{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T00:17:14Z","timestamp":1791505034618,"version":"4.3.4"},"reference-count":22,"publisher":"Elsevier BV","issue":"1","license":[{"start":{"date-parts":[[2021,2,8]],"date-time":"2021-02-08T00:00:00Z","timestamp":1612742400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2021,2,8]],"date-time":"2021-02-08T00:00:00Z","timestamp":1612742400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Ann. Intensive Care"],"published-print":{"date-parts":[[2021,12]]},"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n \n High respiratory drive in mechanically ventilated patients with spontaneous breathing effort may cause excessive lung stress and strain and muscle loading. Therefore, it is important to have a reliable estimate of respiratory effort to guarantee lung and diaphragm protective mechanical ventilation. Recently, a novel non-invasive method was found to detect excessive dynamic transpulmonary driving pressure (\u2206\n P<\/jats:italic>\n L<\/jats:sub>\n ) and respiratory muscle pressure (\n P<\/jats:italic>\n mus<\/jats:sub>\n ) with reasonable accuracy. During the Coronavirus disease 2019 (COVID-19) pandemic, it was impossible to obtain the gold standard for respiratory effort, esophageal manometry, in every patient. Therefore, we investigated whether this novel non-invasive method could also be applied in COVID-19 patients.\n <\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n \n \u2206\n P<\/jats:italic>\n L<\/jats:sub>\n and\n P<\/jats:italic>\n mus<\/jats:sub>\n were derived from esophageal manometry in COVID-19 patients. In addition, \u2206\n P<\/jats:italic>\n L<\/jats:sub>\n and\n P<\/jats:italic>\n mus<\/jats:sub>\n were computed from the occlusion pressure (\u2206\n P<\/jats:italic>\n occ<\/jats:sub>\n ) obtained during an expiratory occlusion maneuver. Measured and computed \u2206\n P<\/jats:italic>\n L<\/jats:sub>\n and\n P<\/jats:italic>\n mus<\/jats:sub>\n were compared and discriminative performance for excessive \u2206\n P<\/jats:italic>\n L<\/jats:sub>\n and\n P<\/jats:italic>\n mus<\/jats:sub>\n was assessed. The relation between occlusion pressure and respiratory effort was also assessed.\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n Thirteen patients were included. Patients had a low dynamic lung compliance [24 (20\u201331) mL\/cmH\n 2<\/jats:sub>\n O], high \u2206\n P<\/jats:italic>\n L<\/jats:sub>\n (25\u2009\u00b1\u20096 cmH\n 2<\/jats:sub>\n O) and high\n P<\/jats:italic>\n mus<\/jats:sub>\n (16\u2009\u00b1\u20097 cmH\n 2<\/jats:sub>\n O). Low agreement was found between measured and computed \u2206\n P<\/jats:italic>\n L<\/jats:sub>\n and\n P<\/jats:italic>\n mus<\/jats:sub>\n . Excessive \u2206\n P<\/jats:italic>\n L<\/jats:sub>\n \u2009>\u200920 cmH\n 2<\/jats:sub>\n O and\n P<\/jats:italic>\n mus<\/jats:sub>\n \u2009>\u200915 cmH\n 2<\/jats:sub>\n O were accurately detected (area under the receiver operating curve (AUROC) 1.00 [95% confidence interval (CI), 1.00\u20131.00], sensitivity 100% (95% CI, 72\u2013100%) and specificity 100% (95% CI, 16\u2013100%) and AUROC 0.98 (95% CI, 0.90\u20131.00), sensitivity 100% (95% CI, 54\u2013100%) and specificity 86% (95% CI, 42\u2013100%), respectively). Respiratory effort calculated per minute was highly correlated with \u2206\n P<\/jats:italic>\n occ<\/jats:sub>\n (for esophageal pressure time product per minute (PTP\n es\/min<\/jats:sub>\n )\n r<\/jats:italic>\n 2<\/jats:sup>\n \u2009=\u20090.73;\n P<\/jats:italic>\n \u2009=\u20090.0002 and work of breathing (WOB)\n r<\/jats:italic>\n 2<\/jats:sup>\n \u2009=\u20090.85;\n P<\/jats:italic>\n \u2009<\u20090.0001).\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n \n \u2206\n P<\/jats:italic>\n L<\/jats:sub>\n and\n P<\/jats:italic>\n mus<\/jats:sub>\n can be computed from an expiratory occlusion maneuver and can predict excessive \u2206\n P<\/jats:italic>\n L<\/jats:sub>\n and\n P<\/jats:italic>\n mus<\/jats:sub>\n in patients with COVID-19 with high accuracy.\n <\/jats:p>\n <\/jats:sec>","DOI":"10.1186\/s13613-021-00821-9","type":"journal-article","created":{"date-parts":[[2021,2,8]],"date-time":"2021-02-08T17:46:35Z","timestamp":1612806395000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Non-invasive method to detect high respiratory effort and transpulmonary driving pressures in COVID-19 patients during mechanical ventilation"],"prefix":"10.1016","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7375-926X","authenticated-orcid":false,"given":"Lisanne","family":"Roesthuis","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maarten","family":"van den Berg","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hans","family":"van der Hoeven","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","published-online":{"date-parts":[[2021,2,8]]},"reference":[{"issue":"2","key":"821_CR1","doi-asserted-by":"publisher","first-page":"204","DOI":"10.1164\/rccm.201703-0536OC","volume":"197","author":"EC Goligher","year":"2018","unstructured":"Goligher EC, Dres M, Fan E, Rubenfeld GD, Scales DC, Herridge MS, et al. 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