Diagnostic Value of Complete Blood Count Ratios in Identifying Periprosthetic Joint Infections: A Retrospective Cohort Study

Diagnostic Value of Complete Blood Count Ratios in Identifying Periprosthetic Joint Infections: A Retrospective Cohort Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Diagnostic Value of Complete Blood Count Ratios in Identifying Periprosthetic Joint Infections: A Retrospective Cohort Study Shıkhalı Isgandarlı, Evrim Sırın, Vali Mamedov, Fatih Küçükdurmaz This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6605766/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: It is challenging to diagnose a periprosthetic joint infection (PJI) that frequently requires a combination of clinical and laboratory findings. Simple predictors of inflammation include the monocyte/lymphocyte ratio (MLR), neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), and platelet/mean platelet volume ratio (PVR), all of which may be easily documented from a complete blood count. This study's objective is to search possible adjunctive diagnostic parameters to support Musculoskeletal Infection Society (MSIS) criteria(Table 1) in patients with suspected PJI, that are not costly, non-invasive, and helpful to non-gold standard diagnostic criteria. Methods: We compared the blood results of two patient groups a group of 66 patients with chronic periprosthetic joint infection who were scheduled for two-staged arthroplasty with those of a group of 65 arthroplasty patients with similar sociodemographic characteristics and without any complications. Results: According to the analysis results, a threshold value of > 2.26 for NLR and a threshold value of >29.5 for PVR in the preoperative period had the highest sensitivity (78.7 %), while a threshold value of > 0.35 for MLR in the preoperative period had the highest specificity (73.9%). Conclusion: Despite having moderate diagnostic accuracy NLR, PVR, and PLR were not considered as a useful diagnostic test to support the diagnosis of PJI. In conclusion, although NLR, PVR, and PLR showed moderate diagnostic accuracy, they were not reliable enough to serve as diagnostic tools for PJI. Further studies are warranted to explore their potential roles. Periprosthetic joint infection CRP neutrophil/lymphocyte ratio platelet/lymphocyte ratio platelet /mean platelet volume ratio two-stage revision arthroplasty Figures Figure 1 INTRODUCTION Patients with severe arthritis can regain their quality of life and experience pain relief after total joint arthroplasty (TJA) 1 . After a total knee or hip arthroplasty, periprosthetic joint infection (PJI) is a devastating complication with a high morbidity and mortality rate 2 . PJI occurs when bacteria or other microorganisms invade the surgical site and establish an infection around the implanted joint prosthesis 3 . Challenges in diagnosis and management of PJI pose a major challenge in orthopaedic surgery and treatment remains challenging. Early and accurate diagnosis of infection is essential to enable appropriate treatment, which can range from debridement with retention to single-stage or two-stage revision surgery 4 , 5 . The treatment of PJI greatly benefits from the early and accurate identification. In the early postoperative stage, a less traumatic method to keep the prosthetic components in place could be preferred. But still, the lack of a definitive test makes PJI diagnosis extremely challenging. 6 The Musculoskeletal Infection Society (MSIS) established guidelines in attempt to standardize the definition of PJI (Table 1 ) 7 . These criteria are now extensively used by surgeons all over the world and they have significantly increased treatment efficiency and diagnostic confidence. Although the major criteria for infection or the definite proof are the same across all definitions, the minor criteria or the supportive evidence vary and are less universally accepted. In recent years, a variety of markers have been examined and made available, such as synovial CRP, synovial alpha-defensin, synovial leukocyte esterase (LE), and molecular methods like next-generation sequencing 8 – 17 . Table 1 Musculoskeletal Infection Society (MSIS) diagnostic criteria. Major Criteria (at least one of the following) Decision Two positive cultures of the same organism Infected Sinus tract with evidence of communication to the joint or visualization of the prosthesis Preoperative Diagnosis Minor Criteria Score Decision Serum Elevated CRP or D-Dimer 2 ≥6 Infected 2–5 Possibly Infected a 0–1 Not Infected Elevated ESR 1 Synovial Elevated synovial WBC count or LE 3 Positive alpha-defensin 3 Elevated synovial PMN (%) 2 Elevated synovial CRP 1 Intraoperative Diagnosis Inclusive pre-op score or dry tap a Score Decision Preoperative score - ≥6 Infected 4–5 Inconclusive b ≤3 Not Infected Positive histology 3 Positive purulence 3 Single positive culture 2 a For patients with inconclusive minor criteria, operative criteria can also be used to fulfill definition for PJI. b Consider further molecular diagnostics such as next-generation sequencing. CRP, C-reactive protein; ESR, erythrocyte sedimentation rate; LE, leukocyte esterase; PMN, polymorphonuclear; WBC, white blood cell. Blood biomarkers may be the most appealing of these diagnostic markers due to their ease, particularly for some routine tests given to all inpatients. The purpose of our study is to search, whether there are some auxiliary criteria for MSIS for diagnosing PJI by analyzing the ratios within the simple CBC. MATERIAL AND METHODS Study Design This retrospective analysis was performed on patients who underwent revision hip or knee arthroplasty at our hospital between January 2010 and September 2021. The study was authorized by the hospital's ethics committee. 227 patients, who were operated for lower extremity periprosthetic infection were identified by retrospectively scanning the hospital automation system. Patients who underwent DAIR (Debridement-Antibiotics-Implant Retention) procedure (n = 125), joint arthrodesis (n = 12) and one-stage revision operation (n = 10) were excluded from the study. In addition, patients who were under immunosuppression due to systemic diseases affecting blood results, such as systemic lupus erythematosus (SLE) and hemolytic uremic syndrome (HUS)-like thrombocytopenia, were also excluded from the study (n = 14). Two-stage procedure was planned for 66 of these patients, and erythrocyte sedimentation rate (ESR), complete blood count (CBC) and C-reactive protein (CRP) parameters were taken from all patients before the first stage. At the same time, we identified a total of 65 total knee and total hip arthroplasty patients with similar sociodemographic characteristics and no complications as control group. ESR, CRP, CBC and biochemistry panel were obtained from all patients in the control group before hospitalization. We compared the ratios such as monocyte/lymphocyte ratio (MLR), neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), and platelet/mean platelet volume ratio (PVR) in CBC and ESR and CRP in both groups. Data Analyses Descriptive data are shown with percentage values ​​from categorical data, and median minimum-maximum values ​​in continuous data. In the comparison of categorical data, Chi -Square and Fisher Tests were used in appropriate places. Measurement data were tested with Kolmogorov-Smirnov tests for the assumption of normal distribution. Mann-Whitney U test and Kruskal Wallis test were used in appropriate places for the comparison of measurement data that did not show normal distribution. Spearman correlation analysis was used to examine the correlation of two measurement data. P < 0.05 was accepted for statistical significance in all analyzes. Bonferroni correction was made for the P -value in Post Hoc analyses. Analyzes were performed with IBM © SPSS program version 20. The study was carried out with a total of 131 participants, 34 of whom were men and 97 were women. When the sociodemographic and clinical characteristics of the study groups were examined, no statistically significant difference was found (p > 0.05) (Table 2 – 3 ). Table 2 Examination of socio-demographic characteristics according to study groups. PJI group, n (%) Control group, n (%) P value Sex Male 15 (22.7) 19 (29.2) 0.396 a Female 51 (77.3) 46 (70.8) Age Young 21 (31.8) 28 (43.1) 0.183 a Elder 45 (68.2) 37 (56.9) Age* 70.0 (43.0–90.0) 68.0 (28.0–95.0) 0.135 b BMI* 32.4 (21.4–47.8) 29.7 (20.9–47.3) 0.107 b BMI groups Normal 9 (13.6) 9 (14.1) 0.228 a Overweight 16 (24.2) 24 (37.5) Obesity 41 (62.1) 31(48.4) Smoke Yes 8 (12.3) 7 (10.8) 0.784 a No 41 (62.1) 31 (48.4) a Chi-square test, b Mann-Whitney U test, * In measurements, median minimum-maximum values ​​are presented instead of numbers and percentages. Table 3 Examination of clinical features according to study groups. PJI group, n (%) Control group, n (%) P value Intensive care Yes 31 (47.7) 35 (53.8) 0.483 a No 34 (52.3) 30 (46.2) Survival status Live 51 (77.3) 64 (98.5) <0.001 a Dead 15 (22.7) 1 (1.5) Surgery site Right 31 (47.0) 28 (43.1) 0.654 a Left 35 (53.0) 37 (56.9) Laterality Unilateral 54 (81.8) 65 (100.0) <0.001 a Bilateral 12 (18.2) 0 (0.0) Blood transfusion Yes 23 (34.8) 7 (10.8) <0.001 a No 43 (65.2) 58 (89.2) CCI* 4.0 (0.0–9.0) 3.0 (0.0–8.0) 0.006 b a Chi-square test, b Mann-Whitney U test * In the measurements, median minimum-maximum values ​​are presented instead of numbers and percentages. RESULTS When preoperative laboratory values were compared according to the study groups, a statistically significant correlation was found between ESR, CRP, lymphocyte count, neutrophil count, Mean Platelet Volume (MPV), platelet count, MLR, PLR, NLR, PVR and values between both groups (Table 4 ). Table 4 Examination of preoperative laboratory data according to the study groups (before the 1st stage for the infected group and before the arthroplasty surgery for the control group) and postoperative (interstage interval for the infected group, after the arthroplasty surgery for the control group) PJI Group Median (Min-Max) Control Group Median (Min-Max) P value a Preoperative Sedimentation 65.0 (17.0-120.0) 25.5 (1.0–87.0) <0.001 CRP 29.5 (3.1–304.0) 3.2 (0.5–30.8) <0.001 Monocyte 0.6 (0.0-1.4) 0.5 (0.2–1.2) 0.111 Lymphocyte 1.6 (0.1–4.7) 1.9 (0.5-4.0) 0.003 Neutrophile 5.3 (1.5–14.7) 4.4 (1.3–11.6) 0.001 MPV 8.1 (6.3–12.7) 9.0 (7.1–12.5) <0.001 Platelet 291.0 (163.0-607.0) 243.0 (111.0-424.0) 0.001 MLR 0.4 (0.0-1.2) 0.3 (0.1–1.6) 0.002 PLR 189.0 (49.4–2930.0) 122.6 (48.3–522.0) <0.001 NLR 3.6 (1.0-16.3) 2.0 (0.6–11.7) <0.001 PVR 38.0 (16.5–71.8) 27.6 (8.9–57.2) <0.001 4th weeks after surgery Sedimentation 46.0 (2.0-1332.0) 33.0 (4.0–87.0) 0.010 CRP 16.9 (1.1-304.8) 5.0 (1.5–154.0) <0.001 Monocyte 0.5 (0.2–3.4) 0.6 (0.2–10.2) 0.025 Lymphocyte 1.4 (0.6–4.2) 1.9 (0.6–4.5) 0.002 Neutrophile 4.3 (1.4–20.1) 4.9 (1.9–11.6) 0.024 MPV 8.1 (6.3–11.9) 9.1 (7.0-322.0) <0.001 Platelet 278.0 (115.0-589.0) 250.0 (109.0-424.0) 0.015 MLR 0.4 (0.2–1.4) 0.3 (0.1–4.6) 0.441 PLR 190.0 (62.5-420.7) 129.5 (57.9-353.3) <0.001 NLR 2.8 (1.0-22.3) 2.8 (0.9–8.2) 0.605 PVR 35.1 (9.7–91.6) 26.5 (1.0-58.9) <0.001 a Mann-Whitney U test MLR: monocyte/lymphocyte ratio, NLR: neutrophil/lymphocyte ratio, PLR: platelet/lymphocyte ratio, PVR: platelet/mean platelet volume ratio, ESR: erythrocyte sedimentation rate, CRP: C reactive protein, MVP: Mean platelet volume Before the first stage, ESR, CRP, neutrophil count, platelet count, MLR, PLR, NLR and PVR values were found to be significantly higher in the PJI group compared to the control group. There was no significant difference in serum glucose and monocyte count values for both groups. In the comparison with the PJI group before the first stage and the control group before the arthroplasty surgery, lymphocyte count and mean platelet volume values ​​were found to be significantly lower in the PJI group. (Table 4 ) When the postoperative 4th week laboratory values ​​were compared a statistically significant relationship was found for ESR, CRP, monocyte count, lymphocyte count, platelet count, neutrophil count, MPV, PLR and PVR values. ESR and CRP values ​​were significantly higher in the patient group compared to the control group. In the comparison of the post-op 4 weeks blood results after 1 stage in the infected group with the post-op 4week blood results in the control group, there was no significant distinction between NLR and MLR. However, PVR values ​​were found to be significantly higher in the patient group (35.1 (9.7–91.6)) compared to the control group (26.5 (1.0-58.9)) (p:<0.001) (Table 4 ). However, when we used Receiver Operating Characteristic (ROC) curve analysis, we found low sensitivity and specificity of NLR, PVR and PLR (Table 5 ) (Fig. 2). Table 5 Receiver Operating Characteristic (ROC) curve analysis results for determination of threshold values of laboratory values for disease prediction. AUC 95% CI P value Threshold Value SEN SPE +LR -LR PPV NPV Sedimentation 0.859 0.783–0.916 49 66.7 91.7 8.0 0.4 88.9 73.3 CRP 0.960 0.908–0.987 8.71 93.4 91.7 11.2 0.1 91.9 93.2 Monocyte 0.581 0.490–0.668 0.107 Lymphocyte 0.656 0.566–0.739 0.002 ≤1.7 58.3 72.3 2.1 0.6 66.0 65.3 Neutrophile 0.670 0.581–0.751 5 55.7 70.8 1.9 0.6 64.2 63.0 MPV 0.728 0.642–0.804 <0.001 ≤8.4 67.2 69.2 2.2 0.5 67.2 69.2 Platelet 0.676 0.586–0.756 331 41.0 86.2 3.0 0.7 73.5 60.9 MLR 0.662 0.572–0.744 0.001 >0.35 55.0 73.9 2.1 0.6 66.0 64.0 PLR 0.763 0.679–0.834 129.5 80.3 64.6 2.3 0.3 68.1 77.8 NLR 0.748 0.663–0.821 2.26 78.7 64.6 2.2 0.3 67.6 76.4 PVR 0.745 0.660 29.5 78.7 61.5 2.1 0.4 65.8 75.5 AUC: Area under curve, CI: Confidence Interval, SEN: Sensitivity, SPE: Specificity, +LR: Positive likelihood ratio, -LR: Negative likelihood ratio, PPV: Positive predictive value, NPV: Negative predictive value, MLR: monocyte/lymphocyte ratio, NLR: neutrophil/lymphocyte ratio, PLR: platelet/lymphocyte ratio, PVR: platelet/mean platelet volume ratio, ESR: erythrocyte sedimentation rate, CRP: C reactive protein, MVP: Mean platelet volume. DISCUSSION PJI is a significant concern in orthopaedic surgery. The incidence ranges from 1–3% after the arthroplasty population 18 – 21 . Treatment options vary from debridement with retention to single-stage or two-stage revision. This condition is a major challenge in orthopaedic surgery, leading to multiple surgeries, prolonged hospitalization, increased morbidity, and a significant economic burden. Additionally, accurate and early diagnosis of PJI is essential for appropriate treatment. Furthermore, PJI is one of the leading indications for revision surgery and poses a significant threat to patients after an arthroplasty procedure. The two stage reimplantation arthroplasty treatment is the gold standard method accepted worldwide for the treatment of chronic PJI patients 22 . However, the most important stage is the difficulties in diagnosis due to the lack of a gold standard test. Early PJI is managed mostly with DAIR procedure, and patients who do not respond to this treatment are candidates for a two-stage reimplantation treatment. Early diagnosis not only reduces treatment costs but also has a profound impact on the psychosocial status of the patient 23 . A combination of clinical assessment, blood tests, synovial fluid aspiration, microbiologic and histopathologic examinations, as well as imaging, must be used to make an early and accurate diagnosis of PJI. The Magnetic Resonance Imaging (MRI) and ultrasonography (US) may be useful tools for the diagnosis, which are defined by sinus surrounding the joint, fluid accumulation, and soft tissue swelling 24 . The synovial fluid aspiration is also a useful test however, it’s an invasive procedure, and occasionally synovial fluid cannot be obtained despite repeated aspirations, particularly for the hip joint. Besides, a non-infected joint can get contaminated because of repeated aspirations. 25 Recent advances in biomarker research have expanded the diagnostic options for periprosthetic joint infection (PJI). Tripathi et al. 26 reviewed a wide array of serum and synovial biomarkers and concluded that while traditional indicators such as ESR and CRP remain central to diagnosis, novel markers like D-dimer, fibrinogen, and CBC-derived ratios (MLR, NLR, PLR) are gaining attention, though their roles are not yet definitive. Tian et al. 27 , in a meta-analysis, confirmed the high diagnostic accuracy of alpha-defensin while also noting the limited and variable utility of D-dimer and IL-6. Importantly, Xu et al. 28 conducted a large retrospective study and demonstrated that CRP alone exhibited superior diagnostic accuracy compared to other markers, and that combining CBC-derived ratios such as MLR, NLR, and PLR did not significantly improve diagnostic performance. These findings highlight that while CBC-based ratios are easily accessible and cost-effective, their diagnostic value remains modest, especially in patients with underlying inflammatory disorders or in complex clinical scenarios. Consistent with these reports, our study also found that although NLR, PVR, and PLR showed moderate diagnostic accuracy, they were not reliable enough to serve as standalone diagnostic tools for PJI. These results collectively emphasize the need for careful interpretation of such markers and suggest that they should be considered as adjuncts rather than definitive indicators in the diagnostic algorithm for PJI. The gradual method is advised because a single, genuine gold standard continues to be inaccessible. Purchasing of many of the relevant tests and markers is costly or time-consuming. Furthermore, some diagnostic procedures, such synovial alpha defensin, require for tools and knowledge that might not be widely accessible or available at all institutions 29 . For the diagnosis of PJI, a mixture of different clinical examination techniques is still advised. Therefore, the key to the preoperative diagnosis and the creation of an appropriate treatment plan is the identification of reliable and accurate potential markers for the diagnosis of PJI. The primary objectives of this study were to evaluate the effectiveness of ratio indicators as a diagnostic tool and the performance of PJI combination diagnosis using simple results obtained from complete blood counts. PLR has emerged as a potential marker for PJI. Previous studies have indicated that platelet counts and MPV should be considered in the diagnosis of PJI in patients undergoing total knee and hip revision surgery. Moreover, high platelet counts have been shown to be an important additional test for the diagnosis of deep surgical site infections after open internal fixation 30 . Furthermore, perioperative PLR and NLR have been identified as potential predictors of deep vein thrombosis (DVT) following total joint arthroplasty. 31 As DVT was not specifically screened for or excluded in our study cohort, this represents a potential confounding factor. Elevated ratios observed in our infected group may, in part, reflect underlying thromboembolic processes rather than infection alone. Therefore, the influence of such conditions should be taken into consideration when interpreting these biomarkers for diagnosing periprosthetic joint infection. Use of hematological markers, including PLR and NLR have shown promising results in evaluating and diagnosing periprosthetic joint infection 32 , 33 . Additionally, MLR has been proposed as an indicator in the diagnosis and risk stratification of infectious diseases, including PJI. The use of hematological markers, such as PLR, NLR and MLR, may provide valuable insight into the presence and severity of periprosthetic joint infection. Hong Xu et al investigated serum biomarkers to evaluate patients with inflammatory disorders for periprosthetic joint infections prior to revision arthroplasty 34 . The study focused on the efficacy of CRP, ESR, plasma fibrinogen, MLR and NLR as biomarkers. 30 of the 62 patients in the retrospective analysis had infections related to inflammatory disorders, including psoriatic arthritis, rheumatoid arthritis, ankylosing spondylitis, systemic lupus erythematosus (SLE) and gouty arthritis. The current study used receiver operating characteristic (ROC) curves to determine the sensitivity and specificity of the biomarkers tested to diagnose infection, and then optimal cutoffs were determined based on the Youden index. The results showed that CRP, fibrinogen and the combination of CRP and fibrinogen were effective in screening PJI in patients with inflammatory diseases. The combination of CRP with fibrinogen produced 86.2% sensitivity and 78.1% specificity. The current study also examined other biomarkers, including ESR, MLR, and NLR, but discovered that these markers had limited diagnostic utility in screening individuals with inflammatory disorders for infection before revision arthroplasty. Another study conducted by Maimaiti et al. 35 aimed to investigate the possibility of using routine blood tests for the accurate diagnosis of PJI. The study included 246 patients undergoing total hip or knee revision surgery and collected laboratory parameters including erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), D-dimer, plasma fibrinogen, serum white blood cell (WBC) and various rate markers calculated based on complete blood count ratios. The researchers found that the combination of coagulation-related markers such as MLR, NLR, PLR and platelet/average platelet volume ratio (PVR), showed promising diagnostic performance in differentiating PJI from aseptic loosening. Although MLR, NLR, PVR, and PLR demonstrated moderate diagnostic accuracy in our study, their overall performance was found to be insufficient for reliable initial diagnosis of PJI. This finding is in accordance with the results of a recent meta-analysis by Festa et al. 36 , which evaluated 11 publications and concluded that these CBC-derived ratios, while easily obtainable, show limited diagnostic value and cannot replace established biomarkers due to their low specificity and variable sensitivity. Therefore, although they may serve as supportive markers, they should not be considered standalone diagnostic tools for . Gao et al proved that MLR had accurate predictive value in predicting knee osteoarthritis(36). In other studies, the marker was found to be useful for predicting outcomes in cases of cancer, tuberculosis, and a variety of autoimmune illnesses 37 – 39 . These investigations hypothesized that MLR may be used as an additional diagnostic tool when there were less lymphocytes present due to an increase in monocyte count brought on by systemic immunological responses. In the current study, the MLR was similar in both PJI group and non-infected control group. Therefore, MLR was not found to support the diagnosis of a PJI. In addition, the low sensitivity and specificity of NLR, PVR and PLR alone in estimating PJI in our study were limiting the use of these criteria in estimating PJI alone. Contrary to the MSIS criteria, when we compared the PJI group with the non-infected control group, a CRP value above 8.71 was significant for infection. This difference may be attributed to variations in patient characteristics and the timing of diagnosis. In our cohort, many infections were likely identified at earlier stages or involved low-grade pathogens, which may have resulted in lower systemic inflammatory responses. Furthermore, while the MSIS criteria propose generalized thresholds, population-specific cut-off values can vary according to clinical circumstances and diagnostic sensitivity. Supporting this, Parvizi et al. 40 demonstrated that optimal CRP cut-off values differ based on the type of joint and clinical context, emphasizing that rigid thresholds may not be universally applicable .Therefore, in our study, a CRP level above 8.71 mg/L proved significant, likely reflecting these contextual factors and the heterogeneity of our patient population. There were various restrictions on the study. The primary restriction is its retrospective feature, which means that a number of confounding factors could have affected PJI. Furthermore, it is important to acknowledge that several patient- and surgery-related factors, including surgical environment, perioperative conditions, and pre-existing comorbidities, may affect the likelihood of periprosthetic joint infection. However, due to limited access to detailed operative data in patients undergoing primary arthroplasty at external centers, our analysis focused exclusively on laboratory parameters as diagnostic indicators. This limitation should be considered when interpreting the diagnostic accuracy of the evaluated biomarkers. In conclusion, we’ve showed that the diagnostic accuracy of PJI in arthroplasty patients can’t be evaluated by using serum PLR, NLR and PVR computed from a simple complete blood count in conjunction with other hematologic and aspirate markers. We have ensured by our study that PLR, PVR and NLR together cannot be used as supportive criteria to the MSIS criteria. Declarations Ethics approval and consent to participate This study was conducted in accordance with the ethical principles of the Declaration of Helsinki. Ethical approval was obtained from the Marmara University Faculty of medicine clinical research ethics committee (Date: 07.01.2022; Document No: 09.2022.110). Written informed consent was waived due to the retrospective nature of the study. Availability of data and materials The datasets used and/or analyzed during the current study were retrospectively retrieved from Marmara University Hospital automation system and are available from the corresponding author on reasonable request. Consent for publication Written informed consent was obtained from the patient for publication of this study and accompanying images. Funding No funding was received for this study. Competing interests The authors declare that they have no competing interests. Authors' contributions Shıkhalı Isgandarlı, MD: Study design, patient management, data collection, manuscript writing and corresponding author. Evrim Şirin, MD: Study design and manuscript review. Vali Mamedov, MD: Case review and literature review. Fatih Küçükdurmaz, MD: Manuscript revision and supervision. All authors read and approved the final manuscript. Acknowledgements Not applicable. Authors' information Not applicable. Ethics approval and consent to participate This study was conducted in accordance with the ethical principles of the Declaration of Helsinki. Ethical approval was obtained from the Marmara University Faculty of medicine clinical research ethics committee (Date: 07.01.2022; Document No: 09.2022.110). Written informed consent was waived due to the retrospective nature of the study. Availability of data and materials The datasets used and/or analyzed during the current study were retrospectively retrieved from Marmara University Hospital automation system and are available from the corresponding author on reasonable request. References Bleß HH, Kip M. White Paper on Joint Replacement. White Paper on Joint Replacement: Status of Hip and Knee Arthroplasty Care in Germany . Published online November 3, 2018:1-135. doi:10.1007/978-3-662-55918-5 Yu BZ, Fu J, Chai W, Hao LB, Chen JY. Neutrophil to lymphocyte ratio as a predictor for diagnosis of early Periprosthetic joint infection. 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Economic burden of periprosthetic joint infection in the United States. J Arthroplasty . 2012;27(8 Suppl). doi:10.1016/J.ARTH.2012.02.022 Lazic I, Scheele C, Pohlig F, von Eisenhart-Rothe R, Suren C. Treatment options in PJI – is two-stage still gold standard? J Orthop . 2021;23:180-184. doi:10.1016/J.JOR.2020.12.021 Kunutsor SK, Beswick AD, Peters TJ, et al. Health Care Needs and Support for Patients Undergoing Treatment for Prosthetic Joint Infection following Hip or Knee Arthroplasty: A Systematic Review. PLoS One . 2017;12(1). doi:10.1371/JOURNAL.PONE.0169068 Romanò CL, Petrosillo N, Argento G, et al. The Role of Imaging Techniques to Define a Peri-Prosthetic Hip and Knee Joint Infection: Multidisciplinary Consensus Statements. J Clin Med . 2020;9(8):1-20. doi:10.3390/JCM9082548 Tande AJ, Patel R. Prosthetic joint infection. Clin Microbiol Rev . 2014;27(2):302-345. doi:10.1128/CMR.00111-13 Tripathi S, Tarabichi S, Parvizi J, Rajgopal A. Current relevance of biomarkers in diagnosis of periprosthetic joint infection: an update. Arthroplasty . 2023;5(1):1-10. doi:10.1186/S42836-023-00192-5/TABLES/10 Tian B, Cui L, Jiang W. The diagnostic effect of α-defensin, D-dimer, and IL-6 in periprosthetic joint infection: A systematic review and diagnostic meta-analysis. Journal of Orthopaedic Surgery . 2020;28(3). doi:10.1177/2309499020971861/ASSET/IMAGES/LARGE/10.1177_2309499020971861-FIG6.JPEG Xu H, Xie J, Zhang S, Wang D, Huang Z, Zhou Z. Potential Blood Biomarkers for Diagnosing Periprosthetic Joint Infection: A Single-Center, Retrospective Study. Antibiotics . 2022;11(4). doi:10.3390/ANTIBIOTICS11040505 Balato G, De Matteo V, Ascione T, et al. Archives of Orthopaedic and Trauma Surgery Laboratory-based versus qualitative assessment of α-defensin in periprosthetic hip and knee infections: a systematic review and meta-analysis. 1:3. doi:10.1007/s00402-019-03232-5 Zhang Z, Ji Y, Wang Z, Qiu X, Chen Y. The association between platelet indices and deep surgical site infection after open induction internal fixation for traumatic limb fractures. Infect Drug Resist . 2018;11:2533. doi:10.2147/IDR.S184877 Yao C, Zhang Z, Yao Y, Xu X, Jiang Q, Shi D. Predictive value of neutrophil to lymphocyte ratio and platelet to lymphocyte ratio for acute deep vein thrombosis after total joint arthroplasty: a retrospective study. J Orthop Surg Res . 2018;13(1). doi:10.1186/S13018-018-0745-X Erre GL, Paliogiannis P, Castagna F, et al. Meta-analysis of neutrophil-to-lymphocyte and platelet-to-lymphocyte ratio in rheumatoid arthritis. Eur J Clin Invest . 2019;49(1). doi:10.1111/ECI.13037 Uslu AU, Deveci K, Korkmaz S, et al. Is neutrophil/lymphocyte ratio associated with subclinical inflammation and amyloidosis in patients with familial Mediterranean fever? Biomed Res Int . 2013;2013. doi:10.1155/2013/185317 Xu H, Xie J, Wan X, Liu L, Wang D, Zhou Z. Combination of C-reactive protein and fibrinogen is useful for diagnosing periprosthetic joint infection in patients with inflammatory diseases. Chin Med J (Engl) . 2022;135(16):1986-1992. doi:10.1097/CM9.0000000000002215 Maimaiti Z, Xu C, Fu J, Chai W, Zhou Y, Chen J. The Potential Value of Monocyte to Lymphocyte Ratio, Platelet to Mean Platelet Volume Ratio in the Diagnosis of Periprosthetic Joint Infections. Orthop Surg . 2022;14(2):306-314. doi:10.1111/OS.12992 Festa E, Ascione T, Bernasconi A, et al. Diagnostic Performance of Neutrophil to Lymphocyte Ratio, Monocyte to Lymphocyte Ratio, Platelet to Lymphocyte Ratio, and Platelet to Mean Platelet Volume Ratio in Periprosthetic Hip and Knee Infections: A Systematic Review and Meta-Analysis. Diagnostics . 2022;12(9). doi:10.3390/DIAGNOSTICS12092033 Yuan C, Li N, Mao X, Liu Z, Ou W, Wang SY. Elevated pretreatment neutrophil/white blood cell ratio and monocyte/lymphocyte ratio predict poor survival in patients with curatively resected non-small cell lung cancer: Results from a large cohort. Thorac Cancer . 2017;8(4):350-358. doi:10.1111/1759-7714.12454 Xun Y, Wang M, Sun H, Shi S, Guan B, Yu C. Prognostic Analysis of Preoperative Inflammatory Biomarkers in Patients With Laryngeal Squamous Cell Carcinoma. Ear Nose Throat J . 2020;99(6):371-378. doi:10.1177/0145561319876910/ASSET/IMAGES/LARGE/10.1177_0145561319876910-FIG2.JPEG Du J, Chen S, Shi J, et al. The association between the lymphocyte-monocyte ratio and disease activity in rheumatoid arthritis. Clin Rheumatol . 2017;36(12):2689-2695. doi:10.1007/S10067-017-3815-2 Parvizi J, Ghanem E, Sharkey P, Aggarwal A, Burnett RSJ, Barrack RL. Diagnosis of infected total knee: findings of a multicenter database. Clin Orthop Relat Res . 2008;466(11):2628-2633. doi:10.1007/S11999-008-0471-5 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6605766","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":455213866,"identity":"cba5f74d-fb36-42fd-b8cb-75b7683241ce","order_by":0,"name":"Shıkhalı Isgandarlı","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7ElEQVRIiWNgGAWjYDACCcYGBoYCCWbG9uYDIK4MkVoMJNiZe44lgLg8RGgBEQYM/OwzcgxATMJa5Gc3t0n8MLCQ5u058/nVjRoLHgb2w0c34NNicOdgs2GPgYSxZHvvNuucY0CH8aSl3cCrRSKx8QGPgUSyYc/ZbcY5bEAtEjxmeLXIz0hsOPjHQKJ+/42cZ8Y5/4jQwnAjsfEx0BZmxhk5zI9z24jQYnAjsdlYBqSl55gZc26fBA8bIb/Iz0h/Jvmmog4UlY8/53yrk+NnP3wMv8OQABs4jtiIVQ4CzB9IUT0KRsEoGAUjBwAANAxGEK52KCwAAAAASUVORK5CYII=","orcid":"","institution":"","correspondingAuthor":true,"prefix":"","firstName":"Shıkhalı","middleName":"","lastName":"Isgandarlı","suffix":""},{"id":455213867,"identity":"7c2f5360-718f-4513-aaad-f3859c18bccd","order_by":1,"name":"Evrim Sırın","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Evrim","middleName":"","lastName":"Sırın","suffix":""},{"id":455213868,"identity":"aabc49a7-12aa-48af-8c42-6d7bdb90de5e","order_by":2,"name":"Vali Mamedov","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Vali","middleName":"","lastName":"Mamedov","suffix":""},{"id":455213869,"identity":"32078193-764d-4aae-8df7-4b39205a6f42","order_by":3,"name":"Fatih Küçükdurmaz","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Fatih","middleName":"","lastName":"Küçükdurmaz","suffix":""}],"badges":[],"createdAt":"2025-05-06 18:38:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6605766/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6605766/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82617988,"identity":"ae7a57f8-28e9-471e-ac6b-c73463c865e6","added_by":"auto","created_at":"2025-05-13 11:55:22","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":158313,"visible":true,"origin":"","legend":"\u003cp\u003ereceiver operating characteristic (ROC) curves for serum markers.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6605766/v1/91edd48f85b7cc1c09b73064.png"},{"id":91056469,"identity":"cc6906d4-9118-4391-9496-45758b6d01d1","added_by":"auto","created_at":"2025-09-11 08:02:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":986409,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6605766/v1/fd988f8c-88bf-4785-8c87-8ddd877afe77.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Diagnostic Value of Complete Blood Count Ratios in Identifying Periprosthetic Joint Infections: A Retrospective Cohort Study","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003ePatients with severe arthritis can regain their quality of life and experience pain relief after total joint arthroplasty (TJA)\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. After a total knee or hip arthroplasty, periprosthetic joint infection (PJI) is a devastating complication with a high morbidity and mortality rate\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. PJI occurs when bacteria or other microorganisms invade the surgical site and establish an infection around the implanted joint prosthesis\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Challenges in diagnosis and management of PJI pose a major challenge in orthopaedic surgery and treatment remains challenging. Early and accurate diagnosis of infection is essential to enable appropriate treatment, which can range from debridement with retention to single-stage or two-stage revision surgery\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. The treatment of PJI greatly benefits from the early and accurate identification. In the early postoperative stage, a less traumatic method to keep the prosthetic components in place could be preferred. But still, the lack of a definitive test makes PJI diagnosis extremely challenging. \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe Musculoskeletal Infection Society (MSIS) established guidelines in attempt to standardize the definition of PJI (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. These criteria are now extensively used by surgeons all over the world and they have significantly increased treatment efficiency and diagnostic confidence. Although the major criteria for infection or the definite proof are the same across all definitions, the minor criteria or the supportive evidence vary and are less universally accepted. In recent years, a variety of markers have been examined and made available, such as synovial CRP, synovial alpha-defensin, synovial leukocyte esterase (LE), and molecular methods like next-generation sequencing\u003csup\u003e\u003cspan additionalcitationids=\"CR9 CR10 CR11 CR12 CR13 CR14 CR15 CR16\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMusculoskeletal Infection Society (MSIS) diagnostic criteria.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e Major Criteria (at least one of the following)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDecision\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eTwo positive cultures of the same organism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eInfected\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eSinus tract with evidence of communication to the joint or visualization of the prosthesis\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e\u003cb\u003ePreoperative Diagnosis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMinor Criteria\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eScore\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eDecision\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSerum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eElevated CRP or D-Dimer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u003cb\u003e\u0026ge;6 Infected\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e2\u0026ndash;5 Possibly Infected\u003c/b\u003e \u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;1 Not Infected\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eElevated ESR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eSynovial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eElevated synovial WBC count or LE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePositive alpha-defensin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eElevated synovial PMN (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eElevated synovial CRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"4\" nameend=\"c2\" namest=\"c1\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003eIntraoperative Diagnosis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eInclusive pre-op score or dry tap\u003c/b\u003e \u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eScore\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eDecision\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePreoperative score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003e\u0026ge;6 Infected\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e4\u0026ndash;5 Inconclusive\u003c/b\u003e \u003csup\u003e\u003cb\u003eb\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e\u0026le;3 Not Infected\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePositive histology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePositive purulence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSingle positive culture\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e For patients with inconclusive minor criteria, operative criteria can also be used to fulfill definition for PJI.\u003c/p\u003e \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e Consider further molecular diagnostics such as next-generation sequencing.\u003c/p\u003e \u003cp\u003eCRP, C-reactive protein; ESR, erythrocyte sedimentation rate; LE, leukocyte esterase; PMN, polymorphonuclear; WBC, white blood cell.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eBlood biomarkers may be the most appealing of these diagnostic markers due to their ease, particularly for some routine tests given to all inpatients. The purpose of our study is to search, whether there are some auxiliary criteria for MSIS for diagnosing PJI by analyzing the ratios within the simple CBC.\u003c/p\u003e"},{"header":"MATERIAL AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design\u003c/h2\u003e \u003cp\u003eThis retrospective analysis was performed on patients who underwent revision hip or knee arthroplasty at our hospital between January 2010 and September 2021. The study was authorized by the hospital's ethics committee.\u003c/p\u003e \u003cp\u003e227 patients, who were operated for lower extremity periprosthetic infection were identified by retrospectively scanning the hospital automation system. Patients who underwent DAIR (Debridement-Antibiotics-Implant Retention) procedure (n\u0026thinsp;=\u0026thinsp;125), joint arthrodesis (n\u0026thinsp;=\u0026thinsp;12) and one-stage revision operation (n\u0026thinsp;=\u0026thinsp;10) were excluded from the study. In addition, patients who were under immunosuppression due to systemic diseases affecting blood results, such as systemic lupus erythematosus (SLE) and hemolytic uremic syndrome (HUS)-like thrombocytopenia, were also excluded from the study (n\u0026thinsp;=\u0026thinsp;14).\u003c/p\u003e \u003cp\u003eTwo-stage procedure was planned for 66 of these patients, and erythrocyte sedimentation rate (ESR), complete blood count (CBC) and C-reactive protein (CRP) parameters were taken from all patients before the first stage.\u003c/p\u003e \u003cp\u003eAt the same time, we identified a total of 65 total knee and total hip arthroplasty patients with similar sociodemographic characteristics and no complications as control group. ESR, CRP, CBC and biochemistry panel were obtained from all patients in the control group before hospitalization. We compared the ratios such as monocyte/lymphocyte ratio (MLR), neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), and platelet/mean platelet volume ratio (PVR) in CBC and ESR and CRP in both groups.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData Analyses\u003c/h3\u003e\n\u003cp\u003eDescriptive data are shown with percentage values ​​from categorical data, and median minimum-maximum values ​​in continuous data. In the comparison of categorical data, \u003cem\u003eChi\u003c/em\u003e-Square and Fisher Tests were used in appropriate places. Measurement data were tested with Kolmogorov-Smirnov tests for the assumption of normal distribution. Mann-Whitney U test and Kruskal Wallis test were used in appropriate places for the comparison of measurement data that did not show normal distribution. Spearman correlation analysis was used to examine the correlation of two measurement data. P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was accepted for statistical significance in all analyzes. Bonferroni correction was made for the \u003cem\u003eP\u003c/em\u003e-value in Post Hoc analyses. Analyzes were performed with IBM \u0026copy; SPSS program version 20.\u003c/p\u003e \u003cp\u003eThe study was carried out with a total of 131 participants, 34 of whom were men and 97 were women. When the sociodemographic and clinical characteristics of the study groups were examined, no statistically significant difference was found (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eExamination of socio-demographic characteristics according to study groups.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePJI group, n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eControl group, n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (22.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 (29.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.396\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51 (77.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46 (70.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYoung\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (31.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28 (43.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.183\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eElder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45 (68.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37 (56.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70.0 (43.0\u0026ndash;90.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68.0 (28.0\u0026ndash;95.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.135\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eBMI*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.4 (21.4\u0026ndash;47.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.7 (20.9\u0026ndash;47.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.107\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eBMI groups\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (13.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (14.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.228\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverweight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (24.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24 (37.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObesity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41 (62.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31(48.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSmoke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (12.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (10.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.784\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41 (62.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31 (48.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e Chi-square test, \u003csup\u003eb\u003c/sup\u003e Mann-Whitney U test, * In measurements, median minimum-maximum values ​​are presented instead of numbers and percentages.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eExamination of clinical features according to study groups.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePJI group, n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eControl group, n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIntensive care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (47.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35 (53.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.483\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (52.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30 (46.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSurvival status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51 (77.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64 (98.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDead\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (22.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (1.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSurgery site\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (47.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28 (43.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.654\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLeft\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (53.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37 (56.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLaterality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnilateral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54 (81.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65 (100.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBilateral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (18.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBlood transfusion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (34.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (10.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43 (65.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58 (89.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCCI*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.0 (0.0\u0026ndash;9.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.0 (0.0\u0026ndash;8.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.006\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e Chi-square test, \u003csup\u003eb\u003c/sup\u003e Mann-Whitney U test\u003c/p\u003e \u003cp\u003e* In the measurements, median minimum-maximum values ​​are presented instead of numbers and percentages.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eWhen preoperative laboratory values were compared according to the study groups, a statistically significant correlation was found between ESR, CRP, lymphocyte count, neutrophil count, Mean Platelet Volume (MPV), platelet count, MLR, PLR, NLR, PVR and values between both groups (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eExamination of preoperative laboratory data according to the study groups (before the 1st stage for the infected group and before the arthroplasty surgery for the control group) and postoperative (interstage interval for the infected group, after the arthroplasty surgery for the control group)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePJI Group\u003c/p\u003e \u003cp\u003eMedian (Min-Max)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControl Group\u003c/p\u003e \u003cp\u003eMedian (Min-Max)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003ePreoperative\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSedimentation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65.0 (17.0-120.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.5 (1.0\u0026ndash;87.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29.5 (3.1\u0026ndash;304.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.2 (0.5\u0026ndash;30.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonocyte\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.6 (0.0-1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5 (0.2\u0026ndash;1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.111\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocyte\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.6 (0.1\u0026ndash;4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.9 (0.5-4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.3 (1.5\u0026ndash;14.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.4 (1.3\u0026ndash;11.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMPV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.1 (6.3\u0026ndash;12.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.0 (7.1\u0026ndash;12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e291.0 (163.0-607.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e243.0 (111.0-424.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.4 (0.0-1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3 (0.1\u0026ndash;1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e189.0 (49.4\u0026ndash;2930.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e122.6 (48.3\u0026ndash;522.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.6 (1.0-16.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.0 (0.6\u0026ndash;11.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePVR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.0 (16.5\u0026ndash;71.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.6 (8.9\u0026ndash;57.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e4th weeks after surgery\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSedimentation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46.0 (2.0-1332.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.0 (4.0\u0026ndash;87.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.9 (1.1-304.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.0 (1.5\u0026ndash;154.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonocyte\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5 (0.2\u0026ndash;3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6 (0.2\u0026ndash;10.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocyte\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.4 (0.6\u0026ndash;4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.9 (0.6\u0026ndash;4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.3 (1.4\u0026ndash;20.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.9 (1.9\u0026ndash;11.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMPV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.1 (6.3\u0026ndash;11.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.1 (7.0-322.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e278.0 (115.0-589.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e250.0 (109.0-424.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.4 (0.2\u0026ndash;1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3 (0.1\u0026ndash;4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.441\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e190.0 (62.5-420.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e129.5 (57.9-353.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.8 (1.0-22.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.8 (0.9\u0026ndash;8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.605\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePVR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35.1 (9.7\u0026ndash;91.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.5 (1.0-58.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003e Mann-Whitney U test\u003c/p\u003e \u003cp\u003eMLR: monocyte/lymphocyte ratio, NLR: neutrophil/lymphocyte ratio, PLR: platelet/lymphocyte ratio, PVR: platelet/mean platelet volume ratio, ESR: erythrocyte sedimentation rate, CRP: C reactive protein, MVP: Mean platelet volume\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eBefore the first stage, ESR, CRP, neutrophil count, platelet count, MLR, PLR, NLR and PVR values were found to be significantly higher in the PJI group compared to the control group. There was no significant difference in serum glucose and monocyte count values for both groups.\u003c/p\u003e \u003cp\u003eIn the comparison with the PJI group before the first stage and the control group before the arthroplasty surgery, lymphocyte count and mean platelet volume values ​​were found to be significantly lower in the PJI group. (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eWhen the postoperative 4th week laboratory values ​​were compared a statistically significant relationship was found for ESR, CRP, monocyte count, lymphocyte count, platelet count, neutrophil count, MPV, PLR and PVR values.\u003c/p\u003e \u003cp\u003eESR and CRP values ​​were significantly higher in the patient group compared to the control group. In the comparison of the post-op 4 weeks blood results after 1 stage in the infected group with the post-op 4week blood results in the control group, there was no significant distinction between NLR and MLR. However, PVR values ​​were found to be significantly higher in the patient group (35.1 (9.7\u0026ndash;91.6)) compared to the control group (26.5 (1.0-58.9)) (p:\u0026lt;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). However, when we used Receiver Operating Characteristic (ROC) curve analysis, we found low sensitivity and specificity of NLR, PVR and PLR (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) (Fig.\u0026nbsp;2).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eReceiver Operating Characteristic (ROC) curve analysis results for determination of threshold values of laboratory values for disease prediction.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eThreshold Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSEN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSPE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e+LR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-LR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePPV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNPV\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSedimentation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.859\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.783\u0026ndash;0.916\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e66.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e91.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e88.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e73.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.908\u0026ndash;0.987\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;8.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e93.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e91.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e11.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e91.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e93.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonocyte\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.581\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.490\u0026ndash;0.668\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocyte\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.656\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.566\u0026ndash;0.739\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026le;1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e72.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e66.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e65.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.670\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.581\u0026ndash;0.751\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e55.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e70.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e64.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e63.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMPV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.728\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.642\u0026ndash;0.804\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026le;8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e67.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e69.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e67.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e69.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.676\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.586\u0026ndash;0.756\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;331\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e41.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e86.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e73.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e60.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.662\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.572\u0026ndash;0.744\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e55.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e73.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e66.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e64.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.763\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.679\u0026ndash;0.834\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;129.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e80.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e64.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e68.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e77.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.748\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.663\u0026ndash;0.821\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;2.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e78.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e64.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e67.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e76.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePVR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.745\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.660\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;29.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e78.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e61.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e65.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e75.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003eAUC: Area under curve, CI: Confidence Interval, SEN: Sensitivity, SPE: Specificity, +LR: Positive likelihood ratio, -LR: Negative likelihood ratio, PPV: Positive predictive value, NPV: Negative predictive value, MLR: monocyte/lymphocyte ratio, NLR: neutrophil/lymphocyte ratio, PLR: platelet/lymphocyte ratio, PVR: platelet/mean platelet volume ratio, ESR: erythrocyte sedimentation rate, CRP: C reactive protein, MVP: Mean platelet volume.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003ePJI is a significant concern in orthopaedic surgery. The incidence ranges from 1\u0026ndash;3% after the arthroplasty population\u003csup\u003e\u003cspan additionalcitationids=\"CR19 CR20\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Treatment options vary from debridement with retention to single-stage or two-stage revision. This condition is a major challenge in orthopaedic surgery, leading to multiple surgeries, prolonged hospitalization, increased morbidity, and a significant economic burden. Additionally, accurate and early diagnosis of PJI is essential for appropriate treatment. Furthermore, PJI is one of the leading indications for revision surgery and poses a significant threat to patients after an arthroplasty procedure.\u003c/p\u003e \u003cp\u003eThe two stage reimplantation arthroplasty treatment is the gold standard method accepted worldwide for the treatment of chronic PJI patients\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. However, the most important stage is the difficulties in diagnosis due to the lack of a gold standard test. Early PJI is managed mostly with DAIR procedure, and patients who do not respond to this treatment are candidates for a two-stage reimplantation treatment. Early diagnosis not only reduces treatment costs but also has a profound impact on the psychosocial status of the patient\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eA combination of clinical assessment, blood tests, synovial fluid aspiration, microbiologic and histopathologic examinations, as well as imaging, must be used to make an early and accurate diagnosis of PJI. The Magnetic Resonance Imaging (MRI) and ultrasonography (US) may be useful tools for the diagnosis, which are defined by sinus surrounding the joint, fluid accumulation, and soft tissue swelling\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe synovial fluid aspiration is also a useful test however, it\u0026rsquo;s an invasive procedure, and occasionally synovial fluid cannot be obtained despite repeated aspirations, particularly for the hip joint. Besides, a non-infected joint can get contaminated because of repeated aspirations.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eRecent advances in biomarker research have expanded the diagnostic options for periprosthetic joint infection (PJI). Tripathi et al.\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e reviewed a wide array of serum and synovial biomarkers and concluded that while traditional indicators such as ESR and CRP remain central to diagnosis, novel markers like D-dimer, fibrinogen, and CBC-derived ratios (MLR, NLR, PLR) are gaining attention, though their roles are not yet definitive. Tian et al.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e, in a meta-analysis, confirmed the high diagnostic accuracy of alpha-defensin while also noting the limited and variable utility of D-dimer and IL-6. Importantly, Xu et al.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e conducted a large retrospective study and demonstrated that CRP alone exhibited superior diagnostic accuracy compared to other markers, and that combining CBC-derived ratios such as MLR, NLR, and PLR did not significantly improve diagnostic performance. These findings highlight that while CBC-based ratios are easily accessible and cost-effective, their diagnostic value remains modest, especially in patients with underlying inflammatory disorders or in complex clinical scenarios. Consistent with these reports, our study also found that although NLR, PVR, and PLR showed moderate diagnostic accuracy, they were not reliable enough to serve as standalone diagnostic tools for PJI. These results collectively emphasize the need for careful interpretation of such markers and suggest that they should be considered as adjuncts rather than definitive indicators in the diagnostic algorithm for PJI.\u003c/p\u003e \u003cp\u003eThe gradual method is advised because a single, genuine gold standard continues to be inaccessible. Purchasing of many of the relevant tests and markers is costly or time-consuming. Furthermore, some diagnostic procedures, such synovial alpha defensin, require for tools and knowledge that might not be widely accessible or available at all institutions\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFor the diagnosis of PJI, a mixture of different clinical examination techniques is still advised. Therefore, the key to the preoperative diagnosis and the creation of an appropriate treatment plan is the identification of reliable and accurate potential markers for the diagnosis of PJI. The primary objectives of this study were to evaluate the effectiveness of ratio indicators as a diagnostic tool and the performance of PJI combination diagnosis using simple results obtained from complete blood counts.\u003c/p\u003e \u003cp\u003ePLR has emerged as a potential marker for PJI. Previous studies have indicated that platelet counts and MPV should be considered in the diagnosis of PJI in patients undergoing total knee and hip revision surgery. Moreover, high platelet counts have been shown to be an important additional test for the diagnosis of deep surgical site infections after open internal fixation\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Furthermore, perioperative PLR and NLR have been identified as potential predictors of deep vein thrombosis (DVT) following total joint arthroplasty.\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e As DVT was not specifically screened for or excluded in our study cohort, this represents a potential confounding factor. Elevated ratios observed in our infected group may, in part, reflect underlying thromboembolic processes rather than infection alone. Therefore, the influence of such conditions should be taken into consideration when interpreting these biomarkers for diagnosing periprosthetic joint infection.\u003c/p\u003e \u003cp\u003eUse of hematological markers, including PLR and NLR have shown promising results in evaluating and diagnosing periprosthetic joint infection\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Additionally, MLR has been proposed as an indicator in the diagnosis and risk stratification of infectious diseases, including PJI. The use of hematological markers, such as PLR, NLR and MLR, may provide valuable insight into the presence and severity of periprosthetic joint infection.\u003c/p\u003e \u003cp\u003eHong Xu et al investigated serum biomarkers to evaluate patients with inflammatory disorders for periprosthetic joint infections prior to revision arthroplasty\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. The study focused on the efficacy of CRP, ESR, plasma fibrinogen, MLR and NLR as biomarkers. 30 of the 62 patients in the retrospective analysis had infections related to inflammatory disorders, including psoriatic arthritis, rheumatoid arthritis, ankylosing spondylitis, systemic lupus erythematosus (SLE) and gouty arthritis.\u003c/p\u003e \u003cp\u003eThe current study used receiver operating characteristic (ROC) curves to determine the sensitivity and specificity of the biomarkers tested to diagnose infection, and then optimal cutoffs were determined based on the Youden index. The results showed that CRP, fibrinogen and the combination of CRP and fibrinogen were effective in screening PJI in patients with inflammatory diseases. The combination of CRP with fibrinogen produced 86.2% sensitivity and 78.1% specificity. The current study also examined other biomarkers, including ESR, MLR, and NLR, but discovered that these markers had limited diagnostic utility in screening individuals with inflammatory disorders for infection before revision arthroplasty.\u003c/p\u003e \u003cp\u003eAnother study conducted by Maimaiti et al.\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e aimed to investigate the possibility of using routine blood tests for the accurate diagnosis of PJI. The study included 246 patients undergoing total hip or knee revision surgery and collected laboratory parameters including erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), D-dimer, plasma fibrinogen, serum white blood cell (WBC) and various rate markers calculated based on complete blood count ratios. The researchers found that the combination of coagulation-related markers such as MLR, NLR, PLR and platelet/average platelet volume ratio (PVR), showed promising diagnostic performance in differentiating PJI from aseptic loosening.\u003c/p\u003e \u003cp\u003eAlthough MLR, NLR, PVR, and PLR demonstrated moderate diagnostic accuracy in our study, their overall performance was found to be insufficient for reliable initial diagnosis of PJI. This finding is in accordance with the results of a recent meta-analysis by Festa et al.\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e, which evaluated 11 publications and concluded that these CBC-derived ratios, while easily obtainable, show limited diagnostic value and cannot replace established biomarkers due to their low specificity and variable sensitivity. Therefore, although they may serve as supportive markers, they should not be considered standalone diagnostic tools for .\u003c/p\u003e \u003cp\u003eGao et al proved that MLR had accurate predictive value in predicting knee osteoarthritis(36). In other studies, the marker was found to be useful for predicting outcomes in cases of cancer, tuberculosis, and a variety of autoimmune illnesses\u003csup\u003e\u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. These investigations hypothesized that MLR may be used as an additional diagnostic tool when there were less lymphocytes present due to an increase in monocyte count brought on by systemic immunological responses. In the current study, the MLR was similar in both PJI group and non-infected control group. Therefore, MLR was not found to support the diagnosis of a PJI.\u003c/p\u003e \u003cp\u003eIn addition, the low sensitivity and specificity of NLR, PVR and PLR alone in estimating PJI in our study were limiting the use of these criteria in estimating PJI alone.\u003c/p\u003e \u003cp\u003eContrary to the MSIS criteria, when we compared the PJI group with the non-infected control group, a CRP value above 8.71 was significant for infection. This difference may be attributed to variations in patient characteristics and the timing of diagnosis. In our cohort, many infections were likely identified at earlier stages or involved low-grade pathogens, which may have resulted in lower systemic inflammatory responses. Furthermore, while the MSIS criteria propose generalized thresholds, population-specific cut-off values can vary according to clinical circumstances and diagnostic sensitivity. Supporting this, Parvizi et al. \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e demonstrated that optimal CRP cut-off values differ based on the type of joint and clinical context, emphasizing that rigid thresholds may not be universally applicable .Therefore, in our study, a CRP level above 8.71 mg/L proved significant, likely reflecting these contextual factors and the heterogeneity of our patient population.\u003c/p\u003e \u003cp\u003eThere were various restrictions on the study. The primary restriction is its retrospective feature, which means that a number of confounding factors could have affected PJI.\u003c/p\u003e \u003cp\u003eFurthermore, it is important to acknowledge that several patient- and surgery-related factors, including surgical environment, perioperative conditions, and pre-existing comorbidities, may affect the likelihood of periprosthetic joint infection. However, due to limited access to detailed operative data in patients undergoing primary arthroplasty at external centers, our analysis focused exclusively on laboratory parameters as diagnostic indicators. This limitation should be considered when interpreting the diagnostic accuracy of the evaluated biomarkers.\u003c/p\u003e \u003cp\u003eIn conclusion, we\u0026rsquo;ve showed that the diagnostic accuracy of PJI in arthroplasty patients can\u0026rsquo;t be evaluated by using serum PLR, NLR and PVR computed from a simple complete blood count in conjunction with other hematologic and aspirate markers. We have ensured by our study that PLR, PVR and NLR together cannot be used as supportive criteria to the MSIS criteria.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the ethical principles of the Declaration of Helsinki. Ethical approval was obtained from the Marmara University Faculty of medicine clinical research ethics committee (Date: 07.01.2022; Document No: 09.2022.110). Written informed consent was waived due to the retrospective nature of the study.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study were retrospectively retrieved from Marmara University Hospital automation system and are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003cbr\u003e\u0026nbsp;Written informed consent was obtained from the patient for publication of this study and accompanying images.\u003cbr\u003e\u0026nbsp;\u003cbr\u003e \u003cstrong\u003eFunding\u003cbr\u003e\u003c/strong\u003eNo funding was received for this study.\u003cbr\u003e\u0026nbsp;\u003cbr\u003e \u003cstrong\u003eCompeting interests\u003cbr\u003e\u003c/strong\u003eThe authors declare that they have no competing interests.\u003cbr\u003e\u0026nbsp;\u003cbr\u003e \u003cstrong\u003eAuthors\u0026apos; contributions\u003cbr\u003e\u003c/strong\u003eShıkhalı Isgandarlı, MD: Study design, patient management, data collection, manuscript writing and corresponding author.\u003cbr\u003e\u0026nbsp;Evrim Şirin, MD: Study design and manuscript review.\u003cbr\u003e\u0026nbsp;Vali Mamedov, MD: Case review and literature review.\u003cbr\u003e\u0026nbsp;Fatih K\u0026uuml;\u0026ccedil;\u0026uuml;kdurmaz, MD: Manuscript revision and supervision.\u003cbr\u003e\u0026nbsp;All authors read and approved the final manuscript.\u003cbr\u003e\u0026nbsp;\u003cbr\u003e \u003cstrong\u003eAcknowledgements\u003cbr\u003e\u003c/strong\u003eNot applicable.\u003cbr\u003e\u0026nbsp;\u003cbr\u003e \u003cstrong\u003eAuthors\u0026apos; information\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Not applicable.\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the ethical principles of the Declaration of Helsinki. Ethical approval was obtained from the Marmara University Faculty of medicine clinical research ethics committee (Date: 07.01.2022; Document No: 09.2022.110). Written informed consent was waived due to the retrospective nature of the study.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study were retrospectively retrieved from Marmara University Hospital automation system and are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eBle\u0026szlig; HH, Kip M. White Paper on Joint Replacement. \u003cem\u003eWhite Paper on Joint Replacement: Status of Hip and Knee Arthroplasty Care in Germany\u003c/em\u003e. Published online November 3, 2018:1-135. doi:10.1007/978-3-662-55918-5\u003c/li\u003e\n \u003cli\u003eYu BZ, Fu J, Chai W, Hao LB, Chen JY. Neutrophil to lymphocyte ratio as a predictor for diagnosis of early Periprosthetic joint infection. \u003cem\u003eBMC Musculoskelet Disord\u003c/em\u003e. 2020;21(1):1-7. doi:10.1186/s12891-020-03704-5\u003c/li\u003e\n \u003cli\u003eBeam E, Osmon D. Prosthetic Joint Infection Update. \u003cem\u003eInfect Dis Clin North Am\u003c/em\u003e. 2018;32(4):843-859. doi:10.1016/J.IDC.2018.06.005\u003c/li\u003e\n \u003cli\u003eLi C, Renz N, Trampuz A. Management of Periprosthetic Joint Infection. \u003cem\u003eHip Pelvis\u003c/em\u003e. 2018;30(3):138. doi:10.5371/hp.2018.30.3.138\u003c/li\u003e\n \u003cli\u003eZimmerli W, Trampuz A, Ochsner PE. \u003cem\u003eProsthetic-Joint Infections\u003c/em\u003e. Vol 16.; 2004. www.nejm.org\u003c/li\u003e\n \u003cli\u003eAltsitzioglou P, Avgerinos K, Karampikas V, et al. 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The diagnostic effect of \u0026alpha;-defensin, D-dimer, and IL-6 in periprosthetic joint infection: A systematic review and diagnostic meta-analysis. \u003cem\u003eJournal of Orthopaedic Surgery\u003c/em\u003e. 2020;28(3). doi:10.1177/2309499020971861/ASSET/IMAGES/LARGE/10.1177_2309499020971861-FIG6.JPEG\u003c/li\u003e\n \u003cli\u003eXu H, Xie J, Zhang S, Wang D, Huang Z, Zhou Z. Potential Blood Biomarkers for Diagnosing Periprosthetic Joint Infection: A Single-Center, Retrospective Study. \u003cem\u003eAntibiotics\u003c/em\u003e. 2022;11(4). doi:10.3390/ANTIBIOTICS11040505\u003c/li\u003e\n \u003cli\u003eBalato G, De Matteo V, Ascione T, et al. Archives of Orthopaedic and Trauma Surgery Laboratory-based versus qualitative assessment of \u0026alpha;-defensin in periprosthetic hip and knee infections: a systematic review and meta-analysis. 1:3. doi:10.1007/s00402-019-03232-5\u003c/li\u003e\n \u003cli\u003eZhang Z, Ji Y, Wang Z, Qiu X, Chen Y. 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Diagnosis of infected total knee: findings of a multicenter database. \u003cem\u003eClin Orthop Relat Res\u003c/em\u003e. 2008;466(11):2628-2633. doi:10.1007/S11999-008-0471-5\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Periprosthetic joint infection, CRP, neutrophil/lymphocyte ratio, platelet/lymphocyte ratio, platelet /mean platelet volume ratio, two-stage revision arthroplasty","lastPublishedDoi":"10.21203/rs.3.rs-6605766/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6605766/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eIt is challenging to diagnose a periprosthetic joint infection (PJI) that frequently requires a combination of clinical and laboratory findings. Simple predictors of inflammation include the monocyte/lymphocyte ratio (MLR), neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), and platelet/mean platelet volume ratio (PVR), all of which may be easily documented from a complete blood count. This study's objective is to search possible adjunctive diagnostic parameters to support Musculoskeletal Infection Society (MSIS) criteria(Table 1) in patients with suspected PJI, that are not costly, non-invasive, and helpful to non-gold standard diagnostic criteria.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eWe compared the blood results of two patient groups a group of 66 patients with chronic periprosthetic joint infection who were scheduled for two-staged arthroplasty with those of a group of 65 arthroplasty patients with similar sociodemographic characteristics and without any complications.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eAccording to the analysis results, a threshold value of \u0026gt; 2.26 for NLR and a threshold value of \u0026gt;29.5 for PVR in the preoperative period had the highest sensitivity (78.7 %), while a threshold value of \u0026gt; 0.35 for MLR in the preoperative period had the highest specificity (73.9%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eDespite having moderate diagnostic accuracy NLR, PVR, and PLR were not considered as a useful diagnostic test to support the diagnosis of PJI. In conclusion, although NLR, PVR, and PLR showed moderate diagnostic accuracy, they were not reliable enough to serve as diagnostic tools for PJI. Further studies are warranted to explore their potential roles.\u003c/p\u003e","manuscriptTitle":"Diagnostic Value of Complete Blood Count Ratios in Identifying Periprosthetic Joint Infections: A Retrospective Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-13 11:39:17","doi":"10.21203/rs.3.rs-6605766/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2633881c-ba53-41d1-928d-3ba000f4fd41","owner":[],"postedDate":"May 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-11T07:54:01+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-13 11:39:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6605766","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6605766","identity":"rs-6605766","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}