed by well-controlled clinical trials. As some of these drugs have probably been used empirically in the treatment of COVID-19, it is hoped that colleagues worldwide will publish patient data to enable evaluation of the potential efficacy of these agents in the clinical context, and rapid implementation in therapeutic protocols if they are shown to have a beneficial effect on clinical outcome.