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.
ObjectiveTo improve clinicians' understanding of severe cytokine release syndrome (CRS) through reporting the clinical manifestation, diagnosis, treatment, and prognosis of CRS after chimeric antigen receptor T (CAR-T) cell therapy in a patient with solid tumor. Methods A patient with ovarian cancer who suffered severe CRS after CAR-T cell therapy in the Department of Critical Care Medicine, the First Affiliated Hospital of Nanjing Medical University was reviewed. Relevant studies were searched for literature review. Results The patient, a 55-year-old woman, was diagnosed with ovarian cancer in early 2016 and continued to progress despite multiple lines of treatment, so she received CAR-T cell therapy on September 16, 2022. The patient developed a fever 2 days after infusion, and developed dyspnea and shortness of breath with oxygen desaturation 2 days later. Her condition kept deteriorating with respiratory distress and severe hypoxia 6 days after infusion, and the level of interleukin-6 and interferon-gamma continued to be elevated. Chest CT showed pleural effusion and massive exudation of both lungs. Considered to have acute respiratory distress syndrome (ARDS) due to severe CRS, she was transferred to the intensive care unit (ICU). The patient was treated with tocilizumab, high-dose intravenous glucocorticoid pulses, mechanical ventilation, and sivelestat sodium for ARDS. Her symptoms were gradually relieved, and the results of laboratory tests were gradually stabilized. The patient was extubated 6 days after ICU admission and discharged from ICU a week later. Six patients were screened out with ARDS or acute respiratory failure caused by CRS after CAR-T cell therapy, whose treatments were mainly anticytokine agents combined with high-flow oxygen therapy or invasive mechanical ventilation. One of them died. ConclusionsClinicians should be alert to severe CRS during the administration of CAR-T cell. Rapid interruption of the inflammation development is the key to all treatments. If respiratory and/or circulatory dysfunction occurs, patients should be transferred to ICU in time for organ support therapy.
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 Exploring the correlation between intravesical pressure (IP) and diaphragm excursion (DE) in patients with severe acute pancreatitis (SAP) and acute respiratory distress syndrome (ARDS), and evaluating its predictive value for weaning outcomes. Methods A retrospective analysis was conducted on the clinical data of 144 SAP patients with ARDS admitted between 2020 and 2023. By collecting the outcome of weaning, collect data on gender, age, acute physiology and chronic health score II (APACHE II), oxygenation index, and IP and DE before weaning and extubation for all patients. Based on weaning outcomes, divide patients into successful and failed groups, and compare the differences in various indicators between the two groups; Use binary logistic regression to analyze whether IP and DE are risk factors affecting weaning in SAP patients with ARDS, and use Pearson correlation analysis to examine the correlation between IP and DE; Use receiver operating characteristic curve (ROC curve) to analyze the predictive value of IP and DE on weaning outcomes in SAP patients with ARDS. ResultsA total of 144 SAP patients with ARDS were included, of which 108 were successfully weaned and 36 were unsuccessful. There were no statistically significant differences in gender, age, and APACHE II scores between the successful and failed groups (males: 62.96% (68/108) compared to 69.44% (25/36), age (years): 41.91 ± 8.14 compared to 42.42 ± 6.22, APACHE II score (points): 18.28 ± 2.22 compared to 18.97 ± 1.83, P>0.05). The IP of the successful group was significantly lower than that of the failed group, and the DE was significantly higher than that of the failed group [IP (mmHg): 18.45 ± 3.76 compared to 23.92 ± 5.65, DE (mm): 16.18 ± 4.23 compared to 12.28 ± 4.44, all P<0.05]. All patients showed a significant negative correlation between IP and DE (r=–0.457, P<0.001). ROC curve analysis showed that the area under the curve (AUC) of IP predicting the withdrawal outcome of SAP patients with ARDS was 0.805, with a 95% confidence interval (95%CI) of 0.724-0.885 and P<0.001. When the cutoff value was 19.5 mmHg, the sensitivity was 91.57% and the specificity was 47.54%; The AUC for predicting the withdrawal outcome of SAP patients with ARDS by DE was 0.738, with a 95%CI of 0.641-0.834 and P<0.001. When the cutoff value was 11.5 points, the sensitivity was 84.82% and the specificity was 59.38%. Conclusions There is a significant negative correlation between IP and DE in SAP combined with ARDS patients, and both have certain predictive value for weaning outcomes.
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.
ObjectiveTo investigate the independent risk factors associated with postoperative acute respiratory distress syndrome in patients undergoing type A aortic dissection surgery.MethodsThe clinical data of 147 patients who underwent acute type A aortic dissection surgery in the First Affiliated Hospital of Anhui Medical University from 2015 to 2019 were retrospectively analyzed. There were 110 males at age of 51.9±10.1 years and 37 females at age of 54.3±11.1 years. According to whether the patients developed ARDS after surgery, all of the patients were divided into a ARDS group or a non-ARDS group. Logistic regress analysis was utilized to establish the predictive mode to identify the independent risk factors related to ARDS.ResultsOf the patients, 25 developed postoperative ARDS. Among them, 5 patients were mild ARDS, 13 patients were moderate, and 7 patients were severe ARDS. Multivariate logistic regression analysis showed that deep hypothermic circulatory arrest time [odds ratio (OR)=1.067, 95% confidence interval (CI) 1.014-1.124, P=0.013], cardiopulmonary bypass time (OR=1.012, 95%CI 1.001-1.022, P=0.027) and perioperative plasma input (OR=1.001, 95%CI 1.000-1.002, P=0.011) were independently associated with ARDS in patients undergoing acute A aortic dissection surgery. Receiver operating characteristic (ROC) curve analysis demonstrated a good discrimination ability of the logistic regression model, with an area under the curve of 0.835 (95%CI 0.740-0.929, P=0.000).ConclusionDuration of deep hypothermic circulatory arrest, cardiopulmonary bypass time and perioperative plasma are independent risk factors for postoperative ARDS in patients undergoing type A aortic dissection surgery.
ObjectiveTo investigate the changes of plasma platelet activating factor (PAF) interleukin-8(IL-8) and interferon-γ (IFN-γ) in patients after surgery with extracorporeal circulation (ECC) and their clinical significance.
MethodsSeventy-five patients undergoing surgery with ECC in the First College of Clinical Medicine,China Three Gorges University from June 2012 to June 2013 were enrolled in this study. According to the presence of postoperative acute lung injury/acute respiratory distress syndrome (ALI/ARDS) all the 75 patients were divided into 2 groups. In ALI/ARDS group, there were 28 patients including 20 male and 8 female patients with their age of 53.6±8.2 years. In the control group,there were 47 patients without postoperative ALI/ARDS,including 32 male and 15 female patients with their age of 56.9±11.8 years. Dynamic variations of plasma PAF,IL-8 and IFN-γ of these patients were examined with enzyme-linked immunosorbent assay (ELISA) and compared between the 2 groups.
ResultsIn ALI/ARDS group,plasma IL-8 and IFN-γ reached peak levels at 48 hours after surgery and gradually decreased after that;plasma PAF reached the peak level at 96 hours after surgery and gradually decreased after that. Postoperative plasma PAF (96 hours after surgery:16 029.5±4 203.7 mU/ml vs. 4 520.1±312.2 mU/ml,P<0.05) IL-8 (48 hours after surgery:48 580.5±8 095.8 pg/ml vs. 5 990.5±1 179.0 pg/ml,P<0.05) and IFN-γ (48 hours after surgery:258.5±76.1 pg/ml vs. 26.1±11.5 pg/ml,P<0.05) of ALI/ARDS group were significantly higher than those of the control group at 48 hours,96 hours and 144 hours after surgery.
ConclusionPlasma PAF,IL-8 and IFN-γ change significantly after surgery with ECC,which may play an important role in the pathogenesis of postoperative ALI/ARDS.
Mechanical ventilation is an importmant life-sustaining treatment for patients with acute respiratory distress syndrome. Its clinical outcomes depend on patients’ characteristics of lung recruitment. Estimation of lung recruitment characteristics is valuable for the determination of ventilatory maneurvers and ventilator parameters. There is no easily-used, bedside method to assess lung recruitment characteristics. The present paper proposed a method to estimate lung recruitment characteristics from the static pressure-volume curve of lungs. The method was evaluated by comparing with published experimental data. Results of lung recruitment derived from the presented method were in high agreement with the published data, suggesting that the proposed method is capable to estimate lung recruitment characteristics. Since some advanced ventilators are capable to measure the static pressure-volume curve automatedly, the presented method is potential to be used at bedside, and it is helpful for clinicians to individualize ventilatory manuevers and the correpsonding ventilator parameters.
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.
