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Aim: To study the microecological characteristics of the airway and similarities and differences between healthy people and patients with the acute exacerbation of chronic obstructive pulmonary disease (AECOPD) in Inner Mongolia, and analyze the correlation between the characteristics of the airway microecological structure and clinical indicators of AECOPD patients. Methods: Sputum samples from 36 healthy volunteers and 34 patients with AECOPD were detected by 16S rDNA high-throughput sequencing, and the airway microecological characteristics of healthy people and AECOPD patients were revealed by an alpha diversity analysis, beta diversity analysis, and LefSe difference analysis. Results: There were differences in the airway microecological structure between healthy people and AECOPD patients in Inner Mongolia. The airway microbiota composition of AECOPD patients showed an increase in the abundance of common pathogens and a decrease in the abundance of commensal bacteria, and the airway microbial diversity in AECOPD patients was lower than that in healthy people. Long-term use of inhaled glucocorticoid + long-acting ß2 agonist mixture (ICS + LABA), procalcitonin (PCT), blood monocyte count (MONO), hemoglobin (HGB), D-dimer (D-D), and body temperature were negatively correlated with the alpha diversity of the airway micro-ecosystem. Conclusion: The airway microecological composition of the AECOPD population in Inner Mongolia was different from that of the healthy population, and the airway microecological diversity was lower than that of the healthy population. The long-term use of ICS + LABA preparation by patients with AECOPD leads to lower alpha diversity. Alpha diversity was negatively correlated with inflammatory markers (PCT, MONO, D-dimer, body temperature) and HGB in AECOPD patients.
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Background and Objectives: Although the pathogenesis and treatment of coronavirus disease 2019 (COVID-19) have been gradually revealed, the risk for re-emergence of coronavirus nucleic acids in recovered patients remains poorly understood. Hence, this study evaluated the risk predictors associated with re-positivity for virus nucleic acid. Methods: Between February 1 and March 20, 2020, we retrospectively reviewed the clinical epidemiological data of 129 COVID-19 patients who were treated at Zhongxiang People's Hospital of Hubei Province in China. Subsequently, a risk prediction model for the re-positivity of virus nucleic acid was developed, and a receiver operating characteristic (ROC) curve was drawn for further validation. Results: In this study, the rate of re-positivity for virus nucleic acid was 17.8% (23/129) where all re-positivity cases were asymptomatic. The median time interval from discharge to nucleic acid re-positivity to discharge after being cured again was 11.5 days (range: 7-23 days). Multivariate logistic regression analysis showed that leukocytopenia [odds ratio (OR) 7.316, 95% confidence interval (CI) 2.319-23.080, p = 0.001], prealbumin < 150 mg/L (OR 4.199, 95% CI 1.461-12.071, p = 0.008), and hyperpyrexia (body temperature >39°C, OR 4.643, 95% CI 1.426-15.117, p = 0.011) were independent risk factors associated with re-positivity. The area under the ROC curve was 0.815 (95% CI, 0.729-0.902). Conclusion: COVID-19 patients with leukocytopenia, low prealbumin level, and hyperpyrexia are more likely to test positive for virus nucleic acid after discharge. Timely and effective treatment and appropriate extension of hospital stays and quarantine periods may be feasible strategies for managing such patients.