Risk prediction models for acute kidney injury after cardiac valve surgery: A systematic review and meta-analysis_Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

Authors：

LU Chengfeng ¹ , HOU Zhenzhen ¹ , FENG Zhenzhen ¹ ,  YANG Qin ²

1. School of Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, P. R. China;
2. Department of ICU, Sichuan Provincial People's Hospital, Chengdu, 610072, P. R. China;

Corresponding?author：

YANG Qin, Email: 20152160@qq.com

Keywords：

Cardiac valve surgery; acute kidney injury; prediction model; systematic review/meta-analysis

DOI：

10.7507/1007-4848.202508051

Video：

Export PDF Favorites Scan Get Citation

Abstract Full text Figures/Tables Video References Cited by

Objective To systematically evaluate the research quality and efficacy of prediction models for acute kidney injury (AKI) after heart valve surgery, screen key predictive factors, and provide evidence-based basis for clinical risk assessment. Methods Computer search was carried out in PubMed, Web of Science, EMBASE, Cochrane Library, Medline, China Biology Medicine Database, China National Knowledge Infrastructure, Wanfang Database, and VIP Database to collect studies on AKI prediction models after heart valve surgery published from January 2015 to July 2025. The PROBAST tool was used to evaluate the bias risk and applicability of the models, and the TRIPOD was used to assess the reporting quality. Meta-analysis was performed to integrate the effect sizes of high-frequency (≥3 times) predictive factors. Results A total of 24 studies (39 models) were included. Area under the curve (AUC) of the receiver operational characteristic curve was between 0.551 and 0.928, and the combined AUC was 0.77 (95%CI 0.72-0.82). The overall bias risk of the models was relatively high (100% of the studies had a high bias risk), only 2 studies conducted external validation, and the models in 10 studies were not validated. In terms of TRIPOD reporting quality, the overall reporting quality of 24 studies was low, with a compliance percentage (number of items) ranging from 36.36% to 77.27%. Meta-analysis showed that age (OR=1.041, P=0.006), diabetes (OR=1.64, P=0.001), hypertension (OR=2.529, P <0.001), blood transfusion (OR=1.49, P=0.001), cystatin C (OR=2.408, P=0.018), history of cardiac surgery (OR=2.585, P <0.001), atrial fibrillation (OR=1.33, P <0.001), and vascular complications (OR=1.22, P=0.008) were independent risk factors for postoperative AKI. Conclusion The clinical applicability of existing prediction models is limited, with high bias risk and low reporting quality, and the methodology needs to be optimized. Eight factors such as age and hypertension can be used as core indicators for postoperative AKI risk assessment. In the future, multicenter prospective studies should be carried out to develop more reliable prediction tools.

1.	李瀟. 心臟瓣膜罕見疾病研究進展. 現代醫藥衛生, 2017, 33(20): 3128-3130.Li X. Research progress on rare heart valve diseases. J Mod Med Health, 2017, 33(20): 3128-3130.
2.	董念國, 曹紅, 周廷文, 等. 心臟瓣膜病治療進展. 臨床心血管病雜志, 2022, 38(6): 429-432.Dong NG, Cao H, Zhou YW, et al. Progress in the treatment of heart valve disease. J Clin Cardiol, 2022, 38(6): 429-432.
3.	劉明波, 何新葉, 楊曉紅, 等. 《中國心血管健康與疾病報告2023》概要(心血管疾病流行及介入診療狀況). 中國介入心臟病學雜志, 2024, 32(10): 541-550.Liu MB, He XY, Yang XH, et al. Interpretation of report on cardiovascular health and diseases in China 2023. Chin J Interv Cardiol, 2024, 32(10): 541-550.
4.	Banovic M, Rajani R. Editorial: advances in the imaging and treatment of valvular heart disease: “rising to the challenge”. Front Cardiovasc Med, 2023, 10: 1276202.
5.	Aluru JS, Barsouk A, Saginala K, et al. Valvular heart disease epidemiology. Med Sci (Basel), 2022, 10(2): 32.
6.	郝星. 2023年中國心血管外科手術和體外循環數據白皮書. 中國體外循環雜志, 2024, 22(4): 259-262.He X. White book of Chinese cardiovascular surgery and extracorporeal circulation in 2023. Chin J Extracorp Circ, 2024, 22(4): 259-262.
7.	楊琳琳, 劉剛, 易銳, 等. 急性腎損傷風險預測方法的研究進展. 實用醫學雜志, 2022, 38(18): 2367-2372.Yang LL, Liu G, Yi R, et al. Research progress on risk prediction of acute renal injury. J Pract Med, 2022, 38(18): 2367-2372.
8.	劉嘉龍, 郭文超, 滕嬌, 等. 成人急性腎損傷患者連續性腎臟替代治療管理的最佳證據總結. 中華急危重癥護理雜志, 2024, 5(2): 172-180.Liu JL, Guo WC, Teng J, et al. Summary of best evidence for the management of continuous renal replacement therapy in adults with acute kidney injury. Chin J Emerg Crit Care Nurs, 2024, 5(2): 172-180.
9.	Nadim MK, Forni LG, Bihorac A, et al. Cardiac and vascular surgery-associated acute kidney injury: the 20th international consensus conference of the ADQI (acute disease quality initiative) group. J Am Heart Assoc, 2018, 7(11): e008834.
10.	高緒霞, 馬立萍, 馬涵英, 等. 4878例心臟外科手術后患者急性腎損傷發生率及其危險因素分析. 中華腎臟病雜志, 2020, 36(5): 359-365.Gao XX, Ma LP, Ma HY, et al. Incidence of acute kidney injury following cardiac surgery and related risk factors in 4878 patients. Chin J Nephrol, 2020, 36(5): 359-365.
11.	Amini S, Najafi MN, Karrari SP, et al. Risk factors and outcome of acute kidney injury after isolated CABG surgery: a prospective cohort study. Braz J Cardiovasc Surg, 2019, 34(1): 70-75.
12.	王添未, 唐程斌, 蔣偉, 等. 心臟術后相關急性腎損傷早期生物標志物研究進展. 實用臨床醫藥雜志, 2024, 28(3): 131-139.Wang TW, Tang CB, Jiang W, et al. Research progress on early biomarkers of cardiac surgery-associated acute kidney injury. J Clin Med Pract, 2024, 28(3): 131-139.
13.	楊蕓, 彭翼, 蔡妍欣, 等. 心臟瓣膜術后早期KDIGO 1期急性腎損傷患者的危險因素分析. 嶺南心血管病雜志, 2024, 30(6): 576-580,586.Yang Y, Peng Y, Cai YX, et al. Risk factors for patients with early KDIGO stage 1 acute kidney injury after cardiac valve surgery. South China J Cardiovasc Dis, 2024, 30(6): 576-580,586.
14.	Moons KGM, Wolff RF, Riley RD, et al. PROBAST: a tool to assess risk of bias and applicability of prediction model studies: explanation and elaboration. Ann Intern Med, 2019, 170(1): W1-W33.
15.	Collins GS, Reitsma JB, Altman DG, et al. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. BMJ, 2015, 350: g7594.
16.	粟宇霜, 李艷, 高虹, 等. 食管癌術后吻合口瘺風險預測模型的系統評價與Meta分析. 中國胸心血管外科臨床雜志, 2025, 32(2): 230-236.Su YS, Li Y, Gao H, et al. The risk prediction models for anastomotic leakage after esophagectomy: a systematic review and meta-analysis. Chin J Clin Thorac Cardiovasc Surg, 2025, 32(2): 230-236.
17.	時紅, 于海濤, 靳澤岳. 心臟瓣膜置換術后急性腎損傷的列線圖預測模型研究. 臨床腎臟病雜志, 2024, 24(3): 177-184.Shi H, Yu HT, Jin ZY. Homogram prediction modeling of acute kidney injury after heart valve replacement. J Clin Nephrol, 2024, 24(3): 177-184.
18.	孫斌, 甄寧, 劉倩, 等. 心臟瓣膜置換患者術后急性腎損傷風險預測模型的建立與驗證. 中華腎臟病雜志, 2022, 38(11): 983-986.Sun B, Zhen N, Liu Q, et al. Establishment and verification of a risk prediction model for acute kidney injury in patients undergoing heart valve replacement. Chin J Nephrol, 2022, 38(11): 983-986.
19.	席志龍, 仇冰梅, 劉強, 等. Cox迷宮Ⅲ聯合心臟瓣膜手術后急性腎損傷風險預測模型的構建與評價. 國際心血管病雜志, 2024, 51(4): 256-261.Xi ZL, Qiu BM, Liu Q, et al. Construction and evaluation of a nomogram to predict acute kidney injury in patients undergoing Cox Maze Ⅲ procedure combined with cardiac valve surgery. Int J Cardiovasc Dis, 2024, 51(4): 256-261.
20.	趙曉茹, 邵澤華, 張文雯, 等. 術前血清尿酸/白蛋白比值對心臟瓣膜術后急性腎損傷的預測價值. 中華腎臟病雜志, 2024, 40(3): 201-208.Zhao XR, Shao ZH, Zhang WW, et al. Predictive value of serum uric acid/albumin ratio for acute kidney injury after cardiac valve surgery. Chin J Nephrol, 2024, 40(3): 201-208.
21.	Huang X, Sun X, Song J, et al. Risk factors analysis and prediction model establishment of acute kidney injury after heart valve replacement in patients with normal renal function. Front Cardiovasc Med, 2025, 12: 1422870.
22.	Jia X, Ma J, Qi Z, et al. Development and validation of a prediction model for acute kidney injury following cardiac valve surgery. Front Med (Lausanne), 2025, 12: 1528147.
23.	Pan L, Deng Y, Dai S, et al. Development and internal validation of a prediction model for acute kidney injury following cardiac valve replacement surgery. Int J Cardiol, 2023, 370: 345-350.
24.	Yan Y, Gong H, Hu J, et al. Perioperative parameters-based prediction model for acute kidney injury in Chinese population following valvular surgery. Front Cardiovasc Med, 2023, 10: 1094997.
25.	Dedemo?lu M, Tüysüz ME. Risk estimation model for acute kidney injury defined by KDIGO classification after heart valve replacement surgery. Gen Thorac Cardiovasc Surg, 2020, 68(9): 922-931.
26.	Liu Y, Xiao J, Duan X, et al. The multivariable prognostic models for severe complications after heart valve surgery. BMC Cardiovasc Disord, 2021, 21(1): 491.
27.	Pasceri V, Pelliccia F, Mehran R, et al. Risk score for prediction of dialysis after transcatheter aortic valve replacement. J Am Heart Assoc, 2024, 13(7): e032955.
28.	Loizzi F, Burattini O, Cafaro A, et al. Early acute kidney injury after transcatheter aortic valve implantation: predictive value of currently available risk scores. Hellenic J Cardiol, 2023, 70: 19-27.
29.	Zivkovic N, Elbaz-Greener G, Qiu F, et al. Bedside risk score for prediction of acute kidney injury after transcatheter aortic valve replacement. Open Heart, 2018, 5(1): e000777.
30.	Kumar N, Garg N. Acute kidney injury after aortic valve replacement in a nationally representative cohort in the USA. Nephrol Dial Transplant, 2019, 34(2): 295-300.
31.	Wu T, Li R, Chen J, et al. Age, creatinine, and ejection fraction score is a risk factor for acute kidney injury after surgical aortic valve replacement. Ren Fail, 2025, 47(1): 2444401.
32.	Liao Y, Li L, Li J, et al. Uric acid to albumin ratio: a predictive marker for acute kidney injury in isolated tricuspid valve surgery. Rev Cardiovasc Med, 2025, 26(2): 26391.
33.	劉丹丹, 王蕊, 楊瑞霞, 等. 細胞間黏附因子-1、尿微量白蛋白、半乳糖凝集素-3在診斷體外循環下心臟瓣膜置換術后急性腎損傷發生中的作用. 中國臨床實用醫學, 2024, 15(5): 16-21.Liu DD, Wang R, Yang RX, et al. Role of intercellular cell adhesion molecule-1, microscale albuminuria and galectin 3 expression in the development and diagnosis of acute kidney injury following cardiac valve replacement under cardiopulmonary bypass. China Clin Pract Med, 2024, 15(5): 16-21.
34.	陳宗皓, 張海波, 李巖, 等. 術前血清HMGB1、MFG-E8、CysC水平與心臟瓣膜置換術后急性腎損傷發生的相關性分析. 疑難病雜志, 2022, 21(8): 809-814.Chen ZH, Zhang HB, Li Y, et al. Correlation analysis of preoperative serum HMGB1, MFG-E8 and CysC levels with acute kidney injury after heart valve replacement. Chin J Diffic Complicat Cases, 2022, 21(8): 809-814.
35.	Tseng PY, Chen YT, Wang CH, et al. Prediction of the development of acute kidney injury following cardiac surgery by machine learning. Crit Care, 2020, 24(1): 478.
36.	Uygur B, Celik O, Demir AR, et al. A simplified acute kidney injury predictor following transcatheter aortic valve implantation: ACEF score. Kardiol Pol, 2021, 79(6): 662-668.
37.	Shishikura D, Kataoka Y, Pisaniello AD, et al. The extent of aortic atherosclerosis predicts the occurrence, severity, and recovery of acute kidney injury after transcatheter aortic valve replacement. Circ Cardiovasc Interv, 2018, 11(8): e006367.
38.	熊偉, 張力凡, 佘凱, 等. 機器學習和Logistic回歸模型預測心臟外科術后患者發生急性腎損傷的比較分析. 中華危重病急救醫學, 2022, 34(11): 1188-1193.Xiong W, Zhang LF, She K, et al. Comparison of machine learning and Logistic regression model in predicting acute kidney injury after cardiac surgery. Chin Crit Care Med, 2022, 34(11): 1188-1193.
39.	范運龍, 邵佳康, 吳遠斌, 等. 基于機器學習的心臟手術后急性腎損傷預測. 解放軍醫學院學報, 2022, 43(2): 168-174.Fan YL, Shan JK, Wu YB, et al. Prediction of acute kidney injury following cardiac surgery by machine learning. Acad J Chin PLA Med Sch, 2022, 43(2): 168-174.
40.	陳婷, 呂蕾, 王琦, 等. 經胸超聲心動圖對心臟瓣膜術后患者合并急性腎損傷的影響因素分析. 巴楚醫學, 2023, 6(3): 68-74.Chen T, Lv L, Wang Q, et al. The predictive value of transthoracic echocardiography for acute kidney injury in patients underwent cardiac valve surgery. Bachu Med J, 2023, 6(3): 68-74.
41.	張娟, 魏璐, 張宇, 等. 腎小球濾過率增齡變化及其影響因素的研究. 中華老年醫學雜志, 2021, 40(10): 1250-1254.Zhang J, Wei L, Zhang Y, et al. Study on changes in the glomerular filtration rate with aging and their influencing factors. Chin J Geriatr, 2021, 40(10): 1250-1254.
42.	Haruhara K, Kanzaki G, Sasaki T, et al. The number and size of glomeruli and podocytes in the aging human kidney. Kidney Int Rep, 2025, 10(7): 2472-2475.
43.	Carrascal Y, Laguna G, Blanco M, et al. Acute kidney injury after heart valve surgery in elderly patients: any risk factors to modify? Braz J Cardiovasc Surg, 2021, 36(1): 1-9.
44.	Damianaki A, Hendriks-Balk M, Brito W, et al. Contrast-enhanced ultrasonography reveals a lower cortical perfusion and a decreased renal flow reserve in hypertensive patients. Nephrol Dial Transplant, 2024, 39(2): 242-250.
45.	唐淵, 王偉, 宋昱. 心臟瓣膜術后急性腎損傷發生的危險因素分析. 天津醫科大學學報, 2021, 27(3): 247-251.Tang Y, Wang W, Song Y. Risk factors of acute kidney injury after cardiac valve operation. J Tianjin Med Univ, 2021, 27(3): 247-251.
46.	張偉, 辛芳冉, 楊忠路, 等. 成人心臟瓣膜手術后發生急性腎損傷危險因素分析. 創傷與急危重病醫學, 2022, 10(3): 174-176,190.Zhang W, Xin FR, Yang ZL, et al. Analysis of risk factors for acute kidney injury after adult heart valve surgery. Trauma Crit Care Med, 2022, 10(3): 174-176,190.
47.	傅之梅, 嚴敏, 郁麗娜, 等. 心肺轉流下心臟瓣膜術后急性腎損傷的危險因素分析. 臨床麻醉學雜志, 2017, 33(6): 534-537.Fu ZM, Yan M, Yu LN, et al. Risk factors for perioperative acute kidney injury in adult cardiac valve surgery with cardiopulmonary bypass. J Clin Anesthesiol, 2017, 33(6): 534-537.
48.	王玉金, 侯志梅. 糖尿病腎病的發病機制及其早期生物標志物的研究進展. 臨床醫學進展, 2024, 14(4): 703-709.Wang YJ, Hou ZM. Research progress on pathogenesis and early biomarkers of diabetic kidney disease. Adv Clin Med, 2024, 14(4): 703-709.
49.	Zhang C, Ning M, Liang W, et al. The association between acute kidney injury and dysglycaemia in critically ill patients with and without diabetes mellitus: a retrospective single-center study. Ren Fail, 2024, 46(2): 2397555.
50.	Ansari DM, Harahwa T, Abuelgasim E, et al. Glycated haemoglobin levels and its effect on outcomes in cardiac surgery. Braz J Cardiovasc Surg, 2022, 37(5): 744-753.
51.	Shlipak MG, Inker LA, Coresh J. Serum cystatin C for estimation of GFR. JAMA, 2022, 328(9): 883-884.
52.	吳春濤. NGAL、Cys C在瓣膜病換瓣術后早期診斷急性腎損傷的意義. 河北醫科大學學報, 2019, 40(12): 1388-1392.Wu CT. Clinical significance of NGAL and Cys C in early diagnosis of acute kidney injury after valvular disease operation. J Hebei Med Univ, 2019, 40(12): 1388-1392.
53.	Yong Z, Pei X, Zhu B, et al. Predictive value of serum cystatin C for acute kidney injury in adults: a meta-analysis of prospective cohort trials. Sci Rep, 2017, 7: 41012.
54.	姬翠, 馬雅雅, 王媛, 等. 心臟瓣膜術后發生急性腎損傷危險因素的Meta分析. 循證護理, 2025, 11(3): 381-387.Ji C, Ma YY, Wang Y, et al. Risk factors for acute kidney injury after heart valve surgery: a meta-analysis. Chin Evid Based Nurs, 2025, 11(3): 381-387.
55.	吳蕾, 欒正剛. 高遷移率族蛋白B1介導血管內皮屏障功能障礙及對白細胞-內皮細胞黏附的調節作用. 中華病理學雜志, 2017, 46(1): 64-67.Wu L, Luan ZG. Mediation of high-mobility group box-1 protein to vascular endothelial barrier dysfunction and adjustment role of leukocyte endothelial adhesion. Chin J Pathol, 2017, 46(1): 64-67.
56.	Merchant AM, Neyra JA, Minhajuddin A, et al. Packed red blood cell transfusion associates with acute kidney injury after transcatheter aortic valve replacement. BMC Anesthesiol, 2019, 19(1): 99.
57.	Bosboom JJ, Klanderman RB, Migdady Y, et al. Transfusion-associated circulatory overload: a clinical perspective. Transfus Med Rev, 2019, 33(2): 69-77.
58.	Luu CH, Nguyen NT, Ta HT. Unravelling surface modification strategies for preventing medical device-induced thrombosis. Adv Healthc Mater, 2024, 13(1): e2301039.
59.	徐嬌, 孫振東, 蔡國華, 等. 成人心臟術后急性腎損傷的影響因素分析. 心肺血管病雜志, 2021, 40(5): 464-467.Xu J, Sun ZD, Cai GH, et al. Risk factors of acute kidney injury after cardiac surgery in adults. J Cardiovasc Pulm Dis, 2021, 40(5): 464-467.
60.	Fischer MA, Howard-Quijano K, Zong NC, et al. Perioperative changes in plasma nitrite and IL-6 levels predict postoperative atrial fibrillation (POAF) and acute kidney injury (AKI) after cardiac surgery. Antioxidants (Basel), 2024, 13(8): 971.
61.	Karakasis P, Theofilis P, Vlachakis PK, et al. Atrial fibrosis in atrial fibrillation: mechanistic insights, diagnostic challenges, and emerging therapeutic targets. Int J Mol Sci, 2024, 26(1): 209.
62.	Ng RRG, Tan GHJ, Liu W, et al. The association of acute kidney injury and atrial fibrillation after cardiac surgery in an Asian prospective cohort study. Medicine (Baltimore), 2016, 95(12): e3005.
63.	Ding WY, Gupta D, Wong CF, et al. Pathophysiology of atrial fibrillation and chronic kidney disease. Cardiovasc Res, 2021, 117(4): 1046-1059.
64.	張倩, 張文佳, 王墨揚, 等. 經導管主動脈瓣置換術后急性腎損傷的發生及危險因素的分析. 中國循環雜志, 2019, 34(11): 1079-1084.Zhang Q, Zhang WJ, Wang MY, et al. Risk factor analysis of acute kidney injury after transcatheter aortic valve replacement. Chin Circ J, 2019, 34(11): 1079-1084.
65.	Ugwu AO, Nnakenyi ID, Okwor CJ. Investigating serum levels of IL-6 and TNF alpha, and the risk of thrombosis in newly diagnosed chemotherapy na?ve obese cancer patients. Niger Med J, 2025, 66(2): 761-769.

1. 李瀟. 心臟瓣膜罕見疾病研究進展. 現代醫藥衛生, 2017, 33(20): 3128-3130.Li X. Research progress on rare heart valve diseases. J Mod Med Health, 2017, 33(20): 3128-3130.
2. 董念國, 曹紅, 周廷文, 等. 心臟瓣膜病治療進展. 臨床心血管病雜志, 2022, 38(6): 429-432.Dong NG, Cao H, Zhou YW, et al. Progress in the treatment of heart valve disease. J Clin Cardiol, 2022, 38(6): 429-432.
3. 劉明波, 何新葉, 楊曉紅, 等. 《中國心血管健康與疾病報告2023》概要(心血管疾病流行及介入診療狀況). 中國介入心臟病學雜志, 2024, 32(10): 541-550.Liu MB, He XY, Yang XH, et al. Interpretation of report on cardiovascular health and diseases in China 2023. Chin J Interv Cardiol, 2024, 32(10): 541-550.
4. Banovic M, Rajani R. Editorial: advances in the imaging and treatment of valvular heart disease: “rising to the challenge”. Front Cardiovasc Med, 2023, 10: 1276202.
5. Aluru JS, Barsouk A, Saginala K, et al. Valvular heart disease epidemiology. Med Sci (Basel), 2022, 10(2): 32.
6. 郝星. 2023年中國心血管外科手術和體外循環數據白皮書. 中國體外循環雜志, 2024, 22(4): 259-262.He X. White book of Chinese cardiovascular surgery and extracorporeal circulation in 2023. Chin J Extracorp Circ, 2024, 22(4): 259-262.
7. 楊琳琳, 劉剛, 易銳, 等. 急性腎損傷風險預測方法的研究進展. 實用醫學雜志, 2022, 38(18): 2367-2372.Yang LL, Liu G, Yi R, et al. Research progress on risk prediction of acute renal injury. J Pract Med, 2022, 38(18): 2367-2372.
8. 劉嘉龍, 郭文超, 滕嬌, 等. 成人急性腎損傷患者連續性腎臟替代治療管理的最佳證據總結. 中華急危重癥護理雜志, 2024, 5(2): 172-180.Liu JL, Guo WC, Teng J, et al. Summary of best evidence for the management of continuous renal replacement therapy in adults with acute kidney injury. Chin J Emerg Crit Care Nurs, 2024, 5(2): 172-180.
9. Nadim MK, Forni LG, Bihorac A, et al. Cardiac and vascular surgery-associated acute kidney injury: the 20th international consensus conference of the ADQI (acute disease quality initiative) group. J Am Heart Assoc, 2018, 7(11): e008834.
10. 高緒霞, 馬立萍, 馬涵英, 等. 4878例心臟外科手術后患者急性腎損傷發生率及其危險因素分析. 中華腎臟病雜志, 2020, 36(5): 359-365.Gao XX, Ma LP, Ma HY, et al. Incidence of acute kidney injury following cardiac surgery and related risk factors in 4878 patients. Chin J Nephrol, 2020, 36(5): 359-365.
11. Amini S, Najafi MN, Karrari SP, et al. Risk factors and outcome of acute kidney injury after isolated CABG surgery: a prospective cohort study. Braz J Cardiovasc Surg, 2019, 34(1): 70-75.
12. 王添未, 唐程斌, 蔣偉, 等. 心臟術后相關急性腎損傷早期生物標志物研究進展. 實用臨床醫藥雜志, 2024, 28(3): 131-139.Wang TW, Tang CB, Jiang W, et al. Research progress on early biomarkers of cardiac surgery-associated acute kidney injury. J Clin Med Pract, 2024, 28(3): 131-139.
13. 楊蕓, 彭翼, 蔡妍欣, 等. 心臟瓣膜術后早期KDIGO 1期急性腎損傷患者的危險因素分析. 嶺南心血管病雜志, 2024, 30(6): 576-580,586.Yang Y, Peng Y, Cai YX, et al. Risk factors for patients with early KDIGO stage 1 acute kidney injury after cardiac valve surgery. South China J Cardiovasc Dis, 2024, 30(6): 576-580,586.
14. Moons KGM, Wolff RF, Riley RD, et al. PROBAST: a tool to assess risk of bias and applicability of prediction model studies: explanation and elaboration. Ann Intern Med, 2019, 170(1): W1-W33.
15. Collins GS, Reitsma JB, Altman DG, et al. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. BMJ, 2015, 350: g7594.
16. 粟宇霜, 李艷, 高虹, 等. 食管癌術后吻合口瘺風險預測模型的系統評價與Meta分析. 中國胸心血管外科臨床雜志, 2025, 32(2): 230-236.Su YS, Li Y, Gao H, et al. The risk prediction models for anastomotic leakage after esophagectomy: a systematic review and meta-analysis. Chin J Clin Thorac Cardiovasc Surg, 2025, 32(2): 230-236.
17. 時紅, 于海濤, 靳澤岳. 心臟瓣膜置換術后急性腎損傷的列線圖預測模型研究. 臨床腎臟病雜志, 2024, 24(3): 177-184.Shi H, Yu HT, Jin ZY. Homogram prediction modeling of acute kidney injury after heart valve replacement. J Clin Nephrol, 2024, 24(3): 177-184.
18. 孫斌, 甄寧, 劉倩, 等. 心臟瓣膜置換患者術后急性腎損傷風險預測模型的建立與驗證. 中華腎臟病雜志, 2022, 38(11): 983-986.Sun B, Zhen N, Liu Q, et al. Establishment and verification of a risk prediction model for acute kidney injury in patients undergoing heart valve replacement. Chin J Nephrol, 2022, 38(11): 983-986.
19. 席志龍, 仇冰梅, 劉強, 等. Cox迷宮Ⅲ聯合心臟瓣膜手術后急性腎損傷風險預測模型的構建與評價. 國際心血管病雜志, 2024, 51(4): 256-261.Xi ZL, Qiu BM, Liu Q, et al. Construction and evaluation of a nomogram to predict acute kidney injury in patients undergoing Cox Maze Ⅲ procedure combined with cardiac valve surgery. Int J Cardiovasc Dis, 2024, 51(4): 256-261.
20. 趙曉茹, 邵澤華, 張文雯, 等. 術前血清尿酸/白蛋白比值對心臟瓣膜術后急性腎損傷的預測價值. 中華腎臟病雜志, 2024, 40(3): 201-208.Zhao XR, Shao ZH, Zhang WW, et al. Predictive value of serum uric acid/albumin ratio for acute kidney injury after cardiac valve surgery. Chin J Nephrol, 2024, 40(3): 201-208.
21. Huang X, Sun X, Song J, et al. Risk factors analysis and prediction model establishment of acute kidney injury after heart valve replacement in patients with normal renal function. Front Cardiovasc Med, 2025, 12: 1422870.
22. Jia X, Ma J, Qi Z, et al. Development and validation of a prediction model for acute kidney injury following cardiac valve surgery. Front Med (Lausanne), 2025, 12: 1528147.
23. Pan L, Deng Y, Dai S, et al. Development and internal validation of a prediction model for acute kidney injury following cardiac valve replacement surgery. Int J Cardiol, 2023, 370: 345-350.
24. Yan Y, Gong H, Hu J, et al. Perioperative parameters-based prediction model for acute kidney injury in Chinese population following valvular surgery. Front Cardiovasc Med, 2023, 10: 1094997.
25. Dedemo?lu M, Tüysüz ME. Risk estimation model for acute kidney injury defined by KDIGO classification after heart valve replacement surgery. Gen Thorac Cardiovasc Surg, 2020, 68(9): 922-931.
26. Liu Y, Xiao J, Duan X, et al. The multivariable prognostic models for severe complications after heart valve surgery. BMC Cardiovasc Disord, 2021, 21(1): 491.
27. Pasceri V, Pelliccia F, Mehran R, et al. Risk score for prediction of dialysis after transcatheter aortic valve replacement. J Am Heart Assoc, 2024, 13(7): e032955.
28. Loizzi F, Burattini O, Cafaro A, et al. Early acute kidney injury after transcatheter aortic valve implantation: predictive value of currently available risk scores. Hellenic J Cardiol, 2023, 70: 19-27.
29. Zivkovic N, Elbaz-Greener G, Qiu F, et al. Bedside risk score for prediction of acute kidney injury after transcatheter aortic valve replacement. Open Heart, 2018, 5(1): e000777.
30. Kumar N, Garg N. Acute kidney injury after aortic valve replacement in a nationally representative cohort in the USA. Nephrol Dial Transplant, 2019, 34(2): 295-300.
31. Wu T, Li R, Chen J, et al. Age, creatinine, and ejection fraction score is a risk factor for acute kidney injury after surgical aortic valve replacement. Ren Fail, 2025, 47(1): 2444401.
32. Liao Y, Li L, Li J, et al. Uric acid to albumin ratio: a predictive marker for acute kidney injury in isolated tricuspid valve surgery. Rev Cardiovasc Med, 2025, 26(2): 26391.
33. 劉丹丹, 王蕊, 楊瑞霞, 等. 細胞間黏附因子-1、尿微量白蛋白、半乳糖凝集素-3在診斷體外循環下心臟瓣膜置換術后急性腎損傷發生中的作用. 中國臨床實用醫學, 2024, 15(5): 16-21.Liu DD, Wang R, Yang RX, et al. Role of intercellular cell adhesion molecule-1, microscale albuminuria and galectin 3 expression in the development and diagnosis of acute kidney injury following cardiac valve replacement under cardiopulmonary bypass. China Clin Pract Med, 2024, 15(5): 16-21.
34. 陳宗皓, 張海波, 李巖, 等. 術前血清HMGB1、MFG-E8、CysC水平與心臟瓣膜置換術后急性腎損傷發生的相關性分析. 疑難病雜志, 2022, 21(8): 809-814.Chen ZH, Zhang HB, Li Y, et al. Correlation analysis of preoperative serum HMGB1, MFG-E8 and CysC levels with acute kidney injury after heart valve replacement. Chin J Diffic Complicat Cases, 2022, 21(8): 809-814.
35. Tseng PY, Chen YT, Wang CH, et al. Prediction of the development of acute kidney injury following cardiac surgery by machine learning. Crit Care, 2020, 24(1): 478.
36. Uygur B, Celik O, Demir AR, et al. A simplified acute kidney injury predictor following transcatheter aortic valve implantation: ACEF score. Kardiol Pol, 2021, 79(6): 662-668.
37. Shishikura D, Kataoka Y, Pisaniello AD, et al. The extent of aortic atherosclerosis predicts the occurrence, severity, and recovery of acute kidney injury after transcatheter aortic valve replacement. Circ Cardiovasc Interv, 2018, 11(8): e006367.
38. 熊偉, 張力凡, 佘凱, 等. 機器學習和Logistic回歸模型預測心臟外科術后患者發生急性腎損傷的比較分析. 中華危重病急救醫學, 2022, 34(11): 1188-1193.Xiong W, Zhang LF, She K, et al. Comparison of machine learning and Logistic regression model in predicting acute kidney injury after cardiac surgery. Chin Crit Care Med, 2022, 34(11): 1188-1193.
39. 范運龍, 邵佳康, 吳遠斌, 等. 基于機器學習的心臟手術后急性腎損傷預測. 解放軍醫學院學報, 2022, 43(2): 168-174.Fan YL, Shan JK, Wu YB, et al. Prediction of acute kidney injury following cardiac surgery by machine learning. Acad J Chin PLA Med Sch, 2022, 43(2): 168-174.
40. 陳婷, 呂蕾, 王琦, 等. 經胸超聲心動圖對心臟瓣膜術后患者合并急性腎損傷的影響因素分析. 巴楚醫學, 2023, 6(3): 68-74.Chen T, Lv L, Wang Q, et al. The predictive value of transthoracic echocardiography for acute kidney injury in patients underwent cardiac valve surgery. Bachu Med J, 2023, 6(3): 68-74.
41. 張娟, 魏璐, 張宇, 等. 腎小球濾過率增齡變化及其影響因素的研究. 中華老年醫學雜志, 2021, 40(10): 1250-1254.Zhang J, Wei L, Zhang Y, et al. Study on changes in the glomerular filtration rate with aging and their influencing factors. Chin J Geriatr, 2021, 40(10): 1250-1254.
42. Haruhara K, Kanzaki G, Sasaki T, et al. The number and size of glomeruli and podocytes in the aging human kidney. Kidney Int Rep, 2025, 10(7): 2472-2475.
43. Carrascal Y, Laguna G, Blanco M, et al. Acute kidney injury after heart valve surgery in elderly patients: any risk factors to modify? Braz J Cardiovasc Surg, 2021, 36(1): 1-9.
44. Damianaki A, Hendriks-Balk M, Brito W, et al. Contrast-enhanced ultrasonography reveals a lower cortical perfusion and a decreased renal flow reserve in hypertensive patients. Nephrol Dial Transplant, 2024, 39(2): 242-250.
45. 唐淵, 王偉, 宋昱. 心臟瓣膜術后急性腎損傷發生的危險因素分析. 天津醫科大學學報, 2021, 27(3): 247-251.Tang Y, Wang W, Song Y. Risk factors of acute kidney injury after cardiac valve operation. J Tianjin Med Univ, 2021, 27(3): 247-251.
46. 張偉, 辛芳冉, 楊忠路, 等. 成人心臟瓣膜手術后發生急性腎損傷危險因素分析. 創傷與急危重病醫學, 2022, 10(3): 174-176,190.Zhang W, Xin FR, Yang ZL, et al. Analysis of risk factors for acute kidney injury after adult heart valve surgery. Trauma Crit Care Med, 2022, 10(3): 174-176,190.
47. 傅之梅, 嚴敏, 郁麗娜, 等. 心肺轉流下心臟瓣膜術后急性腎損傷的危險因素分析. 臨床麻醉學雜志, 2017, 33(6): 534-537.Fu ZM, Yan M, Yu LN, et al. Risk factors for perioperative acute kidney injury in adult cardiac valve surgery with cardiopulmonary bypass. J Clin Anesthesiol, 2017, 33(6): 534-537.
48. 王玉金, 侯志梅. 糖尿病腎病的發病機制及其早期生物標志物的研究進展. 臨床醫學進展, 2024, 14(4): 703-709.Wang YJ, Hou ZM. Research progress on pathogenesis and early biomarkers of diabetic kidney disease. Adv Clin Med, 2024, 14(4): 703-709.
49. Zhang C, Ning M, Liang W, et al. The association between acute kidney injury and dysglycaemia in critically ill patients with and without diabetes mellitus: a retrospective single-center study. Ren Fail, 2024, 46(2): 2397555.
50. Ansari DM, Harahwa T, Abuelgasim E, et al. Glycated haemoglobin levels and its effect on outcomes in cardiac surgery. Braz J Cardiovasc Surg, 2022, 37(5): 744-753.
51. Shlipak MG, Inker LA, Coresh J. Serum cystatin C for estimation of GFR. JAMA, 2022, 328(9): 883-884.
52. 吳春濤. NGAL、Cys C在瓣膜病換瓣術后早期診斷急性腎損傷的意義. 河北醫科大學學報, 2019, 40(12): 1388-1392.Wu CT. Clinical significance of NGAL and Cys C in early diagnosis of acute kidney injury after valvular disease operation. J Hebei Med Univ, 2019, 40(12): 1388-1392.
53. Yong Z, Pei X, Zhu B, et al. Predictive value of serum cystatin C for acute kidney injury in adults: a meta-analysis of prospective cohort trials. Sci Rep, 2017, 7: 41012.
54. 姬翠, 馬雅雅, 王媛, 等. 心臟瓣膜術后發生急性腎損傷危險因素的Meta分析. 循證護理, 2025, 11(3): 381-387.Ji C, Ma YY, Wang Y, et al. Risk factors for acute kidney injury after heart valve surgery: a meta-analysis. Chin Evid Based Nurs, 2025, 11(3): 381-387.
55. 吳蕾, 欒正剛. 高遷移率族蛋白B1介導血管內皮屏障功能障礙及對白細胞-內皮細胞黏附的調節作用. 中華病理學雜志, 2017, 46(1): 64-67.Wu L, Luan ZG. Mediation of high-mobility group box-1 protein to vascular endothelial barrier dysfunction and adjustment role of leukocyte endothelial adhesion. Chin J Pathol, 2017, 46(1): 64-67.
56. Merchant AM, Neyra JA, Minhajuddin A, et al. Packed red blood cell transfusion associates with acute kidney injury after transcatheter aortic valve replacement. BMC Anesthesiol, 2019, 19(1): 99.
57. Bosboom JJ, Klanderman RB, Migdady Y, et al. Transfusion-associated circulatory overload: a clinical perspective. Transfus Med Rev, 2019, 33(2): 69-77.
58. Luu CH, Nguyen NT, Ta HT. Unravelling surface modification strategies for preventing medical device-induced thrombosis. Adv Healthc Mater, 2024, 13(1): e2301039.
59. 徐嬌, 孫振東, 蔡國華, 等. 成人心臟術后急性腎損傷的影響因素分析. 心肺血管病雜志, 2021, 40(5): 464-467.Xu J, Sun ZD, Cai GH, et al. Risk factors of acute kidney injury after cardiac surgery in adults. J Cardiovasc Pulm Dis, 2021, 40(5): 464-467.
60. Fischer MA, Howard-Quijano K, Zong NC, et al. Perioperative changes in plasma nitrite and IL-6 levels predict postoperative atrial fibrillation (POAF) and acute kidney injury (AKI) after cardiac surgery. Antioxidants (Basel), 2024, 13(8): 971.
61. Karakasis P, Theofilis P, Vlachakis PK, et al. Atrial fibrosis in atrial fibrillation: mechanistic insights, diagnostic challenges, and emerging therapeutic targets. Int J Mol Sci, 2024, 26(1): 209.
62. Ng RRG, Tan GHJ, Liu W, et al. The association of acute kidney injury and atrial fibrillation after cardiac surgery in an Asian prospective cohort study. Medicine (Baltimore), 2016, 95(12): e3005.
63. Ding WY, Gupta D, Wong CF, et al. Pathophysiology of atrial fibrillation and chronic kidney disease. Cardiovasc Res, 2021, 117(4): 1046-1059.
64. 張倩, 張文佳, 王墨揚, 等. 經導管主動脈瓣置換術后急性腎損傷的發生及危險因素的分析. 中國循環雜志, 2019, 34(11): 1079-1084.Zhang Q, Zhang WJ, Wang MY, et al. Risk factor analysis of acute kidney injury after transcatheter aortic valve replacement. Chin Circ J, 2019, 34(11): 1079-1084.
65. Ugwu AO, Nnakenyi ID, Okwor CJ. Investigating serum levels of IL-6 and TNF alpha, and the risk of thrombosis in newly diagnosed chemotherapy na?ve obese cancer patients. Niger Med J, 2025, 66(2): 761-769.

Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

Latest ArticlesRisk prediction models for acute kidney injury after cardiac valve surgery: A systematic review and meta-analysis

Abstract Full text Figures/Tables Video References Cited by

Format

Content