Introduction

The coronavirus disease (COVID-19) pandemic is causing a global crisis. COVID-19 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with consequences ranging from asymptomatic disease to death1. However, 14% of SARS-CoV-2-positive patients show severe disease, and 5% show critical health conditions2; the risk of mortality (0.1%) associated with COVID-19 is much higher than that associated with seasonal influenza3. Various risk factors such as age ≥ 65 years, chronic obstructive pulmonary disease (COPD), asthma, hypertension, cardiovascular disease, chronic kidney disease, diabetes, obesity, malignancy, immunosuppressant use and transplantation, and chronic human immunodeficiency virus (HIV) infection have been identified3. In addition, patients with a mental illness were also shown to have a higher risk for severe COVID-19 outcomes4,5.

Benzodiazepines (BZD) and BZD receptor agonists have been known to increase the risk of pneumonia and death due to pneumonia6,7. There is also concern about the risk of respiratory depression by BZD use in people with pre-existing respiratory problems, although reports have been conflicting; an increased risk of respiratory exacerbations was reported for patients with COPD8, while associations of BZD use with hospital admission or impaired blood gases were not significant in COPD patients9. A few recent studies on the characteristics of severe COVID-19 cases10,11,12 have focused on the use of BZD. However, the results have been inconsistent.

BZD were developed and have been widely prescribed for treating anxiety and insomnia, however, recent studies on the prescription trends have shown that BZD use has been increased for so many different indications13,14. Given the high prevalence (2.6–23.7%) of BZD use14,15,16,17,18,19, investigating the impact of BZD use on infection or clinical outcomes of SARS-CoV-2 is beneficial for public health. Here, we assessed the association of BZD use with SARS-CoV-2 positivity and clinical outcomes in three groups of patients, those in need of hospital admission, those with severe symptoms requiring intensive care, and those who died, using a nationwide cohort data from South Korea.

Methods

Study design and population

In this study, National Health Information Database (NHID)-COVID data provided by the National Health Insurance Service (NHIS) were used; data pertaining to the period from 2015 to 2020 were obtained. The dataset included data from patients with COVID-19 who tested positive from January 1 to May 30, 2020. Control groups included general controls and subjects who showed negative SARS-CoV-2 test results.

There are two different study population in this study. Study population 1 is to examine the association between benzodiazepine use and SARS-CoV-2 test positivity, and study population 2 is to investigate the association between benzodiazepine use and clinical outcomes in SARS-CoV-2-positive patients. The initial population for the year 2020 included a total of 351,377 subjects. These were categorized into 8070 patients with SARS-CoV-2, and 343,307 controls. After excluding those with missing values, 328,373 subjects remained. They were divided into two different groups according to whether BZD was used or not: 52,151 subjects used BZD and 276,222 subjects did not use BZD. Using the 1:1 propensity score matching (PSM) method, 52,151 participants each from the case group and the control group were selected as the final study subjects (out of a total of 104,302 subjects). In addition, a total of 7596 patients with COVID-19 were divided into two groups according to whether BZD used or not: 1074 subjects used BZD and 6522 subjects did not use BZD (Fig. 1).

Figure 1
figure 1

Flowchart showing the selection of the study population. NHID-COVID National Health Information Database-Coronavirus disease, SARS-CoV-2 severe acute respiratory syndrome coronavirus 2.

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Measures

Outcome variables

In this study, we set SARS-Cov-2 test positivity and clinical outcomes as the outcome variables. The clinical outcomes for SARS-CoV-2-positive patients consisted of three variables: hospital admission, severe symptoms requiring intensive care or invasive ventilation, and mortality. There have been cases of patients who died before receiving hospital care. They did not receive any treatment according to the data records, however, it was assumed that they needed treatment after SARS-CoV-2 infection but died before receiving it. Therefore, they were included in the group that required hospital admission.

Variables of interest

The study subjects were divided into two groups according to BZD use. Use of BZD was defined based on claim history in 2019, one year before the outbreak of COVID-19 in 2020.

BZD categories were based on the following main ingredient codes: clobazam (135702ATB), clonazepam (136401ATB), chlordiazepoxide (131201ATB, 131202ATB, 255800ATB), diazepam (142930BIJ), flunitrazepam (160601ATB), flurazepam (161801ATB), ethyl loflazepate (156201ATB, 156202ATB), alprazolam (105501ATB, 105502ATB, 105504ATB, 105505ATB, 105507ATB), bromazepam (118501ATB), clotiazepam (137302ATB), etizolam (156501ATB, 156502ATB, 156503ATB), lorazepam (185501ATB, 185504ATB), tofisopam (241201ATB), and triazolam (243501ATB, 243502ATB). In addition, chronic BZD use was categorized based on a 90-day usage period and a 180-day usage period within a year14,20.

Covariates

In this study, we adjusted for variables that could directly or indirectly affect outcomes, including basic independent variables such as sex, age, and residential area. The residential areas were grouped based on the major regions and the metropolitan areas where the incidence of COVID-19 was high in Korea at that time. Gyeonggi-do province is the metropolitan area that surrounds Seoul, and Gyeongbuk province and Daegu city are the regions that caused a social issue due to a cluster infection related to the COVID-19 outbreak. Accordingly, Seoul, Gyeonggi-do, Gyeongbuk, and Daegu were classified into each group, and the rest of the regions were combined into a single group. Type of insurance coverage was classified into three different groups: workplace, local, and medical benefits. Participants’ clinical baseline characteristics were also considered as covariates. The Charlson Comorbidity Index (CCI) was used to confirm the patients’ comorbidity status in 2019, which was the year prior to the COVID-19 outbreak. Based on CCI data, the severity of comorbidity was categorized as 0, 1, or 2+. Additionally, we reviewed the disease records for the period from 2015 to 2018 for diabetes, cardiovascular disease, cerebrovascular disease, COPD, asthma, hypertension, and chronic kidney disease, which could be associated with worse clinical outcomes and BZD use.

Statistical analysis

We investigated the results after 1:1 PSM; in this method, the case and control participants who have a similar propensity score values are matched21. We matched case and control groups by including age, sex, and CCI variables as parameters in the propensity score model. The association between BZD use and SARS-CoV-2 positivity was examined in a total of five models. Model 1 was a crude model for the association between BZD use and SARS-CoV-2 positivity; model 2 was a minimally adjusted model adjusted for age and sex; model 3 was the fully adjusted model, which was adjusted for age, sex, residential area, type of insurance coverage, CCI, and disease history (diabetes, cardiovascular disease, cerebrovascular disease, COPD, asthma, hypertension, and chronic kidney disease); model 4 was the fully adjusted model for the association between the chronic use of BZD for 90 days and SARS-CoV-2 positivity; and model 5 was the fully adjusted model for the association between the chronic use of BZD for 180 days and SARS-CoV-2 positivity. Among patients who tested positive for SARS-CoV-2, Pearson's chi-square tests were used to compare the sociodemographic and clinical characteristics with respect to BZD use and chronic BZD use. To examine the association of BZD use and the chronic BZD use with the risk of SARS-CoV-2 positivity and clinical outcomes, we used multivariable logistic regression models after adjusting for sex, age, residential area, CCI, and disease history.

All the statistical analyses were performed using SAS statistical software version 9.4 (Statistical Analysis System Institute, Cary, NC, USA).

Ethics approval and consent to participate

The data were anonymized before they were obtained; thus, informed consent was not required. The Yonsei University Institutional Review Board approved this study (Approval number: 4-2020-1240). All methods were performed in accordance with the relevant guidelines and regulations.

Results

The characteristics of the study participants are shown in Table 1. A total of 328,373 individuals were divided into two groups as follows: those who did not use BZD (n = 276,222) and those who used BZD (n = 52,151). The two groups were matched by propensity scoring, and 52,151 propensity-matched pairs were defined (eTable S1). Of the total subjects, 145,758 (44.4%) were men and 182,615 (55.6%) were women. A majority of the participants (84.1%) was aged 20–39 years; 31.1% were in the 40–59 age group. Comorbidities were recorded in 193,945 (59.1%) individuals, while no comorbidities were observed in 134,428 (40.9%) individuals.

Table 1 General characteristics of the study population.
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Table 2 shows the association between BZD use and the risk of SARS-CoV-2 positivity; we identified these associations before and after adjusting for potential confounders. After PSM, there was no association between BZD use and the risk of SARS-CoV-2 positivity (model 1: odds ratio [OR]: 1.01, 95% confidence interval [CI] 0.93–1.10, model 2: OR: 1.01, 95% CI 0.93–1.10, model 3: OR: 1.09, 95% CI 1.00–1.20). Moreover, model 4 and 5 showed that there were no associations between chronic BZD use and the risk of SARS-CoV-2 positivity (model 4: OR: 0.94, CI 0.81–1.10, model 5: OR: 0.99, CI 0.83–1.18).

Table 2 The results of the analysis of the association between benzodiazepine use and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positivity after 1:1 propensity score matching.
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Table 3 shows the distribution of the study population who tested positive for SARS-CoV-2. Of 7596 individuals, 1074 (14.1%) used BZD and 6522 (85.9%) did not use BZD. A total of 6019 individuals who were in need of hospitalization, 939 (15.6%) individuals used BZD. A total of 464 individuals who were in need of intensive care or invasive ventilation, 111 (23.9%) individuals used BZD. A total of 233 individuals who died, 59 (25.3%) individuals used BZD.

Table 3 General characteristics of the patients who tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).
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Figure 2 shows the association between BZD use and the clinical outcomes of COVID-19 among patients who tested positive for SARS-CoV-2. After adjusting for potential cofounding variables, the risk of need for hospitalization due to COVID-19 was higher in those with BZD use that in those without BZD use (OR: 1.33, 95% CI 1.07–1.65). In addition, the risk of need for hospitalization was higher in COVID-19 patients who used BZD for more than 180 days than in those who did not use BZD (OR: 2.64, 95% CI 1.08–6.47).

Figure 2
figure 2

The results of the analysis of the association between benzodiazepine use and clinical outcomes. BZD benzodiazepine.

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Discussion

Using a nationwide cohort database from South Korea, in this study, we showed that the chronic use of BZD contributed to an increase in the risk of the need for hospitalization among COVID-19 patients. However, BZD use did not significantly influence the risk of SARS-CoV-2 positivity, severe outcomes, or mortality.

In animal studies, BZD increased mortality due to a variety of bacterial infections22,23,24,25 and bacterial superinfections related to influenza22. In human subjects, controversy persists regarding a causal connection between BZD use and infections26. The association between BZD use and the increased need for hospitalization in this study may be in line with previous studies which showed increased susceptibility to superinfections in influenza-infected animals27 and humans7. The underlying mechanism may be related to the effects of BZD on the immune system; BZD amplifies the effect of the gamma-aminobutyric acid receptor in immune cells, which may lead to an immune-suppressant profile27. Regarding the long term use of BZD, chronic consumption of BZD was related to the appearance of modified lymphocyte subsets28,29. However, relatively few cases of severe COVID-19 and inaccessible variables in our data, such as the dosage of BZD or the difference of health-related behaviors between short-term and chronic BZD users, may require replication of pharmacoepidemiologic research on the relationship between BZD and COVID-19.

Recent studies on the association between mental illness and COVID-19 outcomes have shown a higher risk for severe COVID-19 outcomes in patients with a mental illness, though the analyses did not include adjustment for BZD use4,5. Since BZD is frequently prescribed for anxiety symptoms and sleep disturbances, our findings suggest that BZD use should be considered in further studies on the relationship between mental illness and COVID-19 outcomes. Likewise, adjusting for mental illness in future studies in the association between BZD and COVID-19 outcomes would uncover the risk of BZD use regardless of psychiatric diagnoses. However, it is interesting to note that 87.7% of BZD prescriptions were related to non-psychiatric diagnoses in a nationwide cohort study from South Korea14.

Due to limited medical resources, especially with reference to negative pressure beds, policies on the priority for hospitalization among COVID-19 patients have been amended. For example, South Korea has introduced a residential treatment center to isolate asymptomatic patients or patients who do not need hospital care. Therefore, patients with moderate-to-severe symptoms may be hospitalized first30. In this regard, the results of this nationwide cohort study may be applied to efficiently set strategies for managing COVID-19 patients, based the finding that patients with chronic BZD use need to be monitored frequently due to a high risk of need for hospitalization; however, the strategies should also consider our finding that BZD use does not imply increased severity of clinical outcomes related to COVID-19.

The use of nationwide longitudinal data strengthens the causal relationship established in our study, and the generalizability of our findings, however, some limitations of this study should be acknowledged. First, although a validation study showed the overall agreement of diagnosis at 82.0%31, outcomes were identified by diagnostic and procedural codes, and possible misclassifications cannot be ruled out. Second, data about the indication and BZD dose, as well as the hospitalization period were unavailable, which precluded a full assessment. Especially, since BZD have been prescribed for many indications besides anxiety and insomnia, further studies accessing reasons for BZD uses would help in interpretation of the data. Second, although we adjusted multivariable logistic regression models for the CCI and disease history (diabetes, cardiovascular disease, cerebrovascular disease, COPD, asthma, hypertension, and chronic kidney disease), the result should be interpreted with caution because comorbidities, which may affect prognosis and survival, were recorded in 59.1% of participants in this study. Third, obesity, which is one of the identified risk factors of severe clinical outcomes, was not included in our analyses. In the data we used in this study, body mass index (BMI) can be observed through the results of the patient's health screening questionnaire, but the data on the health screening is not only incomplete but also difficult to actually use it for analysis. For example, the timing and interval of the participants’ health screening varies. Fourth, since the organization in charge of NHIS-COVID data only allowed researchers to extract data for the period that we analyzed in this study, we could not include all the COVID-19 patients up to the present. Thus, we may have missed analyzing new clinical outcomes that may have resulted due to various mutations in SARS-CoV-2. Further studies including the type of mutations in SARS-CoV-2 and the vaccination status of participants could provide a more thorough understanding of the relationship between BZD use and clinical outcomes.

In summary, BZD use was not associated with the risk of SARS-CoV-2 positivity, severe outcomes, or mortality. However, BZD use, especially for more than 180 days, conferred a higher risk of need for hospitalization among COVID-19 patients. Health professionals and public health authorities need to be alert about patients with long-term use of BZD, and these patients need to be closely monitored even if they currently do not need hospital care.