Since the beginning of the coronavirus disease 2019 (COVID-19) pandemic at the end of December 2019, more than 85% of the population in China has been infected. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mainly affects the respiratory system, especially the lungs. The mortality rate of patients with severe infection is high. A percentage of 6% to 10% of patients will eventually develop into COVID-related acute respiratory distress syndrome (CARDS), which requires mechanical ventilation and extracorporeal membrane oxygenation (ECMO) support. Some patients who survive acute lung injury will subsequently develop post COVID-19 pulmonary fibrosis (PCPF). Both fully treated CARDS and severe PCPF are suitable candidates for lung transplantation. Due to the special course, evaluation strategies are different from those used in patients with common end-stage lung disease. After lung transplantation in COVID-19 patients, special treatment is required, including standardized nucleic acid testing for the novel coronavirus, adjustment strategy of immunosuppressive drugs, and rational use of antiviral drugs, which is a big challenge for the postoperative management of lung transplantation. This consensus was evidence-based written and was reached by experts after multiple rounds of discussions, providing reference for assessment and postoperative management of patients with interstitial pneumonia after COVID-19 infection.
Objective To establish a short-term mortality risk scoring standard for sepsis-associated acute respiratory distress syndrome (sARDS) and provide a reference tool for clinicians to evaluate the severity of sARDS patients. Methods A retrospective cohort study was conducted on sARDS patients admitted to the adult intensive care unit (ICU) of the First Affiliated Hospital, Hengyang Medical School, University of South China from January 1, 2013 to August 31, 2020. They were divided into a death group and a survival group according to whether they died within 28 days after admission to ICU. Clinical data of the patients was collected within 24 hours admitted to ICU. Related risk factors for mortality within 28 days after admission to ICU were screened out through univariate logistic regression analysis. A risk prediction model for mortality within 28 days after admission to ICU was established by multivariate logistic regression analysis. The Hosmer-Lemeshow χ2 test and the area under the receiver operating characteristic (ROC) curve were used to evaluate the model’s goodness-fit and accuracy in predicting 28-day mortality of the sARDS patients, respectively. Finally, the clinical prognosis scoring criteria 28-day mortality of the sARDS patients were established according to the weight coefficients of each independent risk factor in the model. Results A total of 150 patients were recruited in this study. There were 67 patients in the survival group and 83 patients in the death group with a 28-day mortality rate of 55.3%. Four independent risk factors for 28-day mortality of the sARDS patients, including invasive mechanical ventilation, the number of dysfunctional organs≥3, serum lactic acid≥4.3 mmol/L and the severity of ARDS. A risk prediction model for mortality within 28 days of the sARDS patients was established. The area under the ROC curve and 95% confidence interval (CI), sensitivity and specificity of the risk prediction model for 28-day mortality for the sARDS patients were 0.896 (95%CI 0.846 - 0.945), 80.7% and 82.1%, respectively, while that for acute physiology and chronic health evaluation Ⅱ (APACHEⅡ) score were 0.865 (95%CI 0.805 - 0.925), 71.1% and 89.6%; for sequential organ failure assessment (SOFA) score were 0.841 (95%CI 0.7799 - 0.904), 68.7%, and 82.1%; for the prediction scores of lung injury were 0.855 (95%CI 0.789 - 0.921), 81.9% and 82.1%, respectively. It was indicated that the prediction accuracy of this risk prediction model of 28-day mortality maybe was better than that of APACHE-Ⅱ score, SOFA score and prediction score of lung injury. In addition, four risk factors were assigned as invasive mechanical ventilation (12 points), serum lactic acid≥4.3mmol /L (1 point), number of organs involved≥3 (3 points), and severity of ARDS (mild for 13 points, moderate for 26 points, severe for 39 points). Further more, the score of each patient was 13 - 55 points according to the scoring criteria, and the score grade was made according to the percentile method: 13 - 23 points for the low-risk group for 28-day mortality, 24 - 34 points for the medium-risk group for 28-day mortality, 35 - 45 points for the high-risk group for 28-day mortality, and over 45 points for the extremely high-risk group for 28-day mortality. According to the scoring criteria, the prognosis of the patients in this study was analyzed. The mortality probability of each group was 0.0% in the low-risk group, 13.8% in the medium-risk group, 51.9% in the high-risk group, and 89.7% in the extremely high-risk group, respectively. Conclusions The invasive mechanical ventilation, the number of involved organs≥3, serum lactic acid≥4.3 mmol /L and the severity of sARDS are independent risk factors for 28-day mortality of the sARDS patients. The scoring criteria may predict the risk of 28-day mortality for the sARDS patients.
Acute respiratory distress syndrome is one of the forms of respiratory failure that seriously threaten human life. It has the characteristics of very high morbidity, mortality and hospitalization costs. How to treat acute respiratory distress syndrome to improve the quality of life of patients is particularly important. Mechanical ventilation is an important treatment for acute respiratory distress syndrome. This article will review the progress in mechanical ventilation therapy for acute respiratory distress syndrome, including non-invasive mechanical ventilation and invasive mechanical ventilation (tidal volume, lung recruitment, positive end-expiratory pressure, prone position ventilation, and high-frequency oscillatory ventilation), aiming to provide basis and reference for future exploration of the treatment direction of acute respiratory distress syndrome.
Objective To investigated the early risk factors of AIDS severe pneumonia complicated with acute respiratory distress syndrome in order to carry out early recognition and intervention of ARDS and improve the prognosis of patients. Methods The clinical data of 232 patients with severe AIDS pneumonia admitted to Chengdu Public Health Clinical Medical Center from January 2017 to December 2020 were retrospectively analyzed, including general data, vital signs, laboratory examination indexes, basic diseases, etc. Firstly influential indexes for complicated with ARDS were screened by single factor logistic regression analysis, then the multicollinearity assessment indicators were filtered out in multi-factor logistic stepwise regression analysis, finally the receiver operating characteristic (ROC) curves were drawn and the predictive value of the indicators were assessed. Results Thirty-three of 232 AIDS patients with severe pneumonia were complicated with ARDS. The mortality rate in ARDS group was 81.8%. The intra-group mortality of non-ARDS group was 33.7%. Single factor logistic regression analysis showed that pH, acute physiology and chronic health evaluation Ⅱ grade, sequential organ failure assessment grade, white blood cell count, lactate dehydrogenase, α-hydroxybutyric acid dehydrogenase (α-HBDH), alanine aminotransferase (ALT), aspartic acid aminotransferase (AST), calcium, fibrinogen degradation produc (FDP) and D-dimer, total 11 indicators were associated with the incidence of ARDS. The multicollinearity analysis of the 11 indicators showed that there was no multicollinearity problem among the other 9 indicators except the variance inflation factor of ALT and AST which was greater than 10. Multivariate logistic stepwise regression analysis showed α-HBDH (OR=1.001, 95% confidence interval 1.000 - 1.002, P=0.045) and D-dimer (OR=1.044, 95% confidence interval 1.006 - 1.083, P=0.024) were independent factors. ROC curve indicated the following: alpha hydroxy butyric acid dehydrogenase (the area under ROC curve=0.667, P=0.002, the optimal threshold was 391 U/L, the corresponding sensitivity and specificity was 78.8% and 61.8%, respectively), D-dimer (the area under ROC curve=0.602, P=0.062, the optimal threshold was 4.855 μg/mL, the corresponding sensitivity and specificity was 42.4% and 82.9%, respectively). Conclusion AIDS severe pneumonia complicated with ARDS is associated with many factors, among whichα-HBDH (≥391 U/L) and D-dimer (≥ 4.855 μg/mL) on admission are independent risk factors, which have great early predictive value and can provide reference for early clinical identification of ARDS high-risk patients.
Acute respiratory distress syndrome (ARDS) is a serious threat to human life and health disease, with acute onset and high mortality. The current diagnosis of the disease depends on blood gas analysis results, while calculating the oxygenation index. However, blood gas analysis is an invasive operation, and can’t continuously monitor the development of the disease. In response to the above problems, in this study, we proposed a new algorithm for identifying the severity of ARDS disease. Based on a variety of non-invasive physiological parameters of patients, combined with feature selection techniques, this paper sorts the importance of various physiological parameters. The cross-validation technique was used to evaluate the identification performance. The classification results of four supervised learning algorithms using neural network, logistic regression, AdaBoost and Bagging were compared under different feature subsets. The optimal feature subset and classification algorithm are comprehensively selected by the sensitivity, specificity, accuracy and area under curve (AUC) of different algorithms under different feature subsets. We use four supervised learning algorithms to distinguish the severity of ARDS (P/F ≤ 300). The performance of the algorithm is evaluated according to AUC. When AdaBoost uses 20 features, AUC = 0.832 1, the accuracy is 74.82%, and the optimal AUC is obtained. The performance of the algorithm is evaluated according to the number of features. When using 2 features, Bagging has AUC = 0.819 4 and the accuracy is 73.01%. Compared with traditional methods, this method has the advantage of continuously monitoring the development of patients with ARDS and providing medical staff with auxiliary diagnosis suggestions.
Objective To investigate the current status and influencing factors of the awake prone position in patients with mild and moderate acute respiratory distress syndrome (ARDS). Methods A total of 210 patients with mild to moderate ARDS admitted between December 2022 and January 2023 were investigated by general information questionnaire and self-made prone position knowledge questionnaire. The daily prone position time during hospitalization was recorded. The influencing factors of awake prone position were analyzed by univariate and multivariate linear regression. Results The 210 mild and moderate ARDS patients had an average daily prone position length of stay of (4.97±3.94)h/d, showing a low level. Multiple linear regression analysis showed that prone position knowledge score, age, waist circumference and BMI were the influencing factors of awake prone position (P<0.05). Conclusions Daily awake prone position length was at a low level in mild and moderate ARDS patients. Healthcare workers can prolong the time in the prone position by developing an individualized treatment plan for the prone position, improving the patient’s perception of the prone position, and resolving the discomfort from the prone position.
A novel coronavirus (SARS-CoV-2) that broke out at the end of 2019 is a newly discovered highly pathogenic human coronavirus and has some similarities with severe acute respiratory syndrome coronavirus (SARS-CoV). Angiotensin-converting enzyme 2 (ACE2) is the receptor for infected cells by SARS-CoV. SARS-CoV can invade cells by binding to ACE2 through the spike protein and SARS-CoV-2 may also infect cells through ACE2. Meanwhile, ACE2 also plays an important role in the course of pneumonia. Therefore the possible role of ACE2 in SARS and coronavirus disease 2019 (COVID-19) is worth discussing. This paper briefly summarized the role of ACE2 in SARS, and discussed the possible function of ACE2 in COVID-19 and potential risk of infection with other organs. At last, the function of ACE2 was explored for possible treatment strategies for SARS. It is hoped to provide ideas and theoretical support for clinical treatment of COVID-19.
Objective To assess the efficacy of ambroxol on acute lung injury/acute respiratory distress syndrome ( ALI/ARDS) . Methods The randomized controlled study involving ambroxol on ALI/ARDS were searched and identified from Cochrane Library, PubMed, China Academic Journals Full-text Database, Chinese Biomedical Literature Database, WanFang Resource Database, and Chinese Journal Fulltext Database. The quality of the chosen randomized controlled studies was evaluated, and then the valid data was extracted for meta-analysis. Results Ten articles were included, all in Chinese, including 459 cases ofpatients ( 233 cases in experimental group,226 cases in control group) , with baseline comparability between the various experiments. Systematic review showed that in ALI/ARDS patients, high-dose ambroxol was in favor to improve PaO2 [ WMD =12. 23, 95% ( 9. 62, 14. 84) , P lt; 0. 0001] and PaO2 /FiO2 [ WMD = 32. 75,95% ( 30. 00, 35. 51) , P lt;0. 0001] , reduce lung injury score [ WMD = - 0. 49, 95% ( - 0. 66, - 0. 33) ,P lt;0. 0001] , decrease the duration of mechanical ventilation [ WMD = - 2. 70, 95% ( - 3. 24, - 1. 12) ,P lt;0. 0001] and the length of ICU stay [ WMD= - 2. 70, 95% ( - 3. 37, - 2. 04) , P lt;0. 0001] , and lower mortality [ OR=0. 46,95%( 0. 22, 1. 00) , P = 0. 05] . Conclusions The existing clinical evidence shows that, compared with conventional therapy, high-dose ambroxol plus can significantly improve PaO2 , PaO2 /FiO2 , lung injury score, duration of mechanical ventilation, length of ICU stay and mortality in ALI/ARDS patients. Due to the quality of research and the limitations of the study sample, there likely to exist a bias,and may affect the strength of result, so we expect more high-quality, large-scale randomized controlled clinical trial to verify.