Skip to main content

The application of Caprini Risk Assessment Model in evaluation of deep vein thrombosis for patients with end-stage osteoarthritis before arthroplasty



Deep vein thrombosis (DVT) was a fatal complication of knee arthroplasty. We had neglected the risk factors of preoperative DVT although patients undergoing knee arthroplasty were at high risk for VTE. This study was to determine the risk factors for preoperative DVT and application of Caprini Risk Assessment Model (RAM) in patients with end-stage knee osteoarthritis (OA).


We retrospectively analyzed 1808 cases with end-stage knee OA undergoing primary knee arthroplasty from May 2015 to December 2020. Based on the results of ultrasonography in lower extremities, all patients were divided into non-DVT group and DVT group. Distribution of risk factors and risk levels were compared using χ2 test between two groups. Binary logistic regression analysis was used to determine the risk factors and relationship of risk levels and preoperative DVT.


The incidence of preoperative DVT was 5.53% (n = 100). Distribution of the study population by risk level was low, 4.09%; moderate, 23.95%; high, 66.98%; and highest 4.98%. Female (P = 0.002), age (P = 0.012), swollen legs (P = 0.035) and history of blood clots (P < 0.001) was correlated with preoperative DVT. Difference among four risk levels was significant (P = 0.007). Patients with highest risk level had statistically significant association with preoperative DVT (P = 0.005, OR = 2.93, 95%CI [1.375–6.246]).


The incidence of preoperative DVT was 5.53% in end-stage knee OA patients. The gender (female) and age were independent risk factors for preoperative DVT. The risk group classification by Caprini RAM was significantly associated with preoperative DVT. The usage of Caprini RAM before knee arthroplasty may be beneficial for prophylaxis of DVT.

Peer Review reports


Venous thromboembolism (VTE), including deep vein thrombosis (DVT) and pulmonary embolism (PE), representing one of the major complications after knee arthroplasty, elevates morbidity and mortality during the perioperative period [1, 2]. It has been reported that the incidence of asymptomatic DVT after total knee arthroplasty (TKA) is 40–85% and the incidence of fatal PE is 0.87%-1.99% without drug intervention [3]. Numerous literatures focused on prevention and treatment for DVT after TKA [4,5,6]. Recently, several studies paid attention to the preoperative DVT in elderly patients with knee osteoarthritis (OA) who have severe disability [7, 8]. The incidence of preoperative DVT in TKA patients ranged from 6.7% to 17.9% [8,9,10]. Patients with DVT underwent surgical procedures like trauma or immobilization, DVT may extend, develop or even detach, resulting in PE, even death [7]. Given to the grave consequences of preoperative DVT, we screened all OA patients underwent TKA in our center with lower extremity venous ultrasound before operations to avoid the venture. However, preoperative ultrasound screen would increase patients’ medical costs and prolong physician’s operating time.

The Caprini score was originally proposed in the 1990s which provided an individualized and adequate VTE prophylaxis risk assessment model [11]. The score assigned points based on more than 20 risk factors taken from person’s history as well as their current health, in which a high score classifies a patient at a higher risk. The Caprini risk assessment model (RAM) has been verified by more than 100 clinical trials and 250 000 patients worldwide. Moreover, rational treatment regimens that depend on Caprini RAM were precisely accomplished [12]. In orthopedic surgery, especially joint arthroplasty and lower limb fractures, the Caprini RAM has been extensively used to evaluate the risk of postoperative DVT and provide the basis for precision therapy [13,14,15]. Nevertheless, the Caprini RAM has not been used to evaluate the quantitative risk until this study. The Caprini RAM also periodically updated based on evolution of the pathophysiology and risk factors of VTE [12, 16, 17].

End-stage knee OA patients were characterized with pain, old age and severe disability which lead to higher risk of DVT comparing to other diseases. Thus, our joint diseases center applied the Caprini RAM (2013version) to assess the risk of VTE in all hospitalized OA patients undergoing knee arthroplasty. The purpose of this study was to assess the effectiveness of the Caprini RAM in evaluating the risk of preoperative DVT and screen out the high risk factors in hospitalized OA patient undergoing knee arthroplasty.

Materials and methods

With the approval of Ethics Committee in Clinical Institution of Nanjing Drum Tower Hospital, a retrospective review of inpatient database from Department of Sports Medicine and Adult Reconstructive Surgery was performed to identify patients underwent TKA or unilateral knee arthroplasty (UKA) from May 2015 to December 2020. Firstly, we included cases according to the following criteria: 1) Age > 18 years old; 2) Diagnosed as end-stage knee osteoarthritis; 3) Selective surgery, including TKA or UKA. Secondly, we excluded 178 cases with non-osteoarthritis underwent knee arthroplasty, 54 cases received non-arthroplasty procedure, such as arthroscopy, osteotomy, revision, infection debridement, etc., 13 cases who cannot receive ultrasound screening for thrombosis diagnosing due to various conditions and 23 cases with incomplete data information retention and cannot be retrospectively analyzed for various reasons. Finally, a total of 1808 cases were enrolled. All cases were divided into non-DVT group (n = 1708 cases) and DVT group (n = 100 cases), according to the results of ultrasonography for DVT in bilateral lower extremities. Retrospective Caprini RAM was used for preoperative DVT risk assessment. All methods in this study were in accordance with the relevant regulations and guidelines.

Preoperative DVT assessment

Each patient received preoperative evaluation for DVT within 3 days before surgery. A bedside ultrasound (SonoSite M-Turbo) was utilized on bilateral lower extremities to preclude DVT by a highly skilled sonographer. The following veins including bilateral common iliac vein, femoral vein, superficial femoral vein, popliteal vein, peroneal vein, anterior tibial vein, posterior tibial vein and muscular veins were mainly examined. The criteria for diagnosing DVT were: 1) Failure of full compressibility of venous segment; 2) Absence or abnormal flow on color Doppler and spectral analysis.

Caprini risk assessment

Caprini RAM (2013 Version) was applied in this study [12]. The cumulative risk score and risk level of Caprini risk assessment were retrospectively conducted, based on the inpatient database from Department of Sports Medicine and Adult Reconstructive Surgery. Body mass index (BMI) was automatically calculated by system with documented height (m) and weight (kg) as follows: BMI = weight divided by the square of your height. Risk factors for each patient were scored by the same professional with in-depth training of Caprini RAM and checked by an experienced physician. Each risk factor has different score (Table 3). Then, summed all risk factors scores to determine the risk level. Total score of 0–1, 2, 3–4 and ≥ 5 are defined as low-risk level, moderate-risk level, high-risk level and highest-risk level respectively. The reliability of this kind of retrospective scoring method has been reported in previous research [18].

Statistical analysis

All the data were analyzed with the use of SPSS statistical software 22.0 (USA). Mean ( ±) standard deviation (x ± s) was calculated to describe continuous variables (age, height, weight and BMI) by independent sample t-test. Differences in the percentage of DVT incidence in two groups were compared using a χ2 test. The distribution of the incidence rate of DVT by risk level and the significance of differences was reported using χ2 test. Binary logistic regression analysis was used to determine the risk factors and relationship of risk levels and preoperative DVT. BMI was excluded from the final model since its coefficient estimates was insignificant contributing to the model fit. For risk level logistic regression analysis, risk level was analyzed as an ordinal categorical variable. Due to the distribution of preoperative DVT in low risk level is 0, low and moderate risk level were combined and coded 1, high and highest risk level were coded 2 and 3 respectively. P < 0.05 was considered as significant value.


Information of clinical data

In this retrospective study, a total of 1808 inpatients underwent knee arthroplasty were retrospectively enrolled in this study, with 80.75% cases undergoing TKA surgery, and 19.25% cases undergoing UKA surgery. There are 1421 females and 387 males. The number of females in DVT group is markedly higher than that in non-DVT group (P = 0.002). Age in DVT group was significantly older than that in non-DVT group (71.67 ± 6.75 vs. 68.22 ± 7.65, P < 0.001). There is no significant difference in BMI between DVT group and non-DVT group (26.55 ± 3.79 vs. 27.05 ± 3.85, P = 0.21). The binary logistic regression showed that gender-female and age were independent risk factors for preoperative DVT (P = 0.002, OR = 2.877, 95%CI = 1.473- 5.618; P < 0.001, OR = 1,071, 95%CI = 1.041–1.103). (Table 1).

Table 1 Demographic characteristics of Non-DVT group and DVT group

Incidence and distribution of preoperative DVT

100 patients (5.53%) were diagnosed as DVT before knee arthroplasty. Among them, 12 cases were found thrombosis in bilateral legs; 48 cases had thrombosis in the affected leg (operated leg), and 40 cases in the contralateral leg. For patients with proximal thrombosis, 1 case occurred in iliac vein, 2 cases occurred in femoral vein, 2 cases occurred in popliteal vein and 1 case had mixed thrombosis in both popliteal and muscular veins. While, for patients with distal thrombosis, majority of cases (n = 93) occurred in muscular veins, and 1 case occurred in both muscular and peroneal veins (Table 2).

Table 2 Locations of DVT

Comparison of cumulative score and risk factors between non-DVT and DVT groups

The range of cumulative score of the study population is from 0 to 9. Distribution by each cumulative score was 0 (0.11%), 1 (3.98%), 2 (23.95%), 3 (49.72%), 4 (17.26%), 5 (2.93%), 6 (1.33%), 7 (0.50%), 8 (0%) and 9 (0.22%) respectively. The detailed distribution of cases and incidence rate of preoperative DVT is illustrated in Fig. 1. The growth of preoperative DVT appears to accelerate according to their cumulative risk score, especially significant for cumulative risk scores of 6–9. Meanwhile, the mean of cumulative score in DVT group is mildly higher than non-DVT group (3.28 ± 1.33 vs. 2.96 ± 0.96, P = 0.022) (Table 2).

Fig. 1
figure 1

Distribution of cumulative Caprini score

Among 37 risk factors listed in the Caprini risk assessment mode, age (P = 0.012), swollen legs (P = 0.035) and history of blood clots (P < 0.001) were associated significantly with increased risk of DVT incidence before knee arthroplasty (Table 3). The incidence rate increased with age significantly (0.00% in ≤ 40 years, 2.43% in 41-60 years, 5.26% in 61–74 years and 8.31% in ≥ 75 years, P = 0.012).

Table 3 Comparison of caprini risk factors between non-DVT group and DVT group

Comparison of risk levels between non-DVT and DVT groups

The distribution by risk levels for these 1808 cases was low (4.09%), moderate (23.95%), high (66.98%) and highest (4.98%). Figure 2 demonstrated the distribution of preoperative DVT in different risk levels. The incidence of preoperative DVT was correlated with increase of risk level. In the highest risk level, 12.22% cases acquired DVT; patients with high and moderate risk level, 5.45%; and patients with low risk, 0%. The difference among 4 risk levels was statistically significant (P = 0.07) (Table 4). Additionally, in the low risk group, the preoperative DVT rate were significant lower than other groups (P = 0.034), while that in the highest risk group were significant higher than others (P = 0,004).

Fig. 2
figure 2

Incidence rate of preoperative DVT by risk level of Caprini RAM

Table 4 Comparison of caprini risk level between non-DVT and DVT groups

The binary logistic regression in Table 5 showed that compared to low and moderate risk levels, cases in high risk level had mildly higher risk (1.213 times) of preoperative DVT (p = 0.436, OR-1.213, 95%CI = 0.746–1.973). While, cases in highest had a significantly higher risk (2.93 times) acquiring DVT before knee arthroplasty (P = 0.005, OR = 2.93, 95%CI = 1.375–6.246).

Table 5 Binary regression analysis of risk levels


Knee arthroplasty has been proven to be safe, cost effective, and widely undertaken for improving quality of life in patients with end-stage knee osteoarthritis [19]. Age, obesity, metabolic syndrome, tourniquet use and other risk factors have been found to be associated with DVT after TKA [4, 20, 21]. However, patients undergoing TKA were at high risk for VTE [7]. End-stage OA patients characterized with pain and high age could increase the risk for DVT [22, 23]. To survey the incidence of surgery-related DVT, the incidence of patients showing DVT before surgery must be subtracted from the total of the incidences before and after surgery. In present study, the incidence of preoperative DVT in end-stage knee OA patient underwent knee arthroplasty was 5.53% which was similar to the preceding literatures [7, 8]. Compared to the 17.9% incidence reported by Wakabayashi et al. [9], our incidence of preoperative DVT was significantly lower. However, it should be noted that subjects with rheumatoid arthritis (RA) accounted for 34% of the sample size in their study, as we know, patients with RA were more prone to DVT comparing to OA patients due to chronical inflammation [24, 25]. In this study, the Caprini RAM (2013 Version) was used to conduct preoperative VTE score and risk grade classification for patients with end-stage OA. The Caprini RAM scores in DVT group were significantly higher than those in non-DVT group (3.28 ± 1.33vs2.96 ± 0.96, P = 0.022). Besides, we studied the incidence of preoperative DVT in patients with different Caprini score and levels. The preoperative DVT rates increased with the improvement of Caprini RAM score and risk level. Furthermore, the preoperative DVT incidence was significantly correlated with Caprini RAM risk level (P = 0.007). The age was an independent risk factor for preoperative DVT (p < 0.001) in Caprini RAM. Different age stratification got different score. After age stratification, the correlation was consistent (p = 0.012). Among 37 risk factors listed in the Caprini risk assessment mode, age (P = 0.012), swollen legs (P = 0.035) and history of blood clots (P < 0.001) were associated significantly with increased risk of DVT incidence before knee arthroplasty. Commonly, elderly patients were more vulnerable to have high blood viscosity, vascular sclerosis, and poor venous valve function, which lead to a high incidence of DVT [26]. As we had known, unilateral limb swelling would raise the suspicion of DVT [27]. In our study, 9 cases (0.53%) with history of blood clots in non-DVT group and 7 cases (7%) in DVT group, history of blood clots was significantly associated with DVT. In our study, the risk of preoperative DVT in the low risk group was significantly lower than that in other groups (P = 0.034), while that in the highest risk group was significantly higher than others (P = 0.004). These results all verified the validity of Caprini RAM to evaluate preoperative DVT risk in end-stage OA patients.

As far as we know, proximal DVT was more prone to cause adverse events (potentially fatal) than distal DVT [28, 29]. In our study, a total of 6 cases (6%) were found to be proximal DVT and positive treatment measures were taken, none of them had serious consequences. Although gender was not included in Caprini RAM, our research addressed that female was an independent risk factor for preoperative DVT, indicating that clinical workers should probably pay more attention to the DVT occurrence for female patients before knee arthroplasty. In previous studies [28, 29], gender (female) seemed to be a risk factor for DVT, however, the association had no statistical significance due to their limited sample sizes. It’s worth noting that our sample size was more than 10 times than theirs, which providing a more solid support for our study result and suggestion for clinical application.

The Caprini RAM had been evaluated to be useful not only for surgical patients but also in medical patients [30,31,32]. In this study, Caprini RAM was used for preoperative DVT evaluation in the end-stage knee OA patients undergoing knee arthroplasty for the first time. This work verified the effective function of Caprini RAM in preoperative DVT risk screening for patients with TKA or UKA. Nonetheless, this study has limitations inherent to retrospective single-center study. There are still other confounders not introduced into the analysis due to the retrospective nature of this study. Also, we only tested for preoperative DVT by using Doppler ultrasonic, which may lead to missed subsequent DVT. However, previous studies had reported that Doppler ultrasonic could replace venography as a screening tool for DVT. Moreover, all ultrasound screening in our study was performed by a greatly skilled physician who has experience of thousands cases of thrombus screening. Meanwhile, it is one-sided to analyze the incidence of preoperative DVT only via Caprini RAM. In the future, we can develop a more comprehensive and accurate evaluation system for preoperative DVT, combining physical questionnaires with routine examination, such as blood examination and other relevant data.


In conclusion, this study evaluated the incidence of preoperative DVT and assessed risk factors by Caprini RAM in end-stage OA patients underwent knee arthroplasty. preoperative DVT was diagnosed in 100 of 1808 (5.33%) patients overall. The Caprini RAM had a significant function in preoperative DVT screening. We found the gender (female) and age were independent risk factors for preoperative DVT in end-stage knee OA patient underwent knee arthroplasty. The risk group classification by Caprini RAM was significantly associated with preoperative DVT. The usage of Caprini RAM before knee arthroplasty may be beneficial for prophylaxis of DVT. We suggested the low-risk group classification by Caprini RAM could be exempted from color doppler ultrasound examination while ultrasound screening was still recommended for the other risk grades, especially for the highest risk grade.

Availability of data and material

The datasets used and/or analyzed during the study are available from the corresponding author on reasonable request.



Body mass index


Confidence interval


Deep vein thrombosis




Odd ratio


Pulmonary embolism


Risk assessment model


Total knee arthroplasty


Unilateral knee arthroplasty


Venous thromboembolism


  1. Fisher WD. Impact of venous thromboembolism on clinical management and therapy after hip and knee arthroplasty. Can J Surg. 2011;54(5):344–51.

    Article  Google Scholar 

  2. Memtsoudis SG, Della Valle AG, Besculides MC, Esposito M, Koulouvaris P, Salvati EA. Risk factors for perioperative mortality after lower extremity arthroplasty: a population-based study of 6,901,324 patient discharges. J Arthroplasty. 2010;25(1):19–26.

    Article  Google Scholar 

  3. Bala A, Huddleston JI 3rd, Goodman SB, Maloney WJ, Amanatullah DF. Venous Thromboembolism Prophylaxis After TKA: Aspirin, Warfarin, Enoxaparin, or Factor Xa Inhibitors? Clin Orthop Relat Res. 2017;475(9):2205–13.

    Article  Google Scholar 

  4. Song K, Rong Z, Yao Y, Shen Y, Zheng M, Jiang Q. Metabolic Syndrome and Deep Vein Thrombosis After Total Knee and Hip Arthroplasty. J Arthroplasty. 2016;31(6):1322–5.

    Article  Google Scholar 

  5. Snyder MA, Sympson AN, Scheuerman CM, Gregg JL, Hussain LR. Efficacy in Deep Vein Thrombosis Prevention With Extended Mechanical Compression Device Therapy and Prophylactic Aspirin Following Total Knee Arthroplasty: A Randomized Control Trial. J Arthroplasty. 2017;32(5):1478–82.

    Article  Google Scholar 

  6. Faour M, Piuzzi NS, Brigati DP, Klika AK, Mont MA, Barsoum WK, et al. Low-Dose Aspirin Is Safe and Effective for Venous Thromboembolism Prophylaxis Following Total Knee Arthroplasty. J Arthroplasty. 2018;33(7s):S131–5.

    Article  Google Scholar 

  7. Xiong X, Cheng B. Preoperative risk factors for deep vein thrombosis in knee osteoarthritis patients undergoing total knee arthroplasty. J Orthop Sci. 2021;S0949-2658(21):00344-4.

  8. Jiang T, Yao Y, Xu X, Song K, Pan P, Chen D, et al. Prevalence and Risk Factors of Preoperative Deep Vein Thrombosis in Patients with End-Stage Knee Osteoarthritis. Ann Vasc Surg. 2020;64:175–80.

    Article  Google Scholar 

  9. Wakabayashi H, Hasegawa M, Niimi R, Yamaguchi T, Naito Y, Sudo A. The risk factor of preoperative deep vein thrombosis in patients undergoing total knee arthroplasty. J Orthop Sci. 2017;22(4):698–702.

    Article  Google Scholar 

  10. Watanabe H, Sekiya H, Kariya Y, Hoshino Y, Sugimoto H, Hayasaka S. The incidence of venous thromboembolism before and after total knee arthroplasty using 16-row multidetector computed tomography. J Arthroplasty. 2011;26(8):1488–93.

    Article  Google Scholar 

  11. Arcelus JI, Candocia S, Traverso CI, Fabrega F, Caprini JA, Hasty JH. Venous thromboembolism prophylaxis and risk assessment in medical patients. Semin Thromb Hemost. 1991;17(Suppl 3):313–8.

    PubMed  Google Scholar 

  12. Cronin M, Dengler N, Krauss ES, Segal A, Wei N, Daly M, et al. Completion of the Updated Caprini Risk Assessment Model (2013 Version). Clin Appl Thromb Hemost. 2019;25:1076029619838052.

    Article  Google Scholar 

  13. Krauss ES, Segal A, Cronin M, Dengler N, Lesser ML, Ahn S, et al. Implementation and Validation of the 2013 Caprini Score for Risk Stratification of Arthroplasty Patients in the Prevention of Venous Thrombosis. Clin Appl Thromb Hemost. 2019;25:1076029619838066.

    Article  Google Scholar 

  14. Gold PA, Ng TY, Coury JR, Garbarino LJ, Sodhi N, Mont MA, et al. Can the Caprini score predict thromboembolism and guide pharmacologic prophylaxis after primary joint arthroplasty? J Orthop. 2020;21:345–9.

    Article  Google Scholar 

  15. Dashe J, Parisien RL, Pina M, De Giacomo AF, Tornetta P 3rd. Is the Caprini Score Predictive of Venothromboembolism Events in Orthopaedic Fracture Patients? J Orthop Trauma. 2019;33(6):269–75.

    Article  Google Scholar 

  16. Caprini JA. Thrombosis risk assessment as a guide to quality patient care. Dis Mon. 2005;51(2–3):70–8.

    Article  Google Scholar 

  17. Caprini JA. Risk assessment as a guide for the prevention of the many faces of venous thromboembolism. Am J Surg. 2010;199(1 Suppl):S3-10.

    Article  Google Scholar 

  18. Bahl V, Hu HM, Henke PK, Wakefield TW, Campbell DA Jr, Caprini JA. A validation study of a retrospective venous thromboembolism risk scoring method. Ann Surg. 2010;251(2):344–50.

    Article  Google Scholar 

  19. Kurtz SM, Ong KL, Lau E, Bozic KJ. Impact of the economic downturn on total joint replacement demand in the United States: updated projections to 2021. J Bone Joint Surg Am. 2014;96(8):624–30.

    Article  Google Scholar 

  20. Zhang H, Mao P, Wang C, Chen D, Xu Z, Shi D, et al. Incidence and risk factors of deep vein thrombosis (DVT) after total hip or knee arthroplasty: a retrospective study with routinely applied venography. Blood Coagul Fibrinolysis. 2017;28(2):126–33.

    Article  Google Scholar 

  21. Tai TW, Lin CJ, Jou IM, Chang CW, Lai KA, Yang CY. Tourniquet use in total knee arthroplasty: a meta-analysis. Knee Surg Sports Traumatol Arthrosc. 2011;19(7):1121–30.

    Article  Google Scholar 

  22. Yao Y, Qiao L, Song K, Xu X, Shi D, Xu Z, et al. Preoperative Evaluation of Soleal Vein Diameter by Ultrasound Is Beneficial for Prophylaxis of Deep Vein Thrombosis after Total Knee or Hip Arthroplasty. Biomed Res Int. 2018;2018:3417648.

    PubMed  PubMed Central  Google Scholar 

  23. Kesieme E, Kesieme C, Jebbin N, Irekpita E, Dongo A. Deep vein thrombosis: a clinical review. Journal of blood medicine. 2011;2:59–69.

    Article  Google Scholar 

  24. Choi HK, Rho YH, Zhu Y, Cea-Soriano L, Aviña-Zubieta JA, Zhang Y. The risk of pulmonary embolism and deep vein thrombosis in rheumatoid arthritis: a UK population-based outpatient cohort study. Ann Rheum Dis. 2013;72(7):1182–7.

    Article  Google Scholar 

  25. Ravi B, Escott B, Shah PS, Jenkinson R, Chahal J, Bogoch E, et al. A systematic review and meta-analysis comparing complications following total joint arthroplasty for rheumatoid arthritis versus for osteoarthritis. Arthritis Rheum. 2012;64(12):3839–49.

    Article  Google Scholar 

  26. Paydar S, Sabetian G, Khalili H, Fallahi J, Tahami M, Ziaian B, et al. Management of Deep Vein Thrombosis (DVT) Prophylaxis in Trauma Patients. Bull Emerg Trauma. 2016;4(1):1–7.

    Article  Google Scholar 

  27. Talbot R, Andrews J, Munns J. Ruptured abdominal aortic aneurysm presenting as acute unilateral leg swelling--not all swelling below the knee is DVT. BMJ Case Rep. 2012:bcr0220125897.

  28. Smith EB, Parvizi J, Purtill JJ. Delayed surgery for patients with femur and hip fractures-risk of deep venous thrombosis. J Trauma. 2011;70(6):E113–6.

    PubMed  Google Scholar 

  29. Cho YH, Byun YS, Jeong DG, Han IH, Park YB. Preoperative Incidence of Deep Vein Thrombosis after Hip Fractures in Korean. Clin Orthop Surg. 2015;7(3):298–302.

    Article  Google Scholar 

  30. Pannucci CJ, Swistun L, MacDonald JK, Henke PK, Brooke BS. Individualized Venous Thromboembolism Risk Stratification Using the 2005 Caprini Score to Identify the Benefits and Harms of Chemoprophylaxis in Surgical Patients: A Meta-analysis. Ann Surg. 2017;265(6):1094–103.

    Article  Google Scholar 

  31. Tafur AJ, Arcelus JI. Caprini Score in Hospitalized Medical Patients. Am J Med. 2016;129(10): e265.

    Article  Google Scholar 

  32. Zhou H, Hu Y, Li X, Wang L, Wang M, Xiao J, et al. Assessment of the Risk of Venous Thromboembolism in Medical Inpatients using the Padua Prediction Score and Caprini Risk Assessment Model. J Atheroscler Thromb. 2018;25(11):1091–104.

    Article  Google Scholar 

Download references


The authors thank Dr Xia Sun (Department of Oncology, the Affiliated Jiangyin Hospital of Southeast University Medical College, China.) for English editing.


This work was supported by Key Program of NSFC (81730067), Major Project of NSFC (81991514), Jiangsu Provincial Key Medical Center Foundation, Jiangsu Provincial Medical Outstanding Talent Foundation, Jiangsu Provincial Medical Youth Talent Foundation and Jiangsu Provincial Key Medical Talent Foundation. the Fundamental Research Funds for the Central Universities (14380493, 14380494).

Author information

Authors and Affiliations



Qing Jiang and Xiaotao Wu contributed substantially to the conception of the study. Yao Yao, Jun Lu, Dongmei Ai provided the clinical data. Wei Sun and Dongmei Ai collected and analysed the data. Wei Sun wrote the manuscript with support from Dongmei Ai. Kewei Ren and Huiqing Sun provided critical revision of the article. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Xiaotao Wu or Qing Jiang.

Ethics declarations

Ethics approval and consent to participate

This study was approved by the Ethics Committee in Clinical Institution of Nanjing Drum Tower Hospital. All participating subjects signed a written, informed consent to participate in the study.

Consent for publication

Not applicable.

Competing interests

Qing Jiang is a member of the editorial board (Section Editor) of BMC Musculoskeletal Disorders. The authors declare that they have no competing of interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sun, W., Ai, D., Yao, Y. et al. The application of Caprini Risk Assessment Model in evaluation of deep vein thrombosis for patients with end-stage osteoarthritis before arthroplasty. BMC Musculoskelet Disord 23, 767 (2022).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: