Risk prediction models for delirium after adult cardiac surgery: A systematic review and meta-analysis_Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

Authors：

CHEN Min ¹ ,  YANG Amin ¹ , SUN Lu ²

1. Ward 2, Department of Cardiovascular Medicine, Affiliated Jinling Hospital, Medical School of Nanjing University (General Hospital of Eastern Theater Command), Nanjing, 210002, P. R. China;
2. Ward 305, Department of Geriatrics, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, 210008, P. R. China;

Corresponding?author：

YANG Amin, Email: 504165799@qq.com

Keywords：

Cardiac surgery; postoperative delirium; risk prediction model; predictive factors; area under the receiver operating characteristic curve; prediction model risk of bias assessment tool; system review/meta-analysis

DOI：

10.7507/1007-4848.202412032

Video：

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Objective To systematically evaluate the risk prediction models for postoperative delirium in adults with cardiac surgery. Methods The SinoMed, CNKI, Wanfang, VIP, PubMed, EMbase, Web of Science, and Cochrane Library databases were searched to collect studies on risk prediction models for postoperative delirium in cardiac surgery published up to January 29, 2025. Two researchers screened the literature according to inclusion and exclusion criteria, used the PROBAST bias tool to assess the quality of the literature, and conducted a meta-analysis of common predictors in the model using Stata 17.0 software. Results A total of 21 articles were included, establishing 45 models with 28733 patients. Age, cardiopulmonary bypass time, history of diabetes, history of cerebrovascular disease, and gender were the top five common predictors. The area under the curve (AUC) of the 45 models ranged from 0.544 to 0.98. Fourteen out of the 21 studies had good applicability, while the applicability of the remaining seven was unclear; 20 studies had a high risk of bias. Meta-analysis showed that the incidence of postoperative delirium in adults with cardiac surgery was 18.6% [95%CI (15.7%, 21.6%)], and age [OR=1.045 (1.036, 1.054), P<0.001], history of cerebrovascular disease [OR=1.758 (1.459, 2.057), P<0.001], gender [OR=1.732 (1.430, 2.034), P<0.001], mini-mental state examination score [OR=3.930 (1.859, 8.309), P<0.001], and length of ICU stay [OR=5.586 (4.289, 6.883), P<0.001] were independent influencing factors for postoperative delirium after cardiac surgery. Conclusion The risk prediction models for postoperative delirium after cardiac surgery have good predictive performance, but there is a high overall risk of bias. In the future, large-sample, multicenter, high-quality prospective clinical studies should be conducted to construct the optimal risk prediction model for postoperative delirium in adults with cardiac surgery, aiming to identify and prevent the occurrence of postoperative delirium as early as possible.

Citation： CHEN Min, YANG Amin, SUN Lu. Risk prediction models for delirium after adult cardiac surgery: A systematic review and meta-analysis. Chinese Journal of Clinical Thoracic and Cardiovascular Surgery, 2026, 33(3): 444-453. doi: 10.7507/1007-4848.202412032 Copy

1.	Reamy BV, Williams PM, Kuckel DP. Prevention of cardiovascular disease. Prim Care, 2018, 45(1): 25-44.
2.	Mali S, Haghaninejad H. Pulmonary complications following cardiac surgery. Arch Med Sci Atheroscler Dis, 2019, 4: e280-e285.
3.	Velazquez EJ, Lee KL, Jones RH, et al. Coronary-artery bypass surgery in patients with ischemic cardiomyopathy. N Engl J Med, 2016, 374(16): 1511-1520.
4.	Gupta KK, Ali S, Sanghera RS. Pharmacological options in atherosclerosis: a review of the existing evidence. Cardiol Ther, 2019, 8(1): 5-20.
5.	宋亞佩, 吳艷, 翟繼衛. 心外科手術后醫院感染特點及影響因素研究. 中國消毒學雜志, 2021, 38(11): 832-835.Song YP, Wu Y, Zhai JW. Clinical characteristics and influencing factors of nosocomial infections after cardiac surgery. Chin J Disinfect, 2021, 38(11): 832-835.
6.	Park J, Bonde PN. Machine learning in cardiac surgery: predicting mortality and readmission. ASAIO J, 2022, 68(12): 1490-1500.
7.	Jiang JL, Zhang L, He LL, et al. Volatile versus total intravenous anesthesia on postoperative delirium in adult patients undergoing cardiac valve surgery: a randomized clinical trial. Anesth Analg, 2023, 136(1): 60-69.
8.	李瑛, 李賢煌, 胡燕, 等. 心臟外科術后患者發生譫妄危險因素的Meta分析. 解放軍護理雜志, 2022, 39(6): 72-76.Li H, Li XH, Hu Y, et al. Risk factors of delirium occurrence in patients after cardiac surgery: a meta-analysis. Nurs J Chin PLA, 2022, 39(6): 72-76.
9.	Falsini G, Grotti S, Porto I, et al. Long-term prognostic value of delirium in elderly patients with acute cardiac diseases admitted to two cardiac intensive care units: a prospective study (DELIRIUM CORDIS). Eur Heart J Acute Cardiovasc Care, 2018, 7(7): 661-670.
10.	Crocker E, Beggs T, Hassan A, et al. Long-term effects of postoperative delirium in patients undergoing cardiac operation: a systematic review. Ann Thorac Surg, 2016, 102(4): 1391-1399.
11.	陳香萍, 張奕, 莊一渝, 等. PROBAST: 診斷或預后多因素預測模型研究偏倚風險的評估工具. 中國循證醫學雜志, 2020, 20(6): 737-744.Chen XP, Zhang Y, Zhuang YY, et al. PROBAST: a tool for assessing risk of bias in the study of diagnostic or prognostic multi-factorial predictive models. Chin J Evid-Based Med, 2020, 20(6): 737-744.
12.	Guenther U, Theuerkauf N, Frommann I, et al. Predisposing and precipitating factors of delirium after cardiac surgery: a prospective observational cohort study. Ann Surg, 2013, 257(6): 1160-1167.
13.	Krzych LJ, Wybraniec MT, Krupka-Matuszczyk I, et al. Complex assessment of the incidence and risk factors of delirium in a large cohort of cardiac surgery patients: a single-center 6-year experience. Biomed Res Int, 2013, 2013: 835850.
14.	Tse L, Schwarz SK, Bowering JB, et al. Incidence of and risk factors for delirium after cardiac surgery at a quaternary care center: a retrospective cohort study. J Cardiothorac Vasc Anesth, 2015, 29(6): 1472-1479.
15.	Mufti HN, Hirsch GM. Perioperative prediction of agitated (hyperactive) delirium after cardiac surgery in adults: the development of a practical scorecard. J Crit Care, 2017, 42: 192-199.
16.	Rao A, Shi SM, Afilalo J, et al. Physical performance and risk of postoperative delirium in older adults undergoing aortic valve replacement. Clin Interv Aging, 2020, 15: 1471-1479.
17.	Mufti HN, Hirsch GM, Abidi SR, et al. Exploiting machine learning algorithms and methods for the prediction of agitated delirium after cardiac surgery: models development and validation study. JMIR Med Inform, 2019, 7(4): e14993.
18.	Wueest AS, Berres M, Bettex DA, et al. Independent external validation of a preoperative prediction model for delirium after cardiac surgery: a prospective observational cohort study. J Cardiothorac Vasc Anesth, 2023, 37(3): 415-422.
19.	He J, Ling Q, Chen Y. Construction and application of a model for predicting the risk of delirium in postoperative patients with type A aortic dissection. Front Surg, 2021, 8: 772675.
20.	Zhang S, Ji MH, Ding S, et al. Inclusion of interleukin-6 improved performance of postoperative delirium prediction for patients undergoing coronary artery bypass graft (POD-CABG): a derivation and validation study. J Cardiol, 2022, 79(5): 634-641.
21.	Li Q, Li J, Chen J, et al. A machine learning-based prediction model for postoperative delirium in cardiac valve surgery using electronic health records. BMC Cardiovasc Disord, 2024, 24(1): 56.
22.	Wang YP, Shen BB, Zhu CC, et al. Unveiling the nexus of postoperative fever and delirium in cardiac surgery: identifying predictors for enhanced patient care. Front Cardiovasc Med, 2023, 10: 1237055.
23.	Yang T, Yang H, Liu Y, et al. Postoperative delirium prediction after cardiac surgery using machine learning models. Comput Biol Med, 2024, 169: 107818.
24.	Zhao X, Li J, Xie X, et al. Online interpretable dynamic prediction models for postoperative delirium after cardiac surgery under cardiopulmonary bypass developed based on machine learning algorithms: a retrospective cohort study. J Psychosom Res, 2024, 176: 111553.
25.	Liu C, Zhang L, Tang W, et al. A nomogram for predicting the risk of postoperative delirium in individuals undergoing cardiovascular surgery. Eur J Neurol, 2024, 31(12): e16483.
26.	洪亮, 孫加奎, 沈驍, 等. 心臟手術后譫妄的危險因素分析及預測模型構建. 臨床麻醉學雜志, 2020, 36(12): 1195-1200.Hong L, Sun JK, Shen X, et al. Risk factors analysis and prediction model construction of postoperative delirium after cardiac surgery. J Clin Anesthesiol, 2020, 36(12): 1195-1200.
27.	劉海棠, 唐倩蕓, 周森. 老年病人心臟術后譫妄風險列線圖預測模型的建立及驗證. 實用老年醫學, 2021, 35(8): 840-844.Liu HT, Tang QY, Zhou S. Establishment and validation of nomogram model for prediction of delirium risk in elderly patients after cardiac surgery. Pract Geriatr, 2021, 35(8): 840-844.
28.	李雪蘋, 王磊, 張淮, 等. Stanford A型主動脈夾層患者術后譫妄風險預測評分模型的構建與效果驗證. 中華護理雜志, 2022, 57(8): 950-957.Li XP, Wang L, Zhang H, et al. Construction and evaluation of a risk prediction model of postoperative delirium in patients with Stanford type A aortic dissection. Chin J Nurs, 2022, 57(8): 950-957.
29.	徐萍. 老年心臟直視術后患者譫妄風險預測模型的構建及驗證. 浙江中醫藥大學, 2022.Xu P. Construction and verification of prediction model of delirium risk in elderly patients after open heart surgery. Zhejiang University of Traditional Chinese Medicine, 2022.
30.	黃琦, 關美嬌, 鄒彬, 等. 機器學習模型預測心臟外科手術患者術后譫妄的有效性. 臨床麻醉學雜志, 2023, 39(4): 363-369.Huang Q, Guan MJ, Zou B, et al. Effectiveness of machine learning models in predicting postoperative delirium in patients undergoing cardiac surgery. J Clin Anesthesiol, 2023, 39(4): 363-369.
31.	左都坤, 吳卓熙, 龍宗泓, 等. 基于機器學習算法構建心臟手術患者術后早期譫妄風險預測模型. 陸軍軍醫大學學報, 2023, 45(8): 753-758.Zuo DK, Wu ZX, Long ZH, et al. Prediction model of early postoperative delirium risk based on machine learning algorithm in patients undergoing cardiac surgery. J Med Coll PLA, 2023, 45(8): 753-758.
32.	胡霄竹, 韓晴, 屈麗楠, 等. 冠狀動脈旁路移植術術后譫妄的危險因素分析及預測模型的建立. 中國醫藥, 2024, 19(5): 679-683.Hu XZ, Han Q, Qu LN, et al. Analysis of risk factors for postoperative delirium after coronary artery bypass grafting and establishment of prediction model. China Med, 2024, 19(5): 679-683.
33.	Ten Broeke M, Koster S, Konings T, et al. Can we predict a delirium after cardiac surgery? A validation study of a delirium risk checklist. Eur J Cardiovasc Nurs, 2018, 17(3): 255-261.
34.	易進, 崔飛環, 梁玉蘭, 等. 心臟外科術后譫妄的臨床特點和危險因素分析. 心肺血管病雜志, 2024, 43(5): 469-473.Yi J, Cui FH, Liang YL, et al. Analysis of clinical characteristics and risk factors of postoperative delirium after cardiac surgery. J Cardiovasc Pulm Dis, 2024, 43(5): 469-473.
35.	Andrási TB, Talipov I, Dinges G, et al. Risk factors for postoperative delirium after cardiac surgical procedures with cardioplegic arrest. Eur J Cardiothorac Surg, 2022, 62(1): ezab570.
36.	沈立, 王恒, 付正晨, 等. 體外循環心臟術后譫妄. 中國體外循環雜志, 2024, 22(4): 345-348.Shen L, Wang H, Fu ZC, et al. Postoperative delirium after cardiopulmonary bypass. Chin J ECC, 2024, 22(4): 345-348.
37.	Baek W, Kim YM, Lee H. Risk factors of postoperative delirium in older adult spine surgery patients: a meta-analysis. AORN J, 2020, 112(6): 650-661.
38.	王東雄, 袁昕. 心臟外科術后譫妄的術前危險因素研究進展. 心血管病學進展, 2022, 43(8): 698-701.Wang DX, Yuan X. Preoperative risk factors of postoperative delirium in cardiac surgery. Adv Cardiovasc Dis, 2022, 43(8): 698-701.
39.	Wansrisuthon W, Ratta-Apha W, Thongchot L, et al. Accuracy of diagnosis and international classification of diseases; tenth revision coding for alcohol dependence, alcohol withdrawal, and alcohol-withdrawal delirium among inpatients at a university hospital. J Addict Med, 2017, 11(3): 241-242.
40.	Suzuki S, Brown CM, Dela Cruz CD, et al. Timing of estrogen therapy after ovariectomy dictates the efficacy of its neuroprotective and antiinflammatory actions. Proc Natl Acad Sci U S A, 2007, 104(14): 6013-6018.
41.	Oldham MA, Hawkins KA, Yuh DD, et al. Cognitive and functional status predictors of delirium and delirium severity after coronary artery bypass graft surgery: an interim analysis of the neuropsychiatric outcomes after heart surgery study. Int Psychogeriatr, 2015, 27(12): 1929-1938.
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1. Reamy BV, Williams PM, Kuckel DP. Prevention of cardiovascular disease. Prim Care, 2018, 45(1): 25-44.
2. Mali S, Haghaninejad H. Pulmonary complications following cardiac surgery. Arch Med Sci Atheroscler Dis, 2019, 4: e280-e285.
3. Velazquez EJ, Lee KL, Jones RH, et al. Coronary-artery bypass surgery in patients with ischemic cardiomyopathy. N Engl J Med, 2016, 374(16): 1511-1520.
4. Gupta KK, Ali S, Sanghera RS. Pharmacological options in atherosclerosis: a review of the existing evidence. Cardiol Ther, 2019, 8(1): 5-20.
5. 宋亞佩, 吳艷, 翟繼衛. 心外科手術后醫院感染特點及影響因素研究. 中國消毒學雜志, 2021, 38(11): 832-835.Song YP, Wu Y, Zhai JW. Clinical characteristics and influencing factors of nosocomial infections after cardiac surgery. Chin J Disinfect, 2021, 38(11): 832-835.
6. Park J, Bonde PN. Machine learning in cardiac surgery: predicting mortality and readmission. ASAIO J, 2022, 68(12): 1490-1500.
7. Jiang JL, Zhang L, He LL, et al. Volatile versus total intravenous anesthesia on postoperative delirium in adult patients undergoing cardiac valve surgery: a randomized clinical trial. Anesth Analg, 2023, 136(1): 60-69.
8. 李瑛, 李賢煌, 胡燕, 等. 心臟外科術后患者發生譫妄危險因素的Meta分析. 解放軍護理雜志, 2022, 39(6): 72-76.Li H, Li XH, Hu Y, et al. Risk factors of delirium occurrence in patients after cardiac surgery: a meta-analysis. Nurs J Chin PLA, 2022, 39(6): 72-76.
9. Falsini G, Grotti S, Porto I, et al. Long-term prognostic value of delirium in elderly patients with acute cardiac diseases admitted to two cardiac intensive care units: a prospective study (DELIRIUM CORDIS). Eur Heart J Acute Cardiovasc Care, 2018, 7(7): 661-670.
10. Crocker E, Beggs T, Hassan A, et al. Long-term effects of postoperative delirium in patients undergoing cardiac operation: a systematic review. Ann Thorac Surg, 2016, 102(4): 1391-1399.
11. 陳香萍, 張奕, 莊一渝, 等. PROBAST: 診斷或預后多因素預測模型研究偏倚風險的評估工具. 中國循證醫學雜志, 2020, 20(6): 737-744.Chen XP, Zhang Y, Zhuang YY, et al. PROBAST: a tool for assessing risk of bias in the study of diagnostic or prognostic multi-factorial predictive models. Chin J Evid-Based Med, 2020, 20(6): 737-744.
12. Guenther U, Theuerkauf N, Frommann I, et al. Predisposing and precipitating factors of delirium after cardiac surgery: a prospective observational cohort study. Ann Surg, 2013, 257(6): 1160-1167.
13. Krzych LJ, Wybraniec MT, Krupka-Matuszczyk I, et al. Complex assessment of the incidence and risk factors of delirium in a large cohort of cardiac surgery patients: a single-center 6-year experience. Biomed Res Int, 2013, 2013: 835850.
14. Tse L, Schwarz SK, Bowering JB, et al. Incidence of and risk factors for delirium after cardiac surgery at a quaternary care center: a retrospective cohort study. J Cardiothorac Vasc Anesth, 2015, 29(6): 1472-1479.
15. Mufti HN, Hirsch GM. Perioperative prediction of agitated (hyperactive) delirium after cardiac surgery in adults: the development of a practical scorecard. J Crit Care, 2017, 42: 192-199.
16. Rao A, Shi SM, Afilalo J, et al. Physical performance and risk of postoperative delirium in older adults undergoing aortic valve replacement. Clin Interv Aging, 2020, 15: 1471-1479.
17. Mufti HN, Hirsch GM, Abidi SR, et al. Exploiting machine learning algorithms and methods for the prediction of agitated delirium after cardiac surgery: models development and validation study. JMIR Med Inform, 2019, 7(4): e14993.
18. Wueest AS, Berres M, Bettex DA, et al. Independent external validation of a preoperative prediction model for delirium after cardiac surgery: a prospective observational cohort study. J Cardiothorac Vasc Anesth, 2023, 37(3): 415-422.
19. He J, Ling Q, Chen Y. Construction and application of a model for predicting the risk of delirium in postoperative patients with type A aortic dissection. Front Surg, 2021, 8: 772675.
20. Zhang S, Ji MH, Ding S, et al. Inclusion of interleukin-6 improved performance of postoperative delirium prediction for patients undergoing coronary artery bypass graft (POD-CABG): a derivation and validation study. J Cardiol, 2022, 79(5): 634-641.
21. Li Q, Li J, Chen J, et al. A machine learning-based prediction model for postoperative delirium in cardiac valve surgery using electronic health records. BMC Cardiovasc Disord, 2024, 24(1): 56.
22. Wang YP, Shen BB, Zhu CC, et al. Unveiling the nexus of postoperative fever and delirium in cardiac surgery: identifying predictors for enhanced patient care. Front Cardiovasc Med, 2023, 10: 1237055.
23. Yang T, Yang H, Liu Y, et al. Postoperative delirium prediction after cardiac surgery using machine learning models. Comput Biol Med, 2024, 169: 107818.
24. Zhao X, Li J, Xie X, et al. Online interpretable dynamic prediction models for postoperative delirium after cardiac surgery under cardiopulmonary bypass developed based on machine learning algorithms: a retrospective cohort study. J Psychosom Res, 2024, 176: 111553.
25. Liu C, Zhang L, Tang W, et al. A nomogram for predicting the risk of postoperative delirium in individuals undergoing cardiovascular surgery. Eur J Neurol, 2024, 31(12): e16483.
26. 洪亮, 孫加奎, 沈驍, 等. 心臟手術后譫妄的危險因素分析及預測模型構建. 臨床麻醉學雜志, 2020, 36(12): 1195-1200.Hong L, Sun JK, Shen X, et al. Risk factors analysis and prediction model construction of postoperative delirium after cardiac surgery. J Clin Anesthesiol, 2020, 36(12): 1195-1200.
27. 劉海棠, 唐倩蕓, 周森. 老年病人心臟術后譫妄風險列線圖預測模型的建立及驗證. 實用老年醫學, 2021, 35(8): 840-844.Liu HT, Tang QY, Zhou S. Establishment and validation of nomogram model for prediction of delirium risk in elderly patients after cardiac surgery. Pract Geriatr, 2021, 35(8): 840-844.
28. 李雪蘋, 王磊, 張淮, 等. Stanford A型主動脈夾層患者術后譫妄風險預測評分模型的構建與效果驗證. 中華護理雜志, 2022, 57(8): 950-957.Li XP, Wang L, Zhang H, et al. Construction and evaluation of a risk prediction model of postoperative delirium in patients with Stanford type A aortic dissection. Chin J Nurs, 2022, 57(8): 950-957.
29. 徐萍. 老年心臟直視術后患者譫妄風險預測模型的構建及驗證. 浙江中醫藥大學, 2022.Xu P. Construction and verification of prediction model of delirium risk in elderly patients after open heart surgery. Zhejiang University of Traditional Chinese Medicine, 2022.
30. 黃琦, 關美嬌, 鄒彬, 等. 機器學習模型預測心臟外科手術患者術后譫妄的有效性. 臨床麻醉學雜志, 2023, 39(4): 363-369.Huang Q, Guan MJ, Zou B, et al. Effectiveness of machine learning models in predicting postoperative delirium in patients undergoing cardiac surgery. J Clin Anesthesiol, 2023, 39(4): 363-369.
31. 左都坤, 吳卓熙, 龍宗泓, 等. 基于機器學習算法構建心臟手術患者術后早期譫妄風險預測模型. 陸軍軍醫大學學報, 2023, 45(8): 753-758.Zuo DK, Wu ZX, Long ZH, et al. Prediction model of early postoperative delirium risk based on machine learning algorithm in patients undergoing cardiac surgery. J Med Coll PLA, 2023, 45(8): 753-758.
32. 胡霄竹, 韓晴, 屈麗楠, 等. 冠狀動脈旁路移植術術后譫妄的危險因素分析及預測模型的建立. 中國醫藥, 2024, 19(5): 679-683.Hu XZ, Han Q, Qu LN, et al. Analysis of risk factors for postoperative delirium after coronary artery bypass grafting and establishment of prediction model. China Med, 2024, 19(5): 679-683.
33. Ten Broeke M, Koster S, Konings T, et al. Can we predict a delirium after cardiac surgery? A validation study of a delirium risk checklist. Eur J Cardiovasc Nurs, 2018, 17(3): 255-261.
34. 易進, 崔飛環, 梁玉蘭, 等. 心臟外科術后譫妄的臨床特點和危險因素分析. 心肺血管病雜志, 2024, 43(5): 469-473.Yi J, Cui FH, Liang YL, et al. Analysis of clinical characteristics and risk factors of postoperative delirium after cardiac surgery. J Cardiovasc Pulm Dis, 2024, 43(5): 469-473.
35. Andrási TB, Talipov I, Dinges G, et al. Risk factors for postoperative delirium after cardiac surgical procedures with cardioplegic arrest. Eur J Cardiothorac Surg, 2022, 62(1): ezab570.
36. 沈立, 王恒, 付正晨, 等. 體外循環心臟術后譫妄. 中國體外循環雜志, 2024, 22(4): 345-348.Shen L, Wang H, Fu ZC, et al. Postoperative delirium after cardiopulmonary bypass. Chin J ECC, 2024, 22(4): 345-348.
37. Baek W, Kim YM, Lee H. Risk factors of postoperative delirium in older adult spine surgery patients: a meta-analysis. AORN J, 2020, 112(6): 650-661.
38. 王東雄, 袁昕. 心臟外科術后譫妄的術前危險因素研究進展. 心血管病學進展, 2022, 43(8): 698-701.Wang DX, Yuan X. Preoperative risk factors of postoperative delirium in cardiac surgery. Adv Cardiovasc Dis, 2022, 43(8): 698-701.
39. Wansrisuthon W, Ratta-Apha W, Thongchot L, et al. Accuracy of diagnosis and international classification of diseases; tenth revision coding for alcohol dependence, alcohol withdrawal, and alcohol-withdrawal delirium among inpatients at a university hospital. J Addict Med, 2017, 11(3): 241-242.
40. Suzuki S, Brown CM, Dela Cruz CD, et al. Timing of estrogen therapy after ovariectomy dictates the efficacy of its neuroprotective and antiinflammatory actions. Proc Natl Acad Sci U S A, 2007, 104(14): 6013-6018.
41. Oldham MA, Hawkins KA, Yuh DD, et al. Cognitive and functional status predictors of delirium and delirium severity after coronary artery bypass graft surgery: an interim analysis of the neuropsychiatric outcomes after heart surgery study. Int Psychogeriatr, 2015, 27(12): 1929-1938.
42. 王宇, 張誠, 吳慶琛. 心臟外科手術患者術后譫妄的發生率及其可干預危險因素: 一項基于傾向性評分匹配的前瞻性觀察研究. 解放軍醫學雜志, 2024, 49(10): 1110-1116.Wang Y, Zhang C, Wu QC. Incidence and modifiable risk factors of postoperative delirium in patients undergoing cardiac surgery: a prospective observational study based on propensity score matching. Med J Chin PLA, 2024, 49(10): 1110-1116.
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Chinese Journal of Clinical Thoracic and Cardiovascular Surgery

Risk prediction models for delirium after adult cardiac surgery: A systematic review and meta-analysis

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