{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,11]],"date-time":"2026-10-11T22:42:01Z","timestamp":1791758521926,"version":"4.3.4"},"reference-count":42,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"7","content-domain":{"domain":["lww.com","ovid.com"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,7]]},"abstract":"\n Objective:<\/jats:title>\n \n Current methods for estimating inspiratory muscle pressure (\n P<\/jats:italic>\n mus<\/jats:sub>\n ) during mechanical ventilation are either invasive or dependent on occlusion maneuvers. A noninvasive artificial intelligence (AI) algorithm estimating in real-time the amplitude and timing of\n P<\/jats:italic>\n mus<\/jats:sub>\n , enabling continuous monitoring of patient effort, driving pressure, and synchrony with the ventilator was designed, and its performance was evaluated against the gold standard obtained with esophageal manometry (\n P<\/jats:italic>\n mus,es<\/jats:sub>\n ).\n <\/jats:p>\n <\/jats:sec>\n \n Design:<\/jats:title>\n A prospective diagnostic accuracy study.<\/jats:p>\n <\/jats:sec>\n \n Setting:<\/jats:title>\n Two ICUs from the University of S\u00e3o Paulo, Brazil.<\/jats:p>\n <\/jats:sec>\n \n Patients:<\/jats:title>\n Adult patients under pressure support ventilation.<\/jats:p>\n <\/jats:sec>\n \n Interventions:<\/jats:title>\n None.<\/jats:p>\n <\/jats:sec>\n \n Measurements and Main Results:<\/jats:title>\n \n P<\/jats:italic>\n mus<\/jats:sub>\n estimated using AI (\n P<\/jats:italic>\n mus,AI<\/jats:sub>\n ) was compared with\n P<\/jats:italic>\n mus,es<\/jats:sub>\n and to values derived from occlusion maneuvers, the pressure muscle index and the occlusion pressure (\n P<\/jats:italic>\n occ<\/jats:sub>\n ). Automatic detection of dyssynchronies based on\n P<\/jats:italic>\n mus,AI<\/jats:sub>\n was compared with experts\u2019 classification. A total of 48 participants with 4918 cycles were analyzed.\n P<\/jats:italic>\n mus,es<\/jats:sub>\n varied from 1.0 to 28.4\u2009cm H\n 2<\/jats:sub>\n O.\n P<\/jats:italic>\n mus,AI<\/jats:sub>\n showed a bias of 0.9\u2009cm H\n 2<\/jats:sub>\n O, 95% limits of agreement \u20135.1, 6.9\u2009cm H\n 2<\/jats:sub>\n O and detected extreme values of both\n P<\/jats:italic>\n mus,es<\/jats:sub>\n and dynamic driving pressure with area under the receiver operating characteristic curve greater than 0.8.\n P<\/jats:italic>\n mus,AI<\/jats:sub>\n accuracy was comparable to occlusion-based techniques. Sensitivity and specificity to detect ineffective effort, autotriggering or reverse triggering were 86.5% and 77.4%, respectively.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions:<\/jats:title>\n \n AI presented good performance in detecting high and low\n P<\/jats:italic>\n mus<\/jats:sub>\n , and allowed the automatic detection of specific types of dyssynchronies. This novel noninvasive method was comparable to intermittent techniques requiring occlusion maneuvers.\n <\/jats:p>\n <\/jats:sec>","DOI":"10.1097\/ccm.0000000000007145","type":"journal-article","created":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T14:00:15Z","timestamp":1779372015000},"page":"1585-1596","update-policy":"https:\/\/doi.org\/10.1097\/lww.0000000000001000","source":"Crossref","is-referenced-by-count":3,"title":["Artificial Intelligence Algorithm to Monitor Inspiratory Muscle Effort and Patient-Ventilator Dyssynchrony During Mechanical Ventilation"],"prefix":"10.1097","volume":"54","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0568-0124","authenticated-orcid":false,"given":"Glauco M.","family":"Plens","sequence":"first","affiliation":[{"name":"Divisao de Pneumologia, Faculdade de Medicina, Instituto do Coracao, Hospital das Clinicas Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil."},{"name":"Division of Respirology, Department of Medicine, University Health Network, Toronto, ON, Canada."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Caio C\u00e9sar Ara\u00fajo","family":"Morais","sequence":"additional","affiliation":[{"name":"Divisao de Pneumologia, Faculdade de Medicina, Instituto do Coracao, Hospital das Clinicas Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil."},{"name":"Divis\u00e3o de Fisioterapia, Hospital das Cl\u00ednicas da Universidade Federal de Pernambuco, Recife, Brazil."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tha\u00eds","family":"Gregol","sequence":"additional","affiliation":[{"name":"Divisao de Pneumologia, Faculdade de Medicina, Instituto do Coracao, Hospital das Clinicas Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paula Breda","family":"Colpani","sequence":"additional","affiliation":[{"name":"Divisao de Pneumologia, Faculdade de Medicina, Instituto do Coracao, Hospital das Clinicas Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Glasiele C.","family":"Alcala","sequence":"additional","affiliation":[{"name":"Divisao de Pneumologia, Faculdade de Medicina, Instituto do Coracao, Hospital das Clinicas Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil."},{"name":"Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"\u00c9der","family":"Pacheco","sequence":"additional","affiliation":[{"name":"Divisao de Pneumologia, Faculdade de Medicina, Instituto do Coracao, Hospital das Clinicas Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu Hao Wang","family":"Xia","sequence":"additional","affiliation":[{"name":"Divisao de Pneumologia, Faculdade de Medicina, Instituto do Coracao, Hospital das Clinicas Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ana Carolina","family":"dos Santos","sequence":"additional","affiliation":[{"name":"Divisao de Pneumologia, Faculdade de Medicina, Instituto do Coracao, Hospital das Clinicas Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luiz Marcelo","family":"Malbouisson","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology, Hospital das Cl\u00ednicas, Universidade de S\u00e3o Paulo, S\u00e3o Paulo, Brazil."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Laurent","family":"Brochard","sequence":"additional","affiliation":[{"name":"Keenan Centre for Biomedical Research, Li Ka Shing Knowledge Institute, Unity Health, Toronto, ON, Canada."},{"name":"Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON, Canada."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elias Baedorf","family":"Kassis","sequence":"additional","affiliation":[{"name":"Division of Pulmonary and Critical Care Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ewan C.","family":"Goligher","sequence":"additional","affiliation":[{"name":"Division of Respirology, Department of Medicine, University Health Network, Toronto, ON, Canada."},{"name":"Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON, Canada."},{"name":"Department of Physiology, University of Toronto, Toronto, ON, Canada."},{"name":"Toronto General Hospital Research Institute, Toronto, ON, Canada."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carlos Roberto Ribeiro 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