{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T07:04:54Z","timestamp":1774940694087,"version":"3.50.1"},"reference-count":40,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T00:00:00Z","timestamp":1774915200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Med."],"abstract":"<jats:sec>\n                    <jats:title>Study aim<\/jats:title>\n                    <jats:p>Evluate bedside lung ultrasound (LUS) diagnostic accuracy versus chest computed tomography (CT) in adult ICU patients with respiratory distress.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design and methods<\/jats:title>\n                    <jats:p>Single-center, cross-sectional study of 200 paired LUS-CT examinations. LUS was performed within 12\u202fh, scanning six zones per hemithorax and classifying findings into A-lines, C1 (pneumonia), C2 (atelectasis), B1, B2 (interstitial patterns), pleural effusion, and emphysema. Diagnostic performance metrics included sensitivity, specificity, predictive values, likelihood ratios, and ROC analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Key results<\/jats:title>\n                    <jats:p>CT showed consolidations (60.5%), pleural effusions (42.5%), interstitial syndrome (28.5%), ground-glass opacities (26%), and emphysema (23.5%). LUS detected C1 in 66.5% (posterior-inferior predominance), B2 in 40.5%, B1 in 40%, pleural effusions in 38.5%, C2 in 13.5%, and emphysema in 16.5%. Overall concordance with CT was 81%. LUS had very high specificity for pleural effusion (Sp\u202f=\u202f96.5%, PLR\u202f=\u202f24.5, accuracy\u202f=\u202f91.9%) and atelectasis (Sp\u202f=\u202f93.7%, NPV\u202f=\u202f97.6%, PLR\u202f=\u202f12.6, accuracy\u202f=\u202f92.3%), very high sensitivity for alveolar-interstitial syndrome (Se\u202f=\u202f96.2%, NPV\u202f=\u202f98.3%, NLR\u202f=\u202f0.05), and good sensitivity for consolidations (Se\u202f=\u202f89.3%).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>LUS is a reliable bedside tool that can reduce CT use, radiation exposure, and enable dynamic monitoring; structured training is essential.<\/jats:p>\n                  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Tunisia"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Asma","family":"Mehdi","sequence":"additional","affiliation":[{"name":"Faculty of Medicine, Tunis El Manar University","place":["Tunis, Tunisia"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lynda","family":"Messaoud","sequence":"additional","affiliation":[{"name":"Faculty of Medicine, Tunis El Manar University","place":["Tunis, Tunisia"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eya","family":"Seghir","sequence":"additional","affiliation":[{"name":"Faculty of Medicine, Tunis El Manar University","place":["Tunis, Tunisia"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Asma","family":"Ouhibi","sequence":"additional","affiliation":[{"name":"Faculty of Medicine, Tunis El Manar University","place":["Tunis, Tunisia"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rochdi","family":"Nasri","sequence":"additional","affiliation":[{"name":"Faculty 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