The crossroads of the hypercoagulability and patient outcomes in osteoarthritis: interactions and connections

The crossroads of the hypercoagulability and patient outcomes in osteoarthritis: interactions and connections | 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 The crossroads of the hypercoagulability and patient outcomes in osteoarthritis: interactions and connections Qiao zhou, jian liu, Yan Zhu, Guizhen Wang, Jinchen Guo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4718192/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract Background Our study aimed to probe whether coagulation indices are linked to patient-reported outcomes (PROs) in OA. Methods A thorough review of the literature on OA and coagulation indices was conducted using bibliometric approaches. Clinical data were retrospectively analyzed in OA patients (7,068) and healthy controls (HC, 795). Coagulation indices—prothrombin time (PT), fibrinogen (FIB), activated partial thromboplastin time (APTT), thrombin time (TT), D-dimer, and platelet count (PLT)—as well as immune-inflammatory indices, PROs (visual analogue scale and Short Form 36), were analyzed for correlations. Results Co-cited literature revealed that research related to OA and coagulation indices focused on inflammation, pain, and clinical utility. The levels of PLT, TT, FIB, and D-dimer were elevated in the OA group compared to the HC group. Hypercoagulable states are present in the OA. The results of the ROC demonstrate that they can differentiate between OA and healthy individuals. Coagulation indices were strongly linked to immune-inflammatory indicators and PROs. Logistic regression analysis indicated that PLT, D-dimer, and C-reactive protein (CRP) were all predictive of disease activity. However, PLT and D-dimer combined with CRP had a superior predictive effect than CRP alone. Conclusion PLT and D-dimer may serve as appropriate biomarkers to correlate with OA disease activity. osteoarthritis coagulation index inflammation patient-reported outcomes data mining Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction Osteoarthritis (OA) is a bone disease characterised by disturbances to cartilage, meniscus, synovium, ligaments, and subchondral bone 1 . Arthralgia, joint malformations, and soft tissue haemorrhage are the symptoms of osteoarthritis. Low-grade systemic inflammation impairs joint tissue homeostasis and exacerbates the deterioration of OA 2 . Clot hypercoagulability is another characteristic of systemic inflammation, and OA also exhibits this characteristic together with a diminished capacity to lyse clots, potentially as a result of actual amyloid production 3 . Localised circulatory disorders in the joints affect the physiochemical microenvironment of the subchondral bone. Frequent localised joint injuries cause osteomalacia, or even erosion of the underlying bone, resulting in the joints becoming more painful, swollen, and stiff 4–5 . Therefore, it is crucial to study the progression of OA from the perspective of inflammatory and hypercoagulable states. The significance of innate immunity is related to the emergence of synovitis, downstream inflammatory activation, and articular cartilage catabolic processes, which contribute to the evolution of OA 6 . Long-term chronic inflammation, cytokine imbalance, and immune disorders in the body contribute to damage to the vascular endothelium, which directly or indirectly activates the coagulation-fibrinolytic system and interferes with anticoagulation, thereby causing microcirculatory disturbances, leading to systemic circulatory abnormalities in patients with OA with hypercoagulability and prothrombotic state 7 . The immune system and the coagulation system work together to positively modify the immunological response. Coagulation factors such as thrombin stimulate immune cells and increase the synthesis of cytokines that promote inflammation 8 . The primary element of blood clotting, fibrin, serves as a scaffold for immune cells and encourages their recruitment and activation at the site of infection or injury. Additionally crucial to OA are platelets, which are involved in vascular integrity, hemostasis, and inflammatory processes 9 . Pro-inflammatory and anti-inflammatory factors—interleukin (IL)-6, IL-1β, tumour necrosis factor (TNF)-α, IL-10, and IL-4—are associated with the development of angiogenesis and chemotaxis in OA. The majority are created, activated, adhered to, or expelled by platelets 10 . Patient-reported outcomes (PROs) are information derived directly from patients' reports of their own health status, functional status, and perceptions of treatment 11 . The Visual Analog Scale (VAS) is widely employed to assess a variety of health-related issues, including pain, mood, and quality of life, and has been recognized as providing robust and valid data 12 . An additional indicator of medical-related quality of life is the MOS item short from the health survey (SF-36) 13 . Bibliometrics is an instrument for applying mathematical and statistical methods to rapidly grasp the hottest research topics and trends in a particular field 14 . This research was conducted to understand the current trends in research related to coagulation and hypercoagulation in patients with OA through bibliometrics. We explore outbreaks of keywords related to coagulation in OA and visualise, evaluate, and predict research status, hotspots, and future trends. Furthermore, we investigated the involvement of coagulation indices—prothrombin time (PT), fibrinogen (FIB), activated partial thromboplastin time (APTT), thrombin time (TT), D-dimer, and platelet count (PLT) in the pathophysiology of OA. The purpose of our research was to verify whether coagulation indices are related to immune-inflammation and whether they correlate with patient-reported outcomes and disease activity status (as defined by VAS). 2. Materials and Methods 2.1 Data 2.1.1 Literature sources The Web of Science (WOS) Core Collection database is an excellent source of science statistics and evaluation 15 . The search terms were as follows: TS = (Osteoarthritides OR Osteoarthrosis OR Osteoarthroses OR (Osteoarthrosis Deformans) OR Osteoarthritis) AND TS = (hypercoagulable state OR hypercoagulability OR platelet OR blood platelet OR soterocyte OR fibrinogen OR D-dimer). Only English-language articles were chosen among numerous forms of publication. Each investigator independently reviewed all the articles to ensure their relevance. All articles' entire records were searched up to December 20, 2023. In total, 1368 articles were analyzed. Table 1 illustrates the results of the complete screening. Table 1 TS search quires and refinement procedure. Set Results Refinement 1 2,184 TS= (Osteoarthritides OR Osteoarthrosis OR Osteoarthroses OR (Osteoarthrosis Deformans) OR osteoarthritis) AND TS= (hypercoagulable state OR hypercoagulability OR platelet OR blood platelet OR soterocyte OR Fibrinogen OR D-dimer) Indexes = SCI-EXPANDED 2 2,152 Refined by LANGUAGES: (English) 3 1,368 Refined by DOCUMENT TYPES: (Articles) 2.1.2 Sources of clinical data This research is an observational, retrospective, single-center study. We enrolled OA patients who were hospitalized between March 2009 and February 2023 at the First Affiliated Hospital of Anhui University of Traditional Chinese Medicine. General information about the patients was retrieved from the hospital case information management system, including basic information such as body mass index (BMI), gender, comorbidities, and length of hospital stay (LOS). Exclusion criteria include: incomplete data; comorbid infections; severe circulatory, respiratory, and hematopoietic diseases; and other autoimmune diseases. The Charlson Comorbidity Index (CCI) 16 is a quantification of patient comorbidities for the purpose of predicting the risk of death from disease. A total of 7,068 osteoarthritis patients took part in the study. On the other side, 795 healthy control group volunteers (HC) were chosen from those who had regular medical checkups at the hospital's medical checkup center. It was not necessary to get informed consent for this retrospective observational investigation. Subjects' personal information was hidden before any analysis. This study was approved by the Ethics Research Committee of the First Affiliated Hospital of Anhui University of Traditional Chinese Medicine (2023AH-52). 2.2 Methodology 2.2.1 Bibliometric Visualization Analysis CiteSpace version 6.2.6 was implemented for the bibliometric analysis study, which examined essential pathways and knowledge inflection points in the advancement of topic areas 17 . In our study, CiteSpace software was adopted to perform visualisation analysis, network analysis, cluster analysis, timeline analysis, and outbreak word detection for reference analysis and keywords. The specific parameters used are as follows: set the time range as January 2007–December 2023; set the time slice as 1, node type to select references and keywords, respectively; and choose the top 50 keywords with the highest frequency of occurrence in each time slice by setting Top N to 50. Paths under and under the pruned slice network in the pruned model are chosen by pruning, and the remaining parameters are default values. 2.2.2 Collection of coagulation indexes and immuno-inflammatory indexes ( 1 ) Coagulation indexes: prothrombin time (PT), activated partial thromboplastin time (APTT), fibrinogen (FIB), thrombin time (TT), platelet count (PLT) and D-dimer. ( 2 ) Immunologic indexes: immunoglobulin (IG) A, G, M, complement 3 (C3), complement 4 (C4). ( 3 ) Inflammation indicators: C-reactive protein (CRP), and erythrocyte sedimentation rate (ESR). 2.2.3 Patient-reported outcomes (PROs) One of the most prevalent unidimensional methods for measuring pain intensity is the VAS, which is extensively utilised in rheumatic diseases 18 . The scale is a 10-cm straight line, where "no pain at all" is indicated at one end and "pain to the extreme" at the other. Eight health-related quality of life questionnaires make up the SF-36 scale: physical function (PF), bodily pain (BP), role-physical (RP), vitality (VT), social function (SF), general health (GH), role-emotional (RE), and mental health (MH) 19 . 2.2.4 Association Rules Apriori is the most impactful algorithm for mining the frequent item sets of Boolean association rules. An association rule is an implication of the form X Y, where X and Y are called the prior (antecedent or left-hand-side, LHS) and the successor (consequent or right-hand-side, RHS) of the association rule, respectively. N denotes the total number of items in the sample, and X and Y represent an item set, respectively. The corresponding equations for support, confidence, and elevation are as follows: 2.2.5 Statistical analysis For data processing, the SPSS 22.0 and R software were adopted. The Kolmogorov-Smirnov with Levene test was applied to test the data for normality and chi-square. Measures with a normal distribution were reported as mean and standard deviation, while measures with a non-normal distribution were displayed as median (P25, P75), and count data were displayed as n/%. To determine statistical significance, the Mann-Whitney test, Wilcoxon signed rank test, t-test, or chi-square test (as appropriate) were utilized to determine statistical significance. Correlations between coagulation indices and other indices were analyzed by Spearman or Pearson analysis (as appropriate). To compare the diagnostic efficacy of coagulation indicators in OA, the receiver operator characteristic curve (ROC) of the subjects was displayed, and the area under the curve (AUC) was computed. Jorden's test was applied to determine the optimal critical value. Logistic regression models were constructed to assess the relationship between coagulation indices and immune-inflammatory indicators, as well as patient reports. In the multivariate logistic regression analysis, variables that were deemed significant in the univariate analysis were incorporated and modelled using stepwise regression. The absolute values of the t-statistic for each model parameter was determined to compare the relative weight of each predictor in the logistic regression model. McFadden's R 2 and Hosmer-Lemeshow goodness-of-fit tests were utilized to evaluate the logistic regression model. McFadden's R 2 values between 0.2 and 0.4 were deemed to indicate a good fit of the model 20 . The Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) were applied to evaluate the quality of fit and complexity of various models and to select the best-balanced model 21 . 3. Results 3.1 Trends in the issuance of papers A total of 1,368 literary collections were included. The number of publications and citations in a particular period can objectively and quantitatively reflect general trends in a region. Annual number of publications issued and citations related to OA and coagulation metrics are depicted in Fig. 1 A. The first peak was reached in 2020 with a total of 182 publications. Overall, there is a steady upward trend in annual publications in this area. In Fig. 1 B, a fitted curve showing the overall annual growth trend is presented. Based on the time curve, the global cumulative number of publications in the field is expected to continue to rise over the next 10 years (R 2 = 0.922) (Fig. 1 B). Furthermore, the citations of these publications showed an increasing trend year by year (Fig. 1 A), with a total of 16,970 citations (15,873 after the self-citation), an average of 24.42 citations, and an overall h-index of 82. These data demonstrate the overall fluctuating upward trend of OA coagulation index-related studies during the last 16 years. 3.2 Analysis of the co-cited literature The topics strongly related to the field of OA-coagulation index were highlighted by evaluating the co-citation network of 1,368 documents. A total of 244 documents (with at least 20 citations) were chosen to map the co-citation analysis network. Cluster analysis categorizes closely related topics to obtain hotspots in this research area. It forms clusters of varying strength based on the co-occurrence links of terms, with significant homophily among terms. Literature clusters were classified using different node colors (Fig. 2 A). The top 11 hot topics were presented for clustering. The main research hot topics were osteoarthritis, platelet-rich plasma, intra-articular injection, clinical outcomes, growth factors, clinical efficacy, real-world evidence, pain, systematic reviews, platelet amplification, inflammation in arthritis, and efficacy. Most of the studies focused on OA inflammatory mediators, patient-reported outcome indicators, and blood derivatives. The articles with a higher citation frequency can be regarded as more influential in a particular field. Figure 2 B presents the details of the top 20 articles, with the blue line indicating the time periods and the red line indicating the strong citation frequency. The research by Kon, E. et al. 22 (26.9) gained the most citations over a 7-year period and had the strongest citation burst value. This research was published in 2,009 under the title "Platelet-rich plasma: intra-articular knee injections produced favorable results on degenerative cartilage plasma: intra-articular knee injections produced favorable results on degenerative cartilage lesions. Natural concentrates of autologous growth factors in the blood may stimulate cartilage anabolism and reduce catabolic processes. Platelet-rich plasma (PRP) influences whole joint homeostasis, decreases synovial hyperplasia, and ultimately boosts knee function, discomfort, and quality of life in OA patients. The citation outbreak published in “The American Journal of Sports Medicine” by van Buul GM et al. took the longest time 23 . This research demonstrates that platelet-rich plasma release reduces the inflammatory effects of IL-1β on human osteoarthritic chondrocytes, including suppression of NF-B activation. This study demonstrates that platelet-rich plasma release attenuates multiple inflammatory effects mediated by IL-1β on human osteoarthritic chondrocytes, including inhibition of NF-κB activation. Notably, an explosion of articles in recent years, such as Dai X et al. 24 and Cheng Y et al. 25 , emphasized blood hypercoagulation as a susceptibility factor for deep vein thrombosis and as a cause of osteoarthritis total knee arthroplasty. According to Liu N et al. 26 , blood rheology alterations and hypercoagulability contributed to the development of petechiae following total knee arthroplasty. 3.3 Analysis of co-cited keywords Keywords are a high degree of summarization and condensation of the article's theme, as high-frequency keywords in different periods reflect the transformation of research hotspots in the field. A total of 458 keywords were identified, and those related to osteoarthritis-coagulation index were displayed in the network diagram (Fig. 3 A). The top 10 high-frequency keywords included osteoarthritis, pain, risk factors, clinical trials, growth factors, platelet-rich plasma (PRP), prevalence, randomized controlled trials, growth factor beta, and chondrogenic differentiation. The term "emergent words" refers to keywords that have been widely cited over a period of time. Among them, the longest burst time is "inflammation" (2011–2018), and the strongest burst intensity is "pain" (16.55) (Fig. 3 B). Meanwhile, we noticed that regenerative medicine, venous thromboembolism, and M 2 macrophage polarization were the most prevalent keywords in the last 3 years (Fig. 3 B). On the basis of the keyword co-occurrence network, further keyword clustering analysis was generated (Fig. 3 C). The results were co-clustered into 10 major categories, including inflammatory processes, osteoarthritis, injured articular cartilage, clinical utility, induced apoptosis, M 2 macrophage polarization, mesenchymal stem cell therapy, pain, controlled trial, and coagulation. 3.4 Results of coagulation index analysis Age, gender, and BMI did not significantly differ between OA patients and healthy controls. Compared with the healthy group, PLT, TT, FIB, and D-D indicators were elevated in OA patients. Immuno-inflammatory markers (such as ferritin, IGA, IGG, CRP, and ESR) were significantly elevated in OA patients than in the HC group (Table 2 ). Table 2 Baseline characteristics, coagulation indices, immunoinflammatory markers and PROs. Variables OA(n = 7,068) HC(n = 795) p -value Baseline characteristics Age(year) 61.48 ± 11.97 59.792 ± 8.74 0.132 Male (%) 1,887(26.70) 224(28.18) 0.231 BMI (kg/m 2 ) 24.66 ± 2.07 24.52 ± 2.03 0.321 LOS (years) 13.00(9.84,16.79) NA / CCI 1.15 ± 1.01 NA / Coagulation indicator PLT (×10^9/L) 382(285,513) 108(89,118) < 0.001 PT (s) 9.81(9.00,11.9) 11.30(11.90,12.90) 0.096 APTT (s) 22.60(20.30,30.41) 27.71(26.21,30.31) 0.064 TT (s) 22.9(16.2,28.6) 16.1(15.1,17.7) 0.045 FIB (g/L) 4.32(3.36,4.96) 2.32(1.09,2.79) 0.031 D-dimer (mg/L) 0.9(0.42,2.61) 0.19(0.11,0.26) < 0.001 Immune-inflammatory markers CRP (mg/L) 11.64(7.78,16.59) 0.09(0.05,0.13) < 0.001 ESR (mm/h) 57(40,64) 5( 1 , 9 ) < 0.001 C3(g/L)) 1.09(1.01,1.51) 0.86(0.78,0.90) 0.245 C4(g/L) 0.26(0.23,0.41) 0.17(0.14,0.22) 0.321 IGA(g/L) 1.22(1.21,2.57) 0.93(0.79,1.04) 0.032 IGG(g/L) 10.43(9.13,15.28) 6.72(5.10,7.11) 0.012 IGM(g/L) 0.56(1.79,1.07) 0.39(0.31,0.44) 0.056 Ferritin (pg/mL) 179.20(141.08,231.81) 54.2(8.96,71.24) < 0.001 PROs VAS (cm) 6.0(5.5,7.5) / / PF (score) 30( 10 , 40 ) / / RP (score) 15( 10 , 35 ) / / BP (score) 28( 21 , 42 ) / / GH (score) 30( 20 , 40 ) VT (score) 35( 25 , 42 ) / / SF (score) 37.5(25,50) / / RE (score) 15(12,33.33) / / MH (score) 48(38,52) / / Note: BMI: body mass index; LOS: length of hospital stay; CCI: charlson comorbidity index; PLT: platelet count; PT: prothrombin time; APTT: activated partial thromboplastin time; TT: thrombin time; FIB: fibrinogen; CRP: C-reactive protein; ESR: erythrocyte sedimentation rate; C3: complement component 3; C4: complement component 4; IG: immunoglobulin; VAS: visual analog scale; PF: physical function; RP: role-physical; BP: bodily pain; GH: general health; VT: vitality; SF: social function; RE: role-emotional; MH: mental health. 3.5 ROC curve of coagulation indices ROC curve analysis suggested (Fig. 4 ) that PLT, TT, FIB, and D-dimer had excellent specificity in differentiating between OA patients and healthy individuals. The best cut-off values of 350 and 0.55 for PLT and D-dimer had the highest sensitivity and specificity among these indices, with AUC (95% CI) of 0.968 (0.907–0.994) and 0.918 (0.841–0.965), respectively. The cut-off values were 20.8 for TT and 4.00 for FIB. 3.6 Correlation analysis between coagulation indices and immuno-inflammatory indexes, PROs The consequences of the correlation analysis showed that PLT, TT, FIB and D-dimer were positively correlated with the immuno-inflammatory index and negatively correlated with the PROs; ​PT, and APTT are the reverse. The findings exhibited a strong correlation between the immune-inflammatory indices, PROs, and the coagulation indexes of OA patients (Table 3 , Fig. 5 ). Table 3 Correlation analysis. Variables PLT PT APTT TT FIB D-dimer r p r p r p r p r p r p Baseline characteristics Age 0.011 0.564 -0.012 0.542 -0.013 0.519 0.032 0.102 0.012 0.552 0.011 0.568 LOS 0.014 0.988 -0.011 0.561 -0.011 0.608 0.026 0.176 0.002 0.990 -0.002 0.923 BMI 0.011 0.572 -0.163 0.001 -0.662 0.001 0.012 0.541 0.011 0.563 0.006 0.752 Immune-inflammatory markers CRP 0.423 < 0.001 0.008 0.694 0.005 0.779 0.543 < 0.001 0.423 < 0.001 0.431 < 0.001 ESR 0.827 < 0.001 -0.795 < 0.001 -0.796 < 0.001 0.151 < 0.001 0.128 < 0.001 0.621 < 0.001 C3 0.334 < 0.001 -0.129 < 0.001 -0.129 < 0.001 0.326 < 0.001 0.267 < 0.001 0.343 < 0.001 C4 0.346 < 0.001 -0.134 < 0.001 -0.131 < 0.001 0.326 < 0.001 0.267 < 0.001 0.343 < 0.001 IGA 0.129 < 0.001 -0.939 < 0.001 -1.001 < 0.001 0.158 < 0.001 0.133 < 0.001 0.132 < 0.001 IGG 0.129 < 0.001 -0.913 < 0.001 -1.003 < 0.001 0.158 < 0.001 0.133 < 0.001 0.132 < 0.001 IGM 0.129 < 0.001 -0.923 < 0.001 -1.003 < 0.001 0.158 < 0.001 0.133 < 0.001 0.132 < 0.001 Ferritin 0.029 0.301 -0.156 < 0.001 -0.155 < 0.001 0.021 0.307 0.019 0.319 0.013 0.515 PROs VAS 0.134 < 0.001 -0.931 < 0.001 -0.930 < 0.001 0.142 < 0.001 0.135 < 0.001 0.119 < 0.001 PF -0.189 < 0.001 0.562 < 0.001 0.562 < 0.001 -0.180 < 0.001 -0.110 < 0.001 -0.183 < 0.001 RP -0.163 < 0.001 0.824 < 0.001 0.827 < 0.001 -0.185 < 0.001 -0.111 < 0.001 -0.188 < 0.001 BP -0.134 < 0.001 0.468 < 0.001 0.469 < 0.001 -0.163 0.001 -0.165 0.001 -0.161 0.002 GH -0.133 < 0.001 0.686 < 0.001 0.685 < 0.001 -0.190 < 0.001 -0.134 < 0.001 -0.189 < 0.001 VT -0.184 < 0.001 0.474 < 0.001 0.472 < 0.001 -0.174 < 0.001 -0.164 < 0.001 -0.173 < 0.001 SF -0.175 < 0.001 0.374 < 0.001 0.375 < 0.001 -0.169 < 0.001 -0.175 < 0.001 -0.167 0.001 RE -0.188 < 0.001 0.527 < 0.001 0.529 < 0.001 -0.154 0.005 -0.188 < 0.001 -0.176 < 0.001 MH -0.014 0.618 -0.115 < 0.001 -0.116 < 0.001 -0.021 0.272 -0.01 0.622 -0.009 0.647 Note: LOS: length of hospital stay; BMI: body mass index; PLT: platelet count; PT: prothrombin time; APTT: activated partial thromboplastin time; TT: thrombin time; FIB: fibrinogen; CRP: C-reactive protein; ESR: erythrocyte sedimentation rate; C3: complement component 3; C4: complement component 4; IG: immunoglobulin; VAS: visual analog scale; PF: physical function; RP: role-physical; BP: bodily pain; GH: general health; VT: vitality; SF: social function; RE: role-emotional; MH: mental health. 3.7 Association rule analysis We evaluated the association between the coagulation index and the immuno-inflammation index using the optimal cut-off value established by the ROC curve, where the minimum support was set at 70% and the minimum confidence interval was used at 50%. The pre- and post-items with the highest confidence level were chosen for each item. The results revealed that PLT, FIB, D-dimer, and APTT had a higher association with CRP. The PT and TT had a higher correlation with ESR. The lift was greater than 1 (Table 4 , Fig. 6 ). Table 4 Correlation analysis between coagulation and immunoinflammatory markers. Items (LHS ⇒ RHS) Support (%) Confidence (%) Lift PLT⇒ CRP 45.814 88.572 1.083 FIB⇒ CRP 44.539 86.875 1.005 D-dimer⇒ CRP 45.422 81.229 1.001 TT⇒ESR 29.686 82.684 1.003 APTT⇒CRP 23.341 70.748 1.024 PT⇒ ESR 25.814 70.274 1.019 Note: PLT: platelet count; PT: prothrombin time; APTT: activated partial thromboplastin time; TT: thrombin time; FIB: fibrinogen; CRP: C-reactive protein; ESR: erythrocyte sedimentation rate. 3.8 Univariate and multivariate regression analysis The optimal cutoff values for PLT, FBG, PT, APTT, D-dimer, and TT were determined from the ROC curves, and the critical values for the other variables were determined from the median values. Logistic regression models were performed to describe the associations of PLT, FIB, PT, APTT, D-dimer, and TT with immunoinflammatory indexes and PROs (using VAS ≥ 6 as a criterion for subgrouping). In univariate regression analysis, PLT (OR = 1.275, p < 0.001), FIB (OR = 1.667, p = 0.024), and D-dimer (OR = 2.346, p < 0.001) were independent risk factors for disease activity in OA. The ESR (OR = 2.326, p < 0.001) and CRP (OR = 2.312, p < 0.001) were markedly correlated with OA disease activity (Table 5 ). Stronger correlations were observed in the multivariate logistic regression analysis, which controlled for sex, age, duration of illness, and BMI. The PLT (OR = 1.874, p = 0.015), D-dimer (OR = 1.534, p = 0.003) and CRP (OR = 1.456, p = 0.021) remained independent predictors of OA disease activity. In the multivariate model, TT (OR = 1.115, p = 0.078), FIB (OR = 1.431, p = 0.081), and ESR (OR = 2.105, p = 0.088) were not able to serve as independent predictors of disease activity (Table 6 ). The PLT, D-dimer and CRP were included as variables of interest in the multivariate simplified model. To determine whether PLT and D-dimer were linked to disease activity when CRP was being considered, we tested PLT and D-dimer while correcting for CRP. When CRP was considered, PLT (+ CRP) (OR = 2.423, p = 0.001) and D-dimer (+ CRP) (OR = 2.987, p = 0.003) remained significant predictors of disease activity, in addition to the afore-mentioned control variables. AIC and BIC indicate that models containing PLT, D-dimer, and CRP outperform models containing CRP only. All independent risk factors screened by regression analysis were integrated to construct a nomogram (Fig. 7 C). Each variable was assigned a score on the rating scale. The overall score was calculated by adding the scores of all variables (Fig. 7 C). C-index values were applied to assess the discriminatory nature of the nomogram for survival prediction in the model (Fig. 7 A). The internal validation cohort proved to have good discriminatory performance. The Hosmer-Lemeshow test findings proved that the calibration curves in the dataset once again performed well ( p = 0.325) (Fig. 7 A). In addition, DCA demonstrated that patients could obtain a satisfactory net benefit from the predictive model. A wide range of high-risk thresholds were observed in DCA (Fig. 7 B). In conclusion, the evaluation of the nomogram based on column-line graphs revealed considerable discriminatory and calibrating power of our research model. Table 5 Univariate logistic regression analysis Note BMI: body mass index; LOS: length of hospital stay; PLT: platelet count; PT: prothrombin time; APTT: activated partial thromboplastin time; TT: thrombin time; FIB: fibrinogen; CRP: C-reactive protein; ESR: erythrocyte sedimentation rate; C3: complement component 3; C4: complement component 4; IG: immunoglobulin. Table 6 Multi-factor logistic regression analysis (as defined by VAS ≥ 6) Laboratory variable (critical value) Odds ratio (95% CI) t-stat p- value AIC BIC PLT (350) 1.874(1.056–4.134) 21.567 0.015 482.46 356.73 TT (20.8) 1.115(0.875–3.311) 9.785 0.078 Not performed Not performed FIB (4.00) 1.431(0.761–2.145) 6.643 0.081 Not performed Not performed D-dimer (0.55) 1.534(1.221–3.667) 22.135 0.003 456.75 342.76 ESR (57) 2.105(1.013–3.245) 8.621 0.088 Not performed Not performed CRP (11.64) 1.456(1.005–3.245) 20.754 0.021 355.78 267.75 PLT (+ CRP) 2.423(1.116–4.067) 30.234 0.001 211.345 135.643 D-dimer (+ CRP) 2.987(1.004–4.157) 26.567 0.003 222.451 115.689 Note: PLT: platelet count; TT: thrombin time; FIB: fibrinogen; CRP: C-reactive protein; ESR: erythrocyte sedimentation rate. 4. Discussion Bibliometrics, through the adoption of mathematical and statistical techniques, aims to explore the distribution pattern, quantitative relationship and changing law of literature information, which can guide not only research design but also clinical practice 27 . We included a total of 1,368 articles of closely related literature in the field of OA -coagulation index. The number of publications has been on an upward trend in the last decade or so. These results suggest that there is a growing interest among researchers in the field of OA-coagulation metrics. Highly cited literature has focused on studies of inflammation, platelet derivatives, and patient-reported OA. With the development of regenerative medicine, platelet derivatives, such as platelet-rich plasma, have gained increasing attention for use in osteoarthritis 28 . Several prospective cohort studies have demonstrated that intra-articular administration of PRP will alleviate pain and enhance joint function in patients with OA 29–30 . In addition to facilitating coagulation, platelets constitute a rich source of cytokines and growth factors that are necessary for bone mineralization and soft tissue repair 31 . The keywords associated with the OA -coagulation index were pain, risk factors, clinical trials, growth factors, and platelet-rich plasma. Cluster analysis of the keywords also focused on inflammation and coagulation. Consequently, it is reasonable to investigate the significance of markers associated with clotting in OA. The hypercoagulable state involves immune system activation 8 . The inflammatory response and alterations in the coagulation system correlate with the severity of osteoarthritis 32 . Relevant mediators of the inflammatory process and inflammatory regulation include thrombin, fibrinogen, coagulation factor XIII, and factors of the fibrinolytic system, among many other hemostatic system components. During inflammation, cytokines may facilitate thrombosis by regulating the coagulation and fibrinolytic systems 7 . The following cytokines are involved in the coagulation process: TNF-α (which increases platelet activation and aggregation), IL-8 (which activates neutrophils and releases coagulation-promoting factors), IL-6 (which produces fibrinogen to promote coagulation), and IL-1 (which upregulates the expression of endothelial cells and monocytes, leading to an increased procoagulant state) 32–34 . The immune cells' (such as neutrophils and macrophages) activation of platelets and coagulation factors is another essential component of immune cell-mediated coagulation. These immune cells secrete chemicals that promote inflammation, such as tissue factors, chemokines, and cytokines, which can start the coagulation cascade 35–36 . An increased platelet count is also a major cause of hypercoagulable states 37 . D-dimer is the product of fibrinolytic enzyme-mediated degradation of cross-linked fibrin clots 38–39 and has been proven to be a sensitive marker for assessing disseminated intravascular coagulation (DIC). In conclusion, the interaction between coagulation and the immune system is of great importance for clinical practice and research 8 . Coagulation factors have the power to stimulate immune cells and increase cytokine production, which promotes inflammation. At the site of damage, fibronectin serves as a scaffold for immune cells, facilitating their recruitment and activation. Additionally, compared to healthy volunteers, OA patients had higher levels of coagulation (PLT, TT, FIB, and D-dimer) as well as immunoinflammatory indexes (ESR, CRP, IGA, IGG, and ferritin), indicating that both hypercoagulation and inflammation are involved in disease onset and progression. In addition, PLT, TT, FIB, and D-dimer have excellent discriminative capabilities and diagnostic value in OA. The PLT, PT, APTT, TT, FIB, and D-dimer correlated with several immuno-inflammatory indexes (CRP, ESR, C3, C4, IGG, IGA, IGM, and ferritin), indicating that coagulation indices correlated with immuno-inflammatory indexes. In addition to this, the coagulation index correlated with PROs (VAS score and SF-36 subscales), contributing to the differentiation of OA disease activity. The VAS and SF-36 have been proven to be valuable in measuring overall health status, disease activity, and self-perceived disease severity in patients with OA 40 . Association rules are designed to uncover interesting and frequently occurring patterns and associations between item sets of data. Similarly, association rule results again support the high correlation between coagulation index, CRP, and ESR. C-reactive protein levels rise dramatically during inflammatory processes in vivo 41 . Separation of the red blood cells from the plasma is measured by the erythrocyte sedimentation rate. Red blood cells stick to each other during inflammation because the blood contains high levels of fibrinogen. "Rouleaux" are stacks of erythrocytes that settle more quickly 42 . These results indicate that coagulation-related indices in OA are involved in the inflammatory response. Following that, we identified additional parameters linked with VAS disease activity, which we analyzed by univariate regression analyses of PLT (OR = 1.275, p < 0.001), FIB (OR = 1.667, p = 0.024), D-dimer (OR = 2.346, p < 0.001), ESR (OR = 2.326, p < 0.001) and CRP (OR = 2.312, p < 0.001) were identified as independent risk factors for OA disease activity. In multivariate logistic regression, only PLT (OR = 1.874, p = 0.015), D-dimer (OR = 1.534, p = 0.003) and CRP (OR = 1.456, p = 0.021) remained independent predictors of OA disease activity. Based on the results of the AIC and BIC evaluations, we observed that the addition of PLT and D-dimer to the model controlling CRP increased the OR while decreasing the AIC and BIC, implying that the model is more accurate in identifying disease activity. Interestingly, our results imply that PLT and D-dimer may improve, rather than replicate, existing models for evaluating disease activity. The results further confirm the strong clinical utility and high benefits of the model by introducing nomogram plots, clinical decision curves, and correction curves. 5. Advantages and disadvantages The present study has a variety of strengths. First, it is a literature-based study with a large sample size and credible outcomes. Second, this is the first realistic study to confirm the diagnostic and prognostic utility of coagulation indices (PLT and D-dimer) in OA patients. However, our study does have a few drawbacks. First, since this was an observational study with single-center retrospective data and lacked longitudinal monitoring, there may have been selection bias. Second, because our study was limited to real-world patients, we were not able to examine or rule out the effect of treatment on the clotting index, which could have led to confounding biases. Therefore, further studies involving multiple centers will provide a larger sample to validate the findings. Declarations Funding Statement This work was supported by the Anhui Famous Traditional Chinese Medicine Liu Jian Studio Construction Project (Traditional Chinese Medicine Development Secret[2018]No.11),Anhui Province Traditional Chinese Medicine Leading Talent Project(Traditional Chinese Medicine Development Secret[2018] No. 23), High-level Chinese Medicine Key Discipline Construction Project-Traditional Chinese Medicine Bi Disease Study(zyyzdxk-2023100), Anhui Provincial Laboratory of Applied Foundation and Development of Internal Medicine of Modern Traditional Chinese Medicine (2016080503B041), Anhui University Natural Science Major Project (2023AH040112), Young Talents Training Project - "Xinglin Qingxiu Cultivation Plan" (0500-48-65) and the Key Projects of Scientific Research Projects of Higher Education Institutions in Anhui Province (Natural Sciences) (No. 2022AH050449). Author Contributions All authors reviewed the results and approved the final version of the manuscript. Qiao Zhou: Data curation, Methodology, Software, Validation, Visualization, Writing-original draft, Writing- review & editing, Jian Liu: Conceptualization, Writing-review & editing; Yan Zhu: Conceptualization, Data curation, Methodology, Validation, Visualization, Writing-review & editing; Guizhen Wang: Conceptualization, Data curation, Methodology, Validation, Visualization, Writing-review & editing, Jinchen Guo: Data curation, Methodology, Validation, Visualization, Writing-review & editing. Data availability statement The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. Ethics statement The research protocol and procedures have been approved by the Ethics Committee of the First Affiliated Hospital of Anhui University of Chinese Medicine (Review No. 2023AH-52). Acknowledgement We thank all the authors for their contributions to this study and the Foundation for its financial support of this project. 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Plasma D-dimer is not useful in the prediction of deep vein thrombosis after total knee arthroplasty in patients using rivaroxaban for thromboprophylaxis. J Orthop Surg Res . 2018; 11;13(1):173. doi: 10.1186/s13018-018-0883-1 . Goh GS, Liow MHL, Chen JY, Tay DK, Lo NN, Yeo SJ. The patient acceptable symptom state for the knee society score, oxford knee score and short form-36 following unicompartmental knee arthroplasty. Knee Surg Sports Traumatol Arthrosc. 2023;31(3):1113–1122. doi: 10.1007/s00167-021-06592-x . Dainese P, Mahieu H, De Mits S, Wittoek R, Stautemas J, Calders P. Associations between markers of inflammation and altered pain perception mechanisms in people with knee osteoarthritis: a systematic review. RMD Open. 2023; 9(2):e002945. doi: 10.1136/rmdopen-2022-002945 Wixted CM, Charalambous LT, Kim BI, Case A, Hendershot EF, Seidelman JL, Seyler TM, Jiranek WA. 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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-4718192","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":329378723,"identity":"a0ee0d64-e2e6-4d29-95c3-06a34b62e573","order_by":0,"name":"Qiao zhou","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4ElEQVRIiWNgGAWjYDACCRBhwMDAz8ADFTlArBbJBh7GBhK0gHQdIFaL/OzmYxJvCuzkjI+fPf7gZw6DHN+NBMbPBXi0MM45liY5xyDZ2OxMXmJj7zYGY8kbCczSM/BoYZbIMZPmMWBO3HYgx7CZcRtD4oYbCWzMPHi0sEG01Cdu7n8D1lJPUAsPRMvhxA0SEFsSDAhpkZBIS7acY3DcWOLGG8OZvdskDGeeedgsjU+L/Izkgzfe/KmW4+/PMfjwc5uNPN/x5IOf8WmBuA7JViCGxg+xWkbBKBgFo2AUYAIALm5HP/Ni1LcAAAAASUVORK5CYII=","orcid":"","institution":"The Second Affiliated Hospital, Anhui University of Chinese Medicine","correspondingAuthor":true,"prefix":"","firstName":"Qiao","middleName":"","lastName":"zhou","suffix":""},{"id":329378725,"identity":"9a9cf293-9d41-406c-bde8-4a9cad339dee","order_by":1,"name":"jian liu","email":"","orcid":"","institution":"The First Affiliated Hospital, Anhui University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"jian","middleName":"","lastName":"liu","suffix":""},{"id":329378727,"identity":"1d3b9052-bf50-49f4-a4ce-88e3f27705c1","order_by":2,"name":"Yan Zhu","email":"","orcid":"","institution":"The Second Affiliated Hospital, Anhui University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Zhu","suffix":""},{"id":329378729,"identity":"b784fc34-7966-42c2-bbdf-96c5c341ba2c","order_by":3,"name":"Guizhen Wang","email":"","orcid":"","institution":"The First Affiliated Hospital, Anhui University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Guizhen","middleName":"","lastName":"Wang","suffix":""},{"id":329378731,"identity":"64ecaf0a-b6bb-4243-b635-c221331c4884","order_by":4,"name":"Jinchen Guo","email":"","orcid":"","institution":"Anhui University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jinchen","middleName":"","lastName":"Guo","suffix":""}],"badges":[],"createdAt":"2024-07-10 13:06:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4718192/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4718192/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":62185422,"identity":"c74f49f6-ca80-4c07-aac6-6a49c242dc32","added_by":"auto","created_at":"2024-08-10 11:52:40","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":347053,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Annual publication and citation volume. (B) Curve fit of the global annual growth trend in publications.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4718192/v1/5439d19f4e869876f5d3351d.png"},{"id":62185428,"identity":"a3f4e5dd-1514-4183-b3b0-7788311385a8","added_by":"auto","created_at":"2024-08-10 11:52:41","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":5618944,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Clustering of co-cited references; (B) Reference emergence analysis graph (top 20 cited articles).\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4718192/v1/abeb888be075ee45074ccc67.png"},{"id":62185425,"identity":"5d0de2d0-31cf-40b8-b7b4-88fead6606db","added_by":"auto","created_at":"2024-08-10 11:52:41","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":7622135,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Keyword co-occurrence network; (B) Keyword clustering map; (C) Keyword emergence analysis graph.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4718192/v1/7e6eddbc67d1d44d2b5bfe1e.png"},{"id":62186984,"identity":"ca2fa1ed-4995-41a0-81c7-0cc07e8f1f81","added_by":"auto","created_at":"2024-08-10 12:08:41","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1298084,"visible":true,"origin":"","legend":"\u003cp\u003eROC curve analysis.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-4718192/v1/9a5b28e0eb23ffa6559a9adb.png"},{"id":62185424,"identity":"377e0c85-511e-4fd3-b54f-5c61894afe83","added_by":"auto","created_at":"2024-08-10 11:52:41","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2010720,"visible":true,"origin":"","legend":"\u003cp\u003eHeat map of correlation.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-4718192/v1/2caa605b12c1bda3abacffd7.png"},{"id":62185429,"identity":"eed11485-a297-4847-805b-408c8646b4d0","added_by":"auto","created_at":"2024-08-10 11:52:41","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":5891422,"visible":true,"origin":"","legend":"\u003cp\u003eVisualization of association rules.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-4718192/v1/927f74446bbd08e11d1bbaa6.png"},{"id":62185935,"identity":"40acbf23-aea4-43d4-a972-81797cd31273","added_by":"auto","created_at":"2024-08-10 12:00:41","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1332686,"visible":true,"origin":"","legend":"\u003cp\u003e(A) The calibration curves. A 45° angle on the grey line would represent an ideal prediction. Better prediction is indicated by the areas of closer approach; the solid line represents bias correction by bootstrapping (B = 1,000 repetitions); and the dashed lines reflect all cohorts. (B) The decision curve analysis. The net benefit is shown on the y-axis. The expected probability threshold is located on the x-axis. (C) Nomogram of the regression model. Three predictors were used to construct this nomogram. On the highest point scale, the points of each predictor are located and put together. The percentage probability of risk is displayed by the total point projected to the bottom of the scale.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-4718192/v1/7d5cd57e3deab58ad4bd31f6.png"},{"id":62188430,"identity":"fa911574-e771-46bb-822e-98e6f3fb123d","added_by":"auto","created_at":"2024-08-10 12:17:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":30722263,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4718192/v1/1178c294-d3bf-43d0-b298-4ecaa565d957.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The crossroads of the hypercoagulability and patient outcomes in osteoarthritis: interactions and connections","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eOsteoarthritis (OA) is a bone disease characterised by disturbances to cartilage, meniscus, synovium, ligaments, and subchondral bone \u003csup\u003e1\u003c/sup\u003e. Arthralgia, joint malformations, and soft tissue haemorrhage are the symptoms of osteoarthritis. Low-grade systemic inflammation impairs joint tissue homeostasis and exacerbates the deterioration of OA \u003csup\u003e2\u003c/sup\u003e. Clot hypercoagulability is another characteristic of systemic inflammation, and OA also exhibits this characteristic together with a diminished capacity to lyse clots, potentially as a result of actual amyloid production \u003csup\u003e3\u003c/sup\u003e. Localised circulatory disorders in the joints affect the physiochemical microenvironment of the subchondral bone. Frequent localised joint injuries cause osteomalacia, or even erosion of the underlying bone, resulting in the joints becoming more painful, swollen, and stiff \u003csup\u003e4\u0026ndash;5\u003c/sup\u003e. Therefore, it is crucial to study the progression of OA from the perspective of inflammatory and hypercoagulable states.\u003c/p\u003e \u003cp\u003eThe significance of innate immunity is related to the emergence of synovitis, downstream inflammatory activation, and articular cartilage catabolic processes, which contribute to the evolution of OA \u003csup\u003e6\u003c/sup\u003e. Long-term chronic inflammation, cytokine imbalance, and immune disorders in the body contribute to damage to the vascular endothelium, which directly or indirectly activates the coagulation-fibrinolytic system and interferes with anticoagulation, thereby causing microcirculatory disturbances, leading to systemic circulatory abnormalities in patients with OA with hypercoagulability and prothrombotic state \u003csup\u003e7\u003c/sup\u003e. The immune system and the coagulation system work together to positively modify the immunological response. Coagulation factors such as thrombin stimulate immune cells and increase the synthesis of cytokines that promote inflammation \u003csup\u003e8\u003c/sup\u003e. The primary element of blood clotting, fibrin, serves as a scaffold for immune cells and encourages their recruitment and activation at the site of infection or injury. Additionally crucial to OA are platelets, which are involved in vascular integrity, hemostasis, and inflammatory processes \u003csup\u003e9\u003c/sup\u003e. Pro-inflammatory and anti-inflammatory factors\u0026mdash;interleukin (IL)-6, IL-1β, tumour necrosis factor (TNF)-α, IL-10, and IL-4\u0026mdash;are associated with the development of angiogenesis and chemotaxis in OA. The majority are created, activated, adhered to, or expelled by platelets \u003csup\u003e10\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003ePatient-reported outcomes (PROs) are information derived directly from patients' reports of their own health status, functional status, and perceptions of treatment \u003csup\u003e11\u003c/sup\u003e. The Visual Analog Scale (VAS) is widely employed to assess a variety of health-related issues, including pain, mood, and quality of life, and has been recognized as providing robust and valid data \u003csup\u003e12\u003c/sup\u003e. An additional indicator of medical-related quality of life is the MOS item short from the health survey (SF-36) \u003csup\u003e13\u003c/sup\u003e. Bibliometrics is an instrument for applying mathematical and statistical methods to rapidly grasp the hottest research topics and trends in a particular field \u003csup\u003e14\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThis research was conducted to understand the current trends in research related to coagulation and hypercoagulation in patients with OA through bibliometrics. We explore outbreaks of keywords related to coagulation in OA and visualise, evaluate, and predict research status, hotspots, and future trends. Furthermore, we investigated the involvement of coagulation indices\u0026mdash;prothrombin time (PT), fibrinogen (FIB), activated partial thromboplastin time (APTT), thrombin time (TT), D-dimer, and platelet count (PLT) in the pathophysiology of OA. The purpose of our research was to verify whether coagulation indices are related to immune-inflammation and whether they correlate with patient-reported outcomes and disease activity status (as defined by VAS).\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Data\u003c/h2\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003e2.1.1 Literature sources\u003c/h2\u003e \u003cp\u003eThe Web of Science (WOS) Core Collection database is an excellent source of science statistics and evaluation \u003csup\u003e15\u003c/sup\u003e. The search terms were as follows: TS = (Osteoarthritides OR Osteoarthrosis OR Osteoarthroses OR (Osteoarthrosis Deformans) OR Osteoarthritis) AND TS = (hypercoagulable state OR hypercoagulability OR platelet OR blood platelet OR soterocyte OR fibrinogen OR D-dimer). Only English-language articles were chosen among numerous forms of publication. Each investigator independently reviewed all the articles to ensure their relevance. All articles' entire records were searched up to December 20, 2023. In total, 1368 articles were analyzed. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates the results of the complete screening.\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\u003eTS search quires and refinement procedure.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSet\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eResults\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRefinement\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTS= (Osteoarthritides OR Osteoarthrosis OR Osteoarthroses OR (Osteoarthrosis Deformans) OR osteoarthritis) AND TS= (hypercoagulable state OR hypercoagulability OR platelet OR blood platelet OR soterocyte OR Fibrinogen OR D-dimer) Indexes\u0026thinsp;=\u0026thinsp;SCI-EXPANDED\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRefined by LANGUAGES: (English)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,368\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRefined by DOCUMENT TYPES: (Articles)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.1.2 Sources of clinical data\u003c/h2\u003e \u003cp\u003eThis research is an observational, retrospective, single-center study. We enrolled OA patients who were hospitalized between March 2009 and February 2023 at the First Affiliated Hospital of Anhui University of Traditional Chinese Medicine. General information about the patients was retrieved from the hospital case information management system, including basic information such as body mass index (BMI), gender, comorbidities, and length of hospital stay (LOS). Exclusion criteria include: incomplete data; comorbid infections; severe circulatory, respiratory, and hematopoietic diseases; and other autoimmune diseases. The Charlson Comorbidity Index (CCI) \u003csup\u003e16\u003c/sup\u003e is a quantification of patient comorbidities for the purpose of predicting the risk of death from disease. A total of 7,068 osteoarthritis patients took part in the study. On the other side, 795 healthy control group volunteers (HC) were chosen from those who had regular medical checkups at the hospital's medical checkup center. It was not necessary to get informed consent for this retrospective observational investigation. Subjects' personal information was hidden before any analysis. This study was approved by the Ethics Research Committee of the First Affiliated Hospital of Anhui University of Traditional Chinese Medicine (2023AH-52).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Methodology\u003c/h2\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1 Bibliometric Visualization Analysis\u003c/h2\u003e \u003cp\u003eCiteSpace version 6.2.6 was implemented for the bibliometric analysis study, which examined essential pathways and knowledge inflection points in the advancement of topic areas \u003csup\u003e17\u003c/sup\u003e. In our study, CiteSpace software was adopted to perform visualisation analysis, network analysis, cluster analysis, timeline analysis, and outbreak word detection for reference analysis and keywords. The specific parameters used are as follows: set the time range as January 2007\u0026ndash;December 2023; set the time slice as 1, node type to select references and keywords, respectively; and choose the top 50 keywords with the highest frequency of occurrence in each time slice by setting Top N to 50. Paths under and under the pruned slice network in the pruned model are chosen by pruning, and the remaining parameters are default values.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2 Collection of coagulation indexes and immuno-inflammatory indexes\u003c/h2\u003e \u003cp\u003e(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) Coagulation indexes: prothrombin time (PT), activated partial thromboplastin time (APTT), fibrinogen (FIB), thrombin time (TT), platelet count (PLT) and D-dimer. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) Immunologic indexes: immunoglobulin (IG) A, G, M, complement 3 (C3), complement 4 (C4). (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) Inflammation indicators: C-reactive protein (CRP), and erythrocyte sedimentation rate (ESR).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.2.3 Patient-reported outcomes (PROs)\u003c/h2\u003e \u003cp\u003eOne of the most prevalent unidimensional methods for measuring pain intensity is the VAS, which is extensively utilised in rheumatic diseases \u003csup\u003e18\u003c/sup\u003e. The scale is a 10-cm straight line, where \"no pain at all\" is indicated at one end and \"pain to the extreme\" at the other. Eight health-related quality of life questionnaires make up the SF-36 scale: physical function (PF), bodily pain (BP), role-physical (RP), vitality (VT), social function (SF), general health (GH), role-emotional (RE), and mental health (MH)\u003csup\u003e19\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.2.4 Association Rules\u003c/h2\u003e \u003cp\u003eApriori is the most impactful algorithm for mining the frequent item sets of Boolean association rules. An association rule is an implication of the form X\u003cspan class=\"InlineEquation\"\u003e\u003c/span\u003eY, where X and Y are called the prior (antecedent or left-hand-side, LHS) and the successor (consequent or right-hand-side, RHS) of the association rule, respectively. N denotes the total number of items in the sample, and X and Y represent an item set, respectively. The corresponding equations for support, confidence, and elevation are as follows:\u003c/p\u003e \u003cp\u003e\u003cimg 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\" width=\"268\" height=\"150\"\u003e\u003c/p\u003e\u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e2.2.5 Statistical analysis\u003c/h2\u003e \u003cp\u003eFor data processing, the SPSS 22.0 and R software were adopted. The Kolmogorov-Smirnov with Levene test was applied to test the data for normality and chi-square. Measures with a normal distribution were reported as mean and standard deviation, while measures with a non-normal distribution were displayed as median (P25, P75), and count data were displayed as n/%. To determine statistical significance, the Mann-Whitney test, Wilcoxon signed rank test, t-test, or chi-square test (as appropriate) were utilized to determine statistical significance. Correlations between coagulation indices and other indices were analyzed by Spearman or Pearson analysis (as appropriate).\u003c/p\u003e \u003cp\u003eTo compare the diagnostic efficacy of coagulation indicators in OA, the receiver operator characteristic curve (ROC) of the subjects was displayed, and the area under the curve (AUC) was computed. Jorden's test was applied to determine the optimal critical value. Logistic regression models were constructed to assess the relationship between coagulation indices and immune-inflammatory indicators, as well as patient reports. In the multivariate logistic regression analysis, variables that were deemed significant in the univariate analysis were incorporated and modelled using stepwise regression. The absolute values of the t-statistic for each model parameter was determined to compare the relative weight of each predictor in the logistic regression model. McFadden's R\u003csub\u003e2\u003c/sub\u003e and Hosmer-Lemeshow goodness-of-fit tests were utilized to evaluate the logistic regression model. McFadden's R\u003csub\u003e2\u003c/sub\u003e values between 0.2 and 0.4 were deemed to indicate a good fit of the model \u003csup\u003e20\u003c/sup\u003e. The Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) were applied to evaluate the quality of fit and complexity of various models and to select the best-balanced model \u003csup\u003e21\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Trends in the issuance of papers\u003c/h2\u003e \u003cp\u003eA total of 1,368 literary collections were included. The number of publications and citations in a particular period can objectively and quantitatively reflect general trends in a region. Annual number of publications issued and citations related to OA and coagulation metrics are depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA. The first peak was reached in 2020 with a total of 182 publications. Overall, there is a steady upward trend in annual publications in this area. In Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB, a fitted curve showing the overall annual growth trend is presented. Based on the time curve, the global cumulative number of publications in the field is expected to continue to rise over the next 10 years (R\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.922) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Furthermore, the citations of these publications showed an increasing trend year by year (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA), with a total of 16,970 citations (15,873 after the self-citation), an average of 24.42 citations, and an overall h-index of 82. These data demonstrate the overall fluctuating upward trend of OA coagulation index-related studies during the last 16 years.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Analysis of the co-cited literature\u003c/h2\u003e \u003cp\u003eThe topics strongly related to the field of OA-coagulation index were highlighted by evaluating the co-citation network of 1,368 documents. A total of 244 documents (with at least 20 citations) were chosen to map the co-citation analysis network. Cluster analysis categorizes closely related topics to obtain hotspots in this research area. It forms clusters of varying strength based on the co-occurrence links of terms, with significant homophily among terms. Literature clusters were classified using different node colors (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). The top 11 hot topics were presented for clustering. The main research hot topics were osteoarthritis, platelet-rich plasma, intra-articular injection, clinical outcomes, growth factors, clinical efficacy, real-world evidence, pain, systematic reviews, platelet amplification, inflammation in arthritis, and efficacy. Most of the studies focused on OA inflammatory mediators, patient-reported outcome indicators, and blood derivatives.\u003c/p\u003e \u003cp\u003eThe articles with a higher citation frequency can be regarded as more influential in a particular field. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB presents the details of the top 20 articles, with the blue line indicating the time periods and the red line indicating the strong citation frequency. The research by Kon, E. et al. \u003csup\u003e22\u003c/sup\u003e (26.9) gained the most citations over a 7-year period and had the strongest citation burst value. This research was published in 2,009 under the title \"Platelet-rich plasma: intra-articular knee injections produced favorable results on degenerative cartilage plasma: intra-articular knee injections produced favorable results on degenerative cartilage lesions. Natural concentrates of autologous growth factors in the blood may stimulate cartilage anabolism and reduce catabolic processes. Platelet-rich plasma (PRP) influences whole joint homeostasis, decreases synovial hyperplasia, and ultimately boosts knee function, discomfort, and quality of life in OA patients. The citation outbreak published in \u0026ldquo;The American Journal of Sports Medicine\u0026rdquo; by van Buul GM et al. took the longest time \u003csup\u003e23\u003c/sup\u003e. This research demonstrates that platelet-rich plasma release reduces the inflammatory effects of IL-1β on human osteoarthritic chondrocytes, including suppression of NF-B activation.\u003c/p\u003e \u003cp\u003eThis study demonstrates that platelet-rich plasma release attenuates multiple inflammatory effects mediated by IL-1β on human osteoarthritic chondrocytes, including inhibition of NF-κB activation. Notably, an explosion of articles in recent years, such as Dai X et al. \u003csup\u003e24\u003c/sup\u003e and Cheng Y et al. \u003csup\u003e25\u003c/sup\u003e, emphasized blood hypercoagulation as a susceptibility factor for deep vein thrombosis and as a cause of osteoarthritis total knee arthroplasty. According to Liu N et al. \u003csup\u003e26\u003c/sup\u003e, blood rheology alterations and hypercoagulability contributed to the development of petechiae following total knee arthroplasty.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Analysis of co-cited keywords\u003c/h2\u003e \u003cp\u003eKeywords are a high degree of summarization and condensation of the article's theme, as high-frequency keywords in different periods reflect the transformation of research hotspots in the field. A total of 458 keywords were identified, and those related to osteoarthritis-coagulation index were displayed in the network diagram (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). The top 10 high-frequency keywords included osteoarthritis, pain, risk factors, clinical trials, growth factors, platelet-rich plasma (PRP), prevalence, randomized controlled trials, growth factor beta, and chondrogenic differentiation. The term \"emergent words\" refers to keywords that have been widely cited over a period of time. Among them, the longest burst time is \"inflammation\" (2011\u0026ndash;2018), and the strongest burst intensity is \"pain\" (16.55) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Meanwhile, we noticed that regenerative medicine, venous thromboembolism, and M\u003csub\u003e2\u003c/sub\u003e macrophage polarization were the most prevalent keywords in the last 3 years (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). On the basis of the keyword co-occurrence network, further keyword clustering analysis was generated (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). The results were co-clustered into 10 major categories, including inflammatory processes, osteoarthritis, injured articular cartilage, clinical utility, induced apoptosis, M\u003csub\u003e2\u003c/sub\u003e macrophage polarization, mesenchymal stem cell therapy, pain, controlled trial, and coagulation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Results of coagulation index analysis\u003c/h2\u003e \u003cp\u003eAge, gender, and BMI did not significantly differ between OA patients and healthy controls. Compared with the healthy group, PLT, TT, FIB, and D-D indicators were elevated in OA patients. Immuno-inflammatory markers (such as ferritin, IGA, IGG, CRP, and ESR) were significantly elevated in OA patients than in the HC group (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\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\u003eBaseline characteristics, coagulation indices, immunoinflammatory markers and PROs.\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 \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOA(n\u0026thinsp;=\u0026thinsp;7,068)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHC(n\u0026thinsp;=\u0026thinsp;795)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eBaseline characteristics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge(year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61.48\u0026thinsp;\u0026plusmn;\u0026thinsp;11.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59.792\u0026thinsp;\u0026plusmn;\u0026thinsp;8.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,887(26.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e224(28.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.231\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.66\u0026thinsp;\u0026plusmn;\u0026thinsp;2.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.52\u0026thinsp;\u0026plusmn;\u0026thinsp;2.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.321\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLOS (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.00(9.84,16.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.15\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eCoagulation indicator\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePLT (\u0026times;10^9/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e382(285,513)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e108(89,118)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePT (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.81(9.00,11.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.30(11.90,12.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAPTT (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.60(20.30,30.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.71(26.21,30.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.064\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTT (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.9(16.2,28.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.1(15.1,17.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFIB (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.32(3.36,4.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.32(1.09,2.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD-dimer (mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9(0.42,2.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.19(0.11,0.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eImmune-inflammatory markers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCRP (mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.64(7.78,16.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.09(0.05,0.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eESR (mm/h)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57(40,64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC3(g/L))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.09(1.01,1.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.86(0.78,0.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.245\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC4(g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.26(0.23,0.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.17(0.14,0.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.321\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIGA(g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.22(1.21,2.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.93(0.79,1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIGG(g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.43(9.13,15.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.72(5.10,7.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIGM(g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.56(1.79,1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.39(0.31,0.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.056\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFerritin (pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e179.20(141.08,231.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54.2(8.96,71.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"8\" rowspan=\"9\"\u003e \u003cp\u003ePROs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVAS (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.0(5.5,7.5)\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\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePF (score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e40\u003c/span\u003e)\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\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRP (score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e35\u003c/span\u003e)\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\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBP (score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e42\u003c/span\u003e)\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\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGH (score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e40\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVT (score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e42\u003c/span\u003e)\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\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSF (score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.5(25,50)\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\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRE (score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15(12,33.33)\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\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMH (score)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48(38,52)\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\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: BMI: body mass index; LOS: length of hospital stay; CCI: charlson comorbidity index; PLT: platelet count; PT: prothrombin time; APTT: activated partial thromboplastin time; TT: thrombin time; FIB: fibrinogen; CRP: C-reactive protein; ESR: erythrocyte sedimentation rate; C3: complement component 3; C4: complement component 4; IG: immunoglobulin; VAS: visual analog scale; PF: physical function; RP: role-physical; BP: bodily pain; GH: general health; VT: vitality; SF: social function; RE: role-emotional; MH: mental health.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.5 ROC curve of coagulation indices\u003c/h2\u003e \u003cp\u003eROC curve analysis suggested (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) that PLT, TT, FIB, and D-dimer had excellent specificity in differentiating between OA patients and healthy individuals. The best cut-off values of 350 and 0.55 for PLT and D-dimer had the highest sensitivity and specificity among these indices, with AUC (95% CI) of 0.968 (0.907\u0026ndash;0.994) and 0.918 (0.841\u0026ndash;0.965), respectively. The cut-off values were 20.8 for TT and 4.00 for FIB.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Correlation analysis between coagulation indices and immuno-inflammatory indexes, PROs\u003c/h2\u003e \u003cp\u003eThe consequences of the correlation analysis showed that PLT, TT, FIB and D-dimer were positively correlated with the immuno-inflammatory index and negatively correlated with the PROs; ​PT, and APTT are the reverse. The findings exhibited a strong correlation between the immune-inflammatory indices, PROs, and the coagulation indexes of OA patients (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\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\u003eCorrelation analysis.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003ePLT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003ePT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eAPTT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eTT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003eFIB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003eD-dimer\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"13\" nameend=\"c13\" namest=\"c1\"\u003e \u003cp\u003eBaseline characteristics\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.564\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.542\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.519\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.568\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.988\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.561\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.608\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.990\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.923\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.662\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.541\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.563\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.752\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"13\" nameend=\"c13\" namest=\"c1\"\u003e \u003cp\u003eImmune-inflammatory markers\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\u003e0.423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.694\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.779\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.431\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eESR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.827\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.795\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.796\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.621\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.343\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.346\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.343\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.939\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.913\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIGM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.923\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFerritin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.319\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.515\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"13\" nameend=\"c13\" namest=\"c1\"\u003e \u003cp\u003ePROs\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVAS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.931\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.930\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.562\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.562\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.827\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.468\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.469\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.686\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.685\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.474\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.472\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.374\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.527\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.529\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.618\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.272\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.622\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.647\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"13\"\u003eNote: LOS: length of hospital stay; BMI: body mass index; PLT: platelet count; PT: prothrombin time; APTT: activated partial thromboplastin time; TT: thrombin time; FIB: fibrinogen; CRP: C-reactive protein; ESR: erythrocyte sedimentation rate; C3: complement component 3; C4: complement component 4; IG: immunoglobulin; VAS: visual analog scale; PF: physical function; RP: role-physical; BP: bodily pain; GH: general health; VT: vitality; SF: social function; RE: role-emotional; MH: mental health.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.7 Association rule analysis\u003c/h2\u003e \u003cp\u003eWe evaluated the association between the coagulation index and the immuno-inflammation index using the optimal cut-off value established by the ROC curve, where the minimum support was set at 70% and the minimum confidence interval was used at 50%. The pre- and post-items with the highest confidence level were chosen for each item. The results revealed that PLT, FIB, D-dimer, and APTT had a higher association with CRP. The PT and TT had a higher correlation with ESR. The lift was greater than 1 (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\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\u003eCorrelation analysis between coagulation and immunoinflammatory markers.\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItems (LHS\u0026thinsp;\u0026rArr;\u0026thinsp;RHS)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSupport (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eConfidence (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLift\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLT\u0026rArr; CRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45.814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e88.572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.083\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFIB\u0026rArr; CRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e44.539\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e86.875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-dimer\u0026rArr; CRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45.422\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e81.229\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTT\u0026rArr;ESR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29.686\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e82.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAPTT\u0026rArr;CRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23.341\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70.748\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePT\u0026rArr; ESR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25.814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70.274\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.019\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNote: PLT: platelet count; PT: prothrombin time; APTT: activated partial thromboplastin time; TT: thrombin time; FIB: fibrinogen; CRP: C-reactive protein; ESR: erythrocyte sedimentation rate.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e3.8 Univariate and multivariate regression analysis\u003c/h2\u003e \u003cp\u003eThe optimal cutoff values for PLT, FBG, PT, APTT, D-dimer, and TT were determined from the ROC curves, and the critical values for the other variables were determined from the median values. Logistic regression models were performed to describe the associations of PLT, FIB, PT, APTT, D-dimer, and TT with immunoinflammatory indexes and PROs (using VAS\u0026thinsp;\u0026ge;\u0026thinsp;6 as a criterion for subgrouping). In univariate regression analysis, PLT (OR\u0026thinsp;=\u0026thinsp;1.275, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), FIB (OR\u0026thinsp;=\u0026thinsp;1.667, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.024), and D-dimer (OR\u0026thinsp;=\u0026thinsp;2.346, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were independent risk factors for disease activity in OA. The ESR (OR\u0026thinsp;=\u0026thinsp;2.326, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and CRP (OR\u0026thinsp;=\u0026thinsp;2.312, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were markedly correlated with OA disease activity (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eStronger correlations were observed in the multivariate logistic regression analysis, which controlled for sex, age, duration of illness, and BMI. The PLT (OR\u0026thinsp;=\u0026thinsp;1.874, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.015), D-dimer (OR\u0026thinsp;=\u0026thinsp;1.534, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003) and CRP (OR\u0026thinsp;=\u0026thinsp;1.456, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.021) remained independent predictors of OA disease activity. In the multivariate model, TT (OR\u0026thinsp;=\u0026thinsp;1.115, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.078), FIB (OR\u0026thinsp;=\u0026thinsp;1.431, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.081), and ESR (OR\u0026thinsp;=\u0026thinsp;2.105, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.088) were not able to serve as independent predictors of disease activity (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The PLT, D-dimer and CRP were included as variables of interest in the multivariate simplified model. To determine whether PLT and D-dimer were linked to disease activity when CRP was being considered, we tested PLT and D-dimer while correcting for CRP. When CRP was considered, PLT (+\u0026thinsp;CRP) (OR\u0026thinsp;=\u0026thinsp;2.423, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) and D-dimer (+\u0026thinsp;CRP) (OR\u0026thinsp;=\u0026thinsp;2.987, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003) remained significant predictors of disease activity, in addition to the afore-mentioned control variables. AIC and BIC indicate that models containing PLT, D-dimer, and CRP outperform models containing CRP only.\u003c/p\u003e \u003cp\u003eAll independent risk factors screened by regression analysis were integrated to construct a nomogram (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC). Each variable was assigned a score on the rating scale. The overall score was calculated by adding the scores of all variables (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC). C-index values were applied to assess the discriminatory nature of the nomogram for survival prediction in the model (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). The internal validation cohort proved to have good discriminatory performance. The Hosmer-Lemeshow test findings proved that the calibration curves in the dataset once again performed well (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.325) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). In addition, DCA demonstrated that patients could obtain a satisfactory net benefit from the predictive model. A wide range of high-risk thresholds were observed in DCA (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB). In conclusion, the evaluation of the nomogram based on column-line graphs revealed considerable discriminatory and calibrating power of our research model.\u003c/p\u003e \u003cp\u003eTable 5 Univariate logistic regression analysis\u003c/p\u003e\u003cp\u003e\u003cimg 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\" width=\"564\" height=\"364\"\u003e\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eNote\u003c/strong\u003e \u003cp\u003eBMI: body mass index; LOS: length of hospital stay; PLT: platelet count; PT: prothrombin time; APTT: activated partial thromboplastin time; TT: thrombin time; FIB: fibrinogen; CRP: C-reactive protein; ESR: erythrocyte sedimentation rate; C3: complement component 3; C4: complement component 4; IG: immunoglobulin.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMulti-factor logistic regression analysis (as defined by VAS\u0026thinsp;\u0026ge;\u0026thinsp;6)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLaboratory variable (critical value)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOdds ratio (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003et-stat\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep-\u003c/em\u003evalue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAIC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBIC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLT (350)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.874(1.056\u0026ndash;4.134)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21.567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e482.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e356.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTT (20.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.115(0.875\u0026ndash;3.311)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.785\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNot performed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNot performed\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFIB (4.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.431(0.761\u0026ndash;2.145)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.643\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.081\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNot performed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNot performed\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-dimer (0.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.534(1.221\u0026ndash;3.667)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e456.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e342.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eESR (57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.105(1.013\u0026ndash;3.245)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.621\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNot performed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNot performed\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP (11.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.456(1.005\u0026ndash;3.245)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20.754\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e355.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e267.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLT (+\u0026thinsp;CRP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.423(1.116\u0026ndash;4.067)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e211.345\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e135.643\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-dimer (+\u0026thinsp;CRP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.987(1.004\u0026ndash;4.157)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e222.451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e115.689\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: PLT: platelet count; TT: thrombin time; FIB: fibrinogen; CRP: C-reactive protein; ESR: erythrocyte sedimentation rate.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eBibliometrics, through the adoption of mathematical and statistical techniques, aims to explore the distribution pattern, quantitative relationship and changing law of literature information, which can guide not only research design but also clinical practice \u003csup\u003e27\u003c/sup\u003e. We included a total of 1,368 articles of closely related literature in the field of OA -coagulation index. The number of publications has been on an upward trend in the last decade or so. These results suggest that there is a growing interest among researchers in the field of OA-coagulation metrics. Highly cited literature has focused on studies of inflammation, platelet derivatives, and patient-reported OA. With the development of regenerative medicine, platelet derivatives, such as platelet-rich plasma, have gained increasing attention for use in osteoarthritis \u003csup\u003e28\u003c/sup\u003e. Several prospective cohort studies have demonstrated that intra-articular administration of PRP will alleviate pain and enhance joint function in patients with OA \u003csup\u003e29\u0026ndash;30\u003c/sup\u003e. In addition to facilitating coagulation, platelets constitute a rich source of cytokines and growth factors that are necessary for bone mineralization and soft tissue repair \u003csup\u003e31\u003c/sup\u003e. The keywords associated with the OA -coagulation index were pain, risk factors, clinical trials, growth factors, and platelet-rich plasma. Cluster analysis of the keywords also focused on inflammation and coagulation. Consequently, it is reasonable to investigate the significance of markers associated with clotting in OA.\u003c/p\u003e \u003cp\u003eThe hypercoagulable state involves immune system activation \u003csup\u003e8\u003c/sup\u003e. The inflammatory response and alterations in the coagulation system correlate with the severity of osteoarthritis \u003csup\u003e32\u003c/sup\u003e. Relevant mediators of the inflammatory process and inflammatory regulation include thrombin, fibrinogen, coagulation factor XIII, and factors of the fibrinolytic system, among many other hemostatic system components. During inflammation, cytokines may facilitate thrombosis by regulating the coagulation and fibrinolytic systems \u003csup\u003e7\u003c/sup\u003e. The following cytokines are involved in the coagulation process: TNF-α (which increases platelet activation and aggregation), IL-8 (which activates neutrophils and releases coagulation-promoting factors), IL-6 (which produces fibrinogen to promote coagulation), and IL-1 (which upregulates the expression of endothelial cells and monocytes, leading to an increased procoagulant state) \u003csup\u003e32\u0026ndash;34\u003c/sup\u003e. The immune cells' (such as neutrophils and macrophages) activation of platelets and coagulation factors is another essential component of immune cell-mediated coagulation. These immune cells secrete chemicals that promote inflammation, such as tissue factors, chemokines, and cytokines, which can start the coagulation cascade \u003csup\u003e35\u0026ndash;36\u003c/sup\u003e. An increased platelet count is also a major cause of hypercoagulable states \u003csup\u003e37\u003c/sup\u003e. D-dimer is the product of fibrinolytic enzyme-mediated degradation of cross-linked fibrin clots \u003csup\u003e38\u0026ndash;39\u003c/sup\u003e and has been proven to be a sensitive marker for assessing disseminated intravascular coagulation (DIC). In conclusion, the interaction between coagulation and the immune system is of great importance for clinical practice and research \u003csup\u003e8\u003c/sup\u003e. Coagulation factors have the power to stimulate immune cells and increase cytokine production, which promotes inflammation. At the site of damage, fibronectin serves as a scaffold for immune cells, facilitating their recruitment and activation.\u003c/p\u003e \u003cp\u003eAdditionally, compared to healthy volunteers, OA patients had higher levels of coagulation (PLT, TT, FIB, and D-dimer) as well as immunoinflammatory indexes (ESR, CRP, IGA, IGG, and ferritin), indicating that both hypercoagulation and inflammation are involved in disease onset and progression. In addition, PLT, TT, FIB, and D-dimer have excellent discriminative capabilities and diagnostic value in OA. The PLT, PT, APTT, TT, FIB, and D-dimer correlated with several immuno-inflammatory indexes (CRP, ESR, C3, C4, IGG, IGA, IGM, and ferritin), indicating that coagulation indices correlated with immuno-inflammatory indexes. In addition to this, the coagulation index correlated with PROs (VAS score and SF-36 subscales), contributing to the differentiation of OA disease activity. The VAS and SF-36 have been proven to be valuable in measuring overall health status, disease activity, and self-perceived disease severity in patients with OA \u003csup\u003e40\u003c/sup\u003e. Association rules are designed to uncover interesting and frequently occurring patterns and associations between item sets of data. Similarly, association rule results again support the high correlation between coagulation index, CRP, and ESR. C-reactive protein levels rise dramatically during inflammatory processes in vivo \u003csup\u003e41\u003c/sup\u003e. Separation of the red blood cells from the plasma is measured by the erythrocyte sedimentation rate. Red blood cells stick to each other during inflammation because the blood contains high levels of fibrinogen. \"Rouleaux\" are stacks of erythrocytes that settle more quickly \u003csup\u003e42\u003c/sup\u003e. These results indicate that coagulation-related indices in OA are involved in the inflammatory response.\u003c/p\u003e \u003cp\u003eFollowing that, we identified additional parameters linked with VAS disease activity, which we analyzed by univariate regression analyses of PLT (OR\u0026thinsp;=\u0026thinsp;1.275, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), FIB (OR\u0026thinsp;=\u0026thinsp;1.667, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.024), D-dimer (OR\u0026thinsp;=\u0026thinsp;2.346, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), ESR (OR\u0026thinsp;=\u0026thinsp;2.326, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and CRP (OR\u0026thinsp;=\u0026thinsp;2.312, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were identified as independent risk factors for OA disease activity. In multivariate logistic regression, only PLT (OR\u0026thinsp;=\u0026thinsp;1.874, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.015), D-dimer (OR\u0026thinsp;=\u0026thinsp;1.534, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003) and CRP (OR\u0026thinsp;=\u0026thinsp;1.456, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.021) remained independent predictors of OA disease activity. Based on the results of the AIC and BIC evaluations, we observed that the addition of PLT and D-dimer to the model controlling CRP increased the OR while decreasing the AIC and BIC, implying that the model is more accurate in identifying disease activity. Interestingly, our results imply that PLT and D-dimer may improve, rather than replicate, existing models for evaluating disease activity. The results further confirm the strong clinical utility and high benefits of the model by introducing nomogram plots, clinical decision curves, and correction curves.\u003c/p\u003e"},{"header":"5. Advantages and disadvantages","content":"\u003cp\u003eThe present study has a variety of strengths. First, it is a literature-based study with a large sample size and credible outcomes. Second, this is the first realistic study to confirm the diagnostic and prognostic utility of coagulation indices (PLT and D-dimer) in OA patients. However, our study does have a few drawbacks. First, since this was an observational study with single-center retrospective data and lacked longitudinal monitoring, there may have been selection bias. Second, because our study was limited to real-world patients, we were not able to examine or rule out the effect of treatment on the clotting index, which could have led to confounding biases. Therefore, further studies involving multiple centers will provide a larger sample to validate the findings.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Anhui Famous Traditional Chinese Medicine Liu Jian Studio Construction Project (Traditional Chinese Medicine Development Secret[2018]No.11),Anhui Province Traditional Chinese Medicine Leading Talent Project(Traditional Chinese Medicine Development Secret[2018] No. 23), High-level Chinese Medicine Key Discipline Construction Project-Traditional Chinese Medicine Bi Disease Study(zyyzdxk-2023100), Anhui Provincial Laboratory of Applied Foundation and Development of Internal Medicine of Modern Traditional Chinese Medicine (2016080503B041), Anhui University Natural Science Major Project (2023AH040112), \u0026nbsp;Young Talents Training Project - \u0026quot;Xinglin Qingxiu Cultivation Plan\u0026quot; (0500-48-65) and the Key Projects of Scientific Research Projects of Higher Education Institutions in Anhui Province (Natural Sciences) (No. 2022AH050449).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors reviewed the results and approved the final version of the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eQiao Zhou: Data curation, Methodology, Software, Validation, Visualization, Writing-original draft, Writing- review \u0026amp; editing, Jian Liu: Conceptualization, Writing-review \u0026amp; editing; Yan Zhu: Conceptualization, Data curation, Methodology, Validation, Visualization, Writing-review \u0026amp; editing; \u0026nbsp;Guizhen Wang: Conceptualization, Data curation, Methodology, Validation, Visualization, Writing-review \u0026amp; editing, Jinchen Guo: Data curation, Methodology, Validation, Visualization, Writing-review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research protocol and procedures have been approved by the Ethics Committee of the First Affiliated Hospital of Anhui University of Chinese Medicine (Review No. 2023AH-52).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all the authors for their contributions to this study and the Foundation for its financial support of this project.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflicts of interest to report regarding the present study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSanchez-Lopez E, Coras R, Torres A, Lane NE, Guma M. 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J Arthroplasty. 2023;38(5):914\u0026ndash;917. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.arth.2022.12.010\u003c/span\u003e\u003cspan address=\"10.1016/j.arth.2022.12.010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-medical-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejmr","sideBox":"Learn more about [European Journal of Medical Research](http://eurjmedres.biomedcentral.com)","snPcode":"40001","submissionUrl":"https://submission.nature.com/new-submission/40001/3","title":"European Journal of Medical Research","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"osteoarthritis, coagulation index, inflammation, patient-reported outcomes, data mining","lastPublishedDoi":"10.21203/rs.3.rs-4718192/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4718192/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eOur study aimed to probe whether coagulation indices are linked to patient-reported outcomes (PROs) in OA.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA thorough review of the literature on OA and coagulation indices was conducted using bibliometric approaches. Clinical data were retrospectively analyzed in OA patients (7,068) and healthy controls (HC, 795). Coagulation indices\u0026mdash;prothrombin time (PT), fibrinogen (FIB), activated partial thromboplastin time (APTT), thrombin time (TT), D-dimer, and platelet count (PLT)\u0026mdash;as well as immune-inflammatory indices, PROs (visual analogue scale and Short Form 36), were analyzed for correlations.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eCo-cited literature revealed that research related to OA and coagulation indices focused on inflammation, pain, and clinical utility. The levels of PLT, TT, FIB, and D-dimer were elevated in the OA group compared to the HC group. Hypercoagulable states are present in the OA. The results of the ROC demonstrate that they can differentiate between OA and healthy individuals. Coagulation indices were strongly linked to immune-inflammatory indicators and PROs. Logistic regression analysis indicated that PLT, D-dimer, and C-reactive protein (CRP) were all predictive of disease activity. However, PLT and D-dimer combined with CRP had a superior predictive effect than CRP alone.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003ePLT and D-dimer may serve as appropriate biomarkers to correlate with OA disease activity.\u003c/p\u003e","manuscriptTitle":"The crossroads of the hypercoagulability and patient outcomes in osteoarthritis: interactions and connections","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-10 11:52:36","doi":"10.21203/rs.3.rs-4718192/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-10-28T10:44:33+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-26T06:43:51+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-13T00:29:58+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-09T11:54:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"261492081757557894327711958913224321641","date":"2024-09-09T11:43:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"107667353219837767538297643688811970231","date":"2024-09-07T13:12:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"231541581327843821956902198398670514976","date":"2024-09-07T12:29:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"270914471196784707480205500602379634351","date":"2024-09-06T21:11:34+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-20T21:42:47+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-12T04:17:15+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-11T09:14:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Medical Research","date":"2024-07-10T13:03:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-medical-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejmr","sideBox":"Learn more about [European Journal of Medical Research](http://eurjmedres.biomedcentral.com)","snPcode":"40001","submissionUrl":"https://submission.nature.com/new-submission/40001/3","title":"European Journal of Medical Research","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2c1d8842-6c40-4795-a7dc-734fb50afb5d","owner":[],"postedDate":"August 10th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-01-16T16:23:34+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-10 11:52:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4718192","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4718192","identity":"rs-4718192","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}