Delta Neutrophil Index in Suspected Septic Arthritis: A Diagnostic Accuracy Study

Delta Neutrophil Index in Suspected Septic Arthritis: A Diagnostic Accuracy 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 Study protocol Delta Neutrophil Index in Suspected Septic Arthritis: A Diagnostic Accuracy Study Hüseyin Emre TEPEDELENLİOGLU, Hilmi ALKAN, Tural TALIBLI, Ünal Erkanov HÜSEYİNOV, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7227655/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: Septic arthritis is an orthopedic emergency requiring prompt diagnosis and treatment to prevent joint destruction and systemic complications. Standard inflammatory markers such as CRP, ESR, and WBC lack specificity, often leading to diagnostic uncertainty, especially in differentiating septic arthritis from inflammatory arthropathies. The Delta Neutrophil Index (DNI), reflecting immature granulocyte levels, may offer improved diagnostic performance. Questions/purposes: We aimed to evaluate (1) Does serum DNI provide superior diagnostic accuracy compared with CRP, ESR, and WBC for culture-positive septic arthritis? (2) What sensitivity and specificity are achieved at an optimal DNI threshold? Methods: In this singlecentre retrospective diagnostic cohort study, 71 patients who underwent surgery for suspected septic arthritis between November 2022 and March 2025 were enrolled. Preoperative serum biomarkers were obtained; synovial aspirate appearance and intraoperative cultures served as the reference standard. PCT measured in 33/71 patients. Diagnostic performance was assessed with ROC analysis; AUCs were compared with the bootstrapadapted DeLong test, and multivariable logistic regression adjusted for age, sex, and affected joint. Results: DNI values were significantly higher in culture-positive patients (p = 0.0002). While CRP and ESR showed moderate diagnostic value, DNI exhibited the strongest correlation with positive cultures and purulent synovial fluid. The ROC AUC for DNI was significantly higher than those of CRP, ESR and WBC (p < 0.001), suggesting better diagnostic performance. A DNI cut-off value of 0.6 yielded the highest sensitivity and specificity among all markers. Importantly, DNI values did not increase significantly in patients with inflammatory arthritis flares, unlike CRP. Conclusions: The Delta Neutrophil Index is a rapid, cost-effective, and more specific biomarker than conventional inflammatory parameters for diagnosing septic arthritis. Its use may help differentiate septic arthritis from inflammatory arthropathies and reduce unnecessary surgical interventions. Level of Evidence: Level III, retrospective diagnostic study. Septic arthritis delta neutrophil index diagnostic accuracy ROC analysis Figures Figure 1 Figure 2 INTRODUCTION Septic arthritis is one of the orthopedic emergencies [ 3 ]. It occurs due to the hematogenous spread or direct inoculation of pathogenic microorganisms into the joint, leading to significant morbidity and complications. Septic arthritis is one of the few conditions in orthopedics that requires immediate surgical intervention. However, it can often be confused with non-infectious diseases such as rheumatologic conditions, inflammatory arthritis, and crystal arthropathy, which can increase comorbidity due to unforeseen unnecessary surgeries. Distinguishing septic arthritis from other inflammatory arthritis is essential to prevent unnecessary surgery while also ensuring that an orthopedic emergency is not overlooked. Currently, the diagnosis of septic arthritis is made through comprehensive medical history, physical examination findings, blood tests, and joint aspiration samples [ 17 ]. However, there are limitations in the clinical and laboratory diagnostic values that are routinely used in diagnosis. The fundamental principle of treating bacterial septic arthritis is prompt joint irrigation and debridement, followed by targeted antibiotic therapy. A 'left shift' in a laboratory blood test has long been associated with bacterial infection. The Delta Neutrophil Index (DNI) provides a quantitative, automated measure of this shift. DNI is derived from the difference between the myeloperoxidase (MPO) channel and the nuclear lobularity channel, which allows automated quantification of immature granulocytes (IG) promyelocytes, myelocytes, metamyelocytes, bands [ 9 ]. In addition to routinely used blood tests, DNI has recently begun to be utilized for the diagnosis of infections [ 14 ]. It has previously been used in orthopedic studies to assess foot infections. DNI is a parameter that indicates the ratio of immature granulocytes in peripheral circulation to the total neutrophil count [ 6 ]. DNI can be calculated by blood cell analyzer routinely used in laboratories and is a rapid and cost-effective parameter for diagnosing infections [ 10 ]. Some studies have shown that DNI is more predictive of infection and prognosis than traditional markers such as white blood cell (WBC) count, absolute neutrophil count (ANC), and C-reactive protein (CRP) [ 1 , 14 ]. However, DNI’s predictive power in the diagnosis of septic arthritis is still debated. The aim of this study is to compare DNI with other routinely used serum markers in diseases with high morbidity, such as septic arthritis of the knee, and to retrospectively examine the correlation of DNI values with bacterial growth in knee joint fluid samples. MATERIALS & METHOD Study Design and Setting This retrospective study was conducted in accordance with the ethical criteria of the Declaration of Helsinki 1964 and was approved by the institutional human research ethics committee (No: AEŞH-BADEK-2024-319, Date: 25.09.2024). Participants Between November 2022 and March 2025, 84 adult (> 18 y) patients presenting with a preliminary diagnosis of acute septic arthritis and undergoing surgery at a single tertiary care center (XXX Hospital) were examined. Eligibility Criteria Exclusion criteria included prior antibiotic therapy exceeding 24 h (n = 6), immunosuppressive medication (n = 4) or malignancy (n = 3). After excluding patients with mentioned comorbidities, a total of 71 patients were included in the study (Fig. 1 ). Biomarker Measurement Venous blood samples were obtained as a routine preoperative analysis within 2 hours before surgery for biomarkers. Patients were categorized as infected and uninfected. Biomarkers were studied with their normal parameters such as white blood cell count (WBC), C-reactive protein (CRP), procalcitonin (PCT), erythrocyte sedimentation rate (ESR), and delta neutrophil index (DNI) were recorded, along with the affected joint (including side), age, and sex, leukocyte count obtained from synovial aspirate (Categorized as 50000) and bacterial presence (Positive or negative), type of synovial fluid (Purulent or serous), and culture results (Negative or positive). Cut-off values for parameters for WBC, CRP, PCT and ESR were 4.5–11⁹/L, 5 mg/L, 0.5 ng/mL and 14 mm/h, respectively. DNI was calculated using an automated counter (ADVIA 120; Siemens Healthcare Diagnostics, Bayer, USA) and cut-off value is set as below 0.6, as indicated in the counter [ 11 ]. The values of the current biomarkers were compared in terms of specificity and sensitivity based on the type of synovial aspirate and culture results. Since PCT is not routinely requested in all patients, the analysis was limited to the 33 patients for whom this measurement was available. Sample-Size Considerations A pilot post-hoc power analysis suggested an AUC of 0.90 for DNI and 0.70 for CRP. Assuming a two-sided α = 0.05, 80% power, and 40% culture positivity, 58 patients were required to detect an AUC difference of 0.20; therefore concluded that the sample size was sufficient for the study. Statistical Analysis The statistical analysis of the study data was conducted at a 95% confidence level, and results with a p-value < 0.05 were considered statistically significant. Normality was assessed using the Shapiro–Wilk test; as biomarkers were non-normally distributed, Mann-Whitney U tests were applied for two-group comparisons (culture positive vs negative) and Kruskal-Wallis tests for multi-group scenarios when required. Relationships between categorical variables (sex, side) were examined with the Chi-square test. Diagnostic performances of DNI, CRP, ESR and WBC were compared via ROC (Receiver Operating Characteristic) curve analysis (higher values assumed positive). AUC (Area Under the Curve) values quantified diagnostic accuracy, and pairwise AUC differences were evaluated using a bootstrap approximation to the DeLong test. The statistical and logistical regression analysis of the data was performed using SPSS version 22.0. RESULTS The demographic characteristics and outcomes of patients are summarized in Table 1 . The distributions of age, sex, and side between the culture-positive group and the negative group were similar (p > 0.05). However, biomarker levels were significantly higher in culture-positive cases (Mann–Whitney U, p < 0.05). The comparative data of synovial leukocyte results and intraoperative culture results are shown in Table 2 . No statistically significant correlation was observed when comparing both groups (p > 0.05). The sensitivity of synovial leukocyte results was found to be 83%, and the specificity was 3%. Among culturenegative patients with an adjudicated clinical diagnosis (Infected n = 20; Uninfected n = 22), DNI values were significantly higher in infected cases (p < 0.001). In ROC analyses using clinical infection as the outcome, DNI achieved the highest overall accuracy (AUC = 0.75). CRP showed moderate performance (AUC = 0.64). ESR performed poorly (AUC = 0.44), whereas WBC favored sensitivity over specificity (AUC = 0.55). Procalcitonin was available in a small subset (n = 16) and was not discriminative (AUC = 0.51) (Table 3 ). Pairwise, DNI outperformed ESR (ΔAUC = 0.31, p = 0.005) and WBC (ΔAUC = 0.20, p < 0.047), while the difference versus CRP did not reach significance (ΔAUC = 0.11, p = 0.25) (Table 4 ). Collectively, these findings suggest that in culturenegative cases, DNI functions as a specific “rulein” threshold for clinically infected presentations, whereas CRP and especially ESR/WBC offer less balanced discrimination. In the ROC curve analysis, DNI achieved the highest diagnostic accuracy with an AUC of 0.92. The sensitivity for a threshold value of ≥ 0.60 was calculated at 93%, with a specificity of 86%. Although the sensitivities for CRP and ESR reached 72% and 41%, respectively, their specificities remained 61% and 85%. WBC demonstrated moderate performance with a sensitivity of 79% and a specificity of 42%. PCT demonstrated sensitivity of 53% and a specificity of 87%. (Table 6) (Fig. 2 ). The bootstrap comparison confirmed that the AUC of DNI was significantly higher than that of CRP, ESR and WBC (p < 0.001), but the AUC difference between DNI and PCT did not exceed the statistical threshold (p = 0.128) (Table 7). DISCUSSION Septic arthritis is most commonly observed in the knee and hip joints, although it can also occur less frequently in the hand, elbow, shoulder, foot, and ankle. In the differential diagnosis of acute septic arthritis, an acute rheumatoid flare should particularly be considered. In our study, we examined the parameters of patients who presented with a preliminary diagnosis of septic arthritis. The study excluded patients who presented with a diagnosis of acute rheumatoid flare, and the sensitivity and specificity of the DNI were compared with other infection parameters. In a study conducted by Pyo et al. [ 13 ], the DNI values were compared between patients presenting with septic arthritis and acute gout attack, and it was found that DNI was the most powerful independent predictor for septic arthritis. Our study also found that DNI had a stronger predictive value compared to other parameters. The most frequently isolated pathogen in culture results was S. Aureus [ 17 ]. Our findings were similar, with S. Aureus being cultured in 65.1% of the samples. E. coli was identified as a Gram-negative bacterium. On the other hand, culture results in patients with septic arthritis do not always return positive. It has been reported that the positivity rate of synovial fluid cultures ranges from 75–95% [ 16 , 7 ]. When examining the clinically uninfected patients from our study group who tested culture-negative, it was observed that there were instances of trauma and rheumatoid flare-ups. This situation explains the relatively low sensitivity of CRP (C-reactive protein) and ESR (erythrocyte sedimentation rate). It was noted that DNI (delta neutrophil index) did not show an increase in these cases. Also DNI has the advantage of being rapid, inexpensive, and universally available with CBC, thus useful when aspiration is delayed or not feasible. Therefore, we believe that in addition to culture results, the patient's clinical condition, the nature of the joint fluid, and the levels of DNI should also be taken into consideration. One of the values used in the diagnosis of septic arthritis is the amount of leukocyte count in the synovial fluid. Traditionally, a measurement of 50000 or more WBCs with a neutrophil percentage of 90% or higher is considered indicative of septic arthritis [ 5 ]. However, the reliability of this parameter is also debated. In a retrospective study conducted by Eren et al. [ 2 ], the synovial WBC counts and culture results of 192 patients with septic arthritis were compared, revealing that 164 patients with WBC counts below 50000 had positive culture results, which could lead to misdiagnosis. We also observed positive culture results in our patients with such low leukocyte counts; the occurrence of negative culture results in the presence of high leukocyte counts raises questions about the reliability of the synovial WBC parameter. The gold standard for the diagnosis of septic arthritis is the results of gram-staining and culture of synovial fluid. However, considering that culture results may take up to 2 days and that emergency surgery may be required within a timeframe of 6 hours, it becomes necessary to implement diagnosis and treatment based on other parameters. Although synovial white blood cell (WBC) count is considered to be indicative in diagnosis, an increase in synovial WBC can also be observed in inflammatory arthritis flares [ 8 ]. Among our excluded patients, 11 of them were known to have experienced an inflammatory arthritis flare, only 1 had a WBC count of below 20,000 in the synovial fluid, while all others exceeded 50,000. In addition, all patients whose leukocyte counts were below 20000 had positive culture results. Therefore, there is a need for a more reliable biomarker. We believe that DNI may address this deficiency. Differentiating septic arthritis from inflammatory arthritis is of great importance. The laboratory parameters commonly used for this purpose are CRP, ESR, and WBC. However, none of these markers have specific cut-off values for diagnostic differentiation, and their specificity is low. When we investigated the cut-off values of the existing markers based on cultures and joint fluids, we found that the cut-off values were 148.52 for CRP, 57 for ESR, and 10.35 for WBC. However, we also determined that only CRP provided a statistically significant interpretation compared to the others. Furthermore, when examining the cut-off data for DNI, we found that its AUC (area under the curve) was statistically more significant than that of the other markers. This indicates that DNI is a more valuable parameter for the diagnosis of septic arthritis compared to the other markers. DNI primarily reflects the ratio of immature granulocytes. It is believed that elevated DNI is associated with the severity of infection and mortality [ 12 , 15 ]. A study conducted by Moon et al.[ 8 ] examined the relationship between DNI and pneumonia-related sepsis, indicating that it has predictive value for 28-day mortality. A similar result was obtained in research conducted by Pyo et al. [ 11 ] who reported finding the highest DNI value of 6.4 in a patient with septic arthritis and bacteremia, identifying a cutoff value for bacteremia in a similar range of 5.2–6.5 in other studies [ 3 , 8 ]. In our study, the highest value observed was 5.9, with no signs of bacteremia. Since PCT is not a routinely used biomarker for the diagnosis of septic arthritis, it was not requested for all patients. Initially, it was planned to conduct the study with 27 patients; however, it was abandoned due to not reaching the required minimum number after power analysis. When examining the role of PCT in the diagnosis of septic arthritis, a retrospective study conducted by West et al. on 53 patients reported cut-off values for PCT as 0.25 and 0.32, respectively, concluding that PCT was superior to WBC, ESR, and CRP in terms of specificity and sensitivity [ 18 ]. Similarly, Zhao et al. concluded that PCT is more valuable than CRP for the diagnosis of septic arthritis [ 19 ]. In our study, the cut-off value for the analyzers used was set at 0.5; although its specificity was found to be higher than that of CRP and WBC, its sensitivity was found to be low. Considering the number of patients we had, we believe that the sensitivity and specificity of PCT could be higher, but still, DNI (delta neutrophil index) is considered to be stronger and more cost-effective for diagnosis. LIMITATIONS Several limitations of this study should be mentioned. First, this study was performed at a single center, sample size was modest and the results were analyzed retrospectively. The reason that another center was not involved most of the local health centers’ analyzers lack of DNI measurement or possesses different types of analyzer thus different values for DNI. Second, not cell analyzers can measure the DNI, thus restricting its clinical application. Third, procalcitonin could not have been requested in all patients, Small PCT sample limits generalizability of its AUC. CONCLUSION This study demonstrates that DNI shows the highest accuracy in the diagnosis of septic arthritis. In patients presenting with findings of septic arthritis, a DNI value of 0.6 or higher can be interpreted as supportive of septic arthritis. Particularly in patients suspected of inflammatory arthritis flare-ups, the DNI value is a parameter as valuable as synovial fluid sampling. Therefore, we believe that including DNI in the diagnostic criteria for septic arthritis would be beneficial. Declarations Conflict of Interests: The authors declare that they have no potential conflict of interest with respect to the authorship and/or publication of this article. Funding: This study received no financial support for the research and/or authorship of this article. Ethical Approval : This study was approved by the Ankara Etlik City Hospital Ethics Committee with the Approval No: AEŞH-BADEK-2024-319 and Approval Date: 25.09.2024. ***Study was conducted in Ankara Etlik City Hospital. Acknowledgments: Not applicable. Authorship Contributions Surgical Practices: V.B., T.T., H.E.T., H.A., Concept: F.A., H.E.T. Design: H.E.T., H.A., E.A., V.B. Data Collection or Processing: Ü.E.H., T.T. Analysis or Interpretation: H.E.T., E.A. Literature Search: H.A., H.E.T., E.A. Writing: H.E.T., F.A., V.B.. References Cho J, Lee JH, Lee DH, Kim J, Uh Y. Performance Comparison of Procalcitonin, Delta Neutrophil Index, C-Reactive Protein, and Serum Amyloid A Levels in Patients with Hematologic Diseases. Diagnostics (Basel). 2023;13(7). Eren TK, Aktekin CN. How reliable are the synovial cell count and blood parameters in the diagnosis of septic arthritis? Jt Dis Relat Surg. 2023;34(3):724–30. Goldenberg DL. Septic arthritis. Lancet. 1998;351(9097):197–202. Horowitz DL, Katzap E, Horowitz S, Barilla-LaBarca ML. Approach to septic arthritis. Am Fam Physician. 2011;84(6):653–60. Jeng GW, Wang CR, Liu ST, et al. Measurement of synovial tumor necrosis factor-alpha in diagnosing emergency patients with bacterial arthritis. Am J Emerg Med. 1997;15(7):626–9. Kratz A, Maloum K, O’Malley C, et al. Enumeration of nucleated red blood cells with the ADVIA 2120 Hematology System: an International Multicenter Clinical Trial. Lab Hematol. 2006;12(2):63–70. Margaretten ME, Kohlwes J, Moore D, Bent S. Does this adult patient have septic arthritis? JAMA. 2007;297(13):1478–88. Moon S, Park Y, Hong CW et al. A usefulness of Delta Neutrophil Index (DNI) for prediction of 28-day mortality in patients with pneumonia-induced sepsis in the intensive care unit. J Clin Med 2025;14(6). Nahm CH, Choi JW, Lee J. Delta neutrophil index in automated immature granulocyte counts for assessing disease severity of patients with sepsis. Ann Clin Lab Sci. 2008;38(3):241–6. Nam M, Son BH, Seo JE, Kim IR, Park CK, Kim HK. Improved diagnostic and prognostic power of combined Delta Neutrophil Index and Mean Platelet Volume in pediatric sepsis. Ann Clin Lab Sci. 2018;48(2):223–30. Park BH, Kang YA, Park MS, et al. Delta neutrophil index as an early marker of disease severity in critically ill patients with sepsis. BMC Infect Dis. 2011;11:299. 10.1186/1471-2334-11-299 . Published 2011 Nov 1. Pyo JY, Park JS, Park YB, Lee SK, Ha YJ, Lee SW. Delta neutrophil index as a marker for differential diagnosis between flare and infection in febrile systemic lupus erythematosus patients. Lupus. 2013;22(11):1102–9. Pyo JY, Kim DS, Jung SM, Song JJ, Park YB, Lee SW. Clinical significance of delta neutrophil index in the differential diagnosis between septic arthritis and acute gout attack within 24 hours after hospitalization. Med (Baltim). 2017;96(30):e7431. Seok Y, Choi JR, Kim J, Kim YK, Lee J, Song J, et al. Delta neutrophil index: a promising diagnostic and prognostic marker for sepsis. Shock. 2012;37(3):242–6. Shin JE, Deok Seo K, Cha HJ, et al. Usefulness of the delta neutrophil index in predicting surgery in patients with foot and ankle infection. PLoS ONE. 2022;17(8):e0272574. Shmerling RH, Delbanco TL, Tosteson AN, Trentham DE. Synovial fluid tests. What should be ordered? JAMA. 1990;264(8):1009–14. Visser S, Tupper J. Septic until proven otherwise: approach to and treatment of the septic joint in adult patients. Can Fam Physician. 2009;55(4):374–5. West K, Almekdash H, Fisher J, Rounds AD, Murphree J, Simpson J. Procalcitonin as a Predictor of Septic Knee Arthritis: A Retrospective Cohort Study. J Am Acad Orthop Surg Glob Res Rev. 2023;7(1):e2200261. Zhao J, Zhang S, Zhang L, Dong X, Li J, Wang Y, Yao Y. Serum procalcitonin levels as a diagnostic marker for septic arthritis: a meta-analysis. Am J Emerg Med. 2017;35(8):1166–71. Tables Table 1: Demographics of the patients Variable Value Age (mean ± SD) 56.3 ± 24.7 Sex: Male 36 (60.0%) Sex: Female 24 (40.0%) Side: Right 36 (51.7%) Side: Left 35 (48.3%) Culture: Negative Infected : Uninfected : 42 (59.2%) 20 (%47,6) 22 (%52,4) Culture: Positive Pathogen : S. Aureus Pathogen : S. Epidermidis Pathogen : S . Dysgalactia Pathogen : E. Coli 29 (40.8%) 15 (51.7%) 3 (10.3%) 1(3.4%) 6 (20.6%) Fluid type: Purulent 51 (71.8%) Fluid type: Serous 20 (28.2%) Joint: Knee 57 (80.3%) Joint: Elbow 4 (5.6%) Joint: Shoulder 3 (4.2%) Joint: Hip 3 (4.2%) Joint: Wrist 1 (1.4%) Joint: Ankle 3 (4.2%) Table 2: Comparative Demographics of the Synovial Leukocyte Count & Culture Results Leukocyte Count Culture: Negative Culture: Positive 50 000 40 25 Pearson χ² = 5.28, df = 2, p = 0.072. Table 3: ROC Performance of Biomarkers in Distinguishing Clinical Infection In Culture Negative Patients Biomarker n AUC (95% CI) Optimal cut‑off Sensitivity (95% CI) Spesivity (95% CI) DNI 41 0.75 (0.60–0.88) ≥ 0.50 0.53 (0.30–0.75) 0.86 (0.71–1.00) CRP (mg/L) 41 0.64 (0.47–0.81) ≥ 124.3 0.53 (0.29–0.75) 0.82 (0.65–0.96) ESR (mm/h) 41 0.44 (0.37–0.74) ≥ 99 0.11 (0.00–0.35) 0.95 (0.71–1.00) WBC (×10⁹/L) 41 0.55 (0.37–0.74) ≥ 9.97 0.84 (0.65–1.00) 0.41 (0.20–0.63) PCT (ng/mL)* 16 0.51 (0.21–0.82) ≥ 0.34 0.25 (0.00–0.60) 0.88 (0.60–1.00) Table 4: Comparison of AUCs in Culture Negative Patients Comparison ΔAUC 95% CI p (bootstrap) DNI vs ESR +0.31 0.11 – 0.51 0.005 DNI vs WBC +0.20 0.00 – 0.40 0.047 DNI vs CRP +0.11 −0.06 – 0.28 0.25 Table 5: ROC Summary and Optimal Cut-Off Biomarker AUC (95 % CI) Cut-off Sensitivity (95 %CI) Specificity (95 % CI) DNI 0.920 0.60 0.931 0.857 CRP 0.685 114.9 mg L⁻¹ 0.724 0.619 ESR 0.631 74 mm h⁻¹ 0.414 0.857 WBC 0.580 10.35 × 10⁹ L⁻¹ 0.793 0.429 PCT 0.671 0.51 ng mL⁻¹ 0.529 0.875 Table 6: Pairwise AUC comparisons (bootstrap) Comparison ΔAUC P Value DNI vs CRP +0.236 < 0.001 DNI vs ESR +0.289 < 0.001 DNI vs WBC +0.341 < 0.001 DNI vs PCT +0.179 0.128 CRP vs ESR +0.053 0.488 CRP vs WBC +0.105 0.183 CRP vs PCT –0.063 0.543 ESR vs WBC +0.052 0.602 ESR vs PCT –0.185 0.097 WBC vs PCT –0.150 0.243 Additional Declarations No competing interests reported. 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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-7227655","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Study protocol","associatedPublications":[],"authors":[{"id":494160523,"identity":"d480d6fa-0c21-4eab-8a72-c2aa3080284d","order_by":0,"name":"Hüseyin Emre TEPEDELENLİOGLU","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4UlEQVRIiWNgGAWjYBACAziLvQdM8fARpyUBpPYMA8MBIMVGvBaJHLAWBoJazNm70z58/GGTxy/59uDjjzl2MmwMzA8f3cCjxbLn7OaZMxLSiiVn5yUbHNyWDHQYm7FxDj6H3cjdzMyTcDhxw+0cM4mD25iBWnjYpPFquf92M/OfhP+J+2+eAWmpJ0LLDd7NzAwJBxI3SPCAtBwmQsuZ3M2MPWnJxRJncowNzm47zsPGTMgvx89uZvhhY5fH337G8EHltmp7fvbmh4/xaYGBBASTmQjlaFpGwSgYBaNgFKABAPONSSciLcqvAAAAAElFTkSuQmCC","orcid":"","institution":"Ankara Etlik City Hospital","correspondingAuthor":true,"prefix":"","firstName":"Hüseyin","middleName":"Emre","lastName":"TEPEDELENLİOGLU","suffix":""},{"id":494160524,"identity":"8dc1e707-70b2-415b-841c-a08a28540bb6","order_by":1,"name":"Hilmi ALKAN","email":"","orcid":"","institution":"Ankara Etlik City Hospital","correspondingAuthor":false,"prefix":"","firstName":"Hilmi","middleName":"","lastName":"ALKAN","suffix":""},{"id":494160527,"identity":"2f583861-c2f9-4d7d-9896-26889d685736","order_by":2,"name":"Tural TALIBLI","email":"","orcid":"","institution":"Ankara Etlik City Hospital","correspondingAuthor":false,"prefix":"","firstName":"Tural","middleName":"","lastName":"TALIBLI","suffix":""},{"id":494160529,"identity":"e5e98b6c-a98f-4314-b08b-d62ff3c7f029","order_by":3,"name":"Ünal Erkanov HÜSEYİNOV","email":"","orcid":"","institution":"Ankara Etlik City Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ünal","middleName":"Erkanov","lastName":"HÜSEYİNOV","suffix":""},{"id":494160530,"identity":"3ba5c83b-b6ed-4757-b040-3189d6fc8c7f","order_by":4,"name":"Ferid ABDULALIYEV","email":"","orcid":"","institution":"Yozgat City Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ferid","middleName":"","lastName":"ABDULALIYEV","suffix":""},{"id":494160531,"identity":"a87002e8-f107-4407-aee5-09a12b445958","order_by":5,"name":"Erkan AKGÜN","email":"","orcid":"","institution":"Lokman Hekim Üniversitesi","correspondingAuthor":false,"prefix":"","firstName":"Erkan","middleName":"","lastName":"AKGÜN","suffix":""},{"id":494160532,"identity":"da0c1d03-e030-4253-b8a7-fdaa71c8d3aa","order_by":6,"name":"Vedat BİÇİCİ","email":"","orcid":"","institution":"Ankara Etlik City Hospital","correspondingAuthor":false,"prefix":"","firstName":"Vedat","middleName":"","lastName":"BİÇİCİ","suffix":""}],"badges":[],"createdAt":"2025-07-27 17:23:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7227655/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7227655/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88409812,"identity":"66054420-645e-46a0-a139-9c2b753b300e","added_by":"auto","created_at":"2025-08-06 08:20:48","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":77746,"visible":true,"origin":"","legend":"\u003cp\u003eFlow Chart\u003c/p\u003e","description":"","filename":"flowchartscreenedborderfixed.png","url":"https://assets-eu.researchsquare.com/files/rs-7227655/v1/7e24e7f0708b3d93ce484d0c.png"},{"id":88411876,"identity":"12e9f364-ba45-4b26-8ba7-1340f80cc16c","added_by":"auto","created_at":"2025-08-06 08:28:48","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":171954,"visible":true,"origin":"","legend":"\u003cp\u003eROC Curve Analysis\u003c/p\u003e","description":"","filename":"ROCmultiauto.png","url":"https://assets-eu.researchsquare.com/files/rs-7227655/v1/53dff550c66dc8485a722fe1.png"},{"id":91787891,"identity":"f9b85610-d5f6-481a-9ed8-ac7ec2a1e3c8","added_by":"auto","created_at":"2025-09-21 09:38:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":924073,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7227655/v1/faf171dc-6f60-4596-9778-39d74b5fb6af.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eDelta Neutrophil Index in Suspected Septic Arthritis: A Diagnostic Accuracy Study\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eSeptic arthritis is one of the orthopedic emergencies [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. It occurs due to the hematogenous spread or direct inoculation of pathogenic microorganisms into the joint, leading to significant morbidity and complications. Septic arthritis is one of the few conditions in orthopedics that requires immediate surgical intervention. However, it can often be confused with non-infectious diseases such as rheumatologic conditions, inflammatory arthritis, and crystal arthropathy, which can increase comorbidity due to unforeseen unnecessary surgeries.\u003c/p\u003e\u003cp\u003eDistinguishing septic arthritis from other inflammatory arthritis is essential to prevent unnecessary surgery while also ensuring that an orthopedic emergency is not overlooked. Currently, the diagnosis of septic arthritis is made through comprehensive medical history, physical examination findings, blood tests, and joint aspiration samples [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. However, there are limitations in the clinical and laboratory diagnostic values that are routinely used in diagnosis. The fundamental principle of treating bacterial septic arthritis is prompt joint irrigation and debridement, followed by targeted antibiotic therapy.\u003c/p\u003e\u003cp\u003eA 'left shift' in a laboratory blood test has long been associated with bacterial infection. The Delta Neutrophil Index (DNI) provides a quantitative, automated measure of this shift. DNI is derived from the difference between the myeloperoxidase (MPO) channel and the nuclear lobularity channel, which allows automated quantification of immature granulocytes (IG) promyelocytes, myelocytes, metamyelocytes, bands [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In addition to routinely used blood tests, DNI has recently begun to be utilized for the diagnosis of infections [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. It has previously been used in orthopedic studies to assess foot infections. DNI is a parameter that indicates the ratio of immature granulocytes in peripheral circulation to the total neutrophil count [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. DNI can be calculated by blood cell analyzer routinely used in laboratories and is a rapid and cost-effective parameter for diagnosing infections [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Some studies have shown that DNI is more predictive of infection and prognosis than traditional markers such as white blood cell (WBC) count, absolute neutrophil count (ANC), and C-reactive protein (CRP) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. However, DNI\u0026rsquo;s predictive power in the diagnosis of septic arthritis is still debated.\u003c/p\u003e\u003cp\u003eThe aim of this study is to compare DNI with other routinely used serum markers in diseases with high morbidity, such as septic arthritis of the knee, and to retrospectively examine the correlation of DNI values with bacterial growth in knee joint fluid samples.\u003c/p\u003e"},{"header":"MATERIALS \u0026 METHOD","content":"\u003cp\u003e\u003cb\u003eStudy Design and Setting\u003c/b\u003e\u003c/p\u003e\u003cp\u003e This retrospective study was conducted in accordance with the ethical criteria of the Declaration of Helsinki 1964 and was approved by the institutional human research ethics committee (No: AEŞH-BADEK-2024-319, Date: 25.09.2024).\u003c/p\u003e\u003cp\u003e\u003cb\u003eParticipants\u003c/b\u003e\u003c/p\u003e\u003cp\u003eBetween November 2022 and March 2025, 84 adult (\u0026gt;\u0026thinsp;18 y) patients presenting with a preliminary diagnosis of acute septic arthritis and undergoing surgery at a single tertiary care center (XXX Hospital) were examined.\u003c/p\u003e\u003cp\u003e\u003cb\u003eEligibility Criteria\u003c/b\u003e\u003c/p\u003e\u003cp\u003eExclusion criteria included prior antibiotic therapy exceeding 24 h (n\u0026thinsp;=\u0026thinsp;6), immunosuppressive medication (n\u0026thinsp;=\u0026thinsp;4) or malignancy (n\u0026thinsp;=\u0026thinsp;3). After excluding patients with mentioned comorbidities, a total of 71 patients were included in the study (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eBiomarker Measurement\u003c/b\u003e\u003c/p\u003e\u003cp\u003eVenous blood samples were obtained as a routine preoperative analysis within 2 hours before surgery for biomarkers. Patients were categorized as infected and uninfected. Biomarkers were studied with their normal parameters such as white blood cell count (WBC), C-reactive protein (CRP), procalcitonin (PCT), erythrocyte sedimentation rate (ESR), and delta neutrophil index (DNI) were recorded, along with the affected joint (including side), age, and sex, leukocyte count obtained from synovial aspirate (Categorized as \u0026lt;\u0026thinsp;20000, 20000\u0026ndash;50000 and \u0026gt;\u0026thinsp;50000) and bacterial presence (Positive or negative), type of synovial fluid (Purulent or serous), and culture results (Negative or positive). Cut-off values for parameters for WBC, CRP, PCT and ESR were 4.5\u0026ndash;11⁹/L, 5 mg/L, 0.5 ng/mL and 14 mm/h, respectively. DNI was calculated using an automated counter (ADVIA 120; Siemens Healthcare Diagnostics, Bayer, USA) and cut-off value is set as below 0.6, as indicated in the counter [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The values of the current biomarkers were compared in terms of specificity and sensitivity based on the type of synovial aspirate and culture results. Since PCT is not routinely requested in all patients, the analysis was limited to the 33 patients for whom this measurement was available.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSample-Size Considerations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA pilot post-hoc power analysis suggested an AUC of 0.90 for DNI and 0.70 for CRP. Assuming a two-sided α\u0026thinsp;=\u0026thinsp;0.05, 80% power, and 40% culture positivity, 58 patients were required to detect an AUC difference of 0.20; therefore concluded that the sample size was sufficient for the study.\u003c/p\u003e\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eThe statistical analysis of the study data was conducted at a 95% confidence level, and results with a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered statistically significant. Normality was assessed using the Shapiro\u0026ndash;Wilk test; as biomarkers were non-normally distributed, Mann-Whitney U tests were applied for two-group comparisons (culture positive vs negative) and Kruskal-Wallis tests for multi-group scenarios when required. Relationships between categorical variables (sex, side) were examined with the Chi-square test. Diagnostic performances of DNI, CRP, ESR and WBC were compared via ROC (Receiver Operating Characteristic) curve analysis (higher values assumed positive). AUC (Area Under the Curve) values quantified diagnostic accuracy, and pairwise AUC differences were evaluated using a bootstrap approximation to the DeLong test. The statistical and logistical regression analysis of the data was performed using SPSS version 22.0.\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eThe demographic characteristics and outcomes of patients are summarized in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. The distributions of age, sex, and side between the culture-positive group and the negative group were similar (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). However, biomarker levels were significantly higher in culture-positive cases (Mann\u0026ndash;Whitney U, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The comparative data of synovial leukocyte results and intraoperative culture results are shown in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. No statistically significant correlation was observed when comparing both groups (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The sensitivity of synovial leukocyte results was found to be 83%, and the specificity was 3%.\u003c/p\u003e\n\u003cp\u003eAmong culturenegative patients with an adjudicated clinical diagnosis (Infected n\u0026thinsp;=\u0026thinsp;20; Uninfected n\u0026thinsp;=\u0026thinsp;22), DNI values were significantly higher in infected cases (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In ROC analyses using clinical infection as the outcome, DNI achieved the highest overall accuracy (AUC\u0026thinsp;=\u0026thinsp;0.75). CRP showed moderate performance (AUC\u0026thinsp;=\u0026thinsp;0.64). ESR performed poorly (AUC\u0026thinsp;=\u0026thinsp;0.44), whereas WBC favored sensitivity over specificity (AUC\u0026thinsp;=\u0026thinsp;0.55). Procalcitonin was available in a small subset (n\u0026thinsp;=\u0026thinsp;16) and was not discriminative (AUC\u0026thinsp;=\u0026thinsp;0.51) (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Pairwise, DNI outperformed ESR (\u0026Delta;AUC\u0026thinsp;=\u0026thinsp;0.31, p\u0026thinsp;=\u0026thinsp;0.005) and WBC (\u0026Delta;AUC\u0026thinsp;=\u0026thinsp;0.20, p\u0026thinsp;\u0026lt;\u0026thinsp;0.047), while the difference versus CRP did not reach significance (\u0026Delta;AUC\u0026thinsp;=\u0026thinsp;0.11, p\u0026thinsp;=\u0026thinsp;0.25) (Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). Collectively, these findings suggest that in culturenegative cases, DNI functions as a specific \u0026ldquo;rulein\u0026rdquo; threshold for clinically infected presentations, whereas CRP and especially ESR/WBC offer less balanced discrimination.\u003c/p\u003e\n\u003cp\u003eIn the ROC curve analysis, DNI achieved the highest diagnostic accuracy with an AUC of 0.92. The sensitivity for a threshold value of \u0026ge;\u0026thinsp;0.60 was calculated at 93%, with a specificity of 86%. Although the sensitivities for CRP and ESR reached 72% and 41%, respectively, their specificities remained 61% and 85%. WBC demonstrated moderate performance with a sensitivity of 79% and a specificity of 42%. PCT demonstrated sensitivity of 53% and a specificity of 87%. (Table 6) (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). The bootstrap comparison confirmed that the AUC of DNI was significantly higher than that of CRP, ESR and WBC (p\u0026thinsp;\u003cstrong\u003e\u0026lt;\u003c/strong\u003e\u0026thinsp;0.001), but the AUC difference between DNI and PCT did not exceed the statistical threshold (p\u0026thinsp;=\u0026thinsp;0.128) (Table 7).\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eSeptic arthritis is most commonly observed in the knee and hip joints, although it can also occur less frequently in the hand, elbow, shoulder, foot, and ankle. In the differential diagnosis of acute septic arthritis, an acute rheumatoid flare should particularly be considered. In our study, we examined the parameters of patients who presented with a preliminary diagnosis of septic arthritis. The study excluded patients who presented with a diagnosis of acute rheumatoid flare, and the sensitivity and specificity of the DNI were compared with other infection parameters. In a study conducted by Pyo et al. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], the DNI values were compared between patients presenting with septic arthritis and acute gout attack, and it was found that DNI was the most powerful independent predictor for septic arthritis. Our study also found that DNI had a stronger predictive value compared to other parameters.\u003c/p\u003e\u003cp\u003eThe most frequently isolated pathogen in culture results was S. Aureus [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Our findings were similar, with S. Aureus being cultured in 65.1% of the samples. E. coli was identified as a Gram-negative bacterium. On the other hand, culture results in patients with septic arthritis do not always return positive. It has been reported that the positivity rate of synovial fluid cultures ranges from 75\u0026ndash;95% [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. When examining the clinically uninfected patients from our study group who tested culture-negative, it was observed that there were instances of trauma and rheumatoid flare-ups. This situation explains the relatively low sensitivity of CRP (C-reactive protein) and ESR (erythrocyte sedimentation rate). It was noted that DNI (delta neutrophil index) did not show an increase in these cases. Also DNI has the advantage of being rapid, inexpensive, and universally available with CBC, thus useful when aspiration is delayed or not feasible. Therefore, we believe that in addition to culture results, the patient's clinical condition, the nature of the joint fluid, and the levels of DNI should also be taken into consideration.\u003c/p\u003e\u003cp\u003eOne of the values used in the diagnosis of septic arthritis is the amount of leukocyte count in the synovial fluid. Traditionally, a measurement of 50000 or more WBCs with a neutrophil percentage of 90% or higher is considered indicative of septic arthritis [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, the reliability of this parameter is also debated. In a retrospective study conducted by Eren et al. [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], the synovial WBC counts and culture results of 192 patients with septic arthritis were compared, revealing that 164 patients with WBC counts below 50000 had positive culture results, which could lead to misdiagnosis. We also observed positive culture results in our patients with such low leukocyte counts; the occurrence of negative culture results in the presence of high leukocyte counts raises questions about the reliability of the synovial WBC parameter.\u003c/p\u003e\u003cp\u003eThe gold standard for the diagnosis of septic arthritis is the results of gram-staining and culture of synovial fluid. However, considering that culture results may take up to 2 days and that emergency surgery may be required within a timeframe of 6 hours, it becomes necessary to implement diagnosis and treatment based on other parameters. Although synovial white blood cell (WBC) count is considered to be indicative in diagnosis, an increase in synovial WBC can also be observed in inflammatory arthritis flares [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Among our excluded patients, 11 of them were known to have experienced an inflammatory arthritis flare, only 1 had a WBC count of below 20,000 in the synovial fluid, while all others exceeded 50,000. In addition, all patients whose leukocyte counts were below 20000 had positive culture results. Therefore, there is a need for a more reliable biomarker. We believe that DNI may address this deficiency.\u003c/p\u003e\u003cp\u003eDifferentiating septic arthritis from inflammatory arthritis is of great importance. The laboratory parameters commonly used for this purpose are CRP, ESR, and WBC. However, none of these markers have specific cut-off values for diagnostic differentiation, and their specificity is low. When we investigated the cut-off values of the existing markers based on cultures and joint fluids, we found that the cut-off values were 148.52 for CRP, 57 for ESR, and 10.35 for WBC. However, we also determined that only CRP provided a statistically significant interpretation compared to the others. Furthermore, when examining the cut-off data for DNI, we found that its AUC (area under the curve) was statistically more significant than that of the other markers. This indicates that DNI is a more valuable parameter for the diagnosis of septic arthritis compared to the other markers.\u003c/p\u003e\u003cp\u003eDNI primarily reflects the ratio of immature granulocytes. It is believed that elevated DNI is associated with the severity of infection and mortality [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. A study conducted by Moon et al.[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] examined the relationship between DNI and pneumonia-related sepsis, indicating that it has predictive value for 28-day mortality. A similar result was obtained in research conducted by Pyo et al. [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] who reported finding the highest DNI value of 6.4 in a patient with septic arthritis and bacteremia, identifying a cutoff value for bacteremia in a similar range of 5.2\u0026ndash;6.5 in other studies [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In our study, the highest value observed was 5.9, with no signs of bacteremia.\u003c/p\u003e\u003cp\u003eSince PCT is not a routinely used biomarker for the diagnosis of septic arthritis, it was not requested for all patients. Initially, it was planned to conduct the study with 27 patients; however, it was abandoned due to not reaching the required minimum number after power analysis. When examining the role of PCT in the diagnosis of septic arthritis, a retrospective study conducted by West et al. on 53 patients reported cut-off values for PCT as 0.25 and 0.32, respectively, concluding that PCT was superior to WBC, ESR, and CRP in terms of specificity and sensitivity [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Similarly, Zhao et al. concluded that PCT is more valuable than CRP for the diagnosis of septic arthritis [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In our study, the cut-off value for the analyzers used was set at 0.5; although its specificity was found to be higher than that of CRP and WBC, its sensitivity was found to be low. Considering the number of patients we had, we believe that the sensitivity and specificity of PCT could be higher, but still, DNI (delta neutrophil index) is considered to be stronger and more cost-effective for diagnosis.\u003c/p\u003e\u003cp\u003e\u003cb\u003eLIMITATIONS\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSeveral limitations of this study should be mentioned. First, this study was performed at a single center, sample size was modest and the results were analyzed retrospectively. The reason that another center was not involved most of the local health centers\u0026rsquo; analyzers lack of DNI measurement or possesses different types of analyzer thus different values for DNI. Second, not cell analyzers can measure the DNI, thus restricting its clinical application. Third, procalcitonin could not have been requested in all patients, Small PCT sample limits generalizability of its AUC.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study demonstrates that DNI shows the highest accuracy in the diagnosis of septic arthritis. In patients presenting with findings of septic arthritis, a DNI value of 0.6 or higher can be interpreted as supportive of septic arthritis. Particularly in patients suspected of inflammatory arthritis flare-ups, the DNI value is a parameter as valuable as synovial fluid sampling. Therefore, we believe that including DNI in the diagnostic criteria for septic arthritis would be beneficial.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of Interests:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no potential conflict of interest with respect to the authorship and/or publication of this article.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis study received no financial support for the research and/or authorship of this article.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e This study was approved by the Ankara Etlik City Hospital Ethics Committee with the Approval No: AEŞH-BADEK-2024-319 and Approval Date: 25.09.2024. ***Study was conducted in Ankara Etlik City Hospital.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthorship Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSurgical Practices: V.B., T.T., H.E.T., H.A.,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConcept: F.A., H.E.T.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDesign: H.E.T., H.A., E.A., V.B.\u003c/p\u003e\n\u003cp\u003eData Collection or Processing: \u0026Uuml;.E.H., T.T.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAnalysis or Interpretation: H.E.T., E.A.\u003c/p\u003e\n\u003cp\u003eLiterature Search: H.A., H.E.T., E.A.\u003c/p\u003e\n\u003cp\u003eWriting: H.E.T., F.A., V.B..\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCho J, Lee JH, Lee DH, Kim J, Uh Y. Performance Comparison of Procalcitonin, Delta Neutrophil Index, C-Reactive Protein, and Serum Amyloid A Levels in Patients with Hematologic Diseases. \u003cem\u003eDiagnostics (Basel).\u003c/em\u003e 2023;13(7).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEren TK, Aktekin CN. How reliable are the synovial cell count and blood parameters in the diagnosis of septic arthritis? Jt Dis Relat Surg. 2023;34(3):724\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGoldenberg DL. Septic arthritis. Lancet. 1998;351(9097):197\u0026ndash;202.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHorowitz DL, Katzap E, Horowitz S, Barilla-LaBarca ML. Approach to septic arthritis. Am Fam Physician. 2011;84(6):653\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJeng GW, Wang CR, Liu ST, et al. Measurement of synovial tumor necrosis factor-alpha in diagnosing emergency patients with bacterial arthritis. Am J Emerg Med. 1997;15(7):626\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKratz A, Maloum K, O\u0026rsquo;Malley C, et al. Enumeration of nucleated red blood cells with the ADVIA 2120 Hematology System: an International Multicenter Clinical Trial. Lab Hematol. 2006;12(2):63\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMargaretten ME, Kohlwes J, Moore D, Bent S. Does this adult patient have septic arthritis? JAMA. 2007;297(13):1478\u0026ndash;88.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMoon S, Park Y, Hong CW et al. A usefulness of Delta Neutrophil Index (DNI) for prediction of 28-day mortality in patients with pneumonia-induced sepsis in the intensive care unit. J Clin Med 2025;14(6).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNahm CH, Choi JW, Lee J. Delta neutrophil index in automated immature granulocyte counts for assessing disease severity of patients with sepsis. Ann Clin Lab Sci. 2008;38(3):241\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNam M, Son BH, Seo JE, Kim IR, Park CK, Kim HK. Improved diagnostic and prognostic power of combined Delta Neutrophil Index and Mean Platelet Volume in pediatric sepsis. Ann Clin Lab Sci. 2018;48(2):223\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePark BH, Kang YA, Park MS, et al. Delta neutrophil index as an early marker of disease severity in critically ill patients with sepsis. BMC Infect Dis. 2011;11:299. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/1471-2334-11-299\u003c/span\u003e\u003cspan address=\"10.1186/1471-2334-11-299\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Published 2011 Nov 1.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePyo JY, Park JS, Park YB, Lee SK, Ha YJ, Lee SW. Delta neutrophil index as a marker for differential diagnosis between flare and infection in febrile systemic lupus erythematosus patients. Lupus. 2013;22(11):1102\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePyo JY, Kim DS, Jung SM, Song JJ, Park YB, Lee SW. Clinical significance of delta neutrophil index in the differential diagnosis between septic arthritis and acute gout attack within 24 hours after hospitalization. Med (Baltim). 2017;96(30):e7431.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSeok Y, Choi JR, Kim J, Kim YK, Lee J, Song J, et al. Delta neutrophil index: a promising diagnostic and prognostic marker for sepsis. Shock. 2012;37(3):242\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShin JE, Deok Seo K, Cha HJ, et al. Usefulness of the delta neutrophil index in predicting surgery in patients with foot and ankle infection. PLoS ONE. 2022;17(8):e0272574.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShmerling RH, Delbanco TL, Tosteson AN, Trentham DE. Synovial fluid tests. What should be ordered? JAMA. 1990;264(8):1009\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVisser S, Tupper J. Septic until proven otherwise: approach to and treatment of the septic joint in adult patients. Can Fam Physician. 2009;55(4):374\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWest K, Almekdash H, Fisher J, Rounds AD, Murphree J, Simpson J. Procalcitonin as a Predictor of Septic Knee Arthritis: A Retrospective Cohort Study. J Am Acad Orthop Surg Glob Res Rev. 2023;7(1):e2200261.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhao J, Zhang S, Zhang L, Dong X, Li J, Wang Y, Yao Y. Serum procalcitonin levels as a diagnostic marker for septic arthritis: a meta-analysis. Am J Emerg Med. 2017;35(8):1166\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1:\u003c/strong\u003e Demographics of the patients\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"576\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eValue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (mean \u0026plusmn; SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e56.3 \u0026plusmn; 24.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex:\u0026nbsp;\u003c/strong\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e36 (60.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex:\u0026nbsp;\u003c/strong\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e24 (40.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSide:\u0026nbsp;\u003c/strong\u003eRight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e36 (51.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSide:\u0026nbsp;\u003c/strong\u003eLeft\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e35 (48.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCulture:\u0026nbsp;\u003c/strong\u003eNegative\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eInfected\u003c/strong\u003e:\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eUninfected\u003c/strong\u003e:\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e42 (59.2%)\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003e20 (%47,6)\u003c/li\u003e\n \u003cli\u003e22 (%52,4)\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCulture:\u0026nbsp;\u003c/strong\u003ePositive\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003e\u003cstrong\u003ePathogen\u003c/strong\u003e: \u003cem\u003eS. Aureus\u003c/em\u003e\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003ePathogen\u003c/strong\u003e: \u003cem\u003eS. Epidermidis\u003c/em\u003e\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003ePathogen\u003c/strong\u003e: S\u003cem\u003e. Dysgalactia\u003c/em\u003e\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003ePathogen\u003c/strong\u003e: \u003cem\u003eE. Coli\u003c/em\u003e\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e29 (40.8%)\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003e15 (51.7%)\u003c/li\u003e\n \u003cli\u003e3 (10.3%)\u003c/li\u003e\n \u003cli\u003e1(3.4%)\u003c/li\u003e\n \u003cli\u003e6 (20.6%)\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFluid type:\u0026nbsp;\u003c/strong\u003ePurulent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e51 (71.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFluid type:\u0026nbsp;\u003c/strong\u003eSerous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e20 (28.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eJoint:\u0026nbsp;\u003c/strong\u003eKnee\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e57 (80.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eJoint:\u0026nbsp;\u003c/strong\u003eElbow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e4 (5.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eJoint:\u0026nbsp;\u003c/strong\u003eShoulder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e3 (4.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eJoint:\u0026nbsp;\u003c/strong\u003eHip\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e3 (4.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eJoint:\u0026nbsp;\u003c/strong\u003eWrist\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e1 (1.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eJoint:\u0026nbsp;\u003c/strong\u003eAnkle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 288px;\"\u003e\n \u003cp\u003e3 (4.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u003c/strong\u003e Comparative Demographics of the Synovial Leukocyte Count \u0026amp; Culture Results\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"387\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003eLeukocyte Count\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003eCulture: Negative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eCulture: Positive\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e\u0026lt; 20 000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e20 000-50 000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 137px;\"\u003e\n \u003cp\u003e\u0026gt; 50 000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ePearson \u0026chi;\u0026sup2; = 5.28, df = 2, p = 0.072.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3:\u0026nbsp;\u003c/strong\u003eROC Performance of Biomarkers in Distinguishing Clinical Infection In Culture Negative Patients\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBiomarker\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAUC (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOptimal cut‑off\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSensitivity (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpesivity (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003eDNI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e0.75 (0.60\u0026ndash;0.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026ge; 0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e0.53 (0.30\u0026ndash;0.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e0.86 (0.71\u0026ndash;1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003eCRP (mg/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e0.64 (0.47\u0026ndash;0.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026ge; 124.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e0.53 (0.29\u0026ndash;0.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e0.82 (0.65\u0026ndash;0.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003eESR (mm/h)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e0.44 (0.37\u0026ndash;0.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026ge; 99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e0.11 (0.00\u0026ndash;0.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e0.95 (0.71\u0026ndash;1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003eWBC (\u0026times;10⁹/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e0.55 (0.37\u0026ndash;0.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026ge; 9.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e0.84 (0.65\u0026ndash;1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e0.41 (0.20\u0026ndash;0.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003ePCT (ng/mL)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e0.51 (0.21\u0026ndash;0.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 121px;\"\u003e\n \u003cp\u003e\u0026ge; 0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e0.25 (0.00\u0026ndash;0.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 149px;\"\u003e\n \u003cp\u003e0.88 (0.60\u0026ndash;1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4:\u003c/strong\u003e Comparison of AUCs in Culture Negative Patients\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eComparison\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026Delta;AUC\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ep (bootstrap)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDNI vs ESR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e+0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.11 \u0026ndash; 0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDNI vs WBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e+0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.00 \u0026ndash; 0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDNI vs CRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e+0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026minus;0.06 \u0026ndash; 0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5:\u003c/strong\u003e ROC Summary and Optimal Cut-Off\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"673\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBiomarker\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAUC (95 % CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCut-off\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSensitivity (95 %CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpecificity (95 % CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003eDNI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e0.920\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e0.931\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e0.857\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003eCRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e0.685\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e114.9 mg L⁻\u0026sup1;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e0.724\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e0.619\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003eESR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e0.631\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e74 mm h⁻\u0026sup1;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e0.414\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e0.857\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003eWBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e0.580\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e10.35 \u0026times; 10⁹ L⁻\u0026sup1;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e0.793\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e0.429\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 106px;\"\u003e\n \u003cp\u003ePCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e0.671\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 117px;\"\u003e\n \u003cp\u003e0.51 ng mL⁻\u0026sup1;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e0.529\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e0.875\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6:\u003c/strong\u003e Pairwise AUC comparisons (bootstrap)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"576\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComparison\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026Delta;AUC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP Value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003eDNI vs CRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e+0.236\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003eDNI vs ESR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e+0.289\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003eDNI vs WBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e+0.341\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003eDNI vs PCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e+0.179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e0.128\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003eCRP vs ESR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e+0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e0.488\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003eCRP vs WBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e+0.105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e0.183\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003eCRP vs PCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u0026ndash;0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e0.543\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003eESR vs WBC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e+0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e0.602\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003eESR vs PCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u0026ndash;0.185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e0.097\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003eWBC vs PCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u0026ndash;0.150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e0.243\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"Septic arthritis, delta neutrophil index, diagnostic accuracy, ROC analysis","lastPublishedDoi":"10.21203/rs.3.rs-7227655/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7227655/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground:\u003c/h2\u003e\u003cp\u003eSeptic arthritis is an orthopedic emergency requiring prompt diagnosis and treatment to prevent joint destruction and systemic complications. Standard inflammatory markers such as CRP, ESR, and WBC lack specificity, often leading to diagnostic uncertainty, especially in differentiating septic arthritis from inflammatory arthropathies. The Delta Neutrophil Index (DNI), reflecting immature granulocyte levels, may offer improved diagnostic performance.\u003c/p\u003e\u003ch2\u003eQuestions/purposes:\u003c/h2\u003e\u003cp\u003eWe aimed to evaluate (1) Does serum DNI provide superior diagnostic accuracy compared with CRP, ESR, and WBC for culture-positive septic arthritis? (2) What sensitivity and specificity are achieved at an optimal DNI threshold?\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e\u003cp\u003eIn this singlecentre retrospective diagnostic cohort study, 71 patients who underwent surgery for suspected septic arthritis between November 2022 and March 2025 were enrolled. Preoperative serum biomarkers were obtained; synovial aspirate appearance and intraoperative cultures served as the reference standard. PCT measured in 33/71 patients. Diagnostic performance was assessed with ROC analysis; AUCs were compared with the bootstrapadapted DeLong test, and multivariable logistic regression adjusted for age, sex, and affected joint.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e\u003cp\u003eDNI values were significantly higher in culture-positive patients (p\u0026thinsp;=\u0026thinsp;0.0002). While CRP and ESR showed moderate diagnostic value, DNI exhibited the strongest correlation with positive cultures and purulent synovial fluid. The ROC AUC for DNI was significantly higher than those of CRP, ESR and WBC (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), suggesting better diagnostic performance. A DNI cut-off value of 0.6 yielded the highest sensitivity and specificity among all markers. Importantly, DNI values did not increase significantly in patients with inflammatory arthritis flares, unlike CRP.\u003c/p\u003e\u003ch2\u003eConclusions:\u003c/h2\u003e\u003cp\u003eThe Delta Neutrophil Index is a rapid, cost-effective, and more specific biomarker than conventional inflammatory parameters for diagnosing septic arthritis. Its use may help differentiate septic arthritis from inflammatory arthropathies and reduce unnecessary surgical interventions.\u003c/p\u003e\u003ch2\u003eLevel of Evidence:\u003c/h2\u003e\u003cp\u003eLevel III, retrospective diagnostic study.\u003c/p\u003e","manuscriptTitle":"Delta Neutrophil Index in Suspected Septic Arthritis: A Diagnostic Accuracy Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-06 08:20:42","doi":"10.21203/rs.3.rs-7227655/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":"9f2d37d2-af1b-4b5a-ad78-63121feb21ae","owner":[],"postedDate":"August 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-21T09:38:11+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-06 08:20:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7227655","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7227655","identity":"rs-7227655","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}