Monitoring the Pendelluft by EIT could predict the failure of non-invasive mechanical ventilation:A Prospective Study

Monitoring the Pendelluft by EIT could predict the failure of non-invasive mechanical ventilation:A Prospective Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Monitoring the Pendelluft by EIT could predict the failure of non-invasive mechanical ventilation:A Prospective Study ling wu, Xuzhen Wang, Ping Hu, Ye Pan, Ning Zhao, Yuanhua Lu, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4315149/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background and objective: Patients with severe hypoxemia have a high mortality rate after failed non-invasive ventilation(NIV).Therefore,we propose utilizing pendelluft monitored by EIT to predict the failures of NIV,providing a new method for clinical practice. Methods: This prospective observational study enrolled all patients with acute respiratory failure who were receiving NIV.The collected indices included patients' baseline characteristics,the measurement of pendelluft by EIT during the initial 24 hours of NIV after admission to the ICU,and the PaO2/FiO2 ratio. Results: This study included 37 patients.There were no statistically significant differences in baseline characteristics between the successful and failed groups of NIV.The amplitude of pendelluft in the successful group (122.3226 (8.5493,193.8191))was significantly higher compared to the failed group (7.7538(2.6880, 25.8338))with a p-value < 0.01.The ROC curve showed the pendelluft amplitude cut-off value of 45.1124.Compared to the PaO2/FiO2,the pendelluft amplitude had a higher predictive value. Conclusion: Monitoring pendelluft using EIT could be one of the methods for predicting the failure of NIV. Health sciences/Biomarkers/Predictive markers Health sciences/Diseases/Respiratory tract diseases/Respiratory distress syndrome Electrical impedance tomography Pendelluft Non-invasive mechanical ventilation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 INTRODUCTION Since the development and application of mechanical ventilation in patients with COPD in 1990 1 , it has been widely used due to its ability to open collapsed alveolar, increase lung volume 2 , improve lung ventilation/ perfusion matching(V/Q), and correct respiratory acidosis 3 . However, the mortality rate is significantly higher for patients with acute respiratory failure who fail non-invasive mechanical ventilation compared to invasive mechanical ventilation 4 . Recent studies have shown that D-dimer levels 5 , Neutrophil-to-Lymphocyte Ratio 6 , C-reactive protein (CRP), creatinine 7 , and Cardiac Troponin I 8 at admission are associated with an increased risk of endotracheal intubation. A study by M. Antonelli et al. 9 in 2021 proposed that an PaO2/FiO2 ≤ 146 mmHg after 1 hour of NIV treatment can predict NIV failure. Additionally, there has an updated HACOR score to assess the failure of non-invasive mechanical ventilation 10 . However, current research indicators are easily affected by factors such as infection and overall health, which leads to a lack of strong timeliness and low specificity. Additionally, the majority of them are invasive procedures.Therefore, identifying the failure of non-invasive mechanical ventilation and avoiding ineffective or potentially harmful non-invasive ventilation 11 is currently a focus of clinical research. We have developed a non-invasive, timely, accurate, and highly reproducible method to monitor lung ventilation. The objective is to predict the failure of non-invasive mechanical ventilation.Respiratory pendelluft refers to the process in which gas is unevenly distributed within some alveoli during the inspiration movement in the lungs, without significantly affecting the overall tidal volume 12 , 13 .The pendelluft phenomenon is found to be associated with the presence of spontaneous respiration during invasive mechanical ventilation 14 and is also related to the duration of invasive mechanical ventilation.Sang Ling et al. 15 found that Electrical Impedance Tomography (EIT) can monitor pendelluft in patients with flail chest, acute respiratory distress syndrome (ARDS), and acute exacerbation of chronic obstructive pulmonary disease (COPD).EIT is a bedside, real-time, non-invasive, and radiation-free monitoring device.It is currently the only instrument capable of repeatedly measuring lung ventilation, blood flow, and other parameters 16 . Therefore, we propose, for the first time, the use of EIT to monitor pendelluft in predicting non-invasive mechanical ventilation failure. By using intuitive quantitative data to assess the effectiveness of non-invasive ventilation, we can guide clinicians in the early detection of appropriate weaning and intubation timing, improve patient survival rates, and reduce the burden on healthcare systems. METHODS This is a single-center, prospective, observational study conducted at the First Affiliated Hospital of Nanchang University. The study included patients who received non-invasive mechanical ventilation from December 2021 to March 2023 in the Department of Intensive Care Medicine. The study received approval and underwent review by the Clinical Research Committee of the First Affiliated Hospital of Nanchang University, with an ethics number of IIT2022090. The study affirms that all research activities were conducted in accordance with applicable guidelines and regulations. We confirm that informed consent was obtained from all participants and/or their legal guardians. Research involving human participants was conducted in accordance with the principles outlined in the Declaration of Helsinki. Patients and measurements Patients who were admitted to the ICU due to symptoms of acute respiratory failure and required non-invasive mechanical ventilation were included. The age of Recruited patients was between 18 and 80 years, and the ICU stay needed to be longer than 24 hours. The exclusion criteria were as follows: hemodynamic instability (mean arterial pressure ≤ 65 mmHg), acute myocardial infarction within one week of onset, severe arrhythmias, implanted cardiac pacemakers, pulmonary surgery within 48 hours, injuries to the airway, thoracic cavity, chest wall, or cranial-brain injury, respiratory arrest requiring emergency intubation, inability to clear secretions, lack of spontaneous respiration, increased intracranial pressure, and patients who are pregnant or breastfeeding. For patients who met the inclusion and exclusion criteria, the Philips V60 non-invasive ventilator was used. The basic settings included bilevel positive airway pressure ventilation in S/T (Spontaneous/Triggered) mode, with an initial IPAP setting of 4 cmH2O and EPAP of 12 cmH2O. The respiratory rate was set at 12 breaths per minute, and the oxygen concentration was adjusted to maintain the patient’s oxygen saturation above 90%. The respiratory parameters of the patient were adjusted by two or more attending physicians with senior professional titles and respiratory therapists based on the patient’s clinical presentation and laboratory results. Patients were encouraged to cooperate with breathing to maintain a pH level between 7.35 and 7.45. The mask covering the nose and mouth was tightly secured to prevent air leaks, and regular examinations of skin pressure marks were conducted. The following conditions require intubation: persistent changes in mental status, continuous worsening of respiratory distress, hypotension, elevated carbon dioxide partial pressure, a decrease in pH value by 0.05–0.1, etc. The decision to intubate patients is made by the attending physician, and if a patient undergoes endotracheal intubation, it is defined as a failure of non-invasive mechanical ventilation. Continuous assessment of patients is conducted, and the duration and level of non-invasive mechanical ventilation support are gradually reduced based on clinical symptoms and laboratory indicators. Oxygen is administered for 15 minutes without ventilatory support. If the patient’s respiratory frequency is less than 30 breaths per minute, PaO 2 is above 75mmHg, and FiO 2 is 50%, ventilatory support is discontinued. Baseline data, vital signs, and arterial blood gas measurements were collected when patients were admitted to the ICU and received non-invasive ventilation (NIV). The baseline data included age, gender, primary disease, and disease severity (APACHE II, SOFA scores). Vital signs included heart rate, respiratory rate, mean arterial pressure (MAP), and blood gas analysis included pH, PaO 2 , and PaCO 2 Monitoring the pendelluft level in each ROI region The cross-section of the chest was divided into four equal parts in a “cross-shaped” pattern, which were designated as ROI1, ROI2, ROI3, and ROI4(Fig. 1 ). Patients who accept non-invasive mechanical ventilation underwent EIT monitoring during the first 24 hours(Fig. 2 ). The pendelluft data was collected for 5 minutes during regular breathing without any other interventions related to the study. EIT images were continuously recorded at a frequency of 50 Hz and saved in a specific folder. A low-pass filter with a cut-off frequency of 50 cycles per minute was applied to the data to eliminate impedance changes related to the heart. The Evaluation Pendelluft software was used to calculate the pendelluft level. The pendelluft amplitude based on EIT was defined as the impedance difference between the sum of all regional tidal impedance changes and the global tidal impedance changes. The regional phase shift or time was defined as the time difference between the global and regional impedance-time curves. These parameters were then evaluated to measure the pendelluft. Statistical analysis Using PASS 23.0 software, sample size estimation is performed based on rates and their confidence intervals. The overall rate is 10%, with a tolerable error of 0.1 and α = 0.05. The calculation yields N = 35 cases. Normality analysis is conducted on all the data. Independent sample t-test is applied for inter-group comparisons, while nonparametric tests are used for non-normally distributed quantitative data. T-test analysis is used to determine the statistical differences between the two groups. The area under the receiver operating characteristic curve is employed to evaluate the predictive ability of non-invasive mechanical ventilation failure. A p-value less than 0.05 is considered statistically significant RESULTS The patient screening process is shown in Fig. 3 , and a total of 37 patients were included based on the inclusion criteria. According to whether the patients underwent tracheal intubation, they were divided into the noninvasive mechanical ventilation failure group (N = 27) and the noninvasive mechanical ventilation success group (N = 11) (Table 1 ). There were no statistically significant differences in demographic baseline characteristics, vital signs, or blood gas analysis between the two groups. However, the etiology analysis between the two groups suggested that CAP (Community-Acquired Pneumonia) was a risk factor for noninvasive mechanical ventilation in such patients (65.4% vs 36.4%, P < 0.05). Table 1 Baseline characteristics of participants across study arms Failed group(n = 26) Successful group(n = 11) P value Baseline characteristics Age,median,years 58.27 ± 11.38 59.09 ± 17.3 0.865 Male sex,n(%) 23(88.5) 9(81.8) 0.623 BMI,kg/m 2 21.76 ± 3.45 22.73 ± 3.12 0.428 APACHE II at ICU admission 18.04 ± 7.71 18.36 ± 4.61 0.453 SOFA at ICU admission 5.88 ± 2.37 4.73 ± 3.07 0.222 Heart rate, beats/min 96.77 ± 14.25 97.09 ± 21.64 0.958 Mean Artery Pressure,mmHg 91.88 ± 14.5 89.26 ± 17.52 0.639 PH 7.42 ± 0.07 7.40 ± 0.11 0.660 PaCO 2 ,mmHg 41.5(33.5, 54.25) 49(36, 76) 0.231 PaO 2 ,mmHg 79(60.5, 104.25) 92(75, 113) 0.118 Baseline Ventilator Settings, median Respiratory rate, breaths/min 29.12 ± 8.89 25.82 ± 5.671 0.377 Tidal Volume, ml 535(425, 772.5) 520(470, 620) 0.781 EPAP, cmH2O 12.96 ± 2.877 13.36 ± 3.264 0.711 IPAP, cmH2O 5.08 ± 0.891 5.09 ± 1.136 0.968 Etiology of Acute respiratory failure, n(%) 0.902 AECOPD 3(11.5) 5(45.5) 0.48 CAP 17(65.4) 4(36.4) 0.005 others 6(23.1) 2(18.2) 0.157 Compared to the failure group, the success group showed statistically significant differences in pendelluft amplitude, inspiration phase, and expiration phase time in each region of interest (ROI) (P < 0.05). The total pendelluft amplitude in the failure group was 7.7538 (2.6880, 25.8338), while in the success group, it was 122.3226 (8.5493, 193.8191). The comparison between the two groups demonstrated a significantly higher pendelluft amplitude in the success group.Compared to the PaO2/FiO2 of the failure group (median of 131 (86.75, 211.87) mmHg), the median PaO2/FiO2 of the success group was significantly higher at 250 (185, 323) mmHg, with a statistically significant difference (P < 0.05), as shown in Table 2 and Fig. 4 . Table 2 Comparison of pendelluft and PaO 2 /FiO 2 between the two groups Amplitude of pendelluft All patients (n = 37) P value Failed group(n = 26) Successful group(n = 11) ROI 1 2.2365(0.3211, 5.3548) 23.3356(3.3655, 43.0755) 0.005 ROI 2 1.3428(0.2750, 2.6985) 9.6097(1.3890, 44.5917) 0.006 ROI 3 2.1372(0.3784, 13.3705) 58.8901(2.3608, 83.4699) 0.006 ROI 4 1.2333(0.1807, 4.9616) 6.0811(2.4332, 22.4161) 0.004 Total 7.7538(2.6880, 25.8338) 122.3226(8.5493, 193.8191) 0.003 Time difference inspiration, s 0.1375(0.05, 0.225) 0.3(0.2, 0.7) 0.004 expiration, s 0.1(0.05, 0.15) 0.5(0.1, 0.4) 0.008 PaO 2 /FiO 2 (mmHg) 131(86.75, 211.87) 250(185, 323) 0.006 Data are listed as mean ± SD The ROC curve analysis was conducted on the sum of pendelluft amplitude, inspiratory time, expiratory time, and PaO2/FiO2. The results are as follows:The AUC for the sum of pendelluft amplitude in assessing the effectiveness of non-invasive mechanical ventilation was 0.815 [95% CI (0.643–0.986), P = 0.003]. The sensitivity was 72.7% and the specificity was 92.3%.The AUC for inspiratory time in assessing the effectiveness of non-invasive mechanical ventilation was 0.799 [95% CI (0.636–0.962), P = 0.004]. The sensitivity was 45.5% and the specificity was 96.2%.The AUC for expiratory time in assessing the effectiveness of non-invasive mechanical ventilation was 0.774 [95% CI (0.622–0.926), P = 0.009]. The sensitivity was 100% and the specificity was 42.3%.The AUC for the PaO2/FiO2 in assessing the effectiveness of non-invasive mechanical ventilation was 0.787 [95% CI (0.640–0.933), P = 0.006]. The sensitivity was 90.9% and the specificity was 57.7%. These results suggest that the evaluation value of the sum of pendelluft amplitude is slightly higher than that of the PaO2/FiO2, with a significant improvement in specificity. By choosing the maximum Youden index, the optimal cutoff values for the sum of pendelluft amplitude, inspiratory time, expiratory time, and PaO2/FiO2 were found to be 45.1124, 0.475s, 0.075s, and 153 mmHg, respectively. When the sum of pendelluft amplitude is greater than 45.1124 or the PaO2/FiO2 is greater than 153 mmHg, the likelihood of non-invasive mechanical ventilation failure is higher (Table 3 and Fig. 5 ). Table 3 ROC curve analysis that impacts the effectiveness of non-invasive mechanical ventilation. Outcomes AUC P value 95%CI Cut-off Sensitivity(%) Specificity(%) Pendelluft amplitude 0.815 0.003 0.643–0.986 45.1124 72.7 92.3 Time difference inspiration, s 0.799 0.004 0.636–0.962 0.475 45.5 96.2 expiration, s 0.774 0.009 0.622–0.926 0.075 100 42.3 PaO 2 /FiO 2 (mmHg) 0.787 0.006 0.640–0.933 153 90.9 57.7 DISCUSSION Our study found that using EIT to monitor pendelluft can predict the failure of non-invasive mechanical ventilation. When the pendelluft amplitude is less than 45.1124, there may be an increased risk of non-invasive mechanical ventilation failure. Compared to the PaO2/FiO2, pendelluft has higher accuracy and specificity in predicting non-invasive mechanical ventilation failure. Some high-quality studies suggest that there is still skepticism regarding the effectiveness of NIV treatment 17 .Giacomo Bellani's research 4 shows that the mortality rate among patients who experience NIV failure is 45.4%. This rate increases to 69% for those who experience NIV failure 18 . Delaying intubation also worsens the prognosis of patients with acute respiratory failure 19 .However,the NIV still has benefits in reducing endotracheal intubation and death in patients 20 .This leads us to approach NIV treatment with even more prudence.Therefore, predicting NIV failure has always been a research focus in clinical practice. In previous reports 10 , it has been demonstrated that an updated HACOR scale can predict failure of noninvasive mechanical ventilation.Onkar K Jha et al.'s study 21 showed that the oxygenation index improves within 24 hours after treatment and is greater than 161mmHg, which can successfully predict the effectiveness of non-invasive mechanical ventilation in patients. Our study similarly confirms that an oxygenation index of less than 153mmHg predicts failure of non-invasive mechanical ventilation.However, these indicators require certain invasive procedures and are susceptible to the influence of the underlying disease of the patients. Therefore, our study proposes a non-invasive and objective indicator to predict the failure of non-invasive mechanical ventilation. Pendelluft is a variable that allows real-time monitoring of ventilation near the bed using Electrical Impedance Tomography (EIT), allowing specific observation of lung ventilation and quantification of respiratory indices related to autonomous breathing.Greenblatt et al. 22 found that pendelluft is primarily concentrated in regions of poor lung ventilation, and this preferential oscillation may contribute to local gas exchange. Takeshi Yoshida et al. 12 confirmed this viewpoint, pendelluft phenomenon is primarily concentrated in the posterior region of the lungs. Therefore, pendelluft phenomenon within a certain range may be beneficial for lung ventilation. Our research indicates that the incidence of intubation is lower when the amplitude of pendelluft is > 45.1124. This demonstrates that higher pendelluft amplitude, especially when occurring in restrictive ventilation zones, may improve patient ventilation during NIV. Despite the description of pendelluft phenomenon, its full impact on the lungs is still not fully understood. Tonelli et al. 23 found that excessive spontaneous inspiratory effort in patients is associated with NIV failure. Furthermore, in patients receiving NIV outside of the ICU 24 , those who experienced NIV failure exhibited higher minute ventilation on the first day (due to slightly higher tidal volume and respiratory rate), which may be related to the increased risk of lung injury caused by excessively strong drive for spontaneous breathing. Guillaume Carteaux et al. 25 shown that a tidal volume exceeding 9.5 mL/kg can predict the failure of noninvasive ventilation.However, current clinical research does not provide a clear answer as to whether pendelluft causes injury. In some studies on invasive mechanical ventilation,pendelluft may potentially pose harm by introducing local overstretch, supplementary tidal volume, and inflammation 15 , 26 . Alveolus are subjected to uneven pressure, expansion and collapse, leading to local overstretch and changes in local pressure that can trigger the release of inflammatory cytokines, leukocyte recruitment, and initiation of local inflammatory processes 27 . A strength of the study is that we applied EIT for the first time to monitor pendelluft in critically ill patients receiving non-invasive mechanical ventilation therapy. This factor helps assess the real-time ventilatory status and quantifies the strength of spontaneous breathing during supportive treatment, providing clinicians with additional information to evaluate the patients' condition.The main limitation of the study is we enrolled only 37 hypoxemic patients undergoing non-invasive mechanical ventilation,with limited etiological species, and there was no continuous multipoint monitoring. Moreover, the small sample size and predominant etiological types included in the study, due to the COVID-19 pandemic outbreak occurring during the research period, may limit the ability to predict non-invasive mechanical ventilation failure using pendelluft. There is no further research to indicate whether excessive pendelluft may cause harm to patients. Besides,the research should continue with multi-site, continuous, and dynamic monitoring to observe the trends in pendelluft changes and identify a critical threshold that better describes patients’ ventilation patterns. Our study indicates that patients in need of NIV are mostly those with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) and CAP. Furthermore, our study did not conduct etiology-based subgroup analyses, which was also due to the limitation in the number of cases. Lastly, although our cohort is the new study on this subject, another limitation of the study is our successful group had much less patients than the failed group. We will continue to expand the sample size and increase the factors analyzed to further elucidate the predictive capacity of pendelluft for NIV failure. Conclusions The pendelluft monitored by EIT can effectively predict the failure of noninvasive mechanical ventilation and has a higher specificity compared to the PaO2/FiO2. It is of great clinical significance in reducing the rate of delayed tracheal intubation and improving the effectiveness of NIV treatment. Declarations Author contributions: LW contributed to the experimentation, data analysis, and preparation of the manuscript. KJQ contributed to the research concept and oversaw the study. PH and WXZ contributed to data analysis, manuscript writing, and revision. NZ and YP contributed to the performance of the experiments. FL contributed to the revision of the manuscript by making important edits and additions. YHL contributed to the article by guiding the statistical analysis. Data availability statement: The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author. Competing interests : The authors declare no competing interests References Brochard, L. et al. Reversal of acute exacerbations of chronic obstructive lung disease by inspiratory assistance with a face mask. N Engl J Med 323 , 1523-1530, doi:10.1056/NEJM199011293232204 (1990). Popowicz, P. & Leonard, K. Noninvasive Ventilation and Oxygenation Strategies. Surg Clin North Am 102 , 149-157, doi:10.1016/j.suc.2021.09.012 (2022). Wang, H. & He, H. ECCO2R and NIV-NAVA for stepwise early weaning in extremely severe COPD patients: a promising solution with details to be defined. Crit Care 24 , 26, doi:10.1186/s13054-020-2735-8 (2020). Bellani, G. et al. Noninvasive Ventilation of Patients with Acute Respiratory Distress Syndrome. Insights from the LUNG SAFE Study. Am J Respir Crit Care Med 195 , 67-77, doi:10.1164/rccm.201606-1306OC (2017). Naymagon, L. et al. Admission D-dimer levels, D-dimer trends, and outcomes in COVID-19. Thromb Res 196 , 99-105, doi:10.1016/j.thromres.2020.08.032 (2020). Tatum, D. et al. Neutrophil-to-Lymphocyte Ratio and Outcomes in Louisiana COVID-19 Patients. Shock 54 , 652-658, doi:10.1097/SHK.0000000000001585 (2020). Bhargava, A. et al. Predictors for Severe COVID-19 Infection. Clin Infect Dis 71 , 1962-1968, doi:10.1093/cid/ciaa674 (2020). Shah, P. et al. Prognostic Value of Elevated Cardiac Troponin I in Hospitalized Covid-19 Patients. Am J Cardiol 135 , 150-153, doi:10.1016/j.amjcard.2020.08.041 (2020). Antonelli, M. et al. Predictors of failure of noninvasive positive pressure ventilation in patients with acute hypoxemic respiratory failure: a multi-center study. Intensive Care Med 27 , 1718-1728, doi:10.1007/s00134-001-1114-4 (2001). Duan, J. et al. An updated HACOR score for predicting the failure of noninvasive ventilation: a multicenter prospective observational study. Crit Care 26 , 196, doi:10.1186/s13054-022-04060-7 (2022). Frat, J. P. et al. Predictors of Intubation in Patients With Acute Hypoxemic Respiratory Failure Treated With a Noninvasive Oxygenation Strategy. Crit Care Med 46 , 208-215, doi:10.1097/CCM.0000000000002818 (2018). Yoshida, T. et al. Spontaneous effort causes occult pendelluft during mechanical ventilation. Am J Respir Crit Care Med 188 , 1420-1427, doi:10.1164/rccm.201303-0539OC (2013). Yoshida, T., Fujino, Y., Amato, M. B. & Kavanagh, B. P. Fifty Years of Research in ARDS. Spontaneous Breathing during Mechanical Ventilation. Risks, Mechanisms, and Management. Am J Respir Crit Care Med 195 , 985-992, doi:10.1164/rccm.201604-0748CP (2017). Su, P. L., Zhao, Z., Ko, Y. F., Chen, C. W. & Cheng, K. S. Spontaneous Breathing and Pendelluft in Patients with Acute Lung Injury: A Narrative Review. J Clin Med 11 , doi:10.3390/jcm11247449 (2022). Chi, Y., Zhao, Z., Frerichs, I., Long, Y. & He, H. Prevalence and prognosis of respiratory pendelluft phenomenon in mechanically ventilated ICU patients with acute respiratory failure: a retrospective cohort study. Ann Intensive Care 12 , 22, doi:10.1186/s13613-022-00995-w (2022). Bachmann, M. C. et al. Electrical impedance tomography in acute respiratory distress syndrome. Crit Care 22 , 263, doi:10.1186/s13054-018-2195-6 (2018). Shu, W. et al. Association between ARDS Etiology and Risk of Noninvasive Ventilation Failure. Ann Am Thorac Soc 19 , 255-263, doi:10.1513/AnnalsATS.202102-161OC (2022). Chawla, R. et al. Acute respiratory distress syndrome: Predictors of noninvasive ventilation failure and intensive care unit mortality in clinical practice. J Crit Care 31 , 26-30, doi:10.1016/j.jcrc.2015.10.018 (2016). De Vita, N. et al. Predictors of intubation in COVID-19 patients treated with out-of-ICU continuous positive airway pressure. Pulmonology 28 , 173-180, doi:10.1016/j.pulmoe.2020.12.010 (2022). Ferreyro, B. L. et al. Association of Noninvasive Oxygenation Strategies With All-Cause Mortality in Adults With Acute Hypoxemic Respiratory Failure: A Systematic Review and Meta-analysis. JAMA 324 , 57-67, doi:10.1001/jama.2020.9524 (2020). Jha, O. K., Kumar, S., Mehra, S., Sircar, M. & Gupta, R. Helmet NIV in Acute Hypoxemic Respiratory Failure due to COVID-19: Change in PaO(2)/FiO(2) Ratio a Predictor of Success. Indian J Crit Care Med 25 , 1137-1146, doi:10.5005/jp-journals-10071-23992 (2021). Greenblatt, E. E., Butler, J. P., Venegas, J. G. & Winkler, T. Pendelluft in the bronchial tree. J Appl Physiol (1985) 117 , 979-988, doi:10.1152/japplphysiol.00466.2014 (2014). Tonelli, R. et al. Early Inspiratory Effort Assessment by Esophageal Manometry Predicts Noninvasive Ventilation Outcome in De Novo Respiratory Failure. A Pilot Study. Am J Respir Crit Care Med 202 , 558-567, doi:10.1164/rccm.201912-2512OC (2020). Avdeev, S. N., Yaroshetskiy, A. I. & Nuralieva, G. S. Can We Reliably Predict the Failure of Noninvasive Ventilation in COVID-19-associated Acute Hypoxemic Respiratory Failure? Ann Am Thorac Soc 18 , 1595, doi:10.1513/AnnalsATS.202101-047LE (2021). Carteaux, G. et al. Failure of Noninvasive Ventilation for De Novo Acute Hypoxemic Respiratory Failure: Role of Tidal Volume. Crit Care Med 44 , 282-290, doi:10.1097/CCM.0000000000001379 (2016). Sang, L. et al. Qualitative and quantitative assessment of pendelluft: a simple method based on electrical impedance tomography. Ann Transl Med 8 , 1216, doi:10.21037/atm-20-4182 (2020). Kuchnicka, K. & Maciejewski, D. Ventilator-associated lung injury. Anaesthesiol Intensive Ther 45 , 164-170, doi:10.5603/AIT.2013.0034 (2013). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4315149","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":299367089,"identity":"b4d3362a-8d03-4d39-99ff-98777abd891a","order_by":0,"name":"ling wu","email":"","orcid":"","institution":"Department of Intensive Care Unit, The First Affiliated Hospital of Nanchang University, Nanchang","correspondingAuthor":false,"prefix":"","firstName":"ling","middleName":"","lastName":"wu","suffix":""},{"id":299367092,"identity":"de306bf6-19d1-4dcb-97e9-621fb59bf023","order_by":1,"name":"Xuzhen Wang","email":"","orcid":"","institution":"Department of Intensive Care Unit, The First Affiliated Hospital of Nanchang University, Nanchang","correspondingAuthor":false,"prefix":"","firstName":"Xuzhen","middleName":"","lastName":"Wang","suffix":""},{"id":299367095,"identity":"31adbc2b-a7a6-4c8d-88ba-facbaf68e279","order_by":2,"name":"Ping Hu","email":"","orcid":"","institution":"Department of Intensive Care Unit, The First Affiliated Hospital of Nanchang University, Nanchang","correspondingAuthor":false,"prefix":"","firstName":"Ping","middleName":"","lastName":"Hu","suffix":""},{"id":299367098,"identity":"8f84be0a-f1e9-40b2-ae48-86af3b83e1df","order_by":3,"name":"Ye Pan","email":"","orcid":"","institution":"Department of Intensive Care Unit, The First Affiliated Hospital of Nanchang University, Nanchang","correspondingAuthor":false,"prefix":"","firstName":"Ye","middleName":"","lastName":"Pan","suffix":""},{"id":299367100,"identity":"9f0147f1-3560-4028-9026-5a9228497240","order_by":4,"name":"Ning Zhao","email":"","orcid":"","institution":"Department of Intensive Care Unit, The First Affiliated Hospital of Nanchang University, Nanchang","correspondingAuthor":false,"prefix":"","firstName":"Ning","middleName":"","lastName":"Zhao","suffix":""},{"id":299367102,"identity":"426254da-7ad3-43e9-b74f-293b2733dae6","order_by":5,"name":"Yuanhua Lu","email":"","orcid":"","institution":"Department of Intensive Care Unit, The First Affiliated Hospital of Nanchang University, Nanchang","correspondingAuthor":false,"prefix":"","firstName":"Yuanhua","middleName":"","lastName":"Lu","suffix":""},{"id":299367103,"identity":"699b5785-185e-44ef-bdb2-794cceb68d87","order_by":6,"name":"Fen Liu","email":"","orcid":"","institution":"Department of Intensive Care Unit, The First Affiliated Hospital of Nanchang University, Nanchang","correspondingAuthor":false,"prefix":"","firstName":"Fen","middleName":"","lastName":"Liu","suffix":""},{"id":299367104,"identity":"e1e79cd2-6054-4410-89fb-04003da01498","order_by":7,"name":"Kejian Qian","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA20lEQVRIiWNgGAWjYBACfvbmgw8+8LDJ2d8/fIA4LZI9x5INZ8jwGTPcYEsgTovBDR8zaR4bucSGGzwGRLoMaLgET44ZY+Psno833jDYyek2ENDBOLv5gIHEmTRmZpmzmy3nMCQbmx0goIVZ5lhCgmHPMTY2htxt0jwMBxK3EdLCJpFjcCDx338eHoacZ8Rp4ZHIMWw4wMMmISGRw0acFgmeY8mMDTxsBgY8x4wt5xgQ4Rf7483Hf//hYavfwN788MabCjs5glrQrCQ2apC0kKpjFIyCUTAKRgQAAF7DQmT96lytAAAAAElFTkSuQmCC","orcid":"","institution":"Department of Intensive Care Unit, The First Affiliated Hospital of Nanchang University, Nanchang","correspondingAuthor":true,"prefix":"","firstName":"Kejian","middleName":"","lastName":"Qian","suffix":""}],"badges":[],"createdAt":"2024-04-24 03:19:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4315149/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4315149/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":56099615,"identity":"3b2eb32f-38f3-4bae-97bf-d9315a1efd95","added_by":"auto","created_at":"2024-05-08 14:26:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":46079,"visible":true,"origin":"","legend":"\u003cp\u003eROI region\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4315149/v1/db8cf6704599a00b96fba13b.png"},{"id":56099616,"identity":"36345d89-1621-470d-a400-256c0587b918","added_by":"auto","created_at":"2024-05-08 14:26:53","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":263640,"visible":true,"origin":"","legend":"\u003cp\u003eMonitoring diagram\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4315149/v1/9f527967ceafbbacc8c89af3.png"},{"id":56099613,"identity":"9e7e1906-39ea-4b32-a39a-dc1af1571f13","added_by":"auto","created_at":"2024-05-08 14:26:52","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":48435,"visible":true,"origin":"","legend":"\u003cp\u003eThe Study Flowchart\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4315149/v1/ea5e5a73a27ce366abeaf105.png"},{"id":56099614,"identity":"b43d4e3f-ded5-4910-ab88-b821a74bb520","added_by":"auto","created_at":"2024-05-08 14:26:52","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":62510,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of pendelluft and PaO\u003csub\u003e2\u003c/sub\u003e/FiO\u003csub\u003e2\u003c/sub\u003e between the two groups\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4315149/v1/64b391a3697f589828f81958.png"},{"id":56099617,"identity":"9ac3cb65-72fd-452f-9fe6-b23e0eafce89","added_by":"auto","created_at":"2024-05-08 14:26:53","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":64361,"visible":true,"origin":"","legend":"\u003cp\u003eThe ROC curve analysis\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4315149/v1/da46f4d987f4c769763ff1c9.png"},{"id":79410038,"identity":"637f0d70-8501-4551-98f5-1551cfc7b9d9","added_by":"auto","created_at":"2025-03-28 05:40:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1194069,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4315149/v1/09183ab9-18ec-4ea4-9b38-a8e0a4eaaa8e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Monitoring the Pendelluft by EIT could predict the failure of non-invasive mechanical ventilation:A Prospective Study","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eSince the development and application of mechanical ventilation in patients with COPD in 1990\u003csup\u003e1\u003c/sup\u003e, it has been widely used due to its ability to open collapsed alveolar, increase lung volume\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, improve lung ventilation/ perfusion matching(V/Q), and correct respiratory acidosis\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. However, the mortality rate is significantly higher for patients with acute respiratory failure who fail non-invasive mechanical ventilation compared to invasive mechanical ventilation\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Recent studies have shown that D-dimer levels\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, Neutrophil-to-Lymphocyte Ratio\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e, C-reactive protein (CRP), creatinine\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, and Cardiac Troponin I\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e at admission are associated with an increased risk of endotracheal intubation. A study by M. Antonelli et al.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003ein 2021 proposed that an PaO2/FiO2\u0026thinsp;\u0026le;\u0026thinsp;146 mmHg after 1 hour of NIV treatment can predict NIV failure. Additionally, there has an updated HACOR score to assess the failure of non-invasive mechanical ventilation\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. However, current research indicators are easily affected by factors such as infection and overall health, which leads to a lack of strong timeliness and low specificity. Additionally, the majority of them are invasive procedures.Therefore, identifying the failure of non-invasive mechanical ventilation and avoiding ineffective or potentially harmful non-invasive ventilation\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e is currently a focus of clinical research.\u003c/p\u003e \u003cp\u003eWe have developed a non-invasive, timely, accurate, and highly reproducible method to monitor lung ventilation. The objective is to predict the failure of non-invasive mechanical ventilation.Respiratory pendelluft refers to the process in which gas is unevenly distributed within some alveoli during the inspiration movement in the lungs, without significantly affecting the overall tidal volume\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e.The pendelluft phenomenon is found to be associated with the presence of spontaneous respiration during invasive mechanical ventilation\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e and is also related to the duration of invasive mechanical ventilation.Sang Ling et al.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e found that Electrical Impedance Tomography (EIT) can monitor pendelluft in patients with flail chest, acute respiratory distress syndrome (ARDS), and acute exacerbation of chronic obstructive pulmonary disease (COPD).EIT is a bedside, real-time, non-invasive, and radiation-free monitoring device.It is currently the only instrument capable of repeatedly measuring lung ventilation, blood flow, and other parameters\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTherefore, we propose, for the first time, the use of EIT to monitor pendelluft in predicting non-invasive mechanical ventilation failure. By using intuitive quantitative data to assess the effectiveness of non-invasive ventilation, we can guide clinicians in the early detection of appropriate weaning and intubation timing, improve patient survival rates, and reduce the burden on healthcare systems.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003eThis is a single-center, prospective, observational study conducted at the First Affiliated Hospital of Nanchang University. The study included patients who received non-invasive mechanical ventilation from December 2021 to March 2023 in the Department of Intensive Care Medicine. The study received approval and underwent review by the Clinical Research Committee of the First Affiliated Hospital of Nanchang University, with an ethics number of IIT2022090. The study affirms that all research activities were conducted in accordance with applicable guidelines and regulations. We confirm that informed consent was obtained from all participants and/or their legal guardians. Research involving human participants was conducted in accordance with the principles outlined in the Declaration of Helsinki.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients and measurements\u003c/h2\u003e \u003cp\u003ePatients who were admitted to the ICU due to symptoms of acute respiratory failure and required non-invasive mechanical ventilation were included. The age of Recruited patients was between 18 and 80 years, and the ICU stay needed to be longer than 24 hours. The exclusion criteria were as follows: hemodynamic instability (mean arterial pressure\u0026thinsp;\u0026le;\u0026thinsp;65 mmHg), acute myocardial infarction within one week of onset, severe arrhythmias, implanted cardiac pacemakers, pulmonary surgery within 48 hours, injuries to the airway, thoracic cavity, chest wall, or cranial-brain injury, respiratory arrest requiring emergency intubation, inability to clear secretions, lack of spontaneous respiration, increased intracranial pressure, and patients who are pregnant or breastfeeding.\u003c/p\u003e \u003cp\u003eFor patients who met the inclusion and exclusion criteria, the Philips V60 non-invasive ventilator was used. The basic settings included bilevel positive airway pressure ventilation in S/T (Spontaneous/Triggered) mode, with an initial IPAP setting of 4 cmH2O and EPAP of 12 cmH2O. The respiratory rate was set at 12 breaths per minute, and the oxygen concentration was adjusted to maintain the patient\u0026rsquo;s oxygen saturation above 90%. The respiratory parameters of the patient were adjusted by two or more attending physicians with senior professional titles and respiratory therapists based on the patient\u0026rsquo;s clinical presentation and laboratory results. Patients were encouraged to cooperate with breathing to maintain a pH level between 7.35 and 7.45. The mask covering the nose and mouth was tightly secured to prevent air leaks, and regular examinations of skin pressure marks were conducted.\u003c/p\u003e \u003cp\u003eThe following conditions require intubation: persistent changes in mental status, continuous worsening of respiratory distress, hypotension, elevated carbon dioxide partial pressure, a decrease in pH value by 0.05\u0026ndash;0.1, etc. The decision to intubate patients is made by the attending physician, and if a patient undergoes endotracheal intubation, it is defined as a failure of non-invasive mechanical ventilation.\u003c/p\u003e \u003cp\u003eContinuous assessment of patients is conducted, and the duration and level of non-invasive mechanical ventilation support are gradually reduced based on clinical symptoms and laboratory indicators. Oxygen is administered for 15 minutes without ventilatory support. If the patient\u0026rsquo;s respiratory frequency is less than 30 breaths per minute, PaO\u003csub\u003e2\u003c/sub\u003e is above 75mmHg, and FiO\u003csub\u003e2\u003c/sub\u003e is 50%, ventilatory support is discontinued.\u003c/p\u003e \u003cp\u003eBaseline data, vital signs, and arterial blood gas measurements were collected when patients were admitted to the ICU and received non-invasive ventilation (NIV). The baseline data included age, gender, primary disease, and disease severity (APACHE II, SOFA scores). Vital signs included heart rate, respiratory rate, mean arterial pressure (MAP), and blood gas analysis included pH, PaO\u003csub\u003e2\u003c/sub\u003e, and PaCO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eMonitoring the pendelluft level in each ROI region\u003c/h2\u003e \u003cp\u003eThe cross-section of the chest was divided into four equal parts in a \u0026ldquo;cross-shaped\u0026rdquo; pattern, which were designated as ROI1, ROI2, ROI3, and ROI4(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePatients who accept non-invasive mechanical ventilation underwent EIT monitoring during the first 24 hours(Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The pendelluft data was collected for 5 minutes during regular breathing without any other interventions related to the study. EIT images were continuously recorded at a frequency of 50 Hz and saved in a specific folder. A low-pass filter with a cut-off frequency of 50 cycles per minute was applied to the data to eliminate impedance changes related to the heart.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe Evaluation Pendelluft software was used to calculate the pendelluft level. The pendelluft amplitude based on EIT was defined as the impedance difference between the sum of all regional tidal impedance changes and the global tidal impedance changes. The regional phase shift or time was defined as the time difference between the global and regional impedance-time curves. These parameters were then evaluated to measure the pendelluft.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eUsing PASS 23.0 software, sample size estimation is performed based on rates and their confidence intervals. The overall rate is 10%, with a tolerable error of 0.1 and α\u0026thinsp;=\u0026thinsp;0.05. The calculation yields N\u0026thinsp;=\u0026thinsp;35 cases. Normality analysis is conducted on all the data. Independent sample t-test is applied for inter-group comparisons, while nonparametric tests are used for non-normally distributed quantitative data. T-test analysis is used to determine the statistical differences between the two groups. The area under the receiver operating characteristic curve is employed to evaluate the predictive ability of non-invasive mechanical ventilation failure. A p-value less than 0.05 is considered statistically significant\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eThe patient screening process is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, and a total of 37 patients were included based on the inclusion criteria. According to whether the patients underwent tracheal intubation, they were divided into the noninvasive mechanical ventilation failure group (N\u0026thinsp;=\u0026thinsp;27) and the noninvasive mechanical ventilation success group (N\u0026thinsp;=\u0026thinsp;11) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). There were no statistically significant differences in demographic baseline characteristics, vital signs, or blood gas analysis between the two groups. However, the etiology analysis between the two groups suggested that CAP (Community-Acquired Pneumonia) was a risk factor for noninvasive mechanical ventilation in such patients (65.4% vs 36.4%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of participants across study arms\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFailed group(n\u0026thinsp;=\u0026thinsp;26)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSuccessful group(n\u0026thinsp;=\u0026thinsp;11)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaseline characteristics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge,median,years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58.27\u0026thinsp;\u0026plusmn;\u0026thinsp;11.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.09\u0026thinsp;\u0026plusmn;\u0026thinsp;17.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.865\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale sex,n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23(88.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9(81.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.623\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI,kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.76\u0026thinsp;\u0026plusmn;\u0026thinsp;3.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.73\u0026thinsp;\u0026plusmn;\u0026thinsp;3.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.428\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAPACHE II at ICU admission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.04\u0026thinsp;\u0026plusmn;\u0026thinsp;7.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.36\u0026thinsp;\u0026plusmn;\u0026thinsp;4.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.453\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOFA at ICU admission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.88\u0026thinsp;\u0026plusmn;\u0026thinsp;2.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.73\u0026thinsp;\u0026plusmn;\u0026thinsp;3.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.222\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart rate, beats/min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96.77\u0026thinsp;\u0026plusmn;\u0026thinsp;14.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97.09\u0026thinsp;\u0026plusmn;\u0026thinsp;21.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.958\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean Artery Pressure,mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91.88\u0026thinsp;\u0026plusmn;\u0026thinsp;14.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89.26\u0026thinsp;\u0026plusmn;\u0026thinsp;17.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.639\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.660\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePaCO\u003csub\u003e2\u003c/sub\u003e,mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41.5(33.5, 54.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49(36, 76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.231\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePaO\u003csub\u003e2\u003c/sub\u003e,mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79(60.5, 104.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92(75, 113)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eBaseline Ventilator Settings, median\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory rate, breaths/min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29.12\u0026thinsp;\u0026plusmn;\u0026thinsp;8.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.82\u0026thinsp;\u0026plusmn;\u0026thinsp;5.671\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.377\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTidal Volume, ml\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e535(425, 772.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e520(470, 620)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.781\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEPAP, cmH2O\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.96\u0026thinsp;\u0026plusmn;\u0026thinsp;2.877\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.36\u0026thinsp;\u0026plusmn;\u0026thinsp;3.264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.711\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIPAP, cmH2O\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.891\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.09\u0026thinsp;\u0026plusmn;\u0026thinsp;1.136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.968\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eEtiology of Acute respiratory failure, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.902\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAECOPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3(11.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(45.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCAP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17(65.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4(36.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eothers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6(23.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(18.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.157\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eCompared to the failure group, the success group showed statistically significant differences in pendelluft amplitude, inspiration phase, and expiration phase time in each region of interest (ROI) (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The total pendelluft amplitude in the failure group was 7.7538 (2.6880, 25.8338), while in the success group, it was 122.3226 (8.5493, 193.8191). The comparison between the two groups demonstrated a significantly higher pendelluft amplitude in the success group.Compared to the PaO2/FiO2 of the failure group (median of 131 (86.75, 211.87) mmHg), the median PaO2/FiO2 of the success group was significantly higher at 250 (185, 323) mmHg, with a statistically significant difference (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of pendelluft and PaO\u003csub\u003e2\u003c/sub\u003e/FiO\u003csub\u003e2\u003c/sub\u003e between the two groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAmplitude of pendelluft\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eAll patients (n\u0026thinsp;=\u0026thinsp;37)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFailed group(n\u0026thinsp;=\u0026thinsp;26)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSuccessful group(n\u0026thinsp;=\u0026thinsp;11)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eROI 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.2365(0.3211, 5.3548)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.3356(3.3655, 43.0755)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eROI 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.3428(0.2750, 2.6985)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.6097(1.3890, 44.5917)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eROI 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.1372(0.3784, 13.3705)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58.8901(2.3608, 83.4699)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eROI 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.2333(0.1807, 4.9616)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.0811(2.4332, 22.4161)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.7538(2.6880, 25.8338)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e122.3226(8.5493, 193.8191)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eTime difference\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003einspiration, s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1375(0.05, 0.225)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3(0.2, 0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eexpiration, s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1(0.05, 0.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5(0.1, 0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePaO\u003csub\u003e2\u003c/sub\u003e/FiO\u003csub\u003e2\u003c/sub\u003e(mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e131(86.75, 211.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e250(185, 323)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eData are listed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe ROC curve analysis was conducted on the sum of pendelluft amplitude, inspiratory time, expiratory time, and PaO2/FiO2. The results are as follows:The AUC for the sum of pendelluft amplitude in assessing the effectiveness of non-invasive mechanical ventilation was 0.815 [95% CI (0.643\u0026ndash;0.986), P\u0026thinsp;=\u0026thinsp;0.003]. The sensitivity was 72.7% and the specificity was 92.3%.The AUC for inspiratory time in assessing the effectiveness of non-invasive mechanical ventilation was 0.799 [95% CI (0.636\u0026ndash;0.962), P\u0026thinsp;=\u0026thinsp;0.004]. The sensitivity was 45.5% and the specificity was 96.2%.The AUC for expiratory time in assessing the effectiveness of non-invasive mechanical ventilation was 0.774 [95% CI (0.622\u0026ndash;0.926), P\u0026thinsp;=\u0026thinsp;0.009]. The sensitivity was 100% and the specificity was 42.3%.The AUC for the PaO2/FiO2 in assessing the effectiveness of non-invasive mechanical ventilation was 0.787 [95% CI (0.640\u0026ndash;0.933), P\u0026thinsp;=\u0026thinsp;0.006]. The sensitivity was 90.9% and the specificity was 57.7%.\u003c/p\u003e \u003cp\u003eThese results suggest that the evaluation value of the sum of pendelluft amplitude is slightly higher than that of the PaO2/FiO2, with a significant improvement in specificity. By choosing the maximum Youden index, the optimal cutoff values for the sum of pendelluft amplitude, inspiratory time, expiratory time, and PaO2/FiO2 were found to be 45.1124, 0.475s, 0.075s, and 153 mmHg, respectively. When the sum of pendelluft amplitude is greater than 45.1124 or the PaO2/FiO2 is greater than 153 mmHg, the likelihood of non-invasive mechanical ventilation failure is higher (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eROC curve analysis that impacts the effectiveness of non-invasive mechanical ventilation.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcomes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCut-off\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSensitivity(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSpecificity(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePendelluft amplitude\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.815\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.643\u0026ndash;0.986\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.1124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e72.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e92.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime difference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003einspiration, s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.799\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.636\u0026ndash;0.962\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.475\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e45.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e96.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eexpiration, s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.774\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.622\u0026ndash;0.926\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.075\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e42.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePaO\u003csub\u003e2\u003c/sub\u003e/FiO\u003csub\u003e2\u003c/sub\u003e(mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.640\u0026ndash;0.933\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e90.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e57.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eOur study found that using EIT to monitor pendelluft can predict the failure of non-invasive mechanical ventilation. When the pendelluft amplitude is less than 45.1124, there may be an increased risk of non-invasive mechanical ventilation failure. Compared to the PaO2/FiO2, pendelluft has higher accuracy and specificity in predicting non-invasive mechanical ventilation failure.\u003c/p\u003e \u003cp\u003eSome high-quality studies suggest that there is still skepticism regarding the effectiveness of NIV treatment\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.Giacomo Bellani's research\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e shows that the mortality rate among patients who experience NIV failure is 45.4%. This rate increases to 69% for those who experience NIV failure\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Delaying intubation also worsens the prognosis of patients with acute respiratory failure\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e.However,the NIV still has benefits in reducing endotracheal intubation and death in patients\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.This leads us to approach NIV treatment with even more prudence.Therefore, predicting NIV failure has always been a research focus in clinical practice.\u003c/p\u003e \u003cp\u003eIn previous reports\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, it has been demonstrated that an updated HACOR scale can predict failure of noninvasive mechanical ventilation.Onkar K Jha et al.'s study\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e showed that the oxygenation index improves within 24 hours after treatment and is greater than 161mmHg, which can successfully predict the effectiveness of non-invasive mechanical ventilation in patients. Our study similarly confirms that an oxygenation index of less than 153mmHg predicts failure of non-invasive mechanical ventilation.However, these indicators require certain invasive procedures and are susceptible to the influence of the underlying disease of the patients. Therefore, our study proposes a non-invasive and objective indicator to predict the failure of non-invasive mechanical ventilation.\u003c/p\u003e \u003cp\u003ePendelluft is a variable that allows real-time monitoring of ventilation near the bed using Electrical Impedance Tomography (EIT), allowing specific observation of lung ventilation and quantification of respiratory indices related to autonomous breathing.Greenblatt et al.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003efound that pendelluft is primarily concentrated in regions of poor lung ventilation, and this preferential oscillation may contribute to local gas exchange. Takeshi Yoshida et al.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e confirmed this viewpoint, pendelluft phenomenon is primarily concentrated in the posterior region of the lungs. Therefore, pendelluft phenomenon within a certain range may be beneficial for lung ventilation.\u003c/p\u003e \u003cp\u003eOur research indicates that the incidence of intubation is lower when the amplitude of pendelluft is \u0026gt;\u0026thinsp;45.1124. This demonstrates that higher pendelluft amplitude, especially when occurring in restrictive ventilation zones, may improve patient ventilation during NIV.\u003c/p\u003e \u003cp\u003eDespite the description of pendelluft phenomenon, its full impact on the lungs is still not fully understood. Tonelli et al.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e found that excessive spontaneous inspiratory effort in patients is associated with NIV failure. Furthermore, in patients receiving NIV outside of the ICU\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, those who experienced NIV failure exhibited higher minute ventilation on the first day (due to slightly higher tidal volume and respiratory rate), which may be related to the increased risk of lung injury caused by excessively strong drive for spontaneous breathing. Guillaume Carteaux et al.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e shown that a tidal volume exceeding 9.5 mL/kg can predict the failure of noninvasive ventilation.However, current clinical research does not provide a clear answer as to whether pendelluft causes injury. In some studies on invasive mechanical ventilation,pendelluft may potentially pose harm by introducing local overstretch, supplementary tidal volume, and inflammation\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Alveolus are subjected to uneven pressure, expansion and collapse, leading to local overstretch and changes in local pressure that can trigger the release of inflammatory cytokines, leukocyte recruitment, and initiation of local inflammatory processes\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eA strength of the study is that we applied EIT for the first time to monitor pendelluft in critically ill patients receiving non-invasive mechanical ventilation therapy. This factor helps assess the real-time ventilatory status and quantifies the strength of spontaneous breathing during supportive treatment, providing clinicians with additional information to evaluate the patients' condition.The main limitation of the study is we enrolled only 37 hypoxemic patients undergoing non-invasive mechanical ventilation,with limited etiological species, and there was no continuous multipoint monitoring. Moreover, the small sample size and predominant etiological types included in the study, due to the COVID-19 pandemic outbreak occurring during the research period, may limit the ability to predict non-invasive mechanical ventilation failure using pendelluft. There is no further research to indicate whether excessive pendelluft may cause harm to patients. Besides,the research should continue with multi-site, continuous, and dynamic monitoring to observe the trends in pendelluft changes and identify a critical threshold that better describes patients\u0026rsquo; ventilation patterns. Our study indicates that patients in need of NIV are mostly those with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) and CAP. Furthermore, our study did not conduct etiology-based subgroup analyses, which was also due to the limitation in the number of cases. Lastly, although our cohort is the new study on this subject, another limitation of the study is our successful group had much less patients than the failed group. We will continue to expand the sample size and increase the factors analyzed to further elucidate the predictive capacity of pendelluft for NIV failure.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe pendelluft monitored by EIT can effectively predict the failure of noninvasive mechanical ventilation and has a higher specificity compared to the PaO2/FiO2. It is of great clinical significance in reducing the rate of delayed tracheal intubation and improving the effectiveness of NIV treatment.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u003c/strong\u003e LW contributed to the experimentation, data analysis, and preparation of the manuscript. KJQ contributed to the research concept and oversaw the study. PH and WXZ contributed to data analysis, manuscript writing, and revision. NZ and YP contributed to the performance of the experiments. FL contributed to the revision of the manuscript by making important edits and additions. YHL contributed to the article by guiding the statistical analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement:\u003c/strong\u003e The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eThe authors declare no competing interests\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eBrochard, L.\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e Reversal of acute exacerbations of chronic obstructive lung disease by inspiratory assistance with a face mask. \u003cem\u003eN Engl J Med\u003c/em\u003e \u003cstrong\u003e323\u003c/strong\u003e, 1523-1530, doi:10.1056/NEJM199011293232204 (1990).\u003c/li\u003e\n \u003cli\u003ePopowicz, P. \u0026amp; Leonard, K. Noninvasive Ventilation and Oxygenation Strategies. \u003cem\u003eSurg Clin North Am\u003c/em\u003e \u003cstrong\u003e102\u003c/strong\u003e, 149-157, doi:10.1016/j.suc.2021.09.012 (2022).\u003c/li\u003e\n \u003cli\u003eWang, H. \u0026amp; He, H. ECCO2R and NIV-NAVA for stepwise early weaning in extremely severe COPD patients: a promising solution with details to be defined. \u003cem\u003eCrit Care\u003c/em\u003e \u003cstrong\u003e24\u003c/strong\u003e, 26, doi:10.1186/s13054-020-2735-8 (2020).\u003c/li\u003e\n \u003cli\u003eBellani, G.\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e Noninvasive Ventilation of Patients with Acute Respiratory Distress Syndrome. Insights from the LUNG SAFE Study. \u003cem\u003eAm J Respir Crit Care Med\u003c/em\u003e \u003cstrong\u003e195\u003c/strong\u003e, 67-77, doi:10.1164/rccm.201606-1306OC (2017).\u003c/li\u003e\n \u003cli\u003eNaymagon, L.\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e Admission D-dimer levels, D-dimer trends, and outcomes in COVID-19. \u003cem\u003eThromb Res\u003c/em\u003e \u003cstrong\u003e196\u003c/strong\u003e, 99-105, doi:10.1016/j.thromres.2020.08.032 (2020).\u003c/li\u003e\n \u003cli\u003eTatum, D.\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e Neutrophil-to-Lymphocyte Ratio and Outcomes in Louisiana COVID-19 Patients. \u003cem\u003eShock\u003c/em\u003e \u003cstrong\u003e54\u003c/strong\u003e, 652-658, doi:10.1097/SHK.0000000000001585 (2020).\u003c/li\u003e\n \u003cli\u003eBhargava, A.\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e Predictors for Severe COVID-19 Infection. \u003cem\u003eClin Infect Dis\u003c/em\u003e \u003cstrong\u003e71\u003c/strong\u003e, 1962-1968, doi:10.1093/cid/ciaa674 (2020).\u003c/li\u003e\n \u003cli\u003eShah, P.\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e Prognostic Value of Elevated Cardiac Troponin I in Hospitalized Covid-19 Patients. \u003cem\u003eAm J Cardiol\u003c/em\u003e \u003cstrong\u003e135\u003c/strong\u003e, 150-153, doi:10.1016/j.amjcard.2020.08.041 (2020).\u003c/li\u003e\n \u003cli\u003eAntonelli, M.\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e Predictors of failure of noninvasive positive pressure ventilation in patients with acute hypoxemic respiratory failure: a multi-center study. \u003cem\u003eIntensive Care Med\u003c/em\u003e \u003cstrong\u003e27\u003c/strong\u003e, 1718-1728, doi:10.1007/s00134-001-1114-4 (2001).\u003c/li\u003e\n \u003cli\u003eDuan, J.\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e An updated HACOR score for predicting the failure of noninvasive ventilation: a multicenter prospective observational study. \u003cem\u003eCrit Care\u003c/em\u003e \u003cstrong\u003e26\u003c/strong\u003e, 196, doi:10.1186/s13054-022-04060-7 (2022).\u003c/li\u003e\n \u003cli\u003eFrat, J. P.\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e Predictors of Intubation in Patients With Acute Hypoxemic Respiratory Failure Treated With a Noninvasive Oxygenation Strategy. \u003cem\u003eCrit Care Med\u003c/em\u003e \u003cstrong\u003e46\u003c/strong\u003e, 208-215, doi:10.1097/CCM.0000000000002818 (2018).\u003c/li\u003e\n \u003cli\u003eYoshida, T.\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e Spontaneous effort causes occult pendelluft during mechanical ventilation. \u003cem\u003eAm J Respir Crit Care Med\u003c/em\u003e \u003cstrong\u003e188\u003c/strong\u003e, 1420-1427, doi:10.1164/rccm.201303-0539OC (2013).\u003c/li\u003e\n \u003cli\u003eYoshida, T., Fujino, Y., Amato, M. B. \u0026amp; Kavanagh, B. P. Fifty Years of Research in ARDS. Spontaneous Breathing during Mechanical Ventilation. Risks, Mechanisms, and Management. \u003cem\u003eAm J Respir Crit Care Med\u003c/em\u003e \u003cstrong\u003e195\u003c/strong\u003e, 985-992, doi:10.1164/rccm.201604-0748CP (2017).\u003c/li\u003e\n \u003cli\u003eSu, P. L., Zhao, Z., Ko, Y. F., Chen, C. W. \u0026amp; Cheng, K. S. Spontaneous Breathing and Pendelluft in Patients with Acute Lung Injury: A Narrative Review. \u003cem\u003eJ Clin Med\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, doi:10.3390/jcm11247449 (2022).\u003c/li\u003e\n \u003cli\u003eChi, Y., Zhao, Z., Frerichs, I., Long, Y. \u0026amp; He, H. Prevalence and prognosis of respiratory pendelluft phenomenon in mechanically ventilated ICU patients with acute respiratory failure: a retrospective cohort study. \u003cem\u003eAnn Intensive Care\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 22, doi:10.1186/s13613-022-00995-w (2022).\u003c/li\u003e\n \u003cli\u003eBachmann, M. C.\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e Electrical impedance tomography in acute respiratory distress syndrome. \u003cem\u003eCrit Care\u003c/em\u003e \u003cstrong\u003e22\u003c/strong\u003e, 263, doi:10.1186/s13054-018-2195-6 (2018).\u003c/li\u003e\n \u003cli\u003eShu, W.\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e Association between ARDS Etiology and Risk of Noninvasive Ventilation Failure. \u003cem\u003eAnn Am Thorac Soc\u003c/em\u003e \u003cstrong\u003e19\u003c/strong\u003e, 255-263, doi:10.1513/AnnalsATS.202102-161OC (2022).\u003c/li\u003e\n \u003cli\u003eChawla, R.\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e Acute respiratory distress syndrome: Predictors of noninvasive ventilation failure and intensive care unit mortality in clinical practice. \u003cem\u003eJ Crit Care\u003c/em\u003e \u003cstrong\u003e31\u003c/strong\u003e, 26-30, doi:10.1016/j.jcrc.2015.10.018 (2016).\u003c/li\u003e\n \u003cli\u003eDe Vita, N.\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e Predictors of intubation in COVID-19 patients treated with out-of-ICU continuous positive airway pressure. \u003cem\u003ePulmonology\u003c/em\u003e \u003cstrong\u003e28\u003c/strong\u003e, 173-180, doi:10.1016/j.pulmoe.2020.12.010 (2022).\u003c/li\u003e\n \u003cli\u003eFerreyro, B. L.\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e Association of Noninvasive Oxygenation Strategies With All-Cause Mortality in Adults With Acute Hypoxemic Respiratory Failure: A Systematic Review and Meta-analysis. \u003cem\u003eJAMA\u003c/em\u003e \u003cstrong\u003e324\u003c/strong\u003e, 57-67, doi:10.1001/jama.2020.9524 (2020).\u003c/li\u003e\n \u003cli\u003eJha, O. K., Kumar, S., Mehra, S., Sircar, M. \u0026amp; Gupta, R. Helmet NIV in Acute Hypoxemic Respiratory Failure due to COVID-19: Change in PaO(2)/FiO(2) Ratio a Predictor of Success. \u003cem\u003eIndian J Crit Care Med\u003c/em\u003e \u003cstrong\u003e25\u003c/strong\u003e, 1137-1146, doi:10.5005/jp-journals-10071-23992 (2021).\u003c/li\u003e\n \u003cli\u003eGreenblatt, E. E., Butler, J. P., Venegas, J. G. \u0026amp; Winkler, T. Pendelluft in the bronchial tree. \u003cem\u003eJ Appl Physiol (1985)\u003c/em\u003e \u003cstrong\u003e117\u003c/strong\u003e, 979-988, doi:10.1152/japplphysiol.00466.2014 (2014).\u003c/li\u003e\n \u003cli\u003eTonelli, R.\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e Early Inspiratory Effort Assessment by Esophageal Manometry Predicts Noninvasive Ventilation Outcome in De Novo Respiratory Failure. A Pilot Study. \u003cem\u003eAm J Respir Crit Care Med\u003c/em\u003e \u003cstrong\u003e202\u003c/strong\u003e, 558-567, doi:10.1164/rccm.201912-2512OC (2020).\u003c/li\u003e\n \u003cli\u003eAvdeev, S. N., Yaroshetskiy, A. I. \u0026amp; Nuralieva, G. S. Can We Reliably Predict the Failure of Noninvasive Ventilation in COVID-19-associated Acute Hypoxemic Respiratory Failure? \u003cem\u003eAnn Am Thorac Soc\u003c/em\u003e \u003cstrong\u003e18\u003c/strong\u003e, 1595, doi:10.1513/AnnalsATS.202101-047LE (2021).\u003c/li\u003e\n \u003cli\u003eCarteaux, G.\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e Failure of Noninvasive Ventilation for De Novo Acute Hypoxemic Respiratory Failure: Role of Tidal Volume. \u003cem\u003eCrit Care Med\u003c/em\u003e \u003cstrong\u003e44\u003c/strong\u003e, 282-290, doi:10.1097/CCM.0000000000001379 (2016).\u003c/li\u003e\n \u003cli\u003eSang, L.\u003cem\u003e\u0026nbsp;et al.\u003c/em\u003e Qualitative and quantitative assessment of pendelluft: a simple method based on electrical impedance tomography. \u003cem\u003eAnn Transl Med\u003c/em\u003e \u003cstrong\u003e8\u003c/strong\u003e, 1216, doi:10.21037/atm-20-4182 (2020).\u003c/li\u003e\n \u003cli\u003eKuchnicka, K. \u0026amp; Maciejewski, D. Ventilator-associated lung injury. \u003cem\u003eAnaesthesiol Intensive Ther\u003c/em\u003e \u003cstrong\u003e45\u003c/strong\u003e, 164-170, doi:10.5603/AIT.2013.0034 (2013).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Electrical impedance tomography, Pendelluft, Non-invasive mechanical ventilation","lastPublishedDoi":"10.21203/rs.3.rs-4315149/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4315149/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground and objective: \u003c/strong\u003ePatients with severe hypoxemia have a high mortality rate after failed non-invasive ventilation(NIV).Therefore,we propose utilizing pendelluft monitored by EIT to predict the failures of NIV,providing a new method for clinical practice.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eThis prospective observational study enrolled all patients with acute respiratory failure who were receiving NIV.The collected indices included patients' baseline characteristics,the measurement of pendelluft by EIT during the initial 24 hours of NIV after admission to the ICU,and the PaO2/FiO2 ratio.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThis study included 37 patients.There were no statistically significant differences in baseline characteristics between the successful and failed groups of NIV.The amplitude of pendelluft in the successful group (122.3226 (8.5493,193.8191))was significantly higher compared to the failed group (7.7538(2.6880, 25.8338))with a p-value \u0026lt; 0.01.The ROC curve showed the pendelluft amplitude cut-off value of 45.1124.Compared to the PaO2/FiO2,the pendelluft amplitude had a higher predictive value.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eMonitoring pendelluft using EIT could be one of the methods for predicting the failure of NIV.\u003c/p\u003e","manuscriptTitle":"Monitoring the Pendelluft by EIT could predict the failure of non-invasive mechanical ventilation:A Prospective Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-08 14:26:48","doi":"10.21203/rs.3.rs-4315149/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8e136c34-fc95-4639-ae89-d23973161f49","owner":[],"postedDate":"May 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":31582121,"name":"Health sciences/Biomarkers/Predictive markers"},{"id":31582123,"name":"Health sciences/Diseases/Respiratory tract diseases/Respiratory distress syndrome"}],"tags":[],"updatedAt":"2025-03-28T05:08:33+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-08 14:26:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4315149","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4315149","identity":"rs-4315149","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}