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Background@#Although coronavirus disease 2019 (COVID-19) is a viral infection, antibiotics are often prescribed due to concerns about accompanying bacterial infection. Therefore, we aimed to analyze the number of patients with COVID-19 who received antibiotic prescriptions, as well as factors that influenced antibiotics prescription, using the National Health Insurance System database. @*Methods@#We retrospectively reviewed claims data for adults aged ≥ 19 years hospitalized for COVID-19 from December 1, 2019 to December 31, 2020. According to the National Institutes of Health guidelines for severity classification, we calculated the proportion of patients who received antibiotics and the number of days of therapy per 1,000 patient-days. Factors contributing to antibiotic use were determined using linear regression analysis. In addition, antibiotic prescription data for patients with influenza hospitalized from 2018 to 2021 were compared with those for patients with COVID-19, using an integrated database from Korea Disease Control and Prevention Agency-COVID19-National Health Insurance Service cohort (K-COV-N cohort), which was partially adjusted and obtained from October 2020 to December 2021. @*Results@#Of the 55,228 patients, 46.6% were males, 55.9% were aged ≥ 50 years, and most patients (88.7%) had no underlying diseases. The majority (84.3%; n = 46,576) were classified as having mild-to-moderate illness, with 11.2% (n = 6,168) and 4.5% (n = 2,484) having severe and critical illness, respectively. Antibiotics were prescribed to 27.3% (n = 15,081) of the total study population, and to 73.8%, 87.6%, and 17.9% of patients with severe, critical, and mild-to-moderate illness, respectively. Fluoroquinolones were the most commonly prescribed antibiotics (15.1%; n = 8,348), followed by third-generation cephalosporins (10.4%; n = 5,729) and beta-lactam/beta-lactamase inhibitors (6.9%; n = 3,822). Older age, COVID-19 severity, and underlying medical conditions contributed significantly to antibiotic prescription requirement. The antibiotic use rate was higher in the influenza group (57.1%) than in the total COVID-19 patient group (21.2%), and higher in severe-to-critical COVID-19 cases (66.6%) than in influenza cases. @*Conclusion@#Although most patients with COVID-19 had mild to moderate illness, more than a quarter were prescribed antibiotics. Judicious use of antibiotics is necessary for patients with COVID-19, considering the severity of disease and risk of bacterial co-infection.
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Purpose@#Long-term safety of pregnancy after breast cancer (BC) remains controversial, especially with respect to BC biological subtypes. @*Methods@#We analyzed a population-based retrospective cohort with BC from 2002 to 2017. Patient-level 1:1 matching was performed between pregnant and nonpregnant women. The study population was categorized into 6 biological subtypes based on the combination of prescribed therapies. Subanalyses were performed considering the time to pregnancy after BC diagnosis, systemic therapy, and pregnancy outcomes. @*Results@#We identified 544 matched women with BC, who were assigned to the pregnant (cases, n = 272) or nonpregnant group (controls, n = 272) of similar characteristics, adjusted for guaranteed bias. These patients were followed up for 10 years, or disease and mortality occurrence after the diagnosis of BC. Survival estimates were calculated. The actuarial 10-year overall survival (OS) rates were 97.4% and 91.9% for pregnant and nonpregnant patients, respectively. The pregnant group showed significantly better OS (adjusted hazard ratio [aHR], 0.29; 95% confidence interval [CI], 0.12–0.68; P = 0.005) and did not have a significantly inferior disease-free survival (aHR, 1.10; 95% CI, 0.61–1.99; P = 0.760). @*Conclusion@#Consistent outcomes were observed in every subgroup analysis. Our observational data provides reassuring evidence on the long-term safety of pregnancy in young patients with BC regardless of the BC biological subtype.
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Although obesity is a risk factor for infection, whether it has the same effect on coronavirus disease 2019 (COVID-19) need confirming. We conducted a retrospective propensity score matched case-control study to examine the association between obesity and COVID-19. This study included data from the Nationwide COVID-19 Registry and the Biennial Health Checkup database, until May 30, 2020. We identified 2,231 patients with confirmed COVID-19 and 10-fold-matched negative test controls. Overweight (body mass index [BMI] 23 to 24.9 kg/m2; adjusted odds ratio [aOR], 1.16; 95% confidence interval [CI], 1.1.03 to 1.30) and class 1 obesity (BMI 25 to 29.9 kg/m2; aOR, 1.27; 95% CI, 1.14 to 1.42) had significantly increased COVID-19 risk, while classes 2 and 3 obesity (BMI ≥30 kg/m2) showed similar but non-significant trend. Females and those <50 years had more robust association pattern. Overweight and obesity are possible risk factors of COVID-19.
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BackgroundThe coronavirus disease (COVID-19) pandemic is an emerging threat worldwide. It is still unclear how comorbidities affect the risk of infection and severity of COVID-19. MethodsA nationwide retrospective case-control study of 65,149 individuals, aged 18 years or older, whose medical cost for COVID-19 testing were claimed until April 8, 2020. The diagnosis of COVID-19 and severity of COVID-19 infection were identified from the reimbursement data using diagnosis codes and based on whether respiratory support was used, respectively. Odds ratios were estimated using multiple logistic regression, after adjusting for age, sex, region, healthcare utilization, and insurance status. ResultsThe COVID-19 group (5,172 of 65,149) was younger and showed higher proportion of females. 5.6% (293 of 5,172) of COVID-19 cases were severe. The severe COVID-19 group had older patients and a higher male ratio than the non-severe group. Cushing syndrome (Odds ratio range (ORR) 2.059-2.358), chronic renal disease (ORR 1.292-1.604), anemia (OR 1.132), bone marrow dysfunction (ORR 1.471-1.645), and schizophrenia (ORR 1.287-1.556) showed significant association with infection of COVID-19. In terms of severity, diabetes (OR 1.417, 95% CI 1.047-1.917), hypertension (OR 1.378, 95% CI 1.008-1.883), heart failure (ORR 1.562-1.730), chronic lower respiratory disease (ORR 1.361-1.413), non-infectious lower digestive system disease (ORR 1.361-1.418), rheumatoid arthritis (ORR 1.865-1.908), substance use (ORR 2.790-2.848), and schizophrenia (ORR 3.434-3.833) were related with severe COVID-19. ConclusionsWe identified several comorbidities associated with COVID-19. Health care workers should be more careful when diagnosing and treating COVID-19 when the patient has the above-mentioned comorbidities. Take Home messageComorbidities that might be associated with COVID-19 infection and severe clinical course were identified, which could assist in formulating public health measures to mitigate the risk in groups with increased risk.
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BackgroundIdentifying the association between medications taken prior to the infection of coronavirus disease (COVID-19) might be useful during the current pandemic until a proven treatment is developed. We aimed to determine whether the risk of developing COVID-19 was associated with the use of various drugs that may increase or decrease susceptibility to severe acute respiratory syndrome coronavirus 2 infection and COVID-19. Methods and FindingsA case-control study was performed using a nationwide claims database of South Korea, where a large testing capacity has been available throughout the pandemic. Exposure was defined as the prescription of study drugs that would have been continued until [≤]7 days before the testing for COVID-19. Adults were considered eligible if they were [≥]18 years old and tested for COVID-19. Among the 65,149 eligible subjects (mean age, 48.3 years; 49.4% male), 5,172 (7.9%) were diagnosed with COVID-19. Hydroxychloroquine was not significantly associated with the risk of COVID-19 (adjusted odds ratio [aOR], 1.48; 95% CI, 0.95-2.31). In the overall population, lower risks of COVID-19 were associated with the use of camostat (aOR, 0.45; 95% CI, 0.20-1.02) and amiodarone (aOR, 0.54; 95% CI, 0.33-0.89), although the differences were not significant in the subgroup analyses. Angiotensin receptor blockers were also associated with a slightly increased risk of COVID-19 (aOR, 1.13; 95% CI, 1.01-1.26), which was also not observed in the subgroup analysis. The study limitations include potential bias regarding the controls characteristics, inability to determine prescription compliance, and a lack of information regarding the severity of underlying conditions. ConclusionsNo medications were consistently associated with increased or decreased risks of COVID-19. These findings suggest that a more cautious approach is warranted for the clinical use of re-purposed drugs until the results are available from clinical trials.
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Background@#The coronavirus disease 2019 (COVID-19) pandemic is an emerging threat worldwide. It remains unclear how comorbidities affect the risk of infection and severity of COVID-19. @*Methods@#This is a nationwide retrospective case-control study of 219,961 individuals, aged 18 years or older, whose medical costs for COVID-19 testing were claimed until May 15, 2020. COVID-19 diagnosis and infection severity were identified from reimbursement data using diagnosis codes and on the basis of respiratory support use, respectively. Odds ratios (ORs) were estimated using multiple logistic regression, after adjusting for age, sex, region, healthcare utilization, and insurance status. @*Results@#The COVID-19 group (7,341 of 219,961) was young and had a high proportion of female. Overall, 13.0% (954 of 7,341) of the cases were severe. The severe COVID-19 group had older patients and a proportion of male ratio than did the non-severe group. Diabetes (odds ratio range [ORR], 1.206–1.254), osteoporosis (ORR, 1.128–1.157), rheumatoid arthritis (ORR, 1.207–1.244), substance use (ORR, 1.321–1.381), and schizophrenia (ORR, 1.614–1.721) showed significant association with COVID-19. In terms of severity, diabetes (OR, 1.247; 95% confidential interval, 1.009–1.543), hypertension (ORR, 1.245–1.317), chronic lower respiratory disease (ORR, 1.216–1.233), chronic renal failure, and end-stage renal disease (ORR, 2.052–2.178) were associated with severe COVID-19. @*Conclusion@#We identified several comorbidities associated with COVID-19. Health care workers should be more careful while diagnosing and treating COVID-19 when patients have the abovementioned comorbidities.
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BACKGROUND: The main factor limiting the increase in brain dead organ donors is low consent rates for organ donation. METHODS: This study is a retrospective analysis of donor records of Korea Organ Donation Agency from 2013 to 2015. Factors related before providing information about organ donation and process of explaining organ donation were analyzed. RESULTS: Donor gender, marital status, religious affiliation, residence area, knowledge of patients' wishes, understanding of brain death status, and the referring system, providing initial information about donation and initial medical staff providing information about donation had a significant influence on decision to donate. Organ donation greatly increased when the donor family knew the patient's intent to donate. As the degree of family understanding of brain death status and the referring system increased, organ donation rate significantly increased. CONCLUSIONS: Providing sufficient information about brain death during the period of delivering medical services as well as activating campaign and public education are essential to improving the positive attitude toward organ donation.