{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T05:59:41Z","timestamp":1780639181178,"version":"3.54.1"},"reference-count":36,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T00:00:00Z","timestamp":1780617600000},"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. Med."],"abstract":"\n Background<\/jats:title>\n Sepsis-associated acute kidney injury (SA-AKI) is one of the most common and serious complications of sepsis, characterized by high mortality, prolonged hospital stay, substantial healthcare burden, and progression to chronic kidney disease in approximately 30% of survivors. Early identification of high-risk patients and accurate prediction of their prognosis are of great significance for clinical decision-making. Currently, there is a lack of simple, intuitive, and externally validated individualized prognostic prediction tools in clinical practice.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n To develop and validate a nomogram model for predicting prognosis in patients with SA-AKI based on clinically accessible indicators.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n \n A retrospective case\u2013control study design was employed. Clinical data were collected from 200 patients with SA-AKI hospitalized at The First Affiliated Hospital of Xinjiang Medical University and The Fifth Affiliated Hospital of Xinjiang Medical University from December 2023 to March 2025. Data from The First Affiliated Hospital of Xinjiang Medical University served as the training set (\n n<\/jats:italic>\n \u202f=\u202f113), while data from The Fifth Affiliated Hospital of Xinjiang Medical University served as the external validation set (\n n<\/jats:italic>\n \u202f=\u202f87). Key predictive variables were selected using least absolute shrinkage and selection operator (LASSO) regression and subsequently incorporated into multivariate logistic regression analysis to identify independent influencing factors, based on which a nomogram prediction model was constructed. Discrimination of the model was assessed using the receiver operating characteristic curve, calibration was evaluated using the Hosmer\u2013Lemeshow test, and clinical utility was assessed using decision curve analysis.\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n LASSO regression identified four variables: age, Sequential Organ Failure Assessment (SOFA) score, creatinine, and serum potassium. Multivariate logistic regression analysis showed that all four variables were independent influencing factors for the prognosis of SA-AKI patients (all\n p<\/jats:italic>\n \u202f&lt;\u202f0.01). Higher levels of age, SOFA score, creatinine, and serum potassium were significantly associated with an unfavorable prognosis: age (OR\u202f=\u202f0.94, 95% CI: 0.91\u20130.97), SOFA score (OR\u202f=\u202f0.75, 95% CI: 0.67\u20130.84), creatinine (OR\u202f=\u202f0.60, 95% CI: 0.39\u20130.91), and serum potassium (OR\u202f=\u202f0.51, 95% CI: 0.32\u20130.80). The nomogram model achieved an AUC of 0.92 (95% CI: 0.86\u20130.97) in the training set, with a sensitivity of 0.82 and a specificity of 0.90; in the external validation set, the AUC was 0.85 (95% CI: 0.76\u20130.94), with a sensitivity of 0.90 and a specificity of 0.66. The Hosmer\u2013Lemeshow test indicated good calibration in both the training set (\n p<\/jats:italic>\n \u202f=\u202f0.41) and the validation set (\n p<\/jats:italic>\n \u202f=\u202f0.57), and decision curve analysis confirmed the clinical utility of the model.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusion<\/jats:title>\n Age, SOFA score, creatinine, and serum potassium are independent predictors of prognosis in SA-AKI patients. The nomogram model constructed based on these indicators demonstrates good discrimination, calibration, and clinical utility, and may serve as a valuable tool for early identification of high-risk patients with poor prognosis and for the development of individualized treatment strategies.<\/jats:p>\n <\/jats:sec>","DOI":"10.3389\/fmed.2026.1838034","type":"journal-article","created":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T05:01:31Z","timestamp":1780635691000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Nomogram analysis of factors associated with prognosis in patients with sepsis-associated acute kidney injury: a case-control study based on LASSO regression"],"prefix":"10.3389","volume":"13","author":[{"given":"Kabinuer","family":"Keyimu","sequence":"first","affiliation":[{"name":"Department of Geriatrics, The First Affiliated Hospital of Xinjiang Medical University","place":["Urumqi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Palida","family":"Abulizi","sequence":"additional","affiliation":[{"name":"Department of Geriatrics, The First Affiliated Hospital of Xinjiang Medical University","place":["Urumqi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julaiti","family":"Rouzhahong","sequence":"additional","affiliation":[{"name":"Department of Geriatrics, The First Affiliated Hospital of Xinjiang Medical University","place":["Urumqi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chen","family":"Wei","sequence":"additional","affiliation":[{"name":"Department of Geriatrics, The First Affiliated Hospital of Xinjiang Medical University","place":["Urumqi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,6,5]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"2043","DOI":"10.1007\/s00134-024-07694-z","article-title":"Sepsis: key insights, future directions, and immediate goals. A review and expert opinion","volume":"50","author":"Martin-Loeches","year":"2024","journal-title":"Intensive Care Med"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"6691","DOI":"10.3390\/jcm14196691","article-title":"The burden of sepsis and septic shock in the intensive care unit","volume":"14","author":"La Via","year":"2025","journal-title":"J Clin Med"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"200","DOI":"10.1016\/S0140-6736(19)32989-7","article-title":"Global, regional, and national sepsis incidence and mortality, 1990\u20132017: analysis for the global burden of disease study","volume":"395","author":"Rudd","year":"2020","journal-title":"Lancet"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"128","DOI":"10.1186\/s13054-025-05351-5","article-title":"Epidemiology of sepsis-associated acute kidney injury in the ICU with contemporary consensus definitions","volume":"29","author":"Takeuchi","year":"2025","journal-title":"Crit Care"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"100959","DOI":"10.1016\/j.xkme.2024.100959","article-title":"Sepsis-associated acute kidney disease incidence, trajectory, and outcomes","volume":"7","author":"Chiang","year":"2025","journal-title":"Kidney Med"},{"key":"ref6","doi-asserted-by":"publisher","first-page":"2700","DOI":"10.1038\/s41380-022-01528-4","article-title":"Clinical prediction models in psychiatry: a systematic review of two decades of progress and challenges","volume":"27","author":"Meehan","year":"2022","journal-title":"Mol Psychiatry"},{"key":"ref7","doi-asserted-by":"publisher","first-page":"144","DOI":"10.3390\/diagnostics14020144","article-title":"Machine learning-based predictive models for detection of cardiovascular diseases","volume":"14","author":"Ogunpola","year":"2024","journal-title":"Diagnostics"},{"key":"ref8","doi-asserted-by":"publisher","first-page":"1674673","DOI":"10.3389\/fimmu.2025.1674673","article-title":"Establishment and validation of the prediction model based on lymphocyte subsets for acute kidney injury in sepsis patients","volume":"16","author":"Wang","year":"2025","journal-title":"Front Immunol"},{"key":"ref9","doi-asserted-by":"publisher","first-page":"311","DOI":"10.1097\/SHK.0000000000002631","article-title":"Development and validation of a prediction model for septic shock\u2013associated acute kidney injury: a multicenter study using nomogram modeling","volume":"64","author":"Jiang","year":"2025","journal-title":"Shock"},{"key":"ref10","doi-asserted-by":"publisher","first-page":"5517872","DOI":"10.1155\/emmi\/5517872","article-title":"Development and validation of a prediction model for respiratory failure in patients with Sepsis-associated acute kidney injury (SA-AKI) within 48 hours of admission","volume":"2025","author":"Wang","year":"2025","journal-title":"Emerg Med Int"},{"key":"ref11","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1002\/bjs.9736","article-title":"Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement","volume":"102","author":"Collins","year":"2015","journal-title":"J Br Surg"},{"key":"ref12","doi-asserted-by":"publisher","first-page":"801","DOI":"10.1001\/jama.2016.0287","article-title":"The third international consensus definitions for sepsis and septic shock (Sepsis-3)","volume":"315","author":"Singer","year":"2016","journal-title":"JAMA"},{"key":"ref13","first-page":"1","article-title":"Kidney disease: improving global outcomes (KDIGO) acute kidney injury work group. KDIGO clinical practice guideline for acute kidney injury","volume":"2","author":"Kellum","year":"2012","journal-title":"Kidney Int Suppl"},{"key":"ref14","doi-asserted-by":"publisher","first-page":"m441","DOI":"10.1136\/bmj.m441","article-title":"Calculating the sample size required for developing a clinical prediction model","volume":"368","author":"Riley","year":"2020","journal-title":"BMJ"},{"key":"ref15","doi-asserted-by":"publisher","first-page":"769","DOI":"10.3390\/jpm14070769","article-title":"Repeated sieving for prediction model building with high-dimensional data","volume":"14","author":"Liu","year":"2024","journal-title":"J Pers Med"},{"key":"ref16","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1111\/j.2517-6161.1996.tb02080.x","article-title":"Regression shrinkage and selection via the lasso","volume":"58","author":"Tibshirani","year":"1996","journal-title":"J R Stat Soc Series B Stat Methodol"},{"key":"ref17","doi-asserted-by":"publisher","first-page":"656","DOI":"10.1186\/s12882-025-04630-1","article-title":"Analysis of prognostic risk factors in critically ill elderly patients with sepsis-associated acute kidney injury","volume":"26","author":"Zeng","year":"2025","journal-title":"BMC Nephrol"},{"key":"ref18","doi-asserted-by":"publisher","first-page":"318","DOI":"10.1186\/s12882-020-01974-8","article-title":"Rates, predictors, and mortality of sepsis-associated acute kidney injury: a systematic review and meta-analysis","volume":"21","author":"Liu","year":"2020","journal-title":"BMC Nephrol"},{"key":"ref19","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1159\/000525932","article-title":"Association of baseline renal function with mortality in patients with sepsis requiring continuous renal replacement therapy for acute kidney injury: a single-center retrospective study","volume":"52","author":"Fukuda","year":"2023","journal-title":"Blood Purif"},{"key":"ref20","doi-asserted-by":"publisher","first-page":"385","DOI":"10.1186\/s13054-022-04266-9","article-title":"Association between age and the host response in critically ill patients with sepsis","volume":"26","author":"Michels","year":"2022","journal-title":"Crit Care"},{"key":"ref21","doi-asserted-by":"publisher","first-page":"665","DOI":"10.25259\/IJMR_2037_2024","article-title":"Prevalence & risk factors of multi-morbidity in critically ill patients with sepsis-associated acute kidney injury (SA-AKI)","volume":"161","author":"Malla","year":"2025","journal-title":"Indian J Med Res"},{"key":"ref22","doi-asserted-by":"publisher","first-page":"390","DOI":"10.1001\/jama.2024.8772","article-title":"Acetaminophen for prevention and treatment of organ dysfunction in critically ill patients with sepsis: the ASTER randomized clinical trial","volume":"332","author":"Ware","year":"2024","journal-title":"JAMA"},{"key":"ref23","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1186\/s12967-022-03364-0","article-title":"Machine learning for the prediction of acute kidney injury in patients with sepsis","volume":"20","author":"Yue","year":"2022","journal-title":"J Transl Med"},{"key":"ref24","doi-asserted-by":"publisher","first-page":"434","DOI":"10.3390\/medicina60030434","article-title":"Sepsis-associated acute kidney injury: where are we now?","volume":"60","author":"Kounatidis","year":"2024","journal-title":"Medicina"},{"key":"ref25","doi-asserted-by":"publisher","first-page":"e0332525","DOI":"10.1371\/journal.pone.0332525","article-title":"Predictive value of SOFA, PCT, lactate, qSOFA and their combinations for mortality in patients with sepsis: a systematic review and meta-analysis","volume":"20","author":"Lu","year":"2025","journal-title":"PLoS One"},{"key":"ref26","doi-asserted-by":"publisher","first-page":"k4891","DOI":"10.1136\/bmj.k4891","article-title":"Sepsis associated acute kidney injury","volume":"364","author":"Poston","year":"2019","journal-title":"BMJ"},{"key":"ref27","doi-asserted-by":"publisher","first-page":"707","DOI":"10.1007\/BF01709751","article-title":"The SOFA (Sepsis-related organ failure assessment) score to describe organ dysfunction\/failure: on behalf of the working group on Sepsis-related problems of the European Society of Intensive Care Medicine (see contributors to the project in the appendix)","volume":"22","author":"Vincent","year":"1996","journal-title":"Intensive Care Med"},{"key":"ref28","doi-asserted-by":"publisher","first-page":"327","DOI":"10.15441\/ceem.24.330","article-title":"Assessment of organ failure in sepsis patients in the emergency department: clinical evaluation, sequential organ failure assessment (SOFA) score, and future 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Microbiol"},{"key":"ref31","doi-asserted-by":"publisher","first-page":"600","DOI":"10.4103\/ijn.ijn_519_21","article-title":"The utility of the creatinine excretion to production ratio and the plasma creatinine and cystatin C based kinetic estimates of glomerular filtration rates in critically ill patients with Sepsis","volume":"32","author":"Ralib","year":"2022","journal-title":"Indian J Nephrol"},{"key":"ref32","doi-asserted-by":"publisher","first-page":"9485","DOI":"10.2147\/JIR.S486596","article-title":"CITED2 mediates metabolic reprogramming in renal tubular epithelial cells via the AKT signaling pathway to induce Sepsis-associated acute kidney injury","volume":"17","author":"Deng","year":"2024","journal-title":"J Inflamm Res"},{"key":"ref33","doi-asserted-by":"publisher","first-page":"253","DOI":"10.1159\/000520698","article-title":"Role of mitochondrial therapy for ischemic-reperfusion injury and acute kidney injury","volume":"146","author":"Pabla","year":"2022","journal-title":"Nephron"},{"key":"ref34","doi-asserted-by":"publisher","first-page":"e0309764","DOI":"10.1371\/journal.pone.0309764","article-title":"Association between admission baseline blood potassium levels and all-cause mortality in patients with acute kidney injury combined with sepsis: a retrospective cohort study","volume":"19","author":"Guo","year":"2024","journal-title":"PLoS One"},{"key":"ref35","first-page":"233","article-title":"Electrolyte disorders and arrhythmogenesis","volume":"18","author":"El-Sherif","year":"2011","journal-title":"Cardiol J"},{"key":"ref36","doi-asserted-by":"publisher","first-page":"421","DOI":"10.1093\/europace\/eup005","article-title":"Serum potassium and arrhythmias","volume":"11","author":"Zaza","year":"2009","journal-title":"Europace"}],"container-title":["Frontiers in 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