Diaphragmatic dysfunction assessed by ultrasound: a key predictor of prolonged ventilation in emergency department.

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Gennaro Sansone, Francesco Barbato, Giovanni Porta, Enrico Allegorico, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6559522/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Jun, 2025 Read the published version in Internal and Emergency Medicine → Version 1 posted 4 You are reading this latest preprint version Abstract Purpose: This study aimed to evaluate the feasibility and diagnostic value of diaphragmatic ultrasound in the management of respiratory failure in the emergency department (ED), with a focus on its potential to guide treatment decisions and improve patient outcomes. Materials and Methods: We conducted an observational study at the ED of Santa Maria delle Grazie Hospital in Pozzuoli, Italy, from November 2023 to April 2024. Patients with type 1 or type 2 respiratory failure requiring non-invasive ventilation (NIV) or continuous positive airway pressure (CPAP) were included. Diaphragmatic ultrasound was performed at baseline to assess diaphragmatic excursion and thickening fraction, alongside arterial blood gas (ABG) measurements. Follow-up ABGs were taken at 1, 3, 6, and 12 hours. Results: A total of 44 patients were included in the study. Patients with diaphragmatic dysfunction (defined as excursion < 10 mm or thickening fraction < 30%) had significantly longer in-ED and in-hospital ventilation times (p = 0.002 and p < 0.001, respectively). Power-type regression analysis showed a significant correlation between diaphragmatic excursion and ventilation time (p = 0.003 for in-ED and p = 0.003 for in-hospital ventilation time). Conclusions: Diaphragmatic ultrasound is a feasible and valuable tool for assessing diaphragmatic function in the ED. Its use provides important prognostic information, potentially guiding ventilatory strategies and improving patient outcomes by identifying those at risk for prolonged ventilation Figures Figure 1 Figure 2 Figure 3 Introduction Respiratory failure is a frequent and critical condition encountered in the emergency department (ED), often resulting from a variety of underlying etiologies. This condition may necessitate the use of several forms of respiratory support, including non-invasive ventilation (NIV), continuous positive airway pressure (CPAP), or, in more severe cases, invasive mechanical ventilation. (1) In recent years, especially following the COVID-19 pandemic, NIV has gained increasing importance in the management of respiratory failure within the ED. (2, 3) This growing reliance on NIV highlights the evolving approach to ventilatory support in acute settings, as healthcare providers strive to minimize invasive interventions when possible. One of the most challenging aspects of managing respiratory failure is determining the appropriate moment to transition the patient from mechanical ventilation, either by initiating weaning or, conversely, by deciding to proceed with intubation. (4) The correct timing for these decisions is critical to patient outcomes, as premature weaning or delayed intubation can lead to significant complications. The diaphragm is a key muscle in the process of ventilation. In a healthy, physiological state, it is responsible for contributing to approximately three-quarters of the inspiratory volume of vital capacity, making its function vital for proper respiratory mechanics. (5) As such, assessing the diaphragm’s condition can provide valuable insight into the patient's ventilatory status. Ultrasound of the diaphragm has become an increasingly utilized method in the evaluation and management of critically ill patients. (6) This non-invasive imaging technique focuses on two key measures: diaphragmatic excursion, which refers to the movement of the diaphragm during respiration, and the Diaphragmatic Thickening Fraction (DTF), which quantifies the thickening of the diaphragm during contraction. Commonly accepted reference values for these parameters are a diaphragmatic excursion greater than 10 mm and a DTF greater than 30%. (7) While diaphragmatic ultrasound is gaining traction in the ED, most research on this technique has been conducted in intensive care units (ICU), where patients are typically more stable or monitored for extended periods. In the ED, however, the urgent nature of care often hinders the ability to perform this type of ultrasound, as clinicians must act quickly to stabilize patients, especially those requiring ventilatory support. (8) Given these challenges, the primary aim of this study was to evaluate the feasibility — in terms of technical success, time required, and operator practicality — of performing diaphragmatic ultrasound in the acute management of patients with respiratory failure in the ED. Additionally, we sought to assess whether this diagnostic tool could provide meaningful information to guide treatment decisions and improve patient outcomes. Materials and methods Study population We conducted an observational study at the ED of the Santa Maria Delle Grazie hospital in Pozzuoli (NA) from November 2023 to April 2024. Patients were considered eligible for NIV/CPAP if they presented with signs of acute respiratory failure, defined by a PaO2 45 mmHg , along with clinical evidence of increased work of breathing (e.g., accessory muscle use, respiratory rate > 25/min, or altered mental status). The decision to initiate NIV/CPAP was made by the attending emergency physician, based on clinical judgment and established protocols. Exclusion Criteria: Age under 18 years Hemodynamic instability Need for Emrgent Intubation Patients with neuromuscular pathologies Patients with known diaphragm paralysis Patients with known rib cage deformity Known lung fibrosis Pneumothorax Absence of consent Study protocol Eligible patients underwent diaphragm ultrasound (right side) and arterial blood gas (ABG) measurements before initiating NIV/CPAP. Follow-up ABGs were performed at 1, 3, 6, and 12 hours after the intervention, as determined by the attending clinician. The study protocol was approved by the “Campania Centro” Ethics Committee and was conducted in accordance with the principles outlined in the Declaration of Helsinki. Diaphragmatic ultrasound Diaphragmatic ultrasound was performed at baseline (T0) to assess both diaphragmatic excursion and thickness, using validated techniques. (9) Ultrasound measurements were conducted at the bedside using an ultrasound machine equipped with either a convex (1.6–4.6 MHz) and a linear (3.4–10.8 MHz) probe (Samsung, Mindray). Patients were placed in a semi-recumbent position for the procedure. Diaphragmatic excursion is measured by placing the (convex) probe in the subcostal area, and the diaphragm excursion is sampled in M-mode. Diaphragmatic thickening fraction (DTF) is measured in M-mode by placing the (linear) probe at the level of the anterior axillary line, and the inspiratory and expiratory diaphragm thickness are sampled in M-mode and is calculated as: DTF = (Thickness inspiration − Thickness expiration)/Thickness expiration×100 Diaphragmatic excursion and thickness measurements were obtained from the right diaphragm. The ultrasound was performed by two operators (AG, GP) Feasibility assessment To evaluate the feasibility of diaphragmatic ultrasound in the ED setting, we recorded whether the exam could be completed successfully, the time required to perform each exam (from probe placement to image acquisition), the operator’s level of experience, and any technical limitations encountered. The procedure was considered feasible if a complete assessment of both diaphragmatic excursion and thickness could be performed within 10 minutes at the bedside. All procedures were performed by two physicians with at least 3 years of PoCUS experience. NIV/CPAP Patients with respiratory failure (defined as PaO2 45 mmHg) (10), and who, in the clinician’s judgment, required NIV or CPAP, were included in the study. NIV was administered using a full-face mask connected to a high-performance ventilator (Trilogy, Philips). CPAP was delivered via helmets (Starmed). Outcome Primary outcomes: In-Emergency department (ED) ventilation time In-Hospital ventilation time Lenght Of Stay in ED Secondary outcomes In-hospital mortality Need for ETI Need for NIV rescue after at least 24 hours of low flow oxygen therapy Statistical analysis First, a descriptive analysis was conducted on the study population. Discrete variables such as gender, disease type, type of respiratory failure, type of respiratory support, need for respiratory support rescue, requirement for intubation, and mortality were analyzed. Among the continuous variables, we considered age, FiO2, EPAP, IPAP, diaphragmatic excursion (mm), Diaphragmatic Thickening Fraction (DTF, %), length of stay in the ED, In-ED ventilation time, in-hospital ventilation time, and blood gas parameters (PaO2/FiO2 ratio, pH, PaCO2, PaO2, lactates, SaO2%, and bicarbonates) at baseline (T0), and at 1, 3, 6, and 12 hours after intervention. We compared the continuous and discrete variables based on the diagnosed pathology. Discrete variables were compared using the Chi-Square test, while continuous variables were analyzed using one-way analysis of variance (ANOVA). Next, the entire study population was divided into two subgroups based on the presence of diaphragmatic dysfunction. Diaphragmatic dysfunction was defined as a diaphragmatic excursion of less than 10 mm and/or a DTF of less than 30%. Discrete variables were analyzed using the Pearson Chi-Square test and Fisher’s Exact test. For continuous variables, due to the two-group structure, the Kruskal-Wallis test was employed. Finally, a power-type regression analysis was performed to assess the relationship between diaphragmatic excursion (in millimetres) and both In-ED ventilation time and In-hospital ventilation time. All statistical analyses were conducted using SPSS version 30.0 (2022). Results Data were collected from 50 patients admitted to the ED at Santa Maria delle Grazie Hospital in Pozzuoli between November 2023 and April 2024 with acute respiratory failure. Six patients were excluded from the study: two had neuromuscular disorders, three required immediate endotracheal intubation (ETI), and one presented with hemodynamic instability. Diaphragmatic ultrasound was successfully performed in 44/50 patients (88%). In the remaining 6 patients, the exam was not feasible due to either emergent intubation (n = 3), neuromuscular disease (n = 2), or hemodynamic instability (n = 1). The average time required for image acquisition was 8 ± 2 minutes. No major technical difficulties were reported. All exams were conducted by trained emergency physicians with at least 3 years of experience in ultrasound. Therefore, 44 patients were included in the final analysis. (Fig. 1 ) The average age of the study population was 74 years (SD = 14), with 24 female and 20 male patients (Table 1 ). The causes of acute respiratory failure (ARF) included acute heart failure (pulmonary edema) in 16 patients, pneumonia in 13 patients, chronic obstructive pulmonary disease (COPD) exacerbations in 9 patients, and acute respiratory distress syndrome (ARDS) in 6 patients. Type 1 respiratory failure was identified in 21 patients, while type 2 respiratory failure was present in 23 patients. Table 1 Demographic characteristics of the entire population. Mean Standard Deviation Age 74 14 Fio2 (%) 58 22 EPAP (cmH2O) 8 2 IPAP (cmH2O) 16 6 Diapragmatic excursion (mm) 15 7 Diaphragmatic thickening fraction (%) 34 23 In-ed lenght of stay (min) 878 502 In-ed ventilation time (min) 476 451 In-hospital ventilation time (min) 1532 2018 p/f t0 185 59 ph T0 7.3 0.13 pCo2 T0 (mmHg) 51 22 pO2 T0 (mmHg) 64 29 Lactate T0 (mmol) 2.9 2 SaO2 T0 (%) 80 14 Bicarbonates T0 (mmol) 24 6 ED emergency department Ventilatory support was required for all 44 patients, with 30 receiving NIV and 14 receiving CPAP. During hospitalization, 12 patients (27%) required rescue ventilatory support. Only one patient (2.3%) required ETI due to severe respiratory failure. Five patients (11.6%) died from complications related to respiratory failure. Statistical analysis of the data revealed a significant difference in the type of respiratory failure (Type I vs. Type II) (p = 0.014), as shown in Table 2 . FiO2 (p = 0.039) and EPAP (p = 0.09) values were also significant. As expected, significant differences were found in in-hospital ventilation time (p = 0.006), and several arterial blood gas (ABG) parameters, as outlined in Table 2 . Table 2 Statistical significance in the comparison between the four populations (Pneumonia vs COPD vs ARDS vs AHF). Pneumonia (n = 13) COPD (n = 9) ARDS (n = 6) AHF (n = 16) Statistical significance (p value) Age 71 +/- 17 75 +/- 9 70 +/- 21 79 +/- 9 0.694 Type of respiratory failure 1 2 1 1 0.014 FiO2 (%) 54 +/- 18 42 +/- 17 69 +/- 16 66 +/- 25 0.039 EPAP (cmH2O) 8 +/- 2 7 +/- 1 10 +/- 1 9 +/- 3 0.009 IPAP (cmH2O) 17+/- 6 20 +/- 2 15 +/- 7 13 +/- 6 0.106 Diaphragmatic excursion (mm) 13 +/- 5 12 +/- 6 14 +/- 5 18 +/- 9 0.101 Diaphragmatic thickening fraction (%) 29 +/- 20 29 +/- 28 39 +/- 15 39 +/- 26 0.462 In-ED Ventilation Time (min) 560 +/- 424 546 +/- 435 366 +/- 347 418 +/- 535 0.096 In-Hospital Ventilation Time (min) 2058 +/- 2449 2099 +/- 2171 2160 +/- 2474 512 +/- 682 0.006 In-ED Lenght of stay (min) 1016 +/- 495 888 +/- 451 631 +/- 210 869 +/- 610 0.421 p/F T0 190 +/- 50 193 +/- 72 159 +/- 66 188 +/- 58 0.715 pH T0 7.3 +/- 0.09 7.22 +/- 0.1 7.46 +/- 0.07 7.29 +/- 0.1 0.003 pCO2 T0 (mmHg) 50 +/- 14 78 +/- 21 31 +/- 7 46 +/- 17 < 0.001 pO2 T0 (mmHg) 80 +/- 36 70 +/- 38 47 +/- 5 54 +/- 11 0.083 Lactate T0 (mmol) 3.7 +/- 2 2.2 +/- 1.6 2.4 +/- 1.8 2.7 +/- 2.1 0.186 SaO2 T0 (%) 85 +/- 15 81 +/- 18 78 +/- 5 78 +/- 13 0.274 Bicarbonates T0 (mmol) 24 +/- 3 32 +/- 9 22 +/- 4 21 +/- 3 0.001 ED emergency department; COPD chronic obstructive pulmonary disease exacerbation; ARDS acute respiratory distress syndrome; AHF acute heart failure Subsequently, the study population was divided into two subgroups based on diaphragmatic dysfunction. The first subgroup included patients with diaphragmatic dysfunction, defined by a diaphragmatic excursion of less than 10 mm and/or a DTF of less than 30%. The second subgroup consisted of patients without diaphragmatic dysfunction. Analysis of the discrete variables revealed no significant differences between the subgroups regarding gender, pathology type, type of respiratory failure, type of respiratory support, need for rescue therapy, intubation, or in-hospital mortality. However, continuous variable analysis showed significant differences in DTF, as well as in both In-ED ventilation time (p = 0.002) and in-hospital ventilation time (p < 0.001). No significant differences were observed between the subgroups in terms of ABG parameters, as shown in Table 3 . Table 3 Statistical significance in continue variables in the comparison between the two populations (Dysfunctional diaphragmatic ultrasound vs normal diaphragmatic ultrasound) Dysfunctional Diaphragmatic ultrasound (n = 21) Normal Diaphragmatic Ultrasound (n = 23) p value Age 73 +/- 9 76 +/- 17 0.370 FiO2 (%) 55 +/- 26 61 +/- 18 0.267 EPAP (cmH2O) 8 +/- 3 9 +/- 2 0.210 IPAP (cmH2O) 15 +/- 7 17 +/- 6 0.551 Diaphragmatic excursion (mm) 10 +/- 2 19 +/- 7 < 0.001 Diaphragmatic thickening fraction (%) 13 +/- 7 52 +/- 16 < 0.001 In-ED ventilation time (min) 661 +/- 471 315 +/- 371 0.002 In-Hospital ventilation time (min) 2740 +/- 2422 476 +/- 442 < 0.001 In-ED Lenght of stay (min) 980 +/- 535 789 +/- 465 0.269 p/F T0 176 +/- 57 193 +/- 61 0.378 Ph T0 7.29 +/- 0.12 7.31 +/- 0.14 0.608 pCO2 T0 (mmHg) 55 +/- 24 48 +/- 19 0.412 pO2 T0 (mmHg) 61 +/- 23 66 +/- 33 0.909 Lactate T0 (mmol) 3 +/- 2.3 2.7 +/- 1.6 1 SaO2 T0 (%) 82 +/- 13 80 +/- 15 0.758 Bicarbonates T0 (mmol) 26 +/- 8 23 +/- 5 0.305 ED emergency department To better understand the relationship between diaphragmatic excursion and ventilation time, a power-type regression analysis was performed between diaphragmatic excursion (in mm) and In-ED ventilation time. This analysis revealed a significant correlation (p = 0.003), with an R value of 0.434, R² of 0.188, and F = 9.951. A similar analysis was conducted for in-hospital ventilation time, yielding an R value of 0.433, R² of 0.188, F = 9.935, and p = 0.003. These results are illustrated in Figs. 2 and 3 . Discussion In recent years, there have been only a limited number of studies examining the role of diaphragmatic ultrasound in the evaluation of patients with respiratory failure. Additionally, most of these studies have focused on a narrow subset of patients, particularly those with specific conditions like Chronic Obstructive Pulmonary Disease (COPD) (11). With our study, we aimed to expand upon this body of work by evaluating a broader range of patients who presented to our Emergency Department (ED) with respiratory failure, including individuals with various underlying conditions that may contribute to respiratory compromise. Respiratory failure, as a clinical entity, can result from a variety of conditions, each with its own pathophysiological mechanisms. The management of respiratory failure typically involves the use of non-invasive ventilation, with clinicians often deciding whether or not to initiate ventilation support based on the type of respiratory failure the patient is experiencing. These include Type 1 respiratory failure, characterized by hypoxemia, and Type 2, which is typically associated with hypercapnia. In our cohort, we observed clear differences in the characteristics of respiratory failure across various underlying pathologies, which influenced the clinical decisions regarding ventilatory support. A striking finding in our study was that patients with Acute Respiratory Distress Syndrome (ARDS) presented with a significantly worse P/F ratio upon admission to the ED (12). This finding is consistent with existing literature, which emphasizes that ARDS typically presents with severe impairment of gas exchange and requires aggressive respiratory support. On the other hand, patients with COPD, a condition characterized by progressive airway obstruction, exhibited elevated pCO2 levels. This increase in carbon dioxide is a hallmark of COPD and serves as an indicator of the progressive exhaustion of the respiratory muscles, including the diaphragm. (13). The pathophysiology of COPD is multifactorial, with dysfunction of both the respiratory and limb muscles playing a central role. Factors such as hyperinflation, increased work of breathing (WOB), and cellular dysfunction, including redox imbalance, mitochondrial dysfunction, and protein catabolism, contribute to the impairment of diaphragmatic function in these patients. Moreover, systemic inflammation, structural alterations in muscle fibers, and a variety of metabolic disturbances further exacerbate muscle dysfunction in COPD (14). These factors together lead to a progressive weakening of the respiratory muscles, particularly the diaphragm, making these patients more reliant on ventilatory support. As expected, patients with type 2 respiratory failure—most commonly associated with hypercapnia and COPD—are more prone to diaphragmatic dysfunction. The chronic mechanical overload, hyperinflation, and progressive respiratory muscle fatigue typical of these conditions likely contribute to the reduced diaphragmatic performance. This is consistent with our findings (low value in the diaphragmatic excursion and thickening fraction), although in our cohort the difference did not reach statistical significance. Nevertheless, it underscores the potential of diaphragmatic ultrasound in differentiating the pathophysiological patterns of respiratory failure and anticipating ventilatory support needs. In contrast, patients with pneumonia who presented to our ED had elevated lactate levels, which are indicative of tissue hypoxia and a more severe clinical course. The literature supports this observation, suggesting that pneumonia with elevated lactate levels and higher PSI/PORT scores tends to be associated with more severe disease, increased ventilation requirements, and higher mortality rates (15). Our findings were consistent with this, as patients with elevated lactate levels required mechanical ventilation more frequently. As part of our standard Point-of-Care Ultrasound (PoCUS) protocol, we performed diaphragmatic ultrasound on all patients with respiratory failure upon arrival at the ED. This procedure, which is simple and highly reproducible, allowed us to obtain valuable insights into the function of the diaphragm during the early stages of respiratory failure. Importantly, the use of diaphragmatic ultrasound provided us with objective measurements of diaphragmatic function, which are not always readily available through other clinical assessments. We divided the patients into two groups based on the functionality of their diaphragm, evaluating two key parameters: diaphragmatic excursion and diaphragmatic thickening fraction (DTF). Diaphragmatic excursion refers to the linear movement of the diaphragm during inspiration, while DTF measures the variation in diaphragm thickness, providing a direct assessment of muscle contractility. These two parameters convey different, yet complementary, information regarding diaphragmatic performance, and together they offer a comprehensive picture of the diaphragm's ability to support respiration in the setting of acute respiratory failure. (6) Our analysis revealed that, despite no significant differences in P/F ratio or oxygen saturation between the two groups—two classic markers of severity in respiratory failure—there was a marked difference in the duration of mechanical ventilation required. Specifically, patients with more pronounced diaphragmatic dysfunction were found to have significantly longer ventilation times both in the ED and throughout their hospital stay. This observation underscores the relationship between diaphragmatic function and the duration of respiratory support. While we did not observe significant differences in mortality between the groups, the extended duration of ventilation in patients with diaphragmatic dysfunction is clinically significant. Prolonged ventilation, especially within the ED, is a known risk factor for increased morbidity, as it can lead to complications such as hospital-acquired infections, ventilator-associated pneumonia, and other adverse outcomes (16). Therefore, patients with diaphragmatic dysfunction, who are more likely to require prolonged ventilation, are at higher risk for these complications. Our findings demonstrate a statistically significant and independent relationship between diaphragmatic dysfunction and prolonged ventilation time, both in the ED and during hospitalization. This suggests that patients with diaphragmatic dysfunction are not only more challenging to wean from non-invasive ventilation, but they are also at greater risk of experiencing a protracted course of mechanical ventilation. This extended ventilation time is critical, as it may exacerbate existing complications and contribute to poorer outcomes. Conclusion We believe that the detection of diaphragmatic dysfunction through bedside PoCUS during the early evaluation of patients with respiratory failure can provide valuable prognostic information. By identifying patients at risk for prolonged ventilation early on, emergency physicians can better stratify risk and tailor management strategies. This early identification allows clinicians to anticipate the need for extended non-invasive ventilation support, optimize ventilatory strategies, and ultimately improve patient outcomes by preventing unnecessary complications associated with prolonged ventilation. Declarations Conflict of Interest The authors declare that they have no conflict of interest References Malas O, Caglayan B, Fidan A et al: Cardiac or pulmonary dyspnea in patients admitted to the emergency department. Respiratory medicine. 2003;97(12):1277-81 Bosso G, Sansone G, Papillo M et al: Lung ultrasound-guided PEEP titration in COVID-19 patients treated with CPAP. 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Parada-Gereda HM, Tibaduiza AL et al: Effectiveness of diaphragmatic ultrasound as a predictor of successful weaning from mechanical ventilation: a systematic review and meta-analysis. Crit Care. 2023 May 5;27(1):174. doi: 10.1186/s13054-023-04430-9. Bobbia X, Cle´ment A, Claret PG et al: Diaphragmatic excursion measurement in emergency patients with acute dyspnea: toward a new diagnostic tool? Am J Emerg Med 2016;34:1653-1657; Laghi FA Jr, Saad M, Shaikh H. Ultrasound and non-ultrasound imaging techniques in the assessment of diaphragmatic dysfunction. BMC Pulm Med. 2021 Mar 15;21(1):85. doi: 10.1186/s12890-021-01441-6. Roussos C, Koutsoukou A. Respiratory failure. Eur Respir J Suppl. 2003 Nov;47:3s-14s. doi: 10.1183/09031936.03.00038503. PMID: 14621112 Cammarota G, Sguazzotti I, Zanoni M et al: Diaphragmatic Ultrasound Assessment in Subjects With Acute Hypercapnic Respiratory Failure Admitted to the Emergency Department. Respir Care. 2019 Dec;64(12):1469-1477. doi: 10.4187/respcare.06803. Epub 2019 Aug 27. PMID: 31455684 Spinelli E, Mauri T. Why improved PF ratio should not be our target when treating ARDS. Minerva Anestesiol. 2021 Jul;87(7):752-754. doi: 10.23736/S0375-9393.21.15664-0. Epub 2021 Mar 10. PMID: 33688707 Vázquez-Gandullo E, Hidalgo-Molina A, Montoro-Ballesteros F et al: Inspiratory Muscle Training in Patients with Chronic Obstructive Pulmonary Disease (COPD) as Part of a Respiratory Rehabilitation Program Implementation of Mechanical Devices: A Systematic Review. Int J Environ Res Public Health. 2022 May 3;19(9):5564. doi: 10.3390/ijerph19095564. Esther Barreiro and Gary Sieck. Muscle dysfunction in COPD. J Appl Physiol 114: 1220 –1221, 2013 Zhou H, Lan T, Guo S. Stratified and prognostic value of admission lactate and severity scores in patients with community-acquired pneumonia in emergency department: A single-center retrospective cohort study. Medicine (Baltimore). 2019 Oct;98(41):e17479. doi: 10.1097/MD.0000000000017479. Angotti LB, Richards JB, Fisher DF et al: Duration of Mechanical Ventilation in the Emergency Department. West J Emerg Med. 2017 Aug;18(5):972-979. doi: 10.5811/westjem.2017.5.34099 Cite Share Download PDF Status: Published Journal Publication published 20 Jun, 2025 Read the published version in Internal and Emergency Medicine → Version 1 posted Reviewers agreed at journal 11 May, 2025 Reviewers invited by journal 08 May, 2025 Editor assigned by journal 30 Apr, 2025 First submitted to journal 29 Apr, 2025 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. 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Nord","correspondingAuthor":false,"prefix":"","firstName":"Paola","middleName":"","lastName":"Arbo","suffix":""},{"id":453979459,"identity":"bde3af34-4c73-40ca-8b86-8955946559d9","order_by":8,"name":"Valentina Latini","email":"","orcid":"","institution":"ASL Napoli 2 Nord: Azienda Sanitaria Locale Napoli 2 Nord","correspondingAuthor":false,"prefix":"","firstName":"Valentina","middleName":"","lastName":"Latini","suffix":""},{"id":453979460,"identity":"3acb5f8a-d3df-4355-9f90-7537278cf497","order_by":9,"name":"Roberto Allocca","email":"","orcid":"","institution":"ASL Napoli 2 Nord: Azienda Sanitaria Locale Napoli 2 Nord","correspondingAuthor":false,"prefix":"","firstName":"Roberto","middleName":"","lastName":"Allocca","suffix":""},{"id":453979461,"identity":"a4f0ebf9-6420-4a7f-848b-b3fbf5128335","order_by":10,"name":"Alessandro Giaquinto","email":"","orcid":"","institution":"ASL Napoli 2 Nord: Azienda Sanitaria Locale Napoli 2 Nord","correspondingAuthor":false,"prefix":"","firstName":"Alessandro","middleName":"","lastName":"Giaquinto","suffix":""},{"id":453979462,"identity":"2b60cf0e-5187-4f6a-a59e-c3520b037181","order_by":11,"name":"Antonio Pagano","email":"","orcid":"","institution":"ASL Napoli 2 Nord: Azienda Sanitaria Locale Napoli 2 Nord","correspondingAuthor":false,"prefix":"","firstName":"Antonio","middleName":"","lastName":"Pagano","suffix":""},{"id":453979463,"identity":"5526868d-9c9d-4e3f-8c0a-ff812a43ac8a","order_by":12,"name":"Giorgio Bosso","email":"","orcid":"","institution":"ASL Napoli 2 Nord: Azienda Sanitaria Locale Napoli 2 Nord","correspondingAuthor":false,"prefix":"","firstName":"Giorgio","middleName":"","lastName":"Bosso","suffix":""},{"id":453979464,"identity":"6f0d7381-d56a-43c7-b665-506012740a85","order_by":13,"name":"Fabio Giuliano Numis","email":"","orcid":"","institution":"ASL Napoli 2 Nord: Azienda Sanitaria Locale Napoli 2 Nord","correspondingAuthor":false,"prefix":"","firstName":"Fabio","middleName":"Giuliano","lastName":"Numis","suffix":""}],"badges":[],"createdAt":"2025-04-29 21:27:41","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6559522/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6559522/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11739-025-04020-3","type":"published","date":"2025-06-20T15:57:30+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":82714360,"identity":"328e812c-036b-4eda-9f84-9c96370b4048","added_by":"auto","created_at":"2025-05-14 12:05:24","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":36028,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart patients included and divided into two groups based on diaphragm ultrasound\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6559522/v1/ff6701e168c204af3c7817ef.jpg"},{"id":82714361,"identity":"9ac6a999-f235-48a9-9d35-8419daf76583","added_by":"auto","created_at":"2025-05-14 12:05:24","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":6389202,"visible":true,"origin":"","legend":"\u003cp\u003ePower-type regression diaphragmatic excursion vs In-Ed ventilation time.\u003c/p\u003e\n\u003cp\u003eThe graph shows the relationship between the diaphragmatic excursion (expressed in millimetres) and the ventilation time in the emergency department (expressed in minutes), modeled through a power-type regression. The analysis shows an inverse relationship between the two variables: as the diaphragmatic excursion increases, the ventilation time tends to decrease.\u003c/p\u003e","description":"","filename":"fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-6559522/v1/a015ce6132ee282092a7447d.png"},{"id":82716151,"identity":"ffb7813e-b034-4e20-8292-fae6c251dc02","added_by":"auto","created_at":"2025-05-14 12:13:24","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":8921992,"visible":true,"origin":"","legend":"\u003cp\u003ePower-type regression diaphragmatic excursion vs In-hospital ventilation time.\u003c/p\u003e\n\u003cp\u003eThe graph shows the relationship between the diaphragmatic excursion (expressed in millimetres) and the ventilation time in the hospital (expressed in minutes), modeled through a power-type regression. The analysis shows an inverse relationship between the two variables: as the diaphragmatic excursion increases, the ventilation time tends to decrease. This is consistent with the pathophysiological hypothesis that a greater diaphragmatic excursion represents a more effective respiratory function, allowing a more rapid suspension of ventilatory support. However, the value of the coefficient of determination indicates that the model explains about 19% of the variability of ventilation time. This suggests that, while there is a general trend, other clinical factors not considered in the model could significantly influence the duration of ventilation.\u003c/p\u003e","description":"","filename":"fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-6559522/v1/d83d6656a0411ea9ba522687.png"},{"id":85231369,"identity":"db2c8abc-a7bb-4271-a492-46762e4adaa1","added_by":"auto","created_at":"2025-06-23 16:06:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":14654866,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6559522/v1/44272868-e7b5-4f07-86bd-c3a61a69b886.pdf"}],"financialInterests":"","formattedTitle":"Diaphragmatic dysfunction assessed by ultrasound: a key predictor of prolonged ventilation in emergency department.","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRespiratory failure is a frequent and critical condition encountered in the emergency department (ED), often resulting from a variety of underlying etiologies. This condition may necessitate the use of several forms of respiratory support, including non-invasive ventilation (NIV), continuous positive airway pressure (CPAP), or, in more severe cases, invasive mechanical ventilation. (1)\u003c/p\u003e \u003cp\u003eIn recent years, especially following the COVID-19 pandemic, NIV has gained increasing importance in the management of respiratory failure within the ED. (2, 3) This growing reliance on NIV highlights the evolving approach to ventilatory support in acute settings, as healthcare providers strive to minimize invasive interventions when possible.\u003c/p\u003e \u003cp\u003eOne of the most challenging aspects of managing respiratory failure is determining the appropriate moment to transition the patient from mechanical ventilation, either by initiating weaning or, conversely, by deciding to proceed with intubation. (4) The correct timing for these decisions is critical to patient outcomes, as premature weaning or delayed intubation can lead to significant complications.\u003c/p\u003e \u003cp\u003eThe diaphragm is a key muscle in the process of ventilation. In a healthy, physiological state, it is responsible for contributing to approximately three-quarters of the inspiratory volume of vital capacity, making its function vital for proper respiratory mechanics. (5)\u003c/p\u003e \u003cp\u003eAs such, assessing the diaphragm\u0026rsquo;s condition can provide valuable insight into the patient's ventilatory status.\u003c/p\u003e \u003cp\u003eUltrasound of the diaphragm has become an increasingly utilized method in the evaluation and management of critically ill patients. (6) This non-invasive imaging technique focuses on two key measures: diaphragmatic excursion, which refers to the movement of the diaphragm during respiration, and the Diaphragmatic Thickening Fraction (DTF), which quantifies the thickening of the diaphragm during contraction. Commonly accepted reference values for these parameters are a diaphragmatic excursion greater than 10 mm and a DTF greater than 30%. (7)\u003c/p\u003e \u003cp\u003eWhile diaphragmatic ultrasound is gaining traction in the ED, most research on this technique has been conducted in intensive care units (ICU), where patients are typically more stable or monitored for extended periods. In the ED, however, the urgent nature of care often hinders the ability to perform this type of ultrasound, as clinicians must act quickly to stabilize patients, especially those requiring ventilatory support. (8)\u003c/p\u003e \u003cp\u003eGiven these challenges, the primary aim of this study was to evaluate the feasibility \u0026mdash; in terms of technical success, time required, and operator practicality \u0026mdash; of performing diaphragmatic ultrasound in the acute management of patients with respiratory failure in the ED.\u003c/p\u003e \u003cp\u003eAdditionally, we sought to assess whether this diagnostic tool could provide meaningful information to guide treatment decisions and improve patient outcomes.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cstrong\u003eStudy population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe conducted an observational study at the ED of the Santa Maria Delle Grazie hospital in Pozzuoli (NA) from November 2023 to April 2024.\u003c/p\u003e\n\u003cp\u003ePatients were considered eligible for NIV/CPAP if they presented with signs of acute respiratory failure, defined by a \u003cstrong\u003ePaO2 \u0026lt; 60 mmHg\u003c/strong\u003e (on room air) and/or \u003cstrong\u003ePaCO2 \u0026gt; 45 mmHg\u003c/strong\u003e, along with clinical evidence of increased work of breathing (e.g., accessory muscle use, respiratory rate \u0026gt; 25/min, or altered mental status). The decision to initiate NIV/CPAP was made by the attending emergency physician, based on clinical judgment and established protocols.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eExclusion Criteria:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eAge under 18 years\u003c/li\u003e\n \u003cli\u003eHemodynamic instability\u003c/li\u003e\n \u003cli\u003eNeed for Emrgent Intubation\u003c/li\u003e\n \u003cli\u003ePatients with neuromuscular pathologies\u003c/li\u003e\n \u003cli\u003ePatients with known diaphragm paralysis\u003c/li\u003e\n \u003cli\u003ePatients with known rib cage deformity\u003c/li\u003e\n \u003cli\u003eKnown lung fibrosis\u003c/li\u003e\n \u003cli\u003ePneumothorax\u003c/li\u003e\n \u003cli\u003eAbsence of consent\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eStudy protocol\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEligible patients underwent diaphragm ultrasound (right side) and arterial blood gas (ABG) measurements before initiating NIV/CPAP. Follow-up ABGs were performed at 1, 3, 6, and 12 hours after the intervention, as determined by the attending clinician. The study protocol was approved by the \u0026ldquo;Campania Centro\u0026rdquo; Ethics Committee and was conducted in accordance with the principles outlined in the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiaphragmatic ultrasound\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDiaphragmatic ultrasound was performed at baseline (T0) to assess both diaphragmatic excursion and thickness, using validated techniques. (9) Ultrasound measurements were conducted at the bedside using an ultrasound machine equipped with either a convex (1.6\u0026ndash;4.6 MHz) and a linear (3.4\u0026ndash;10.8 MHz) probe (Samsung, Mindray). Patients were placed in a semi-recumbent position for the procedure.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDiaphragmatic excursion is measured by placing the (convex) probe in the subcostal area, and the diaphragm excursion is sampled in M-mode.\u003c/p\u003e\n\u003cp\u003eDiaphragmatic thickening fraction (DTF) is measured in M-mode by placing the (linear) probe at the level of the anterior axillary line, and the inspiratory and expiratory diaphragm thickness are sampled in M-mode and is calculated as:\u003c/p\u003e\n\u003cp\u003eDTF = (Thickness inspiration \u0026minus; Thickness expiration)/Thickness expiration\u0026times;100\u003c/p\u003e\n\u003cp\u003eDiaphragmatic excursion and thickness measurements were obtained from the right diaphragm. The ultrasound was performed by two operators (AG, GP)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFeasibility assessment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo evaluate the feasibility of diaphragmatic ultrasound in the ED setting, we recorded whether the exam could be completed successfully, the time required to perform each exam (from probe placement to image acquisition), the operator\u0026rsquo;s level of experience, and any technical limitations encountered. The procedure was considered feasible if a complete assessment of both diaphragmatic excursion and thickness could be performed within 10 minutes at the bedside. All procedures were performed by two physicians with at least 3 years of PoCUS experience.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNIV/CPAP\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePatients with respiratory failure (defined as PaO2 \u0026lt; 60 mmHg and PaCO2 \u0026gt; 45 mmHg) (10), and who, in the clinician\u0026rsquo;s judgment, required NIV or CPAP, were included in the study. NIV was administered using a full-face mask connected to a high-performance ventilator (Trilogy, Philips). CPAP was delivered via helmets (Starmed).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOutcome\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePrimary outcomes:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eIn-Emergency department (ED) ventilation time\u003c/li\u003e\n \u003cli\u003eIn-Hospital ventilation time\u003c/li\u003e\n \u003cli\u003eLenght Of Stay in ED\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eSecondary outcomes\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eIn-hospital mortality\u003c/li\u003e\n \u003cli\u003eNeed for ETI\u003c/li\u003e\n \u003cli\u003eNeed for NIV rescue after at least 24 hours of low flow oxygen therapy\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFirst, a descriptive analysis was conducted on the study population. Discrete variables such as gender, disease type, type of respiratory failure, type of respiratory support, need for respiratory support rescue, requirement for intubation, and mortality were analyzed.\u003c/p\u003e\n\u003cp\u003eAmong the continuous variables, we considered age, FiO2, EPAP, IPAP, diaphragmatic excursion (mm), Diaphragmatic Thickening Fraction (DTF, %), length of stay in the ED, In-ED ventilation time, in-hospital ventilation time, and blood gas parameters (PaO2/FiO2 ratio, pH, PaCO2, PaO2, lactates, SaO2%, and bicarbonates) at baseline (T0), and at 1, 3, 6, and 12 hours after intervention.\u003c/p\u003e\n\u003cp\u003eWe compared the continuous and discrete variables based on the diagnosed pathology. Discrete variables were compared using the Chi-Square test, while continuous variables were analyzed using one-way analysis of variance (ANOVA).\u003c/p\u003e\n\u003cp\u003eNext, the entire study population was divided into two subgroups based on the presence of diaphragmatic dysfunction. Diaphragmatic dysfunction was defined as a diaphragmatic excursion of less than 10 mm and/or a DTF of less than 30%. Discrete variables were analyzed using the Pearson Chi-Square test and Fisher\u0026rsquo;s Exact test. For continuous variables, due to the two-group structure, the Kruskal-Wallis test was employed. Finally, a power-type regression analysis was performed to assess the relationship between diaphragmatic excursion (in millimetres) and both In-ED ventilation time and In-hospital ventilation time.\u003c/p\u003e\n\u003cp\u003eAll statistical analyses were conducted using SPSS version 30.0 (2022).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eData were collected from 50 patients admitted to the ED at Santa Maria delle Grazie Hospital in Pozzuoli between November 2023 and April 2024 with acute respiratory failure. Six patients were excluded from the study: two had neuromuscular disorders, three required immediate endotracheal intubation (ETI), and one presented with hemodynamic instability.\u003c/p\u003e \u003cp\u003eDiaphragmatic ultrasound was successfully performed in 44/50 patients (88%). In the remaining 6 patients, the exam was not feasible due to either emergent intubation (n\u0026thinsp;=\u0026thinsp;3), neuromuscular disease (n\u0026thinsp;=\u0026thinsp;2), or hemodynamic instability (n\u0026thinsp;=\u0026thinsp;1). The average time required for image acquisition was 8\u0026thinsp;\u0026plusmn;\u0026thinsp;2 minutes. No major technical difficulties were reported. All exams were conducted by trained emergency physicians with at least 3 years of experience in ultrasound.\u003c/p\u003e \u003cp\u003eTherefore, 44 patients were included in the final analysis. (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe average age of the study population was 74 years (SD\u0026thinsp;=\u0026thinsp;14), with 24 female and 20 male patients (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The causes of acute respiratory failure (ARF) included acute heart failure (pulmonary edema) in 16 patients, pneumonia in 13 patients, chronic obstructive pulmonary disease (COPD) exacerbations in 9 patients, and acute respiratory distress syndrome (ARDS) in 6 patients. Type 1 respiratory failure was identified in 21 patients, while type 2 respiratory failure was present in 23 patients.\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\u003eDemographic characteristics of the entire population.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStandard Deviation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFio2\u003c/b\u003e (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEPAP\u003c/b\u003e (cmH2O)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIPAP\u003c/b\u003e (cmH2O)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiapragmatic excursion\u003c/b\u003e (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiaphragmatic thickening fraction\u003c/b\u003e (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIn-ed lenght of stay\u003c/b\u003e (min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e878\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e502\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIn-ed ventilation time\u003c/b\u003e (min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e476\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e451\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIn-hospital ventilation time\u003c/b\u003e (min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ep/f t0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eph T0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003epCo2 T0\u003c/b\u003e (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003epO2 T0\u003c/b\u003e (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLactate T0\u003c/b\u003e (mmol)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSaO2 T0\u003c/b\u003e (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBicarbonates T0\u003c/b\u003e (mmol)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eED emergency department\u003c/b\u003e\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 \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eVentilatory support was required for all 44 patients, with 30 receiving NIV and 14 receiving CPAP. During hospitalization, 12 patients (27%) required rescue ventilatory support. Only one patient (2.3%) required ETI due to severe respiratory failure. Five patients (11.6%) died from complications related to respiratory failure.\u003c/p\u003e \u003cp\u003eStatistical analysis of the data revealed a significant difference in the type of respiratory failure (Type I vs. Type II) (p\u0026thinsp;=\u0026thinsp;0.014), as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. FiO2 (p\u0026thinsp;=\u0026thinsp;0.039) and EPAP (p\u0026thinsp;=\u0026thinsp;0.09) values were also significant. As expected, significant differences were found in in-hospital ventilation time (p\u0026thinsp;=\u0026thinsp;0.006), and several arterial blood gas (ABG) parameters, as outlined in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\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\u003eStatistical significance in the comparison between the four populations (Pneumonia vs COPD vs ARDS vs AHF).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePneumonia\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;13)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCOPD\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;9)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eARDS\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;6)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAHF\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;16)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStatistical significance (p value)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71 +/- 17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75 +/- 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70 +/- 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e79 +/- 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.694\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of respiratory failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFiO2 (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54 +/- 18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 +/- 17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e69 +/- 16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66 +/- 25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.039\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\u003e8 +/- 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 +/- 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 +/- 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9 +/- 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.009\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\u003e17+/- 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 +/- 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 +/- 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13 +/- 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.106\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiaphragmatic excursion (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 +/- 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 +/- 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 +/- 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18 +/- 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.101\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiaphragmatic thickening fraction (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 +/- 20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 +/- 28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39 +/- 15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39 +/- 26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.462\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIn-ED Ventilation Time (min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e560 +/- 424\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e546 +/- 435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e366 +/- 347\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e418 +/- 535\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIn-Hospital Ventilation Time (min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2058 +/- 2449\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2099 +/- 2171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2160 +/- 2474\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e512 +/- 682\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIn-ED Lenght of stay (min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1016 +/- 495\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e888 +/- 451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e631 +/- 210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e869 +/- 610\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.421\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep/F T0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e190 +/- 50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e193 +/- 72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e159 +/- 66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e188 +/- 58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.715\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epH T0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.3 +/- 0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.22 +/- 0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.46 +/- 0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.29 +/- 0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epCO2 T0 (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50 +/- 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78 +/- 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31 +/- 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46 +/- 17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epO2 T0 (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80 +/- 36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70 +/- 38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47 +/- 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54 +/- 11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLactate T0 (mmol)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.7 +/- 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.2 +/- 1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.4 +/- 1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.7 +/- 2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.186\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSaO2 T0 (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85 +/- 15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81 +/- 18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78 +/- 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e78 +/- 13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.274\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBicarbonates T0 (mmol)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 +/- 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 +/- 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 +/- 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21 +/- 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eED emergency department; COPD chronic obstructive pulmonary disease exacerbation; ARDS acute respiratory distress syndrome; AHF acute heart failure\u003c/em\u003e\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\u003eSubsequently, the study population was divided into two subgroups based on diaphragmatic dysfunction. The first subgroup included patients with diaphragmatic dysfunction, defined by a diaphragmatic excursion of less than 10 mm and/or a DTF of less than 30%. The second subgroup consisted of patients without diaphragmatic dysfunction.\u003c/p\u003e \u003cp\u003eAnalysis of the discrete variables revealed no significant differences between the subgroups regarding gender, pathology type, type of respiratory failure, type of respiratory support, need for rescue therapy, intubation, or in-hospital mortality. However, continuous variable analysis showed significant differences in DTF, as well as in both In-ED ventilation time (p\u0026thinsp;=\u0026thinsp;0.002) and in-hospital ventilation time (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). No significant differences were observed between the subgroups in terms of ABG parameters, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\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\u003eStatistical significance in continue variables in the comparison between the two populations (Dysfunctional diaphragmatic ultrasound vs normal diaphragmatic ultrasound)\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\u003eDysfunctional Diaphragmatic ultrasound\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;21)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNormal Diaphragmatic Ultrasound\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;23)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73 +/- 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76 +/- 17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.370\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFiO2 (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55 +/- 26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61 +/- 18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.267\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\u003e8 +/- 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 +/- 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.210\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\u003e15 +/- 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 +/- 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.551\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiaphragmatic excursion (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 +/- 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 +/- 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiaphragmatic thickening fraction (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 +/- 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52 +/- 16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIn-ED ventilation time (min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e661 +/- 471\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e315 +/- 371\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIn-Hospital ventilation time (min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2740 +/- 2422\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e476 +/- 442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIn-ED Lenght of stay (min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e980 +/- 535\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e789 +/- 465\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.269\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep/F T0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e176 +/- 57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e193 +/- 61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.378\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePh T0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.29 +/- 0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.31 +/- 0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.608\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epCO2 T0 (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55 +/- 24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48 +/- 19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.412\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epO2 T0 (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61 +/- 23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66 +/- 33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.909\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLactate T0 (mmol)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 +/- 2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.7 +/- 1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSaO2 T0 (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82 +/- 13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80 +/- 15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.758\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBicarbonates T0 (mmol)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26 +/- 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 +/- 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.305\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eED emergency department\u003c/em\u003e\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 \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTo better understand the relationship between diaphragmatic excursion and ventilation time, a power-type regression analysis was performed between diaphragmatic excursion (in mm) and In-ED ventilation time. This analysis revealed a significant correlation (p\u0026thinsp;=\u0026thinsp;0.003), with an R value of 0.434, R\u0026sup2; of 0.188, and F\u0026thinsp;=\u0026thinsp;9.951. A similar analysis was conducted for in-hospital ventilation time, yielding an R value of 0.433, R\u0026sup2; of 0.188, F\u0026thinsp;=\u0026thinsp;9.935, and p\u0026thinsp;=\u0026thinsp;0.003. These results are illustrated in Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn recent years, there have been only a limited number of studies examining the role of diaphragmatic ultrasound in the evaluation of patients with respiratory failure. Additionally, most of these studies have focused on a narrow subset of patients, particularly those with specific conditions like Chronic Obstructive Pulmonary Disease (COPD) (11). With our study, we aimed to expand upon this body of work by evaluating a broader range of patients who presented to our Emergency Department (ED) with respiratory failure, including individuals with various underlying conditions that may contribute to respiratory compromise.\u003c/p\u003e \u003cp\u003eRespiratory failure, as a clinical entity, can result from a variety of conditions, each with its own pathophysiological mechanisms. The management of respiratory failure typically involves the use of non-invasive ventilation, with clinicians often deciding whether or not to initiate ventilation support based on the type of respiratory failure the patient is experiencing. These include Type 1 respiratory failure, characterized by hypoxemia, and Type 2, which is typically associated with hypercapnia. In our cohort, we observed clear differences in the characteristics of respiratory failure across various underlying pathologies, which influenced the clinical decisions regarding ventilatory support.\u003c/p\u003e \u003cp\u003eA striking finding in our study was that patients with Acute Respiratory Distress Syndrome (ARDS) presented with a significantly worse P/F ratio upon admission to the ED (12). This finding is consistent with existing literature, which emphasizes that ARDS typically presents with severe impairment of gas exchange and requires aggressive respiratory support. On the other hand, patients with COPD, a condition characterized by progressive airway obstruction, exhibited elevated pCO2 levels. This increase in carbon dioxide is a hallmark of COPD and serves as an indicator of the progressive exhaustion of the respiratory muscles, including the diaphragm. (13).\u003c/p\u003e \u003cp\u003eThe pathophysiology of COPD is multifactorial, with dysfunction of both the respiratory and limb muscles playing a central role. Factors such as hyperinflation, increased work of breathing (WOB), and cellular dysfunction, including redox imbalance, mitochondrial dysfunction, and protein catabolism, contribute to the impairment of diaphragmatic function in these patients. Moreover, systemic inflammation, structural alterations in muscle fibers, and a variety of metabolic disturbances further exacerbate muscle dysfunction in COPD (14). These factors together lead to a progressive weakening of the respiratory muscles, particularly the diaphragm, making these patients more reliant on ventilatory support.\u003c/p\u003e \u003cp\u003eAs expected, patients with type 2 respiratory failure\u0026mdash;most commonly associated with hypercapnia and COPD\u0026mdash;are more prone to diaphragmatic dysfunction. The chronic mechanical overload, hyperinflation, and progressive respiratory muscle fatigue typical of these conditions likely contribute to the reduced diaphragmatic performance. This is consistent with our findings (low value in the diaphragmatic excursion and thickening fraction), although in our cohort the difference did not reach statistical significance. Nevertheless, it underscores the potential of diaphragmatic ultrasound in differentiating the pathophysiological patterns of respiratory failure and anticipating ventilatory support needs.\u003c/p\u003e \u003cp\u003eIn contrast, patients with pneumonia who presented to our ED had elevated lactate levels, which are indicative of tissue hypoxia and a more severe clinical course. The literature supports this observation, suggesting that pneumonia with elevated lactate levels and higher PSI/PORT scores tends to be associated with more severe disease, increased ventilation requirements, and higher mortality rates (15). Our findings were consistent with this, as patients with elevated lactate levels required mechanical ventilation more frequently.\u003c/p\u003e \u003cp\u003eAs part of our standard Point-of-Care Ultrasound (PoCUS) protocol, we performed diaphragmatic ultrasound on all patients with respiratory failure upon arrival at the ED. This procedure, which is simple and highly reproducible, allowed us to obtain valuable insights into the function of the diaphragm during the early stages of respiratory failure. Importantly, the use of diaphragmatic ultrasound provided us with objective measurements of diaphragmatic function, which are not always readily available through other clinical assessments.\u003c/p\u003e \u003cp\u003eWe divided the patients into two groups based on the functionality of their diaphragm, evaluating two key parameters: diaphragmatic excursion and diaphragmatic thickening fraction (DTF). Diaphragmatic excursion refers to the linear movement of the diaphragm during inspiration, while DTF measures the variation in diaphragm thickness, providing a direct assessment of muscle contractility. These two parameters convey different, yet complementary, information regarding diaphragmatic performance, and together they offer a comprehensive picture of the diaphragm's ability to support respiration in the setting of acute respiratory failure. (6)\u003c/p\u003e \u003cp\u003eOur analysis revealed that, despite no significant differences in P/F ratio or oxygen saturation between the two groups\u0026mdash;two classic markers of severity in respiratory failure\u0026mdash;there was a marked difference in the duration of mechanical ventilation required. Specifically, patients with more pronounced diaphragmatic dysfunction were found to have significantly longer ventilation times both in the ED and throughout their hospital stay. This observation underscores the relationship between diaphragmatic function and the duration of respiratory support.\u003c/p\u003e \u003cp\u003eWhile we did not observe significant differences in mortality between the groups, the extended duration of ventilation in patients with diaphragmatic dysfunction is clinically significant. Prolonged ventilation, especially within the ED, is a known risk factor for increased morbidity, as it can lead to complications such as hospital-acquired infections, ventilator-associated pneumonia, and other adverse outcomes (16). Therefore, patients with diaphragmatic dysfunction, who are more likely to require prolonged ventilation, are at higher risk for these complications.\u003c/p\u003e \u003cp\u003eOur findings demonstrate a statistically significant and independent relationship between diaphragmatic dysfunction and prolonged ventilation time, both in the ED and during hospitalization. This suggests that patients with diaphragmatic dysfunction are not only more challenging to wean from non-invasive ventilation, but they are also at greater risk of experiencing a protracted course of mechanical ventilation. This extended ventilation time is critical, as it may exacerbate existing complications and contribute to poorer outcomes.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eWe believe that the detection of diaphragmatic dysfunction through bedside PoCUS during the early evaluation of patients with respiratory failure can provide valuable prognostic information. By identifying patients at risk for prolonged ventilation early on, emergency physicians can better stratify risk and tailor management strategies. This early identification allows clinicians to anticipate the need for extended non-invasive ventilation support, optimize ventilatory strategies, and ultimately improve patient outcomes by preventing unnecessary complications associated with prolonged ventilation.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConflict of Interest\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no conflict of interest\u003c/p\u003e \u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003e\u003cem\u003eMalas O, Caglayan B, Fidan A et al: Cardiac or pulmonary dyspnea in patients admitted to the emergency department. Respiratory medicine. 2003;97(12):1277-81\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003e\u003cem\u003eBosso G, Sansone G, Papillo M et al: Lung ultrasound-guided PEEP titration in COVID-19 patients treated with CPAP. J Basic Clin Physiol Pharmacol. 2023 Jul 20;34(5):677-682. doi: 10.1515/jbcpp-2023-0165.\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003e\u003cem\u003eFerreyro BL, Angriman F, Munshi 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. 2020;324(1):57\u0026ndash;67\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003e\u003cem\u003eAntonelli M, Conti G, Moro ML et al: Predictors of failure of noninvasive positive pressure ventilation in patients with acute hypoxemic respiratory failure: a multi-center study. Intensive Care Med. 2001;27(11):1718\u0026ndash;28. \u003c/em\u003e\u003c/li\u003e\n\u003cli\u003e\u003cem\u003eCorbellini C, Boussuges A, et al. \u003c/em\u003e\u003cem\u003eDiaphragmatic Mobility Loss in Subjects With Moderate to Very Severe COPD May Improve After In-Patient Pulmonary Rehabilitation. Respir Care. 2018 Oct;63(10):1271-1280\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003e\u003cem\u003eMatamis D, Soilemezi E, Tsagourias M et al. \u003c/em\u003e\u003cem\u003eSonographic evaluation of the diaphragm in critically ill patients. Technique and clinical applications. Intensive Care Med 2013;39:801-810.\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003e\u003cem\u003eParada-Gereda HM, Tibaduiza AL et al: Effectiveness of diaphragmatic ultrasound as a predictor of successful weaning from mechanical ventilation: a systematic review and meta-analysis. Crit Care. 2023 May 5;27(1):174. doi: 10.1186/s13054-023-04430-9.\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003e\u003cem\u003eBobbia X, Cle\u0026acute;ment A, Claret PG et al: Diaphragmatic excursion measurement in emergency patients with acute dyspnea: toward a new diagnostic tool? Am J Emerg Med 2016;34:1653-1657;\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003e\u003cem\u003eLaghi FA Jr, Saad M, Shaikh H. Ultrasound and non-ultrasound imaging techniques in the assessment of diaphragmatic dysfunction. BMC Pulm Med. 2021 Mar 15;21(1):85. doi: 10.1186/s12890-021-01441-6.\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003e\u003cem\u003eRoussos C, Koutsoukou A. Respiratory failure. Eur Respir J Suppl. 2003 Nov;47:3s-14s. doi: 10.1183/09031936.03.00038503. PMID: 14621112\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003e\u003cem\u003eCammarota G, Sguazzotti I, Zanoni M et al: Diaphragmatic Ultrasound Assessment in Subjects With Acute Hypercapnic Respiratory Failure Admitted to the Emergency Department. Respir Care. 2019 Dec;64(12):1469-1477. doi: 10.4187/respcare.06803. Epub 2019 Aug 27. PMID: 31455684\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003e\u003cem\u003eSpinelli E, Mauri T. Why improved PF ratio should not be our target when treating ARDS. Minerva Anestesiol. 2021 Jul;87(7):752-754. doi: 10.23736/S0375-9393.21.15664-0. Epub 2021 Mar 10. PMID: 33688707\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003e\u003cem\u003eV\u0026aacute;zquez-Gandullo E, Hidalgo-Molina A, Montoro-Ballesteros F et al: Inspiratory Muscle Training in Patients with Chronic Obstructive Pulmonary Disease (COPD) as Part of a Respiratory Rehabilitation Program Implementation of Mechanical Devices: A Systematic Review. Int J Environ Res Public Health. 2022 May 3;19(9):5564. doi: 10.3390/ijerph19095564.\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003e\u003cem\u003eEsther Barreiro and Gary Sieck. Muscle dysfunction in COPD. J Appl Physiol 114: 1220 \u0026ndash;1221, 2013\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003e\u003cem\u003eZhou H, Lan T, Guo S. Stratified and prognostic value of admission lactate and severity scores in patients with community-acquired pneumonia in emergency department: A single-center retrospective cohort study. Medicine (Baltimore). 2019 Oct;98(41):e17479. doi: 10.1097/MD.0000000000017479. \u003c/em\u003e\u003c/li\u003e\n\u003cli\u003e\u003cem\u003eAngotti LB, Richards JB, Fisher DF et al: Duration of Mechanical Ventilation in the Emergency Department. West J Emerg Med. 2017 Aug;18(5):972-979. doi: 10.5811/westjem.2017.5.34099\u003c/em\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"internal-and-emergency-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"iaem","sideBox":"Learn more about [Internal and Emergency Medicine](http://link.springer.com/journal/11739)","snPcode":"11739","submissionUrl":"https://www.editorialmanager.com/iaem/default.aspx","title":"Internal and Emergency Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6559522/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6559522/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose:\u003c/h2\u003e \u003cp\u003eThis study aimed to evaluate the feasibility and diagnostic value of diaphragmatic ultrasound in the management of respiratory failure in the emergency department (ED), with a focus on its potential to guide treatment decisions and improve patient outcomes.\u003c/p\u003e\u003ch2\u003eMaterials and Methods:\u003c/h2\u003e \u003cp\u003eWe conducted an observational study at the ED of Santa Maria delle Grazie Hospital in Pozzuoli, Italy, from November 2023 to April 2024. Patients with type 1 or type 2 respiratory failure requiring non-invasive ventilation (NIV) or continuous positive airway pressure (CPAP) were included. Diaphragmatic ultrasound was performed at baseline to assess diaphragmatic excursion and thickening fraction, alongside arterial blood gas (ABG) measurements. Follow-up ABGs were taken at 1, 3, 6, and 12 hours.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e \u003cp\u003eA total of 44 patients were included in the study. Patients with diaphragmatic dysfunction (defined as excursion\u0026thinsp;\u0026lt;\u0026thinsp;10 mm or thickening fraction\u0026thinsp;\u0026lt;\u0026thinsp;30%) had significantly longer in-ED and in-hospital ventilation times (p\u0026thinsp;=\u0026thinsp;0.002 and p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, respectively). Power-type regression analysis showed a significant correlation between diaphragmatic excursion and ventilation time (p\u0026thinsp;=\u0026thinsp;0.003 for in-ED and p\u0026thinsp;=\u0026thinsp;0.003 for in-hospital ventilation time).\u003c/p\u003e\u003ch2\u003eConclusions:\u003c/h2\u003e \u003cp\u003eDiaphragmatic ultrasound is a feasible and valuable tool for assessing diaphragmatic function in the ED. Its use provides important prognostic information, potentially guiding ventilatory strategies and improving patient outcomes by identifying those at risk for prolonged ventilation\u003c/p\u003e","manuscriptTitle":"Diaphragmatic dysfunction assessed by ultrasound: a key predictor of prolonged ventilation in emergency department.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-14 12:05:20","doi":"10.21203/rs.3.rs-6559522/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2025-05-11T15:38:10+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-08T21:00:13+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-01T03:01:34+00:00","index":"","fulltext":""},{"type":"submitted","content":"Internal and Emergency Medicine","date":"2025-04-29T17:26:48+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"internal-and-emergency-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"iaem","sideBox":"Learn more about [Internal and Emergency Medicine](http://link.springer.com/journal/11739)","snPcode":"11739","submissionUrl":"https://www.editorialmanager.com/iaem/default.aspx","title":"Internal and Emergency Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"ff01618f-feff-4aee-8658-c7fd1690130b","owner":[],"postedDate":"May 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-06-23T16:01:11+00:00","versionOfRecord":{"articleIdentity":"rs-6559522","link":"https://doi.org/10.1007/s11739-025-04020-3","journal":{"identity":"internal-and-emergency-medicine","isVorOnly":false,"title":"Internal and Emergency Medicine"},"publishedOn":"2025-06-20 15:57:30","publishedOnDateReadable":"June 20th, 2025"},"versionCreatedAt":"2025-05-14 12:05:20","video":"","vorDoi":"10.1007/s11739-025-04020-3","vorDoiUrl":"https://doi.org/10.1007/s11739-025-04020-3","workflowStages":[]},"version":"v1","identity":"rs-6559522","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6559522","identity":"rs-6559522","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}