Predictive value of lymphocyte-to-C-reactive protein ratio for predicting initial and repeated intravenous immunoglobulin resistance in a large cohort of Kawasaki disease: a prospective cohort study

Predictive value of lymphocyte-to-C-reactive protein ratio for predicting initial and repeated intravenous immunoglobulin resistance in a large cohort of Kawasaki disease: a prospective cohort study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Predictive value of lymphocyte-to-C-reactive protein ratio for predicting initial and repeated intravenous immunoglobulin resistance in a large cohort of Kawasaki disease: a prospective cohort study Yaru Cui, Pingting Ye, Hongyu Duan, Xiaoliang Liu, Kaiyu Zhou, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5840515/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Lmphocyte to C-reactive protein ratio (LCR) has tremendous predictive power for diseases with similar pathogenesis to Kawasaki disease (KD). The evidence on the prognostic value of LCR for IVIG resistance, especially for repeated IVIG resistance in KD, was scarce. We conducted a prospective cohort study comprising 1607 individuals with Kawasaki disease to evaluate the predictive value of LCR for both the initial and repeated IVIG resistance in KD. A comparison was made between the initial/repeated IVIG-resistance group and the initial/repeated IVIG-response group. We found that LCR was markedly reduced in both initial and repeated IVIG non-responders and was recognized as an independent risk factor for forecasting both initial and repeated IVIG resistance in KD. The optimal cut-off values of LCR for predicting initial and repeated IVIG resistance were 0.042×10^9 and 0.025×10^9, respectively, with sensitivities of 74.1% and 51.3%, and specificities of 65.9% and 55.8%. LCR may be a complementary laboratory marker for predicting initial and repeated IVIG resistance to guide clinical management. Health sciences/Biomarkers/Predictive markers Health sciences/Medical research/Paediatric research Kawasaki disease prediction Intravenous immunoglobulin resistance lymphocyte to C-reactive protein ratio Figures Figure 1 Figure 2 Background Kawasaki disease (KD) is an acute, systemic vasculitis affecting small to medium-sized vessels, primarily in children, with coronary artery lesions (CALs) being the most severe complication[1]. Intravenous immunoglobulin (IVIG) is the primary treatment for KD, however, over 10% of patients are resistant to both first and subsequent IVIG therapies, resulting in an elevated risk of developing CALs. Consequently, prompt recognition of initial and repeated IVIG resistance, together with appropriate intervention with steroids or infliximab, might mitigate the occurrence of CALs and decrease the healthcare expenses linked to repeated IVIG treatments[1-3]. However, current biomarkers for predicting initial and repeated IVIG resistance have low levels of evidence, and there is still no reliable biomarker to predict IVIG resistance in KD effectively[4]. This is especially significant for patient groups outside Japan, since risk-scoring methods formulated in Japan have proven non-reproducible in Chinese populations, and efforts to create analogous algorithms have failed. Although the exact aetiology of KD remains unclear, the pathogenesis is known to involve immune and inflammatory responses[5]. Lymphocytes, a type of white blood cell, reflect immune system function and have anti-inflammatory properties, helping to stabilize vascular endothelium. Recently, the changed lymphocytes counts in peripheral blood resulting from immunosuppression has been observed in the pathological process of KD[6-7]. In addition, C-reactive protein (CRP) is a recognized acute phase response protein, and higher levels indicate a more severe inflammatory state. Thus, the disparity between elevated CRP levels and decreased lymphocyte counts may suggest that patients are experiencing significant inflammatory responses and a severe clinical progression of KD. Nonetheless, an individual inflammatory parameter may be readily affected by other factors. The combined analysis of inflammatory indicators, including the neutrophil-to-lymphocyte ratio (NLR) and the platelet-to-lymphocyte ratio (PLR), has been recognized as independent risk factors for IVIG resistance and/or coronary artery lesions (CALs); nonetheless, their predictive capabilities remain non-inclusive[4]. Lymphocyte-to-C-reactive protein ratio (LCR) is a novel prognostic biomarker and has been proved useful for peri-operative management and post-operative follow-up. Previous studies have shown that LCR can predict the severity and prognosis of diseases with similar pathogenesis to KD, such as certain kinds of cancers and COVID-19[8-11]. A recent retrospective investigation indicated that LCR may serve as a robust biomarker for the prompt identification of sepsis in infants suspected of having the condition[12]. Yet, the possible implications of LCR in predicting IVIG resistance in patients with KD have not been detailed. Thus, this research prospectively examined the predictive capacity of LCR for initial and recurrent IVIG resistance in KD, and assessed the prognostic accuracy of LCR in comparison to the NLR and PLR. Patients and methods This research prospectively included children diagnosed with KD at the Pediatric Cardiovascular Center of West China Second University Hospital, Sichuan University, from January 2013 to June 2022. KD was diagnosed by two seasoned pediatricians, at least one of whom was a KD specialist, in accordance with the American Heart Association's diagnostic criteria[13]. The parents of the diagnosed children completed a questionnaire covering personal information, symptom descriptions, and treatment processes. Blood samples were collected from the KD patients before initiating IVIG therapy. The study was approved by the Ethics Committee of Sichuan University (NO. 201712160121). All research was performed in accordance with relevant guidelines/regulations. Informed consent was obtained from all participants and/or their legal guardians. Initially, 1849 KD patients were included. Patients who had undergone IVIG therapy at other medical facilities (n = 119) or who did not get IVIG within 10 days after fever start (n = 34) were excluded. Fifty-three individuals were eliminated for initiating IVIG therapy prior to blood sample collection. Additionally, 36 patients with incomplete laboratory data or lacking follow-up results were excluded. Ultimately, 1,607 KD patients were included in the study, comprising 1406 initial responded to IVIG treatment and 201 initial resistence to IVIG treatment. Among the 201 patients with initial IVIG resistance, 88 patients were non-responders to repeated IVIG treatment and were treated with pulse methylprednisolone (Figure 1, Flowchart). No patients received additional treatments such as infliximab, plasmapheresis, or cytotoxic drugs. All patients were administered an identical therapy protocol within 10 days of illness start, including high-dose IVIG(2 g/kg as a single infusion) and aspirin (30–50 mg/kg/day). Following defervescence, aspirin dosage was decreased to 3–5 mg/kg/day for a duration of 6–8 weeks. Initial IVIG resistance was characterized by persistent fever (T > 38.0°C) or other clinical signs of Kawasaki Disease persisting for a minimum of 36 hours and a maximum of 7 days after the first and second IVIG administrations (2 g/kg single intravenous infusion)[14]. If fever or clinical symptoms recurred or remained after the second IVIG treatment, it was classified as repeated IVIG resistance, necessitating the addition of intravenous prednisolone (10-30 mg/kg/day for 3 days), followed by oral prednisolone (2 mg/kg/day) for 7 days with slow tapering. Statistical analyses SPSS 27.0 (SPSS Inc. Chicago, IL, USA) processed and analyzed data. Quantitative data was given as “the median with the 25th and 75th percentiles” and qualitative data as numbers (n) vs percentages (%). After verifying normal distribution and group homogeneity, the Shapiro-Wilk and homogeneity of variance tests were performed. The chi-square test and unpaired Student's t-test or Mann-Whitney U test evaluated demographics, clinical symptoms, and laboratory data between IVIG response and IVIG resistance groups. Pearson's examination of statistically distinct laboratory markers with LCR excluded indications with strong association. Multivariate logistic regression analysis identified independent predictors of IVIG resistance for the remaining statistically distinct markers. For the receiver operating characteristic (ROC) curve, the greatest sensitivity and specificity Youden index was used as the cut-off value. Statistical significance was calculated at P<0.05. Results Comparison of subjects between groups of initial IVIG-response and IVIG-resistance The baseline statistics of the initial IVIG-response and IVIG-resistance children were comparable. Initial IVIG resistance group was associated with greater rates of rash, edema, oral and pharyngeal mucosa erythema, and cervical lymphadenopathy compared to the response group (p < 0.05). aspartate aminotransferase(AST), alanine aminotransferase(ALT), creatinine, urea nitrogen, total bilirubin (TB), C-reactive protein (CRP), neutrophil-lymphocyte ratio (NLR), and platelet-lymphocyte ratio (PLR) were significantly higher in the initial IVIG-resistance group than in the responsed group, while lymphocyte count (LYMPH), platelet(PLT), albumin(ALB), sodium, potassium, and lymphocyte-CRP ratio (LCR) were significantly lower(Table 1 ). Table 1 Comparison of clinical data between the groups of initial IVIG-resistant and IVIG-responsive in KD IVIG-resistant(n = 201) IVIG-responsive(n = 1406) P value Age(months) 28.00(1.00-115.00) 27.00(1.00-152.00) 0.274 Male (%) 109(54.2%) 804(57.2%) 0.429 Day of illness before admission, (days) 5(3–7) 5(3–7) 0.963 Day of illness before IVIG 0.091 0-7days, n(%) 188(93.5%) 1328(94.5%) 8-10days, n(%) 13(6.5%) 78(5.5%) Clinical manifestations Rash, n (%) 160(79.6%) 949(67.2) < 0.001* Bilateral bulbar conjunctive injection, n (%) 186(92.5%) 1287(91.5%) 0.631 Edema & erythema of the extremities, n (%) 128(63.7%) 767(54.7%) 0.017* Erythema of oral and pharyngeal mucosa, n (%) 191(95%) 1277(90.8%) 0.048* Cervical lymphadenopathy, n (%) 105(52.5%) 586(41.7%) 0.004* Incomplete KD, n (%) 36(17.9%) 322(22.9%) 0.112 CALs, n(%) 32(15.9%) 176(12.5%) 0.291 Laboratory features WBC count(10 9 /L) 12.80(9.70-16.45) 13.30(10.70–16.40) 0.120 NEUT(10 9 /L) 9.63(6.54–12.53) 8.91(6.47–11.71) 0.062 LYMPH(10 9 /L) 1.90(1.15–3.16) 2.97(2.04–4.19) < 0.001* Hemoglobin(g/L) 109.00(102.00-116.00) 110.00(103.00-117.00) 0.220 PLT count(10 9 /L) 306.00(238.00-359.50) 336.00(280.00-407.00) < 0.001* AST(IU/L) 39.00(26.00-73.50) 33.00(25.50–49.00) 0.004* ALT(IU/L) 54.00(23.50-127.50) 32.00(17.00–78.00) < 0.001* ALB(g/L) 37.00(32.40–40.00) 38.85(35.70–42.00) < 0.001* Creatinine(umol/L) 28.00(23.00-33.50) 26.00(22.00–31.00) < 0.001* Urea nitrogen(mmol/L) 2.91(2.40–3.7) 2.80(2.20–3.40) 0.008* TB (umol/L) 7.60(5.30-18.45) 6.00(4.10–8.90) < 0.001* Sodium(mmol/L) 134.5(132.15–136.40) 136.70(134.60-138.50) < 0.001* Potassium(mmol/L) 4.00(3.60–4.34) 4.17(3.80–4.50) < 0.001* ESR(mm/h) 63.00(3.00–82.00) 62.00(42.00–81.00) 0.612 CRP(mg/L) 93.30(62.85–136.00) 71.00(43.00-107.00) < 0.001* LCR(10 9 ) 0.02(0.01–0.04) 0.04(0.02–0.08) < 0.001* NLR 4.87(2.70–9.54) 2.85(1.75–5.06) < 0.001* PLR 146.82(94.01-238.13) 113.43(81.40-168.04) < 0.001* The data are presented as the median with the 25th and 75th percentiles in square brackets for continuous variables and as the percentage for the categorical variables. Comparison of subjects between repeated IVIG-response and IVIG-resistance group Children in the repeated IVIG-response and IVIG-resistance groups had comparable baseline data as well as comparable clinical presentations. CRP, NLR, and PLR were considerably greater in the IVIG-resistant group than in the IVIG-responsed group, whereas LYMPH, hemoglobin, ALB, and LCR were significantly lower(Table 2 ). Table 2 Comparison of clinical data between the groups of repeated IVIG-resistant and IVIG-responsive in KD IVIG-resistant(n = 88) IVIG-responsive(n = 113) P value Age(months) 26.50(14.00-52.75) 28.50(16.00-46.50) 0.622 Male (%) 43(48.9%) 67(59.6%) 0.081 Day of illness before admission, (days) 5(2–10) 4(2–10) 0.204 Day of illness before IVIG 0.066 0-7days, n(%) 82(93.18%) 108(95.6%) 8-10days, n(%) 6(6.2%) 5(4.4%) Clinical manifestations Rash, n (%) 74(84.1%) 87(76.9%) 0.128 Bilateral bulbar conjunctive injection, n (%) 86(97.7%) 105(92.9%) 0.461 Edema & erythema of the extremities, n (%) 55(62.5%) 76(67.3%) 0.191 Erythema of oral and pharyngeal mucosa, n (%) 87(98.9%) 109(96.5%) 0.487 Cervical lymphadenopathy, n (%) 41(46.6%) 65(57.5%) 0.065 Incomplete KD, n (%) 17(19.3%) 19(16.8%) 0.437 CALs, n(%) 14(15.9%0 18(15.9%) 0.713 Laboratory features WBC count(10 9 /L) 12.55(9.23–16.78) 13.3(10.25–16.20) 0.505 N(10 9 /L) 9.45(6.54–12.91) 9.69(6.66–12.23) 0.876 L(10 9 /L) 1.64(0.87–2.72) 2.22(1.40–3.28) < 0.001* Hemoglobin(g/L) 107.00(100.00-113.00) 112.00(103.00-119.00) 0.018* PLT count(10 9 /L) 289.50(240.50-341.75) 316.00(235.00-364.00) 0.204 AST(IU/L) 39.00(26.50–66.00) 40.50(25.25-87.00) 0.441 ALT(IU/L) 48.00(26.00-96.50) 62.50(21.00-159.50) 0.278 ALB(g/L) 34.20(30.65–38.80) 37.70(33.85–40.90) < 0.001* Creatinine(umol/L) 28.00(24.00–34.00) 27.50(23.00–33.00) 0.555 Urea nitrogen(mmol/L) 2.90(2.30–3.50) 3.00(2.40–3.83) 0.462 TB (umol/L) 6.80(4.65-29.00) 7.80(6.03–16.45) 0.519 Sodium(mmol/L) 134.00(132.00-136.00) 134.80(132.23–137.00) 0.215 Potassium(mmol/L) 4.00(3.51–4.37) 4.05(3.63–4.31) 0.371 ESR(mm/h) 61.00(40.25-80.00) 64.00(43.50–87.50) 0.501 CRP(mg/L) 96.95(69.50-151.95) 93.30(59.50-123.50) 0.034* LCR(10 9 ) 0.02(0.01–0.04) 0.03(0.01–0.05) < 0.001* NLR 7.25(2.77–12.32) 3.89(2.68–7.40) 0.03* PLR 181.13(95.34-331.92) 137.08(91.81-209.23) 0.08* The data are presented as the median with the 25th and 75th percentiles in square brackets for continuous variables and as the percentage for the categorical variables. Abbreviations: IVIG, intravenous immunoglobulin; KD, Kawasaki Disease; CALs, coronary artery lesions; WBC, white blood cell; NEUT: neutrophil count; LYMPH: lymphocyte count; PLT, platelet; AST, aspartate aminotransferase; ALT, alanine aminotransferase; ALB, Albumin; TB, total bilirubin; ESR, erythrocyte sedimentation rate; CRP, C-reactive protein; NLR, neutrophil-lymphocyte ratio; LCR, lymphocyte-CRP ratio; PLR, platelet-lymphocyte ratio # Variables between two groups were compared by the Mann–Whitney U test due to abnormal data distribution. * Statistically significant (P < 0.05) Multivariate logistic regression analysis Pearson's analysis was performed to analyze initial and repeated IVIG resistance using LCR and other statistically distinct laboratory single-factor variables (Table 3 ). We used multivariate logistic regression after removing factors with substantial correlations. LCR was shown to be an independent risk factor for both first IVIG resistance (OR: 3804.00, 95%CI (64.60-224002.83), p < 0.001) and recurring IVIG resistance (OR: 9549037.28, 95%CI (87.41-1043208403740.78), p = 0.004) (Table 4 ). Table 3 Clinical correlation between univariate factors and LCR in the KD subjects Parameters LYMPH(10 9 /L) PLT(10 9 /L) ALT(IU/L) ALB(g/L) TB (umol/L) Na+(mmol/L) K+(mmol/L) CRP(g/L) r P r P r P r P r p r P r p r p Initial-LCR(10 9 ) 0.169 < 0.001* 0.150 < 0.001* -0.069 0.006* 0.119 < 0.001* -0.072 0.005* 0.079 0.002* 0.065 0.011* -0.247 < 0.001* Repeated-LCR LYMPH(10 9 /L) HGB(g/L) ALB(g/L) CRP(g/L) Repeated-LCR(10 9 ) r p r p r p r p 0.514 < 0.001* 0.218 0.002* 0.302 < 0.001* -0.493 < 0.001* Abbreviations: LYMPH: lymphocyte count; PLT, platelet; ALT, alanine aminotransferase; ALB, Albumin; TB, total bilirubin; Na+, sodium; K+, Potassium; CRP, C-reactive protein; NLR, neutrophil-lymphocyte ratio; HGB, hemoglobin. *Statistically significant (P < 0.05). Table 4 A multivariate logistic regression model for initial and repeated intravenous immunoglobulin (IVIG)-resistance in Kawasaki Disease. Initial Variates β SE Walds P value OR 95%CI LCR(10 9 ) 8.244 2.079 15.717 < 0.001* 3804.00 64.60-224002.83 Urea nitrogen(mmol/L) -0.010 0.009 1.221 0.269 0.99 0.97–1.01 Creatinine(umol/L) -0.049 0.064 0.569 0.451 0.95 0.84–1.10 AST(IU/L) -0.001 0.001 2.572 0.109 0.99 0.99-1.00 Rash -0.504 0.199 6.380 0.012* 0.60 0.41–0.89 Edema & erythema of the extremities -0.223 0.169 1.735 0.188 0.80 0.58–1.12 Erythema of oral and pharyngeal mucosa -0.416 0.346 1.449 0.229 0.66 0.34–1.30 Cervical lymphadenopathy -0.258 0.162 2.545 0.111 0.77 0.56–1.06 Repeated Variates LCR(10 9 ) -0.246 0.216 1.298 0.007* 9549037.28 87.41-1043208403740.78 Abbreviations: IVIG, intravenous immunoglobulin; LCR, lymphocyte-CRP ratio; AST, aspartate aminotransferase; OR, odds ratio; CI, confidence ratio *Statistically significant (P < 0.05) Predictive value of LCR for initial IVIG-resistance and repeated IVIG-resistance in KD patients For initial IVIG resistance prediction, LCR ≤ 0.042 had an AUC of 0.694 [OR(95%CI): 0.33(0.24–0.46)], with a corresponding sensitivity, specificity, PPV, NPV of 74.1%, 51.3%, 17.9%, 93.3%, respectively (Table 5 and Fig. 2 A). For repeated IVIG resistance prediction, LCR ≤ 0.025 had an AUC of 0.636 [OR(95%CI): 0.41(0.23–0.73)], with a corresponding sensitivity, specificity, PPV, NPV of 65.9%, 55.8%, 53.7%, 67.7%, respectively (Table 5 and Fig. 2 B). Table 5 The validity of LCR, LYMPH, CRP NLR and PLR cut-off values in predicting initial and repeated IVIG resistance for the total group. Initial IVIG resistance Diagnostic test Gold standard Sen Spe PPV NPV Diagnostic accuracy OR(95%CI) P n = 1607 LCR(10 9 ) ≤ 0.042 positive 721 685 74.1% 51.3% 17.9% 93.3% 0.694 0.33(0.24–0.46) < 0.001* negative 52 149 LYMPH(10 9 /L) ≤ 1.932 positive 1087 319 51.7% 77.3% 24.6% 91.8% 0.678 0.27(0.20–0.37) < 0.001* negative 97 104 CRP(mg/L) ≥ 59.95 positive 567 839 80.1% 40.3% 16.1% 93.4% 0.636 0.37(0.26–0.53) < 0.001* negative 40 161 NLR ≥ 5.858 positive 1124 282 45.3% 79.9% 24.4% 91.1% 0.666 0.30(0.22–0.41) < 0.001* negative 119 91 PLR ≥ 186.407 positive 1137 269 38.3% 80.9% 22.3% 90.2% 0.613 0.38(0.28–0.52) < 0.001* negative 124 77 Repeated IVIG resistance Diagnostic test Gold standard Sen Spe PPV NPV Diagnostic accuracy OR(95%CI) P n = 206 LCR(10 9 ) ≤ 0.025 positive 63 50 65.9% 55.8% 53.7% 67.7% 0.636 0.41(0.23–0.73) 0.002* negative 30 58 LYMPH(10 9 /L) ≤ 1.039 positive 101 12 36.4% 89.4% 72.7% 64.3% 0.635 0.21(0.10–0.44) < 0.001* negative 56 32 CRP(mg/L) ≥ 116.85 positive 83 30 43.2% 73.5% 55.9% 62.4% 0.587 0.48(0.26–0.86) 0.013* negative 50 38 NLR ≥ 7.414 positive 86 27 50.0% 76.1 62.0% 66.2% 0.621 0.31(0.17–0.57) < 0.001* negative 44 44 PLR ≥ 245.63 positive 97 16 37.5% 85.5% 67.3% 63.8% 0.610 0.28(0.14–0.54) < 0.001* negative 55 33 Abbreviations: IVIG, intravenous immunoglobulin; Sen: sensitivity; Spe: specificity; PPV: positive predictive value; NPV: negative predictive value; OR, odds ratio; CI, confidence ratio; LCR, lymphocyte-CRP ratio; LYMPH: lymphocyte count; CRP, C-reactive protein; NLR, neutrophil-lymphocyte ratio; PLR, platelet-lymphocyte ratio *Statistically significant (P < 0.05) Discussion Predicting resistance to IVIG is a major problem in Kawasaki disease. This research prospectively examined the predictive value of LCR for initial IVIG resistance in KD and compared it with the predictive values of NLR and PLR using the biggest sample size to date. Most significantly, the best of our knowledge, this was the first research that to established the validity of LCR in repeated IVIG resistance prediction. LCR was considerably reduced in both the initial and repeated IVIG-resistant groups compared to responders. In addition, we also found that the predictive validities of several risk score systems[15-20](Supplementary table 1), our merging indicators of NLR as well as PLR(Table 5) did not have a much greater predictive ability than LCR. Considering the LCR are routinely detectable indicators that can be obtained without additional cost, it thus might provide some references for clinical management. LCR serves to highlight a relative lymphopenia compared to normal and raised CRP levels. LCR was recently shown to be a viable predictor of postoperative morbidity, prognosis, and recurrence in a variety of cancer types, COVID-19 associated with inflammation, and probable sepsis. Iseda et al. discovered that preoperative LCR serves as a novel and easy prognostic indicator for patients with hepatocellular carcinoma, suggested that LC was correlated with the immunological state of the tumor microenvironment[21]. In addition, Ullah et al found that LCR was associated with impending clinical deterioration and the need for invasive mechanical ventilation for patients with severe COVID-19[22]. Yang et al. indicated that LCR had more efficacy compared to CRP or lymphocytes alone in evaluating severe COVID-19[23]. Moreover, Li et al. identified a significant negative correlation between LCR and procalcitonin, with a diminished LCR serving as an independent marker for the detection of sepsis and its severe manifestations[12]. The above findings suggest that the combination of LCR could be a sensitive biomarker during the acute inflammatory phase. However, the correlation between LCR and KD in forecasting IVIG resistance has been little explored in existing literature. Lymphocytes are a kind of white blood cells primarily generated by lymphoid organs. These cells combat bacterial and viral infections in the body, thereby holding crucial prognostic value in the immune response to infections. It is postulated that KD pathogens associated with extensive inflammation lead to immunological dysregulation and apoptotic depletion of lymphocytes. This mechanism may further provoke a state of immunosuppression, hence increasing host vulnerability to invading infections[25-27]. Moreover, as a systemic inflammatory mediator, CRP is an evolutionarily conserved innate immune polymer protein, recognized as a significant biomarker for predicting disease severity and used in several predictive models[28-30]. Therefore, the lower lymphopenia and higher CRP level, a quickly, inexpensively, and non-invasively biomarker, might be more accurately and sensitively for predicting IVIG resistance since the more severity of inflammation of these children they are and an earlier treatment with hormones, infliximab or plasmapheresis may be attempted to use to minimize the occurrence of CALs. Therefore, during this research, the association of LCR with initial and repeated IVIG resistant children were both studied. LCR was identified as an independent predictor for initial and recurrent IVIG-resistant KD in children, and we firstly discovered that repeated IVIG nonresponders had a significantly reduced LCR than responders. A comparatively greater sensitivity of 74.1% and 65.9% was obtained for initial and repeated nonresponders, respectively, with cutoff values of 0.042 and 0.025. Although we were unable to identify all non-responders to initial and repeated IVIG using LCR calculation, these data may enhance the added knowledge on predicting resistance to initial and repeated IVIG and provide references for therapeutic care. In addition, we also found that the combined indicators such as NLR and PLR were not satisfied for simultaneously predicting initial and repeated IVIG resistance in our population. The asynchronous peak in neutrophils, platelets, and lymphocytes during the acute phase of Kawasaki Disease (KD), together with the earlier elevation of C-reactive protein (CRP) compared to neutrophilia in more severe cases of KD, may be the underlying cause[22, 24]. Moreover, several risk scoring systems, such as Kobayashi[15], Egami[16], Sano[17], Ming[18], Yang[19], and Tang[20], seemed to be less optimal and clinically relevant in comparison to ours due to their more intricate calculations and indications (Supplementary table 1). The disparities in starting medication, the definition of IVIG resistance, patient inclusion criteria, genetic backgrounds, and the uneven timing of regular blood tests between their research and ours likely account for the divergent results. This work should be considered in the context of several possible limitations. Since our hospital is the biggest Children Medical Center in Southwest China, the fact that this research was conducted in a single institution may result in some selection bias in the admission of more serious patients. Secondly, the current investigation was prospective cohort research with stringent inclusion and exclusion criteria. The results of our investigation were only relevant to KD patients who received standardized IVIG therapy within 10 days of fever start. Notwithstanding the aforementioned limitations, this research is the inaugural investigation to ascertain the prognostic significance of LCR for both initial and repeated IVIG resistance, using a substantial patient cohort and a prospective methodology. LCR was considerably lower in IVIG nonresponders; nevertheless, it may only function as a supplementary laboratory marker for predicting both initial and recurrent IVIG resistance in KD. Considering the uncertain etiology of KD, we propose that a predictive model including alternative specific indications, rather than only clinical and routine laboratory characteristics, may provide superior results. Conclusion In conclusion, this study demonstrated that LCR is an independent risk factor for predicting initial and repeat IVIG resistance in KD. Considering the convenient and cost-effectively indicator it is, LCR may be a complementary laboratory marker for predicting IVIG resistance to guide clinical management. Declarations Ethics approval and consent to participate: The study was approved by the University Ethics Committee on Human Subjects at Sichuan University. All research was performed in accordance with relevant guidelines/regulations. Informed consent was obtained from all participants and/or their legal guardians. Consent for publication: Written consent obtained. Availability of data and material: Data is provided within the manuscript or supplementary information files. Competing interests: The authors declare that they have no competing interests. Funding: This work was supported by Science-TechnologySupport Plan Proiects in Sichuan Province (2024YFFK0272; 2024NSFSC1711; 2024YFFK0078). National Natural Science Foundation of China (No.82370236; No.82070324) and National Key Research and Development Program of China (No.2023YFC2706402; No.2022YFC2703902). Contributor Statement: CYR and YPT drafted the manuscript, contributed to the data collection, interpreted the statistical analysis and approved the final manuscript as submitted. DHY and LXL contributed to the study design and approved the final manuscript as submitted. MF provided Table1 and Table2, contributed to the data collection, study design and as well as approved the final manuscript as submitted. LJH provided Table3 ,Table4, Table5 and Table6 contributed to the data collection and approved the final manuscript as submitted. ZKY and HYM provided major treatment on these patients while admitted, contributed to the study design, approved financial support and as well as approved the final manuscript as submitted. WC and SSR conceived conception and designed the study, contributed to the data collection and approved the final manuscript as submitted. Acknowledgments: We are grateful to the patients and families for their contributions to this work. References McCrindle, B. W. et al. Diagnosis, treatment, and long-term management of kawasaki disease (a scientific statement for health professionals from the American Heart Association, 2017). Kobayashi, T. et al. Efficacy of immunoglobulin plus prednisolone for prevention of coronary artery abnormalities in severe Kawasaki disease (RAISE study): a randomised, open-label, blinded-endpoints trial. Lancet 379 (9826), 1613–1620 (2012). Pilania, R. K., Jindal, A. K., Guleria, S. & Singh, S. An update on treatment of Kawasaki disease, Curr. Treat. Options Rheumatol. 5 (1), 36–55 (2019). Kim, T. H. et al. Biomarkers and Related Factors for the Diagnosis, Risk of Coronary Artery Lesions, and Resistance to Intravenous Immunoglobulin in Kawasaki Disease: An Umbrella Review of Meta-Analyses. Pediatr Cardiol. Published online July . 9 10.1007/s00246-024-03563-0 (2024). Lindquist, M. E. & Hicar, M. D. B Cells and Antibodies in Kawasaki Disease. Int. J. Mol. Sci. 20 (8), 1834. 10.3390/ijms20081834 (2019). Published 2019 Apr 13. Huang, X. B., Zhao, S., Liu, Z. Y., Xu, Y. Y. & Deng, F. Serum amyloid A as a biomarker for immunoglobulin resistance in Kawasaki disease. Ann. Med. 55 (2), 2264315. 10.1080/07853890.2023.2264315 (2023). Liu, X. et al. Predictive role of sampling-time specific prognostic nutritional index cut-off values for intravenous immunoglobulin resistance and cardiovascular complications in Kawasaki disease. Int. Immunopharmacol. 110 , 108986. 10.1016/j.intimp.2022.108986 (2022). Erdogan, A., Can, F. E. & Gönüllü, H. Evaluation of the prognostic role of NLR, LMR, PLR, and LCR ratio in COVID-19 patients. J. Med. Virol. 93 (9), 5555–5559. 10.1002/jmv.27097 (2021). Yamamoto, T., Kawada, K. & Obama, K. Inflammation-Related Biomarkers for the Prediction of Prognosis in Colorectal Cancer Patients. Int J Mol Sci. ;22(15):8002. Published 2021 Jul 27. (2021). 10.3390/ijms22158002 Zhang, J. N. et al. Lymphocyte-C-reactive protein ratio can differentiate disease severity of COVID-19 patients and serve as an assistant screening tool for hospital and ICU admission. Front. Immunol. 13 , 957407. 10.3389/fimmu.2022.957407 (2022). Published 2022 Sep 23. Lu, L. H. et al. Lymphocyte-C-reactive protein ratio as a novel prognostic index in intrahepatic cholangiocarcinoma: A multicentre cohort study. Liver Int. 41 (2), 378–387. 10.1111/liv.14567 (2021). Li, X. et al. Lymphocyte-to-C-Reactive Protein Ratio as an Early Sepsis Biomarker for Neonates with Suspected Sepsis. Mediators Inflamm. ;2023:9077787. Published 2023 May 8. (2023). 10.1155/2023/9077787 Newburger, J. W. et al. Diagnosis, treatment, and long-term management of Kawasaki disease: a statement for health professionals from the Committee on Rheumatic Fever, Endocarditis, and Kawasaki Disease, Council on Cardiovascular Disease in the Young, American Heart Association. Pediatrics 114 , 1708–1733 (2004). Bayers, S. et al. Kawasaki disease: part II. Complications and treatment. Journal of the; 69: 513.e1–513.e1–8; quiz 521–2.Bayers AS. Kawasaki disease: part II. Complications and treatment. Journal of the American Academy of Dermatology. 2013; 69: 513.e1–513.e1–8; quiz 521–2. (2013). Kobayashi, T. et al. Prediction of intravenous immunoglobulin unresponsiveness in patients with Kawasaki disease. Circulation 113 (22), 2606–2612. 10.1161/CIRCULATIONAHA.105.592865 (2006). Egami, K. et al. Prediction of resistance to intravenous immunoglobulin treatment in patients with Kawasaki disease. J. Pediatr. 149 (2), 237–240. 10.1016/j.jpeds.2006.03.050 (2006). Sano, T. et al. Prediction of non-responsiveness to standard high-dose gamma-globulin therapy in patients with acute Kawasaki disease before starting initial treatment. Eur. J. Pediatr. 166 (2), 131–137. 10.1007/s00431-006-0223-z (2007). Lin, M. T. et al. Risk factors and derived formosa score for intravenous immunoglobulin unresponsiveness in Taiwanese children with Kawasaki disease. J. Formos. Med. Assoc. 115 (5), 350–355. 10.1016/j.jfma.2015.03.012 (2016). Yang, S., Song, R., Zhang, J., Li, X. & Li, C. Predictive tool for intravenous immunoglobulin resistance of Kawasaki disease in Beijing. Arch. Dis. Child. 104 (3), 262–267. 10.1136/archdischild-2017-314512 (2019). Tang, Y. et al. Prediction of intravenous immunoglobulin resistance in Kawasaki disease in an East China population. Clin. Rheumatol. 35 (11), 2771–2776. 10.1007/s10067-016-3370-2 (2016). Iseda, N. et al. Lymphocyte-to-C-reactive protein ratio as a prognostic factor for hepatocellular carcinoma. Int. J. Clin. Oncol. 26 (10), 1890–1900. 10.1007/s10147-021-01985-x (2021). Ullah, W. et al. Lymphocyte-to-C-Reactive Protein Ratio: A Novel Predictor of Adverse Outcomes in COVID-19. J. Clin. Med. Res. 12 (7), 415–422. 10.14740/jocmr4227 (2020). Zhang, J. N. et al. Lymphocyte-C-reactive protein ratio can differentiate disease severity of COVID-19 patients and serve as an assistant screening tool for hospital and ICU admission. Front. Immunol. 13 , 957407. 10.3389/fimmu.2022.957407 (2022). Published 2022 Sep 23. Liu, X. et al. Predictive Value of the Systemic Immune-Inflammation Index for Intravenous Immunoglobulin Resistance and Cardiovascular Complications in Kawasaki Disease. Front. Cardiovasc. Med. 8 , 711007. 10.3389/fcvm.2021.711007 (2021). Published 2021 Aug 24. Hotchkiss, R. S. et al. Accelerated lymphocyte death in sepsis occurs by both the death receptor and mitochondrial pathways. J. Immunol. 174 (8), 5110–5118. 10.4049/jimmunol.174.8.5110 (2005). Lang, J. D. & Matute-Bello, G. Lymphocytes, apoptosis and sepsis: making the jump from mice to humans. Crit. Care . 13 (1), 109. 10.1186/cc7144 (2009). Chu, C. M. et al. Increased Death of Peripheral Blood Mononuclear Cells after TLR4 Inhibition in Sepsis Is Not via TNF/TNF Receptor-Mediated Apoptotic Pathway. Mediators Inflamm. 2021 , 2255017. 10.1155/2021/2255017 (2021). Published 2021 Oct 25. Póvoa, P. et al. C-reactive protein as an indicator of sepsis. Intensive Care Med. 24 (10), 1052–1056. 10.1007/s001340050715 (1998). Wang, H. E. et al. High-sensitivity C-reactive protein and risk of sepsis. PLoS One . 8 (7), e69232. 10.1371/journal.pone.0069232 (2013). Published 2013 Jul 23. Tian, T., Wei, B. & Wang, J. Study of C-reactive protein, procalcitonin, and immunocyte ratios in 194 patients with sepsis. BMC Emerg. Med. 21 (1), 81. 10.1186/s12873-021-00477-5 (2021). Published 2021 Jul 7. Additional Declarations No competing interests reported. Supplementary Files Supplementarytable1.docx Supplementary table 1. Prediction of IVIG resistance in this sample by several risk scoring systems Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5840515","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":405793468,"identity":"65792390-1097-4f6c-85e2-4a9f91232b10","order_by":0,"name":"Yaru Cui","email":"","orcid":"","institution":"Sichuan University Chengdu","correspondingAuthor":false,"prefix":"","firstName":"Yaru","middleName":"","lastName":"Cui","suffix":""},{"id":405793469,"identity":"5cdcd1f8-4d1e-4c11-9704-49e9dbb021ad","order_by":1,"name":"Pingting Ye","email":"","orcid":"","institution":"Sichuan University Chengdu","correspondingAuthor":false,"prefix":"","firstName":"Pingting","middleName":"","lastName":"Ye","suffix":""},{"id":405793470,"identity":"f0f4ba59-e462-473f-b744-1bbc4c041bbd","order_by":2,"name":"Hongyu Duan","email":"","orcid":"","institution":"Sichuan University Chengdu","correspondingAuthor":false,"prefix":"","firstName":"Hongyu","middleName":"","lastName":"Duan","suffix":""},{"id":405793471,"identity":"144a8ddf-404e-4d72-9a6f-c5b1b55b2e31","order_by":3,"name":"Xiaoliang Liu","email":"","orcid":"","institution":"Sichuan University Chengdu","correspondingAuthor":false,"prefix":"","firstName":"Xiaoliang","middleName":"","lastName":"Liu","suffix":""},{"id":405793473,"identity":"b1baeb6d-122e-4ef7-8635-95c284ddeab9","order_by":4,"name":"Kaiyu Zhou","email":"","orcid":"","institution":"Sichuan University Chengdu","correspondingAuthor":false,"prefix":"","firstName":"Kaiyu","middleName":"","lastName":"Zhou","suffix":""},{"id":405793475,"identity":"89550413-9b8a-4c31-93fc-5b6739591c62","order_by":5,"name":"Yimin Hua","email":"","orcid":"","institution":"Sichuan University Chengdu","correspondingAuthor":false,"prefix":"","firstName":"Yimin","middleName":"","lastName":"Hua","suffix":""},{"id":405793477,"identity":"c6d3acba-76f5-4239-a922-ee39a2479e6f","order_by":6,"name":"Fan Ma","email":"","orcid":"","institution":"Sichuan University Chengdu","correspondingAuthor":false,"prefix":"","firstName":"Fan","middleName":"","lastName":"Ma","suffix":""},{"id":405793480,"identity":"fa7b7cdc-4fcc-486e-829e-cad61d6291fc","order_by":7,"name":"Jinhui Li","email":"","orcid":"","institution":"Sichuan University Chengdu","correspondingAuthor":false,"prefix":"","firstName":"Jinhui","middleName":"","lastName":"Li","suffix":""},{"id":405793481,"identity":"04504555-bd96-4588-a2e4-b7167ba3df86","order_by":8,"name":"Shuran Shao","email":"","orcid":"","institution":"Sichuan University Chengdu","correspondingAuthor":false,"prefix":"","firstName":"Shuran","middleName":"","lastName":"Shao","suffix":""},{"id":405793483,"identity":"5b8f07dd-31c2-467e-8827-9a06dc93fa97","order_by":9,"name":"Chuan wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7ElEQVRIiWNgGAWjYLACxgYgwcx+4MCHCgk5eeK1sPMkPpxxxsLYsIFoLfwMxsa8bRWJDAcIqDY4fvbwi587DsubMzOkSc6cJ5HA2MD88NENfFrO5KVZ9p45bLizmfGYxMdtEnnsDGzGxjl4tJgdyDEzZmw7zLjhMMiWbRLFjA08bNJ4tZx/A9ZiD9RiJs07RyKx4QAhLTdyjB8DtSQCtQC930CEFvsbb8wYe9vSkzccBgXyMQljw2YCfpHszzH+8LPN2nbD+ePAqKypk5Nnb374GJ8WIGCTQOUz41cOVvKBsJpRMApGwSgY0QAAVzxRzhgdJvgAAAAASUVORK5CYII=","orcid":"","institution":"Sichuan University Chengdu","correspondingAuthor":true,"prefix":"","firstName":"Chuan","middleName":"","lastName":"wang","suffix":""}],"badges":[],"createdAt":"2025-01-16 09:23:31","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5840515/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5840515/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":74568048,"identity":"600452a6-4788-434f-af33-1695cf5ee651","added_by":"auto","created_at":"2025-01-23 13:56:25","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":264552,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart\u003c/p\u003e\n\u003cp\u003eInitially, 1849 KD patients were included. Patients who had received IVIG treatment at other medical institutions (n = 119) or who did not receive IVIG within 10 days of fever onset (n = 34) were excluded. Fifty-three patients were excluded due to starting IVIG treatment before blood sample collection. Additionally, 36 patients with incomplete laboratory data or lacking follow-up results were excluded. Ultimately, 1,607 KD patients were included in the study, comprising 1406 initial responded to IVIG treatment and 201 initial resistence to IVIG treatment. Among the 201 patients with initial IVIG resistance, 88 patients were non-responders to repeated IVIG treatment and were treated with pulse methylprednisolone\u003c/p\u003e","description":"","filename":"OnlineFigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-5840515/v1/171a941314984fb3c99c2032.png"},{"id":74568046,"identity":"1408259d-c82e-424d-bf35-00c631b59193","added_by":"auto","created_at":"2025-01-23 13:56:25","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":303900,"visible":true,"origin":"","legend":"\u003cp\u003eThe receiver-operating characteristic (ROC) curve for LCR, LYMPH and CRP in predicting initial(A) and repeated(B) IVIG resistance.\u003c/p\u003e","description":"","filename":"OnlineFigure21.png","url":"https://assets-eu.researchsquare.com/files/rs-5840515/v1/a1348d1b0a3e96dc698a13e1.png"},{"id":79272464,"identity":"e913b2ef-9985-4c12-b8c5-995aa5d2ebec","added_by":"auto","created_at":"2025-03-26 11:32:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1702178,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5840515/v1/110b7cf6-6765-4e04-8802-f3247f21a140.pdf"},{"id":74568568,"identity":"d02f3631-5f9d-4a74-89fb-8ae854750253","added_by":"auto","created_at":"2025-01-23 14:04:25","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":16066,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary table 1. \u003c/strong\u003ePrediction of IVIG resistance in this sample by several risk scoring systems\u003c/p\u003e","description":"","filename":"Supplementarytable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-5840515/v1/e92eb2d4c93dd147ea3b7368.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Predictive value of lymphocyte-to-C-reactive protein ratio for predicting initial and repeated intravenous immunoglobulin resistance in a large cohort of Kawasaki disease: a prospective cohort study","fulltext":[{"header":"Background","content":"\u003cp\u003eKawasaki disease (KD) is an acute, systemic vasculitis affecting small to medium-sized vessels, primarily in children, with coronary artery lesions (CALs) being the most severe complication[1]. Intravenous immunoglobulin (IVIG) is the primary treatment for KD, however, over 10% of patients are resistant to both first and subsequent IVIG therapies, resulting in an elevated risk of developing CALs. Consequently, prompt recognition of initial and repeated IVIG resistance, together with appropriate intervention with steroids or infliximab, might mitigate the occurrence of CALs and decrease the healthcare expenses linked to repeated IVIG treatments[1-3]. However, current biomarkers for predicting initial and repeated IVIG resistance have low levels of evidence, and there is still no reliable biomarker to predict IVIG resistance in KD effectively[4]. This is especially significant for patient groups outside Japan, since risk-scoring methods formulated in Japan have proven non-reproducible in Chinese populations, and efforts to create analogous algorithms have failed.\u003c/p\u003e\n\u003cp\u003eAlthough the exact aetiology of KD remains unclear, the pathogenesis is known to involve immune and inflammatory responses[5]. Lymphocytes, a type of white blood cell, reflect immune system function and have anti-inflammatory properties, helping to stabilize vascular endothelium. Recently, the changed lymphocytes counts in peripheral blood resulting from immunosuppression has been observed in the pathological process of KD[6-7]. In addition, C-reactive protein (CRP) is a recognized acute phase response protein, and higher levels indicate a more severe inflammatory state. Thus, the disparity between elevated CRP levels and decreased lymphocyte counts may suggest that patients are experiencing significant inflammatory responses and a severe clinical progression of KD. Nonetheless, an individual inflammatory parameter may be readily affected by other factors. The combined analysis of inflammatory indicators, including the neutrophil-to-lymphocyte ratio (NLR) and the platelet-to-lymphocyte ratio (PLR), has been recognized as independent risk factors for IVIG resistance and/or coronary artery lesions (CALs); nonetheless, their predictive capabilities remain non-inclusive[4].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLymphocyte-to-C-reactive protein ratio (LCR) is a novel prognostic biomarker and has been proved useful for peri-operative management and post-operative follow-up. Previous studies have shown that LCR can predict the severity and prognosis of diseases with similar pathogenesis to KD, such as certain kinds of cancers and COVID-19[8-11]. A recent retrospective investigation indicated that LCR may serve as a robust biomarker for the prompt identification of sepsis in infants suspected of having the condition[12]. Yet, the possible implications of LCR in predicting IVIG resistance in patients with KD have not been detailed.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThus, this research prospectively examined the predictive capacity of LCR for initial and recurrent IVIG resistance in KD, and assessed the prognostic accuracy of LCR in comparison to the NLR and PLR.\u003c/p\u003e"},{"header":"Patients and methods","content":"\u003cp\u003eThis research prospectively included children diagnosed with KD at the Pediatric Cardiovascular Center of West China Second University Hospital, Sichuan University, from January 2013 to June 2022. KD was diagnosed by two seasoned pediatricians, at least one of whom was a KD specialist, in accordance with the American Heart Association\u0026apos;s diagnostic criteria[13]. The parents of the diagnosed children completed a questionnaire covering personal information, symptom descriptions, and treatment processes. Blood samples were collected from the KD patients before initiating IVIG therapy. The study was approved by the Ethics Committee of Sichuan University (NO. 201712160121). All research was performed in accordance with relevant guidelines/regulations. Informed consent was obtained from all participants and/or their legal guardians.\u003c/p\u003e\n\u003cp\u003eInitially, 1849 KD patients were included. Patients who had undergone IVIG therapy at other medical facilities (n = 119) or who did not get IVIG within 10 days after fever start (n = 34) were excluded. Fifty-three individuals were eliminated for initiating IVIG therapy prior to blood sample collection. Additionally, 36 patients with incomplete laboratory data or lacking follow-up results were excluded. Ultimately, 1,607 KD patients were included in the study, comprising 1406 initial responded to IVIG treatment and 201 initial resistence to IVIG treatment. Among the 201 patients with initial IVIG resistance, 88 patients were non-responders to repeated IVIG treatment and were treated with pulse methylprednisolone (Figure 1, Flowchart). No patients received additional treatments such as infliximab, plasmapheresis, or cytotoxic drugs.\u003c/p\u003e\n\u003cp\u003eAll patients were administered an identical therapy protocol within 10 days of illness start, including high-dose IVIG(2 g/kg as a single infusion) and aspirin (30\u0026ndash;50 mg/kg/day). Following defervescence, aspirin dosage was decreased to 3\u0026ndash;5 mg/kg/day for a duration of 6\u0026ndash;8 weeks. Initial IVIG resistance was characterized by persistent fever (T \u0026gt; 38.0\u0026deg;C) or other clinical signs of Kawasaki Disease persisting for a minimum of 36 hours and a maximum of 7 days after the first and second IVIG administrations (2 g/kg single intravenous infusion)[14]. If fever or clinical symptoms recurred or remained after the second IVIG treatment, it was classified as repeated\u0026nbsp;IVIG resistance, necessitating the addition of intravenous prednisolone (10-30 mg/kg/day for 3 days), followed by oral prednisolone (2 mg/kg/day) for 7 days with slow tapering.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSPSS 27.0 (SPSS Inc. Chicago, IL, USA) processed and analyzed data. Quantitative data was given as \u0026ldquo;the median with the 25th and 75th percentiles\u0026rdquo; and qualitative data as numbers (n) vs percentages (%). After verifying normal distribution and group homogeneity, the Shapiro-Wilk and homogeneity of variance tests were performed. The chi-square test and unpaired Student\u0026apos;s t-test or Mann-Whitney U test evaluated demographics, clinical symptoms, and laboratory data between IVIG response and IVIG resistance groups. Pearson\u0026apos;s examination of statistically distinct laboratory markers with LCR excluded indications with strong association. Multivariate logistic regression analysis identified independent predictors of IVIG resistance for the remaining statistically distinct markers. For the receiver operating characteristic (ROC) curve, the greatest sensitivity and specificity Youden index was used as the cut-off value. Statistical significance was calculated at P\u0026lt;0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eComparison of subjects between groups of initial IVIG-response and IVIG-resistance\u003c/h2\u003e \u003cp\u003eThe baseline statistics of the initial IVIG-response and IVIG-resistance children were comparable. Initial IVIG resistance group was associated with greater rates of rash, edema, oral and pharyngeal mucosa erythema, and cervical lymphadenopathy compared to the response group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). aspartate aminotransferase(AST), alanine aminotransferase(ALT), creatinine, urea nitrogen, total bilirubin (TB), C-reactive protein (CRP), neutrophil-lymphocyte ratio (NLR), and platelet-lymphocyte ratio (PLR) were significantly higher in the initial IVIG-resistance group than in the responsed group, while lymphocyte count (LYMPH), platelet(PLT), albumin(ALB), sodium, potassium, and lymphocyte-CRP ratio (LCR) were significantly lower(Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of clinical data between the groups of initial IVIG-resistant and IVIG-responsive in KD\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIVIG-resistant(n\u0026thinsp;=\u0026thinsp;201)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIVIG-responsive(n\u0026thinsp;=\u0026thinsp;1406)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge(months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.00(1.00-115.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.00(1.00-152.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.274\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e109(54.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e804(57.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.429\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDay of illness before admission, (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5(3\u0026ndash;7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(3\u0026ndash;7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.963\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDay of illness before IVIG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.091\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0-7days, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e188(93.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1328(94.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8-10days, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13(6.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78(5.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinical manifestations\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRash, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e160(79.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e949(67.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\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\u003eBilateral bulbar conjunctive injection, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e186(92.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1287(91.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.631\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEdema \u0026amp; erythema of the extremities, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e128(63.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e767(54.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.017*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eErythema of oral and pharyngeal mucosa, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e191(95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1277(90.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.048*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCervical lymphadenopathy, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105(52.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e586(41.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.004*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncomplete KD, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36(17.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e322(22.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCALs, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32(15.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e176(12.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.291\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLaboratory features\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC count(10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.80(9.70-16.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.30(10.70\u0026ndash;16.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.120\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNEUT(10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.63(6.54\u0026ndash;12.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.91(6.47\u0026ndash;11.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLYMPH(10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.90(1.15\u0026ndash;3.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.97(2.04\u0026ndash;4.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\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\u003eHemoglobin(g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e109.00(102.00-116.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e110.00(103.00-117.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.220\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLT count(10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e306.00(238.00-359.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e336.00(280.00-407.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\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\u003eAST(IU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39.00(26.00-73.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.00(25.50\u0026ndash;49.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.004*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT(IU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54.00(23.50-127.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.00(17.00\u0026ndash;78.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\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\u003eALB(g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.00(32.40\u0026ndash;40.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.85(35.70\u0026ndash;42.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\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\u003eCreatinine(umol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.00(23.00-33.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.00(22.00\u0026ndash;31.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\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\u003eUrea nitrogen(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.91(2.40\u0026ndash;3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.80(2.20\u0026ndash;3.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.008*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTB (umol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.60(5.30-18.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.00(4.10\u0026ndash;8.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\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\u003eSodium(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e134.5(132.15\u0026ndash;136.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e136.70(134.60-138.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\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\u003ePotassium(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.00(3.60\u0026ndash;4.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.17(3.80\u0026ndash;4.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\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(mm/h)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63.00(3.00\u0026ndash;82.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.00(42.00\u0026ndash;81.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.612\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP(mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93.30(62.85\u0026ndash;136.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.00(43.00-107.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\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\u003eLCR(10\u003csup\u003e9\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.02(0.01\u0026ndash;0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.04(0.02\u0026ndash;0.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\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\u003eNLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.87(2.70\u0026ndash;9.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.85(1.75\u0026ndash;5.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\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\u003ePLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e146.82(94.01-238.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e113.43(81.40-168.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eThe data are presented as the median with the 25th and 75th percentiles in square brackets for continuous variables and as the percentage for the categorical variables.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eComparison of subjects between repeated IVIG-response and IVIG-resistance group\u003c/h3\u003e\n\u003cp\u003eChildren in the repeated IVIG-response and IVIG-resistance groups had comparable baseline data as well as comparable clinical presentations. CRP, NLR, and PLR were considerably greater in the IVIG-resistant group than in the IVIG-responsed group, whereas LYMPH, hemoglobin, ALB, and LCR were significantly lower(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\u003eComparison of clinical data between the groups of repeated IVIG-resistant and IVIG-responsive in KD\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIVIG-resistant(n\u0026thinsp;=\u0026thinsp;88)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIVIG-responsive(n\u0026thinsp;=\u0026thinsp;113)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge(months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.50(14.00-52.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.50(16.00-46.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.622\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43(48.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67(59.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.081\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDay of illness before admission, (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5(2\u0026ndash;10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4(2\u0026ndash;10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.204\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDay of illness before IVIG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0-7days, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82(93.18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e108(95.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8-10days, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6(6.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(4.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinical manifestations\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRash, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74(84.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87(76.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.128\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBilateral bulbar conjunctive injection, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86(97.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e105(92.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.461\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEdema \u0026amp; erythema of the extremities, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55(62.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76(67.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.191\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eErythema of oral and pharyngeal mucosa, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87(98.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e109(96.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.487\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCervical lymphadenopathy, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41(46.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65(57.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncomplete KD, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17(19.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19(16.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.437\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCALs, n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14(15.9%0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18(15.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.713\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLaboratory features\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC count(10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.55(9.23\u0026ndash;16.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.3(10.25\u0026ndash;16.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.505\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN(10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.45(6.54\u0026ndash;12.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.69(6.66\u0026ndash;12.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.876\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eL(10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.64(0.87\u0026ndash;2.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.22(1.40\u0026ndash;3.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\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\u003eHemoglobin(g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e107.00(100.00-113.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e112.00(103.00-119.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.018*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLT count(10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e289.50(240.50-341.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e316.00(235.00-364.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.204\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST(IU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39.00(26.50\u0026ndash;66.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.50(25.25-87.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.441\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT(IU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48.00(26.00-96.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.50(21.00-159.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.278\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALB(g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34.20(30.65\u0026ndash;38.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.70(33.85\u0026ndash;40.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\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\u003eCreatinine(umol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.00(24.00\u0026ndash;34.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.50(23.00\u0026ndash;33.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.555\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrea nitrogen(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.90(2.30\u0026ndash;3.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.00(2.40\u0026ndash;3.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.462\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTB (umol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.80(4.65-29.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.80(6.03\u0026ndash;16.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.519\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSodium(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e134.00(132.00-136.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e134.80(132.23\u0026ndash;137.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.215\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePotassium(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.00(3.51\u0026ndash;4.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.05(3.63\u0026ndash;4.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.371\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eESR(mm/h)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61.00(40.25-80.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.00(43.50\u0026ndash;87.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.501\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP(mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96.95(69.50-151.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93.30(59.50-123.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.034*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLCR(10\u003csup\u003e9\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.02(0.01\u0026ndash;0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.03(0.01\u0026ndash;0.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\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\u003eNLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.25(2.77\u0026ndash;12.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.89(2.68\u0026ndash;7.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.03*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e181.13(95.34-331.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e137.08(91.81-209.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.08*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eThe data are presented as the median with the 25th and 75th percentiles in square brackets for continuous variables and as the percentage for the categorical variables.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eAbbreviations: IVIG, intravenous immunoglobulin; KD, Kawasaki Disease; CALs, coronary artery lesions; WBC, white blood cell; NEUT: neutrophil count; LYMPH: lymphocyte count; PLT, platelet; AST, aspartate aminotransferase; ALT, alanine aminotransferase; ALB, Albumin; TB, total bilirubin; ESR, erythrocyte sedimentation rate; CRP, C-reactive protein; NLR, neutrophil-lymphocyte ratio; LCR, lymphocyte-CRP ratio; PLR, platelet-lymphocyte ratio\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003e\u003cb\u003e#\u003c/b\u003e\u003c/sup\u003eVariables between two groups were compared by the Mann\u0026ndash;Whitney U test due to abnormal data distribution.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e* Statistically significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eMultivariate logistic regression analysis\u003c/h3\u003e\n\u003cp\u003ePearson's analysis was performed to analyze initial and repeated IVIG resistance using LCR and other statistically distinct laboratory single-factor variables (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). We used multivariate logistic regression after removing factors with substantial correlations. LCR was shown to be an independent risk factor for both first IVIG resistance (OR: 3804.00, 95%CI (64.60-224002.83), p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and recurring IVIG resistance (OR: 9549037.28, 95%CI (87.41-1043208403740.78), p\u0026thinsp;=\u0026thinsp;0.004) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\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\u003eClinical correlation between univariate factors and LCR in the KD subjects\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"24\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c18\" colnum=\"18\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c19\" colnum=\"19\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c20\" colnum=\"20\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c21\" colnum=\"21\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c22\" colnum=\"22\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c23\" colnum=\"23\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c24\" colnum=\"24\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eLYMPH(10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003ePLT(10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eALT(IU/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c13\" namest=\"c11\"\u003e \u003cp\u003eALB(g/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c16\" namest=\"c14\"\u003e \u003cp\u003eTB (umol/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c19\" namest=\"c17\"\u003e \u003cp\u003eNa+(mmol/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c22\" namest=\"c20\"\u003e \u003cp\u003eK+(mmol/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c24\" namest=\"c23\"\u003e \u003cp\u003eCRP(g/L)\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\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\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\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c17\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c20\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c22\" namest=\"c21\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c23\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c24\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInitial-LCR(10\u003csup\u003e9\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e0.006*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-0.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003e0.005*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e \u003cp\u003e0.002*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c22\" namest=\"c21\"\u003e \u003cp\u003e0.011*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e-0.247\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\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\u003eRepeated-LCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eLYMPH(10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c12\" namest=\"c7\"\u003e \u003cp\u003eHGB(g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c18\" namest=\"c13\"\u003e \u003cp\u003eALB(g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c24\" namest=\"c19\"\u003e \u003cp\u003eCRP(g/L)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRepeated-LCR(10\u003csup\u003e9\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c12\" namest=\"c10\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c15\" namest=\"c13\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c18\" namest=\"c16\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c21\" namest=\"c19\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c24\" namest=\"c22\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e0.514\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003e0.218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c12\" namest=\"c10\"\u003e \u003cp\u003e0.002*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c15\" namest=\"c13\"\u003e \u003cp\u003e0.302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c18\" namest=\"c16\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c21\" namest=\"c19\"\u003e \u003cp\u003e-0.493\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c24\" namest=\"c22\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"24\"\u003eAbbreviations: LYMPH: lymphocyte count; PLT, platelet; ALT, alanine aminotransferase; ALB, Albumin; TB, total bilirubin; Na+, sodium; K+, Potassium; CRP, C-reactive protein; NLR, neutrophil-lymphocyte ratio; HGB, hemoglobin.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"24\"\u003e*Statistically significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\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\u003eA multivariate logistic regression model for initial and repeated intravenous immunoglobulin (IVIG)-resistance in Kawasaki Disease.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eInitial Variates\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWalds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLCR(10\u003csup\u003e9\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.717\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\u003e3804.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e64.60-224002.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrea nitrogen(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.97\u0026ndash;1.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine(umol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.569\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.84\u0026ndash;1.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST(IU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.99-1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRash\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.504\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.012*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.41\u0026ndash;0.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEdema \u0026amp; erythema of the extremities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.223\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.735\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.58\u0026ndash;1.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eErythema of oral and pharyngeal mucosa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.416\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.346\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.449\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.229\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.34\u0026ndash;1.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCervical lymphadenopathy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.258\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.545\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.56\u0026ndash;1.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRepeated Variates\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLCR(10\u003csup\u003e9\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.246\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.007*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9549037.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e87.41-1043208403740.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eAbbreviations: IVIG, intravenous immunoglobulin; LCR, lymphocyte-CRP ratio; AST, aspartate aminotransferase; OR, odds ratio; CI, confidence ratio\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e*Statistically significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePredictive value of LCR for initial IVIG-resistance and repeated IVIG-resistance in KD patients\u003c/h2\u003e \u003cp\u003eFor initial IVIG resistance prediction, LCR\u0026thinsp;\u0026le;\u0026thinsp;0.042 had an AUC of 0.694 [OR(95%CI): 0.33(0.24\u0026ndash;0.46)], with a corresponding sensitivity, specificity, PPV, NPV of 74.1%, 51.3%, 17.9%, 93.3%, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). For repeated IVIG resistance prediction, LCR\u0026thinsp;\u0026le;\u0026thinsp;0.025 had an AUC of 0.636 [OR(95%CI): 0.41(0.23\u0026ndash;0.73)], with a corresponding sensitivity, specificity, PPV, NPV of 65.9%, 55.8%, 53.7%, 67.7%, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe validity of LCR, LYMPH, CRP NLR and PLR cut-off values in predicting initial and repeated IVIG resistance for the total group.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInitial IVIG resistance\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiagnostic test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eGold standard\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSen\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSpe\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePPV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNPV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eDiagnostic accuracy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eOR(95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"9\" rowspan=\"10\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;1607\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLCR(10\u003csup\u003e9\u003c/sup\u003e)\u0026thinsp;\u0026le;\u0026thinsp;0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003epositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e721\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e685\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e74.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e51.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e17.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e93.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.694\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.33(0.24\u0026ndash;0.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003enegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e149\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLYMPH(10\u003csup\u003e9\u003c/sup\u003e/L)\u0026thinsp;\u0026le;\u0026thinsp;1.932\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003epositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e319\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e51.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e77.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e24.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e91.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.678\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.27(0.20\u0026ndash;0.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003enegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e104\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCRP(mg/L)\u0026thinsp;\u0026ge;\u0026thinsp;59.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003epositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e839\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e80.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e40.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e16.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e93.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.636\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.37(0.26\u0026ndash;0.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003enegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e161\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNLR\u0026thinsp;\u0026ge;\u0026thinsp;5.858\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003epositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e282\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e45.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e79.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e24.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e91.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.666\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.30(0.22\u0026ndash;0.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003enegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePLR\u0026thinsp;\u0026ge;\u0026thinsp;186.407\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003epositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e38.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e80.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e22.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e90.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.613\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.38(0.28\u0026ndash;0.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003enegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRepeated IVIG resistance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiagnostic test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eGold standard\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSpe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePPV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNPV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eDiagnostic accuracy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eOR(95%CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"9\" rowspan=\"10\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLCR(10\u003csup\u003e9\u003c/sup\u003e)\u0026thinsp;\u0026le;\u0026thinsp;0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003epositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e65.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e55.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e53.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e67.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.636\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.41(0.23\u0026ndash;0.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.002*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003enegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLYMPH(10\u003csup\u003e9\u003c/sup\u003e/L)\u0026thinsp;\u0026le;\u0026thinsp;1.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003epositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e36.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e89.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e72.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e64.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.635\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.21(0.10\u0026ndash;0.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003enegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCRP(mg/L)\u0026thinsp;\u0026ge;\u0026thinsp;116.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003epositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e43.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e73.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e55.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e62.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.587\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.48(0.26\u0026ndash;0.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.013*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003enegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNLR\u0026thinsp;\u0026ge;\u0026thinsp;7.414\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003epositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e50.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e76.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e62.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e66.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.621\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.31(0.17\u0026ndash;0.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003enegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePLR\u0026thinsp;\u0026ge;\u0026thinsp;245.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003epositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e37.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e85.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e67.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e63.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.610\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.28(0.14\u0026ndash;0.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003enegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003eAbbreviations: IVIG, intravenous immunoglobulin; Sen: sensitivity; Spe: specificity; PPV: positive predictive value; NPV: negative predictive value; OR, odds ratio; CI, confidence ratio; LCR, lymphocyte-CRP ratio; LYMPH: lymphocyte count; CRP, C-reactive protein; NLR, neutrophil-lymphocyte ratio; PLR, platelet-lymphocyte ratio\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003e*Statistically significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\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":"Discussion","content":"\u003cp\u003ePredicting resistance to IVIG is a major problem in Kawasaki disease. This research prospectively examined the predictive value of LCR for initial IVIG resistance in KD and compared it with the predictive values of NLR and PLR using the biggest sample size to date. Most significantly, the best of our knowledge, this was the first research that to \u0026nbsp; established the validity of LCR in repeated IVIG resistance prediction. LCR was considerably reduced in both the initial and repeated IVIG-resistant groups compared to responders. In addition, we also found that the predictive validities of several risk score systems[15-20](Supplementary table 1), our merging indicators of NLR as well as PLR(Table 5) did not have a much greater predictive ability than LCR. Considering the LCR are routinely detectable indicators that can be obtained without additional cost, it thus might provide some references for clinical management.\u003c/p\u003e\n\u003cp\u003eLCR serves to highlight a relative lymphopenia compared to normal and raised CRP levels. LCR was recently shown to be a viable predictor of postoperative morbidity, prognosis, and recurrence in a variety of cancer types, COVID-19 associated with inflammation, and probable sepsis. Iseda et al. discovered that preoperative LCR serves as a novel and easy prognostic indicator for patients with hepatocellular carcinoma, suggested that LC was correlated with the immunological state of the tumor microenvironment[21]. In addition, Ullah et al found that LCR was associated with impending clinical deterioration and the need for invasive mechanical ventilation for patients with severe COVID-19[22]. Yang et al. indicated that LCR had more efficacy compared to CRP or lymphocytes alone in evaluating severe COVID-19[23]. Moreover, Li et al. identified a significant negative correlation between LCR and procalcitonin, with a diminished LCR serving as an independent marker for the detection of sepsis and its severe manifestations[12]. The above findings suggest that the combination of LCR could be a sensitive biomarker during the acute inflammatory phase. However, the correlation between LCR and KD in forecasting IVIG resistance has been little explored in existing literature.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLymphocytes are a kind of white blood cells primarily generated by lymphoid organs. These cells combat bacterial and viral infections in the body, thereby holding crucial prognostic value in the immune response to infections. It is postulated that KD pathogens associated with extensive inflammation lead to immunological dysregulation and apoptotic depletion of lymphocytes. This mechanism may further provoke a state of immunosuppression, hence increasing host vulnerability to invading infections[25-27].\u0026nbsp;Moreover, as a systemic inflammatory mediator, CRP is an evolutionarily conserved innate immune polymer protein, recognized as a significant biomarker for predicting disease severity and used in several predictive models[28-30]. Therefore, the lower lymphopenia and higher CRP level, a quickly, inexpensively, and non-invasively biomarker, might be more accurately and sensitively for predicting IVIG resistance since the more severity of inflammation of these children they are and an earlier treatment with hormones, infliximab or plasmapheresis may be attempted to use to minimize the occurrence of CALs.\u003c/p\u003e\n\u003cp\u003eTherefore, during this research, the association of LCR with initial and repeated IVIG resistant children were both studied. LCR was identified as an independent predictor for initial and recurrent IVIG-resistant KD in children, and we firstly discovered that repeated IVIG nonresponders had a significantly reduced LCR than responders. A comparatively greater sensitivity of 74.1% and 65.9% was obtained for initial and repeated nonresponders, respectively, with cutoff values of 0.042 and 0.025. Although we were unable to identify all non-responders to initial and repeated IVIG using LCR calculation, these data may enhance the added knowledge on predicting resistance to initial and repeated IVIG and provide references for therapeutic care. In addition, we also found that the combined indicators such as NLR and PLR were not satisfied for simultaneously predicting initial and repeated IVIG resistance in our population. The asynchronous peak in neutrophils, platelets, and lymphocytes during the acute phase of Kawasaki Disease (KD), together with the earlier elevation of C-reactive protein (CRP) compared to neutrophilia in more severe cases of KD, may be the underlying cause[22, 24]. Moreover, several risk scoring systems, such as Kobayashi[15], Egami[16], Sano[17], Ming[18], Yang[19], and Tang[20], seemed to be less optimal and clinically relevant in comparison to ours due to their more intricate calculations and indications (Supplementary table 1). The disparities in starting medication, the definition of IVIG resistance, patient inclusion criteria, genetic backgrounds, and the uneven timing of regular blood tests between their research and ours likely account for the divergent results.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis work should be considered in the context of several possible limitations. Since our hospital is the biggest Children Medical Center in Southwest China, the fact that this research was conducted in a single institution may result in some selection bias in the admission of more serious patients. Secondly, the current investigation was prospective cohort research with stringent inclusion and exclusion criteria. The results of our investigation were only relevant to KD patients who received standardized IVIG therapy within 10 days of fever start. Notwithstanding the aforementioned limitations, this research is the inaugural investigation to ascertain the prognostic significance of LCR for both initial and repeated IVIG resistance, using a substantial patient cohort and a prospective methodology. LCR was considerably lower in IVIG nonresponders; nevertheless, it may only function as a supplementary laboratory marker for predicting both initial and recurrent IVIG resistance in KD. Considering the uncertain etiology of KD, we propose that a predictive model including alternative specific indications, rather than only clinical and routine laboratory characteristics, may provide superior results.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, this study demonstrated that LCR is an independent risk factor for predicting initial and repeat IVIG resistance in KD. Considering the convenient and cost-effectively indicator it is, LCR may be a complementary laboratory marker for predicting IVIG resistance to guide clinical management.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/strong\u003eThe study was approved by the University Ethics Committee on Human Subjects at Sichuan University. All research was performed in accordance with relevant guidelines/regulations. Informed consent was obtained from all participants and/or their legal guardians.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eWritten consent obtained.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material:\u0026nbsp;\u003c/strong\u003eData is provided within the manuscript or supplementary information files.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This work was supported by Science-TechnologySupport Plan Proiects in Sichuan Province (2024YFFK0272; 2024NSFSC1711; 2024YFFK0078). National Natural Science Foundation of China (No.82370236; No.82070324) and National Key Research and Development Program of China (No.2023YFC2706402; No.2022YFC2703902).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributor Statement:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCYR and YPT drafted the manuscript, contributed to the data collection, interpreted the statistical analysis and approved the final manuscript as submitted. DHY and LXL contributed to the study design and approved the final manuscript as submitted. MF provided Table1 and Table2, contributed to the data collection, study design and as well as approved the final manuscript as submitted. LJH provided Table3 ,Table4, Table5 and Table6 contributed to the data collection and approved the final manuscript as submitted. ZKY and HYM provided major treatment on these patients while admitted, contributed to the study design, approved financial support and as well as approved the final manuscript as submitted. WC and SSR conceived conception and designed the study, contributed to the data collection and approved the final manuscript as submitted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e We are grateful to the patients and families for their contributions to this work.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMcCrindle, B. W. et al. \u003cem\u003eDiagnosis, treatment, and long-term management of kawasaki disease\u003c/em\u003e (a scientific statement for health professionals from the American Heart Association, 2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKobayashi, T. et al. Efficacy of immunoglobulin plus prednisolone for prevention of coronary artery abnormalities in severe Kawasaki disease (RAISE study): a randomised, open-label, blinded-endpoints trial. \u003cem\u003eLancet\u003c/em\u003e \u003cb\u003e379\u003c/b\u003e (9826), 1613\u0026ndash;1620 (2012).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePilania, R. K., Jindal, A. K., Guleria, S. \u0026amp; Singh, S. An update on treatment of Kawasaki disease, Curr. \u003cem\u003eTreat. Options Rheumatol.\u003c/em\u003e \u003cb\u003e5\u003c/b\u003e (1), 36\u0026ndash;55 (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim, T. H. et al. Biomarkers and Related Factors for the Diagnosis, Risk of Coronary Artery Lesions, and Resistance to Intravenous Immunoglobulin in Kawasaki Disease: An Umbrella Review of Meta-Analyses. Pediatr Cardiol. \u003cem\u003ePublished online July\u003c/em\u003e. \u003cb\u003e9\u003c/b\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00246-024-03563-0\u003c/span\u003e\u003cspan address=\"10.1007/s00246-024-03563-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLindquist, M. E. \u0026amp; Hicar, M. D. B Cells and Antibodies in Kawasaki Disease. \u003cem\u003eInt. J. Mol. Sci.\u003c/em\u003e \u003cb\u003e20\u003c/b\u003e (8), 1834. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijms20081834\u003c/span\u003e\u003cspan address=\"10.3390/ijms20081834\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019). Published 2019 Apr 13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuang, X. B., Zhao, S., Liu, Z. Y., Xu, Y. Y. \u0026amp; Deng, F. Serum amyloid A as a biomarker for immunoglobulin resistance in Kawasaki disease. \u003cem\u003eAnn. Med.\u003c/em\u003e \u003cb\u003e55\u003c/b\u003e (2), 2264315. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/07853890.2023.2264315\u003c/span\u003e\u003cspan address=\"10.1080/07853890.2023.2264315\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu, X. et al. Predictive role of sampling-time specific prognostic nutritional index cut-off values for intravenous immunoglobulin resistance and cardiovascular complications in Kawasaki disease. \u003cem\u003eInt. Immunopharmacol.\u003c/em\u003e \u003cb\u003e110\u003c/b\u003e, 108986. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.intimp.2022.108986\u003c/span\u003e\u003cspan address=\"10.1016/j.intimp.2022.108986\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eErdogan, A., Can, F. E. \u0026amp; G\u0026ouml;n\u0026uuml;ll\u0026uuml;, H. Evaluation of the prognostic role of NLR, LMR, PLR, and LCR ratio in COVID-19 patients. \u003cem\u003eJ. Med. Virol.\u003c/em\u003e \u003cb\u003e93\u003c/b\u003e (9), 5555\u0026ndash;5559. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/jmv.27097\u003c/span\u003e\u003cspan address=\"10.1002/jmv.27097\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYamamoto, T., Kawada, K. \u0026amp; Obama, K. Inflammation-Related Biomarkers for the Prediction of Prognosis in Colorectal Cancer Patients. Int J Mol Sci. ;22(15):8002. Published 2021 Jul 27. (2021). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijms22158002\u003c/span\u003e\u003cspan address=\"10.3390/ijms22158002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang, J. N. et al. Lymphocyte-C-reactive protein ratio can differentiate disease severity of COVID-19 patients and serve as an assistant screening tool for hospital and ICU admission. \u003cem\u003eFront. Immunol.\u003c/em\u003e \u003cb\u003e13\u003c/b\u003e, 957407. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fimmu.2022.957407\u003c/span\u003e\u003cspan address=\"10.3389/fimmu.2022.957407\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022). Published 2022 Sep 23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLu, L. H. et al. Lymphocyte-C-reactive protein ratio as a novel prognostic index in intrahepatic cholangiocarcinoma: A multicentre cohort study. \u003cem\u003eLiver Int.\u003c/em\u003e \u003cb\u003e41\u003c/b\u003e (2), 378\u0026ndash;387. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/liv.14567\u003c/span\u003e\u003cspan address=\"10.1111/liv.14567\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi, X. et al. Lymphocyte-to-C-Reactive Protein Ratio as an Early Sepsis Biomarker for Neonates with Suspected Sepsis. Mediators Inflamm. ;2023:9077787. Published 2023 May 8. (2023). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1155/2023/9077787\u003c/span\u003e\u003cspan address=\"10.1155/2023/9077787\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNewburger, J. W. et al. Diagnosis, treatment, and long-term management of Kawasaki disease: a statement for health professionals from the Committee on Rheumatic Fever, Endocarditis, and Kawasaki Disease, Council on Cardiovascular Disease in the Young, American Heart Association. \u003cem\u003ePediatrics\u003c/em\u003e \u003cb\u003e114\u003c/b\u003e, 1708\u0026ndash;1733 (2004).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBayers, S. et al. Kawasaki disease: part II. Complications and treatment. Journal of the; 69: 513.e1\u0026ndash;513.e1\u0026ndash;8; quiz 521\u0026ndash;2.Bayers AS. Kawasaki disease: part II. Complications and treatment. Journal of the American Academy of Dermatology. 2013; 69: 513.e1\u0026ndash;513.e1\u0026ndash;8; quiz 521\u0026ndash;2. (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKobayashi, T. et al. Prediction of intravenous immunoglobulin unresponsiveness in patients with Kawasaki disease. \u003cem\u003eCirculation\u003c/em\u003e \u003cb\u003e113\u003c/b\u003e (22), 2606\u0026ndash;2612. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1161/CIRCULATIONAHA.105.592865\u003c/span\u003e\u003cspan address=\"10.1161/CIRCULATIONAHA.105.592865\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2006).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEgami, K. et al. Prediction of resistance to intravenous immunoglobulin treatment in patients with Kawasaki disease. \u003cem\u003eJ. Pediatr.\u003c/em\u003e \u003cb\u003e149\u003c/b\u003e (2), 237\u0026ndash;240. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jpeds.2006.03.050\u003c/span\u003e\u003cspan address=\"10.1016/j.jpeds.2006.03.050\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2006).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSano, T. et al. Prediction of non-responsiveness to standard high-dose gamma-globulin therapy in patients with acute Kawasaki disease before starting initial treatment. \u003cem\u003eEur. J. Pediatr.\u003c/em\u003e \u003cb\u003e166\u003c/b\u003e (2), 131\u0026ndash;137. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00431-006-0223-z\u003c/span\u003e\u003cspan address=\"10.1007/s00431-006-0223-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2007).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLin, M. T. et al. Risk factors and derived formosa score for intravenous immunoglobulin unresponsiveness in Taiwanese children with Kawasaki disease. \u003cem\u003eJ. Formos. Med. Assoc.\u003c/em\u003e \u003cb\u003e115\u003c/b\u003e (5), 350\u0026ndash;355. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jfma.2015.03.012\u003c/span\u003e\u003cspan address=\"10.1016/j.jfma.2015.03.012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang, S., Song, R., Zhang, J., Li, X. \u0026amp; Li, C. Predictive tool for intravenous immunoglobulin resistance of Kawasaki disease in Beijing. \u003cem\u003eArch. Dis. Child.\u003c/em\u003e \u003cb\u003e104\u003c/b\u003e (3), 262\u0026ndash;267. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/archdischild-2017-314512\u003c/span\u003e\u003cspan address=\"10.1136/archdischild-2017-314512\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTang, Y. et al. Prediction of intravenous immunoglobulin resistance in Kawasaki disease in an East China population. \u003cem\u003eClin. Rheumatol.\u003c/em\u003e \u003cb\u003e35\u003c/b\u003e (11), 2771\u0026ndash;2776. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10067-016-3370-2\u003c/span\u003e\u003cspan address=\"10.1007/s10067-016-3370-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIseda, N. et al. Lymphocyte-to-C-reactive protein ratio as a prognostic factor for hepatocellular carcinoma. \u003cem\u003eInt. J. Clin. Oncol.\u003c/em\u003e \u003cb\u003e26\u003c/b\u003e (10), 1890\u0026ndash;1900. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10147-021-01985-x\u003c/span\u003e\u003cspan address=\"10.1007/s10147-021-01985-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUllah, W. et al. Lymphocyte-to-C-Reactive Protein Ratio: A Novel Predictor of Adverse Outcomes in COVID-19. \u003cem\u003eJ. Clin. Med. Res.\u003c/em\u003e \u003cb\u003e12\u003c/b\u003e (7), 415\u0026ndash;422. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.14740/jocmr4227\u003c/span\u003e\u003cspan address=\"10.14740/jocmr4227\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang, J. N. et al. Lymphocyte-C-reactive protein ratio can differentiate disease severity of COVID-19 patients and serve as an assistant screening tool for hospital and ICU admission. \u003cem\u003eFront. Immunol.\u003c/em\u003e \u003cb\u003e13\u003c/b\u003e, 957407. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fimmu.2022.957407\u003c/span\u003e\u003cspan address=\"10.3389/fimmu.2022.957407\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022). Published 2022 Sep 23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu, X. et al. Predictive Value of the Systemic Immune-Inflammation Index for Intravenous Immunoglobulin Resistance and Cardiovascular Complications in Kawasaki Disease. \u003cem\u003eFront. Cardiovasc. Med.\u003c/em\u003e \u003cb\u003e8\u003c/b\u003e, 711007. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fcvm.2021.711007\u003c/span\u003e\u003cspan address=\"10.3389/fcvm.2021.711007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021). Published 2021 Aug 24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHotchkiss, R. S. et al. Accelerated lymphocyte death in sepsis occurs by both the death receptor and mitochondrial pathways. \u003cem\u003eJ. Immunol.\u003c/em\u003e \u003cb\u003e174\u003c/b\u003e (8), 5110\u0026ndash;5118. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4049/jimmunol.174.8.5110\u003c/span\u003e\u003cspan address=\"10.4049/jimmunol.174.8.5110\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2005).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLang, J. D. \u0026amp; Matute-Bello, G. Lymphocytes, apoptosis and sepsis: making the jump from mice to humans. \u003cem\u003eCrit. Care\u003c/em\u003e. \u003cb\u003e13\u003c/b\u003e (1), 109. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/cc7144\u003c/span\u003e\u003cspan address=\"10.1186/cc7144\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2009).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChu, C. M. et al. Increased Death of Peripheral Blood Mononuclear Cells after TLR4 Inhibition in Sepsis Is Not via TNF/TNF Receptor-Mediated Apoptotic Pathway. \u003cem\u003eMediators Inflamm.\u003c/em\u003e \u003cb\u003e2021\u003c/b\u003e, 2255017. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1155/2021/2255017\u003c/span\u003e\u003cspan address=\"10.1155/2021/2255017\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021). Published 2021 Oct 25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eP\u0026oacute;voa, P. et al. C-reactive protein as an indicator of sepsis. \u003cem\u003eIntensive Care Med.\u003c/em\u003e \u003cb\u003e24\u003c/b\u003e (10), 1052\u0026ndash;1056. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s001340050715\u003c/span\u003e\u003cspan address=\"10.1007/s001340050715\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1998).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang, H. E. et al. High-sensitivity C-reactive protein and risk of sepsis. \u003cem\u003ePLoS One\u003c/em\u003e. \u003cb\u003e8\u003c/b\u003e (7), e69232. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0069232\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0069232\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2013). Published 2013 Jul 23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTian, T., Wei, B. \u0026amp; Wang, J. Study of C-reactive protein, procalcitonin, and immunocyte ratios in 194 patients with sepsis. \u003cem\u003eBMC Emerg. Med.\u003c/em\u003e \u003cb\u003e21\u003c/b\u003e (1), 81. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12873-021-00477-5\u003c/span\u003e\u003cspan address=\"10.1186/s12873-021-00477-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021). Published 2021 Jul 7.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Kawasaki disease, prediction, Intravenous immunoglobulin resistance, lymphocyte to C-reactive protein ratio","lastPublishedDoi":"10.21203/rs.3.rs-5840515/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5840515/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eLmphocyte to C-reactive protein ratio (LCR) has tremendous predictive power for diseases with similar pathogenesis to Kawasaki disease (KD). The evidence on the prognostic value of LCR for IVIG resistance, especially for repeated IVIG resistance in KD, was scarce. We conducted a prospective cohort study comprising 1607 individuals with Kawasaki disease to evaluate the predictive value of LCR for both the initial and repeated IVIG resistance in KD. A comparison was made between the initial/repeated IVIG-resistance group and the initial/repeated IVIG-response group. We found that LCR was markedly reduced in both initial and repeated IVIG non-responders and was recognized as an independent risk factor for forecasting both initial and repeated IVIG resistance in KD. The optimal cut-off values of LCR for predicting initial and repeated IVIG resistance were 0.042\u0026times;10^9 and 0.025\u0026times;10^9, respectively, with sensitivities of 74.1% and 51.3%, and specificities of 65.9% and 55.8%. LCR may be a complementary laboratory marker for predicting initial and repeated IVIG resistance to guide clinical management.\u003c/p\u003e","manuscriptTitle":"Predictive value of lymphocyte-to-C-reactive protein ratio for predicting initial and repeated intravenous immunoglobulin resistance in a large cohort of Kawasaki disease: a prospective cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-23 13:56:20","doi":"10.21203/rs.3.rs-5840515/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fe9d8fc4-32f3-4780-9368-56919b68fee0","owner":[],"postedDate":"January 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":43270159,"name":"Health sciences/Biomarkers/Predictive markers"},{"id":43270160,"name":"Health sciences/Medical research/Paediatric research"}],"tags":[],"updatedAt":"2025-03-26T11:23:51+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-23 13:56:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5840515","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5840515","identity":"rs-5840515","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}