The severe acute respiratory syndrome coronavirus 2 is known to infect host cells by interacting with ACE2 (angiotensin-converting enzyme 2) expressed in the respiratory epithelium. There have been concerns on whether alterations of ACE2 expression by renin-angiotensin-aldosterone system (RAAS) inhibitors would contribute to the infectivity and severity of coronavirus disease 2019 (COVID-19). We performed a case-control study to investigate the association between RAAS inhibitors and risk and severity of COVID-19 infection in South Korea using the population-based data provided by the Korean National Health Insurance System. Of 16 281 subjects with hypertension, there were 950 (5.8%) confirmed COVID-19 cases. After case-control matching, multivariable-adjusted conditional logistic regression analysis was performed. The adjusted odds ratio and 95% CIs for COVID-19 infection and long-term hospitalization comparing exposure to RAAS inhibitors and nonexposure to RAAS inhibitors was 1.161 (0.958–1.407) and 0.863 (0.533–1.397), respectively. When comparing exposure to RAAS inhibitors and nonexposure to RAAS inhibitors for intensive care unit admission, high-flow oxygen therapy, and death, the adjusted odds ratios (95% CIs) were 1.515 (0.402–5.701), 0.663 (0.272–1.619), and 1.363 (0.513–3.662), respectively. In all analyses, P values were not significant ( P >0.05). The present study demonstrates the absence of an identifiable association between the exposure to RAAS inhibitors and risk and severity of COVID-19 infection, supporting the current medical guidelines and recommendations that patients should not discontinue RAAS inhibitors out of a concern that they are at increased risk for infection or severe illness of COVID-19.

Early identification of pneumonia is essential in patients with acute febrile respiratory illness (FRI). We evaluated the performance and added value of a commercial deep learning (DL) algorithm in detecting pneumonia on chest radiographs (CRs) of patients visiting the emergency department (ED) with acute FRI. This single-centre, retrospective study included 377 consecutive patients who visited the ED and the resulting 387 CRs in August 2018–January 2019. The performance of a DL algorithm in detection of pneumonia on CRs was evaluated based on area under the receiver operating characteristics (AUROC) curves, sensitivity, specificity, negative predictive values (NPVs), and positive predictive values (PPVs). Three ED physicians independently reviewed CRs with observer performance test to detect pneumonia, which was re-evaluated with the algorithm eight weeks later. AUROC, sensitivity, and specificity measurements were compared between “DL algorithm” vs. “physicians-only” and between “physicians-only” vs. “physicians aided with the algorithm”. Among 377 patients, 83 (22.0%) had pneumonia. AUROC, sensitivity, specificity, PPV, and NPV of the algorithm for detection of pneumonia on CRs were 0.861, 58.3%, 94.4%, 74.2%, and 89.1%, respectively. For the detection of ‘visible pneumonia on CR’ (60 CRs from 59 patients), AUROC, sensitivity, specificity, PPV, and NPV were 0.940, 81.7%, 94.4%, 74.2%, and 96.3%, respectively. In the observer performance test, the algorithm performed better than the physicians for pneumonia (AUROC, 0.861 vs. 0.788, p = 0.017; specificity, 94.4% vs. 88.7%, p < 0.0001) and visible pneumonia (AUROC, 0.940 vs. 0.871, p = 0.007; sensitivity, 81.7% vs. 73.9%, p = 0.034; specificity, 94.4% vs. 88.7%, p < 0.0001). Detection of pneumonia (sensitivity, 82.2% vs. 53.2%, p = 0.008; specificity, 98.1% vs. 88.7%; p < 0.0001) and ‘visible pneumonia’ (sensitivity, 82.2% vs. 73.9%, p = 0.014; specificity, 98.1% vs. 88.7%, p < 0.0001) significantly improved when the algorithm was used by the physicians. Mean reading time for the physicians decreased from 165 to 101 min with the assistance of the algorithm. Thus, the DL algorithm showed a better diagnosis of pneumonia, particularly visible pneumonia on CR, and improved diagnosis by ED physicians in patients with acute FRI.

Objectives Despite the growing pieces of evidence linking hyperuricemia with metabolic syndrome and cardiovascular disease, the relationship between dyslipidemia and serum uric acid has not yet been established. This study aimed to investigate the association between individual components of dyslipidemia and serum uric acid by using the nationally representative Korea National Health and Nutrition Examination Survey 2016-2017. Methods A total of 8,722 participants (age � 19 years) without missing values were analyzed for this study. Serum uric acid levels according to the presence of individual dyslipidemia components were calculated using multivariable-adjusted general linear models (GLM). Odds ratios of individual dyslipidemia components to hyperuricemia were calculated using unadjusted and multivariable-adjusted logistic regression analysis. Results A total of 1,061 participants were identified as having hyperuricemia, with a prevalence of 12.2%. Multivariable-adjusted GLM demonstrated a significant trend between individual dyslipidemia components and serum uric acid levels (P < 0.05). A positive association between the numbers of dyslipidemia components and the increments of serum uric acid levels was also observed (P < 0.001). In multivariable-adjusted logistic regression analysis, odds ratios (OR) and 95% confidence interval (CI) of all dyslipidemia components to hyperuricemia were shown to be statistically significant (P < 0.05). When further adjusted for the combined components themselves, each 10 mg/dL increments of total cholesterol (OR

BackgroundRituximab plus cyclophosphamide, vincristine, and prednisone (R-CVP) is one of the effective chemotherapeutic regimens for patients with advanced stage marginal zone lymphoma (MZL). However, prognostic factors that affect the outcome of treatment for MZL are not well understood.MethodsBetween August 2006 and June 2013, patients with newly diagnosed stage III and IV MZL treated with R-CVP as a first-line therapy from 15 institutions were retrospectively analyzed. Patients' clinical and laboratory data at diagnosis were collected by review of medical records.ResultsA total of 80 patients were analyzed. Bone marrow involvement was observed in 30% cases. Twelve patients (15%) had nodal MZL, and 41.3% patients exhibited multiple mucosa-associated lymphoma tissue sites. Overall response rate was 91.3%, including 73.8% achieving complete response. Advanced MZL patients treated with R-CVP showed a 3-year progression-free survival (PFS) rate of 69.6%. Prognostic markers significantly affecting PFS in univariate analysis were platelet to lymphocyte ratio (PLR, <95 vs. ≥95, P=0.014), serum albumin (≤3.9 vs. >3.9 g/dL, P=0.008), and the International Prognostic Index (IPI) score (1 vs. 2–4, P=0.032). In multivariate analysis, only PLR (<95 vs. ≥95, HR 0.367, 95% CI, 0.139–0.971, P=0.043) was an independent risk factor for PFS.ConclusionPLR ≥95 at diagnosis is an independent prognostic marker for PFS in advanced stage MZL patients treated with R-CVP. This marker may aid clinicians in predicting the response to R-CVP chemotherapy in stage III and IV MZL patients.

Background/Aims Since the onset of the coronavirus disease 2019 (COVID-19) pandemic, there have been concerns about the association between exposure to renin-angiotensin-aldosterone system (RAAS) inhibitors and the risk and severity of COVID-19. Methods We performed a case-control study that utilized up-to-date data on the South Korean population provided by the Korean National Health Insurance System. Of the 62,909 patients with hypertension or heart failure tested for COVID-19, there were 1,644 (2.6%) confirmed cases. After case-control matching, multivariable-adjusted conditional logistic regression analysis was performed. Results Comparison between patients exposed to RAAS inhibitors and those not exposed to RAAS inhibitors revealed that the adjusted odds ratio (OR) and 95% confidence interval (95% CI) for COVID-19 infection and death were 0.981 (0.849-1.135) and 0.875 (0.548-1.396), respectively. Subgroup analysis for the major confounders, age and region of diagnosis, resulted in OR and 95% CI of 0.912 (0.751-1.108) and 0.942 (0.791-1.121), respectively. Conclusions The present study demonstrated no evidence of association between RAAS inhibitor exposure and risk and severity of COVID-19.