{"paper_id":"48111d3a-e1da-492d-a888-ca7e029d5a42","body_text":"Risk Factors and Bacterial Resistance in Pediatric Invasive Pneumococcal Disease Complicated by Purulent Meningitis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Risk Factors and Bacterial Resistance in Pediatric Invasive Pneumococcal Disease Complicated by Purulent Meningitis Mi Yang, Zhenxing Liu, Ling Yang, Guangbo Li, Zhiqiang Zhuo, Dequan Su This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6864829/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 Objective: To analyze the risk factors and bacterial resistance associated with invasive pneumococcal disease (IPD) complicated by purulent meningitis in children, with the goal of enhancing early diagnosis and treatment, preventing complications, and improving patient outcomes. Methods: The study involved 56 pediatric patients with IPD and admitted to our hospital from January 2016 and December 2024. Patients were stratified into two groups based on the presence or absence of purulent meningitis. Clinical characteristics, laboratory parameters, and bacterial resistance profiles were collected and analyzed using univariate and multivariate methods to identify risk factors. A risk prediction model based on logistic regression was developed, and its performance was assessed via the area under the receiver operating characteristic (ROC) curve. Results: The study cohort comprised 27 males and 29 females, including 13 patients with purulent meningitis and 43 without. A significant seasonal distribution was noted, with 58.93% (33/56) of cases occurring between November and January. Underlying diseases were present in 53.84% (7/13) of the purulent meningitis group compared to 4.65% (2/43) in the non-meningitic group (P < 0.001). Univariate analysis of laboratory indicators revealed significant intergroup differences in eight parameters(NLR, PCT, Alb, Na, Scr,D-Dimer, FDP, TT) (P < 0.05). Further, multivariate analysis identified PCT (OR = 1.209, 95% CI: 1.023–1.428, P = 0.026) and NLR (OR = 1.210, 95% CI: 1.010–1.449, P = 0.038) as independent risk factors for IPD complicated by purulent meningitis. The curve analysis results indicate that PCT>4.215 ng/ml and NLR>12.94 individually predicted the presence of purulent meningitis with AUCs of 0.863 and 0.606.The AUC for the model constructed with PCT > 4.215 ng/ml and NLR > 12.94 was 0.885, indicating that its predictive value for combined purulent meningitis is higher than that of the individual indicators, with sensitivity of 84.60% and specificity of 86%. Additionally, drug resistance analysis of 56 Streptococcus pneumoniae isolates revealed penicillin resistance rates of 73.21% (41/56) in meningitic strains versus 60.71% (34/56) in non-meningitic strains, and ceftriaxone resistance rates of 28.57% (16/56) versus 10.71% (6/56), respectively. Conclusion: Elevated PCT and NLR levels constitute independent risk factors for IPD complicated by purulent meningitis. The combined predictive model based on PCT > 4.215 ng/ml and NLR > 12.94 demonstrates robust clinical utility. Furthermore, the higher resistance rates of pneumococcal meningitis isolates to ceftriaxone and penicillin warrant heightened clinical attention. Invasive pneumococcal disease Purulent meningitis Children Risk factors Bacterial resistance Figures Figure 1 Figure 2 Figure 3 1. Introduction Streptococcus pneumoniae ( S.pneumoniae ) is one of the most prevalent bacteria causing invasive infections in pediatric populations[1-2]. According to the Global Burden of Diseases, Injuries, and Risk Factors Study, infections due to Streptococcus pneumoniae were responsible for over 34,100 child deaths across 195 countries in 2016[3]. This data highlights the high incidence and mortality rates among children under 5 years of age and underscores the substantial burden imposed on healthcare systems worldwide[4-5]. Invasive pneumococcal disease (IPD) is notably linked to significant socioeconomic costs due to its high morbidity and mortality rates[6-7]. Previous studies have reported that 10% to 30% of invasive infections in children are complicated by meningitis, with these cases exhibiting a higher mortality rate[5-7]. Furthermore, research indicates that 57% of Gram-negative invasive infections and 36% of confirmed Gram-positive invasive infections occur concurrently with meningitis[8]. Notably, there are differences in antibiotic resistance between meningitic and non-meningitic strains of Streptococcus pneumoniae , with penicillin insensitivity rates of 69.5% and 35.9%,and the resistance rate in meningitic strains has been increasing over time[9]. These findings suggest that IPD is more likely to be complicated by meningitis and that distinct bacterial resistance profiles exist. However, few studies have explored the risk factors for meningitis in children with IPD. Therefore, this study aims to analyze the risk factors for meningitis and the patterns of bacterial resistance in pediatric patients with IPD by reviewing clinical records from our hospital. 2. Materials and Methods 2.1. Study Subjects A total of 56 pediatric patients with IPD were enrolled from the Children's Hospital of Fudan University Xiamen Hospital (Xiamen Children’s Hospital) between January 2016 and December 2024. The cohort comprised 27 males and 29 females, corresponding to a male-to-female ratio of 0.93:1. Patients were stratified into two groups: 13 cases of complicated purulent meningitis and 43 cases of non-purulent meningitis. This study received approval from the Ethics Review Committee of Xiamen Children’s Hospital and fulfilled the criteria for exemption from informed consent (Approval No. 20250605-1). All procedures were conducted in accordance with the Declaration of Helsinki. 2.2 Inclusion Criteria 2.2.1 Diagnostic criteria for pediatric IPD [ 10 ]: (1) Patients aged 0–18 years; (2) Isolation of Streptococcus pneumoniae from sterile bodily sites such as blood, bone marrow, pleural effusion, ascites, or joint effusion. 2.2.2 Diagnostic criteria for pneumococcal meningitis [ 11 ]: (1) Clinical manifestations including fever, convulsions, headache, projectile vomiting, and varying degrees of consciousness impairment; in young infants, additional signs may include regurgitation of milk, irritability, abnormal crying, and fixed gaze. Meningeal irritation is evidenced by positive neck stiffness, Kernig’s sign, and Brudzinski’s sign; increased intracranial pressure may be indicated by a bulging anterior fontanelle or widened cranial sutures in infants and, in severe cases, cerebral herniation. (2) Cerebrospinal fluid analysis showing an elevated white blood cell count with neutrophilic predominance, significantly increased protein content, and markedly decreased glucose levels. (3) Positive cerebrospinal fluid culture for S. pneumoniae . 3. Exclusion Criteria Patients were excluded if they exhibited severe dysfunction of vital organs (e.g., heart, liver, kidneys), had incomplete clinical data, or were diagnosed and partially treated at other medical institutions. 4. Research Methods Demographic information and clinical data were collected, including the length of hospital stay, season of onset, white blood cell (WBC) count, neutrophil (NE) count, lymphocyte (LY) count, neutrophil-to-lymphocyte ratio (NLR), procalcitonin (PCT), hemoglobin (HGB), platelet count (PLT), C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), alanine aminotransferase (ALT), aspartate aminotransferase (AST), albumin (ALb), lactate dehydrogenase (LDH), serum sodium (Na), serum creatinine (Scr), blood urea nitrogen (BUN), prothrombin time (PT), activated partial thromboplastin time (APTT), D-dimer (D-D), thrombin time (TT), and antimicrobial resistance profiles of S. pneumoniae . 5. Isolation, Identification, and Antimicrobial Susceptibility Testing of Strains 5. Isolation, Identification, and Antimicrobial Susceptibility Testing of S. pneumoniae Strains Specimens including blood, cerebrospinal fluid, and bone marrow were collected in accordance with the \"National Clinical Laboratory Practice\" (fourth edition). Samples were inoculated onto blood agar, chocolate agar, and MacConkey agar plates and incubated at 35°C with 5–10% CO2 for 24–72 hours. Initial screening of suspected isolates was accomplished using optochin sensitivity; isolates displaying inhibition zones of ≥ 14 mm underwent further identification with GP cards, and antimicrobial susceptibility was tested using ATB Strep5 strips. The Kirby-Bauer (KB) method was employed to assess sensitivity to erythromycin, clindamycin, and tetracycline. 6. Statistical Methods Analyses were performed using SPSS version 22.0. Continuous variables with a normal distribution were presented as mean ± standard deviation and compared between groups using the t-test; non-normally distributed data were expressed as medians with interquartile ranges (M [IQR]) and compared using the Mann-Whitney U test. Categorical variables were summarized as counts (n) and percentages (%) and compared using the chi-square test. Logistic regression analysis was utilized for multivariate analyses, with P < 0.05 considered statistically significant. Receiver operating characteristic (ROC) curves were constructed to determine the optimal cutoff value, area under the curve (AUC), sensitivity, and specificity of each independent predictor and predictive model for combined purulent meningitis. 3. Results 3.1 Baseline Demographic and Clinical Characteristics A total of 56 community-acquired infection cases were included, comprising 27 males and 29 females, and the median age at onset was 30.50 months (IQR: 11.25–46.75 months). Notably, 42.90% of patients experienced disease onset before the age of 2 years, and 92.90% before 5 years. The highest incidence occurred between November and January, accounting for 58.93% (33/56) of total cases (Figs. 1 and 2 ). Patients were categorized into two groups based on the presence of purulent meningitis: a meningitis group (n = 13) and a non-meningitis group (n = 43). No statistically significant differences in gender, age at onset, season of onset, type of infection, or primary lesion were observed between the groups (P > 0.05). However, the proportion of patients with underlying diseases was significantly higher in the purulent meningitis group (P < 0.001). Four patients were co-infected with other pathogens: one with Respiratory Syncytial virus (RSV), one with both RSV and Haemophilus influenzae , one with Epstein–Barr virus (EBV), and one with Rhinovirus infection. The median length of hospital stay was 21.50 (10.25–38.00 )days in the meningitis group, and median length of ICU stay was 3.50 ( 0.00–9.25) days, both significantly longer than those observed in the non-meningitis group (P < 0.05). Moreover, the meningitis group also had significantly higher mortality rate (23.08% ; 3/13),than the non-meningitis grouy (P < 0.05) (see Table 1 ). Table 1 Baseline Demograohic and Clinical Characteristics Clinical Characteristics meningitis group (N = 13)༈%༉ nonmeningitis group (N = 43)(%) x2 / U P Age(months, M༈P25,P75) 26(11, 44) 38(9.5,59) 2.504 0.114 Sex 2.964 Male 4(30.77) 23(53.49) 0.151 Female 9(69.23) 20(46.51) Season of onset Spring 3(23.08) 10(23.26) 0.075 0.995 Summet 1(7.69) 4(9.30) Autumn 4(30.77) 14(32.56) Winter 5(38.46) 15(34.88) Weight(P) <P3 1(7.69) 2(4.65) 0.78 0.677 P3-P97 12(92.31) 39(9.07) >P97 0(0.00) 2(4.65) place of residence City 11(84.62) 37(86.05) 0.017 0.897 Rural/suburban 2(15.38) 6(13.95) Primary foci of infection 2.208 0.137 Respiratory tract 8(61.54) 35(81.40) Others 5(38.46) 8(18.60) Underlying diseases/ Risk factors 18.222 < 0.001 Trauma or surgery 5(38.46) 1(2.33) Immunocompromised 2(15.38) 1(2.33) None 6(46.15) 41(95.35) Complicated with respiratory infections 8(61.54) 35(81.40) 2.208 0.137 Co-infection with other pathogens 0(0.00) 4(9.30) 0.277 0.598 Length of hospitliztion(days) 21.5(10.25, 38.00) 10(7, 12) 7.501 0.016 Lenth of ICU stay(days) 3.5(0, 9.25) 0(0, 0) 15.746 < 0.001 Death 3(23.08) 1(2.33) 0.035 3.2 Analysis of Risk Factors for IPD Patients with Complicated Purulent Meningitis 3.2.1Univariate Analysis of Laboratory parameters White blood cell count (WBC), neutrophil count (NE), lymphocyte count (LY), neutrophil-to-lymphocyte ratio (NLR), C-reactive protein (CRP), hemoglobin (Hb), procalcitonin (PCT), aspartate aminotransferase (AST), alanine aminotransferase (ALT), albumin (Alb), lactate dehydrogenase (LDH), sodium (Na), serum creatinine (Scr), blood urea nitrogen (BUN), D-dimer, fibrinogen degradation product (FDP), activated partial thromboplastin time (APTT), thrombin time (TT), and prothrombin time (PT) were compared between patients with meningitis group and non-meningitis group. Statistically significant differences were identified in the NLR, PCT, Alb, Na, Scr, D-dimer, FDP, and TT (P < 0.05), whereas the remaining parameters did not show significant differences (P > 0.05). (Table 2 ). Table 2 Univariate analysis of IPD patients with complicated purulent meningitis Laboratory indicators Brain group Amorphous brain group P WBC(*10^9/L) 19.65 ± 11.27 26.63 ± 10.67 0.622 NE(*10^9/L) 15.73 ± 9.07 20.04 ± 9.89 0.676 LY(*10^9/L) 2.69 ± 3.09 4.27 ± 2.83 0.639 NLR 10.72 ± 9.38 6.45 ± 4.73 0.003 CRP(mg/L) 121.73 ± 85.16 48.89 ± 53.09 0.072 HGB(g/L) 110.31 ± 18.69 114.83 ± 14.18 0.17 PCT(ng/ml) 22.19 ± 31.72 2.77 ± 4.46 < 0.001 AST(U/L) 71.46 ± 103.7 40.56 ± 72.46 0.073 ALT(U/L) 21.15 ± 17.68 29.26 ± 79.48 0.504 Alb(g/L) 37.085 ± 8.21 42.070 ± 3.79 0.003 LDH(U/L) 477.46 ± 405.856 378.43 ± 307.191 0.09 Na(mmol/L) 133.43 ± 3.97 135.14 ± 2.62 0.027 BUN(mmol/L) 3.53 ± 1.57 3.30 ± 0.98 0.211 Scr(umol/L) 32.68 ± 26.79 27.68 ± 8.26 0.003 Fib (g/L) 4.76 ± 1.61 4.70 ± 1.45 0.953 D-dimer(mg/L) 7.81 ± 15.03 0.57 ± 0.98 0.002 FDP(ug/ml) 52.09 ± 91.02 4.57 ± 5.56 < 0.001 APTT(s) 34.41 ± 9.29 34.06 ± 5.35 0.233 TT(s) 15.10 ± 3.56 14.35 ± 1.17 0.029 PT(s) 15.24 ± 3.12 15.01 ± 2.09 0.281 WBC, white blood cells; NE,neutrophil; LY, lymphocyte; NLR: Ratio of neutrophil count to lymphocyte count; CRP, C-reactive protein; HGB,hemoglobin; PCT, Procalcitonin; AST,glutamic-pyruvic transaminase; ALT,glutamic oxaloacetic transaminase;ALB, Albumin;LDH, L-Lactate Dehydrogenase;Na, Natrium༛BUN,Blood Urea Nitrogen; Scr, Silicon Controlled Rectifier‌; Fib, fibrinogen; FDP,Fibrinogen;APTT,Activated Partial Thromboplastin Time;TT, Thrombin time;PT, Prothrombin time. 3.2.2 Multivariate Logistic Regression Analysis The eight laboratory indicators that reached statistically significant in the univariate analysis were subsequently entered into a binary logistic regression model. The multivariate analysis revealed that PCT (odds ratio [OR] = 1.209, 95% confidence interval [CI]: 1.023–1.428, P = 0.026) and NLR (OR = 1.210, 95% CI: 1.010–1.449, P = 0.038) served as independent risk factors for IPD patients with purulent meningitis.(Table 3 ) Table 3 Multivariate logistic analysis of risk factors for IPD complicated with purulent meningitis Laboratory indicators B S.E. Wald OR 95%CI P D-dimer(mg/L) -0.127 0.486 0.069 0.88 0.339 2.284 0.793 FDP(ug/ml) 0.085 0.099 0.731 1.088 0.896 1.321 0.392 TT(s) -0.018 0.394 0.002 0.982 0.454 2.127 0.964 PCT(ng/ml) 0.19 0.085 4.967 1.209 1.023 1.428 0.026 Na(mmol/L) -0.236 0.18 1.721 0.79 0.555 1.124 0.19 Scr(umol/L) -0.091 0.063 2.11 0.913 0.807 1.032 0.146 NLR 0.19 0.092 4.283 1.21 1.01 1.449 0.038 Alb(g/L) -0.114 0.123 0.853 0.892 0.7 1.136 0.356 NLR: Ratio of neutrophil count to lymphocyte count; PCT, Procalcitonin; Na, Natrium;Scr, Silicon Controlled Rectifier‌; FDP,Fibrinogen;TT, Thrombin time; ALB, Albumin; 3.2.3 Predictive Value and Cutoff Values Receiver operating characteristic (ROC) curve analysis was conducted to determine the area under the curve (AUC), p-value, sensitivity, specificity, and optimal cutoff values—defined by the maximum Youden’s index—for both PCT and NLR. The AUCs for PCT and NLR, twere 0.863 and 0.606,while the AUC for the combination model of NLR and PCT were 0.885. The combination model demonstrated superior predictive value for S.pneumoniae purulent meningitis compared to individual markers, with sensitivity of 84.60% and specificity of 86.00%. (Table 4 and Fig. 3 ). Table 4 :Diagnostic value of NLR, PCT, and their combined model in predicting IPD complicated with purulent meningitis CUT-OFF AUC SE P 95%CI Sensitivity Specificity NLR 12.94 0.606 0.102 0.251 0.406–0.806 46.20% 65.70% PCT(ng/ml) 4.215 0.863 0.074 0.000 0.718-1.000 92.30% 83.30% PCT + NLR 0.196 0.885 0.055 0.000 0.776–0.993 84.60% 86.00% NLR: Ratio of neutrophil count to lymphocyte count; PCT, Procalcitonin; 3.3 Drug Resistance Analysis of Streptococcus pneumoniae Strains Fifty-six S.pneumoniae strains were isolated (strains obtained from different specimens from the same patient at the same time were considered identical). Among these, 53 cases had positive blood culture, 10 cases had positive cerebrospinal fluid culture, and 14 patients also had positive sputum cultures. One patient presented with both pyogenic arthritis and osteomyelitis, with S. pneumoniae detected in both blood and pus cultures. All strains underwent antimicrobial susceptibility testing. The prevalent rates of penicillin-resistant were 73.21% (41/56) and 60.71% (34/56) in meningitis and non-meningitis isolates, respectively. Similarly, 28.57% (16/56) of meningitis strains and 10.71% (6/56) of non-meningitis had resistance to ceftriaxone; 28.57% (16/56) of meningitis and 8.93% (5/56) of non-meningitis had intermediate resistance, respectively. The nonsusceptibility (resistance and intermediate susceptibility) rates to meropenem were 21.42%(12/56). Susceptibility rates to levofloxacin and erythromycin were 10.71% (6/56) and 1.79% (1/56), respectively. Notably, no vancomycin-resistant strains were detected. (Table 5 ). Table 5 :Antimicrobial susceptibility of invasive pneumococcal isolates to common antibiotics Antimicrobial agent S(%) I(%) R(%) Penicillin(n = 56) meningitis 10 (17.85) 5 (8.9) 41 (73.21) nonmeningitis 11 (19.64) 11 (19.64) 34 (60.71) Ceftriaxone(n = 56) meningitis 24 (42.86) 16 (28.57) 16 (28.57) nonmeningitis 45 (80.36) 5 (8.93) 6 (10.71) Erythromycin(n = 56) 1 (1.79) 0 ( 0.00) 55 (98.21) Levofloxacin(n = 56) 0 ( 0.00 ) 6 (10.71) 50 (89.29) Vancomycin(n = 56) 56 (100) 0 ( 0.00 ) 0 ( 0.00) Meropenem(n = 56) 44 (78.57) 10 (17.86) 2 (3.57) SMZ(n = 53) 10 (17.86) 9 (16.07) 34 (60.71) 4. Discussion In this study, we analyzed the clinical symptoms and laboratory indicators in 56 children with invasive pneumococcal disease (IPD) and identified elevated procalcitonin (PCT) and neutrophil-to-lymphocyte ratio (NLR) as independent risk factors for the development of purulent meningitis. The combination predictive model, using thresholds of PCT > 4.215 ng/mL and NLR > 12.94, demonstrated strong clinical performance in predicting purulent meningitis. Additionally, meningitis strains exhibited higher resistance rates to ceftriaxone and penicillin compared to non-meningitic strains. Our findings showed that sepsis was the most common manifestation of IPD, particularly among patients with oncological diseases or compromised immune function. Of the 56 children with IPD, 13 (23.21%) developed purulent meningitis. In a study by Cameron Burtond et al. [ 12 ], 12% of 93 children with IPD had concurrent purulent meningitis, while another study involving 377 children reported a rate of 29.8% [ 13 ]. These results were consistent with our findings. Furthermore, our study indicated that children with underlying diseases were more prone to developing purulent meningitis; among the 13 children with purulent meningitis, 7 (53.84%) had comorbidities: 5 with tumors (and postoperative history) and 2 with immune deficiencies, suggesting that reduced immunity may facilitate bacterial invasion of the central nervous system. Previous studies reported mortality rates in children with IPD ranging from approximately 2.5–23.5% [ 13 – 15 ]. In our cohort, the overall mortality rate was 7.14%, with 23.07% of patients with purulent meningitis, underscoring the need for clinical vigilance. PCT is a propeptide glycoprotein produced by thyroid cells that rises significantly during the early stages of bacterial infection, making it a sensitive biomarker for diagnosing bacterial infections and sepsis, as well as for prognostication. Studies have shown that PCT levels correlate with the severity of pneumonia in patients with S.pneumoniae infection, and patients with bacteremia exhibited even higher levels of PCT, establishing PCT as a sensitive indicator for predicting S.pneumoniae bacteremia [16]. A prospective cohort study of 1,821 febrile infants aged ≤ 60 days demonstrated that combination of PCT with urine analysis and neutrophil evaluation yielded a negative predictive value of 99.6% for bacterial meningitis [ 17 ]. Our study reinforced the diagnostic value of PCT in IPD and highlight its potential role as a high-risk factor for bacterial meningitis. Moreover, the combination of PCT and NLR enhances predictive accuracy in these patients. NLR, calculated as the ratio of absolute neutrophil count to absolute lymphocyte count, reflects the body’s immune response to various pathogenic agents. Previous studies have already suggested a link between NLR and sepsis outcomes, and investigated its utility in predicting the prognosis of bacterial meningitis [ 18 , 19 ]. Our results add evidence supporting the use of NLR as a diagnostic tool in IPD-associated bacterial meningitis in children. Additionally, our study found that the sensitivity of non-meningitic IPD strains to penicillin was approximately 19.64%, compared to 17.85% in meningitic strains. In contrast, although the overall sensitivity rate to ceftriaxone was about 80.36%, meningitic strains had a markedly lower sensitivity rate of 42.86%. A prior analysis involving 54 cases of pediatric IPD reported that resistance to penicillin and ceftriaxone among S.pneumoniae reached up to 24.5% and has been increasing over time [ 20 ]. Conversely, Rajalakshmi Arjun et al. [ 21 ] observed penicillin and ceftriaxone sensitivity rates of 80% and 82%, respectively. in IPD patients. These discrepancies reflected regional variations in antibiotic susceptibility, potentially influenced by widespread use of penicillins and cephalosporins in children, which could drive drug resistance. Therefore, for children with IPD complicated by purulent meningitis, initial empirical treatment should be approached with caution due to potential resistance to penicillin and ceftriaxone. This study has several limitations. First, it was a single-center cohort study with a relatively small sample size. Second, some data were missing during collection, which may have introduced bias. Future research should include multi-center, prospective, randomized controlled trials to confirm these findings. 5. Conclusion our study demonstrates that PCT(> 4.215 ng/mL) and NLR (> 12.94) are independent risk factors for developing purulent meningitis in children with invasive pneumococcal disease. These markers should be considered in the clinical diagnosis and management of affected patients. Furthermore, given the high resistance rates of S.pneumoniae meningitis strains to penicillin and ceftriaxone, clinicians should consider alternative antibiotics when treating these cases. Abbreviations IPD Invasive Pneumococcal Disease WBC white blood cells NE neutrophil LY lymphocyte NLR Ratio of neutrophil count to lymphocyte count CRP C-reactive protein HGB Hemoglobin PCT Procalcitonin AST Glutamic-pyruvic transaminase ALT Glutamic oxaloacetic transaminase ALB Albumin LDH L-Lactate Dehydrogenase Na Natrium BUN Blood Urea Nitrogen Scr Silicon Controlled Rectifier‌ Fib Fibrinogen FDP Fibrinogen APTT Activated Partial Thromboplastin Time TT Thrombin time PT Prothrombin time ROC Receiver operating characteristic AUC Under the curve Declarations Ethics approval and consent to participate The studies involving human participants were reviewed and approved by the Ethical Committee of Xiamen Children's Hospital. The participants' legal guardian or next of kin provided written informed consent for participation in this study. Informed consent has been obtained from the participants, their parents and legally authorized representatives in this study. Consent for publication Not applicable. Availability of data and materials No datasets were generated or analysed during the current study. Competing Interests The authors declare no competing interests. Funding This study was supported by Xiamen City Health Guidance Project (Grant No.3502Z20224ZD1268 and No.3502Z2024ZD1277] 、Construction of Key Clinical Disciplines at Xiamen Children's Hospital (Fudan University Affiliated Children's Hospital Xiamen Hospital) ((Grant No. XE2022-YNPY-B03) and Xiamen Children's Hospital 1125 Talent Program. Authors' contributions YM and LZ were responsible for data analysis and drafted the manuscript. SD and ZZ contributed to designing the study and critically revised the manuscript for significant intellectual content. YL and LG were involved in patient follow-up and data collection. All authors have approved the final version of the manuscript for publication. Each author participated sufficiently in the work to be responsible for the content. Acknowledgements Not applicable. Clinical trial number Not applicable. References Ferreira-Coimbra J, Sarda C, Rello J. Burden of Community-Acquired Pneumonia and Unmet Clinical Needs. Adv Ther. 2020 Apr;37(4):1302-1318. doi: 10.1007/s12325-020-01248-7. Epub 2020 Feb 18. PMID: 32072494; PMCID: PMC7140754. Li Q, Cheng J, Wu Y, Wang Z, Luo S, Li Y, Tian X, Zhang G, Chen D, Luo Z. Effects of Delayed Antibiotic Therapy on Outcomes in Children with Streptococcus pneumoniae Sepsis. Antimicrob Agents Chemother. 2019 Aug 23;63(9):e00623-19. doi: 10.1128/AAC.00623-19. PMID: 31262764; PMCID: PMC6709508. Ouseph MM, Simons M, Treaba DO, Yakirevich E, Green PH, Bhagat G, Moss SF, Mangray S. Fatal Streptococcus pneumoniae Sepsis in a Patient With Celiac Disease-Associated Hyposplenism. ACG Case Rep J. 2016 Oct 12;3(4):e140. doi: 10.14309/crj.2016.113. PMID: 27761478; PMCID: PMC5064423. Erdem I, Elbasan Omar S, Ali RK, Gunes H, Topkaya AE. Streptococcus pneumoniae sepsis as the initial presentation of systemic lupus erythematosus. Int J Gen Med. 2016 Sep 8; 9:315-7. doi: 10.2147/IJGM.S105070. PMID: 27660485; PMCID: PMC5019324. Asner SA, Agyeman PKA, Gradoux E, Posfay-Barbe KM, Heininger U, Giannoni E, Crisinel PA, Stocker M, Bernhard-Stirnemann S, Niederer-Loher A, Kahlert CR, Hasters P, Relly C, Baer W, Aebi C, Schlapbach LJ, Berger C. Burden of Streptococcus pneumoniae Sepsis in Children After Introduction of Pneumococcal Conjugate Vaccines: A Prospective Population-based Cohort Study. Clin Infect Dis. 2019 Oct 15;69(9):1574-1580. doi: 10.1093/cid/ciy1139. PMID: 30601988. Greenberg D, Shinwell ES, Yagupsky P, Greenberg S, Leibovitz E, Mazor M, Dagan R. A prospective study of neonatal sepsis and meningitis in southern Israel. Pediatr Infect Dis J. 1997 Aug;16(8):768-73. doi: 10.1097/00006454-199708000-00008. PMID: 9271039. Groeneveld NS, Olie SE, Visser DH, Snoek L, van de Beek D, Brouwer MC, Bijlsma MW; NOGBS study group:. Cerebrospinal fluid inflammatory markers to differentiate between neonatal bacterial meningitis and sepsis: A prospective study of diagnostic accuracy. Int J Infect Dis. 2024 May; 142:106970. doi: 10.1016/j.ijid.2024.02.013. Epub 2024 Feb 21. PMID: 38395221. Bansal N, Sukhwani KS, Ganta V. Predictors of mortality in patients with Gram-Negative Bacilli (GNB) blood stream infections (BSI): multicentre data from India. Infect Dis (Lond). 2025 Jun;57(6):518-525. doi: 10.1080/23744235.2025.2453581. Epub 2025 Jan 13. PMID: 39804585. Zhu Liang, Li Wenhui, Wang Xinhong, et al. Multi-center clinical study on 1,138 cases of invasive pneumococcal disease in children from 2012 to 2017 [J]. Chinese Journal of Pediatrics, 2018, 56(12): 915-922 Xu Y, Zhou X, Zheng W, Cui B, Xie C, Liu Y, Qin X, Liu J. Serotype distribution, antibiotic resistance, multilocus sequence typing, and virulence factors of invasive and non-invasive Streptococcus pneumoniae in Northeast China from 2000 to 2021. Med Microbiol Immunol. 2024 Jul 2;213(1):12. doi: 10.1007/s00430-024-00797-w. PMID: 38954065.. Ishikawa K, Matsuo T, Suzuki T, Kawai F, Uehara Y, Mori N. Penicillin- and third-generation cephalosporin-resistant strains of Streptococcus pneumoniae meningitis: Case report and literature review. J Infect Chemother. 2022 May;28(5):663-668. doi: 10.1016/j.jiac.2022.01.021. Epub 2022 Feb 8. PMID: 35144879. Burton C, Webb R, Anglemyer A, Humphrey A, Tuatoo A, Best E. Severe Invasive Pneumococcal Disease Caused by Serotype 19A in Children Under Five Years in Tāmaki Makaurau Auckland, Aotearoa New Zealand. Pediatr Infect Dis J. 2025 Jan 1;44(1):90-96. doi: 10.1097/INF.0000000000004528. Epub 2024 Sep 11. PMID: 39259857; PMCID: PMC11627305. Xu Y, Wang Q, Yao KH, et al. Clinical characteristics and serotype distribution of invasive pneumococcal disease in pediatric patients from Beijing, China. Eur J Clin Microbiol Infect Dis. 2021; 40:1833–1842. doi: 10.1007/s10096-021-04238-x Manoharan A, Manchanda V, Balasubramanian S, et al. Invasive pneumococcal disease in children aged younger than 5 years in India: a surveillance study. Lancet Infect Dis. 2017; 17:305–312. doi: 10.1016/S1473-3099(16)30466-2. Yildirim I, Shea KM, Little BA, et al. Members of the Massachusetts Department of Public Health. Vaccination, underlying comorbidities, and risk of invasive pneumococcal disease. Pediatrics. 2015; 135:495–503. doi: 10.1542/peds.2014-2426 Akagi T, Nagata N, Miyazaki H, Harada T, Takeda S, Yoshida Y, Wada K, Fujita M, Watanabe K. Procalcitonin is not an independent predictor of 30-day mortality, albeit predicts pneumonia severity in patients with pneumonia acquired outside the hospital. BMC Geriatr. 2019 Jan 7;19(1):3. doi: 10.1186/s12877-018-1008-8. PMID: 30616612; PMCID: PMC6323702. Pereira JM, Teixeira-Pinto A, Basílio C, Sousa-Dias C, Mergulhão P, Paiva JA. Can we predict pneumococcal bacteremia in patients with severe community-acquired pneumonia? J Crit Care. 2013 Dec;28(6):970-4. doi: 10.1016/j.jcrc.2013.04.016. PMID: 24216331. Kuppermann N, Dayan PS, Levine DA, Vitale M, Tzimenatos L, Tunik MG, Saunders M, Ruddy RM, Roosevelt G, Rogers AJ, Powell EC, Nigrovic LE, Muenzer J, Linakis JG, Grisanti K, Jaffe DM, Hoyle JD Jr, Greenberg R, Gattu R, Cruz AT, Crain EF, Cohen DM, Brayer A, Borgialli D, Bonsu B, Browne L, Blumberg S, Bennett JE, Atabaki SM, Anders J, Alpern ER, Miller B, Casper TC, Dean JM, Ramilo O, Mahajan P; Febrile Infant Working Group of the Pediatric Emergency Care Applied Research Network (PECARN). A Clinical Prediction Rule to Identify Febrile Infants 60 Days and Younger at Low Risk for Serious Bacterial Infections. JAMA Pediatr. 2019 Apr 1;173(4):342-351. doi: 10.1001/jamapediatrics.2018.5501. PMID: 30776077; PMCID: PMC6450281. Chen Q, Zhang M, Xia Y, Deng Y, Yang Y, Dai L, Niu H. Dynamic risk stratification and treatment optimization in sepsis: the role of NLPR. Front Pharmacol. 2025 Apr 2; 16:1572677. doi: 10.3389/fphar.2025.1572677. PMID: 40242435; PMCID: PMC11999927. Phuong LK, Cheung A, Templeton T, Abebe T, Ademi Z, Buttery J, Clark J, Cole T, Curtis N, Dobinson H, Shahul Hameed N, Hernstadt H, Ojaimi S, Sharp EG, Sinnaparajar P, Wen S, Daley A, McMullan B, Gwee A. Epidemiology of childhood invasive pneumococcal disease in Australia: a prospective cohort study. Arch Dis Child. 2024 Dec 13;110(1):52-58. doi: 10.1136/archdischild-2024-327497. PMID: 39322267. Rodríguez WC, Mora-Salamanca AF, Santacruz-Arias J, Alvarado-Gonzalez JC, Saavedra L, Pinzón-Redondo H, Alvis Guzmán NR, Alvis-Zakzuk NR, Zakzuk J. Pediatric invasive pneumococcal disease in Bolívar, Colombia: a descriptive cross-sectional study. Infez Med. 2024 Dec 1;32(4):506-517. doi: 10.53854/liim-3204-9. PMID: 39660158; PMCID: PMC11627489. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-6864829\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":472171735,\"identity\":\"0cc72ee0-00ff-4fd3-abb9-d816a719311d\",\"order_by\":0,\"name\":\"Mi Yang\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Fudan University Affiliated Children's Hospital Xiamen Hospital, Xiamen Children's Hospital)\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Mi\",\"middleName\":\"\",\"lastName\":\"Yang\",\"suffix\":\"\"},{\"id\":472171738,\"identity\":\"c63b3cc1-b079-4e2c-8a1f-cfba0169179e\",\"order_by\":1,\"name\":\"Zhenxing Liu\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Fudan University Affiliated Children's Hospital Xiamen Hospital, Xiamen Children's Hospital)\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Zhenxing\",\"middleName\":\"\",\"lastName\":\"Liu\",\"suffix\":\"\"},{\"id\":472171740,\"identity\":\"9f0b3f3d-cb6c-4862-817c-11ba0d8a9f75\",\"order_by\":2,\"name\":\"Ling Yang\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Fudan University Affiliated Children's Hospital Xiamen Hospital, Xiamen Children's Hospital)\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Ling\",\"middleName\":\"\",\"lastName\":\"Yang\",\"suffix\":\"\"},{\"id\":472171741,\"identity\":\"d2884c39-58f5-4bf0-a3a6-a0c61b8e65fb\",\"order_by\":3,\"name\":\"Guangbo Li\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Fudan University Affiliated Children's Hospital Xiamen Hospital, Xiamen Children's Hospital)\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Guangbo\",\"middleName\":\"\",\"lastName\":\"Li\",\"suffix\":\"\"},{\"id\":472171744,\"identity\":\"c193d113-9fd4-426d-94e0-2f9178698966\",\"order_by\":4,\"name\":\"Zhiqiang Zhuo\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Fudan University Affiliated Children's Hospital Xiamen Hospital, Xiamen Children's Hospital)\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Zhiqiang\",\"middleName\":\"\",\"lastName\":\"Zhuo\",\"suffix\":\"\"},{\"id\":472171757,\"identity\":\"e34c063b-3e7c-48c6-8100-cb59ee9e82ec\",\"order_by\":5,\"name\":\"Dequan Su\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuklEQVRIiWNgGAWjYDCCAwwMjB8M/suxsbcfIF4Ls0QBszEfz5kE4rUw8HxgTpwn4WBAnA6+48efSUgYsKW3STAkMPyo2EZYi+SZHDOJAgOe3DbpxgOMPWduE9ZicCCHDWiLRG6bzIEEZsY2YrScf/5MgsfAIJ1NIsGASC03EsyAWhISiNcieeONsbWEwQHDNmAgHyTKL3zn0x/e/PDngLx8e/vBBz8qiNCCAg6QqH4UjIJRMApGAS4AAM2+O3Y42sjmAAAAAElFTkSuQmCC\",\"orcid\":\"\",\"institution\":\"Fudan University Affiliated Children's Hospital Xiamen Hospital, Xiamen Children's Hospital)\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Dequan\",\"middleName\":\"\",\"lastName\":\"Su\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2025-06-10 15:53:27\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-6864829/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-6864829/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":85169942,\"identity\":\"297007f0-21d9-4db4-9a8e-ca46ca002d62\",\"added_by\":\"auto\",\"created_at\":\"2025-06-23 05:30:29\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":38744,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eDistribution of invasive pneumococcal disease in our hospital from January 2016 to December 2024\\u003c/strong\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6864829/v1/78a8781c4d386f5b030c6f2a.png\"},{\"id\":85169907,\"identity\":\"2bde2cc9-669c-4462-8b97-19cbbc7a014a\",\"added_by\":\"auto\",\"created_at\":\"2025-06-23 05:30:29\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":23707,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eAge distribution of invasive pneumococcal disease\\u003c/strong\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6864829/v1/80a9d6d5119af86c898ea767.png\"},{\"id\":85169934,\"identity\":\"aa9b1df4-1ece-40cc-8070-c646fe6ca0f6\",\"added_by\":\"auto\",\"created_at\":\"2025-06-23 05:30:29\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":26333,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eROC curves of NLR, PCT, and NLR-PCT for predicting the presence of meningitis\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6864829/v1/12a43dd1d9cfab812d74622f.png\"},{\"id\":92106522,\"identity\":\"c1e47bb2-8b40-4c19-b63a-89ed3745e9b3\",\"added_by\":\"auto\",\"created_at\":\"2025-09-24 17:01:51\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":1616194,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6864829/v1/2946dcfc-2780-4124-ad12-82574952764f.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Risk Factors and Bacterial Resistance in Pediatric Invasive Pneumococcal Disease Complicated by Purulent Meningitis\",\"fulltext\":[{\"header\":\"1. Introduction\",\"content\":\"\\u003cp\\u003e\\u003cem\\u003eStreptococcus pneumoniae\\u0026nbsp;\\u003c/em\\u003e(\\u003cem\\u003eS.pneumoniae\\u003c/em\\u003e) is one of the most prevalent bacteria causing invasive infections in pediatric populations[1-2]. According to the Global Burden of Diseases, Injuries, and Risk Factors Study, infections due to\\u003cem\\u003e\\u0026nbsp;Streptococcus pneumoniae\\u003c/em\\u003e were responsible for over 34,100 child deaths across 195 countries in 2016[3]. This data highlights the high incidence and mortality rates among children under 5 years of age and underscores the substantial burden imposed on healthcare systems worldwide[4-5]. Invasive pneumococcal disease (IPD) is notably linked to significant socioeconomic costs due to its high morbidity and mortality rates[6-7]. Previous studies have reported that 10% to 30% of invasive infections in children are complicated by meningitis, with these cases exhibiting a higher mortality rate[5-7]. Furthermore, research indicates that 57% of Gram-negative invasive infections and 36% of confirmed Gram-positive invasive infections occur concurrently with meningitis[8]. Notably, there are differences in antibiotic resistance between meningitic and non-meningitic strains of \\u003cem\\u003eStreptococcus pneumoniae\\u003c/em\\u003e, with penicillin insensitivity rates of 69.5% and 35.9%,and the resistance rate in meningitic strains has been increasing over time[9]. These findings suggest that IPD is more likely to be complicated by meningitis and that distinct bacterial resistance profiles exist. However, few studies have explored the risk factors for meningitis in children with IPD. Therefore, this study aims to analyze the risk factors for meningitis and the patterns of bacterial resistance in pediatric patients with IPD by reviewing clinical records from our hospital.\\u003c/p\\u003e\"},{\"header\":\"2. Materials and Methods\",\"content\":\"\\u003cdiv id=\\\"Sec2\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003e2.1. Study Subjects\\u003c/h2\\u003e\\n \\u003cp\\u003eA total of 56 pediatric patients with IPD were enrolled from the Children\\u0026apos;s Hospital of Fudan University Xiamen Hospital (Xiamen Children\\u0026rsquo;s Hospital) between January 2016 and December 2024. The cohort comprised 27 males and 29 females, corresponding to a male-to-female ratio of 0.93:1. Patients were stratified into two groups: 13 cases of complicated purulent meningitis and 43 cases of non-purulent meningitis. This study received approval from the Ethics Review Committee of Xiamen Children\\u0026rsquo;s Hospital and fulfilled the criteria for exemption from informed consent (Approval No. 20250605-1). All procedures were conducted in accordance with the Declaration of Helsinki.\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e\\n \\u003ch2\\u003e2.2 Inclusion Criteria\\u003c/h2\\u003e\\n \\u003cp\\u003e2.2.1 Diagnostic criteria for pediatric IPD [\\u003cspan class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e]: (1) Patients aged 0\\u0026ndash;18 years; (2) Isolation of \\u003cem\\u003eStreptococcus pneumoniae\\u003c/em\\u003e from sterile bodily sites such as blood, bone marrow, pleural effusion, ascites, or joint effusion.\\u003c/p\\u003e\\n \\u003cp\\u003e2.2.2 Diagnostic criteria for pneumococcal meningitis [\\u003cspan class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e]: (1) Clinical manifestations including fever, convulsions, headache, projectile vomiting, and varying degrees of consciousness impairment; in young infants, additional signs may include regurgitation of milk, irritability, abnormal crying, and fixed gaze. Meningeal irritation is evidenced by positive neck stiffness, Kernig\\u0026rsquo;s sign, and Brudzinski\\u0026rsquo;s sign; increased intracranial pressure may be indicated by a bulging anterior fontanelle or widened cranial sutures in infants and, in severe cases, cerebral herniation. (2) Cerebrospinal fluid analysis showing an elevated white blood cell count with neutrophilic predominance, significantly increased protein content, and markedly decreased glucose levels. (3) Positive cerebrospinal fluid culture for \\u003cem\\u003eS. pneumoniae\\u003c/em\\u003e.\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003ch3\\u003e3. Exclusion Criteria\\u003c/h3\\u003e\\n\\u003cp\\u003ePatients were excluded if they exhibited severe dysfunction of vital organs (e.g., heart, liver, kidneys), had incomplete clinical data, or were diagnosed and partially treated at other medical institutions.\\u003c/p\\u003e\\n\\u003ch3\\u003e4. Research Methods\\u003c/h3\\u003e\\n\\u003cp\\u003eDemographic information and clinical data were collected, including the length of hospital stay, season of onset, white blood cell (WBC) count, neutrophil (NE) count, lymphocyte (LY) count, neutrophil-to-lymphocyte ratio (NLR), procalcitonin (PCT), hemoglobin (HGB), platelet count (PLT), C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), alanine aminotransferase (ALT), aspartate aminotransferase (AST), albumin (ALb), lactate dehydrogenase (LDH), serum sodium (Na), serum creatinine (Scr), blood urea nitrogen (BUN), prothrombin time (PT), activated partial thromboplastin time (APTT), D-dimer (D-D), thrombin time (TT), and antimicrobial resistance profiles of \\u003cem\\u003eS. pneumoniae\\u003c/em\\u003e.\\u003c/p\\u003e\\n\\u003ch3\\u003e5. Isolation, Identification, and Antimicrobial Susceptibility Testing of Strains\\u003c/h3\\u003e\\n\\u003cdiv class=\\\"Heading\\\"\\u003e5. Isolation, Identification, and Antimicrobial Susceptibility Testing of \\u003cem\\u003eS. pneumoniae\\u003c/em\\u003e Strains\\u003c/div\\u003e \\u003cp\\u003eSpecimens including blood, cerebrospinal fluid, and bone marrow were collected in accordance with the \\\"National Clinical Laboratory Practice\\\" (fourth edition). Samples were inoculated onto blood agar, chocolate agar, and MacConkey agar plates and incubated at 35\\u0026deg;C with 5\\u0026ndash;10% CO2 for 24\\u0026ndash;72 hours. Initial screening of suspected isolates was accomplished using optochin sensitivity; isolates displaying inhibition zones of \\u0026ge;\\u0026thinsp;14 mm underwent further identification with GP cards, and antimicrobial susceptibility was tested using ATB Strep5 strips. The Kirby-Bauer (KB) method was employed to assess sensitivity to erythromycin, clindamycin, and tetracycline.\\u003c/p\\u003e\\n\\u003ch3\\u003e6. Statistical Methods\\u003c/h3\\u003e\\n\\u003cp\\u003eAnalyses were performed using SPSS version 22.0. Continuous variables with a normal distribution were presented as mean\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;standard deviation and compared between groups using the t-test; non-normally distributed data were expressed as medians with interquartile ranges (M [IQR]) and compared using the Mann-Whitney U test. Categorical variables were summarized as counts (n) and percentages (%) and compared using the chi-square test. Logistic regression analysis was utilized for multivariate analyses, with P\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05 considered statistically significant. Receiver operating characteristic (ROC) curves were constructed to determine the optimal cutoff value, area under the curve (AUC), sensitivity, and specificity of each independent predictor and predictive model for combined purulent meningitis.\\u003c/p\\u003e\"},{\"header\":\"3. Results\",\"content\":\"\\u003cdiv id=\\\"Sec9\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.1 Baseline Demographic and Clinical Characteristics\\u003c/h2\\u003e \\u003cp\\u003eA total of 56 community-acquired infection cases were included, comprising 27 males and 29 females, and the median age at onset was 30.50 months (IQR: 11.25\\u0026ndash;46.75 months). Notably, 42.90% of patients experienced disease onset before the age of 2 years, and 92.90% before 5 years. The highest incidence occurred between November and January, accounting for 58.93% (33/56) of total cases (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e and \\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). Patients were categorized into two groups based on the presence of purulent meningitis: a meningitis group (n\\u0026thinsp;=\\u0026thinsp;13) and a non-meningitis group (n\\u0026thinsp;=\\u0026thinsp;43). No statistically significant differences in gender, age at onset, season of onset, type of infection, or primary lesion were observed between the groups (P\\u0026thinsp;\\u0026gt;\\u0026thinsp;0.05). However, the proportion of patients with underlying diseases was significantly higher in the purulent meningitis group (P\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001). Four patients were co-infected with other pathogens: one with Respiratory Syncytial virus (RSV), one with both RSV and \\u003cem\\u003eHaemophilus influenzae\\u003c/em\\u003e, one with Epstein\\u0026ndash;Barr virus (EBV), and one with Rhinovirus infection. The median length of hospital stay was 21.50 (10.25\\u0026ndash;38.00 )days in the meningitis group, and median length of ICU stay was 3.50 ( 0.00\\u0026ndash;9.25) days, both significantly longer than those observed in the non-meningitis group (P\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05). Moreover, the meningitis group also had significantly higher mortality rate (23.08% ; 3/13),than the non-meningitis grouy (P\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05) (see Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\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\\u003eBaseline Demograohic and Clinical Characteristics\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"6\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"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 \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003eClinical Characteristics\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003emeningitis group\\u003c/p\\u003e \\u003cp\\u003e(N\\u0026thinsp;=\\u0026thinsp;13)༈%༉\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003enonmeningitis group\\u003c/p\\u003e \\u003cp\\u003e(N\\u0026thinsp;=\\u0026thinsp;43)(%)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003ex2 / U\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eP\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003eAge(months, M༈P25,P75)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e26(11, 44)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e38(9.5,59)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e2.504\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.114\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSex\\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 \\u003cp\\u003e2.964\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eMale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e4(30.77)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e23(53.49)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.151\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eFemale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e9(69.23)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e20(46.51)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSeason of onset\\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 \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eSpring\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3(23.08)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e10(23.26)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.075\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.995\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eSummet\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1(7.69)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e4(9.30)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eAutumn\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e4(30.77)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e14(32.56)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eWinter\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e5(38.46)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e15(34.88)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eWeight(P)\\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 \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u0026lt;P3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1(7.69)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2(4.65)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.78\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.677\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eP3-P97\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e12(92.31)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e39(9.07)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u0026gt;P97\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0(0.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2(4.65)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003eplace of residence\\u003c/p\\u003e \\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 \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eCity\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e11(84.62)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e37(86.05)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.017\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.897\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eRural/suburban\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2(15.38)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e6(13.95)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePrimary foci of infection\\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 \\u003cp\\u003e2.208\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.137\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eRespiratory tract\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e8(61.54)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e35(81.40)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eOthers\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e5(38.46)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e8(18.60)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003eUnderlying diseases/ Risk factors\\u003c/p\\u003e \\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 \\u003cp\\u003e18.222\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eTrauma or surgery\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e5(38.46)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1(2.33)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eImmunocompromised\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2(15.38)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1(2.33)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eNone\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e6(46.15)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e41(95.35)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003eComplicated with respiratory infections\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e8(61.54)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e35(81.40)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e2.208\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.137\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003eCo-infection with other pathogens\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0(0.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e4(9.30)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.277\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.598\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003eLength of hospitliztion(days)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e21.5(10.25, 38.00)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e10(7, 12)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e7.501\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.016\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003eLenth of ICU stay(days)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3.5(0, 9.25)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0(0, 0)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e15.746\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003eDeath\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3(23.08)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e1(2.33)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.035\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec10\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.2 Analysis of Risk Factors for IPD Patients with Complicated Purulent Meningitis\\u003c/h2\\u003e \\u003cdiv id=\\\"Sec11\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e3.2.1Univariate Analysis of Laboratory parameters\\u003c/h2\\u003e \\u003cp\\u003eWhite blood cell count (WBC), neutrophil count (NE), lymphocyte count (LY), neutrophil-to-lymphocyte ratio (NLR), C-reactive protein (CRP), hemoglobin (Hb), procalcitonin (PCT), aspartate aminotransferase (AST), alanine aminotransferase (ALT), albumin (Alb), lactate dehydrogenase (LDH), sodium (Na), serum creatinine (Scr), blood urea nitrogen (BUN), D-dimer, fibrinogen degradation product (FDP), activated partial thromboplastin time (APTT), thrombin time (TT), and prothrombin time (PT) were compared between patients with meningitis group and non-meningitis group. Statistically significant differences were identified in the NLR, PCT, Alb, Na, Scr, D-dimer, FDP, and TT (P\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05), whereas the remaining parameters did not show significant differences (P\\u0026thinsp;\\u0026gt;\\u0026thinsp;0.05). (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\\u003eUnivariate analysis of IPD patients with complicated purulent meningitis\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"4\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLaboratory indicators\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eBrain group\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eAmorphous brain group\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\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\\u003eWBC(*10^9/L)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e19.65\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;11.27\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e26.63\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;10.67\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.622\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eNE(*10^9/L)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e15.73\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;9.07\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e20.04\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;9.89\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.676\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLY(*10^9/L)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e2.69\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;3.09\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e4.27\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.83\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.639\\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\\u003e10.72\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;9.38\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e6.45\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.73\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.003\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCRP(mg/L)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e121.73\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;85.16\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e48.89\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;53.09\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.072\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHGB(g/L)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e110.31\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;18.69\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e114.83\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;14.18\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.17\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePCT(ng/ml)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e22.19\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;31.72\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2.77\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4.46\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" 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(U/L)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e71.46\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;103.7\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e40.56\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;72.46\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.073\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eALT(U/L)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e21.15\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;17.68\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e29.26\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;79.48\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.504\\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\\u003e37.085\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;8.21\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e42.070\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;3.79\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.003\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLDH(U/L)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e477.46\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;405.856\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e378.43\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;307.191\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.09\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eNa(mmol/L)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e133.43\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;3.97\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e135.14\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.62\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.027\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBUN(mmol/L)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e3.53\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.57\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3.30\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.98\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.211\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eScr(umol/L)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e32.68\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;26.79\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e27.68\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;8.26\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.003\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFib (g/L)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e4.76\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.61\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e4.70\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.45\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.953\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eD-dimer(mg/L)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e7.81\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;15.03\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.57\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.98\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.002\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFDP(ug/ml)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e52.09\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;91.02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e4.57\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;5.56\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" 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\\u003eAPTT(s)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e34.41\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;9.29\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e34.06\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;5.35\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.233\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTT(s)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e15.10\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;3.56\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e14.35\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.17\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.029\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePT(s)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e15.24\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;3.12\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e15.01\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.09\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.281\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"4\\\"\\u003eWBC, white blood cells; NE,neutrophil; LY, lymphocyte; NLR: Ratio of neutrophil count to lymphocyte count; CRP, C-reactive protein; HGB,hemoglobin; PCT, Procalcitonin; AST,glutamic-pyruvic transaminase; ALT,glutamic oxaloacetic transaminase;ALB, Albumin;LDH, L-Lactate Dehydrogenase;Na, Natrium༛BUN,Blood Urea Nitrogen; Scr, Silicon Controlled Rectifier\\u0026zwnj;; Fib, fibrinogen; FDP,Fibrinogen;APTT,Activated Partial Thromboplastin Time;TT, Thrombin time;PT, Prothrombin time.\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec12\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e3.2.2 Multivariate Logistic Regression Analysis\\u003c/h2\\u003e \\u003cp\\u003eThe eight laboratory indicators that reached statistically significant in the univariate analysis were subsequently entered into a binary logistic regression model. The multivariate analysis revealed that PCT (odds ratio [OR]\\u0026thinsp;=\\u0026thinsp;1.209, 95% confidence interval [CI]: 1.023\\u0026ndash;1.428, P\\u0026thinsp;=\\u0026thinsp;0.026) and NLR (OR\\u0026thinsp;=\\u0026thinsp;1.210, 95% CI: 1.010\\u0026ndash;1.449, P\\u0026thinsp;=\\u0026thinsp;0.038) served as independent risk factors for IPD patients with purulent meningitis.(Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\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\\u003eMultivariate logistic analysis of risk factors for IPD complicated with purulent meningitis\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"8\\\"\\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 \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLaboratory indicators\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eB\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eS.E.\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eWald\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eOR\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c7\\\" namest=\\\"c6\\\"\\u003e \\u003cp\\u003e95%CI\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eP\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eD-dimer(mg/L)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e-0.127\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.486\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.069\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.88\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.339\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e2.284\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.793\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFDP(ug/ml)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.085\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.099\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.731\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1.088\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.896\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e1.321\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.392\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eTT(s)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e-0.018\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.394\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.002\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.982\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.454\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e2.127\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.964\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003ePCT(ng/ml)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.19\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.085\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e4.967\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e1.209\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e1.023\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e1.428\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.026\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eNa(mmol/L)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e-0.236\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.18\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e1.721\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.79\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.555\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e1.124\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.19\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eScr(umol/L)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e-0.091\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.063\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e2.11\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.913\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.807\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e1.032\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.146\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eNLR\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.19\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.092\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e4.283\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e1.21\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e1.01\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e1.449\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.038\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eAlb(g/L)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e-0.114\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.123\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.853\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.892\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.7\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e1.136\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.356\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"8\\\"\\u003eNLR: Ratio of neutrophil count to lymphocyte count; PCT, Procalcitonin; Na, Natrium;Scr, Silicon Controlled Rectifier\\u0026zwnj;; FDP,Fibrinogen;TT, Thrombin time; ALB, Albumin;\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec13\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e3.2.3 Predictive Value and Cutoff Values\\u003c/h2\\u003e \\u003cp\\u003eReceiver operating characteristic (ROC) curve analysis was conducted to determine the area under the curve (AUC), p-value, sensitivity, specificity, and optimal cutoff values\\u0026mdash;defined by the maximum Youden\\u0026rsquo;s index\\u0026mdash;for both PCT and NLR. The AUCs for PCT and NLR, twere 0.863 and 0.606,while the AUC for the combination model of NLR and PCT were 0.885. The combination model demonstrated superior predictive value for \\u003cem\\u003eS.pneumoniae\\u003c/em\\u003e purulent meningitis compared to individual markers, with sensitivity of 84.60% and specificity of 86.00%. (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e and Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab4\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 4\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003e:Diagnostic value of NLR, PCT, and their combined model in predicting IPD complicated with purulent meningitis\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"8\\\"\\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 \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eCUT-OFF\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eAUC\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eSE\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eP\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e95%CI\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eSensitivity\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eSpecificity\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eNLR\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e12.94\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.606\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.102\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.251\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.406\\u0026ndash;0.806\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e46.20%\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e65.70%\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePCT(ng/ml)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e4.215\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.863\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.074\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.000\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.718-1.000\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e92.30%\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e83.30%\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003ePCT\\u0026thinsp;+\\u0026thinsp;NLR\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.196\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.885\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.055\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.000\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.776\\u0026ndash;0.993\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e84.60%\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e86.00%\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"8\\\"\\u003eNLR: Ratio of neutrophil count to lymphocyte count; PCT, Procalcitonin;\\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 \\u003c/div\\u003e \\u003cdiv id=\\\"Sec14\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.3 Drug Resistance Analysis of \\u003cem\\u003eStreptococcus pneumoniae\\u003c/em\\u003e Strains\\u003c/h2\\u003e \\u003cp\\u003eFifty-six \\u003cem\\u003eS.pneumoniae\\u003c/em\\u003e strains were isolated (strains obtained from different specimens from the same patient at the same time were considered identical). Among these, 53 cases had positive blood culture, 10 cases had positive cerebrospinal fluid culture, and 14 patients also had positive sputum cultures. One patient presented with both pyogenic arthritis and osteomyelitis, with \\u003cem\\u003eS. pneumoniae\\u003c/em\\u003e detected in both blood and pus cultures. All strains underwent antimicrobial susceptibility testing. The prevalent rates of penicillin-resistant were 73.21% (41/56) and 60.71% (34/56) in meningitis and non-meningitis isolates, respectively. Similarly, 28.57% (16/56) of meningitis strains and 10.71% (6/56) of non-meningitis had resistance to ceftriaxone; 28.57% (16/56) of meningitis and 8.93% (5/56) of non-meningitis had intermediate resistance, respectively. The nonsusceptibility (resistance and intermediate susceptibility) rates to meropenem were 21.42%(12/56). Susceptibility rates to levofloxacin and erythromycin were 10.71% (6/56) and 1.79% (1/56), respectively. Notably, no vancomycin-resistant strains were detected. (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e).\\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\\u003e:Antimicrobial susceptibility of invasive pneumococcal isolates to common antibiotics\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"5\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAntimicrobial agent\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eS(%)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eI(%)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eR(%)\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePenicillin(n\\u0026thinsp;=\\u0026thinsp;56)\\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 \\u003c/tr\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003emeningitis\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e10 (17.85)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e5 (8.9)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e41 (73.21)\\u003c/p\\u003e \\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\\u003e\\u003cb\\u003enonmeningitis\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e11 (19.64)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e11 (19.64)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e34 (60.71)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eCeftriaxone(n\\u0026thinsp;=\\u0026thinsp;56)\\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 \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003emeningitis\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e24 (42.86)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e16 (28.57)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e16 (28.57)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003enonmeningitis\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e45 (80.36)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e5 (8.93)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e6 (10.71)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eErythromycin(n\\u0026thinsp;=\\u0026thinsp;56)\\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 \\u003cp\\u003e\\u003cb\\u003e1 (1.79)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0 ( 0.00)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e55 (98.21)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eLevofloxacin(n\\u0026thinsp;=\\u0026thinsp;56)\\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 \\u003cp\\u003e\\u003cb\\u003e0 ( 0.00 )\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e6 (10.71)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e50 (89.29)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eVancomycin(n\\u0026thinsp;=\\u0026thinsp;56)\\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 \\u003cp\\u003e\\u003cb\\u003e56 (100)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0 ( 0.00 )\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0 ( 0.00)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eMeropenem(n\\u0026thinsp;=\\u0026thinsp;56)\\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 \\u003cp\\u003e\\u003cb\\u003e44 (78.57)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e10 (17.86)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e2 (3.57)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eSMZ(n\\u0026thinsp;=\\u0026thinsp;53)\\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 \\u003cp\\u003e\\u003cb\\u003e10 (17.86)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e9 (16.07)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e34 (60.71)\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"4. Discussion\",\"content\":\"\\u003cp\\u003eIn this study, we analyzed the clinical symptoms and laboratory indicators in 56 children with invasive pneumococcal disease (IPD) and identified elevated procalcitonin (PCT) and neutrophil-to-lymphocyte ratio (NLR) as independent risk factors for the development of purulent meningitis. The combination predictive model, using thresholds of PCT\\u0026thinsp;\\u0026gt;\\u0026thinsp;4.215 ng/mL and NLR\\u0026thinsp;\\u0026gt;\\u0026thinsp;12.94, demonstrated strong clinical performance in predicting purulent meningitis. Additionally, meningitis strains exhibited higher resistance rates to ceftriaxone and penicillin compared to non-meningitic strains.\\u003c/p\\u003e \\u003cp\\u003eOur findings showed that sepsis was the most common manifestation of IPD, particularly among patients with oncological diseases or compromised immune function. Of the 56 children with IPD, 13 (23.21%) developed purulent meningitis. In a study by Cameron Burtond et al. [\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e], 12% of 93 children with IPD had concurrent purulent meningitis, while another study involving 377 children reported a rate of 29.8% [\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e]. These results were consistent with our findings. Furthermore, our study indicated that children with underlying diseases were more prone to developing purulent meningitis; among the 13 children with purulent meningitis, 7 (53.84%) had comorbidities: 5 with tumors (and postoperative history) and 2 with immune deficiencies, suggesting that reduced immunity may facilitate bacterial invasion of the central nervous system. Previous studies reported mortality rates in children with IPD ranging from approximately 2.5\\u0026ndash;23.5% [\\u003cspan additionalcitationids=\\\"CR14\\\" citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e]. In our cohort, the overall mortality rate was 7.14%, with 23.07% of patients with purulent meningitis, underscoring the need for clinical vigilance.\\u003c/p\\u003e \\u003cp\\u003ePCT is a propeptide glycoprotein produced by thyroid cells that rises significantly during the early stages of bacterial infection, making it a sensitive biomarker for diagnosing bacterial infections and sepsis, as well as for prognostication. Studies have shown that PCT levels correlate with the severity of pneumonia in patients with \\u003cem\\u003eS.pneumoniae\\u003c/em\\u003e infection, and patients with bacteremia exhibited even higher levels of PCT, establishing PCT as a sensitive indicator for predicting \\u003cem\\u003eS.pneumoniae\\u003c/em\\u003e bacteremia [16]. A prospective cohort study of 1,821 febrile infants aged\\u0026thinsp;\\u0026le;\\u0026thinsp;60 days demonstrated that combination of PCT with urine analysis and neutrophil evaluation yielded a negative predictive value of 99.6% for bacterial meningitis [\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e]. Our study reinforced the diagnostic value of PCT in IPD and highlight its potential role as a high-risk factor for bacterial meningitis. Moreover, the combination of PCT and NLR enhances predictive accuracy in these patients. NLR, calculated as the ratio of absolute neutrophil count to absolute lymphocyte count, reflects the body\\u0026rsquo;s immune response to various pathogenic agents. Previous studies have already suggested a link between NLR and sepsis outcomes, and investigated its utility in predicting the prognosis of bacterial meningitis [\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e]. Our results add evidence supporting the use of NLR as a diagnostic tool in IPD-associated bacterial meningitis in children.\\u003c/p\\u003e \\u003cp\\u003eAdditionally, our study found that the sensitivity of non-meningitic IPD strains to penicillin was approximately 19.64%, compared to 17.85% in meningitic strains. In contrast, although the overall sensitivity rate to ceftriaxone was about 80.36%, meningitic strains had a markedly lower sensitivity rate of 42.86%. A prior analysis involving 54 cases of pediatric IPD reported that resistance to penicillin and ceftriaxone among \\u003cem\\u003eS.pneumoniae\\u003c/em\\u003e reached up to 24.5% and has been increasing over time [\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e]. Conversely, Rajalakshmi Arjun et al. [\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e] observed penicillin and ceftriaxone sensitivity rates of 80% and 82%, respectively. in IPD patients. These discrepancies reflected regional variations in antibiotic susceptibility, potentially influenced by widespread use of penicillins and cephalosporins in children, which could drive drug resistance. Therefore, for children with IPD complicated by purulent meningitis, initial empirical treatment should be approached with caution due to potential resistance to penicillin and ceftriaxone.\\u003c/p\\u003e \\u003cp\\u003eThis study has several limitations. First, it was a single-center cohort study with a relatively small sample size. Second, some data were missing during collection, which may have introduced bias. Future research should include multi-center, prospective, randomized controlled trials to confirm these findings.\\u003c/p\\u003e\"},{\"header\":\"5. Conclusion\",\"content\":\"\\u003cp\\u003eour study demonstrates that PCT(\\u0026gt;\\u0026thinsp;4.215 ng/mL) and NLR (\\u0026gt;\\u0026thinsp;12.94) are independent risk factors for developing purulent meningitis in children with invasive pneumococcal disease. These markers should be considered in the clinical diagnosis and management of affected patients. Furthermore, given the high resistance rates of \\u003cem\\u003eS.pneumoniae\\u003c/em\\u003e meningitis strains to penicillin and ceftriaxone, clinicians should consider alternative antibiotics when treating these cases.\\u003c/p\\u003e\"},{\"header\":\"Abbreviations\",\"content\":\"\\u003cdiv class=\\\"DefinitionList\\\"\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eIPD\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eInvasive Pneumococcal Disease\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eWBC\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003ewhite blood cells\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eNE\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eneutrophil\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eLY\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003elymphocyte\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eNLR\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eRatio of neutrophil count to lymphocyte count\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eCRP\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eC-reactive protein\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eHGB\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eHemoglobin\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003ePCT\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eProcalcitonin\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eAST\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eGlutamic-pyruvic transaminase\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eALT\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eGlutamic oxaloacetic transaminase\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eALB\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eAlbumin\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eLDH\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eL-Lactate Dehydrogenase\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eNa\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eNatrium\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eBUN\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eBlood Urea Nitrogen\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eScr\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eSilicon Controlled Rectifier\\u0026zwnj;\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eFib\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eFibrinogen\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eFDP\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eFibrinogen\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eAPTT\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eActivated Partial Thromboplastin Time\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eTT\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eThrombin time\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003ePT\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eProthrombin time\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eROC\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eReceiver operating characteristic\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eAUC\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eUnder the curve\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003c/div\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eEthics approval and consent to participate\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe studies involving human participants were reviewed and approved by the Ethical Committee of Xiamen Children\\u0026apos;s Hospital. The participants\\u0026apos; legal guardian or next of kin provided written informed consent for participation in this study. Informed consent has been obtained from the participants, their parents and legally authorized representatives in this study.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent for publication\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAvailability of data and materials\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNo datasets were generated or analysed during the current study.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCompeting Interests\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors declare no competing interests.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis study was supported by Xiamen City Health Guidance Project (Grant No.3502Z20224ZD1268 and No.3502Z2024ZD1277]\\u0026nbsp;、Construction of Key Clinical Disciplines at Xiamen Children\\u0026apos;s Hospital (Fudan University Affiliated Children\\u0026apos;s Hospital Xiamen Hospital) ((Grant No. XE2022-YNPY-B03) and Xiamen Children\\u0026apos;s Hospital 1125 Talent Program.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthors\\u0026apos; contributions\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eYM and LZ were responsible for data analysis and drafted the manuscript. SD and ZZ contributed to designing the study and critically revised the manuscript for significant intellectual content. YL and LG were involved in patient follow-up and data collection. All authors have approved the final version of the manuscript for publication. Each author participated sufficiently in the work to be responsible for the content.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgements\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eClinical trial number\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eFerreira-Coimbra J, Sarda C, Rello J. Burden of Community-Acquired Pneumonia and Unmet Clinical Needs. Adv Ther. 2020 Apr;37(4):1302-1318. doi: 10.1007/s12325-020-01248-7. Epub 2020 Feb 18. PMID: 32072494; PMCID: PMC7140754.\\u003c/li\\u003e\\n\\u003cli\\u003eLi Q, Cheng J, Wu Y, Wang Z, Luo S, Li Y, Tian X, Zhang G, Chen D, Luo Z. Effects of Delayed Antibiotic Therapy on Outcomes in Children with Streptococcus pneumoniae Sepsis. Antimicrob Agents Chemother. 2019 Aug 23;63(9):e00623-19. doi: 10.1128/AAC.00623-19. PMID: 31262764; PMCID: PMC6709508.\\u003c/li\\u003e\\n\\u003cli\\u003eOuseph MM, Simons M, Treaba DO, Yakirevich E, Green PH, Bhagat G, Moss SF, Mangray S. Fatal Streptococcus pneumoniae Sepsis in a Patient With Celiac Disease-Associated Hyposplenism. ACG Case Rep J. 2016 Oct 12;3(4):e140. doi: 10.14309/crj.2016.113. PMID: 27761478; PMCID: PMC5064423.\\u003c/li\\u003e\\n\\u003cli\\u003eErdem I, Elbasan Omar S, Ali RK, Gunes H, Topkaya AE. Streptococcus pneumoniae sepsis as the initial presentation of systemic lupus erythematosus. Int J Gen Med. 2016 Sep 8; 9:315-7. doi: 10.2147/IJGM.S105070. PMID: 27660485; PMCID: PMC5019324.\\u003c/li\\u003e\\n\\u003cli\\u003eAsner SA, Agyeman PKA, Gradoux E, Posfay-Barbe KM, Heininger U, Giannoni E, Crisinel PA, Stocker M, Bernhard-Stirnemann S, Niederer-Loher A, Kahlert CR, Hasters P, Relly C, Baer W, Aebi C, Schlapbach LJ, Berger C. Burden of Streptococcus pneumoniae Sepsis in Children After Introduction of Pneumococcal Conjugate Vaccines: A Prospective Population-based Cohort Study. Clin Infect Dis. 2019 Oct 15;69(9):1574-1580. doi: 10.1093/cid/ciy1139. PMID: 30601988.\\u003c/li\\u003e\\n\\u003cli\\u003eGreenberg D, Shinwell ES, Yagupsky P, Greenberg S, Leibovitz E, Mazor M, Dagan R. A prospective study of neonatal sepsis and meningitis in southern Israel. Pediatr Infect Dis J. 1997 Aug;16(8):768-73. doi: 10.1097/00006454-199708000-00008. PMID: 9271039.\\u003c/li\\u003e\\n\\u003cli\\u003eGroeneveld NS, Olie SE, Visser DH, Snoek L, van de Beek D, Brouwer MC, Bijlsma MW; NOGBS study group:. Cerebrospinal fluid inflammatory markers to differentiate between neonatal bacterial meningitis and sepsis: A prospective study of diagnostic accuracy. Int J Infect Dis. 2024 May; 142:106970. doi: 10.1016/j.ijid.2024.02.013. Epub 2024 Feb 21. PMID: 38395221.\\u003c/li\\u003e\\n\\u003cli\\u003eBansal N, Sukhwani KS, Ganta V. Predictors of mortality in patients with Gram-Negative Bacilli (GNB) blood stream infections (BSI): multicentre data from India. Infect Dis (Lond). 2025 Jun;57(6):518-525. doi: 10.1080/23744235.2025.2453581. Epub 2025 Jan 13. PMID: 39804585.\\u003c/li\\u003e\\n\\u003cli\\u003eZhu Liang, Li Wenhui, Wang Xinhong, et al. Multi-center clinical study on 1,138 cases of invasive pneumococcal disease in children from 2012 to 2017 [J]. Chinese Journal of Pediatrics, 2018, 56(12): 915-922\\u003c/li\\u003e\\n\\u003cli\\u003eXu Y, Zhou X, Zheng W, Cui B, Xie C, Liu Y, Qin X, Liu J. Serotype distribution, antibiotic resistance, multilocus sequence typing, and virulence factors of invasive and non-invasive Streptococcus pneumoniae in Northeast China from 2000 to 2021. Med Microbiol Immunol. 2024 Jul 2;213(1):12. doi: 10.1007/s00430-024-00797-w. PMID: 38954065..\\u003c/li\\u003e\\n\\u003cli\\u003eIshikawa K, Matsuo T, Suzuki T, Kawai F, Uehara Y, Mori N. Penicillin- and third-generation cephalosporin-resistant strains of Streptococcus pneumoniae meningitis: Case report and literature review. J Infect Chemother. 2022 May;28(5):663-668. doi: 10.1016/j.jiac.2022.01.021. Epub 2022 Feb 8. PMID: 35144879.\\u003c/li\\u003e\\n\\u003cli\\u003eBurton C, Webb R, Anglemyer A, Humphrey A, Tuatoo A, Best E. Severe Invasive Pneumococcal Disease Caused by Serotype 19A in Children Under Five Years in Tāmaki Makaurau Auckland, Aotearoa New Zealand. Pediatr Infect Dis J. 2025 Jan 1;44(1):90-96. doi: 10.1097/INF.0000000000004528. Epub 2024 Sep 11. PMID: 39259857; PMCID: PMC11627305.\\u003c/li\\u003e\\n\\u003cli\\u003eXu Y, Wang Q, Yao KH, et al. Clinical characteristics and serotype distribution of invasive pneumococcal disease in pediatric patients from Beijing, China. Eur J Clin Microbiol Infect Dis. 2021; 40:1833\\u0026ndash;1842. doi: 10.1007/s10096-021-04238-x\\u003c/li\\u003e\\n\\u003cli\\u003eManoharan A, Manchanda V, Balasubramanian S, et al. Invasive pneumococcal disease in children aged younger than 5 years in India: a surveillance study. Lancet Infect Dis. 2017; 17:305\\u0026ndash;312. doi: 10.1016/S1473-3099(16)30466-2.\\u003c/li\\u003e\\n\\u003cli\\u003eYildirim I, Shea KM, Little BA, et al. Members of the Massachusetts Department of Public Health. Vaccination, underlying comorbidities, and risk of invasive pneumococcal disease. Pediatrics. 2015; 135:495\\u0026ndash;503. doi: 10.1542/peds.2014-2426 \\u003c/li\\u003e\\n\\u003cli\\u003eAkagi T, Nagata N, Miyazaki H, Harada T, Takeda S, Yoshida Y, Wada K, Fujita M, Watanabe K. Procalcitonin is not an independent predictor of 30-day mortality, albeit predicts pneumonia severity in patients with pneumonia acquired outside the hospital. BMC Geriatr. 2019 Jan 7;19(1):3. doi: 10.1186/s12877-018-1008-8. PMID: 30616612; PMCID: PMC6323702.\\u003c/li\\u003e\\n\\u003cli\\u003ePereira JM, Teixeira-Pinto A, Bas\\u0026iacute;lio C, Sousa-Dias C, Mergulh\\u0026atilde;o P, Paiva JA. Can we predict pneumococcal bacteremia in patients with severe community-acquired pneumonia? J Crit Care. 2013 Dec;28(6):970-4. doi: 10.1016/j.jcrc.2013.04.016. PMID: 24216331.\\u003c/li\\u003e\\n\\u003cli\\u003eKuppermann N, Dayan PS, Levine DA, Vitale M, Tzimenatos L, Tunik MG, Saunders M, Ruddy RM, Roosevelt G, Rogers AJ, Powell EC, Nigrovic LE, Muenzer J, Linakis JG, Grisanti K, Jaffe DM, Hoyle JD Jr, Greenberg R, Gattu R, Cruz AT, Crain EF, Cohen DM, Brayer A, Borgialli D, Bonsu B, Browne L, Blumberg S, Bennett JE, Atabaki SM, Anders J, Alpern ER, Miller B, Casper TC, Dean JM, Ramilo O, Mahajan P; Febrile Infant Working Group of the Pediatric Emergency Care Applied Research Network (PECARN). A Clinical Prediction Rule to Identify Febrile Infants 60 Days and Younger at Low Risk for Serious Bacterial Infections. JAMA Pediatr. 2019 Apr 1;173(4):342-351. doi: 10.1001/jamapediatrics.2018.5501. PMID: 30776077; PMCID: PMC6450281.\\u003c/li\\u003e\\n\\u003cli\\u003eChen Q, Zhang M, Xia Y, Deng Y, Yang Y, Dai L, Niu H. Dynamic risk stratification and treatment optimization in sepsis: the role of NLPR. Front Pharmacol. 2025 Apr 2; 16:1572677. doi: 10.3389/fphar.2025.1572677. PMID: 40242435; PMCID: PMC11999927.\\u003c/li\\u003e\\n\\u003cli\\u003ePhuong LK, Cheung A, Templeton T, Abebe T, Ademi Z, Buttery J, Clark J, Cole T, Curtis N, Dobinson H, Shahul Hameed N, Hernstadt H, Ojaimi S, Sharp EG, Sinnaparajar P, Wen S, Daley A, McMullan B, Gwee A. Epidemiology of childhood invasive pneumococcal disease in Australia: a prospective cohort study. Arch Dis Child. 2024 Dec 13;110(1):52-58. doi: 10.1136/archdischild-2024-327497. PMID: 39322267.\\u003c/li\\u003e\\n\\u003cli\\u003eRodr\\u0026iacute;guez WC, Mora-Salamanca AF, Santacruz-Arias J, Alvarado-Gonzalez JC, Saavedra L, Pinz\\u0026oacute;n-Redondo H, Alvis Guzm\\u0026aacute;n NR, Alvis-Zakzuk NR, Zakzuk J. Pediatric invasive pneumococcal disease in Bol\\u0026iacute;var, Colombia: a descriptive cross-sectional study. Infez Med. 2024 Dec 1;32(4):506-517. doi: 10.53854/liim-3204-9. PMID: 39660158; PMCID: PMC11627489.\\u003c/li\\u003e\\n\\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\":\"info@researchsquare.com\",\"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\":\"Invasive pneumococcal disease, Purulent meningitis, Children, Risk factors, Bacterial resistance\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-6864829/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-6864829/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003e\\u003cstrong\\u003eObjective: \\u003c/strong\\u003eTo analyze the risk factors and bacterial resistance associated with invasive pneumococcal disease (IPD) complicated by purulent meningitis in children, with the goal of enhancing early diagnosis and treatment, preventing complications, and improving patient outcomes.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eMethods:\\u003c/strong\\u003e The study involved 56 pediatric patients with IPD and admitted to our hospital from January 2016 and December 2024. Patients were stratified into two groups based on the presence or absence of purulent meningitis. Clinical characteristics, laboratory parameters, and bacterial resistance profiles were collected and analyzed using univariate and multivariate methods to identify risk factors. A risk prediction model based on logistic regression was developed, and its performance was assessed via the area under the receiver operating characteristic (ROC) curve.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eResults:\\u003c/strong\\u003e The study cohort comprised 27 males and 29 females, including 13 patients with purulent meningitis and 43 without. A significant seasonal distribution was noted, with 58.93% (33/56) of cases occurring between November and January. Underlying diseases were present in 53.84% (7/13) of the purulent meningitis group compared to 4.65% (2/43) in the non-meningitic group (P \\u0026lt; 0.001). Univariate analysis of laboratory indicators revealed significant intergroup differences in eight parameters(NLR, PCT, Alb, Na, Scr,D-Dimer, FDP, TT) (P \\u0026lt; 0.05). Further, multivariate analysis identified PCT (OR = 1.209, 95% CI: 1.023–1.428, P = 0.026) and NLR (OR = 1.210, 95% CI: 1.010–1.449, P = 0.038) as independent risk factors for IPD complicated by purulent meningitis. The curve analysis results indicate that PCT\\u0026gt;4.215 ng/ml and NLR\\u0026gt;12.94 individually predicted the presence of purulent meningitis with AUCs of 0.863 and 0.606.The AUC for the model constructed with PCT \\u0026gt; 4.215 ng/ml and NLR \\u0026gt; 12.94 was 0.885, indicating that its predictive value for combined purulent meningitis is higher than that of the individual indicators, with sensitivity of 84.60% and specificity of 86%. Additionally, drug resistance analysis of 56 \\u003cem\\u003eStreptococcus pneumoniae\\u003c/em\\u003e isolates revealed penicillin resistance rates of 73.21% (41/56) in meningitic strains versus 60.71% (34/56) in non-meningitic strains, and ceftriaxone resistance rates of 28.57% (16/56) versus 10.71% (6/56), respectively.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConclusion: \\u003c/strong\\u003eElevated PCT and NLR levels constitute independent risk factors for IPD complicated by purulent meningitis. The combined predictive model based on PCT \\u0026gt; 4.215 ng/ml and NLR \\u0026gt; 12.94 demonstrates robust clinical utility. Furthermore, the higher resistance rates of pneumococcal meningitis isolates to ceftriaxone and penicillin warrant heightened clinical attention.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Risk Factors and Bacterial Resistance in Pediatric Invasive Pneumococcal Disease Complicated by Purulent Meningitis\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-06-23 05:29:44\",\"doi\":\"10.21203/rs.3.rs-6864829/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"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\":\"b093bd3f-2bb3-45d6-b0cc-322bdab875aa\",\"owner\":[],\"postedDate\":\"June 23rd, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2025-09-24T16:53:41+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2025-06-23 05:29:44\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-6864829\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-6864829\",\"identity\":\"rs-6864829\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}