{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T04:20:23Z","timestamp":1747196423202,"version":"3.40.5"},"reference-count":30,"publisher":"Public Library of Science (PLoS)","issue":"1","license":[{"start":{"date-parts":[[2024,1,2]],"date-time":"2024-01-02T00:00:00Z","timestamp":1704153600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:sec id=\"sec001\">\n<jats:title>Introduction<\/jats:title>\n<jats:p>The decision to intubate and ventilate a patient is mainly clinical. Both delaying intubation (when needed) and unnecessarily invasively ventilating (when it can be avoided) are harmful. We recently developed an algorithm predicting respiratory failure and invasive mechanical ventilation in COVID-19 patients. This is an internal validation study of this model, which also suggests a categorized \u201ctime-weighted\u201d model.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec002\">\n<jats:title>Methods<\/jats:title>\n<jats:p>We used a dataset of COVID-19 patients who were admitted to Rabin Medical Center after the algorithm was developed. We evaluated model performance in predicting ventilation, regarding the actual endpoint of each patient. We further categorized each patient into one of four categories, based on the strength of the prediction of ventilation over time. We evaluated this categorized model performance regarding the actual endpoint of each patient.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec003\">\n<jats:title>Results<\/jats:title>\n<jats:p>881 patients were included in the study; 96 of them were ventilated. AUC of the original algorithm is 0.87\u20130.94. The AUC of the categorized model is 0.95.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec004\">\n<jats:title>Conclusions<\/jats:title>\n<jats:p>A minor degradation in the algorithm accuracy was noted in the internal validation, however, its accuracy remained high. The categorized model allows accurate prediction over time, with very high negative predictive value.<\/jats:p>\n<\/jats:sec>","DOI":"10.1371\/journal.pone.0296386","type":"journal-article","created":{"date-parts":[[2024,1,2]],"date-time":"2024-01-02T19:59:55Z","timestamp":1704225595000},"page":"e0296386","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Predicting invasive mechanical ventilation in COVID 19 patients: A validation study"],"prefix":"10.1371","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8980-7860","authenticated-orcid":true,"given":"Liran","family":"Statlender","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Leonid","family":"Shvartser","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shmuel","family":"Teppler","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Itai","family":"Bendavid","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shiri","family":"Kushinir","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Roy","family":"Azullay","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pierre","family":"Singer","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"340","published-online":{"date-parts":[[2024,1,2]]},"reference":[{"key":"pone.0296386.ref001","doi-asserted-by":"crossref","first-page":"950","DOI":"10.4187\/respcare.02319","article-title":"Noninvasive Ventilation for Acute Respiratory Failure","volume":"58","author":"DR Hess","year":"2013","journal-title":"Respiratory Care"},{"key":"pone.0296386.ref002","doi-asserted-by":"crossref","first-page":"1688","DOI":"10.1056\/NEJMra2204556","article-title":"Noninvasive Respiratory Support for Adults with Acute Respiratory Failure. Hardin CC, editor","volume":"387","author":"L Munshi","year":"2022","journal-title":"N Engl J Med"},{"key":"pone.0296386.ref003","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/j.rmed.2008.08.001","article-title":"Impact of noninvasive ventilation (NIV) trial for various types of acute respiratory failure in the emergency department; decreased mortality and use of the ICU","volume":"103","author":"K Tomii","year":"2009","journal-title":"Respiratory Medicine"},{"key":"pone.0296386.ref004","doi-asserted-by":"crossref","first-page":"1438","DOI":"10.1164\/rccm.200301-072OC","article-title":"Noninvasive ventilation in severe hypoxemic respiratory failure: a randomized clinical trial","volume":"168","author":"M Ferrer","year":"2003","journal-title":"Am J Respir Crit Care Med"},{"key":"pone.0296386.ref005","doi-asserted-by":"crossref","first-page":"1585","DOI":"10.1164\/ajrccm.160.5.9903015","article-title":"Acute respiratory failure in patients with severe community-acquired pneumonia. A prospective randomized evaluation of noninvasive ventilation","volume":"160","author":"M Confalonieri","year":"1999","journal-title":"Am J Respir Crit Care Med"},{"key":"pone.0296386.ref006","doi-asserted-by":"crossref","first-page":"935","DOI":"10.1016\/S2213-2600(18)30388-6","article-title":"Beyond the guidelines for non-invasive ventilation in acute respiratory failure: implications for practice","volume":"6","author":"SC Bourke","year":"2018","journal-title":"Lancet Respir Med"},{"key":"pone.0296386.ref007","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1186\/1471-2466-14-19","article-title":"Timing of noninvasive ventilation failure: causes, risk factors, and potential remedies.","volume":"14","author":"E Ozyilmaz","year":"2014","journal-title":"BMC Pulm Med"},{"key":"pone.0296386.ref008","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1186\/s13613-015-0044-1","article-title":"Failed noninvasive positive-pressure ventilation is associated with an increased risk of intubation-related complications","volume":"5","author":"JM Mosier","year":"2015","journal-title":"Ann Intensive Care"},{"key":"pone.0296386.ref009","doi-asserted-by":"crossref","first-page":"e74937","DOI":"10.1371\/journal.pone.0074937","article-title":"Time to Intubation Is Associated with Outcome in Patients with Community-Acquired Pneumonia. Tang JW, editor","volume":"8","author":"S Hraiech","year":"2013","journal-title":"PLoS ONE"},{"key":"pone.0296386.ref010","doi-asserted-by":"crossref","first-page":"623","DOI":"10.1007\/s00134-015-3693-5","article-title":"Failure of high-flow nasal cannula therapy may delay intubation and increase mortality","volume":"41","author":"BJ Kang","year":"2015","journal-title":"Intensive Care Med"},{"key":"pone.0296386.ref011","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1186\/s13054-021-03882-1","article-title":"Impact of time to intubation on mortality and pulmonary sequelae in critically ill patients with COVID-19: a prospective cohort study","volume":"26","author":"J Gonz\u00e1lez","year":"2022","journal-title":"Crit Care"},{"key":"pone.0296386.ref012","doi-asserted-by":"crossref","first-page":"101092","DOI":"10.1016\/j.accpm.2022.101092","article-title":"Delayed intubation is associated with mortality in patients with severe COVID-19: A single-centre observational study in Switzerland.","volume":"41","author":"C Le Terrier","year":"2022","journal-title":"Anaesthesia Critical Care & Pain Medicine"},{"key":"pone.0296386.ref013","doi-asserted-by":"crossref","first-page":"546","DOI":"10.1001\/jama.2022.0028","article-title":"Effect of Noninvasive Respiratory Strategies on Intubation or Mortality Among Patients With Acute Hypoxemic Respiratory Failure and COVID-19: The RECOVERY-RS Randomized Clinical Trial","volume":"327","author":"GD Perkins","year":"2022","journal-title":"JAMA"},{"key":"pone.0296386.ref014","doi-asserted-by":"crossref","first-page":"1212","DOI":"10.1001\/jama.2022.15613","article-title":"Effect of High-Flow Nasal Cannula Oxygen vs Standard Oxygen Therapy on Mortality in Patients With Respiratory Failure Due to COVID-19: The SOHO-COVID Randomized Clinical Trial","volume":"328","author":"J-P Frat","year":"2022","journal-title":"JAMA"},{"key":"pone.0296386.ref015","doi-asserted-by":"crossref","first-page":"1203","DOI":"10.1001\/jama.2022.15229","article-title":"\u2019Kane C, McAuley DF. Respiratory Support in the Time of COVID-19","volume":"328","author":"O Nichol AD","year":"2022","journal-title":"JAMA"},{"volume-title":"Coronavirus Disease 2019 (COVID-19) Treatment Guidelines.","year":"2023","author":"COVID-19 Treatment Guidelines Panel","key":"pone.0296386.ref016"},{"key":"pone.0296386.ref017","doi-asserted-by":"crossref","first-page":"286","DOI":"10.21037\/atm.2017.07.08","article-title":"Driving pressure and mechanical power: new targets for VILI prevention","volume":"5","author":"T Tonetti","year":"2017","journal-title":"Ann Transl Med"},{"key":"pone.0296386.ref018","doi-asserted-by":"crossref","first-page":"e0214465","DOI":"10.1371\/journal.pone.0214465","article-title":"Machine learning for patient risk stratification for acute respiratory distress syndrome","volume":"14","author":"D Zeiberg","year":"2019","journal-title":"PLoS One"},{"key":"pone.0296386.ref019","doi-asserted-by":"crossref","first-page":"e0276509","DOI":"10.1371\/journal.pone.0276509","article-title":"Machine learning predicts the short-term requirement for invasive ventilation among Australian critically ill COVID-19 patients. Rashid TA, editor","volume":"17","author":"R Karri","year":"2022","journal-title":"PLoS ONE"},{"key":"pone.0296386.ref020","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1016\/S2213-2600(20)30559-2","article-title":"Development and validation of the ISARIC 4C Deterioration model for adults hospitalised with COVID-19: a prospective cohort study","volume":"9","author":"RK Gupta","year":"2021","journal-title":"The Lancet Respiratory Medicine"},{"key":"pone.0296386.ref021","doi-asserted-by":"crossref","first-page":"e516","DOI":"10.1016\/S2589-7500(20)30217-X","article-title":"Clinical features of COVID-19 mortality: development and validation of a clinical prediction model","volume":"2","author":"AS Yadaw","year":"2020","journal-title":"The Lancet Digital Health"},{"key":"pone.0296386.ref022","doi-asserted-by":"crossref","first-page":"2001104","DOI":"10.1183\/13993003.01104-2020","article-title":"Development of a Clinical Decision Support System for Severity Risk Prediction and Triage of COVID-19 Patients at Hospital Admission: an International Multicenter Study","author":"G Wu","year":"2020","journal-title":"Eur Respir J"},{"key":"pone.0296386.ref023","doi-asserted-by":"crossref","first-page":"e0249285","DOI":"10.1371\/journal.pone.0249285","article-title":"Machine learning methods to predict mechanical ventilation and mortality in patients with COVID-19. Chen RJ, editor","volume":"16","author":"L Yu","year":"2021","journal-title":"PLoS ONE"},{"key":"pone.0296386.ref024","doi-asserted-by":"crossref","first-page":"4200","DOI":"10.1038\/s41598-021-83784-y","article-title":"Early risk assessment for COVID-19 patients from emergency department data using machine learning","volume":"11","author":"FS Heldt","year":"2021","journal-title":"Sci Rep"},{"key":"pone.0296386.ref025","doi-asserted-by":"crossref","first-page":"1668","DOI":"10.3390\/jcm9061668","article-title":"Using Machine Learning to Predict ICU Transfer in Hospitalized COVID-19 Patients","volume":"9","author":"F-Y Cheng","year":"2020","journal-title":"JCM"},{"key":"pone.0296386.ref026","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.jcrc.2020.10.033","article-title":"Development of a machine learning algorithm to predict intubation among hospitalized patients with COVID-19","volume":"62","author":"V Arvind","year":"2021","journal-title":"Journal of Critical Care"},{"key":"pone.0296386.ref027","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1038\/s42256-020-0180-7","article-title":"An interpretable mortality prediction model for COVID-19 patients.","volume":"2","author":"L Yan","year":"2020","journal-title":"Nat Mach Intell"},{"key":"pone.0296386.ref028","doi-asserted-by":"crossref","first-page":"10573","DOI":"10.1038\/s41598-022-14758-x","article-title":"A novel machine learning model to predict respiratory failure and invasive mechanical ventilation in critically ill patients suffering from COVID-19","volume":"12","author":"I Bendavid","year":"2022","journal-title":"Sci Rep"},{"key":"pone.0296386.ref029","doi-asserted-by":"crossref","first-page":"2145","DOI":"10.1256\/003590002320603584","article-title":"Areas beneath the relative operating characteristics (ROC) and relative operating levels (ROL) curves: Statistical significance and interpretation","volume":"128","author":"SJ Mason","year":"2002","journal-title":"Q J R Meteorol Soc"},{"key":"pone.0296386.ref030","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1007\/s00134-016-4601-3","article-title":"Assessment of heart rate, acidosis, consciousness, oxygenation, and respiratory rate to predict noninvasive ventilation failure in hypoxemic patients","volume":"43","author":"J Duan","year":"2017","journal-title":"Intensive Care Med"}],"container-title":["PLOS ONE"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0296386","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,2]],"date-time":"2024-01-02T20:00:13Z","timestamp":1704225613000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0296386"}},"subtitle":[],"editor":[{"given":"Samuele","family":"Ceruti","sequence":"first","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2024,1,2]]},"references-count":30,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,1,2]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pone.0296386","relation":{},"ISSN":["1932-6203"],"issn-type":[{"type":"electronic","value":"1932-6203"}],"subject":[],"published":{"date-parts":[[2024,1,2]]}}}