{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T15:54:31Z","timestamp":1790870071537,"version":"4.1.0"},"reference-count":31,"publisher":"Walter de Gruyter GmbH","issue":"1","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,1,23]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec id=\"j_med-2026-1522_abs_001\">\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>Early identification of septic patients at high risk of mortality is crucial for improving outcomes. Renal function indicators such as blood urea nitrogen (BUN) and cystatin C (Cys C) have been individually associated with sepsis outcomes. However, the comparative prognostic value of these indicators and their ratio remained unclear.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"j_med-2026-1522_abs_002\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We conducted a retrospective cohort study in two hospitals in China. Associations between renal indicators and mortality were examined using multivariable logistic regression, restricted cubic spline modelling, and threshold analysis. Discrimination was assessed with receiver operating characteristic (ROC) curves, net reclassification improvement (NRI), and integrated discrimination improvement (IDI), evaluated both individually and in combination with the SOFA score. Clinical applicability was examined with calibration and decision curve analyses.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"j_med-2026-1522_abs_003\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A total of 1,039 patients were included in this study. After adjustment for covariates, multivariable logistic regression identified both BCR (OR 1.247, 95\u202f% CI 1.165\u20131.335, p&lt;0.001) and BUN (OR 1.047, 95\u202f% CI 1.029\u20131.065, p&lt;0.001) as independent predictors of in-hospital mortality among patients with sepsis, and these findings were replicated in the independent external cohort. In the exploration cohort, both BCR and BUN exhibited nonlinear associations with mortality risk. Incorporating BCR into the SOFA score resulted in the highest overall predictive performance (AUC 0.717) and the greatest net clinical benefit (0.106). Reclassification analyses further demonstrated that BCR achieved higher NRI and IDI values than BUN or Cys C, and that adding BCR to the SOFA score improved both NRI and IDI compared with SOFA\u00a0alone.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"j_med-2026-1522_abs_004\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>BCR and BUN were independently associated with in-hospital mortality in patients with sepsis. BCR showed modestly better prognostic performance than BUN or Cys C alone, and its integration with SOFA may provide supplementary risk-stratification information. However, BCR should not be considered a replacement for established severity scores, and further prospective validation is warranted.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1515\/med-2026-1522","type":"journal-article","created":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T14:58:50Z","timestamp":1790866730000},"source":"Crossref","is-referenced-by-count":0,"title":["Predictive performance of blood urea nitrogen, cystatin C, and their ratio for in-hospital mortality in sepsis: a Chinese two-center analysis"],"prefix":"10.1515","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-0135-1766","authenticated-orcid":false,"given":"Zhitao","family":"Zhong","sequence":"first","affiliation":[{"name":"Emergency Department , Zigong Fourth People\u2019s Hospital , Zigong , Sichuan , China"},{"name":"Institute of Medical Big Data, Zigong Academy of Artificial Intelligence and Big Data for Medical Science , Zigong , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-7113-611X","authenticated-orcid":false,"given":"Zhihua","family":"Xie","sequence":"additional","affiliation":[{"name":"Emergency Department , Fushun People\u2019s Hospital , Zigong , Sichuan , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-6622-2791","authenticated-orcid":false,"given":"Shihao","family":"Liu","sequence":"additional","affiliation":[{"name":"Emergency Department , Zigong Fourth People\u2019s Hospital , Zigong , Sichuan , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-2539-9014","authenticated-orcid":false,"given":"Lukai","family":"Lv","sequence":"additional","affiliation":[{"name":"Emergency Department , Zigong Fourth People\u2019s Hospital , Zigong , Sichuan , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-3169-7402","authenticated-orcid":false,"given":"Minyan","family":"Fan","sequence":"additional","affiliation":[{"name":"Emergency Department , Zigong Fourth People\u2019s Hospital , Zigong , Sichuan , China"},{"name":"Institute of Medical Big Data, Zigong Academy of Artificial Intelligence and Big Data for Medical Science , Zigong , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7233-4347","authenticated-orcid":false,"given":"Kefeng","family":"Li","sequence":"additional","affiliation":[{"name":"Faculty of Applied Sciences, Macao Polytechnic University , Macao SAR , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chao","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering , Sichuan University of Science and Engineering , Zigong , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9974-4867","authenticated-orcid":false,"given":"Guan","family":"Wang","sequence":"additional","affiliation":[{"name":"Innovation Center of Nursing Research, Nursing Key Laboratory of Sichuan Province, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University , Chengdu , Sichuan , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-8075-7399","authenticated-orcid":false,"given":"Li","family":"Ye","sequence":"additional","affiliation":[{"name":"Emergency Department , Fushun People\u2019s Hospital , Zigong , Sichuan , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1379-4295","authenticated-orcid":false,"given":"Ping","family":"Xu","sequence":"additional","affiliation":[{"name":"Emergency Department , Zigong Fourth People\u2019s Hospital , Zigong , Sichuan , China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"374","published-online":{"date-parts":[[2026,10,1]]},"reference":[{"key":"2026100114584866187_j_med-2026-1522_ref_001","doi-asserted-by":"crossref","unstructured":"Zhang, W, Shi, H, Peng, J. 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