{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,5]],"date-time":"2026-11-05T02:29:59Z","timestamp":1793845799491,"version":"4.6.1"},"reference-count":25,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T00:00:00Z","timestamp":1787875200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T00:00:00Z","timestamp":1787875200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/501100022617","name":"Fisher and Paykel Healthcare","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100022617","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of the Intensive Care Society"],"published-print":{"date-parts":[[2026,11]]},"abstract":"<jats:sec>\n                    <jats:title>Background:<\/jats:title>\n                    <jats:p>Early management decisions after intubation, such as humidification strategy or initiation of prevention bundles for ventilator-associated pneumonia, often depend on the expected duration of invasive mechanical ventilation (IMV). However, no simple, standardised method exists to support such estimates at the bedside. We aimed to develop and validate the Length of Ventilation (LoVe) index, a score to predict prolonged IMV beyond 48\u2009h using peri-intubation data.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>We conducted a retrospective cohort study using two large, publicly available ICU databases: AmsterdamUMCdb for model development and internal validation, and MIMIC-IV for external validation. The primary outcome was prolonged IMV, defined as support beyond 48\u2009h or death within 48\u2009h. Two LoVe variants were derived: a ventilator-inclusive version incorporating ventilator settings, and a ventilator-agnostic version without ventilator settings. Predictors identified via logistic regression were discretised into clinically interpretable ranges and summed into an additive score. Clinical utility was assessed using decision curve analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>In the cardiac surgery and non-cardiac surgery cohorts, the ventilator-inclusive LoVe index achieved AUROC scores of 0.82 and 0.75, respectively. The ventilator-agnostic version reached 0.72 in the non-cardiac surgery cohort. Validation in MIMIC-IV yielded 0.71 and 0.68 for the ventilator-inclusive version, and 0.71 and 0.65 for the ventilator-agnostic index. Decision curve analysis demonstrated that both LoVe indices provided meaningful clinical utility.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions:<\/jats:title>\n                    <jats:p>The LoVe index provides a simple, interpretable bedside tool to estimate the likelihood of prolonged IMV early after intubation, showing consistent external validity and potential to support early ICU decision-making.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/17511437261479649","type":"journal-article","created":{"date-parts":[[2026,8,29]],"date-time":"2026-08-29T00:35:02Z","timestamp":1787963702000},"page":"474-486","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["The LoVe score: Development and validation of a bedside clinical index to identify patients at risk for prolonged invasive mechanical ventilation"],"prefix":"10.1177","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1345-0433","authenticated-orcid":false,"given":"Paul A.","family":"Hilders","sequence":"first","affiliation":[{"name":"Department of Intensive Care Medicine, Center for Critical Care Computational Intelligence, Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Science (ACS), Amsterdam Public Health (APH), Amsterdam Institute for Immunology and Infectious Diseases (AII), Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands"},{"name":"Computer Science Department, Vrije Universiteit Amsterdam, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lada","family":"Lijovi\u0107","sequence":"additional","affiliation":[{"name":"Department of Intensive Care Medicine, Center for Critical Care Computational Intelligence, Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Science (ACS), Amsterdam Public Health (APH), Amsterdam Institute for Immunology and Infectious Diseases (AII), Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands"},{"name":"Department of Anesthesiology, Intensive Care and Pain Management, University Hospital Center Sestre Milosrdnice, Zagreb, Croatia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martijn","family":"Otten","sequence":"additional","affiliation":[{"name":"Department of Intensive Care Medicine, Center for Critical Care Computational Intelligence, Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Science (ACS), Amsterdam Public Health (APH), Amsterdam Institute for Immunology and Infectious Diseases (AII), Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands"},{"name":"Computer Science Department, Vrije Universiteit Amsterdam, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Laurens A.","family":"Biesheuvel","sequence":"additional","affiliation":[{"name":"Department of Intensive Care Medicine, Center for Critical Care Computational Intelligence, Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Science (ACS), Amsterdam Public Health (APH), Amsterdam Institute for Immunology and Infectious Diseases (AII), Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands"},{"name":"Computer Science Department, Vrije Universiteit Amsterdam, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ameet R.","family":"Jagesar","sequence":"additional","affiliation":[{"name":"Department of Intensive Care Medicine, Center for Critical Care Computational Intelligence, Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Science (ACS), Amsterdam Public Health (APH), Amsterdam Institute for Immunology and Infectious Diseases (AII), Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands"},{"name":"Computer Science Department, Vrije Universiteit Amsterdam, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Olof","family":"Sigling","sequence":"additional","affiliation":[{"name":"Department of Intensive Care Medicine, Center for Critical Care Computational Intelligence, Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Science (ACS), Amsterdam Public Health (APH), Amsterdam Institute for Immunology and Infectious Diseases (AII), Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands"},{"name":"Computer Science Department, Vrije Universiteit Amsterdam, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0447-6893","authenticated-orcid":false,"given":"Paul W. 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