{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T04:27:53Z","timestamp":1787027273908,"version":"build-2736575974"},"reference-count":26,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T00:00:00Z","timestamp":1783900800000},"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. Public Health"],"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To investigate the association between multidrug-resistant organisms (MDROs) colonization and subsequent infection in intensive care unit (ICU) patients.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      A retrospective analysis was conducted on 388 ICU patients admitted to the Second Xiangya Hospital between January 2023 and December 2025. Patients were divided into infection (\n                      <jats:italic>n<\/jats:italic>\n                      \u202f=\u202f47) and non-infection (\n                      <jats:italic>n<\/jats:italic>\n                      \u202f=\u202f341) groups according to whether they developed an MDROs infection within 28\u202fdays of ICU admission. Clinical data were collected, and univariate and multivariate logistic regression analyses were performed to identify the factors associated with MDROs infection. A nomogram model was constructed.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Among the 388 ICU patients, 99 (25.52, 95%CI: 21.44\u201330.08%) were colonized by MDROs. A total of 108 MDROs isolates were detected, including 29 strains of ESBL-producing\n                      <jats:italic>Escherichia coli<\/jats:italic>\n                      (ESBL-EC, 26.61%), 54 strains of ESBL-producing\n                      <jats:italic>Klebsiella pneumoniae<\/jats:italic>\n                      (ESBL-KP, 49.54%), 16 strains of methicillin-resistant\n                      <jats:italic>Staphylococcus aureus<\/jats:italic>\n                      (MRSA, 14.68%), and 9 strains of methicillin-resistant\n                      <jats:italic>Staphylococcus epidermidis<\/jats:italic>\n                      (MRSE, 9.17%). Logistic regression analysis showed that diabetes (OR\u202f=\u202f2.523, 95% CI: 1.095\u20135.814), MDROs colonization (OR\u202f=\u202f5.155, 95% CI: 2.302\u201311.544), APACHE II score (OR\u202f=\u202f2.043, 95% CI: 1.597\u20132.614), and albumin level (OR\u202f=\u202f0.778, 95% CI: 0.679\u20130.893) were independent factors associated with MDROs infection in ICU patients. When these variables were incorporated into a logistic regression nomogram, the AUC values for the training and validation sets were 0.894 (95% CI: 0.832\u20130.957) and 0.896 (95% CI: 0.828\u20130.964), respectively.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Diabetes, MDROs colonization, high APACHE II scores, and low albumin levels are factors associated with MDROs infection in ICU patients. The nomogram constructed based on these factors may facilitate the early identification of patients at high risk for MDROs infection and provide a basis for individualized treatment strategies.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpubh.2026.1863334","type":"journal-article","created":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T13:18:49Z","timestamp":1784035129000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Association between MDROs colonization and subsequent infections in ICU patients: a retrospective cohort study"],"prefix":"10.3389","volume":"14","author":[{"given":"Shanbi","family":"Cheng","sequence":"first","affiliation":[{"name":"Department of Hospital Infection Control, The Second Xiangya Hospital Central South University","place":["Changsha, Hunan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dejun","family":"Tong","sequence":"additional","affiliation":[{"name":"Department of Hospital Infection Control, The Second Xiangya Hospital Central South University","place":["Changsha, Hunan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qianqian","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Emergency, The Second Xiangya Hospital, Central South University","place":["Changsha, Hunan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bing","family":"Xiao","sequence":"additional","affiliation":[{"name":"Department of Emergency, The Second Xiangya Hospital, Central South University","place":["Changsha, Hunan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yudong","family":"Zhang","sequence":"additional","affiliation":[{"name":"Guilin Hospital of the Second Xiangya Hospital, Central South University","place":["Changsha, Hunan, China"]},{"name":"Simulation Medicine Center, The Second Xiangya Hospital, Central South University","place":["Changsha, Hunan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yibo","family":"Gong","sequence":"additional","affiliation":[{"name":"Department of Cardiac Surgery, The Second Xiangya Hospital Central South University","place":["Changsha, Hunan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,7,13]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1186\/s13756-024-01428-y","article-title":"Development and validation of machine learning models to predict MDRO colonization or infection on ICU admission by using electronic health record data","volume":"13","author":"Li","year":"2024","journal-title":"Antimicrob Resist Infect 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