With the global population increasing and population aging progressing, the number of total joint arthroplasties (TJAs) is expected to surpass 4 million per year in the UK and the United States by 2030 (Kapadia et al., 2016). TJA is a common treatment for end-stage osteoarthritis, effectively reducing pain and promoting joint function recovery. However, periprosthetic joint infection (PJI), although rare with an incidence of only 0.5-2% (Whitehouse et al., 2016; Gundtoft et al., 2017; Koh et al., 2017), poses a severe and devastating complication following TJA, imposing significant burdens on patients and society both in terms of health and economic impact. The incidence of PJI is projected to rise due to the increasing prevalence of obesity, diabetes, and other comorbidities (Kapadia et al., 2016). Numerous studies have already demonstrated that obesity/morbid obesity is a significant risk factor for TJA failure (Houdek et al., 2015; Watts et al., 2015; Kapadia et al., 2016; Roth et al., 2019).

Since the 1980s, the body mass index (BMI) and obesity rates among the Chinese population have been steadily increasing (Wang et al., 2021). Obesity not only serves as a significant risk factor for cardiovascular and kidney diseases (Wang et al., 2021) but also impacts the levels of various serum inflammatory biomarkers (Cohen et al., 2021). Adipose cells play a role in synthesizing the pro-inflammatory cytokine IL-6, which subsequently leads to increased production of C-reactive protein (CRP) by the liver (Laaksonen et al., 2004; Cohen et al., 2021). Obese individuals have been found to exhibit higher levels of fibrinogen compared to those with normal body weight, with an increase of 93.5 mg/dl (95% CI, 72.9-114.1) based on reference values from individuals with normal body weight (Nguyen et al., 2009). Leff et al. have discovered that obese patients who exceed their ideal weight by 45 kg exhibit significantly higher average erythrocyte sedimentation rates (ESR) compared to patients with normal weight (17 mm/h vs. 4 mm/h, P=0.015) (Leff and Akre, 1986). PJI and aseptic failure (AF) share certain clinical symptoms, such as pain and joint swelling. Therefore, accurately distinguishing between PJI and AF holds crucial importance for guiding targeted treatments in the future. PET-CT is an important tool for diagnosing PJI, and whole-body PET/CT may detect other infectious lesions, which can have an impact on subsequent treatment strategies (Roschke et al., 2021). A study reported abnormalities in 99mTC labeled scintigraphy in patients with early prosthetic infections, but the study did not discuss the low specificity of the test (Matthews et al., 2009). However, these technological methods are expensive and difficult to widely use in primary hospitals. There is currently a lack of research regarding the impact of obesity on the levels of various biomarkers and the diagnostic capability for PJI patients. Hence, our study aimed to incorporate the CAR, CLR, and the newly introduced CMR alongside traditional biomarkers (CRP and ESR) and fibrinolytic biomarkers (fibrinogen and D-dimer), all of which have demonstrated promising diagnostic value in previous studies conducted by our research team (Shi et al., 2022; Shi et al., 2023) and by others (Pevzner et al., 2011).

The primary research objectives of this study were as follows: (1) to investigate the impact of obesity on the levels of serum inflammatory biomarkers in PJI patients; (2) to determine the optimal diagnostic biomarkers for PJI patients in both the obese and non-obese groups; (3) to explore the possibility of identifying an ideal biomarker that could be universally applied to both groups of patients; (4) and to assess the diagnostic value of various biomarkers in subgroup analyses of obese and non-obese patients.

By addressing these objectives, we aimed to enhance our understanding of the relationship between obesity and serum inflammatory biomarkers in PJI patients, identify effective diagnostic biomarkers tailored to the specific needs of obese and non-obese patients, and evaluate the diagnostic performance of these biomarkers within subgroups.

We conducted a comprehensive comparison of the diagnostic value of traditional inflammatory biomarkers (CRP and ESR), fibrinolytic biomarkers (fibrinogen and D-dimer), and previously established biomarkers (CAR, CLR, and CMR) in PJI patients, considering their obesity status. Our study findings revealed that the levels of serum inflammatory markers in obese PJI patients did not show a significant increase compared to the AF group. Among all biomarkers, CRP and CAR emerged as the most effective indicators for diagnosing PJI in obese and non-obese patients, respectively. Notably, the optimal cutoff value for CRP was higher in the obese group than in the non-obese group, while no significant difference was observed in CAR between the two groups. These results highlighted the importance of considering patients’ BMI when using CRP as a diagnostic indicator for PJI to avoid false positive results. Furthermore, it is noteworthy that all biomarkers performed poorly in subgroup analyses of obese and non-obese patients, indicating limited diagnostic ability in these specific populations.

CRP, as a widely studied traditional inflammatory biomarker, is known to be an acute-phase protein synthesized by liver cells in response to inflammation triggered by various factors, such as infection or obesity. Recent research has highlighted the complex relationship between obesity and chronic inflammation, with studies such as demonstrating that elevated CRP levels are not only indicative of acute infections but also reflect chronic inflammatory states associated with obesity. These findings further underscore the importance of developing tailored diagnostic thresholds for obese patients (Marongiu et al., 2020). Previous studies have demonstrated a positive association between CRP concentration and increasing BMI. For instance, Nguyen et al. have observed that as BMI increases, CRP concentration rises from 0.11 ± 0.03 mg/dl to 0.73 ± 0.09 mg/dl, with the strongest association seen in individuals with a BMI > 40 kg/m² (Nguyen et al., 2009). Similarly, Visser et al. have reported elevated odds ratios (OR) for elevated CRP in obese males (OR: 2.13, 95% CI: 1.56-2.91) and females (OR: 6.21, 95% CI: 4.94-7.81) (Visser et al., 1999). Cohen et al. have also demonstrated significantly increased OR for elevated CRP across all BMI groups compared to individuals with normal BMI, irrespective of gender (Houdek et al., 2015). Furthermore, ESR levels have been found to be elevated in obese patients (Houdek et al., 2015). Given this existing research, it would be reasonable to expect higher CRP and ESR levels in obese PJI patients compared to non-obese PJI patients.

Probasco and his colleagues found that elevated CRP and ESR levels in preoperative inflammation are positively correlated with BMI, and they believed that traditional biomarkers should be used with caution in the diagnosis of obesity PJI (Probasco et al., 2020). However, in our study, we did not observe a significant difference in CRP and ESR levels between the obese and non-obese groups. Several factors may contribute to these unexpected findings. Firstly, obesity is characterized by chronic inflammation, and while inflammatory biomarkers may increase in obese patients, PJI represents a more acute and severe form of inflammation that can have a greater impact on markers like CRP and ESR. Secondly, the sample size of obese PJI patients in our study was relatively small compared to previous studies, which may have introduced greater variability and potential errors. Future large-scale research is needed to confirm these conclusions regarding inflammation. Additionally, it is important to consider that BMI is influenced by race (Issa et al., 2014), and variations in grouping criteria can also lead to discrepancies in results.

While the levels of CRP and ESR in obese PJI patients were not found to be significantly higher than those in non-obese groups, this study identified higher optimal cutoff values for diagnosing PJI using CRP and ESR. Moreover, both sensitivity and specificity were higher compared to our previous studies (Shi et al., 2021). Although these results should be interpreted cautiously due to the limited sample size, they indicated that traditional biomarkers still held considerable diagnostic value in obese PJI patients. Currently, clinical practice does not differentiate between obese and non-obese PJI patients, and using lower cutoff values for CRP and ESR may result in the overtreatment of obese individuals. On the other hand, the CAR, which is previously discovered in our study, demonstrated good performance in both obese and non-obese PJI patients. Importantly, there was no significant difference in the optimal cutoff value between the two patient groups. Thus, we recommend considering the correlation between CRP and CAR to enhance the accuracy of PJI diagnosis.

A recent study has highlighted that hip and knee infections are distinct issues. Specifically, in obese and severely obese patients with hip infection, higher rates of polymicrobial infection and Enterococcus are observed, while severely obese patients show a higher incidence of Gram-negative infections. However, this phenomenon is not observed in knee infections (Lowik et al., 2019). The underlying reason may be attributed to the increase in bacterial colonization on the hip skin, particularly in the groin, as BMI rises (OR=1.15, 95% CI: 1.03-1.29, P=0.01) (Boni et al., 2018). Conversely, in our present study, we observed a higher proportion of knee infections in the obese group. We speculated that this could be due to the hip joint’s proximity to the perineum, leading to more meticulous disinfection by medical professionals. Additionally, the knee joint is more exposed and poses an increased risk of postoperative infection. Another contributing factor could be the small sample size and inherent data biases, which may have resulted in contradictory outcomes.

Furthermore, another study has proposed that obese PJI patients (BMI > 35 kg/m²) exhibit a higher rate of positive intraoperative cultures, likely due to challenges in disinfection and lower tissue concentration of cefazolin in obese individuals (Font-Vizcarra et al., 2011; Pevzner et al., 2011). In our present study, the culture-positive rate in the obese group was 70.0% (21/30), while it was 68.9% (42/61) in the non-obese group. However, it is important to note that our study was retrospective and unable to accurately determine whether each patient received antibiotic treatment before surgery, unlike the prospective study that excludes patients who have received antibiotic treatment within 2 weeks prior to surgery. Therefore, confounding factors cannot be entirely excluded, potentially accounting for the different findings between the two studies.

Our study represented the first attempt to classify PJI patients based on BMI and assess the diagnostic value of traditional biomarkers, fibrinolytic biomarkers, and other inflammatory markers. However, it is crucial to acknowledge the limitations of this study. Firstly, it was a retrospective study conducted at a single center, which inevitably introduced inherent data biases. Secondly, the study focused on Chinese individuals, and racial differences may result in variations in the definition of “obesity.” Therefore, further validation of our research findings is necessary for other ethnic populations. Thirdly, the lack of a gold standard for PJI diagnosis introduces the possibility of misclassification of patients. Fourthly, the sample size in our study, particularly for PJI patients in the obese group, was limited. Thus, larger sample sizes and prospective studies are needed to ensure the reliability of our conclusions.

In conclusion, among the biomarkers studied, CRP and CAR demonstrated the highest diagnostic value in the obese and non-obese groups, respectively. While the subgroup analysis did not yield optimal results, these findings do not diminish the promising potential of CRP and CAR as diagnostic biomarkers for PJI patients with varying BMI levels.