Objective To investigate the characteristics of micro-biology in the respiratory tract in the patients who were suffering acute exacerbation of chronic obstructive pulmonary disease (AECOPD) with/without their respiratory failures as well as with the high/low frequency of exacerbation. MethodsSixty confirmed subjects in the Department of Respiratory and Critical Care in Guizhou Provincial Hospital from Nov. 2021 to Mar. 2022 were chosen and then divided them into two pairs of sub-groups randomly. Sub-group pairs one were based on the frequency of AECOPD: higher frequency and lower frequency. Sub-group pairs two were based on whether the patients were once with respiratory failure or not. 16S rRNA high-throughput sequencing method was used to detect sputum microecology. The Alpha and Beta diversity of each subgroup, and the differences in bacterial composition and relative abundance, were compared. Results For the AECOPD group with low-frequent of exacerbation, its diversity and abundance of microbiology were higher than those group with high-frequent of exacerbation. The group of AECOPD with respiratory failure had lower bacteria micro diversity but abundancy was higher than those group without respiratory failure. ConclusionThe frequency of AECOPD and whether it is with respiratory failure is related to the change of micro-biology in respiratory tract, so such change plays a great role in this disease.
During the new coronavirus disease 2019 (COVID-19) pandemic, there has been controversy over whether emergency surgical management should be performed or not in the patients with COVID-19. Stanford type A aortic dissection is a very urgent life-threatening disease, and guidelines recommend surgical treatment for patients with type A aortic dissection in the first instance. However, intraoperative extracorporeal circulation can be fatal to patients recovering from COVID-19. During the pandemic, extracorporeal membrane oxygenation (ECMO) has played an important role in supporting COVID-19 patients with acute respiratory failure. This article reports a successful V-V ECMO treatment for a Stanford type A aortic dissection patient, who suffered respiratory failure caused by COVID-19 after emergency surgery.
Objective
To systematically review the efficacy of noninvasive positive pressure ventilation (NPPV) by helmet in adults with acute respiratory failure.
Methods
Randomized controlled trials (RCTs) or cohort studies about noninvasive positive pressure ventilation (NPPV) by helmet in adults with acute respiratory failure were retrieved in PubMed, The Cochrane Library (Issue 11, 2016), Web of Science, EMbase, CBM, CNKI and WanFang Data databases from inception to November 2016. Two reviewers independently screened literature, extracted data and assessed the risk of bias of included studies. Stata 12.0 software was then used to perform meta-analysis.
Results
A total of eight studies were included. The results of meta-analysis showed that, NPPV by helmet could significantly reduce the carbon dioxide partial pressure (cohort study: SMD=–0.46, 95%CI –0.75 to –0.18, P=0.001), tracheal intubation rate (RCT: OR=0.36, 95%CI 0.17 to 0.77, P=0.008) and hospital mortality (RCT: OR=0.48, 95%CI 0.24 to 0.98, P=0.044), improve the positive end expiratory pressure (RCT: SMD=1.27, 95%CI 0.87 to 1.67, P<0.05) and respiratory status (RCT: SMD=–0.45, 95%CI –0.81 to –0.08,P=0.017). There was no significant difference in the duration of NPPV(cohort study: OR=–0.20, 95%CI –0.50 to 0.09, P=0.177; RCT: OR=–0.24, 95%CI –0.86 to 0.38, P=0.445).
Conclusion
NPPV by helmet can reduce the carbon dioxide partial pressure, tracheal intubation rate, hospital mortality and improve the positive end expiratory pressure, respiratory status. But the effects in the duration of NPPV and oxygenation index are uncertain. Due to limited quality and quantity of the included studies, more high quality studies are needed to verify above conclusion.
Objective To explore the predictive value of serum procalcitonin (PCT), D-dimer (D-D) and decoy receptor 3 (DcR3) for prognosis of patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) and respiratory failure undergoing non-invasive ventilation (NIV). Methods A total of 95 patients with AECOPD and respiratory failure undergoing basic treatment and NIV in the hospital were retrospectively enrolled between September (n=65) 2017 and February 2021. According to prognosis after treatment, they were divided into a good prognosis group and a poor prognosis group (n=30). The general data of all patients were collected. The influencing factors of prognosis were analyzed by multivariate logistic regression model. The levels of DcR3, PCT and D-D were detected by enzyme-linked immunosorbent assay, colloidal gold colorimetry and immunoturbidimetry. The patients condition was assessed by scores of acute physiology chronic health evaluation scoring system Ⅱ (APACHEⅡ). The partial pressure of arterial oxygen (PaO2) and partial pressure of carbon dioxide (PaCO2) were recorded. And the above indexes between the two groups were compared. The relationship between DcR3, PCT, D-D and APACHEⅡ score, PaO2, PaCO2 was analyzed by Pearson correlation analysis. The prognostic value of DcR3, PCT and D-D was analyzed by receiver operating characteristic (ROC) curve. Results There was no significant difference in gender, GOLD grading or underlying diseases between the poor prognosis group and the good prognosis group (P>0.05), but there were significant differences in age, DcR3, PCT, D-D, APACHEⅡ score, PaO2 and PaCO2 after treatment (P<0.05). DcR3, PCT, D-D, APACHEⅡ score and PaCO2 in the poor prognosis group were higher than those in the good prognosis group, while PaO2 was lower than that in the good prognosis group (P<0.05). Logistic regression analysis showed that DcR3 ≥5.50 ng/mL (OR=21.889), PCT ≥ 5.00 μg/L (OR=3.782), D-D ≥3.00 μg/L (OR=4.162) and APACHEⅡ score ≥20 points (OR=2.540) were all influencing factors of prognosis (P<0.05). The results of Pearson correlation analysis showed that DcR3, PCT and D-D were positively correlated with APACHEⅡ score and PaCO2, while negatively correlated with PaO2 (P<0.05). The results of ROC curve analysis showed that area under ROC curve of DcR3, PCT and D-D for predicting the prognosis were 0.745 (95%CI 0.631 - 0.859), 0.691 (95%CI 0.579 - 0.803) and 0.796 (95%CI 0.696 - 0.895), respectively (P<0.05). Conclusion The serum DcR3, PCT and D-D levels are related to disease progression in patients with AECOPD and respiratory failure after NIV, which have good predictive efficiency for prognosis and can be applied as important biological indexes to evaluate prognosis and guide treatment.
ObjectiveTo evaluate the reliability,validity and feasibility of a patient-reported outcomes (PRO) scale in the subjects with respiratory failure.
Methods364 patients with chronic respiratory failure and 97 healthy subjects were face-to-face interviewed by well-trained investigators,and the data of respiratory failure -PRO instrument were collected. The psychometric performance such as reliability,validity,responsiveness and clinical feasibility in the respiratory failure -PRO instrument was evaluated.
ResultsThe Cronbach's alpha coefficient of the respiratory failure -PRO instrument and each dimension were greater than 0.7. Factor analysis showed that the instrument had good construct validity. The scores of each of the facets and total scores between the patients and the healthy subjects were different. The recovery rate and the efficient rate of the questionnaire were more than 95%,and the time required to complete a questionnaire was within 15 minutes,indicating that the scale had a high clinical feasibility.
ConclusionThe respiratory failure -PRO instrument has good reliability,validity,responsiveness and clinical feasibility.
Objective To identify the clinical features and risk factors for mortality associated with severe influenza B pneumonia of adults admitted to respiratory intensive care unit (ICU). Methods Patients with confirmed influenza B infection and respiratory failure between February 2020 and February 2022 who were admitted to the ICU were sequentially included. Demographic features, clinical data, microbiological data, complications, and outcomes were collected. Univariate logistic regression analysis was performed to identify risk factors associated with hospital mortality. A comparison with severe influenza A pneumonia was made to explore the characteristics of influenza B virus-associated pneumonia. Results A total of 23 patients with influenza B pneumonia were included. The survival group included 18 patients and the death group included 5 patients, with an ICU mortality of 21.7%. The median age in the death group was 64 (64, 72.5) years, which was significantly older than the survival group, with a median age 59 (30.25, 64.25) years (P=0.030). Univariate logistic regression analysis indicated that SOFA score [odds ratio (OR) 1.307, 95% confidential interval (CI) 1.013 - 1.686, P=0.039], decreased hemoglobin (OR 0.845, 95%CI 0.715 - 0.997, P=0.046), and high blood urea nitrogen (BUN) (OR 1.432, 95%CI 1.044 - 1.963, P=0.026) were independent risk factors for hospital mortality. Compared with influenza A pneumonia, patients with severe influenza B pneumonia had more complications (60.0% vs. 87.0%, P=0.023). Conclusions The mortality of severe influenza B virus-associated pneumonia with was high. Increased SOFA score, anemia, and high BUN were risk factors for ICU mortality of severe influenza B infection in adults.
Objectives
To assess the prognostic value of blood sugar level for acute respiratory failure patients undergoing mechanical ventilation.
Methods
The study collected 139 acute respiratory failure patients undergoing mechanical ventilation admitted between February 2012 and October 2013. The patients were divided into a hyperglycemic group (n=123, blood sugar ≥143 mg/dl) and a non-hyperglycemic group (n=16, blood sugar <143 mg/dl). The data for basic clinical pathological characteristics and the blood sugar levels were collected, and the correlation between the blood sugar level and the prognosis was assessed using single factor analysis and logistic regression method.
Results
In the study, 88.49% of patients with acute respiratory failure undergoing mechanical ventilation had hyperglycemia (blood sugar ≥143 mg/dl). The proportions of patients with APACHEⅡ score ≥10, chronic obstructive pulmonary disease (COPD) or hypoxemia in the hyperglycemic group were significantly higher than those in the non-hyperglycemic group (P<0.05). APACHEⅡ ≥10, COPD and hypoxemia were significant risk factors for hyperglycemia. At the same time, the proportions of patients in the death group with hyperglycemia ≥143 mg/dl ( OR=8.354, 95%CI 1.067-65.388, P=0.018), APACHEⅡ≥10 ( OR=2.545, 95%CI 1.109-6.356, P=0.046), COPD ( OR=2.871, 95%CI 1.203-6.852, P=0.015), and hypoxemia ( OR=3.500, 95%CI 1.556-7.874, P=0.002) were significantly higher than those in the survival group. Kaplan-Meier curve analysis found that the overall survival of the hyperglycemic patients with acute respiratory failure was significantly lower than that in the non-hyperglycemic patients (P<0.001).
Conclusion
Blood sugar level can be used as an independent predictor for acute respiratory failure patients undergoing mechanical ventilation.
Objective To develop and validate a nomogram model that can be used to predict the prognosis of acute exacerbation of chronic obstructive pulmonary disease (AECOPD) patients with type II respiratory failure. Methods A retrospective analysis was conducted on the clinical data of 300 hospitalized AECOPD patients in the People’s Hosipital of Leshan from August 2016 to December 2021. Patients were grouped into a training cohort (n=210) and a validation cohort (n=90) in a 7:3 ratio. The variables for the patients in the training cohort were selected using the least absolute shrinkage and selection operator (LASSO), followed by multivariate logistic regression analysis to identify independent risk factors of poor prognosis in AECOPD with type II respiratory failure, and a nomogram model was constructed. Receiver operating characteristic (ROC) curves were plotted for the training and validation cohorts, and the area under ROC curve (AUC) was calculated.The model was validated by conducting the Hosmer-Lemeshow test, drawing calibration curves, and performing decision curve analysis(DCA).ResultsCardiovascular disease, lymphocyte percentage, and red cell distribution width-standard deviation(RDW-SD) were identified as independent risk factors of poor prognosis for AECOPD patients with type II respiratory failure (P<0.05). The AUC values for the training and validation cohorts were 0.742 (95%CI: 0.672-0.812) and 0.793 (95%CI: 0.699-0.888), respectively. The calibration curves of the two cohorts are close to the desirable curves.The Hosmer-Lemeshow test P-values were greater than 0.05, indicating good clinical practicality. The DCA curve indicates that the model has good clinical value. Conclusions The clinical prediction model, based on factors such as cardiovascular disease, lymphocyte percentage, and RDW-SD, showed good predictive value for AECOPD patients complicated by type II respiratory failure.
As an extracorporeal life support technology, veno-venous extracorporeal membrane oxygenation (VV-ECMO) has been demonstrated its role in the treatment of patients with severe respiratory failure. Its main advantages include the ability to maintain adequate oxygenation and remove excess CO2, increase oxygen delivery, improve tissue perfusion and metabolism, and implement lung protection strategies. Clinicians should accurately assess and identify the patient's condition, timely and accurately carry out VV-ECMO operation and management. This article will review the patient selection, cannulation strategy, anticoagulation, clinical management and weaning involved in the application of VV-ECMO.
ObjectiveTo explore the risk factors for postoperative respiratory failure (RF) in patients with esophageal cancer, construct a predictive model based on the least absolute shrinkage and selection operator (LASSO)-logistic regression, and visualize the constructed model. MethodsA retrospective analysis was conducted on patients with esophageal cancer who underwent surgical treatment in the Department of Thoracic Surgery, Sun Yat-sen University Cancer Center Gansu Hospital from 2020 to 2023. Patients were divided into a RF group and a non-RF (NRF) group according to whether RF occurred after surgery. Clinical data of the two groups were collected, and LASSO-logistic regression was used to optimize feature selection and construct the predictive model. The model was internally validated by repeated sampling 1000 times based on the Bootstrap method. ResultsA total of 217 patients were included, among which 24 were in the RF group, including 22 males and 2 females, with an average age of (63.33±9.10) years; 193 were in the NRF group, including 161 males and 32 females, with an average age of (62.14±8.44) years. LASSO-logistic regression analysis showed that the percentage of forced expiratory volume in one second/forced vital capacity (FEV1/FVC) to predicted value (FEV1/FVC%pred) [OR=0.944, 95%CI (0.897, 0.993), P=0.026], postoperative anastomotic fistula [OR=4.106, 95%CI (1.457, 11.575), P=0.008], and postoperative lung infection [OR=3.776, 95%CI (1.373, 10.388), P=0.010] were risk factors for postoperative RF in patients with esophageal cancer. Based on the above risk factors, a predictive model was constructed, with an area under the receiver operating characteristic curve of 0.819 [95%CI (0.737, 0.901)]. The Hosmer-Lemeshow test for the calibration curve showed that the model had good goodness of fit (P=0.527). The decision curve showed that the model had good clinical net benefit when the threshold probability was between 5% and 50%. Conclusion FEV1/FVC%pred, postoperative anastomotic fistula, and postoperative lung infection are risk factors for postoperative RF in patients with esophageal cancer. The predictive model constructed based on LASSO-logistic regression analysis is expected to help medical staff screen high-risk patients for early individualized intervention.
