{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,17]],"date-time":"2025-12-17T09:02:51Z","timestamp":1765962171920,"version":"3.48.0"},"reference-count":14,"publisher":"EDP Sciences","issue":"4","license":[{"start":{"date-parts":[[2025,12,17]],"date-time":"2025-12-17T00:00:00Z","timestamp":1765929600000},"content-version":"vor","delay-in-days":16,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J Extra Corpor Technol","JECT"],"accepted":{"date-parts":[[2025,7,24]]},"published-print":{"date-parts":[[2025,12]]},"abstract":"<jats:p>\n                    <jats:italic>Introduction<\/jats:italic>\n                    : Patients receiving mechanical circulatory support (MCS) risk the development of sepsis. Examining risk factors for the development of sepsis and their relationships to MCS may allow for an improved understanding of these complications.\n                    <jats:italic>Methods<\/jats:italic>\n                    : Following IRB approval, patient characteristics, previously reported comorbidities, and the incidence of sepsis were studied in 199 patients who received 244 MCS therapies from January 2017 to October 2023. The clinical variables underwent ensemble machine learning modeling. Significant comorbidities predicting sepsis from the ensemble machine modeling underwent decision-tree analysis.\n                    <jats:italic>Results<\/jats:italic>\n                    : In this study, the incidence of sepsis was 20% (95% CI: 16\u201326%). Following machine learning modeling, patients with a history of congestive heart failure or a history of previous cardiac surgery were associated with an increased risk for developing sepsis. The c-index statistic for this model was 0.76, with a misclassification rate of 19%. Decision-tree analysis observed that patients without chronic cardiovascular disease but with a history of prior cardiac surgery have a 60.3% (95% CI: 60.1\u201365.2%) incidence of sepsis during MCS therapy. Patients with a history of chronic cardiovascular disease and with a history of congestive heart failure have an 18.1% (95% CI: 17.2\u201318.7%) incidence of developing sepsis.\n                    <jats:italic>Conclusion<\/jats:italic>\n                    : The incidence of sepsis is high in this patient population. The novel associations of patients who have histories of congestive heart failure or previous cardiac surgery requiring MCS suggest an increased systemic inflammatory state exists that escalates the risk for developing sepsis. Further investigation into these background inflammatory conditions in patients requiring MCS is warranted.\n                  <\/jats:p>","DOI":"10.1051\/ject\/2025041","type":"journal-article","created":{"date-parts":[[2025,7,31]],"date-time":"2025-07-31T18:42:56Z","timestamp":1753987376000},"page":"225-228","source":"Crossref","is-referenced-by-count":0,"title":["Risk for sepsis during mechanical circulatory support"],"prefix":"10.1051","volume":"57","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-4248-3752","authenticated-orcid":false,"given":"Kelsey","family":"Gore","sequence":"first","affiliation":[{"name":"Department of Cardiovascular Perfusion and Extracorporeal Technology, Ochsner Health","place":["USA"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"suffix":"Jr.","given":"Dean","family":"Linder","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Perfusion and Extracorporeal Technology, Ochsner Health","place":["USA"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Juan Jos\u00e9 Martinez","family":"Duque","sequence":"additional","affiliation":[{"name":"CES University","place":["Colombia"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junxi","family":"Wang","sequence":"additional","affiliation":[{"name":"The University of Queensland Medical School","place":["Australia"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joshua","family":"Baguley","sequence":"additional","affiliation":[{"name":"The University of Queensland Medical School","place":["Australia"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cortland","family":"Kolesnikowicz","sequence":"additional","affiliation":[{"name":"The University of Queensland Medical School","place":["Australia"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4828-6437","authenticated-orcid":false,"given":"Shaun","family":"Yockelson","sequence":"additional","affiliation":[{"name":"Department of Critical Care Section, Anesthesiology & Perioperative Medicine, Ochsner Health","place":["USA"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Manila","family":"Singh","sequence":"additional","affiliation":[{"name":"Department of Critical Care Section, Anesthesiology & Perioperative Medicine, Ochsner Health","place":["USA"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Adrian Alexis","family":"Ruiz","sequence":"additional","affiliation":[{"name":"Department of Critical Care Section, Anesthesiology & Perioperative Medicine, Ochsner Health","place":["USA"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bobby D.","family":"Nossaman","sequence":"additional","affiliation":[{"name":"Department of Critical Care Section, Anesthesiology & Perioperative Medicine, Ochsner Health","place":["USA"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"250","published-online":{"date-parts":[[2025,12,17]]},"reference":[{"issue":"4","key":"R1","doi-asserted-by":"crossref","first-page":"1079","DOI":"10.3390\/microorganisms11041079","volume":"11","author":"Mornese Pinna","year":"2023","journal-title":"Microorganisms"},{"issue":"1","key":"R2","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1186\/s13613-022-01067-9","volume":"12","author":"Rajsic","year":"2022","journal-title":"Ann Intensive Care"},{"issue":"9","key":"R3","doi-asserted-by":"crossref","first-page":"e0203643","DOI":"10.1371\/journal.pone.0203643","volume":"13","author":"Allyn","year":"2018","journal-title":"PLoS One"},{"issue":"22","key":"R4","doi-asserted-by":"crossref","first-page":"6821","DOI":"10.3390\/jcm11226821","volume":"11","author":"Rajsic","year":"2022","journal-title":"J Clin Med"},{"issue":"Suppl 2","key":"R5","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1002\/ejhf.857","volume":"19","author":"Ostadal","year":"2017","journal-title":"Eur J Heart Fail"},{"issue":"7","key":"R6","doi-asserted-by":"crossref","first-page":"468","DOI":"10.1016\/j.medin.2012.08.009","volume":"37","author":"Pieri","year":"2013","journal-title":"Med Intensiva"},{"issue":"4","key":"R7","doi-asserted-by":"crossref","first-page":"693","DOI":"10.1016\/j.idc.2024.07.005","volume":"38","author":"Eichenberger","year":"2024","journal-title":"Infect Dis Clin North Am"},{"issue":"1","key":"R8","first-page":"e20221110","volume":"1","author":"Mihu","year":"2022","journal-title":"J Shock Hemodyn"},{"key":"R9","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1016\/j.pharmthera.2017.02.040","volume":"177","author":"Hattori","year":"2017","journal-title":"Pharmacol Ther"},{"issue":"12","key":"R10","doi-asserted-by":"crossref","first-page":"1633","DOI":"10.1093\/cid\/cis783","volume":"55","author":"Schmidt","year":"2012","journal-title":"Clin Infect Dis"},{"key":"R11","doi-asserted-by":"crossref","unstructured":"Izonin I, Tkachenko R. Chapter 6: Universal intraensemble method using nonlinear AI techniques for regression modeling of small medical data sets. In: Bhoi AK, de Albuquerque VHC, Srinivasu PN, Marques G, eds. Cognitive and soft computing techniques for the analysis of healthcare data. Academic Press; 2022; 123\u2013150. https:\/\/doi.org\/10.1016\/B978-0-323-85751-2.00002-5","DOI":"10.1016\/B978-0-323-85751-2.00002-5"},{"issue":"4","key":"R12","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1037\/a0016973","volume":"14","author":"Strobl","year":"2009","journal-title":"Psychol Methods"},{"issue":"3","key":"R13","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1097\/EC9.0000000000000033","volume":"2","author":"Skovran","year":"2022","journal-title":"Emerg Crit Care Med"},{"issue":"9","key":"R14","doi-asserted-by":"crossref","first-page":"989","DOI":"10.1177\/0885066620928299","volume":"36","author":"Jones","year":"2021","journal-title":"J Intensive Care Med"}],"container-title":["The Journal of ExtraCorporeal Technology"],"original-title":[],"link":[{"URL":"https:\/\/ject.edpsciences.org\/10.1051\/ject\/2025041\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,17]],"date-time":"2025-12-17T08:57:12Z","timestamp":1765961832000},"score":1,"resource":{"primary":{"URL":"https:\/\/ject.edpsciences.org\/10.1051\/ject\/2025041"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12]]},"references-count":14,"journal-issue":{"issue":"4"},"alternative-id":["ject250031"],"URL":"https:\/\/doi.org\/10.1051\/ject\/2025041","relation":{},"ISSN":["0022-1058","2969-8960"],"issn-type":[{"type":"print","value":"0022-1058"},{"type":"electronic","value":"2969-8960"}],"subject":[],"published":{"date-parts":[[2025,12]]}}}