title: Integrated use of bedside lung ultrasound and echocardiography in acute respiratory failure: a prospective observational study in ICU.
abstract: BACKGROUND
  It has been suggested that the complementary use of echocardiography could improve the diagnostic accuracy of lung ultrasonography (LUS) in patients with acute respiratory failure (ARF). Nevertheless, the additional diagnostic value of echocardiographic data when coupled with LUS is still debated in this setting. The aim of the current study was to compare the diagnostic accuracy of LUS and an integrative cardiopulmonary ultrasound approach (thoracic ultrasonography [TUS]) in patients with ARF.
  
  
  METHODS
  We prospectively recruited patients consecutively admitted for ARF to the ICU of a university teaching hospital over a 12-month period. Inclusion criteria were age ≥ 18 years and the presence of criteria for severe ARF justifying ICU admission. We compared both LUS and TUS approaches and the final diagnosis determined by a panel of experts using machine learning methods to improve the accuracy of the final diagnostic classifiers.
  
  
  RESULTS
  One hundred thirty-six patients were included (age, 68 ± 15 years; sex ratio, 1). A three-dimensional partial least squares and multinomial logistic regression model was developed and subsequently tested in an independent sample of patients. Overall, the diagnostic accuracy of TUS was significantly greater than LUS (P < .05, learning and test sample). Comparisons between receiver operating characteristic curves showed that TUS significantly improves the diagnosis of cardiogenic edema (P < .001, learning and test samples), pneumonia (P < .001, learning and test samples), and pulmonary embolism (P < .001, learning sample).
  
  
  CONCLUSIONS
  This study demonstrated for the first time to our knowledge a significantly better performance of TUS than LUS in the diagnosis of ARF. The value of the TUS approach was particularly important to disambiguate cases of hemodynamic pulmonary edema and pneumonia. We suggest that the bedside use of artificial intelligence methods in this setting could pave the way for the development of new clinically relevant integrative diagnostic models.
authors.affiliation: Réanimation Polyvalente, CHR Hotel Dieu, Narbonne, France.
authors.forename: Benoit
authors.initials: B
authors.lastname: Bataille
authors.affiliation: Réanimation Polyvalente et Médecine Hyperbare, CHU Purpan, Toulouse, France; Pôle Anesthésie-Réanimation, CHU Purpan, Toulouse, France.
authors.forename: Beatrice
authors.initials: B
authors.lastname: Riu
authors.affiliation: Réanimation Polyvalente et Médecine Hyperbare, CHU Purpan, Toulouse, France; Pôle Anesthésie-Réanimation, CHU Purpan, Toulouse, France.
authors.forename: Fabrice
authors.initials: F
authors.lastname: Ferre
authors.affiliation: Réanimation Polyvalente, CHR Hotel Dieu, Narbonne, France.
authors.forename: Pierre Etienne
authors.initials: PE
authors.lastname: Moussot
authors.affiliation: Réanimation Polyvalente et Médecine Hyperbare, CHU Purpan, Toulouse, France; Pôle Anesthésie-Réanimation, CHU Purpan, Toulouse, France.
authors.forename: Arnaud
authors.initials: A
authors.lastname: Mari
authors.affiliation: Réanimation Polyvalente et Médecine Hyperbare, CHU Purpan, Toulouse, France; Pôle Anesthésie-Réanimation, CHU Purpan, Toulouse, France.
authors.forename: Elodie
authors.initials: E
authors.lastname: Brunel
authors.affiliation: Réanimation Polyvalente et Médecine Hyperbare, CHU Purpan, Toulouse, France; Pôle Anesthésie-Réanimation, CHU Purpan, Toulouse, France.
authors.forename: Jean
authors.initials: J
authors.lastname: Ruiz
authors.affiliation: Réanimation Polyvalente, CHR Hotel Dieu, Narbonne, France.
authors.forename: Michel
authors.initials: M
authors.lastname: Mora
authors.affiliation: Pôle Anesthésie-Réanimation, CHU Purpan, Toulouse, France.
authors.forename: Olivier
authors.initials: O
authors.lastname: Fourcade
authors.affiliation: Réanimation Polyvalente et Médecine Hyperbare, CHU Purpan, Toulouse, France; Pôle Anesthésie-Réanimation, CHU Purpan, Toulouse, France.
authors.forename: Michele
authors.initials: M
authors.lastname: Genestal
authors.affiliation: Réanimation Polyvalente et Médecine Hyperbare, CHU Purpan, Toulouse, France; Pôle Anesthésie-Réanimation, CHU Purpan, Toulouse, France; INSERM U825, CHU Purpan, Toulouse, France. Electronic address: silvastein@me.com.
authors.forename: Stein
authors.initials: S
authors.lastname: Silva
mesh_terms: D000328:Adult; D000368:Aged; D015150:Echocardiography, Doppler / Q000379:methods*; D005260:Female; D005602:France; D006785:Hospitals, University; D006801:Humans; D007362:Intensive Care Units; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D019095:Point-of-Care Systems; D011446:Prospective Studies; D012372:ROC Curve; D012128:Respiratory Distress Syndrome / Q000000981:diagnostic imaging* / Q000503:physiopathology; D012680:Sensitivity and Specificity; D018709:Statistics, Nonparametric; D018608:Ultrasonography, Doppler / Q000379:methods*