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Incidence of and risk factors for preoperative deep vein thrombosis in elderly patients with end-stage osteoarthritis following total knee arthroplasty: a retrospective cohort study

BMC Musculoskeletal Disorders volume 25, Article number: 754 (2024) Cite this article

Abstract

Background

Deep vein thrombosis (DVT) is a common and serious risk in elderly patients with knee osteoarthritis (OA), making preoperative detection crucial. Despite this, identifying OA patients at high risk for preoperative DVT and appropriately targeting them for venous ultrasound screening remains a challenge. There is limited research-based evidence on the risk factors for preoperative DVT in elderly patients with end-stage OA. We examined the incidence of and risk factors for preoperative DVT in elderly patients with end-stage OA scheduled for total knee arthroplasty.

Methods

We retrospectively analyzed the demographic data (age, sex, body mass index, current smoking, alcohol consumption, walking status, and Barthel index score), medical history, and laboratory test indices of 1411 patients with end-stage OA aged ≥ 60 years scheduled for total knee arthroplasty from January 2015 to December 2018. Risk factors for preoperative DVT were evaluated by univariate and multivariate logistic analyses. Receiver operating characteristic analysis was performed to determine optimal cut-off values.

Results

The incidence of preoperative DVT was 4.5% (63 of 1411 patients). Seven independent risk factors were correlated with preoperative DVT in the multivariate logistic regression: age (odds ratio [OR], 1.073; P = 0.002), D-dimer concentration (OR, 1.173; P = 0.003), hyperlipidemia (OR, 2.038; P = 0.045), atrial fibrillation (OR, 4.004; P = 0.033), chronic renal failure (OR, 6.732; P = 0.008), chronic obstructive pulmonary disease (COPD) (OR, 8.721; P = 0.001), and walking status (wheelchair) (OR, 2.697; P = 0.002). The optimal cut-off values for predicting preoperative DVT were 0.585 µg/mL for the D-dimer concentration (area under the curve [AUC], 0.769; P < 0.001) and 72.5 years for age (AUC, 0.668; P < 0.001).

Conclusion

Among elderly patients with end-stage OA, venous ultrasonography to rule out DVT risk should be prioritized in those with a high D-dimer concentration (> 0.585 µg/mL), high age (> 72.5 years), hyperlipidemia, atrial fibrillation, chronic renal failure, COPD, and walking status (wheelchair).

Peer Review reports

Introduction

Total knee arthroplasty (TKA) has become a widely used surgical treatment for end-stage knee osteoarthritis (OA) during the past decade, significantly improving patients’ quality of life, pain levels, and physical function [1, 2]. However, perioperative complications, particularly the risk of deep vein thrombosis (DVT), remain a significant concern and require further investigation.

DVT is a common complication following TKA. Without prophylaxis, the risk of developing asymptomatic DVT ranges from 35 to 84% [3]. Even with routine thromboprophylaxis, approximately 0.63% of patients still develop symptomatic DVT [4]. Additionally, the incidence of preoperative DVT in patients with OA before undergoing TKA ranges from 2.6 to 17.4% [5,6,7,8]. Notably, preoperative DVT may lead to intraoperative embolus dislodgement. Because fresh blood clots do not adhere tightly to the vessel wall, they may easily dislodge and cause a pulmonary embolism (PE) [9]. Furthermore, preoperative DVT has been linked to an increased risk of postoperative DVT [10]. Therefore, efficient identification of preoperative DVT in patients with knee OA is of particular importance.

Ultrasonography has been suggested as an effective method of preoperative DVT detection [11]. Although ultrasonography is a valuable diagnostic tool, performing ultrasound examinations for preoperative screening in all patients with OA is considered overuse [12]. Patients with OA who are at high risk for DVT should be prioritized for ultrasonography screening. Several studies indicate that those undergoing TKA are more likely to develop preoperative DVT if they have conditions such as rheumatoid arthritis (RA), connective tissue disease, revision TKA, a high D-dimer level (> 0.5 µg/mL), or age of > 75 years [5, 7, 13]. However, there is little research-based evidence on the risk factors for preoperative DVT in elderly patients with end-stage OA, especially those related to patients’ medical history.

Thus, the aim of this study was to investigate the incidence of and risk factors for preoperative DVT in elderly patients with end-stage OA scheduled for TKA. We hypothesized that certain risk factors are significantly associated with preoperative DVT and that identifying these factors will help improve screening and prevention strategies.

Materials and methods

Study participants

This retrospective cohort study was conducted at Peking Union Medical College Hospital from January 2015 to December 2018 and involved 1411 patients with knee OA, selected from a total of 1969 patients. The inclusion criteria were an age ≥ 60 years, end-stage knee OA, and scheduled primary TKA. The exclusion criteria were other types of arthritis (e.g., RA, traumatic osteoarthritis, ankylosing spondylitis, and hemophilic arthritis), absence of lower extremity ultrasonography examination, and incomplete medical records. This study was approved by the Institutional Review Board of Peking Union Medical College Hospital (IRB number: K3692). The research followed the Declaration of Helsinki guidelines, and the ethics committee waived the requirement for informed consent because the study used a retrospective design and the data were anonymized. Figure 1 shows that 1411 patients with end-stage knee OA were finally enrolled in the study.

Fig. 1
figure 1

Flow chart of study inclusion and exclusion criteria

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Data collection

The hospital’s information system was used to obtain the patients’ clinical data, including sex, age, body mass index, current smoking, alcohol consumption, walking status, and Barthel index (BI) score. Walking status included three categories: walking independently, using a mobility aid, and using a wheelchair.

We assessed the patients’ history of illnesses, including hypertension, diabetes, hyperlipidemia, coronary atherosclerotic heart disease, atrial fibrillation (AF), coronary stent implantation, chronic renal failure (CRF), Parkinson’s disease (PD), osteoporosis, depression, arteriosclerosis obliterans, cerebral infarction, lower extremity varicose veins, and chronic obstructive pulmonary disease (COPD).

Several laboratory parameters were measured, including coagulation markers (D-dimer, fibrinogen, international normalized ratio, and activated partial thromboplastin time), routine blood indices (platelets, white blood cells, neutrophils, and hemoglobin), and high-sensitivity C-reactive protein.

Preoperative DVT determination

For diagnosis of DVT, the patients underwent lower extremity venous ultrasound 1 to 3 days preoperatively. These scans were conducted on the bilateral lower extremities to detect venous thrombosis in the proximal veins (common femoral, femoral, and popliteal veins) and distal veins (posterior tibial, peroneal, soleal, and sural veins). In this study, a positive case was defined as the diagnosis of DVT on lower extremity venous ultrasound, regardless of whether the DVT was located on affected side (with OA) or the contralateral side. Additionally, both proximal or distal DVT were included as positive cases.

Data analyses

The data were analyzed using SPSS Version 24.0 (IBM Corp., Armonk, NY, USA). The sample data were analyzed using the Kolmogorov–Smirnov test to evaluate their conformity to a normal distribution. Normally distributed continuous variables are presented as mean ± standard deviation, and the means of the two groups were compared using Student’s t test. Non-normally distributed continuous variables are presented as median and interquartile range; the Mann–Whitney U test was used to determine the distribution difference. The chi-square test or Fisher’s exact test was performed for categorical variables such as numbers and proportions.

To include all potential risk factors, variables with a P value of < 0.1 in the univariate analysis were entered into the multivariate logistic analysis to determine the risk factors for preoperative DVT in patients with OA. A stepwise forward (LR) multivariate logistic regression analysis was conducted with an entry probability of 0.05 and a removal probability of 0.1 for variables associated with categorical outcomes (development of DVT) in the univariate analysis. A P value of < 0.05 indicated statistical significance.

A receiver operating characteristic (ROC) curve analysis was performed to determine the optimal cut-off values for continuous variables that were statistically significant (P < 0.05) according to multivariate logistic regression. These were determined by maximizing the Youden index (sensitivity + specificity − 1). Additionally, the sensitivity, specificity, and area under the ROC curve (AUC) were determined.

Results

Participant selection

After application of the exclusion criteria, 1411 elderly patients with end-stage knee OA (241 men, 1170 women) were included in the study (Fig. 1). The patients’ mean age was 69.2 ± 5.8 years (range, 60–91 years).

Baseline characteristics

The incidence of preoperative DVT was 4.5% (63 of 1411 patients). The univariate analysis revealed statistical differences in the walking status (walking independently, mobility aid, or wheelchair) between the DVT group (63 patients) and non-DVT group (1348 patients) (P < 0.001). Patients with DVT had a higher prevalence of comorbidities, including CRF (4.8% vs. 0.6%, P = 0.011) and COPD (6.3% vs. 0.7%, P = 0.002). Additionally, patients with DVT were older (72.5 ± 5.8 vs. 69.1 ± 5.8 years, P < 0.001), had higher D-dimer levels (1.4 ± 1.8 vs. 0.7 ± 1.3 µg/mL, P < 0.001), and had lower BI scores (88.3 ± 9.6 vs. 91.6 ± 6.4, P = 0.013) (Table 1).

Table 1 Distribution and differences in demographic characteristics between DVT and non-DVT groups
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Univariate and multivariate logistic regression analyses for DVT risk factors

A multivariate logistic analysis was performed using the variables with a P value of < 0.1 in the univariate analysis (age, BI score, walking status, hyperlipidemia, AF, CRF, COPD, white blood cells, neutrophils, and D-dimer level). After adjusting for confounding variables, the findings indicated that age (odds ratio [OR], 1.073; 95% confidence interval [CI], 1.026–1.123; P = 0.002), D-dimer (OR, 1.173; 95% CI, 1.054–1.305; P = 0.003), hyperlipidemia (OR, 2.038; 95% CI, 1.015–4.094; P = 0.045), AF (OR, 4.004; 95% CI, 1.121–14.304; P = 0.033), CRF (OR, 6.732; 95% CI, 1.628–27.831; P = 0.008), COPD (OR, 8.721; 95% CI, 2.484–30.623; P = 0.001), and walking status (wheelchair) (OR, 2.697; 95% CI, 1.446–5.030; P = 0.002) were independent risk factors for preoperative DVT in elderly patients with end-stage OA (Table 2). Additionally, the following factors were identified as significant predictors of preoperative DVT in elderly patients with end-stage OA: high age (B = 0.071), high D-dimer concentration (B = 0.160), hyperlipidemia (B = 0.712), AF (B = 1.387), CRF (B = 1.907), COPD (B = 2.166), and walking status (wheelchair) (B = 0.992) (Table 2).

Table 2 Univariate and multivariate logistic regression analysis of risk factors associated with preoperative DVT
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Determination of cut-off values of continuous variables

The ROC curve of age and D-dimer level is shown in Fig. 2. On the basis of the ROC curve analysis for predicting preoperative DVT (Table 3), the optimal cut-off values were 72.5 years for age (AUC, 0.668; 95% CI, 0.601–0.735; P < 0.001) and 0.585 µg/mL for the D-dimer level (AUC, 0.769; 95% CI, 0.710–0.828; P < 0.001).

Table 3 ROC curve analysis to determine the optimal cut-off value
Full size table
Fig. 2
figure 2

ROC curve of age and D-dimer

Full size image

Discussion

The most important finding of the present study is that 4.5% of elderly patients with end-stage OA scheduled for TKA had preoperative DVT. In addition, the D-dimer level, age, hyperlipidemia, AF, CRF, COPD, and walking status (wheelchair) were identified as risk factors for preoperative DVT in our study.

Wakabayashi et al. [7] found a higher incidence of preoperative DVT (17.4%) in patients undergoing TKA than observed in our study (4.5%). This difference may be explained by their inclusion of patients with RA and those undergoing revision TKA, both of which are independent risk factors for preoperative DVT. Moreover, one meta-analysis showed that patients with RA are more likely than patients with OA to develop DVT after TKA [14]. Similarly, Sato et al. [15] reported a higher incidence of preoperative DVT (14.7%) among patients with OA, RA, and idiopathic osteonecrosis. They performed lower extremity ultrasounds only on patients with a D-dimer level of ≥ 1 µg/mL or those deemed by physicians to be at high risk for DVT (683 of 1236 patients, 55.3%). However, our results were comparable to those of Sun et al. [13], who limited their study cohort to patients with primary OA. They reported that the prevalence of preoperative DVT before TKA was 5.53%. Therefore, the differences between patients with RA and OA should be acknowledged when assessing the risk of preoperative DVT.

The D-dimer level can be measured to predict DVT risk [16, 17]. Our study showed that the D-dimer level was associated with the risk of preoperative DVT in elderly patients with end-stage OA. The D-dimer cut-off value used in our study (> 0.58 µg/mL) was similar to that reported by Jiang et al. [5], who found that preoperative DVT in patients with end-stage OA was associated with a D-dimer level of > 0.5 µg/mL. In Europe and North America, a D-dimer level of < 0.5 µg/mL is used to rule out DVT in non-surgical patients [18]. Similarly, a higher D-dimer level is a reliable marker of hypercoagulability, indicating a higher risk of thrombosis and enhancing the negative predictive value [19]. Consequently, it has been suggested that a D-dimer cut-off value of 0.585 µg/mL should be used in elderly patients with end-stage OA to rule out DVT prior to surgery. Nevertheless, the specific D-dimer cut-off value should be considered based on the impact of surgical factors. In addition, predicting postoperative DVT based on the preoperative D-dimer level may be challenging. Most studies have shown that D-dimer testing is not accurate for predicting or diagnosing postoperative DVT after TKA [20,21,22,23]. Both joint arthroplasty and thrombosis may increase the D-dimer level during the acute postoperative period, making it difficult to distinguish between D-dimer increases caused by thrombosis and those caused by surgery. Therefore, an increase in the D-dimer level may be a useful biomarker for predicting preoperative DVT before total joint arthroplasty without being influenced by surgical factors.

Our study showed that age was a risk factor for preoperative DVT. Imai et al. [24] and Wu et al. [25] also reported that age was associated with preoperative DVT before TKA. Elderly patients, particularly women aged > 60 years, have been shown to be at an increased risk of DVT [26]; however, our study found no evidence that gender affects the development of DVT. Because of the high incidence of comorbidities such as hypertension, diabetes, hyperlipidemia, and heart failure, these patients are more susceptible to coagulation activation [27]. In addition, hyperlipidemia was identified as a risk factor for preoperative DVT in our study. Hyperlipidemia may aggravate the endothelial dysfunction caused by high cholesterol levels, contributing to venous thrombosis progression [28]. Thus, elderly patients aged > 72.5 years with hyperlipidemia are more likely to develop preoperative DVT and should be closely monitored.

The association between AF and the risk of preoperative DVT was further demonstrated in our study. Wang et al. [29] also indicated that patients with AF had a higher risk of DVT than those without AF (adjusted hazard ratio [HR], 1.74; 95% CI, 1.36–2.24). Because of the disruption of physiological hemostatic mechanisms, AF is associated with an increased risk of pathological thrombus formation [30]. However, Enga et al. [31] found that AF was only associated with DVT for the first 6 months after diagnosis (HR, 6.20; 95% CI, 3.37–11.39), whereas no relationship existed beyond this time period. This may be attributed to the patient’s hesitation when dealing with the diagnosis of AF, which delays the initiation of heart rate control and anticoagulation administration [31]. However, another study showed that the incidence of DVT after TKA was not higher in patients with than without AF [32]. Patients with AF were switched from preoperative oral anticoagulants (warfarin, rivaroxaban, or dabigatran) to low-molecular-weight heparin (LMWH) bridging therapy. This was continued until oral anticoagulants therapy was resumed after TKA wound drain removal. These findings suggest that LMWH bridging therapy can effectively prevent thrombosis events in patients with AF after TKA. Our findings therefore suggest that adherence to anticoagulation for thromboprophylaxis in patients with AF might be poor, and further studies of medication adherence in patients with AF are needed.

All stages of chronic kidney disease (CKD) significantly increase the risk of DVT, encompassing conditions such as nephrotic syndrome, end-stage renal disease (ESRD), and kidney transplantation [33]. Wattanakit et al. [34] showed an almost two-fold increased risk of DVT among patients with stage 3/4 CKD compared with the risk among those who had normal renal function in the general population. Furthermore, patients with stage 5 CKD, also known as ESRD, are at higher risk of developing DVT. In an Asian study population, patients with ESRD had a higher incidence of DVT than those without ESRD (adjusted HR, 13.92; 95% CI, 9.25–20.95) [35]. Additionally, patients with ESRD undergoing total joint arthroplasty had a higher risk of DVT than patients without ESRD (OR, 1.4; P = 0.03) [36]. Stage 3–5 CKD is referred to as CKF. Our study showed that elderly patients with end-stage OA who had CKF were at increased risk for preoperative DVT. Hemostatic derangements may contribute to this increased risk and include activated procoagulants, decreased endogenous anticoagulants, enhanced platelet activity, and decreased fibrinolysis [33]. In addition, patients with ESRD commonly require long-term dialysis, and repeated punctures of arteriovenous fistulas may increase embolus formation. However, LMWH or fondaparinux for treatment of DVT is not recommended in patients with ESRD [37] because of concerns about drug accumulation and increased bleeding risks. Therefore, future research should focus on choosing the most appropriate anticoagulant and balancing the anticoagulant dosage in patients with ESRD to prevent DVT.

Our study showed that COPD was a risk factor for preoperative DVT. Similar results have been obtained in studies of femoral and pelvic fractures [38] and intertrochanteric fractures [39]. Patients with COPD are at increased risk of thromboembolic events because of various mechanisms such as systemic inflammation, hypoxemia, oxidative stress, endothelial dysfunction, and prothrombotic conditions [40]. Additionally, the persistence of chronic hypoxia causes severe impairment in daily activities, resulting in venous stasis and hypercoagulability in the lower limbs and thus increasing the risk of thrombosis. Patients with COPD are likely to develop DVT; however, it is more likely to be combined with PE [41]. Therefore, when a patient has decreased oxygen saturation and an increased heart rate, it is essential not only to consider COPD as a possible cause but also to perform computed tomography pulmonary angiography to rule out PE.

Our study also showed that walking status (wheelchair) was a risk factor for preoperative DVT. Patients using a wheelchair upon admission may be incapable of independently performing activities of daily living and experience limited mobility. As a result of poor physical activity, thrombosis is more likely to occur secondary to inadequate blood circulation and increased venous stasis, which is a key factor in DVT development [42]. However, active ankle movement can significantly improve venous outflow and capacity, helping to prevent DVT [43]. In addition, compared with intermittent pneumatic compression, active ankle exercise can produce the same effect as increasing venous outflow [44]. Therefore, patients with declining ambulatory ability are recommended to increase the amount of active ankle exercises performed while in bed.

Our study had some limitations. Because this was a retrospective study, some DVT risk factors may have been omitted, resulting in biased results. Additionally, this study only included elderly patients with end-stage knee OA (age of ≥ 60 years). The inclusion of an etiology-specific population and age-factor considerations may limit the generalizability of the results. For example, patients with RA, ankylosing spondylitis, and traumatic OA were not included. Another limitation is that our study results were obtained from a single center and cannot be widely extrapolated. Hence, prospective multicenter studies are needed to validate our results and examine other risks associated with DVT in patients with RA.

Conclusion

In our study, 4.5% of elderly patients with end-stage OA were found to have preoperative DVT. Moreover, elevated D-dimer levels (> 0.585 µg/mL), age of > 72.5 years, hyperlipidemia, atrial fibrillation, chronic renal failure, chronic obstructive pulmonary disease, and a wheelchair-dependent status were all associated with an increased risk of preoperative DVT.

Data availability

As a result of restrictions regarding ethical approval involving patient data and anonymity, the datasets generated and/or analysed during this study are not available publicly, but may be obtained from the corresponding author upon reasonable request.

Abbreviations

TKA:

total knee arthroplasty

DVT:

deep vein thrombosis

PE:

pulmonary embolism

OA:

osteoarthritis

RA:

rheumatoid arthritis

ROC:

receiver operating characteristic

OR:

odds ratio

AUC:

area under the ROC curve

References

  1. Canovas F, Dagneaux L. Quality of life after total knee arthroplasty. Orthop Traumatol Surg Res. 2018;104(1S):S41–6.

    Article  CAS  PubMed  Google Scholar 

  2. Kahn TL, Soheili A, Schwarzkopf R. Outcomes of total knee arthroplasty in relation to preoperative patient-reported and radiographic measures: data from the osteoarthritis initiative. Geriatr Orthop Surg Rehabil. 2013;4(4):117–26.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Parvizi J, Ceylan HH, Kucukdurmaz F, Merli G, Tuncay I, Beverland D. Venous thromboembolism following hip and knee arthroplasty: the role of aspirin. J Bone Joint Surg Am. 2017;99(11):961–72.

    Article  PubMed  Google Scholar 

  4. Januel JM, Chen G, Ruffieux C, Quan H, Douketis JD, Crowther MA, Colin C, Ghali WA, Burnand B. Symptomatic in-hospital deep vein thrombosis and pulmonary embolism following hip and knee arthroplasty among patients receiving recommended prophylaxis: a systematic review. JAMA. 2012;307(3):294–303.

    Article  CAS  PubMed  Google Scholar 

  5. Jiang T, Yao Y, Xu X, Song K, Pan P, Chen D, Xu Z, Dai J, Qin J, Shi 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  PubMed  Google Scholar 

  6. 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  PubMed  Google Scholar 

  7. 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  PubMed  Google Scholar 

  8. Chang MJ, Song MK, Kyung MG, Shin JH, Chang CB, Kang SB. Incidence of deep vein thrombosis before and after total knee arthroplasty without pharmacologic prophylaxis: a 128-row multidetector CT indirect venography study. BMC Musculoskelet Disord. 2018;19(1):274.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Burns MWN, Mattrey RF, Lux J. Microbubbles Cloaked with hydrogels as Activatable Ultrasound contrast agents. ACS Appl Mater Interfaces. 2020;12(47):52298–306.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Imuro T, Saito M. Preoperative Lower Extremity Motor weakness affects deep vein thrombosis during the Perioperative period of lumbar surgery. Spine (Phila Pa 1976). 2022;47(3):E116–23.

    Article  PubMed  Google Scholar 

  11. Zierler BK. Ultrasonography and diagnosis of venous thromboembolism. Circulation. 2004;109(12 Suppl 1):I9–14.

    PubMed  Google Scholar 

  12. Mousa AY, Broce M, Gill G, Kali M, Yacoub M, AbuRahma AF. Appropriate use of D-dimer testing can minimize over-utilization of venous duplex ultrasound in a contemporary high-volume hospital. Ann Vasc Surg. 2015;29(2):311–7.

    Article  PubMed  Google Scholar 

  13. Sun W, Ai D, Yao Y, Ren K, Lu J, Sun H, Wu X, Jiang Q. The application of Caprini Risk Assessment Model in evaluation of deep vein thrombosis for patients with end-stage osteoarthritis before arthroplasty. BMC Musculoskelet Disord. 2022;23(1):767.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Qiao Y, Li F, Zhang L, Song X, Yu X, Zhang H, Liu P, Zhou S. A systematic review and meta-analysis comparing outcomes following total knee arthroplasty for rheumatoid arthritis versus for osteoarthritis. BMC Musculoskelet Disord. 2023;24(1):484.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Sato K, Date H, Michikawa T, Morita M, Hayakawa K, Kaneko S, Fujita N. Preoperative prevalence of deep vein thrombosis in patients scheduled to have surgery for degenerative musculoskeletal disorders. BMC Musculoskelet Disord. 2021;22(1):513.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Fronas SG, Wik HS, Dahm AEA, Jørgensen CT, Gleditsch J, Raouf N, Klok FA, Ghanima W. Safety of D-dimer testing as a stand-alone test for the exclusion of deep vein thrombosis as compared with other strategies. J Thromb Haemost. 2018;16(12):2471–81.

    Article  CAS  PubMed  Google Scholar 

  17. Riva N, Camporese G, Iotti M, Bucherini E, Righini M, Kamphuisen PW, Verhamme P, Douketis JD, Tonello C, Prandoni P, et al. Age-adjusted D-dimer to rule out deep vein thrombosis: findings from the PALLADIO algorithm. J Thromb Haemost. 2018;16(2):271–8.

    Article  CAS  PubMed  Google Scholar 

  18. Wells PS, Anderson DR, Rodger M, Forgie M, Kearon C, Dreyer J, Kovacs G, Mitchell M, Lewandowski B, Kovacs MJ. Evaluation of D-dimer in the diagnosis of suspected deep-vein thrombosis. N Engl J Med. 2003;349(13):1227–35.

    Article  CAS  PubMed  Google Scholar 

  19. Nomura H, Wada H, Mizuno T, Katayama N, Abe Y, Noda M, Nakatani K, Matsumoto T, Ota S, Yamada N, et al. Negative predictive value of D-dimer for diagnosis of venous thromboembolism. Int J Hematol. 2008;87(3):250–5.

    Article  CAS  PubMed  Google Scholar 

  20. Chotanaphuthi T, Heebthamai D, Taweewuthisub W, Thiengwittayaporn S, Roschan S, Kanchanaroek K. Prediction of deep vein thrombosis after total knee arthroplasty with preoperative D-dimer plasma measurement. J Med Assoc Thai. 2009;92(Suppl 6):S6–10.

    PubMed  Google Scholar 

  21. Mitani G, Takagaki T, Hamahashi K, Serigano K, Nakamura Y, Sato M, Mochida J. Associations between venous thromboembolism onset, D-dimer, and soluble fibrin monomer complex after total knee arthroplasty. J Orthop Surg Res. 2015;10:172.

    Article  PubMed  PubMed Central  Google Scholar 

  22. An TJ, Engstrom SM, Oelsner WK, Benvenuti MA, Polkowski GG, Schoenecker JG. Elevated d-Dimer is not predictive of symptomatic deep venous thrombosis after total joint arthroplasty. J Arthroplasty. 2016;31(10):2269–72.

    Article  PubMed  Google Scholar 

  23. Wu CT, Chen B, Wang JW, Yen SH, Huang CC. Plasma D-dimer is not useful in the prediction of deep vein thrombosis after total knee arthroplasty in patients using rivaroxaban for thromboprophylaxis. J Orthop Surg Res. 2018;13(1):173.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Imai N, Miyasaka D, Shimada H, Suda K, Ito T, Endo N. Usefulness of a novel method for the screening of deep vein thrombosis by using a combined D-dimer- and age-based index before total hip arthroplasty. PLoS ONE. 2017;12(2):e0172849.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Wu JX, Qing JH, Yao Y, Chen DY, Jiang Q. Performance of age-adjusted D-dimer values for predicting DVT before the knee and hip arthroplasty. J Orthop Surg Res. 2021;16(1):82.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Silverstein MD, Heit JA, Mohr DN, Petterson TM, O’Fallon WM, Melton LJ. 3rd: Trends in the incidence of deep vein thrombosis and pulmonary embolism: a 25-year population-based study. Arch Intern Med. 1998;158(6):585–93.

    Article  CAS  PubMed  Google Scholar 

  27. Fimognari FL, Repetto L, Moro L, Gianni W, Incalzi RA. Age, cancer and the risk of venous thromboembolism. Crit Rev Oncol Hematol. 2005;55(3):207–12.

    Article  PubMed  Google Scholar 

  28. Gresele P, Momi S, Migliacci R. Endothelium, venous thromboembolism and ischaemic cardiovascular events. Thromb Haemost. 2010;103(1):56–61.

    Article  CAS  PubMed  Google Scholar 

  29. Wang CC, Lin CL, Wang GJ, Chang CT, Sung FC, Kao CH. Atrial fibrillation associated with increased risk of venous thromboembolism. A population-based cohort study. Thromb Haemost. 2015;113(1):185–92.

    Article  PubMed  Google Scholar 

  30. Ding WY, Gupta D, Lip GYH. Atrial fibrillation and the prothrombotic state: revisiting Virchow’s triad in 2020. Heart. 2020;106(19):1463–8.

    Article  PubMed  Google Scholar 

  31. Enga KF, Rye-Holmboe I, Hald EM, Løchen ML, Mathiesen EB, Njølstad I, Wilsgaard T, Braekkan SK, Hansen JB. Atrial fibrillation and future risk of venous thromboembolism:the Tromsø study. J Thromb Haemost. 2015;13(1):10–6.

    Article  CAS  PubMed  Google Scholar 

  32. Long G, Suqin S, Li G, Weihong Y, Zhenhu W. Impact of atrial fibrillation on postoperative outcomes after total knee arthroplasty-A retrospective study. J Orthop Sci. 2016;21(5):652–7.

    Article  PubMed  Google Scholar 

  33. Wattanakit K, Cushman M. Chronic kidney disease and venous thromboembolism: epidemiology and mechanisms. Curr Opin Pulm Med. 2009;15(5):408–12.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Wattanakit K, Cushman M, Stehman-Breen C, Heckbert SR, Folsom AR. Chronic kidney disease increases risk for venous thromboembolism. J Am Soc Nephrol. 2008;19(1):135–40.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Lu HY, Liao KM. Increased risk of deep vein thrombosis in end-stage renal disease patients. BMC Nephrol. 2018;19(1):204.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Cavanaugh PK, Chen AF, Rasouli MR, Post ZD, Orozco FR, Ong AC. Complications and mortality in chronic renal failure patients undergoing total joint arthroplasty: a comparison between Dialysis and renal transplant patients. J Arthroplasty. 2016;31(2):465–72.

    Article  PubMed  Google Scholar 

  37. Kakkos SK, Gohel M, Baekgaard N, Bauersachs R, Bellmunt-Montoya S, Black SA, Ten Cate-Hoek AJ, Elalamy I, Enzmann FK, Geroulakos G’s Choice - European Society for Vascular Surgery (ESVS) 2021 Clinical Practice Guidelines on the Management of Venous Thrombosis, et al. editors. Eur J Vasc Endovasc Surg 2021, 61(1):9–82.

  38. Wu L, Cheng B. Analysis of perioperative risk factors for deep vein thrombosis in patients with femoral and pelvic fractures. J Orthop Surg Res. 2020;15(1):597.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Fan J, Zhou F, Xu X, Zhang Z, Tian Y, Ji H, Guo Y, Lv Y, Yang Z, Hou G. Clinical predictors for deep vein thrombosis on admission in patients with intertrochanteric fractures: a retrospective study. BMC Musculoskelet Disord. 2021;22(1):328.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Mejza F, Lamprecht B, Niżankowska-Mogilnicka E, Undas A. Arterial and venous thromboembolism in chronic obstructive pulmonary disease: from pathogenic mechanisms to prevention and treatment. Pneumonol Alergol Pol. 2015;83(6):485–94.

    PubMed  Google Scholar 

  41. Bertoletti L, Quenet S, Mismetti P, Hernández L, Martín-Villasclaras JJ, Tolosa C, Valdés M, Barrón M, Todolí JA, Monreal M. Clinical presentation and outcome of venous thromboembolism in COPD. Eur Respir J. 2012;39(4):862–8.

    Article  CAS  PubMed  Google Scholar 

  42. Sochart DH, Hardinge K. The relationship of foot and ankle movements to venous return in the lower limb. J Bone Joint Surg Br. 1999;81(4):700–4.

    Article  CAS  PubMed  Google Scholar 

  43. Wang Z, Chen Q, Ye M, Shi GH, Zhang B. Active Ankle Movement May prevent deep vein thrombosis in patients undergoing lower limb surgery. Ann Vasc Surg. 2016;32:65–72.

    Article  PubMed  Google Scholar 

  44. Sakai K, Takahira N, Tsuda K, Akamine A. Effects of intermittent pneumatic compression on femoral vein peak venous velocity during active ankle exercise. J Orthop Surg (Hong Kong). 2021;29(1):2309499021998105.

    Article  PubMed  Google Scholar 

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Acknowledgements

We thank Angela Morben, DVM, ELS, from Liwen Bianji (Edanz) for editing the English text of a draft of this manuscript.

Funding

This work was supported by the National Natural Science Foundation of China (No.72204268) and the Fundamental Research Funds for the Central Universities (No.3332022002).

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Authors and Affiliations

  1. School of Nursing, Xi’an Jiaotong University Health Science Center, No.76, West Yanta Road, Xi’an, Shaanxi, 710061, China

    Yi-Feng Guo & Yin-Ping Zhang

  2. Department of Orthopedic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China

    Yi-Feng Guo, Na Gao, Yaping Chen, Xisheng Weng, Jin Lin, Jin Jin, Wenwei Qian & Yan Zhang

  3. School of Nursing, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100144, China

    Aimin Guo

  4. Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China

    Wei Han

  5. Department of Nursing, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China

    Yufen Ma & Xiaopeng Huo

  6. Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China

    Weinan Liu

Authors
  1. Yi-Feng Guo
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Contributions

Conceptualization, Methodology, Data curation, Funding acquisition, Writing - original draft: YFG, NG, YPZ, XPH. Data curation, Formal analysis: YPC, AMG, WH. Investigation, Resources: XSW, JL, JJ, WWQ, YZ. Visualization, Supervision: YFM, WNL. Project administration, Writing - review & editing: YPZ, XPH. All authors read and approved the final manuscript to be published.

Corresponding authors

Correspondence to Yin-Ping Zhang or Xiaopeng Huo.

Ethics declarations

Ethics approval and consent to participate

The study was approved by the Institutional Review Board of the Peking Union Medical College Hospital (K3692). The ethics committee waived the requirement for informed consent because this study was retrospective and the data are anonymous.

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Not applicable.

Competing interests

The authors declare no competing interests.

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Guo, YF., Gao, N., Chen, Y. et al. Incidence of and risk factors for preoperative deep vein thrombosis in elderly patients with end-stage osteoarthritis following total knee arthroplasty: a retrospective cohort study. BMC Musculoskelet Disord 25, 754 (2024). https://doi.org/10.1186/s12891-024-07871-7

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Keywords

BMC Musculoskeletal Disorders

ISSN: 1471-2474

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