{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T06:20:19Z","timestamp":1783059619750,"version":"3.54.6"},"reference-count":38,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T00:00:00Z","timestamp":1783036800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002347","name":"Bundesministerium f\u00fcr Bildung und Forschung","doi-asserted-by":"publisher","award":["LS-2-2-037a"],"award-info":[{"award-number":["LS-2-2-037a"]}],"id":[{"id":"10.13039\/501100002347","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007210","name":"RWTH Aachen University","doi-asserted-by":"publisher","award":["G:(DE-82)ZUK2-SF-SFFAIR001"],"award-info":[{"award-number":["G:(DE-82)ZUK2-SF-SFFAIR001"]}],"id":[{"id":"10.13039\/501100007210","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Digit. Health"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Acute respiratory distress syndrome is a heterogeneous syndrome that complicates risk stratification, therapy monitoring and personalised treatment during veno-venous extracorporeal membrane oxygenation. This study aims to identify discrete acute respiratory distress syndrome subphenotypes among veno-venous extracorporeal membrane oxygenation (VV-ECMO) patients using high-resolution electronic health record clustering, and to assess differences in clinical outcomes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and methods<\/jats:title>\n                    <jats:p>We conducted a study of 598 adult patients with acute respiratory distress syndrome treated with VV-ECMO. Twenty-six clinically relevant parameters spanning inflammation, coagulation, kidney\/liver function, mechanical ventilation, and ECMO parameters were analysed using K-means clustering. Shapley Additive Explanations models were used to identify key differentiating parameters between clusters and independent survival factors. Clinical outcomes were compared between clusters, including treatment duration and survival rates in intensive care.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Cluster analysis revealed distinct subphenotypes primarily driven by differences in inflammation (procalcitonin and C-reactive protein), kidney\/liver function (creatinine and urea), coagulation (fibrinogen and D-dimer), and mechanical ventilation (positive end-expiratory pressure). Survival rates varied considerably between clusters, most notably within the kidney\/liver function (32%) and combined parameter categories (21%). Subphenotypes defined solely by ECMO or ventilator settings showed smaller differences. Intensive care unit length of stay was longer in clusters with multi-organ dysfunction.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Early data-driven clustering of electronic health record parameters identifies clinically meaningful acute respiratory distress syndrome subphenotypes among veno-venous extracorporeal membrane oxygenation patients. Renal, hepatic, and inflammatory dysfunctions are critical determinants of survival. Subphenotype-based stratification may refine risk stratification and management in severe acute respiratory distress syndrome treated with VV-ECMO.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fdgth.2026.1736849","type":"journal-article","created":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T05:39:29Z","timestamp":1783057169000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Data-driven subphenotyping of severe ARDS patients requiring VV-ECMO"],"prefix":"10.3389","volume":"8","author":[{"given":"Micha","family":"Landoll","sequence":"first","affiliation":[{"name":"Department of Pneumology and Critical Care Medicine, ARDS and ECMO Centre, Cologne-Merheim Hospital","place":["Cologne, Germany"]},{"name":"Cardiovascular Engineering, Applied Medical Engineering, RWTH Aachen University","place":["Aachen, Germany"]},{"name":"Institute for Computational Biomedicine, RWTH Aachen University","place":["Aachen, Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephan","family":"Strassmann","sequence":"additional","affiliation":[{"name":"Department of Pneumology and Critical Care Medicine, ARDS and ECMO Centre, Cologne-Merheim Hospital","place":["Cologne, Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wolfram","family":"Windisch","sequence":"additional","affiliation":[{"name":"Department of Pneumology and Critical Care Medicine, ARDS and ECMO Centre, Cologne-Merheim Hospital","place":["Cologne, Germany"]},{"name":"Department of Respiratory Medicine, University Witten\/Herdecke","place":["Witten, Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ulrich","family":"Steinseifer","sequence":"additional","affiliation":[{"name":"Cardiovascular Engineering, Applied Medical Engineering, RWTH Aachen University","place":["Aachen, Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andreas","family":"Schuppert","sequence":"additional","affiliation":[{"name":"Institute for Computational Biomedicine, RWTH Aachen University","place":["Aachen, Germany"]},{"name":"Center for Computational Life Sciences, RWTH Aachen University","place":["Aachen, Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Neidlin","sequence":"additional","affiliation":[{"name":"Cardiovascular Engineering, Applied Medical Engineering, RWTH Aachen University","place":["Aachen, Germany"]},{"name":"Center for Computational Life Sciences, RWTH Aachen University","place":["Aachen, Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christian","family":"Karagiannidis","sequence":"additional","affiliation":[{"name":"Department of Pneumology and Critical Care Medicine, ARDS and ECMO Centre, Cologne-Merheim Hospital","place":["Cologne, Germany"]},{"name":"Department of 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