Correction to: Association of Antihypertensive Agents with the Risk of In-Hospital Death in Patients with Covid-19

Effects of previous exposure to different medications on the clinical course of COVID-19 patients in Istanbul, Turkey

Background/Aim: Multiple studies have investigated the effects of drugs that alter ACE2 expression, such as renin-angiotensin system inhibitors, non-steroidal anti-inflammatory drugs, and thiazolidinediones, on the clinical course of coronavirus disease-2019 (COVID-19). But a consensus has not yet been reached, and it has been stated that they do not have any effect. There are publications in which metformin is associated with low mortality and insulin with high mortality. Data from different parts of the world are important given that the rate of spread of COVID-19 may be related to the expression status of ACE2 or TMPRSS2 receptors or some other unknown genetic factors. This study aims to examine the effects of medications used chronically in the last 6 months before contracting COVID-19 on the clinical course of COVID-19 in a sample of Istanbul, Turkey. Methods: In this retrospective cohort study, which included 525 patients diagnosed with COVID-19 between March and November 2020 from four family health centers in Istanbul, the records of the patients were retrospectively analyzed. In addition to demographic information, all medications chronically used by the patients in the last 6 months before the diagnosis of COVID-19 were noted. The effects of demographic data and medications on the three main endpoints of the study, which were hospitalization, intensive care unit (ICU) admission, and mortality, were analyzed using logistic regression models. Results: Of the 525 COVID-19 patients included in the study, 109 (20.8%) were hospitalized, 18 (3.4%) were treated in ICU, and 11 (2.1%) patients died. Increasing age is associated with hospitalization, ICU admission and mortality. Also, the presence of COVID-19 thoracic computed tomography (CT) findings and polypharmacy was associated with increased hospitalization. Living alone and the presence of COVID-19 thoracic CT findings was associated with increased ICU admission. When adjusted for age and comorbidity, logistic regression models revealed that medications for diabetes mellitus (DM) increased the probability of hospitalization (OR: 3.9, 95% CI 1.2-13.0), and calcium channel blockers (CCBs) increased the probability of ICU admission (OR: 15.8, 95% CI 2.1–120.2) and mortality (OR: 295.1, 95% CI 4.6–18946.6). Conclusion: Previous use of DM medications and CCBs may negatively affect the clinical course of COVID-19.

Mining Electronic Health Records for Drugs Associated With 28-day Mortality in COVID-19: Pharmacopoeia-wide Association Study (PharmWAS)

BACKGROUND

Patients hospitalized for a given condition may be receiving other treatments for other contemporary conditions or comorbidities. The use of such observational clinical data for pharmacological hypothesis generation is appealing in the context of an emerging disease but particularly challenging due to the presence of drug indication bias.

OBJECTIVE

With this study, our main objective was the development and validation of a fully data-driven pipeline that would address this challenge. Our secondary objective was to generate pharmacological hypotheses in patients with COVID-19 and demonstrate the clinical relevance of the pipeline.

METHODS

We developed a pharmacopeia-wide association study (PharmWAS) pipeline inspired from the PheWAS methodology, which systematically screens for associations between the whole pharmacopeia and a clinical phenotype. First, a fully data-driven procedure based on adaptive least absolute shrinkage and selection operator (LASSO) determined drug-specific adjustment sets. Second, we computed several measures of association, including robust methods based on propensity scores (PSs) to control indication bias. Finally, we applied the Benjamini and Hochberg procedure of the false discovery rate (FDR). We applied this method in a multicenter retrospective cohort study using electronic medical records from 16 university hospitals of the Greater Paris area. We included all adult patients between 18 and 95 years old hospitalized in conventional wards for COVID-19 between February 1, 2020, and June 15, 2021. We investigated the association between drug prescription within 48 hours from admission and 28-day mortality. We validated our data-driven pipeline against a knowledge-based pipeline on 3 treatments of reference, for which experts agreed on the expected association with mortality. We then demonstrated its clinical relevance by screening all drugs prescribed in more than 100 patients to generate pharmacological hypotheses.

RESULTS

A total of 5783 patients were included in the analysis. The median age at admission was 69.2 (IQR 56.7-81.1) years, and 3390 (58.62%) of the patients were male. The performance of our automated pipeline was comparable or better for controlling bias than the knowledge-based adjustment set for 3 reference drugs: dexamethasone, phloroglucinol, and paracetamol. After correction for multiple testing, 4 drugs were associated with increased in-hospital mortality. Among these, diazepam and tramadol were the only ones not discarded by automated diagnostics, with adjusted odds ratios of 2.51 (95% CI 1.52-4.16, Q=.1) and 1.94 (95% CI 1.32-2.85, Q=.02), respectively.

CONCLUSIONS

Our innovative approach proved useful in generating pharmacological hypotheses in an outbreak setting, without requiring a priori knowledge of the disease. Our systematic analysis of early prescribed treatments from patients hospitalized for COVID-19 showed that diazepam and tramadol are associated with increased 28-day mortality. Whether these drugs could worsen COVID-19 needs to be further assessed.

Clinical outcomes of hypertensive patients with COVID-19 receiving calcium channel blockers: a systematic review and meta-analysis

We aimed to perform a systematic review and meta-analysis to determine the overall effect of the preadmission/prediagnosis use of calcium channel blockers (CCBs) on the clinical outcomes in hypertensive patients with COVID-19. A systematic literature search with no language restriction was conducted in electronic databases in July 2021 to identify eligible studies. A random-effects model was used to estimate the pooled summary measure for outcomes of interest with the preadmission/prediagnosis use of CCBs relative to the nonuse of CCBs at 95% confidence intervals (CIs). The meta-analysis revealed a significant reduction in the odds of all-cause mortality with the preadmission/prediagnosis use of CCBs relative to the nonuse of CCBs (pooled OR = 0.65; 95% CI 0.49-0.86) and a significant reduction in the odds of severe illness with preadmission/prediagnosis use of CCBs relative to the nonuse of CCBs (pooled OR = 0.61; 95% CI 0.44-0.84), and is associated with adequate evidence to reject the model hypothesis of 'no significant difference' at the current sample size. The potential protective effects offered by CCBs in hypertensive patients with COVID-19 merit large-scale prospective investigations.