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Lung-Dependent Areas Collapse, Monitored by Electrical Impedance Tomography, May Predict the Oxygenation Response to Prone Ventilation in COVID-19 Acute Respiratory Distress Syndrome.
Cardinale, Michael; Boussen, Salah; Cungi, Pierre-Julien; Esnault, Pierre; Mathais, Quentin; Bordes, Julien; Meaudre, Eric; Goutorbe, Philippe.
  • Cardinale M; Intensive Care Unit, Sainte Anne Military Teaching Hospital, Toulon, France.
  • Boussen S; Intensive Care Unit, Timone University Hospital, Marseille, France.
  • Cungi PJ; Intensive Care Unit, Sainte Anne Military Teaching Hospital, Toulon, France.
  • Esnault P; Intensive Care Unit, Sainte Anne Military Teaching Hospital, Toulon, France.
  • Mathais Q; Department of Anesthesia, Sainte Anne Military Teaching Hospital, Toulon, France.
  • Bordes J; Department of Anesthesia, Sainte Anne Military Teaching Hospital, Toulon, France.
  • Meaudre E; Intensive Care Unit, Sainte Anne Military Teaching Hospital, Toulon, France.
  • Goutorbe P; Intensive Care Unit, Sainte Anne Military Teaching Hospital, Toulon, France.
Crit Care Med ; 50(7): 1093-1102, 2022 07 01.
Article in English | MEDLINE | ID: covidwho-1708182
ABSTRACT

OBJECTIVES:

ICUs have had to deal with a large number of patients with acute respiratory distress syndrome COVID-19, a significant number of whom received prone ventilation, which is a substantial consumer of care time. The selection of patients that we have to ventilate in prone position seems interesting. We evaluate the correlation between the percentage of collapsed dependent lung areas in the supine position, monitoring by electrical impedance tomography and the oxygenation response (change in Pao2/Fio2 ratio) to prone position.

DESIGN:

An observational prospective study.

SETTING:

From October 21, 2020, to 30 March 30, 2021. At the Sainte Anne military teaching Hospital and the Timone University Hospital. PATIENTS Fifty consecutive patients admitted in our ICUs, with COVID-19 acute respiratory distress syndrome and required mechanical, were included. Twenty-four (48%) received prone ventilation. Fifty-eight prone sessions were investigated.

INTERVENTIONS:

An electrical impedance tomography recording was made in supine position, daily and repeated just before and just after the prone session. The daily dependent area collapse was calculated in relation to the previous electrical impedance tomography recording. Prone ventilation response was defined as a Pao2/Fio2 ratio improvement greater than 20%. MEASUREMENT AND MAIN

RESULTS:

The main outcome was the correlation between dependent area collapse and the oxygenation response to prone ventilation. Dependent area collapse was correlated with oxygenation response to prone ventilation (R2 = 0.49) and had a satisfactory prediction accuracy of prone response with an area under the curve of 0.94 (95% CI, 0.87-1.00; p < 0.001). Best Youden index was obtained for a dependent area collapse greater than 13.5 %. Sensitivity of 92% (95% CI, 78-97), a specificity of 91% (95% CI, 72-97), a positive predictive value of 94% (95% CI, 88-100), a negative predictive value of 87% (95% CI, 78-96), and a diagnostic accuracy of 91% (95% CI, 84-98).

CONCLUSIONS:

Dependent lung areas collapse (> 13.5%), monitored by electrical impedance tomography, has an excellent positive predictive value (94%) of improved oxygenation during prone ventilation.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Respiratory Distress Syndrome / Shock / COVID-19 Type of study: Cohort study / Diagnostic study / Experimental Studies / Observational study / Prognostic study Limits: Humans Language: English Journal: Crit Care Med Year: 2022 Document Type: Article Affiliation country: CCM.0000000000005487

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Respiratory Distress Syndrome / Shock / COVID-19 Type of study: Cohort study / Diagnostic study / Experimental Studies / Observational study / Prognostic study Limits: Humans Language: English Journal: Crit Care Med Year: 2022 Document Type: Article Affiliation country: CCM.0000000000005487