Systematic review of predictive models for postoperative chronic pain risk in patients undergoing knee arthroplasty_West China Medical Journal

Authors：

 ZHOU Yang ^1,2 , ZENG Biyun ³ , GUO Yabin ^1,2 , WANG Boya ^1,2 , LIU Xiaotong ^1,2 , ZHOU Yang ¹

1. Teaching and Research Section of Clinical Nursing, Xiangya Hospital of Central South University, Changsha, Hunan 410005, P. R. China;
2. Xiang Ya school of Nursing, Central South University, Changsha, Hunan 410013, P. R. China;
3. Orthopedic Ward 6, Xiangya Hospital of Central South University, Changsha, Hunan 410005, P. R. China;

Corresponding author：

ZHOU Yang, Email: zhouyang1030@csu.edu.cn

Keywords：

Knee arthroplasty; postoperative chronic pain; prediction model; systematic review

DOI：

10.7507/1002-0179.202507211

Video：

Export PDF Favorites Scan Get Citation

Abstract Full text Figures/Tables Video References Cited by

Objective To conduct a systematic review of the construction methods, predictive factors, and model quality of risk prediction models for postoperative chronic pain in knee replacement surgery patients, providing evidence for the development of nursing-sensitive dynamic prediction models. Methods A systematic review of risk prediction models for postoperative chronic pain in knee replacement surgery patients was conducted by searching PubMed, Web of Science, Cochrane Library, CINAHL, Sinomed, CNKI, China Biomedical Literature Database, Wanfang Database, and VIP Database. The search period was from the establishment of the databases to February 28, 2025. Two researchers independently screened the literature, extracted data, and assessed the risk of bias and applicability of the included studies. Results A total of 10 studies involving 10 predictive models were included in this review. Among these, three models underwent internal validation, and one model underwent external validation. Commonly reported predictive factors included postoperative 24-hour NRS scores, postoperative knee function scores, sleep disorders, preoperative depression, postoperative functional exercises, postoperative complications, preoperative pain, and postoperative C-reactive protein levels. All 10 studies had a high risk of bias and were generally applicable. Conclusions Existing risk prediction models generally rely on static indicators and lack dynamic monitoring of postoperative rehabilitation behaviors and psychosocial factors, with severe deficiencies in model validation. Future research should focus on developing nursing-led multidimensional dynamic models that incorporate functional exercise adherence data collected via wearable devices, standardize external model validation, and enhance clinical translation value.

1.	Jaffe WL, Dundon JM, Camus T. Alignment and balance methods in total knee arthroplasty. J Am Acad Orthop Surg, 2018, 26(20): 709-716.
2.	周宗科, 翁习生, 曲铁兵, 等. 中国髋、膝关节置换术加速康复——围术期管理策略专家共识. 中华骨与关节外科杂志, 2016, 9(1): 1-9.
3.	Safiri S, Kolahi A, Smith E, et al. Global, regional and national burden of osteoarthritis 1990-2017: a systematic analysis of the global burden of disease study 2017. Ann Rheum Dis, 2020, 79(6): 819-828.
4.	Damen J, van Rijn RM, Emans PJ, et al. Prevalence and development of hip and knee osteoarthritis according to American College of Rheumatology criteria in the CHECK cohort. Arthritis Res Ther, 2019, 21(1): 4.
5.	Lo CWT, Tsang WWN, Yan CH, et al. Risk factors for falls in patients with total hip arthroplasty and total knee arthroplasty: a systematic review and meta-analysis. Osteoarthritis Cartilage, 2019, 27(7): 979-993.
6.	Lee CR, Kim CW, Park DH, et al. Risk of infection after septic and aseptic revision total knee arthroplasty: a systematic review. J Bone Joint Surg Am, 2023, 105(20): 1630-1637.
7.	薛照静, 黄宇光, 赵晶, 等. 慢性术后疼痛研究进展. 中国疼痛医学杂志, 2013, 19(11): 685-689.
8.	Tang S, Jin Y, Hou Y, et al. Predictors of chronic pain in elderly patients undergoing total knee and hip arthroplasty: a prospective observational study. J Arthroplasty, 2023, 38(9): 1693-1699.
9.	Imai R, Nishigami T, Kubo T, et al. Using a postoperative pain trajectory to predict pain at 1 year after total knee arthroplasty. Knee, 2021, 32: 194-200.
10.	孙欣, 历广招, 孙一诺, 等. 全膝关节置换术后患者慢性疼痛的研究进展. 解放军护理杂志, 2020, 37(10): 71-73.
11.	Crombie IK, Davies HT, Macrae WA. Cut and thrust: antecedent surgery and trauma among patients attending a chronic pain clinic. PAIN, 1998, 76(1/2): 167-171.
12.	Hofmann S, Seitlinger G, Djahani O, et al. The painful knee after TKA: a diagnostic algorithm for failure analysis. Knee Surg Sports Traumatol Arthrosc, 2011, 19(9): 1442-1452.
13.	吕岩, 程建国, 樊碧发, 等. ICD-11 慢性疼痛分类中文编译版. 中国疼痛医学杂志, 2018, 24(11): 801-805.
14.	Fregoso G, Wang A, Tseng K, et al. Transition from acute to chronic pain: evaluating risk for chronic postsurgical pain. Pain Physician, 2019, 22(5): 479-488.
15.	Treede RD, Rief W, Barke A, et al. Chronic pain as a symptom or a disease: the IASP classification of chronic pain for the international classification of diseases (ICD-11). Pain, 2019, 160(1): 19-27.
16.	Nicholas M, Vlaeyen JWS, Rief W, et al. The IASP classification of chronic pain for ICD-11: chronic primary pain. Pain, 2019, 160(1): 28-37.
17.	Glare P, Aubrey KR, Myles PS. Transition from acute to chronic pain after surgery. Lancet, 2019, 393(10180): 1537-1546.
18.	Cohen SP, Vase L, Hooten WM. Chronic pain: an update on burden, best practices, and new advances. Lancet, 2021, 397(10289): 2082-2097.
19.	Khalid S, Mohammad HR, Gooberman-Hill R, et al. Post-operative determinants of chronic pain after primary knee replacement surgery: analysis of data on 258, 386 patients from the National Joint Registry for England, Wales, Northern Ireland and the Isle of Man (NJR). Osteoarthr Cartil Open, 2021, 3(1): 100139.
20.	Richebé P, Capdevila X, Rivat C. Persistent postsurgical pain: pathophysiology and preventative pharmacologic considerations. Anesthesiology, 2018, 129(3): 590-607.
21.	Bonnin MP, Basiglini L, Archbold HA. What are the factors of residual pain after uncomplicated TKA?. Knee Surg Sports Traumatol Arthrosc, 2011, 19(9): 1411-1417.
22.	Bin Abd Razak HR, Tan CS, Chen YJ, et al. Age and preoperative knee society score are significant predictors of outcomes among asians following total knee arthroplasty. J Bone Joint Surg Am, 2016, 98(9): 735-741.
23.	Liu YM, Feng Y, Liu YQ, et al. Chinese association for the study of pain: expert consensus on chronic postsurgical pain. World J Clin Cases, 2021, 9(9): 2090-2099.
24.	王峰, 鞠晓聪, 王冰, 等. 外侧单髁和全膝关节置换治疗外侧单间室膝骨关节炎. 中国组织工程研究, 2021, 25(12): 1836-1841.
25.	Wilson HA, Middleton R, Abram SGF, et al. Patient relevant outcomes of unicompartmental versus total knee replacement: systematic review and meta-analysis. BMJ, 2019: l352.
26.	Wu CL, Raja SN. Treatment of acute postoperative pain. Lancet, 2011, 377(9784): 2215-2225.
27.	鲁小丹, 卫建华, 沈建通, 等. 预测模型系统评价的制作方法与步骤. 中国循证医学杂志, 2023, 23(5): 602-609.
28.	陈香萍, 张奕, 庄一渝, 等. PROBAST: 诊断或预后多因素预测模型研究偏倚风险的评估工具. 中国循证医学杂志, 2020, 20(6): 737-744.
29.	王子怡, 卢存存, 张晶磊, 等. 个体预后与诊断多变量预测模型系统评价/Meta 分析报告规范(TRIPOD-SRMA)解读. 中国循证医学杂志, 2024, 24(2): 202-210.
30.	罗海萍, 田梅梅. 全膝关节置换术后病人慢性疼痛的影响因素分析及预测模型构建. 护理研究, 2022, 36(7): 1281-1286.
31.	万国立, 史晨辉, 王维山, 等. 全膝关节置换后慢性疼痛影响因素的回顾性分析. 中国组织工程研究, 2023, 27(4): 558-564.
32.	陈诚, 吴战坡, 丁祖运, 等. 老年患者行全膝关节置换术后慢性疼痛的危险因素及预测模型的建立. 转化医学杂志, 2024, 13(11): 1880-1884.
33.	Yang J, Gao H, Wang C, et al. Related factors and risk prediction of chronic pain after knee replacement. Ann Ital Chir, 2024, 95(5): 934-943.
34.	Qian J, Wang X. Construction and validation of chronic pain prediction model after total knee arthroplasty. Pak J Med Sci, 2024, 40(4): 657-662.
35.	Zhao S, Hu Y, Li Y, et al. Construction and validation of nomogram model for chronic postsurgical pain in patients after total knee arthroplasty: a retrospective study. Pak J Med Sci, 2025, 41(3): 780-787.
36.	高静, 陈琼华, 何晓铭, 等. 基于中医证型的人工全膝关节置换术后慢性疼痛的危险因素探究及风险预测模型构建. 广州中医药大学学报, 2023, 40(3): 549-555.
37.	Yan Z, Liu M, Wang X, et al. Construction and validation of machine learning algorithms to predict chronic post-surgical pain among patients undergoing total knee arthroplasty. Pain Manag Nurs, 2023, 24(6): 627-633.
38.	Ashoorion V, Sadeghirad B, Wang L, et al. Predictors of persistent post-surgical pain following total knee arthroplasty: a systematic review and meta-analysis of observational studies. Pain Med, 2023, 24(4): 369-381.
39.	Carriere JS, Martel MO, Meints SM, et al. What do you expect? Catastrophizing mediates associations between expectancies and pain-facilitatory processes. Eur J Pain, 2019, 23(4): 800-811.
40.	Shim J, Mclernon DJ, Hamilton D, et al. Development of a clinical risk score for pain and function following total knee arthroplasty: results from the TRIO study. Rheumatol Adv Pract, 2018, 2(2): rky021.
41.	许汝福. Logistic 回归变量筛选及回归方法选择实例分析. 中国循证医学杂志, 2016, 16(11): 1360-1364.
42.	Chowdhury MZI, Turin TC. Variable selection strategies and its importance in clinical prediction modelling. Fam Med Community Health, 2020, 8(1): e000262.
43.	莫航沣, 陈亚萍, 韩慧, 等. 临床预测模型研究方法与步骤. 中国循证医学杂志, 2024, 24(2): 228-236.
44.	Raita Y, Goto T, Faridi MK, et al. Emergency department triage prediction of clinical outcomes using machine learning models. Crit Care, 2019, 23(1): 64.
45.	黄光成, 周良, 石建伟, 等. 机器学习算法在疾病风险预测中的应用与比较. 中国卫生资源, 2020, 23(4): 432-436.
46.	Macrae WA. Chronic post-surgical pain: 10 years on. Br J Anaesth, 2008, 101(1): 77-86.
47.	陈茹, 王胜锋, 周家琛, 等. 预测模型研究的偏倚风险和适用性评估工具解读. 中华流行病学杂志, 2020, 41(5): 776-781.
48.	Betz U, Clarius M, Krieger M, et al. Time-dependent prediction models for individual prognosis of chronic postsurgical pain following knee replacement based on an extensive multivariable data set. J Clin Med, 2024, 13(3): 862.
49.	Shu B, Xu F, Zheng X, et al. Change in perioperative neutrophil-lymphocyte ratio as a potential predictive biomarker for chronic postsurgical pain and quality of life: an ambispective observational cohort study. Front Immunol, 2023, 14: 1177285.
50.	兰岭, 黄宇光, 申乐. 术后慢性疼痛相关炎症反应与免疫调节机制研究进展. 中国疼痛医学杂志, 2017, 23(3): 161-164.

1. Jaffe WL, Dundon JM, Camus T. Alignment and balance methods in total knee arthroplasty. J Am Acad Orthop Surg, 2018, 26(20): 709-716.
2. 周宗科, 翁习生, 曲铁兵, 等. 中国髋、膝关节置换术加速康复——围术期管理策略专家共识. 中华骨与关节外科杂志, 2016, 9(1): 1-9.
3. Safiri S, Kolahi A, Smith E, et al. Global, regional and national burden of osteoarthritis 1990-2017: a systematic analysis of the global burden of disease study 2017. Ann Rheum Dis, 2020, 79(6): 819-828.
4. Damen J, van Rijn RM, Emans PJ, et al. Prevalence and development of hip and knee osteoarthritis according to American College of Rheumatology criteria in the CHECK cohort. Arthritis Res Ther, 2019, 21(1): 4.
5. Lo CWT, Tsang WWN, Yan CH, et al. Risk factors for falls in patients with total hip arthroplasty and total knee arthroplasty: a systematic review and meta-analysis. Osteoarthritis Cartilage, 2019, 27(7): 979-993.
6. Lee CR, Kim CW, Park DH, et al. Risk of infection after septic and aseptic revision total knee arthroplasty: a systematic review. J Bone Joint Surg Am, 2023, 105(20): 1630-1637.
7. 薛照静, 黄宇光, 赵晶, 等. 慢性术后疼痛研究进展. 中国疼痛医学杂志, 2013, 19(11): 685-689.
8. Tang S, Jin Y, Hou Y, et al. Predictors of chronic pain in elderly patients undergoing total knee and hip arthroplasty: a prospective observational study. J Arthroplasty, 2023, 38(9): 1693-1699.
9. Imai R, Nishigami T, Kubo T, et al. Using a postoperative pain trajectory to predict pain at 1 year after total knee arthroplasty. Knee, 2021, 32: 194-200.
10. 孙欣, 历广招, 孙一诺, 等. 全膝关节置换术后患者慢性疼痛的研究进展. 解放军护理杂志, 2020, 37(10): 71-73.
11. Crombie IK, Davies HT, Macrae WA. Cut and thrust: antecedent surgery and trauma among patients attending a chronic pain clinic. PAIN, 1998, 76(1/2): 167-171.
12. Hofmann S, Seitlinger G, Djahani O, et al. The painful knee after TKA: a diagnostic algorithm for failure analysis. Knee Surg Sports Traumatol Arthrosc, 2011, 19(9): 1442-1452.
13. 吕岩, 程建国, 樊碧发, 等. ICD-11 慢性疼痛分类中文编译版. 中国疼痛医学杂志, 2018, 24(11): 801-805.
14. Fregoso G, Wang A, Tseng K, et al. Transition from acute to chronic pain: evaluating risk for chronic postsurgical pain. Pain Physician, 2019, 22(5): 479-488.
15. Treede RD, Rief W, Barke A, et al. Chronic pain as a symptom or a disease: the IASP classification of chronic pain for the international classification of diseases (ICD-11). Pain, 2019, 160(1): 19-27.
16. Nicholas M, Vlaeyen JWS, Rief W, et al. The IASP classification of chronic pain for ICD-11: chronic primary pain. Pain, 2019, 160(1): 28-37.
17. Glare P, Aubrey KR, Myles PS. Transition from acute to chronic pain after surgery. Lancet, 2019, 393(10180): 1537-1546.
18. Cohen SP, Vase L, Hooten WM. Chronic pain: an update on burden, best practices, and new advances. Lancet, 2021, 397(10289): 2082-2097.
19. Khalid S, Mohammad HR, Gooberman-Hill R, et al. Post-operative determinants of chronic pain after primary knee replacement surgery: analysis of data on 258, 386 patients from the National Joint Registry for England, Wales, Northern Ireland and the Isle of Man (NJR). Osteoarthr Cartil Open, 2021, 3(1): 100139.
20. Richebé P, Capdevila X, Rivat C. Persistent postsurgical pain: pathophysiology and preventative pharmacologic considerations. Anesthesiology, 2018, 129(3): 590-607.
21. Bonnin MP, Basiglini L, Archbold HA. What are the factors of residual pain after uncomplicated TKA?. Knee Surg Sports Traumatol Arthrosc, 2011, 19(9): 1411-1417.
22. Bin Abd Razak HR, Tan CS, Chen YJ, et al. Age and preoperative knee society score are significant predictors of outcomes among asians following total knee arthroplasty. J Bone Joint Surg Am, 2016, 98(9): 735-741.
23. Liu YM, Feng Y, Liu YQ, et al. Chinese association for the study of pain: expert consensus on chronic postsurgical pain. World J Clin Cases, 2021, 9(9): 2090-2099.
24. 王峰, 鞠晓聪, 王冰, 等. 外侧单髁和全膝关节置换治疗外侧单间室膝骨关节炎. 中国组织工程研究, 2021, 25(12): 1836-1841.
25. Wilson HA, Middleton R, Abram SGF, et al. Patient relevant outcomes of unicompartmental versus total knee replacement: systematic review and meta-analysis. BMJ, 2019: l352.
26. Wu CL, Raja SN. Treatment of acute postoperative pain. Lancet, 2011, 377(9784): 2215-2225.
27. 鲁小丹, 卫建华, 沈建通, 等. 预测模型系统评价的制作方法与步骤. 中国循证医学杂志, 2023, 23(5): 602-609.
28. 陈香萍, 张奕, 庄一渝, 等. PROBAST: 诊断或预后多因素预测模型研究偏倚风险的评估工具. 中国循证医学杂志, 2020, 20(6): 737-744.
29. 王子怡, 卢存存, 张晶磊, 等. 个体预后与诊断多变量预测模型系统评价/Meta 分析报告规范(TRIPOD-SRMA)解读. 中国循证医学杂志, 2024, 24(2): 202-210.
30. 罗海萍, 田梅梅. 全膝关节置换术后病人慢性疼痛的影响因素分析及预测模型构建. 护理研究, 2022, 36(7): 1281-1286.
31. 万国立, 史晨辉, 王维山, 等. 全膝关节置换后慢性疼痛影响因素的回顾性分析. 中国组织工程研究, 2023, 27(4): 558-564.
32. 陈诚, 吴战坡, 丁祖运, 等. 老年患者行全膝关节置换术后慢性疼痛的危险因素及预测模型的建立. 转化医学杂志, 2024, 13(11): 1880-1884.
33. Yang J, Gao H, Wang C, et al. Related factors and risk prediction of chronic pain after knee replacement. Ann Ital Chir, 2024, 95(5): 934-943.
34. Qian J, Wang X. Construction and validation of chronic pain prediction model after total knee arthroplasty. Pak J Med Sci, 2024, 40(4): 657-662.
35. Zhao S, Hu Y, Li Y, et al. Construction and validation of nomogram model for chronic postsurgical pain in patients after total knee arthroplasty: a retrospective study. Pak J Med Sci, 2025, 41(3): 780-787.
36. 高静, 陈琼华, 何晓铭, 等. 基于中医证型的人工全膝关节置换术后慢性疼痛的危险因素探究及风险预测模型构建. 广州中医药大学学报, 2023, 40(3): 549-555.
37. Yan Z, Liu M, Wang X, et al. Construction and validation of machine learning algorithms to predict chronic post-surgical pain among patients undergoing total knee arthroplasty. Pain Manag Nurs, 2023, 24(6): 627-633.
38. Ashoorion V, Sadeghirad B, Wang L, et al. Predictors of persistent post-surgical pain following total knee arthroplasty: a systematic review and meta-analysis of observational studies. Pain Med, 2023, 24(4): 369-381.
39. Carriere JS, Martel MO, Meints SM, et al. What do you expect? Catastrophizing mediates associations between expectancies and pain-facilitatory processes. Eur J Pain, 2019, 23(4): 800-811.
40. Shim J, Mclernon DJ, Hamilton D, et al. Development of a clinical risk score for pain and function following total knee arthroplasty: results from the TRIO study. Rheumatol Adv Pract, 2018, 2(2): rky021.
41. 许汝福. Logistic 回归变量筛选及回归方法选择实例分析. 中国循证医学杂志, 2016, 16(11): 1360-1364.
42. Chowdhury MZI, Turin TC. Variable selection strategies and its importance in clinical prediction modelling. Fam Med Community Health, 2020, 8(1): e000262.
43. 莫航沣, 陈亚萍, 韩慧, 等. 临床预测模型研究方法与步骤. 中国循证医学杂志, 2024, 24(2): 228-236.
44. Raita Y, Goto T, Faridi MK, et al. Emergency department triage prediction of clinical outcomes using machine learning models. Crit Care, 2019, 23(1): 64.
45. 黄光成, 周良, 石建伟, 等. 机器学习算法在疾病风险预测中的应用与比较. 中国卫生资源, 2020, 23(4): 432-436.
46. Macrae WA. Chronic post-surgical pain: 10 years on. Br J Anaesth, 2008, 101(1): 77-86.
47. 陈茹, 王胜锋, 周家琛, 等. 预测模型研究的偏倚风险和适用性评估工具解读. 中华流行病学杂志, 2020, 41(5): 776-781.
48. Betz U, Clarius M, Krieger M, et al. Time-dependent prediction models for individual prognosis of chronic postsurgical pain following knee replacement based on an extensive multivariable data set. J Clin Med, 2024, 13(3): 862.
49. Shu B, Xu F, Zheng X, et al. Change in perioperative neutrophil-lymphocyte ratio as a potential predictive biomarker for chronic postsurgical pain and quality of life: an ambispective observational cohort study. Front Immunol, 2023, 14: 1177285.
50. 兰岭, 黄宇光, 申乐. 术后慢性疼痛相关炎症反应与免疫调节机制研究进展. 中国疼痛医学杂志, 2017, 23(3): 161-164.

West China Medical Journal

Latest ArticlesSystematic review of predictive models for postoperative chronic pain risk in patients undergoing knee arthroplasty

Abstract Full text Figures/Tables Video References Cited by

Format

Content