Zhang D, et al. J Korean Med Sci. 2023 Apr;38(15):e120. https://doi.org/10.3346/jkms.2023.38.e120

This study aimed to evaluate the clinical value of metagenomic next-generation sequencing (mNGS) in patients with suspected lower respiratory tract infections. This retrospective study reviewed patients with suspected lower respiratory tract infections at the Wuhan Union Hospital. Data including demographic, laboratory, and radiological profiles; treatment; and outcomes were recorded and analyzed. mNGS identified pathogenic microbes in 100/140 (71.4%) patients, although 135 (96.4%) had received empiric antibiotic treatment before the mNGS tests. Single bacterial infection (35/100, 35%) was the most common type of infection in patients with positive mNGS results, followed by single fungal infection (14/100, 14%), bacterial-viral coinfection (14/100, 14%), single viral infection (12/100, 12%), bacterial-fungal coinfection (9/100, 9%), fungal-viral coinfection (9/100, 9%), and bacterial-fungal-viral coinfection (7/100, 7%). Moreover, compared with culture test, mNGS showed higher sensitivity (63/85, 74.1% vs 22/85, 25.9% P = 0.001) and lower processing time (24 hours vs 48 hours). Antibiotic treatment was adjusted or confirmed based on the mNGS results in 123 (87.9%) patients, including five (3.6%), 33 (23.6%), and 85 (60.7%) patients, in whom treatment was downgraded, upgraded, and unchanged, respectively. Almost all patients, regardless of escalation, de-escalation, or no change in treatment, showed significant improvement in clinical symptoms and inflammatory indicators. In addition, 17 (12.1%) patients were referred to Wuhan Pulmonary Hospital for further treatment because of confirmed or suspected tuberculosis. mNGS could be a promising technique for microbiological diagnosis and antibiotic management, potentially improving outcomes for patients.

Both regulatory T cells (Tregs) and T helper IL-17-producing cells (Th17 cells) have been found to be involved in human malignancies, however, the possible implication of Tregs in regulating generation and differentiation of Th17 cells in malignant pleural effusion remains to be elucidated.

The objective of the present study was to investigate the presence of interleukin (IL)-27 in pleural effusions and to evaluate the diagnostic significance of pleural IL-27. The concentrations of IL-27 were determined in pleural fluids and sera from 68 patients with tuberculous pleural effusion, 63 malignant pleural effusion, 22 infectious pleural effusion, and 21 transudative pleural effusion. Flow cytometry was used to identify which pleural cell types expressed IL-27. It was found that the concentrations of pleural IL-27 in tuberculous group were significantly higher than those in malignant, infectious, and transudative groups, respectively. Pleural CD4⁺ T cells, CD8⁺ T cells, NK cells, NKT cells, B cells, monocytes, macrophages, and mesothelial cells might be the cell sources for IL-27. IL-27 levels could be used for diagnostic purpose for tuberculous pleural effusion, with the cut off value of 1,007 ng/L, IL-27 had a sensitivity of 92.7% and specificity of 99.1% for differential diagnosing tuberculous pleural effusion from non-tuberculous pleural effusions. Therefore, compared to non-tuberculous pleural effusions, IL-27 appeared to be increased in tuberculous pleural effusion. IL-27 in pleural fluid is a sensitive and specific biomarker for the differential diagnosing tuberculous pleural effusion from pleural effusions with the other causes.

Background: The 2019 novel coronavirus disease (COVID-19) emerged in Wuhan, Hubei province, China, and was characterized as pandemic by the World Health Organization. Diabetes mellitus is an established risk factor for poor clinical outcomes, but the association of diabetes with the prognosis of COVID-19 have not been reported yet. Methods: In this cohort study, we retrospectively reviewed 258 consecutive hospitalized COVID-19 patients with or without diabetes at the West Court of Union Hospital of Huazhong University of Science and Technology in Wuhan, China, recruited from January 29 to February 12, 2020. The cases were confirmed by real-time PCR and the demographic, clinical, laboratory, radiological, and treatment data were collected and analyzed. Prognosis was defined as hospitalization, discharged survivor and death, which was followed up until March 12, 2020. Results: Of the 258 hospitalized patients (63 with diabetes) with COVID-19, the median age was 64 years (range 23-91), and 138 (53.5%) were male. No significant differences in age and sex were identified between patients with and without diabetes. Common symptoms included fever (82.2%), dry cough (67.1%), polypnea (48.1%), and fatigue (38%). Patients with diabetes had significantly higher leucocyte and neutrophil counts, and higher levels of fasting blood glucose, serum creatinine, urea nitrogen and creatine kinase isoenzyme MB at admission compared with those without diabetes. COVID-19 patients with diabetes were more likely to develop severe or critical disease condition with more complications at presentation, and had higher incidence rates of antibiotic therapy, non-invasive and invasive mechanical ventilation, and death (11.1% vs. 4.1%). Cox proportional hazard model showed that diabetes (adjusted hazard ratio [aHR]=3.64; 95% confidence interval [CI]: 1.09, 12.21) and fasting blood glucose (aHR=1.19; 95% CI: 1.08, 1.31) were associated with the fatality of COVID-19, adjusting for potential confounders. Conclusions: Diabetes mellitus is associated with greater disease severity and a higher risk of mortality in patients with COVID-19. Primary and secondary prevention strategies are needed for COVID-19 patients with diabetes.

Background: The mortality rate from acute respiratory distress syndrome (ARDS) is high among hospitalized patients with coronavirus disease 2019 (COVID-19). Hence, risk evaluation tools are required to immediately identify high-risk patients upon admission for early intervention. Methods: A cohort of 220 consecutive patients with COVID-19 were included in this study. To analyze the risk factors of ARDS, data obtained from approximately 70% of the participants were randomly selected and used as training dataset to establish a logistic regression model. Meanwhile, data obtained from the remaining 30% of the participants were used as test dataset to validate the effect of the model. Results: Lactate dehydrogenase, blood urea nitrogen, D-dimer, procalcitonin, and ferritin levels were included in the risk score system and were assigned a score of 25, 15, 34, 20, and 24, respectively. The cutoff value for the total score was > 35, with a sensitivity of 100.00% and specificity of 81.20%. The area under the receiver operating characteristic curve and the Hosmer–Lemeshow test were 0.967 (95% confidence interval [CI]: 0.925–0.989) and 0.437(P Value = 0.437). The model had excellent discrimination and calibration during internal validation. Conclusions: The novel risk score may be a valuable risk evaluation tool for screening patients with COVID-19 who are at high risk of ARDS.