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. 2025 Jun 20;111(10):7155–7167. doi: 10.1097/JS9.0000000000002773

Impact of preoperative frailty on venous thromboembolism risk following total hip and knee arthroplasty: a meta-analysis

Chang Lan a, Ziqing Mao a, Yun Zhou a, Guangqing Cai a, Zihao Ren a, Zheng Hu a, Shengwen Xiang a, Zhijian Ao a, Weiguo Hu a, Licheng Wei b,*, Xing Li a,*
PMCID: PMC12527706  PMID: 40540311

Abstract

Background:

Frailty is commonly observed in older adults and may elevate the risk of venous thromboembolism (VTE) following total hip arthroplasty (THA) or total knee arthroplasty (TKA). This meta-analysis elucidates the association between frailty and the risk of postoperative VTE, encompassing deep vein thrombosis (DVT) and pulmonary embolism (PE), among patients undergoing THA or TKA.

Materials and methods:

A systematic search was conducted across PubMed, Embase, and Web of Science through August 22, 2024, to identify relevant observational studies with longitudinal follow-up. Eligible studies reported on frailty status preoperatively and subsequent postoperative VTE events. We synthesized data using random-effects models that accounted for heterogeneity and performed subgroup analyses based on the type of surgery and duration of follow-up.

Results:

Our meta-analysis included 14 cohort studies covering 2 218 293 patients. Analysis of univariate results from sixteen datasets showed that frailty was associated with an increased risk of VTE post-THA/TKA (odds ratio [OR]: 2.32, 95% confidence interval [CI]: 1.84–2.93, P < 0.001). This association remained consistent across primary and revision THA/TKA surgeries. Frail patients exhibited heightened risk of DVT (OR: 1.41, 95% CI: 1.12–1.78, P = 0.004) and PE (OR: 1.59, 95% CI: 1.38–1.84, P < 0.001). Subgroup analyses revealed that the link with PE was more pronounced in studies with follow-ups of 90 days (OR: 7.42) than in studies with other follow-up durations (mostly 30 days). Multivariate analysis confirmed that frailty independently predicted increased risks of DVT (OR: 1.69) and PE (OR: 1.57).

Conclusion:

Preoperative frailty significantly heightens the risk of postoperative VTE, DVT, and PE in patients undergoing THA or TKA.

Keywords: frailty, meta-analysis, total hip arthroplasty, total knee arthroplasty, venous thromboembolism

HIGHLIGHTS

  • Frailty before surgery is significantly associated with an elevated risk of venous thromboembolism (VTE) in patients undergoing total hip (THA) and knee arthroplasty (TKA).

  • Meta-analysis of over two million patients shows frail individuals have a 2.3-fold increased risk of VTE post-THA/TKA.

  • Frailty increases the risk of both deep vein thrombosis and pulmonary embolism (PE) postoperatively.

  • The risk of PE is particularly high in frail patients within 90 days post-surgery.

  • Findings highlight the need for careful preoperative assessment and tailored thromboprophylaxis in frail patients undergoing THA or TKA.

Introduction

Total hip arthroplasty (THA) and total knee arthroplasty (TKA) are widely performed procedures, particularly among older adults, to alleviate pain and improve mobility in cases of severe osteoarthritis and other joint disorders[1–3]. As the population ages, the demand for THA and TKA has significantly increased, establishing these operations as some of the most prevalent orthopedic procedures globally[4,5]. However, these surgeries are associated with a substantial risk of postoperative venous thromboembolism (VTE), which encompasses deep vein thrombosis (DVT) and pulmonary embolism (PE)[6]. VTE remains a primary postoperative concern, with incidences ranging from 1% to 10% depending on the surgical type, patient risk factors, and the application of prophylactic anticoagulation[7,8]. DVT typically presents as lower limb pain and swelling, whereas PE may manifest acutely with chest pain and shortness of breath and can lead to potentially fatal complications[9]. The development of VTE following THA and TKA is attributed to several factors, including prolonged immobility, surgical trauma, and inflammation. These conditions promote hypercoagulability and stasis, thereby increasing the risk of clot formation[10,11].

The adverse effects of VTE following THA or TKA are significant, as these events can lead to prolonged hospitalization, additional treatment costs, impaired recovery, and increased mortality[12]. Given these risks, preoperative identification of patients at high risk for VTE is critical for optimizing perioperative care. Frailty, a syndrome characterized by decreased physiological reserves and increased vulnerability to stressors, has recently been recognized as a potential risk factor for adverse outcomes following surgery[13–15], including VTE[16]. Frailty is defined by deficits in physical health, cognition, and social support, resulting in a limited ability to recover from stressors like surgery[17]. It is especially relevant in patients undergoing THA or TKA, as frailty prevalence is estimated to be between 10% and 40% in this population due to advanced age and coexisting chronic conditions[18]. For these patients, frailty has been associated with higher rates of postoperative complications, readmissions, prolonged rehabilitation, and mortality, revealing its clinical significance in managing THA and TKA cases[19].

The association between frailty and VTE following THA and TKA is biologically plausible. Frail individuals often have impaired mobility, low muscle mass, chronic inflammation, and reduced cardiorespiratory function, all of which may contribute to venous stasis, coagulation abnormalities, and a heightened inflammatory response[20,21]. These mechanisms may collectively increase the susceptibility of frail patients to VTE[20,21]. Despite this rationale, findings on the relationship between frailty and VTE risk after THA or TKA have been inconsistent, with some studies reporting a strong association[22–29] and others showing no significant link [30–35]. To our knowledge, no prior meta-analysis has systematically assessed the risk of VTE associated with preoperative frailty, specifically in the context of elective THA or TKA. Considering this knowledge gap, this meta-analysis seeks to elucidate the relationship between preoperative frailty and the risk of VTE, encompassing both DVT and PE, in patients undergoing THA or TKA. By including both univariate and multivariate analyses, we aim to provide a robust and clinically meaningful synthesis that may inform perioperative risk stratification and management strategies.

Methods

This study was conducted per the PRISMA 2020[36,37], the Cochrane Handbook for Systematic Reviews and Meta-analyses[38] guideline, and the Assessing the Methodological Quality of Systematic Reviews Guidelines[39]. These guidelines directed our meta-analysis design, data collection, statistical analysis, and interpretation of results. Furthermore, our meta-analysis protocol was registered with the International Prospective Register under registration identifier ***. No AI was used in the research and manuscript development, as clarified in the TITAN Checklist[40].

Literature search

To identify studies pertinent to this meta-analysis, we searched the PubMed, Embase, and Web of Science databases using an extensive array of search terms, which included the combination of the terms: (1) “frailty” OR “frail”; (2) “total hip arthroplasty” OR “total knee arthroplasty” OR “total hip replacement” OR “total knee replacement” OR “THA” OR “TKA”; (3) “venous thromboembolism” OR “VTE” OR “deep vein thrombosis” OR “DVT” OR “pulmonary embolism” OR “PE” OR “complications” OR “postoperative” OR “outcomes”; and (4) “cohort” OR “cohorts” OR “prospective” OR “prospectively” OR “retrospective” OR “retrospectively” OR “follow-up” OR “followed” OR “risk” OR “incidence” OR “longitudinal.” The search was limited to research involving human subjects, and we only included studies published in English as full-length articles in peer-reviewed journals. Additionally, we manually reviewed the references of relevant original and review articles to identify further pertinent studies. The literature was assessed from the inception of the searched databases up to August 22, 2024. The detailed search strategy for each database is shown in Supplemental Digital Content File 1, available at: http://links.lww.com/JS9/E416.

Inclusion and exclusion criteria

The inclusion criteria for potential studies were defined according to the PICOS framework:

P (patients): Adult patients (aged 18 years or older) undergoing primary or revision THA or TKA;

I (exposure): Patients with frailty evaluated preoperatively. The tools and criteria used to determine frailty were consistent with those of the original studies.

C (comparison): Patients without frailty;

O (outcome): Reported at least one of the following outcomes, which included the incidence of VTE, DVT, or PE after surgery, compared between patients with and without frailty at enrollment;

S (study design): Observational studies with longitudinal follow-up were considered for this meta-analysis, including cohort studies, nested case-control studies, and post hoc analyses of clinical trials;

Exclusion Criteria: Excluded from this analysis were reviews, editorials, meta-analyses, preclinical studies, cross-sectional studies, and studies focusing on nonsurgical patients. Also excluded were studies that did not evaluate frailty as an exposure factor or failed to report the outcome of postoperative VTE events. When two or more studies with overlapping populations were identified, the study with the largest sample size was selected for inclusion in the meta-analysis.

Study quality evaluation and data extraction

Two authors independently performed the literature search, study identification, quality assessment, and data extraction. Any disagreements were resolved through discussion with the corresponding author. The quality of the studies was evaluated using the Newcastle–Ottawa Scale (NOS)[41], which assesses the selection of study groups, control of confounders, and the measurement and analysis of outcomes. The scale ranges from 1 to 9, with 9 representing the highest quality. The data collected for analysis included study details (author, year, country, and design), the type of surgery performed, participant characteristics (number of patients, mean age, and proportion of men), tools used for frailty evaluation, number of frail patients, follow-up duration, reported VTE events, methods used to validate VTE events, number of patients who developed VTE events post-THA/TKA, and the models used to evaluate the association between frailty and the risk of VTE events post-THA/TKA (univariate or multivariate analyses).

Statistical analyses

The associations between frailty and the risk of VTE events after THA/TKA, including total VTE, DVT, and PE, were analyzed separately in this meta-analysis in univariate and multivariate analyses. For studies reporting univariate analysis data, the odds ratios (ORs) and 95% confidence intervals (CIs) for the associations between frailty and the risk of VTE events were calculated based on the events number of postoperative VTE in patients with and without preoperative frailty[38]. For studies reporting multivariate analysis data, the adjusted OR values and their standard errors were calculated from 95% CIs or P-values, logarithmically transformed for variance stabilization, and subsequently pooled in a meta-analysis[38]. ORs were chosen as the effect size because most included studies were retrospective in design and reported associations using logistic regression models. ORs are appropriate for pooling in this context, particularly given the relatively low event rate of postoperative VTE. We used the Cochrane Q test and I2 statistics[42] to assess heterogeneity, with an I2 value greater than 50% indicating significant statistical heterogeneity. A random-effects model was applied to integrate the results, accounting for study variability[38]. Via excluding individual studies sequentially, a sensitivity analysis was performed to evaluate the robustness of the findings. For outcomes involving at least ten datasets, the predefined subgroup analyses were performed to explore the influence of surgery type and follow-up duration on the outcome of the meta-analyses. The medians of the continuous variables were used as cutoff values to define subgroups.

Publication bias was evaluated using funnel plots and visual inspection for asymmetry, supplemented by Egger’s regression test[43]. Analyses were performed using RevMan (Version 5.1; Cochrane Collaboration, Oxford, UK) and Stata software (version 12.0; Stata Corporation, College Station, TX, USA).

Results

Study inclusion

The study inclusion process is illustrated in Figure 1. Initially, 515 potentially relevant records were identified from the five searched databases, with 172 excluded due to duplication. Subsequent screening of the titles and abstracts resulted in the exclusion of 318 studies, primarily because they did not align with the objectives of the meta-analysis. The full texts of the remaining 25 records were reviewed by two independent authors, excluding 11 more studies for various reasons, as detailed in Figure 1. Finally, 14 cohort studies were deemed appropriate for inclusion in the quantitative analysis[22–35].

Figure 1.

Figure 1.

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Flowchart of database search and study inclusion.

Overview of the study characteristics

Table 1 shows the summarized characteristics of the available studies in the meta-analysis. Overall, one prospective cohort study[33] and 13 retrospective studies[22–32,34,35] were included in the meta-analysis. Three studies[29–31] reported outcomes for patients undergoing different surgeries (THA or TKA), and three additional studies reported outcomes for patients with different indications for THA or TKA[23,27,28]. Consequently, these datasets were separately included in the meta-analysis. Accordingly, 23 datasets were involved in the meta-analysis, which included 2 218 293 patients who underwent primary or revision THA/TKA. The mean age range of these patients was 65.0–72.1 years, and the proportion of men ranged from 27.6%–59.6%. Various tools were used to evaluate frailty in the studies, including the Hospital Frailty Risk Score, the modified frailty index, the age-adjusted modified frailty index, and the Frailty-Defining Diagnoses. Of the patients, 264 098 (11.9%) were identified as frail. The follow-up durations varied from during hospitalization to 1 year post-surgery. Postoperative VTE events were confirmed using clinical follow-up data in two studies[32,33] and by the International Classification of Diseases codes in twelve studies [22–31,34,35]. Overall, 9115 (0.4%) patients developed postoperative VTE events. All included studies reported results from univariate analyses, and three studies also provided results from multivariate analyses[22,25,26]. Two of them[22,25] adjusted for gender, race, body mass index, type of anesthesia, and operative time. Another study[26] applied inverse probability of treatment weighting using propensity scores derived from demographics, hospital characteristics, indication/type of revision, and Elixhauser comorbidities. These adjustments improve the internal validity of the multivariate estimates and support the robustness of the pooled effect sizes. The NOS scores ranged from five to seven, indicating an overall moderate quality of the included studies (Table 2).

Table 1.

Characteristics of the included cohort studies

Study Country Study design Type of surgery Number of patients Age (years) Men (%) Methods for frailty evaluation Number of patients with frailty Follow-up duration VTE outcomes reported Methods for VTE outcome validation Numbers of patients with overall VTE Analytic model
Meyer 2020 THA Germany RC pTHA 4558 65 45.7 HFRS ≥5 210 90 days VTE and PE ICD codes 11 Univariate
Meyer 2020 TKA Germany RC pTKA 3692 67.5 38.4 HFRS ≥5 176 90 days VTE and PE ICD codes 14 Univariate
Meyer 2021 THA Germany RC rTHA 331 68.7 43.7 HFRS ≥5 24 90 days VTE and PE ICD codes 1 Univariate
Meyer 2021 TKA Germany RC rTKA 234 68.6 41.2 HFRS ≥5 18 90 days VTE and PE ICD codes 2 Univariate
Seilern 2022 USA RC pTHA 165 957 65.2 45.4 aamFI ≥2 45 611 30 days DVT and PE ICD codes 528 Univariate and multivariate
Tram 2022 OA USA RC pTHA 167 700 NR 44.4 HFRS ≥5 9513 30 days VTE and PE ICD codes 234 Univariate
Tram 2022 ON USA RC pTHA 5353 NR 59.6 HFRS ≥5 397 30 days VTE and PE ICD codes 13 Univariate
Tram 2022 HF USA RC pTHA 7246 NR 33.3 HFRS ≥5 4355 30 days VTE and PE ICD codes 37 Univariate
Lakra 2023 USA RC pTKA 882 479 NR 37.7 HFRS ≥5 62 321 30 days VTE and PE ICD codes 1889 Univariate
Zamanzadeh 2023 USA RC pTKA 271 271 67 38.1 aamFI ≥2 92 947 30 days DVT and PE ICD codes 1856 Univariate and multivariate
Karumuri 2023 India RC pTKA 435 70 43.2 FI >0.2 49 365 days VTE Clinical follow-up data 7 Univariate
Alibayli 2024 Turkey PC Primary or revision TKA or THA 145 67.6 27.6 mFI ≥0.27 42 30 days PE Clinical diagnosis evidenced by medical records 4 Univariate
Tram 2024 Dislocation USA RC rTHA 15 448 NR 34.3 HFRS ≥5 4375 30 days VTE and PE ICD codes 97 Univariate
Tram 2024 Loosening USA RC rTHA 11 062 NR 45.8 HFRS ≥5 1749 30 days VTE and PE ICD codes 31 Univariate
Tram 2024 Infection USA RC rTHA 9733 NR 51 HFRS ≥5 3883 30 days VTE and PE ICD codes 109 Univariate
Kyaw 2024 Loosening USA RC rTKA 25 177 NR 40.3 HFRS ≥5 2464 30 days VTE and PE ICD codes 60 Univariate
Kyaw 2024 Infection USA RC rTKA 12 709 NR 54.9 HFRS ≥5 3703 30 days VTE and PE ICD codes 91 Univariate
Kyaw 2024 Instable USA RC rTKA 9458 NR 34.7 HFRS ≥5 1153 30 days VTE and PE ICD codes 24 Univariate
Zamanzadeh 2024 rTHA USA RC rTHA 13 307 68 44.3 aamFI ≥2 4716 30 days DVT and PE ICD codes 75 Univariate
Zamanzadeh 2024 rTKA USA RC rTKA 18 762 66 39.5 aamFI ≥2 6413 30 days DVT and PE ICD codes 95 Univariate
Kim 2024 USA RC rTHA 7540 72.1 33 mFI-5 ≥2 962 30 days DVT and PE ICD codes 70 Univariate
Arapovic 2024 USA RC rTKA 576 920 67.2 42.6 FDD 17 727 During hospitalization DVT and PE ICD codes 3666 Univariate and multivariate
Garcia 2024 USA RC Simultaneous bilateral pTKA 8776 65 43.7 mFI-5 ≥2 1290 30 days VTE ICD codes 201 Univariate
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VTE, venous thromboembolism; DVT, deep vein thrombosis; PE, pulmonary embolism; HFRS, Hospital Frailty Risk Score; aamFI, age-adjusted modified frailty index; ON, osteonecrosis; HF, hip fracture; FDD, Frailty-Defining Diagnoses; PC, prospective cohort; RC, retrospective cohort; pTKA, primary total knee arthroplasty; pTHA, primary total hip arthroplasty; rTKA, total knee arthroplasty revision; rTHA, total hip arthroplasty revision; NR, not reported; ICD, International Classification of Diseases.

Table 2.

Study quality evaluation via the Newcastle–Ottawa Scale

Study Representativeness of the exposed cohort Selection of the non-exposed cohort Ascertainment of exposure Outcome not present at baseline Control for age and sex Control for other confounding factors Assessment of outcome Enough long follow-up duration Adequacy of follow-up of cohorts Total
Meyer 2020 1 1 1 1 0 0 0 1 1 6
Meyer 2021 1 1 1 1 0 0 0 1 1 6
Seilern 2022 1 1 1 1 1 1 0 0 1 7
Tram 2022 1 1 1 1 0 0 0 0 1 5
Lakra 2023 1 1 1 1 0 0 0 0 1 5
Zamanzadeh 2023 1 1 1 1 1 1 0 0 1 7
Karumuri 2023 1 1 1 1 0 0 1 1 1 7
Alibayli 2024 1 1 1 1 0 0 1 0 1 6
Tram 2024 1 1 1 1 0 0 0 0 1 5
Kyaw 2024 1 1 1 1 0 0 0 0 1 5
Zamanzadeh 2024 1 1 1 1 0 0 0 0 1 5
Kim 2024 1 1 1 1 0 0 0 0 1 5
Arapovic 2024 1 1 1 1 1 1 0 0 1 7
Garcia 2024 1 1 1 1 0 0 0 0 1 5
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Results of the meta-analysis based on univariate analysis

Overall, the pooled results of 16 datasets from eight studies[23,24,27,28,30–32,34] suggested that patients with frailty were associated with a higher incidence of VTE after THA/TKA (OR: 2.32, 95% CI: 1.84–2.93, P < 0.001; I2 = 63%; Fig. 2A). The sensitivity analyses were performed by excluding one dataset at a time but did not significantly change the results (OR: 2.25–2.44, P < 0.05 for all). Further subgroup analyses showed consistent association between frailty and a higher risk of postoperative VTE in patients receiving primary THA, primary TKA, revision THA, and revision TKA (OR = 3.05, 1.67, 2.57, and 2.22, P for subgroup difference = 0.32; Fig. 2B), and in studies with follow-up duration<and ≥ 90 days (OR = 2.24 and 4.06, P for subgroup difference = 0.19; Fig. 2C).

Figure 2.

Figure 2.

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Forest plots for the meta-analysis of the association between frailty and the risk of VTE after THA/TKA based on the univariate analysis: (A) overall meta-analysis; (B) subgroup analysis according to surgery type; and (C) subgroup analysis according to follow-up duration.

A subsequent meta-analysis involving six datasets from five studies[22,25,26,29,35] indicated a higher incidence of postoperative DVT in patients with frailty (OR: 1.41, 95% CI: 1.12–1.78, P = 0.004; I2 = 85%; Fig. 3A). Further sensitivity analysis, excluding one dataset at a time, yielded consistent results (OR: 1.32–1.53, P < 0.05).

Figure 3.

Figure 3.

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Forest plots for the meta-analysis of the association between frailty and the risk of DVT and PE after THA/TKA based on the univariate analysis: (A) overall meta-analysis for the outcome of DVT; and (B) overall meta-analysis for the outcome of PE.

The pooled analysis of 21 datasets from 12 studies[22–31,33,35] indicated that frail patients had a higher incidence of PE following THA/TKA (OR: 1.59, 95% CI: 1.38–1.84, P < 0.001; I2 = 52%; Fig. 3B). Sensitivity analyses, performed by excluding one dataset at a time, did not significantly alter the results (OR range: 1.53–1.65, with all P-values <0.05). Further subgroup analyses demonstrated a consistent association between frailty and an increased risk of postoperative PE across primary THA, primary TKA, revision THA, and revision TKA (OR = 1.87, 1.37, 1.53, and 1.56, respectively; P for subgroup difference = 0.56; Fig. 4A). A stronger association between frailty and postoperative PE was observed in studies with a follow-up duration of ≥90 days compared to those with <90 days (OR: 7.42 vs. 1.54, P for subgroup difference = 0.005; Fig. 4B).

Figure 4.

Figure 4.

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Forest plots for the subgroup analyses of the association between frailty and the risk of PE after THA/TKA based on the univariate analysis: (A) subgroup analysis according to surgery type; and (B) subgroup analysis according to follow-up duration.

Results of the meta-analysis based on multivariate analysis

No previous study reported the association between frailty and the incidence of postoperative VTE based on multivariate analysis. This study investigated the relationship between frailty and the incidence of postoperative VTE in patients undergoing THA/TKA using multivariate analysis. Our further meta-analyses based on three studies[22,25,26] showed that frailty may be independently associated with a higher incidence of DVT (OR: 1.69, 95% CI: 1.23–2.34, P = 0.001; I2 = 79%; Fig. 5A) and PE (OR: 1.57, 95% CI: 1.32–1.88, P < 0.001; I2 = 0%; Fig. 5B).

Figure 5.

Figure 5.

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Forest plots for the meta-analysis of the association between frailty and the risk of DVT and PE after THA/TKA based on the multivariate analysis: (A) overall meta-analysis for the outcome of DVT; and (B) overall meta-analysis for the outcome of PE.

Publication bias

Upon visual inspection, the funnel plots for meta-analyses of the association between frailty and the risk of postoperative VTE and PE, based on univariate analysis, were symmetrical, indicating a low likelihood of publication bias (Fig. 6A and B). Additionally, Egger’s regression test results (P = 0.31 and 0.49) supported this conclusion by suggesting a low risk of publication bias. The publication biases for other meta-analysis outcomes, such as the association between frailty and the risk of postoperative DVT based on univariate and multivariate analyses, and the association between frailty and the risk of postoperative PE based on multivariate analysis, could not be determined because only six or three datasets were available for these outcomes.

Figure 6.

Figure 6.

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Funnel plots evaluating the publication bias for meta-analyses: (A) funnel plots for the meta-analysis of the association between frailty and the risk of VTE after THA/TKA based on the univariate analysis; and (B) funnel plots for the meta-analysis of the association between frailty and the risk of PE after THA/TKA based on the univariate analysis.

Discussion

The results of this meta-analysis confirm that preoperative frailty is significantly associated with an increased risk of postoperative VTE, encompassing both DVT and PE, in patients undergoing THA or TKA. Our findings indicate that frailty nearly doubles the odds of postoperative VTE, with ORs of 2.32 for overall VTE, 1.41 for DVT, and 1.59 for PE. Notably, in multivariate analyses that control for potential confounding factors, frailty remained independently associated with elevated risks for both DVT and PE, revealing its role as a predictor of adverse thromboembolic events following THA or TKA. These findings are clinically meaningful, especially given the subgroup analysis results, which reveal that frail patients with follow-up durations of 90 days or more had markedly higher risks for PE. This suggests that short-term and long-term vigilance is crucial for this high-risk population.

Several potential mechanisms may underlie the association between frailty and the risk of VTE following THA or TKA. Clinically, frail patients often present with impaired mobility, muscle weakness, and reduced physical resilience, all of which may delay postoperative mobilization – a critical factor in VTE prevention[44]. These physical limitations can lead to prolonged immobilization, venous stasis, and an increased risk of clot formation[45]. Additionally, frail patients frequently have comorbid conditions, such as cardiovascular disease, chronic inflammation, and malnutrition, which can predispose them to hypercoagulability and vascular injury[46]. Pathophysiologically, frailty is characterized by a chronic, low-grade inflammatory state marked by elevated levels of cytokines and coagulation factors, including interleukin-6 and fibrinogen[47]. This inflammatory profile may further amplify the risk of VTE by promoting endothelial dysfunction, platelet aggregation, and thrombus formation[48]. Our analysis reveals that these mechanisms align with the increased susceptibility to DVT and PE in frail patients, suggesting that the interplay between systemic inflammation and coagulation may be central to the observed associations.

In interpreting the subgroup findings, it is notable that the association between frailty and PE was particularly pronounced in studies with more extended follow-up periods (≥90 days), with an OR of 7.42. This could reflect the lasting impact of frailty on recovery trajectories and mobility post-surgery, as frail patients may have delayed functional recovery and remain at heightened VTE risk even beyond the typical perioperative period[49]. The elevated PE risk in these patients with extended follow-up may suggest the need for prolonged monitoring and potentially extended prophylactic anticoagulation for frail individuals undergoing THA or TKA[50]. In contrast, the more modest increase in DVT risk observed in our analysis may suggest that immobility and venous stasis contribute more directly to DVT development, which is generally more prevalent immediately post-surgery[51]. The difference in risk patterns between DVT and PE observed here reveals the importance of tailored postoperative care and vigilant long-term monitoring for frail patients.

This meta-analysis provides several novel insights into the literature. First, it is the first comprehensive synthesis to specifically evaluate the impact of preoperative frailty on the risk of VTE following elective total hip or knee arthroplasty, distinct from prior studies focused on hip fracture surgery[16]. Second, our inclusion of both univariate and multivariate analyses confirms frailty as an independent predictor of DVT and PE, reinforcing its value in preoperative risk stratification. Third, our subgroup analysis revealed that frailty is associated with a markedly elevated risk of PE when follow-up exceeds 90 days, suggesting a prolonged vulnerability window that may warrant extended prophylaxis or monitoring. Additionally, our comprehensive and up-to-date literature search, covering studies through August 2024, enables this study to serve as a timely synthesis of the latest evidence. Collectively, these findings support the integration of frailty assessments into routine surgical planning to identify high-risk patients and guide individualized perioperative care. From a clinical perspective, preoperative frailty assessment may help stratify patients who are at elevated thromboembolic risk following THA or TKA. Integrating frailty screening into routine surgical evaluation enables clinicians to initiate tailored interventions such as enhanced mobilization strategies, extended-duration anticoagulation, and closer postoperative monitoring. Although direct evidence linking frailty interventions to reduced VTE risk remains scarce, multidisciplinary prehabilitation programs – focusing on physical conditioning, nutritional support, and optimization of comorbidities – have shown promise in improving surgical outcomes in frail populations. Future research is warranted to determine whether such interventions can also attenuate thromboembolic complications in this high-risk group.

Our study observed significant heterogeneity across the primary outcomes (association between frailty and VTE, DVT, and PE), with all I2 values exceeding 50%. The potential sources of heterogeneity may include the following: (1) the predominance of retrospective studies, which may introduce selection and recall biases; (2) the use of different frailty assessment tools across studies; (3) variations in the perioperative frailty levels among patients; (4) differences in postoperative rehabilitation protocols and anticoagulant therapy regimens; (5) an imbalance in sample sizes across studies, ranging from 18 to 92 947 participants; and (6) substantial variability in follow-up durations, ranging from hospitalization to 12 months. Although subgroup analyses were conducted, heterogeneity could not be eliminated, representing a limitation of our study. However, we believe our conclusions remain clinically significant, as the impact of frailty was confirmed through multivariate analysis. Additionally, the heterogeneity in frailty assessment tools among included studies represents a methodological limitation. Various indices were used to define frailty, each with distinct components and thresholds. Due to the lack of a universally accepted standard and limited head-to-head comparisons of these tools, we could not verify their equivalence or conduct subgroup analyses by frailty type. Existing literature suggests that different frailty measures, although varying in structure, often demonstrate comparable predictive utility for adverse outcomes[52,53]. Further prospective research is needed to validate and standardize frailty assessments in the context of THA and TKA. Moreover, although multivariate analyses accounted for several demographic and clinical variables, potential confounding from unmeasured factors such as the burden of comorbidities, variations in perioperative management, and differences in thromboprophylaxis protocols cannot be excluded. These factors may influence the observed association between frailty and VTE risk, particularly in extensive administrative database studies where such granular data are often unavailable. Future prospective investigations should aim to include detailed and standardized reporting of perioperative care practices to better delineate the independent predictive value of frailty.

The findings of this meta-analysis have several important clinical implications. These results suggest that preoperative frailty assessments should be integrated into routine clinical evaluations for patients undergoing THA or TKA to identify those at higher risk of VTE. Early identification of frailty can enable targeted interventions, including enhanced VTE prophylaxis, mobilization strategies, and possibly extended-duration anticoagulation tailored to the needs of frail patients. Given the association between frailty and poor postoperative outcomes, multidisciplinary approaches to frailty management, including physical therapy, nutritional support, and optimization of comorbidities, may further mitigate the risk of VTE and improve recovery in these patients[54]. Moreover, the marked PE risk observed with prolonged follow-up reveals the importance of considering frailty status in postoperative care planning, as it may warrant extended monitoring and preventive measures for this high-risk population[55]. This likely reflects the time-dependent nature of thromboembolic events and suggests that frail individuals may remain at elevated risk beyond the standard 30-day postoperative window. These findings highlight the importance of extended surveillance in this vulnerable population and the need for future studies to adopt standardized follow-up durations for outcome assessment. However, the pooled estimate for the incidence of PE of the ≥90 days subgroup was based on only two studies, and the markedly elevated OR (7.42) may reflect the influence of small-sample effects or study-specific factors. Additional studies with longer follow-up durations are needed to verify this observation and better characterize the temporal relationship between frailty and PE risk. Future research should prioritize prospective studies to better elucidate the causal relationship between frailty and postoperative VTE in THA and TKA patients, ideally employing standardized definitions and assessments of frailty. Notably, none of the included studies reported key perioperative factors such as adherence to thromboprophylaxis protocols, mobility status post-surgery, or the presence of sarcopenia or nutritional deficiencies, which may confound the relationship between frailty and thromboembolic risk. These factors are highly relevant clinically, as they may either mediate or modify VTE risk and could serve as potential targets for tailored interventions. Future studies could incorporate prospective cohort designs or pragmatic trials that systematically capture these variables, ideally using electronic health records or standardized perioperative data collection frameworks. Research is also needed to determine the optimal duration and type of VTE prophylaxis for frail patients and examine the potential benefits of interventions to reduce frailty, such as prehabilitation programs. Further exploration of the mechanisms linking frailty to VTE risk could provide insights into novel therapeutic targets, particularly those involving inflammation and coagulation pathways, which may play pivotal roles in this association.

Conclusions

This meta-analysis provides strong evidence that preoperative frailty significantly elevates the risk of postoperative VTE, DVT, and PE in patients undergoing THA or TKA. These findings emphasize the importance of preoperative frailty assessment in identifying patients at higher risk of thromboembolic complications. Given the rising prevalence of frailty in the aging surgical population, our results highlight the critical need for tailored perioperative care strategies to reduce VTE risk and improve postoperative outcomes for frail individuals undergoing joint arthroplasty.

Acknowledgements

We thank Medjaden Inc. for the scientific editing of this manuscript.

Footnotes

C.L. and Z.M. contributed equally to this work and shared first authorship.

Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article.

Supplemental Digital Content is available for this article. Direct URL citations are provided in the HTML and PDF versions of this article on the journal’s website, www.lww.com/international-journal-of-surgery.

Published online 20 June 2025

Contributor Information

Chang Lan, Email: Lanchang04@163.com.

Ziqing Mao, Email: 906321861@qq.com.

Yun Zhou, Email: Zhouyun0308@sina.com.

Guangqing Cai, Email: 405318659@qq.com.

Zihao Ren, Email: 290193383@qq.com.

Shengwen Xiang, Email: 646942904@qq.com.

Licheng Wei, Email: Weilicheng78@163.com.

Ethical approval

Not applicable.

Consent

Not applicable.

Sources of funding

Natural Science Foundation of Changsha City, grant number: Kq 2202058, Natural Science Foundation of Hunan Province Administration of Traditional Chinese Medicine, grant number: C2024031, Natural Science Foundation of Changsha City Health Commission, grant number: KJ-A2023011, Natural Science Foundation of Changsha City Health Commission, grant number: KJ-B2023072, Natural Science Foundation of Changsha City Health Commission, grant number: KJ-B2023073, Science and Technology Innovation Program of Hunan Province, grant number: 2021SK53103.

Author contributions

Funding acquisition, investigation, validation, writing – original draft, writing – review and editing: C.L.; investigation, validation, writing – original draft, writing – review and editing: Z.M.; data curation, funding acquisition, resources, writing – review and editing: Y.Z.; data curation, resources, writing – review and editing: G.C.; data curation, funding acquisition, resources, writing – review and editing: Z.R.; formal analysis, funding acquisition, resources, writing – review and editing: Z.H.; formal analysis, software, visualization, writing – review and editing: S.X.; methodology, software, visualization, writing – review and editing: Z.A.; methodology, software, visualization, writing – review and editing: W.H.; conceptualization, funding acquisition, project administration, supervision, writing – review and editing: L.W.; conceptualization, project administration, supervision, writing – review and editing: X.L.

Conflicts of interest disclosure

The authors confirm they have no conflicts of interest to declare.

Research registration unique identifying number (UIN)

We registered our study protocol on the International Prospective Register of Systematic Reviews (PROSPERO) website with the registration number CRD42024603116.

Guarantor

Licheng Wei and Xing Li.

Provenance and peer review

Not commissioned, externally peer-reviewed.

Data availability statement

The authors confirm that the data supporting the findings of this study are available within the article. Further inquiries can be directed to the corresponding author.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The authors confirm that the data supporting the findings of this study are available within the article. Further inquiries can be directed to the corresponding author.

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