Despite the fact that the MSIS guideline has been recommending the use of CRP and ESR as useful biomarkers in aiding the diagnosis of PJI, some cases could still be missed during clinical practice, making the right diagnosis time-consuming and costly, and ultimately dramatically increasing the burden for patients. The investigation of markers that would improve the diagnosis is thus required. On this context, it should be noted that the association between preoperative levels of NLR and PJI is yet to be elucidated. In the present study, we investigated the diagnostic performance of the cost-effective and easily accessible NLR marker in facilitating the diagnosis of PJI, aiming to improve the timely and accurate detection of PJI. We found that the level of NLR was significantly higher in the PJI group than that in the aseptic mechanic failure group. However, the diagnostic value of NLR alone was demonstrated to not be a superior marker to those of CRP and ESR in diagnosing PJI, as shown in the analysis of the ROC curve, where its AUC and DOR values were lower than those of CRP and ESR. Nonetheless, when we combined NLR with CRP, this combination was shown to achieve nearly the same diagnostic value as the combination of CRP and ESR or the combination of all 3 markers together, enhancing the specificity and thus improving the ability to rule out PJI when used as a confirmatory test.
Nowadays, all patients who were admitted for different kinds of surgeries are required to have the CBC checked preoperatively, aiming to rule out contraindications of surgeries, such as systemic infection. Accordingly, NLR is calculated directly from the commonly ordered and readily available count of neutrophils and lymphocytes in CBC, making it easily accessible and cost-effective. Aside from that, NLR has been recognized as a marker of the systemic inflammatory response [8]. As such, NLR has been reported to reflect a heightened inflammatory reaction and has gained increasing attention as a prognostic marker in many conditions, such as solid tumors, inflammatory diseases, and postoperative infection [10, 11, 14]. A previous study reported that NLR was significantly higher in patients with polymyalgia rheumatica and was shown to be associated with disease activity and specific clinical features [10]. Inose et al. retrospectively investigated the association of NLR with the surgical site infection in 242 patients who underwent spinal instrumentation surgery. They found that the level of NLR at 6 to 7 d postoperatively was significantly related to the surgical site infection with a cutoff of 3.87 [14]. Several studies have explored the roles of NLR in cases of TJA. Yombi et al. investigated the distribution and fluctuation of NLR compared with that of CRP in 587 patients who underwent total knee arthroplasty, and found that NLR had a faster normalization and was more stable than CRP, demonstrating that NLR might be utilized as a potential biomarker to monitor postoperative inflammation or early infection [16]. Another study conducted by Golge found that NLR was significantly increased in patients with PJI [15]. Similarly, in our study, the level of NLR was significantly higher in patients with PJI in comparison with patients with aseptic mechanic failure, even after adjustments for age, sex, joint, diabetes mellitus, and hypertension, indicating that NLR might play a pivotal role in the inflammatory condition of patients with PJI.
Recently, more studies have been evaluating new biomarkers in diagnosing PJI, such as platelet count, mean platelet volume, fibrinogen, and NLR [15, 17, 18]. Our present study addressed that NLR had a fair diagnostic performance in predicting PJI with a sensitivity of 56.25%, specificity of 80.52%, and AUC of 0.658. In comparison to the study conducted by Golge [15], the sensitivity of NLR in our study was demonstrated to be relatively lower and the specificity higher when using an optimal cutoff of 2.52. Their study revealed that by using 2.45 as the optimal threshold, the sensitivity and specificity of NLR in detecting PJI was 90 and 72%, respectively [15]. However, the study involved patients with either PJI or primary total knee arthroplasty, with the patients with primary arthroplasty being considered as the control group, which would have a great impact on the diagnostic performance of NLR because of the larger heterogeneity between the 2 groups. As the selection of patients is crucial for exploring the diagnostic value of markers, patients should be generalized under the consistent condition to decrease the confounding effect [19].
Further, combinations of biomarkers have been demonstrated to enhance diagnostic performance [17, 20, 21]. Paziuk et al. demonstrated that the ratio of the platelet count to mean platelet volume was inferior to CRP and ESR when employed as a single index. However, when the ratio was used in combination with ESR and CRP, a statistically significant increase in the diagnostic performance of the combination of markers in predicting PJI was observed [17]. Qin et al. revealed that the combination of D-dimer and CRP improved the diagnostic performance in diagnosing PJI [21]. Likewise, we found that NLR alone was inferior to CRP and ESR, while when it was combined with CRP, this marker combination was demonstrated to achieve nearly the same diagnostic value as the combination of CRP and ESR or the combination of all 3 markers together, increasing the specificity and thus improving the ability to rule out PJI. Therefore, it was suggested that NLR, as a complementary biomarker with CRP, could improve the diagnostic performance in diagnosing PJI.
Many studies have investigated the role of CRP and ESR in diagnosing PJI, and have tried to establish an optimal threshold, as well as delineate the diagnostic performance of CRP and ESR for the diagnosis of PJI. Both the CRP and ESR, which are considered as specific indicators of infection, were shown to be highly elevated in the PJI group and to gradually decline postoperatively [20, 22]. The sensitivity of CRP for diagnosing PJI has been reported to range from 74 to 94%, whereas its specificity ranged from 20 to 100%, with different predictive cutoffs [20, 22–25]. On the other hand, the sensitivity and specificity of ESR were reported to vary from 42 to 94%, and 33 to 90%, respectively [17, 22–24, 26]. Compared with these reports, in our study, the sensitivity for CRP and ESR in predicting PJI was shown to be 62.50% and 59.38%, while the specificity was 83.12% and 80.52%, respectively. Except for the sensitivity of CRP, our obtained results were consistent with previous studies. The fluctuation observed in the sensitivity of CRP might be due to the variation of optimal thresholds and sample sizes yielded from different studies in comparison with our study [19, 23, 26, 27]. A study by Bingham et al. tried to explain that different cutoff values would affect the diagnostic performance of a marker, and attempted to determine the optimal thresholds for ESR and CRP to achieve a sensitivity ≥ 95% compared with the optimal thresholds recommended by MSIS. They revealed that when 30 mm/h and 10 mg/L were used as optimal thresholds for ESR and CRP, they observed an unacceptably low sensitivity and a high number of false negatives. To improve sensitivity and prevent any false negatives, an ESR and CRP threshold of > 10 mm/h and > 5 mg/L, respectively was recommended to achieve a sensitivity ≥ 95% [27]. Obviously, different thresholds exert effect on diagnostic performance. Additionally, differences in the genetic background of different races have been reported to contribute to the discrepancy of the diagnostic performance of some markers, such as D-dimer [28].
There were several limitations associated with our study, which should be taken into account when interpreting our findings. First, this was a retrospective study conducted at a single medical center and therefore might have introduced selection bias. Not all confounding variables were considered into the analysis. Some of the confounding variables including body mass index, medications, underlying inflammatory or autoimmune conditions, specifically those that could impact the count of neutrophils or lymphocytes, were underestimated. Regarding the confounding factors we included, despite the significant differences reported for joint and hypertension status between the 2 groups, we used the multivariate logistic regression method to adjust the p value when comparing the aseptic and septic groups in order to subtract the confounding effects. Second, only patients requiring revision arthroplasty were enrolled in the study. Therefore, it was possible that patients with asymptomatic infections or mild clinical manifestations that did not need to undergo revision surgery were excluded from the study, predisposing it to a level of selection bias. Finally, the number of patients involved in our study, especially the PJI group, was relatively small. Recruiting more patients and better adjusting selection criteria in a future prospective study would allow for better representation.