{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T20:16:44Z","timestamp":1783714604293,"version":"3.55.0"},"reference-count":48,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,8,8]],"date-time":"2025-08-08T00:00:00Z","timestamp":1754611200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,8,8]],"date-time":"2025-08-08T00:00:00Z","timestamp":1754611200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"name":"Zhejiang Yangtze River Delta Health Research Fund Project","award":["2022CSJ-A002"],"award-info":[{"award-number":["2022CSJ-A002"]}]},{"name":"Zhejiang Yangtze River Delta Health Research Fund Project","award":["2022CSJ-A003"],"award-info":[{"award-number":["2022CSJ-A003"]}]},{"name":"Zhejiang Provincial Health Science and Technology Plan","award":["2022KY063"],"award-info":[{"award-number":["2022KY063"]}]},{"name":"Zhejiang Provincial People\u2019s Hospital Seed Fund","award":["C-2022-YYQD26"],"award-info":[{"award-number":["C-2022-YYQD26"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Med Inform Decis Mak"],"DOI":"10.1186\/s12911-025-03142-0","type":"journal-article","created":{"date-parts":[[2025,8,8]],"date-time":"2025-08-08T08:11:13Z","timestamp":1754640673000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Development and validation of interpretable machine learning models for predicting AKI risk in patients treated with PD-1\/PD-L1: a retrospective study"],"prefix":"10.1186","volume":"25","author":[{"given":"Wentong","family":"Liu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaiyue","family":"Ji","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qianwen","family":"Tang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weiqi","family":"Xia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lina","family":"Shao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiana","family":"Shi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yukun","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ping","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaolan","family":"Ye","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,8,8]]},"reference":[{"key":"3142_CR1","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1146\/annurev-pathol-042020-042741","volume":"16","author":"S Bagchi","year":"2021","unstructured":"Bagchi S, Yuan R, Engleman EG. Immune checkpoint inhibitors for the treatment of cancer: clinical impact and mechanisms of response and resistance. Annu Rev Pathol. 2021;16:223\u201349. https:\/\/doi.org\/10.1146\/annurev-pathol-042020-042741.","journal-title":"Annu Rev Pathol"},{"key":"3142_CR2","doi-asserted-by":"publisher","first-page":"1002","DOI":"10.1016\/S0140-6736(21)01206-X","volume":"398","author":"MS Carlino","year":"2021","unstructured":"Carlino MS, Larkin J, Long GV. Immune checkpoint inhibitors in melanoma. Lancet. 2021;398:1002\u201314. https:\/\/doi.org\/10.1016\/S0140-6736(21)01206-X.","journal-title":"Lancet"},{"key":"3142_CR3","doi-asserted-by":"publisher","DOI":"10.1016\/j.kint.2024.09.017","author":"SM Herrmann","year":"2024","unstructured":"Herrmann SM, et al. Diagnosis and management of immune checkpoint inhibitor-associated nephrotoxicity: a position statement from the American society of Onco-nephrology. Kidney Int. 2024. https:\/\/doi.org\/10.1016\/j.kint.2024.09.017.","journal-title":"Kidney Int"},{"key":"3142_CR4","doi-asserted-by":"publisher","first-page":"ITC66","DOI":"10.7326\/AITC201711070","volume":"167","author":"AS Levey","year":"2017","unstructured":"Levey AS, James MT. Acute kidney injury. Ann Intern Med. 2017;167:ITC66\u201380. https:\/\/doi.org\/10.7326\/AITC201711070.","journal-title":"Ann Intern Med"},{"key":"3142_CR5","doi-asserted-by":"publisher","first-page":"3365","DOI":"10.1681\/ASN.2004090740","volume":"16","author":"GM Chertow","year":"2005","unstructured":"Chertow GM, Burdick E, Honour M, Bonventre JV, Bates DW. Acute kidney injury, mortality, length of stay, and costs in hospitalized patients. J Am Soc Nephrol. 2005;16:3365\u201370. https:\/\/doi.org\/10.1681\/ASN.2004090740.","journal-title":"J Am Soc Nephrol"},{"key":"3142_CR6","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1016\/0002-9343(83)90618-6","volume":"74","author":"SH Hou","year":"1983","unstructured":"Hou SH, Bushinsky DA, Wish JB, Cohen JJ, Harrington JT. Hospital-acquired renal insufficiency: a prospective study. Am J Med. 1983;74:243\u20138. https:\/\/doi.org\/10.1016\/0002-9343(83)90618-6.","journal-title":"Am J Med"},{"key":"3142_CR7","doi-asserted-by":"publisher","first-page":"930","DOI":"10.1053\/ajkd.2002.32766","volume":"39","author":"K Nash","year":"2002","unstructured":"Nash K, Hafeez A, Hou S. Hospital-acquired renal insufficiency. Am J Kidney Dis. 2002;39:930\u20136. https:\/\/doi.org\/10.1053\/ajkd.2002.32766.","journal-title":"Am J Kidney Dis"},{"key":"3142_CR8","doi-asserted-by":"publisher","first-page":"2552","DOI":"10.1097\/CCM.0b013e3181a5906f","volume":"37","author":"CV Thakar","year":"2009","unstructured":"Thakar CV, Christianson A, Freyberg R, Almenoff P, Render ML. Incidence and outcomes of acute kidney injury in intensive care units: a veterans administration study. Crit Care Med. 2009;37:2552\u20138. https:\/\/doi.org\/10.1097\/CCM.0b013e3181a5906f.","journal-title":"Crit Care Med"},{"issue":"1","key":"3142_CR9","doi-asserted-by":"publisher","first-page":"8","DOI":"10.17305\/bjbms.2010.2639","volume":"10","author":"P Kes","year":"2010","unstructured":"Kes P. Basic jukic, N. Acute kidney injury in the intensive care unit. Bosn J Basic Med Sci. 2010;10(1):8\u201312. https:\/\/doi.org\/10.17305\/bjbms.2010.2639.","journal-title":"Bosn J Basic Med Sci"},{"key":"3142_CR10","doi-asserted-by":"publisher","first-page":"187","DOI":"10.2215\/CJN.03200314","volume":"10","author":"FE Sileanu","year":"2015","unstructured":"Sileanu FE, et al. AKI in low-risk versus high-risk patients in intensive care. Clin J Am Soc Nephrol. 2015;10:187\u201396. https:\/\/doi.org\/10.2215\/CJN.03200314.","journal-title":"Clin J Am Soc Nephrol"},{"key":"3142_CR11","doi-asserted-by":"publisher","first-page":"1411","DOI":"10.1007\/s00134-015-3934-7","volume":"41","author":"EA Hoste","year":"2015","unstructured":"Hoste EA, et al. Epidemiology of acute kidney injury in critically ill patients: the multinational AKI-EPI study. Intensive Care Med. 2015;41:1411\u201323. https:\/\/doi.org\/10.1007\/s00134-015-3934-7.","journal-title":"Intensive Care Med"},{"key":"3142_CR12","doi-asserted-by":"publisher","first-page":"2238823","DOI":"10.1080\/0886022X.2023.2238823","volume":"45","author":"Q Lou","year":"2023","unstructured":"Lou Q, et al. Acute kidney injury in patients with cancer receiving anti-PD-1\/PD-L1 antibodies: incidence, risk factors, and prognosis. Ren Fail. 2023;45:2238823. https:\/\/doi.org\/10.1080\/0886022X.2023.2238823.","journal-title":"Ren Fail"},{"key":"3142_CR13","doi-asserted-by":"publisher","first-page":"1700","DOI":"10.1016\/j.ekir.2020.07.011","volume":"5","author":"H Seethapathy","year":"2020","unstructured":"Seethapathy H, et al. Incidence and clinical features of Immune-Related acute kidney injury in patients receiving programmed cell death Ligand-1 inhibitors. Kidney Int Rep. 2020;5:1700\u20135. https:\/\/doi.org\/10.1016\/j.ekir.2020.07.011.","journal-title":"Kidney Int Rep"},{"key":"3142_CR14","doi-asserted-by":"publisher","first-page":"18752","DOI":"10.1038\/s41598-022-21912-y","volume":"12","author":"MS Ji","year":"2022","unstructured":"Ji MS, et al. Incidence, risk factors and prognosis of acute kidney injury in patients treated with immune checkpoint inhibitors: a retrospective study. Sci Rep. 2022;12:18752. https:\/\/doi.org\/10.1038\/s41598-022-21912-y.","journal-title":"Sci Rep"},{"key":"3142_CR15","doi-asserted-by":"publisher","first-page":"1692","DOI":"10.2215\/CJN.00990119","volume":"14","author":"H Seethapathy","year":"2019","unstructured":"Seethapathy H, et al. The incidence, causes, and risk factors of acute kidney injury in patients receiving immune checkpoint inhibitors. Clin J Am Soc Nephrol. 2019;14:1692\u2013700. https:\/\/doi.org\/10.2215\/CJN.00990119.","journal-title":"Clin J Am Soc Nephrol"},{"key":"3142_CR16","doi-asserted-by":"publisher","unstructured":"Meraz-Munoz A, et al. Acute kidney injury associated with immune checkpoint inhibitor therapy: incidence, risk factors and outcomes. J Immunother Cancer. 2020;8. https:\/\/doi.org\/10.1136\/jitc-2019-000467.","DOI":"10.1136\/jitc-2019-000467"},{"key":"3142_CR17","doi-asserted-by":"publisher","first-page":"e0252978","DOI":"10.1371\/journal.pone.0252978","volume":"16","author":"MS Koks","year":"2021","unstructured":"Koks MS, et al. Immune checkpoint inhibitor-associated acute kidney injury and mortality: an observational study. PLoS ONE. 2021;16:e0252978. https:\/\/doi.org\/10.1371\/journal.pone.0252978.","journal-title":"PLoS ONE"},{"key":"3142_CR18","doi-asserted-by":"publisher","first-page":"887","DOI":"10.1093\/ndt\/gfab034","volume":"37","author":"C Garcia-Carro","year":"2022","unstructured":"Garcia-Carro C, et al. Acute kidney injury as a risk factor for mortality in oncological patients receiving checkpoint inhibitors. Nephrol Dial Transpl. 2022;37:887\u201394. https:\/\/doi.org\/10.1093\/ndt\/gfab034.","journal-title":"Nephrol Dial Transpl"},{"key":"3142_CR19","doi-asserted-by":"publisher","first-page":"479","DOI":"10.1007\/s10157-020-02008-1","volume":"25","author":"Y Shimamura","year":"2021","unstructured":"Shimamura Y, et al. Incidence and risk factors of acute kidney injury, and its effect on mortality among Japanese patients receiving immune check point inhibitors: a single-center observational study. Clin Exp Nephrol. 2021;25:479\u201387. https:\/\/doi.org\/10.1007\/s10157-020-02008-1.","journal-title":"Clin Exp Nephrol"},{"key":"3142_CR20","doi-asserted-by":"publisher","unstructured":"Lumlertgul N, et al. Acute kidney injury in patients receiving immune checkpoint inhibitors: a retrospective real-world study. Eur J Cancer. 2023;191. https:\/\/doi.org\/10.1016\/j.ejca.2023.112967.","DOI":"10.1016\/j.ejca.2023.112967"},{"key":"3142_CR21","doi-asserted-by":"publisher","first-page":"sfad292","DOI":"10.1093\/ckj\/sfad292","volume":"17","author":"JJ Chen","year":"2024","unstructured":"Chen JJ, et al. All-cause and immune checkpoint inhibitor-associated acute kidney injury in immune checkpoint inhibitor users: a meta-analysis of occurrence rate, risk factors and mortality. Clin Kidney J. 2024;17:sfad292. https:\/\/doi.org\/10.1093\/ckj\/sfad292.","journal-title":"Clin Kidney J"},{"key":"3142_CR22","doi-asserted-by":"publisher","first-page":"1834","DOI":"10.1093\/ckj\/sfad109","volume":"16","author":"J Miao","year":"2023","unstructured":"Miao J, Herrmann SM. Immune checkpoint inhibitors and their interaction with proton pump inhibitors-related interstitial nephritis. Clin Kidney J. 2023;16:1834\u201344. https:\/\/doi.org\/10.1093\/ckj\/sfad109.","journal-title":"Clin Kidney J"},{"key":"3142_CR23","doi-asserted-by":"publisher","first-page":"e0298673","DOI":"10.1371\/journal.pone.0298673","volume":"19","author":"M Sakuragi","year":"2024","unstructured":"Sakuragi M, et al. Interpretable machine learning-based individual analysis of acute kidney injury in immune checkpoint inhibitor therapy. PLoS ONE. 2024;19:e0298673. https:\/\/doi.org\/10.1371\/journal.pone.0298673.","journal-title":"PLoS ONE"},{"key":"3142_CR24","doi-asserted-by":"publisher","first-page":"2326186","DOI":"10.1080\/0886022X.2024.2326186","volume":"46","author":"P Zhou","year":"2024","unstructured":"Zhou P, et al. Acute kidney injury in patients treated with immune checkpoint inhibitors: a single-center retrospective study. Ren Fail. 2024;46:2326186. https:\/\/doi.org\/10.1080\/0886022X.2024.2326186.","journal-title":"Ren Fail"},{"key":"3142_CR25","doi-asserted-by":"publisher","first-page":"1737","DOI":"10.1056\/NEJMoa2102953","volume":"385","author":"LA Inker","year":"2021","unstructured":"Inker LA, et al. New Creatinine- and Cystatin C-Based equations to estimate GFR without race. N Engl J Med. 2021;385:1737\u201349. https:\/\/doi.org\/10.1056\/NEJMoa2102953.","journal-title":"N Engl J Med"},{"key":"3142_CR26","doi-asserted-by":"publisher","first-page":"102409","DOI":"10.1016\/j.eclinm.2023.102409","volume":"68","author":"J Hu","year":"2024","unstructured":"Hu J, et al. Identification and validation of an explainable prediction model of acute kidney injury with prognostic implications in critically ill children: a prospective multicenter cohort study. EClinicalMedicine. 2024;68:102409. https:\/\/doi.org\/10.1016\/j.eclinm.2023.102409.","journal-title":"EClinicalMedicine"},{"key":"3142_CR27","doi-asserted-by":"publisher","first-page":"649","DOI":"10.1053\/j.ajkd.2013.02.349","volume":"61","author":"PM Palevsky","year":"2013","unstructured":"Palevsky PM, et al. KDOQI US commentary on the 2012 KDIGO clinical practice guideline for acute kidney injury. Am J Kidney Dis. 2013;61:649\u201372. https:\/\/doi.org\/10.1053\/j.ajkd.2013.02.349.","journal-title":"Am J Kidney Dis"},{"key":"3142_CR28","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1056\/NEJMoa1611391","volume":"376","author":"A Kaddourah","year":"2017","unstructured":"Kaddourah A, Basu RK, Bagshaw SM, Goldstein SL, Investigators A. Epidemiology of acute kidney injury in critically ill children and young adults. N Engl J Med. 2017;376:11\u201320. https:\/\/doi.org\/10.1056\/NEJMoa1611391.","journal-title":"N Engl J Med"},{"key":"3142_CR29","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1177\/1536867X0900900101","volume":"9","author":"M Pepe","year":"2009","unstructured":"Pepe M, Longton G, Janes H. Estimation and comparison of receiver operating characteristic curves. Stata J. 2009;9:1.","journal-title":"Stata J"},{"key":"3142_CR30","doi-asserted-by":"publisher","first-page":"837","DOI":"10.2307\/2531595","volume":"44","author":"ER DeLong","year":"1988","unstructured":"DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988;44:837\u201345.","journal-title":"Biometrics"},{"key":"3142_CR31","doi-asserted-by":"publisher","first-page":"114","DOI":"10.1097\/EDE.0000000000000018","volume":"25","author":"KF Kerr","year":"2014","unstructured":"Kerr KF, et al. Net reclassification indices for evaluating risk prediction instruments: a critical review. Epidemiology. 2014;25:114\u201321. https:\/\/doi.org\/10.1097\/EDE.0000000000000018.","journal-title":"Epidemiology"},{"key":"3142_CR32","doi-asserted-by":"publisher","first-page":"128","DOI":"10.1097\/EDE.0b013e3181c30fb2","volume":"21","author":"EW Steyerberg","year":"2010","unstructured":"Steyerberg EW, et al. Assessing the performance of prediction models: a framework for traditional and novel measures. Epidemiology. 2010;21:128\u201338. https:\/\/doi.org\/10.1097\/EDE.0b013e3181c30fb2.","journal-title":"Epidemiology"},{"key":"3142_CR33","unstructured":"Lundberg SM, Lee S-I. In Proceedings of the 31st International Conference on Neural Information Processing Systems. Long Beach, California, USA. Curran Associates Inc.; 2017. p. 4768\u201377."},{"key":"3142_CR34","doi-asserted-by":"publisher","first-page":"1262","DOI":"10.34067\/KID.0000000000000528","volume":"5","author":"C Yamawaki","year":"2024","unstructured":"Yamawaki C, et al. Association between proton pump inhibitors, immune checkpoint inhibitors, and acute kidney injury: A nested Case-Control study. Kidney360. 2024;5:1262\u20139. https:\/\/doi.org\/10.34067\/KID.0000000000000528.","journal-title":"Kidney360"},{"key":"3142_CR35","doi-asserted-by":"publisher","first-page":"439","DOI":"10.1159\/000538274","volume":"55","author":"A Mohan","year":"2024","unstructured":"Mohan A, et al. Association of proton pump inhibitor use and immune checkpoint inhibitor-Mediated acute kidney injury: A Meta-Analysis and a review of related outcomes. Am J Nephrol. 2024;55:439\u201349. https:\/\/doi.org\/10.1159\/000538274.","journal-title":"Am J Nephrol"},{"key":"3142_CR36","doi-asserted-by":"publisher","first-page":"92","DOI":"10.1016\/j.cell.2020.03.022","volume":"181","author":"J Goecks","year":"2020","unstructured":"Goecks J, Jalili V, Heiser LM, Gray JW. How machine learning will transform biomedicine. Cell. 2020;181:92\u2013101. https:\/\/doi.org\/10.1016\/j.cell.2020.03.022.","journal-title":"Cell"},{"key":"3142_CR37","doi-asserted-by":"publisher","first-page":"e213460","DOI":"10.1001\/jamanetworkopen.2021.3460","volume":"4","author":"RW Moehring","year":"2021","unstructured":"Moehring RW, et al. Development of a machine learning model using electronic health record data to identify antibiotic use among hospitalized patients. JAMA Netw Open. 2021;4:e213460. https:\/\/doi.org\/10.1001\/jamanetworkopen.2021.3460.","journal-title":"JAMA Netw Open"},{"key":"3142_CR38","doi-asserted-by":"publisher","first-page":"e2023547","DOI":"10.1001\/jamanetworkopen.2020.23547","volume":"3","author":"BA Goldstein","year":"2020","unstructured":"Goldstein BA, et al. Development and performance of a clinical decision support tool to inform resource utilization for elective operations. JAMA Netw Open. 2020;3:e2023547. https:\/\/doi.org\/10.1001\/jamanetworkopen.2020.23547.","journal-title":"JAMA Netw Open"},{"key":"3142_CR39","doi-asserted-by":"publisher","first-page":"101431","DOI":"10.1016\/j.eclinm.2022.101431","volume":"48","author":"X Zhang","year":"2022","unstructured":"Zhang X, et al. A novel machine learning model and a public online prediction platform for prediction of post-ERCP-cholecystitis (PEC). EClinicalMedicine. 2022;48:101431. https:\/\/doi.org\/10.1016\/j.eclinm.2022.101431.","journal-title":"EClinicalMedicine"},{"key":"3142_CR40","doi-asserted-by":"publisher","first-page":"sfae426","DOI":"10.1093\/ckj\/sfae426","volume":"18","author":"T Takeuchi","year":"2025","unstructured":"Takeuchi T, et al. Epidemiological risk factors for acute kidney injury outcomes in hospitalized adult patients: a multicenter cohort study. Clin Kidney J. 2025;18:sfae426. https:\/\/doi.org\/10.1093\/ckj\/sfae426.","journal-title":"Clin Kidney J"},{"key":"3142_CR41","doi-asserted-by":"publisher","first-page":"5592","DOI":"10.1038\/s41598-024-56335-4","volume":"14","author":"X She","year":"2024","unstructured":"She X, et al. Electrolyte disorders induced by six multikinase inhibitors therapy for renal cell carcinoma: a large-scale pharmacovigilance analysis. Sci Rep. 2024;14:5592. https:\/\/doi.org\/10.1038\/s41598-024-56335-4.","journal-title":"Sci Rep"},{"key":"3142_CR42","doi-asserted-by":"publisher","first-page":"1121","DOI":"10.1007\/s40520-019-01196-5","volume":"32","author":"Q Li","year":"2020","unstructured":"Li Q, Zhao M, Zhou F. Hospital-acquired acute kidney injury in very elderly men: clinical characteristics and short-term outcomes. Aging Clin Exp Res. 2020;32:1121\u20138. https:\/\/doi.org\/10.1007\/s40520-019-01196-5.","journal-title":"Aging Clin Exp Res"},{"key":"3142_CR43","doi-asserted-by":"publisher","first-page":"2349113","DOI":"10.1080\/0886022X.2024.2349113","volume":"46","author":"H Lin","year":"2024","unstructured":"Lin H, Guo X, Wang M, Su X, Qiao X. Risk factors and early prediction of cardiorenal syndrome type 3 among acute kidney injury patients: a cohort study. Ren Fail. 2024;46:2349113. https:\/\/doi.org\/10.1080\/0886022X.2024.2349113.","journal-title":"Ren Fail"},{"key":"3142_CR44","doi-asserted-by":"publisher","first-page":"m3919","DOI":"10.1136\/bmj.m3919","volume":"371","author":"Y Li","year":"2020","unstructured":"Li Y, Sperrin M, Ashcroft DM, van Staa TP. Consistency of variety of machine learning and statistical models in predicting clinical risks of individual patients: longitudinal cohort study using cardiovascular disease as exemplar. BMJ. 2020;371:m3919. https:\/\/doi.org\/10.1136\/bmj.m3919.","journal-title":"BMJ"},{"key":"3142_CR45","doi-asserted-by":"publisher","first-page":"801","DOI":"10.1016\/S2213-2600(18)30425-9","volume":"6","author":"The Lancet Respiratory","year":"2018","unstructured":"The Lancet Respiratory. Opening the black box of machine learning. Lancet Respir Med. 2018;6:801. https:\/\/doi.org\/10.1016\/S2213-2600(18)30425-9.","journal-title":"Lancet Respir Med"},{"key":"3142_CR46","doi-asserted-by":"publisher","first-page":"641","DOI":"10.2147\/CIA.S162764","volume":"13","author":"ZB You","year":"2018","unstructured":"You ZB, et al. Association of prealbumin levels with contrast-induced acute kidney injury in elderly patients with elective percutaneous coronary intervention. Clin Interv Aging. 2018;13:641\u20139. https:\/\/doi.org\/10.2147\/CIA.S162764.","journal-title":"Clin Interv Aging"},{"key":"3142_CR47","doi-asserted-by":"publisher","first-page":"1193","DOI":"10.1159\/000485866","volume":"42","author":"Y Hu","year":"2017","unstructured":"Hu Y, Liu H, Fu S, Wan J, Li X. Red blood cell distribution width is an independent predictor of AKI and mortality in patients in the coronary care unit. Kidney Blood Press Res. 2017;42:1193\u2013204. https:\/\/doi.org\/10.1159\/000485866.","journal-title":"Kidney Blood Press Res"},{"key":"3142_CR48","doi-asserted-by":"publisher","first-page":"11870","DOI":"10.1038\/s41598-018-19881-2","volume":"8","author":"CT Kor","year":"2018","unstructured":"Kor CT, Hsieh YP, Chang CC, Chiu PF. The prognostic value of interaction between mean corpuscular volume and red cell distribution width in mortality in chronic kidney disease. Sci Rep. 2018;8:11870. https:\/\/doi.org\/10.1038\/s41598-018-19881-2.","journal-title":"Sci Rep"}],"container-title":["BMC Medical Informatics and Decision Making"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12911-025-03142-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12911-025-03142-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12911-025-03142-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,8]],"date-time":"2025-09-08T19:22:50Z","timestamp":1757359370000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcmedinformdecismak.biomedcentral.com\/articles\/10.1186\/s12911-025-03142-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,8]]},"references-count":48,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["3142"],"URL":"https:\/\/doi.org\/10.1186\/s12911-025-03142-0","relation":{},"ISSN":["1472-6947"],"issn-type":[{"value":"1472-6947","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,8]]},"assertion":[{"value":"6 June 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 August 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 August 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The study was conducted following the Declaration of Helsinki and was approved by the Ethics Committee of Zhejiang Provincial People\u2019s Hospital (Approval No. KT2024116) in 3 Jan. 2025, and the requirement for written informed consent was waived.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"295"}}