DISCUSSION

Respiratory failure is one of the most common conditions in the ICU and often requires chest imaging for accurate diagnosis38, 39. Physicians need to make an accurate diagnosis, define disease severity, assess response to treatment and prognosticate, and PU represents an emerging technique for accomplishing these in a safe, timely, and cost-efficient manner. Portable chest x-ray has significant limitations7 and potential risks (e.g. accidental removal of lines/tubes) while chest CT has notable drawbacks such as increased radiation, cost, and the need to transport the patient from the ICU9, 10, 40.
Small studies of PU scoring systems in disease-specific patient populations and their association to various clinical metrics exist5, 11, 15–20, as does a large (260 patients) study proposing a standardized diagnostic system based on lung ultrasound profiles1. However, to our knowledge a large prospective study of a simple lung ultrasound scoring system and its association to clinical outcomes including mortality across a wide spectrum of clinical disease has not been previously reported. The current approach was studied in 250 patients from medical/surgical, neuro, and cardiovascular ICUs, and thus the results are highly applicable to a diverse ICU population. Furthermore, this 9-point , taking on average 2-3 minutes to perform, can be feasibly integrated into the daily physical of patients in their typical positioning.
The 9 lung zones included in this algorithm reflect a clinical in an applied setting, rather than a workflow designed for a research protocol. There are no formally endorsed approaches to a clinical PU , though both an 8 and 28-point have been described5. A clinical PU sequence often involves conceptual lobar anatomy, and thus the right lateral, caudal area was divided into both an anterior and posterior zone over the right middle and lower lobes respectively. Designation of an “extra” zone in the right lung, in addition to being clinically relevant, can be physiologically rationalized based on the greater total lung capacity of the right lung41. Of interest, 3.9% of our patients with aspiration and pneumonia had findings present only in the right lateral, caudal zone on the anterior axillary line that would have been missed if that zone was not included in the . A sensitivity analysis was conducted both with and without this additional zone included, and similar associations between lung scores and outcomes were observed with both methods.
Many previous studies have examined the association of the presence of B-lines to various outcomes. However, in this study, ascending points (0 to 3) were assigned to the continuum of lung abnormality classifications from the normal, fully aerated A classification (0 points) to the least aerated consolidation and atelectasis (3 points). Of note, there was no significant difference in the predictive power of our score when atelectasis, consolidation, or small consolidations resulted in an extra point beyond the B3 classification (i.e. the zone was given a total of 4 points rather than 3) versus if each of these entities received 3 points for simplicity. By assigning 1 point for each zone with effusion (with patients positioned semi-upright) a feasible and semi-quantitative assessment of pleural effusion was incorporated into the TLS. The modification of isolated atelectasis in the lateral caudal lung zone on the posterior axillary line receiving 1 point instead of 3, resulted in improved predictive power across metrics and is consistent with the limited significance this isolated finding has in the clinical environment.
The association of this PU scoring system to mortality in a large population of intubated ICU patients with ARF is important from a clinical standpoint, as various small studies have only demonstrated associations of specific PU findings with outcomes in specific disease states15, 17–20. Non-ultrasound based models predict mortality amongst ICU patients, however they typically rely on a combination of physiologic variables and comorbid conditions, and few exist specifically for intubated patients42, 43. Beyond the observed association with mortality, potential use of the TLS in predicting ventilator hours and LOS may be useful in guiding family expectations, patient flow, and quality measures tied to LOS, but this requires further study.
Some limitations to our study exist. To preserve efficiency, we examined a limited surface area of the lung and this may have led to overestimation of a process that only existed under the transducer, or the inability to visualize a pulmonary process present just outside the area of examination. Our inter-observer agreement was calculated based solely on image review, thus dismissing the variability that can exist in image acquisition. Physicians performing the were blinded to patient data, but there were opportunities for this blinding to have been incomplete and possibly influence their assessment (e.g. medication infusions visible at the bedside, other provider discussions in/around the patient room). Having a single provider perform the repeat on an individual patient, while meant to ensure consistency, may have introduced bias with the examiner knowing the previous location of findings. Despite these instances of potential “unblinding”, they all do reflect the reality of PU in the clinical setting. Retrospective chart review was used to determine a final diagnosis, but, as can be the case in ARF patients, more than one etiology may have been contributing, or the diagnosis was not definitive. The number of extubation more than 48 hours after the initial exam was small (n=30) due to ICU workflow and difficulty coordinating a blinded US with the treatment team. This prevented us from adequately assessing TLS change from baseline to extubation.
The differential diagnosis for ARF is often difficult to narrow based on history, physical , and laboratory data alone. PU is immediately available at the bedside and can provide helpful diagnostic information in these patients, especially when combined with cardiac and vascular US. This simple PU scoring system, which provides for standardized quantification and communication of PU findings between and providers, had good agreement amongst providers, was quick to perform, and correlated well with important clinical outcomes.

References

1. Lichtenstein DA, Mézière GA. Relevance of lung ultrasound in the diagnosis of acute respiratory failure: The BLUE Protocol. Chest 2008;134:117.
2. Blaivas M. Lung ultrasound in evaluation of pneumonia. J Ultrasound Med 2012;31:823.
3. Bataille B, Riu B, Ferre F, et al. Integrated use of bedside lung ultrasound and echocardiography in acute respiratory failure: a prospective observational study in ICU. Chest 2014;146:1586.
4. Bilotta F, Giudici LD, Zeppa IO, et al. Ultrasound imaging and use of B-lines for functional lung evaluation in neurocritical care: a prospective, observational study. Eur J Anaesthesiol 2013;30:464.
5. Volpicelli G, Elbarbary M, Blaivas M, et al. International evidence-based recommendations for point-of-care lung ultrasound. Intensive Care Med 2012;38:577.
6. Pivetta E, Goffi A, Lupia E, et al. Lung Ultrasound-Implemented Diagnosis of Acute Decompensated Heart Failure in the ED: A SIMEU Multicenter Study. Chest 2015;148:202.
7. Xirouchaki N, Magkanas E, Vaporidi K, et al. Lung ultrasound in critically ill patients: comparison with bedside chest radiography. Intensive Care Med 2011;37:1488.
8. Fanara B, Manzon C, Barbot O, et al. Recommendations for the intra-hospital transport of critically ill patients. Crit Care 2010;14:R87.
9. Ott LK, Hoffman LA, Hravnak M. Intrahospital Transport to the Radiology Department: Risk for Adverse Events, Nursing Surveillance, Utilization of a MET and Practice Implications. J Radiol Nurs 2011;30:49.
10. Waydhas C. Intrahospital transport of critically ill patients. Crit Care 1999;3:R83.
11. Anderson KL, Fields JM, Panebianco NL, et al. Inter-rater reliability of quantifying pleural B-lines using multiple counting methods. J Ultrasound Med 2013;32:115.
12. Sperandeo M, Trovato GM, Catalano D. Quantifying B-lines on lung sonography: insufficient evidence as an objective, constructive, and educational tool. J Ultrasound Med 2014;33:362.
13. Cibinel GA, Casoli G, Elia F, et al. Diagnostic accuracy and reproducibility of pleural and lung ultrasound in discriminating cardiogenic causes of acute dyspnea in the emergency department. Intern Emerg Med 2012;7:65.
14. Chiem AT, Chan CH, Ander DS, et al. Comparison of expert and novice sonographers’ performance in focused lung ultrasonography in dyspnea (FLUID) to diagnose patients with acute heart failure syndrome. Acad Emerg Med 2015;22:564.
15. Frassi F, Gargani L, Tesorio P, et al. Prognostic value of extravascular lung water assessed with ultrasound lung comets by chest sonography in patients with dyspnea and/or chest pain. J Card Fail 2007;13:830.
16. Enghard P, Rademacher S, Nee J, et al. Simplified lung ultrasound protocol shows excellent prediction of extravascular lung water in ventilated intensive care patients. Crit Care 2015;19:36.
17. Zhao Z, Jiang L, Xi X, et al. Prognostic value of extravascular lung water assessed with lung ultrasound score by chest sonography in patients with acute respiratory distress syndrome. BMC Pulm Med 2015;15:98.
18. Li L, Yang Q, Li L, et al. [The value of lung ultrasound score on evaluating clinical severity and prognosis in patients with acute respiratory distress syndrome]. Zhonghua Wei Zhong Bing Ji Jiu Yi Xue 2015;27:579.
19. Zoccali C, Torino C, Tripepi R, et al. Pulmonary congestion predicts cardiac events and mortality in ESRD. J Am Soc Nephrol 2013;24:639.
20. Platz E, Lewis EF, Uno H, et al. Detection and prognostic value of pulmonary congestion by lung ultrasound in ambulatory heart failure patients. European heart journal 2016;37:1244.
21. Noble VE, Murray AF, Capp R, et al. Ultrasound assessment for extravascular lung water in patients undergoing hemodialysis. Time course for resolution. Chest 2009;135:1433.
22. Lichtenstein D, Mézière G, Biderman P, et al. The comet-tail artifact. An ultrasound sign of alveolar-interstitial syndrome. Am J Respir Crit Care Med 1997;156:1640.
23. Picano E, Frassi F, Agricola E, et al. Ultrasound lung comets: a clinically useful sign of extravascular lung water. Journal of the American Society of Echocardiography 2006;19:356.
24. Jambrik Z, Gargani L, Adamicza Ã, et al. B-lines quantify the lung water content: a lung ultrasound versus lung gravimetry study in acute lung injury. Ultrasound in medicine & biology 2010;36:2004.
25. Lubrano R, Cecchetti C, Elli M, et al. Prognostic value of extravascular lung water index in critically ill children with acute respiratory failure. Intensive Care Med 2011;37:124.
26. Sakka SG, Klein M, Reinhart K, et al. Prognostic value of extravascular lung water in critically ill patients. Chest 2002;122:2080.
27. Yang CS, Qiu HB, Liu SQ, et al. [The prognostic value of extravascular lung water index in critically ill septic shock patients]. Zhonghua Nei Ke Za Zhi 2006;45:192.
28. Zhang Z, Lu B, Ni H. Prognostic value of extravascular lung water index in critically ill patients: a systematic review of the literature. J Crit Care 2012;27:420.
29. Bognar Z, Foldi V, Rezman B, et al. Extravascular lung water index as a sign of developing sepsis in burns. Burns 2010;36:1263.
30. Chung FT, Lin SM, Lin SY, et al. Impact of extravascular lung water index on outcomes of severe sepsis patients in a medical intensive care unit. Respir Med 2008;102:956.
31. Chung FT, Lin HC, Kuo CH, et al. Extravascular lung water correlates multiorgan dysfunction syndrome and mortality in sepsis. PLoS One 2010;5:e15265.
32. Craig TR, Duffy MJ, Shyamsundar M, et al. Extravascular lung water indexed to predicted body weight is a novel predictor of intensive care unit mortality in patients with acute lung injury. Crit Care Med 2010;38:114.
33. Davey-Quinn A, Gedney JA, Whiteley SM, et al. Extravascular lung water and acute respiratory distress syndrome–oxygenation and outcome. Anaesth Intensive Care 1999;27:357.
34. Martin GS, Eaton S, Mealer M, et al. Extravascular lung water in patients with severe sepsis: a prospective cohort study. Crit Care 2005;9:R74.
35. Phillips CR, Chesnutt MS, Smith SM. Extravascular lung water in sepsis-associated acute respiratory distress syndrome: indexing with predicted body weight improves correlation with severity of illness and survival. Crit Care Med 2008;36:69.
36. Lichtenstein DA, Mezière GA. The BLUE-points: three standardized points used in the BLUE-protocol for ultrasound assessment of the lung in acute respiratory failure. Critical Ultrasound Journal 2011;3:109.
37. Brattain LJ, Telfer BA, Liteplo AS, et al. Automated B-line scoring on thoracic sonography. J Ultrasound Med 2013;32:2185.
38. Lichtenstein DA. BLUE-protocol and FALLS-protocol: two applications of lung ultrasound in the critically ill. Chest 2015;147:1659.
39. Via G, Storti E, Gulati G, et al. Lung ultrasound in the ICU: from diagnostic instrument to respiratory monitoring tool. Minerva Anestesiol 2012;78:1282.
40. Gargani L, Picano E. The risk of cumulative radiation exposure in chest imaging and the advantage of bedside ultrasound. Crit Ultrasound J 2015;7:4.
41. Johansen B, Bjørtuft O, Boe J. Static lung volumes in healthy subjects assessed by helium dilution during occlusion of one mainstem bronchus. Thorax 1993;48:381.
42. Pannu SR, Moreno Franco P, Li G, et al. Development and validation of severe hypoxemia associated risk prediction model in 1,000 mechanically ventilated patients. Crit Care Med 2015;43:308.
43. Umegaki T, Nishimura M, Tajimi K, et al. An in-hospital mortality equation for mechanically ventilated patients in intensive care units. J Anesth 2013;27:541.

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