{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T07:10:36Z","timestamp":1772521836890,"version":"3.50.1"},"reference-count":56,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T00:00:00Z","timestamp":1772496000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Cell. Infect. Microbiol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Enterococcal bloodstream infection (EBSI) carries high mortality in hematologic patients, yet no prognostic model tailored to this population exists.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We retrospectively analyzed 192 hematologic patients (\u226514 years) with EBSI admitted between 2014 and 2024. Clinical features, microbiology, treatment, and outcomes were assessed. Candidate predictors for 30-day mortality were selected by LASSO and entered into multivariable logistic regression. A simplified risk score was derived from regression coefficients and internally validated by bootstrap resampling.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The median patient age was 43 years, and acute leukemia was the predominant underlying disease (72.4%).\n                      <jats:italic>Enterococcus faecium<\/jats:italic>\n                      was the leading pathogen (71.4%), with low vancomycin resistance (1.6%). Most cases (71.9%) occurred as breakthrough infections, mainly during carbapenem therapy, and 72.9% met mucosal barrier injury laboratory-confirmed bloodstream infection criteria. The 14- and 30-day all-cause mortality rates were 13.5% and 22.4%, respectively. Independent predictors of 30-day mortality included age \u226550 years (aOR=2.29, p=0.038), severe graft-versus-host disease (aOR=6.06, p=0.003), septic shock (aOR=30.01, p&amp;lt;0.001). The final predictive model, incorporating these three factors along with pneumonia and high-risk hematologic disease, demonstrated optimal discrimination (AUROC 0.79, 95% CI 0.705\u20130.867) and calibration. A derived risk score stratified patients into low- (&amp;lt;2 points) and high-risk (\u22652 points) groups, with markedly different 30-day mortality (11.3%\n                      <jats:italic>vs<\/jats:italic>\n                      . 39.0%, P&amp;lt;0.001).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>In hematologic patients, EBSIs commonly arise as breakthrough infections despite broad-spectrum antibiotic coverage, most often associated with mucosal barrier injury. Our parsimonious risk score enables early identification of patients at high risk of 30-day mortality to guide timely interventions.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fcimb.2026.1762404","type":"journal-article","created":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T06:49:22Z","timestamp":1772520562000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Who is at risk? Clinical features and a predictive model for 30-day mortality in hematologic patients with enterococcal bloodstream infection"],"prefix":"10.3389","volume":"16","author":[{"given":"Nuobing","family":"Yang","sequence":"first","affiliation":[{"name":"State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College","place":["Tianjin, China"]},{"name":"Tianjin Institutes of Health Science","place":["Tianjin, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sisi","family":"Zhen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical 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