{"paper_id":"4747455c-972c-4cd4-be0f-30443b029e2d","body_text":"A correlational study of lipopolysaccharide-binding protein on the prognosis of septic patients in the emergency department | 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 A correlational study of lipopolysaccharide-binding protein on the prognosis of septic patients in the emergency department Ying Zhang, Ye Zhang, Lei Zhen, Jia Wang, Le Hu, Hongmeng Dong, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4209402/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 3 You are reading this latest preprint version Abstract Objective To explore the predictive value of lipopolysaccharide-binding protein (LBP) in assessing the risk of death in septic patients, to provide a reference for clinical work. Methods Data from 168 septic patients who were admitted to the emergency department of Beijing Chaoyang Hospital from September 2021 to September 2022 were retrospectively analyzed. SPSS25.0 software was used for data analysis and MedCalc 22.013 was applied to generate receiver operating characteristics (ROC) curves. Results A total of 54 patients were included in the non-survival group and 114 were included in the survival group. Age, respiratory rate, Acute Physiology and Chronic Health Evaluation II (APACHE II) score, Sequential Organ Failure Assessment (SOFA) score, LBP and lactate values were higher and the Glasgow Coma Scale (GCS) score and albumin were lower in the non-survival group than in the surviving group (all P < 0.001). Multivariate regression analysis showed that the APACHE II score, SOFA score, LBP and albumin were independent risk factors affecting the prognosis of septic patients. The area under the receiver operating characteristic curve (AUC) values were 0.801, 0.874 and 0.82 for LBP, APACHE II score and SOFA score, respectively, which better predicted the prognosis of septic patients. The AUC value of LBP and APACHE II score was 0.936, which was better than that of APACHE II score, SOFA score and LBP alone (P < 0.001). APACHE II + LBP had a sensitivity of 0.963 and a specificity of 0.798. Conclusion LBP is an independent risk factor affecting the outcome of septic patients and has a moderate predictive power of mortality outcome. APACHE II + LBP score has better predictive performance. lipopolysaccharide-binding protein LBP sepsis mortality prognosis Figures Figure 1 Introduction Sepsis — a clinical syndrome of physiological, pathological and biochemical abnormalities caused by infection — is one of the major causes of death and increased medical costs in modern intensive care units and is a major public health problem in society [ 1 , 2 ] . It is a regulated immune response to infection, which leads to life-threatening organ dysfunction. A recent meta-analysis showed that the incidence of sepsis among hospitalized patients was significantly higher in 2020 than in 2008, and the statistical incidence of sepsis was 189 cases/100,000 people/year, with about 26.7% deaths [ 3 ] . In 2017, the World Health Assembly and the World Health Organization designated sepsis as a global health priority [ 4 ] . Sepsis is a common infectious disease in the emergency department (ED), and despite the increasing medical technology, its mortality rate remains high. Recognizing early signs and symptoms of severe sepsis is of great significance for clinical guidance, which can help clinicians to better implement clinical diagnosis and treatment and reduce disability and mortality. A previous review classified 258 biomarkers based on their pathophysiological roles and found that only a few biomarkers, including lipopolysaccharide-binding protein (LBP), were particularly relevant to the pathophysiology of sepsis [ 5 ] . LBP is a protein encoded by the LBP gene in the human body, which is mainly produced in epithelial cells in the liver, lung and gastrointestinal tract. It is an acute serum protein whose plasma concentration increases exponentially during an acute inflammatory response and plays an important role in the innate immune response [ 6 , 7 ] . LBP is considered a carrier of lipopolysaccharide (LPS). LPS, also known as endotoxin, is an important component of the cell envelope of most Gram-negative bacteria. LPS is released into the blood during the acute phase of Gram-negative bacterial infection and causes the host innate immune response through the toll-like receptor 4 (TLR 4) pathway [ 8 ] . Elevated LPS concentrations in the blood trigger a pathophysiological cascade in sepsis and septic shock [ 9 ] . LBP and LPS binding promote the transfer of LPS to the sensing receptor differentiation cluster 14 (CD14), TLR 4/myeloid differentiation factor 2 (MD2) complex, thus initiating the inflammatory response [ 10 , 11 , 12 ] . Herein, we evaluated serum LBP levels measured within 24 hours of admission and explored the diagnostic efficacy of LBP on the outcomes of septic patients by comparing baseline data, Acute Physiology and Chronic Health Evaluation II (APACHE II) scores, Sequential Organ Failure Assessment (SOFA) scores, Glasgow Coma Scale (GCS) scores and laboratory tests. Materials and methods Collection of patient baseline data Data from 168 septic patients who were admitted to the ED of Beijing Chaoyang Hospital from September 2021 to September 2022 were retrospectively analyzed. Patient basic information was collected through the hospital’s inpatient electronic information system, including gender, age, medical history, hematological test results, etc. This study was approved by the Ethics Committee of the Beijing Chaoyang Hospital (approval No. 2021-KE-636). Inclusion and exclusion criteria The inclusion criteria were as follows: (1) patients aged ≥ 18 years; (2) septic patients. The exclusion criteria were as follows: (1) autoimmune diseases; (2) pregnant and lactating women; (3) immunotherapy (long-term use of glucocorticoids or immunosuppressants); (4) tumor; (5) long-term dialysis patients. Sepsis was diagnosed according to the Third International Consensus Definitions. Sepsis was defined as the life-threatening organ dysfunction caused by a dysregulated host response to infection and an acute change in total SOFA score ≥ 2 points consequent to the infection [ 1 ] . Measurement of LBP, C-reactive protein (CRP) and procalcitonin (PCT) (1) Blood samples were drawn for biomarker testing immediately after the patient was admitted to the ED. (2) LBP was tested using the human enzyme-linked immunosorbent assay kit (ab213805, Abcam, UK). (3) The concentration of PCT was determined using an HR201 immunoquantification analyzer (Shenzhen Huaakui Technology Co., Ltd., Shenzhen, China). (4) CRP was detected using an aristo automatic orbital specific protein analyzer (Shenzhen Guoai Biotechnology Co., Ltd., Goldsite, Shenzhen, China). (5) A routine complete blood count (absolute neutrophil and lymphocyte count) was determined using an XS-800i automatic blood analyzer (Sysmex, Kobe, Japan). Statistical analysis All statistical analyses were performed using SPSS25.0 software. SPSS25.0 and MedCalc 22.013 were used to generate the receiver operating characteristic (ROC) curves. Normally distributed continuous data were expressed as mean ± standard deviation and compared using the t-test. Continuous variables with non-normal distribution were presented as the median and interquartile range (IQR: 25%-75%) and compared using the Wilcoxon rank-sum test. Count data were expressed as percentages and analyzed using the chi-square test. Univariate and multivariate logistic regressions were used for independent predictor analysis, and the ROC curve analysis was performed to evaluate the predictive value of the regression model. P < 0.05 was considered statistically significant. Results Patient baseline characteristics A total of 168 septic patients who were admitted to the ED were recruited, including 54 patients in the non-survival group (death group) and 114 patients in the survival group (discharge group). There were 101 males and 67 females, with no significant difference in gender between the two groups (P = 0.604). The median age of the survival was 69.0 (63, 80) and that of the non-survival group was 83 (74, 87), which differed significantly (P<0.001). Meanwhile, SOFA and APACHE II scores were significantly higher in the death group, and GCS scores were significantly higher in the survival group (P<0.001). The non-survival group exhibited higher respiratory and heart rates and a lower diastolic systolic blood pressure than the survival group, with statistically significant differences (all P<0.05). The incidence of coronary heart disease was higher in the death group than in the discharge group, with a statistically significant difference (P<0.05). However, no significant difference in the occurrence of diabetes, hypertension and chronic obstructive pulmonary disease was found between the two groups (all P>0.05). Patient baseline characteristics are summarized in Table 1. Laboratory data analysis LBP and lactate were higher in the death group than in the discharge group (P<0.001). Albumin (ALB) levels were lower in the death group than in the survival group, with significant differences (P<0.001). In addition, the white blood cell count, absolute neutrophil value, CRP and blood urea nitrogen were higher in the death group than in the survival group, with a statistically significant difference (P<0.05). However, no significant difference in absolute PCT, sodium, potassium and lymphocytes was detected between the two groups (P>0.05). More detailed results are shown in Table 2. Multivariate regression analysis We performed logistic multivariate regression analysis on indicators that showed significant results from univariate regression analysis. The results revealed that the APACHE II score (odds ratio [OR] = 1.264, 95% confidence interval [CI]: 1.009-1.584, P = 0.042), SOFA score (OR = 1.509, 95% CI: 1.177-1.936, P = 0.001), LBP (OR = 1.235, 95% CI: 1.109-1.376, P<0.001) and ALB (OR = 0.732, 95% CI: 0.594-0.901, P=0.003) were independent risk factors affecting the prognosis of patients with sepsis (Table 3). ROC curve analysis The ROC curve was plotted to evaluate the diagnostic performance of various statistically significant indicators in logistic multivariate regression analysis. The ROC curve analysis revealed that area under the curve (AUC) values for the APACHE II score, SOFA score, LBP, ALB, APACHE II+LBP and SOFA+LBP were 0.874 (95% CI: 0.821-0.926), 0.82 (95%CI: 0.754-0.886), 0.801 (95% CI: 0.736-0.866), 0.781 (95% CI: 0.711-0.852), 0.936 (95% CI: 0.9-0.971) and 0.889 (95% CI: 0.836-0.942), respectively. Notably, the AUC values of the APACHE II score, SOFA score, LBP, APACHE II+LBP and SOFA+LBP were all greater than 0.8, among which the AUC values of APACHE II score and LBP were the largest (AUC = 0.936). APACHE II+LBP and LBP had the highest sensitivity (both 0.963), while SOFA+LBP had the highest specificity (0.939). The cut-off values, Youden index and ROC plots of each index are shown in Table 4 and Figure 1. Table 1 Baseline characteristics of the study population APACHE II, Acute Physiology and Chronic Health Evaluation; SOFA, Sequential Organ Failure Assessment; GCS, Glasgow Coma Scale; P<0.05 indicates statistical significance. Table 2 Laboratory variables of the study population WBC, white blood cell; LYM, lymphocyte; NEU, neutrophil; Abs, absolute value; CRP, C-reactive protein; PCT, procalcitonin; LBP, lipopolysaccharide-binding protein; Lac, lactic acid; BUN, blood urea nitrogen; Na, serum sodium; K, serum potassium; ALB, albumin; P < 0:05 indicates statistical significance. Table 3 Multivariate regression analysis APACHE II, Acute Physiology and Chronic Health Evaluation; SOFA, Sequential Organ Failure Assessment; GCS, Glasgow Coma Scale; CHD, coronary heart disease; SE, standard error; df, degree of freedom; CI, confidence interval; LL, lower limit; UL, upper limit; Sig., statistically significant results. Table 4 Receiver operating characteristic curve analysis AUC, area under the curve; CI, confidence interval; APACHE II, Acute Physiology and Chronic Health Evaluation; SOFA, Sequential Organ Failure Assessment; LBP, lipopolysaccharide-binding protein; ALB, albumin Discussion With the high mortality rate of sepsis and great harm to individuals, families and society, predicting the prognosis of sepsis after its early recognition is urgent to achieve effective prevention, diagnosis and treatment. Guidelines highlight the importance of early intervention in patients with sepsis; early identification and appropriate management in the first hours of sepsis discovery can improve outcomes in septic patients [ 13 ] . However, the traditional microbial culture has a long time and a low positive rate, which cannot provide help for early clinical diagnosis and treatment. Only a few biomarkers in the management of septic patients have been extensively studied, with only a handful evaluated in large or replicated studies. Accumulating data show that the currently known biomarkers have limited predictive power for sepsis, including sensitivity and specificity [ 14 , 15 , 16 ] . LBP and sepsis have been widely studied in recent years, and the results show that LBP plays a role in the diagnosis of sepsis. However, a previous meta-analysis of LBP and sepsis showed weak sensitivity and specificity for the diagnosis of sepsis, and LBP may not be recommended as a single biomarker for clinical use; however, the number of included studies was small, which warrants further studies to elucidate this proposition [ 17 ] . The early prediction of sepsis prognosis is necessary to understand its severity and adopt more effective interventions. Currently, there are few studies on the predictive value of LBP for the prognosis of patients with sepsis. Therefore, the present single-center study was conducted to evaluate the predictive value of LBP. LBP is the carrier of LPS (also known as endotoxin). As an important component of the cell envelope of most Gram-negative bacteria, LPS can establish a permeability barrier on the cell surface to resist the entry of antimicrobial drugs and plays an important role in the resistance of Gram-negative bacteria to antimicrobial drugs. Meanwhile, LPS plays a key role in bacterial-host interactions by regulating the response of the host immune system. During cell death or cell division in Gram-negative bacteria, the rupture of bacterial cell membranes releases endotoxin [ 18 ] . Persistent low levels of circulating LPS may be associated with the development of metabolic diseases such as insulin resistance, type 2 diabetes, atherosclerosis and cardiovascular disease, while high concentrations of LPS in systemic circulation can lead to septic shock. The body has different responses to LPS with different symptoms. Mild reactions may result in cough, chest tightness and fever, while severe reactions can lead to multiple organ failure, shock and even death [ 19 , 20 , 21 ] . The normal serum LBP concentration is 5–10 µg/mL, reaching a median peak level of 30–40 µg/ml, which is approximately 7-fold during sepsis [ 22 ] . One study showed that LBP was significantly higher in septic patients than in non-septic patients [ 23 ] . The immune function of circulating LBP is concentration-dependent, below normal LBP enhances LPS-induced cell activation, phagocytosis and clearance, and may promote inflammation at the local infection site. Contrarily, at high concentrations, LBP has immunosuppressive effects, attenuates the release of proinflammatory cytokines and alleviates LPS-induced systemic inflammatory response [ 10 , 11 ] . In addition to septic patients, LBP was also found in non-septic patients, such as trauma, cardiac insufficiency, and renal insufficiency patients [ 24 , 25 , 26 ] . LBP can also identify the partial cell surface component of Gram-positive bacteria [ 27 ] . The current study found that the APACHE II score, SOFA score, LBP, and ALB were independent risk factors affecting the prognosis of septic patients in the ED. An increase in APACHE II, SOFA and LBP values increases the risk of death, while an increase in ALB values decreases the risk of death.The ROC curve analysis showed that APACHE II, SOFA and LBP were better predictors of the prognosis of septic patients, of which APACHE II was the best predictor, and the diagnostic effect of ALB was relatively poor. APACHE II + LBP had better predictive performance than APACHE II, SOFA, LBP and ALB alone, the difference was statistically significant (P < 0.001). For single indicator prediction, LBP was more sensitive and ALB was more specific. A combination of two indicators showed that APACHE II + LBP had higher sensitivity and SOFA + LBP had higher specificity. Jabandziev et al showed that polymorphism analysis of five genes, including LBP, bactericidal/permeability-increasing protein (BPI), TLR, heat shock protein 70 (HSP70) and interleukin-6 (IL-6), could be used as predictors of childhood sepsis prognosis [ 28 ] . More recently, Jung et al demonstrated that LBP is a feature of community-acquired pneumonia (CAP) diagnosis and a combination of LBP, soluble Fas (sFas), TNF-related apoptosis-inducing ligand (TRAIL), IL-6 and IL-8 could distinguish between the severity of pneumonia [ 29 ] . However, some studies showed that LBP and PCT at admission had no significance in predicting prognosis in patients with sepsis and septic shock [ 30 , 31 ] . Therefore, further studies are needed to validate the predictive significance of LBP in septic patients, and assessment of the combined prediction effect may perhaps be more valuable. Nonetheless, this study has several limitations. Firstly, the limited sample size may affect the conclusion to some extent. Secondly, since this is a single-center retrospective study, the conclusions drawn are not necessarily applicable to other hospitals or institutions. Our future study will explore the underlying molecular mechanism through which LBP affects the prognosis of sepsis patients. Conclusion In summary, LBP, APACHE II score and SOFA score were independent predictors of outcomes in critically ill patients in the ED. LBP is a reliable predictor of outcomes in critically ill patients in EDs. APACHE II + LBP had better predictive power, and the combined prediction was better in sensitivity and specificity than LBP alone. Declarations Author Contribution Ying Zhang wrote the main manuscript text and all authors reviewed the manuscript. Acknowledgments The authors would like to thank all the individuals for their expertise and assistance throughout all aspects of our study.Funding from the Shijingshan District medical key support specialty construction foundation is gratefully acknowledged. Declaration of conflicting interests The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article. Funding The author(s) received no financial support for the research, authorship and/or publication of this article. Ethical approval The study was approved by the Ethics Committee of Beijing Chao-Yang Hospital (approval No. 2021-KE-636). References Singer M, Deutschman CS, Seymour CW, et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA. 2016;315(8):801–10. Liu D, Huang SY, Sun JH, et al. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-4209402\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":287414777,\"identity\":\"a4b932da-db07-4a6b-ab18-cfaa453d830a\",\"order_by\":0,\"name\":\"Ying Zhang\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Beijing Chao-Yang Hospital\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Ying\",\"middleName\":\"\",\"lastName\":\"Zhang\",\"suffix\":\"\"},{\"id\":287414778,\"identity\":\"3137cb62-1006-4f1a-b71a-50a65dbf2717\",\"order_by\":1,\"name\":\"Ye 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Wei\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA00lEQVRIiWNgGAWjYDCCAyDC4AAPAwPzgQMfKkjTwpZ4cMYZorWASR7jw7wtROjgu32ATeJDwR0Zc/41Hw7wNjDI84sdwK9F8lwCm+QMg2c8ljPebjgguYPBcObsBPxaDM4wsN3mMTjMY3Dj7IYDhmcYEgxuE6PlD1jLmQcHEtuI1cIA0nK+h+HAQWK0SJ5hYP/ZA/SLwQ02g4MNZyQI+4XvDAOzwY8/d+wNzh9+/PlPhY08vzQBLQwM/B8gtARYpQQh5ShaD5CiehSMglEwCkYSAADCxk2LWieAzwAAAABJRU5ErkJggg==\",\"orcid\":\"\",\"institution\":\"Beijing Chao-Yang Hospital\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Bing\",\"middleName\":\"\",\"lastName\":\"Wei\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2024-04-03 02:29:15\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-4209402/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-4209402/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":54371636,\"identity\":\"e7fa43bd-ac0f-4b51-8d5b-6de0b0aa3302\",\"added_by\":\"auto\",\"created_at\":\"2024-04-09 13:15:58\",\"extension\":\"jpg\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":74793,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eReceiver operating characteristic curve of the model\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure1.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4209402/v1/8bdad2301622d47e84d16b59.jpg\"},{\"id\":54371810,\"identity\":\"fe2d6e12-2d27-4a8d-89b0-cea28df0228d\",\"added_by\":\"auto\",\"created_at\":\"2024-04-09 13:16:36\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":418609,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4209402/v1/0cd6a377-deb2-4d90-9fa0-0fcdeebf3be8.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"A correlational study of lipopolysaccharide-binding protein on the prognosis of septic patients in the emergency department\",\"fulltext\":[{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eSepsis \\u0026mdash; a clinical syndrome of physiological, pathological and biochemical abnormalities caused by infection \\u0026mdash; is one of the major causes of death and increased medical costs in modern intensive care units and is a major public health problem in society \\u003csup\\u003e[\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e]\\u003c/sup\\u003e. It is a regulated immune response to infection, which leads to life-threatening organ dysfunction. A recent meta-analysis showed that the incidence of sepsis among hospitalized patients was significantly higher in 2020 than in 2008, and the statistical incidence of sepsis was 189 cases/100,000 people/year, with about 26.7% deaths \\u003csup\\u003e[\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e]\\u003c/sup\\u003e. In 2017, the World Health Assembly and the World Health Organization designated sepsis as a global health priority \\u003csup\\u003e[\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e]\\u003c/sup\\u003e.\\u003c/p\\u003e \\u003cp\\u003eSepsis is a common infectious disease in the emergency department (ED), and despite the increasing medical technology, its mortality rate remains high. Recognizing early signs and symptoms of severe sepsis is of great significance for clinical guidance, which can help clinicians to better implement clinical diagnosis and treatment and reduce disability and mortality. A previous review classified 258 biomarkers based on their pathophysiological roles and found that only a few biomarkers, including lipopolysaccharide-binding protein (LBP), were particularly relevant to the pathophysiology of sepsis \\u003csup\\u003e[\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e]\\u003c/sup\\u003e.\\u003c/p\\u003e \\u003cp\\u003eLBP is a protein encoded by the \\u003cem\\u003eLBP\\u003c/em\\u003e gene in the human body, which is mainly produced in epithelial cells in the liver, lung and gastrointestinal tract. It is an acute serum protein whose plasma concentration increases exponentially during an acute inflammatory response and plays an important role in the innate immune response \\u003csup\\u003e[\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e]\\u003c/sup\\u003e. LBP is considered a carrier of lipopolysaccharide (LPS). LPS, also known as endotoxin, is an important component of the cell envelope of most Gram-negative bacteria. LPS is released into the blood during the acute phase of Gram-negative bacterial infection and causes the host innate immune response through the toll-like receptor 4 (TLR 4) pathway \\u003csup\\u003e[\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e]\\u003c/sup\\u003e. Elevated LPS concentrations in the blood trigger a pathophysiological cascade in sepsis and septic shock \\u003csup\\u003e[\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e]\\u003c/sup\\u003e. LBP and LPS binding promote the transfer of LPS to the sensing receptor differentiation cluster 14 (CD14), TLR 4/myeloid differentiation factor 2 (MD2) complex, thus initiating the inflammatory response \\u003csup\\u003e[\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e]\\u003c/sup\\u003e.\\u003c/p\\u003e \\u003cp\\u003eHerein, we evaluated serum LBP levels measured within 24 hours of admission and explored the diagnostic efficacy of LBP on the outcomes of septic patients by comparing baseline data, Acute Physiology and Chronic Health Evaluation II (APACHE II) scores, Sequential Organ Failure Assessment (SOFA) scores, Glasgow Coma Scale (GCS) scores and laboratory tests.\\u003c/p\\u003e\"},{\"header\":\"Materials and methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eCollection of patient baseline data\\u003c/h2\\u003e \\u003cp\\u003eData from 168 septic patients who were admitted to the ED of Beijing Chaoyang Hospital from September 2021 to September 2022 were retrospectively analyzed. Patient basic information was collected through the hospital\\u0026rsquo;s inpatient electronic information system, including gender, age, medical history, hematological test results, etc. This study was approved by the Ethics Committee of the Beijing Chaoyang Hospital (approval No. 2021-KE-636).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eInclusion and exclusion criteria\\u003c/h2\\u003e \\u003cp\\u003eThe inclusion criteria were as follows: (1) patients aged\\u0026thinsp;\\u0026ge;\\u0026thinsp;18 years; (2) septic patients. The exclusion criteria were as follows: (1) autoimmune diseases; (2) pregnant and lactating women; (3) immunotherapy (long-term use of glucocorticoids or immunosuppressants); (4) tumor; (5) long-term dialysis patients.\\u003c/p\\u003e \\u003cp\\u003eSepsis was diagnosed according to the Third International Consensus Definitions. Sepsis was defined as the life-threatening organ dysfunction caused by a dysregulated host response to infection and an acute change in total SOFA score\\u0026thinsp;\\u0026ge;\\u0026thinsp;2 points consequent to the infection \\u003csup\\u003e[\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e]\\u003c/sup\\u003e.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eMeasurement of LBP, C-reactive protein (CRP) and procalcitonin (PCT)\\u003c/h2\\u003e \\u003cp\\u003e(1) Blood samples were drawn for biomarker testing immediately after the patient was admitted to the ED. (2) LBP was tested using the human enzyme-linked immunosorbent assay kit (ab213805, Abcam, UK). (3) The concentration of PCT was determined using an HR201 immunoquantification analyzer (Shenzhen Huaakui Technology Co., Ltd., Shenzhen, China). (4) CRP was detected using an aristo automatic orbital specific protein analyzer (Shenzhen Guoai Biotechnology Co., Ltd., Goldsite, Shenzhen, China). (5) A routine complete blood count (absolute neutrophil and lymphocyte count) was determined using an XS-800i automatic blood analyzer (Sysmex, Kobe, Japan).\\u003c/p\\u003e \\u003c/li\\u003e \\u003c/span\\u003e \\u003c/ol\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec6\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eStatistical analysis\\u003c/h2\\u003e \\u003cp\\u003eAll statistical analyses were performed using SPSS25.0 software. SPSS25.0 and MedCalc 22.013 were used to generate the receiver operating characteristic (ROC) curves. Normally distributed continuous data were expressed as mean\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;standard deviation and compared using the t-test. Continuous variables with non-normal distribution were presented as the median and interquartile range (IQR: 25%-75%) and compared using the Wilcoxon rank-sum test. Count data were expressed as percentages and analyzed using the chi-square test. Univariate and multivariate logistic regressions were used for independent predictor analysis, and the ROC curve analysis was performed to evaluate the predictive value of the regression model. P\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05 was considered statistically significant.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003ePatient baseline characteristics\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eA total of 168 septic patients who were admitted to the ED were recruited, including 54 patients in the non-survival group (death group) and 114 patients in the survival group (discharge group). There were 101 males and 67 females, with no significant difference in gender between the two groups (P = 0.604). The median age of the survival was 69.0 (63, 80) and that of the non-survival group was 83 (74, 87), which differed significantly (P\\u0026lt;0.001). Meanwhile, SOFA and APACHE II scores were significantly higher in the death group, and GCS scores were significantly higher in the survival group (P\\u0026lt;0.001). The non-survival group exhibited higher respiratory and heart rates and a lower diastolic systolic blood pressure than the survival group, with statistically significant differences (all P\\u0026lt;0.05). The incidence of coronary heart disease was higher in the death group than in the discharge group, with a statistically significant difference (P\\u0026lt;0.05). However, no significant difference in the occurrence of diabetes, hypertension and chronic obstructive pulmonary disease was found between the two groups (all P\\u0026gt;0.05). Patient baseline characteristics are summarized in Table 1.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eLaboratory data analysis\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eLBP and lactate were\\u0026nbsp;higher in the death group than in the discharge group (P\\u0026lt;0.001). Albumin (ALB) levels were lower in the death group than in the survival group, with significant differences (P\\u0026lt;0.001). In addition, the white blood cell count, absolute neutrophil value, CRP and blood urea nitrogen were higher in the death group than in the survival group, with a statistically significant difference (P\\u0026lt;0.05). However, no significant difference in absolute PCT, sodium, potassium and lymphocytes was detected between the two groups (P\\u0026gt;0.05). More detailed results are shown in Table 2.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eMultivariate regression analysis\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eWe performed logistic multivariate regression analysis on indicators that showed significant results from univariate regression analysis. The results revealed that the APACHE II score (odds ratio [OR] = 1.264, 95% confidence interval [CI]: 1.009-1.584, P = 0.042), SOFA score (OR = 1.509, 95% CI: 1.177-1.936, P = 0.001), LBP (OR = 1.235, 95% CI: 1.109-1.376, P\\u0026lt;0.001) and ALB (OR = 0.732, 95% CI: 0.594-0.901, P=0.003) were independent risk factors affecting the prognosis of patients with sepsis (Table 3).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eROC curve analysis\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe ROC curve was plotted to evaluate the diagnostic performance of various statistically significant indicators in logistic multivariate regression analysis. The ROC curve analysis revealed that area under the curve (AUC) values for the APACHE II score, SOFA score, LBP, ALB, APACHE II+LBP and SOFA+LBP were 0.874 (95% CI: 0.821-0.926), 0.82 (95%CI: 0.754-0.886), 0.801 (95% CI: 0.736-0.866), 0.781 (95% CI: 0.711-0.852), 0.936 (95% CI: 0.9-0.971) and 0.889 (95% CI: 0.836-0.942), respectively. Notably, the AUC values of the APACHE II score, SOFA score, LBP, APACHE II+LBP and SOFA+LBP were all greater than 0.8, among which the AUC values of APACHE II score and LBP were the largest (AUC = 0.936). APACHE II+LBP and LBP had the highest sensitivity (both 0.963), while SOFA+LBP had the highest specificity (0.939). The cut-off values, Youden index and ROC plots of each index are shown in Table 4 and Figure 1.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable 1\\u0026nbsp;\\u003c/strong\\u003eBaseline characteristics of the study population\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cimg src=\\\"https://myfiles.space/user_files/127393_c7e80a1c9bb65875/127393_custom_files/img1712644928.png\\\"\\u003e\\u003cbr\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAPACHE II, Acute Physiology and Chronic Health Evaluation; SOFA, Sequential Organ Failure\\u003c/p\\u003e\\n\\u003cp\\u003eAssessment; GCS, Glasgow Coma Scale; P\\u0026lt;0.05 indicates statistical significance.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable 2\\u003c/strong\\u003e Laboratory variables of the study population\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cimg src=\\\"https://myfiles.space/user_files/127393_c7e80a1c9bb65875/127393_custom_files/img1712644976.png\\\"\\u003e\\u003cbr\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eWBC, white blood cell; LYM, lymphocyte; NEU, neutrophil; Abs, absolute value; CRP, C-reactive protein; PCT, procalcitonin; LBP, lipopolysaccharide-binding protein; Lac, lactic acid; BUN, blood urea nitrogen; Na, serum sodium; K, serum potassium; ALB, albumin; P \\u0026lt; 0:05 indicates statistical significance.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable 3\\u0026nbsp;\\u003c/strong\\u003eMultivariate regression analysis\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cimg src=\\\"https://myfiles.space/user_files/127393_c7e80a1c9bb65875/127393_custom_files/img1712645015.png\\\"\\u003e\\u003cbr\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAPACHE II, Acute Physiology and Chronic Health Evaluation; SOFA, Sequential Organ Failure Assessment; GCS, Glasgow Coma Scale; CHD, coronary heart disease; SE, standard error; df, degree of freedom; CI, confidence interval; LL, lower limit; UL, upper limit; Sig., statistically significant \\u0026nbsp;results.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable 4\\u0026nbsp;\\u003c/strong\\u003eReceiver operating characteristic curve analysis\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cimg src=\\\"https://myfiles.space/user_files/127393_c7e80a1c9bb65875/127393_custom_files/img1712645053.png\\\"\\u003e\\u003cbr\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAUC, area under the curve; CI, confidence interval; APACHE II, Acute Physiology and Chronic \\u0026nbsp; \\u0026nbsp;Health Evaluation; SOFA, Sequential Organ Failure \\u0026nbsp;Assessment; LBP, lipopolysaccharide-binding protein; ALB, albumin\\u003c/p\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eWith the high mortality rate of sepsis and great harm to individuals, families and society, predicting the prognosis of sepsis after its early recognition is urgent to achieve effective prevention, diagnosis and treatment. Guidelines highlight the importance of early intervention in patients with sepsis; early identification and appropriate management in the first hours of sepsis discovery can improve outcomes in septic patients \\u003csup\\u003e[\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e]\\u003c/sup\\u003e. However, the traditional microbial culture has a long time and a low positive rate, which cannot provide help for early clinical diagnosis and treatment. Only a few biomarkers in the management of septic patients have been extensively studied, with only a handful evaluated in large or replicated studies. Accumulating data show that the currently known biomarkers have limited predictive power for sepsis, including sensitivity and specificity \\u003csup\\u003e[\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e]\\u003c/sup\\u003e. LBP and sepsis have been widely studied in recent years, and the results show that LBP plays a role in the diagnosis of sepsis. However, a previous meta-analysis of LBP and sepsis showed weak sensitivity and specificity for the diagnosis of sepsis, and LBP may not be recommended as a single biomarker for clinical use; however, the number of included studies was small, which warrants further studies to elucidate this proposition \\u003csup\\u003e[\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e]\\u003c/sup\\u003e. The early prediction of sepsis prognosis is necessary to understand its severity and adopt more effective interventions. Currently, there are few studies on the predictive value of LBP for the prognosis of patients with sepsis. Therefore, the present single-center study was conducted to evaluate the predictive value of LBP.\\u003c/p\\u003e \\u003cp\\u003eLBP is the carrier of LPS (also known as endotoxin). As an important component of the cell envelope of most Gram-negative bacteria, LPS can establish a permeability barrier on the cell surface to resist the entry of antimicrobial drugs and plays an important role in the resistance of Gram-negative bacteria to antimicrobial drugs. Meanwhile, LPS plays a key role in bacterial-host interactions by regulating the response of the host immune system. During cell death or cell division in Gram-negative bacteria, the rupture of bacterial cell membranes releases endotoxin \\u003csup\\u003e[\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e]\\u003c/sup\\u003e. Persistent low levels of circulating LPS may be associated with the development of metabolic diseases such as insulin resistance, type 2 diabetes, atherosclerosis and cardiovascular disease, while high concentrations of LPS in systemic circulation can lead to septic shock. The body has different responses to LPS with different symptoms. Mild reactions may result in cough, chest tightness and fever, while severe reactions can lead to multiple organ failure, shock and even death \\u003csup\\u003e[\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e]\\u003c/sup\\u003e. The normal serum LBP concentration is 5\\u0026ndash;10 \\u0026micro;g/mL, reaching a median peak level of 30\\u0026ndash;40 \\u0026micro;g/ml, which is approximately 7-fold during sepsis \\u003csup\\u003e[\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e]\\u003c/sup\\u003e. One study showed that LBP was significantly higher in septic patients than in non-septic patients \\u003csup\\u003e[\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e]\\u003c/sup\\u003e. The immune function of circulating LBP is concentration-dependent, below normal LBP enhances LPS-induced cell activation, phagocytosis and clearance, and may promote inflammation at the local infection site. Contrarily, at high concentrations, LBP has immunosuppressive effects, attenuates the release of proinflammatory cytokines and alleviates LPS-induced systemic inflammatory response \\u003csup\\u003e[\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e]\\u003c/sup\\u003e. In addition to septic patients, LBP was also found in non-septic patients, such as trauma, cardiac insufficiency, and renal insufficiency patients \\u003csup\\u003e[\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e]\\u003c/sup\\u003e. LBP can also identify the partial cell surface component of Gram-positive bacteria \\u003csup\\u003e[\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e]\\u003c/sup\\u003e.\\u003c/p\\u003e \\u003cp\\u003eThe current study found that the APACHE II score, SOFA score, LBP, and ALB were independent risk factors affecting the prognosis of septic patients in the ED. An increase in APACHE II, SOFA and LBP values increases the risk of death, while an increase in ALB values decreases the risk of death.The ROC curve analysis showed that APACHE II, SOFA and LBP were better predictors of the prognosis of septic patients, of which APACHE II was the best predictor, and the diagnostic effect of ALB was relatively poor. APACHE II\\u0026thinsp;+\\u0026thinsp;LBP had better predictive performance than APACHE II, SOFA, LBP and ALB alone, the difference was statistically significant (P\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001). For single indicator prediction, LBP was more sensitive and ALB was more specific. A combination of two indicators showed that APACHE II\\u0026thinsp;+\\u0026thinsp;LBP had higher sensitivity and SOFA\\u0026thinsp;+\\u0026thinsp;LBP had higher specificity.\\u003c/p\\u003e \\u003cp\\u003eJabandziev et al showed that polymorphism analysis of five genes, including LBP, bactericidal/permeability-increasing protein (BPI), TLR, heat shock protein 70 (HSP70) and interleukin-6 (IL-6), could be used as predictors of childhood sepsis prognosis \\u003csup\\u003e[\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e]\\u003c/sup\\u003e. More recently, Jung et al demonstrated that LBP is a feature of community-acquired pneumonia (CAP) diagnosis and a combination of LBP, soluble Fas (sFas), TNF-related apoptosis-inducing ligand (TRAIL), IL-6 and IL-8 could distinguish between the severity of pneumonia \\u003csup\\u003e[\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e]\\u003c/sup\\u003e. However, some studies showed that LBP and PCT at admission had no significance in predicting prognosis in patients with sepsis and septic shock \\u003csup\\u003e[\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e]\\u003c/sup\\u003e. Therefore, further studies are needed to validate the predictive significance of LBP in septic patients, and assessment of the combined prediction effect may perhaps be more valuable.\\u003c/p\\u003e \\u003cp\\u003eNonetheless, this study has several limitations. Firstly, the limited sample size may affect the conclusion to some extent. Secondly, since this is a single-center retrospective study, the conclusions drawn are not necessarily applicable to other hospitals or institutions. Our future study will explore the underlying molecular mechanism through which LBP affects the prognosis of sepsis patients.\\u003c/p\\u003e\"},{\"header\":\"Conclusion\",\"content\":\"\\u003cp\\u003eIn summary, LBP, APACHE II score and SOFA score were independent predictors of outcomes in critically ill patients in the ED. LBP is a reliable predictor of outcomes in critically ill patients in EDs. APACHE II\\u0026thinsp;+\\u0026thinsp;LBP had better predictive power, and the combined prediction was better in sensitivity and specificity than LBP alone.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003ch2\\u003eAuthor Contribution\\u003c/h2\\u003e\\u003cp\\u003eYing Zhang wrote the main manuscript text and all authors reviewed the manuscript.\\u003c/p\\u003e\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgments\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors would like to thank all the individuals for their expertise and assistance throughout all aspects of our study.Funding from the Shijingshan District medical key support specialty construction foundation is gratefully acknowledged.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eDeclaration of conflicting interests\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe author(s) received no financial support for the research, authorship and/or publication of this article.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eEthical approval\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe study was approved by the Ethics Committee of \\u0026nbsp;Beijing Chao-Yang Hospital (approval No. 2021-KE-636).\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eSinger M, Deutschman CS, Seymour CW, et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA. 2016;315(8):801\\u0026ndash;10.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLiu D, Huang SY, Sun JH, et al. Sepsis-induced immunosuppression: mechanisms, diagnosis and current treatment options. Military Med Res. 2022;9(1):56.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eFleischmann-Struzek C, Mellhammar L, Rose N, et al. Incidence and mortality of hospital and ICU-treated sepsis: results from an updated and expanded systematic review and meta-analysis. Intensive Care Med. 2020;46(8):1552\\u0026ndash;62.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eReinhart K, Daniels R, Kissoon N, et al. Recognizing Sepsis as a Global Health Priority \\u0026mdash; A WHO Resolution. N Engl J Med. 2017;377(5):414\\u0026ndash;7.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003ePierrakos C, Velissaris D, Bisdorff M, et al. Biomarkers of sepsis: time for a reappraisal. Crit Care. 2020;24(1):287.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eTsukamoto H, Takeuchi S, Kubota K, et al. Lipopolysaccharide (LPS)-binding protein stimulates CD14-dependent Toll-like receptor 4 internalization and LPS-induced TBK1-IKKε-IRF3 axis activation. J Biol Chem. 2018;293(26):10186\\u0026ndash;201.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMuta T, Takeshige K. Essential roles of CD14 and lipopolysaccharide-binding protein for activation of toll-like receptor (TLR)2 as well as TLR4 reconstitution of TLR2- and TLR4-activation by distinguishable ligands in LPS. preparations. Eur J Biochem. 2001;268(16):4580\\u0026ndash;9.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eJagtap P, Prasad P, Pateria A, et al. A Single Step In vitro Bioassay Mimicking TLR4-LPS Pathway and the Role of MD2 and CD14 Coreceptors. Front Immunol. 2020;11:5.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWand S, Klages M, Kirbach C, et al. IgM-Enriched Immunoglobulin Attenuates Systemic Endotoxin Activity in Early Severe Sepsis: A Before-After Cohort Study. PLoS ONE. 2016;11(8):e0160907.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMeng LL, Song ZC, Liu AD, et al. Effects of Lipopolysaccharide Binding Protein (LBP) Single Nucleotide Polymorphism (SNP) in Infections, Inflammatory Diseases, Metabolic Disorders and Cancers. Front Immunol. 2021;12:681810.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKumpf O, G\\u0026uuml;rtler K, Sur S, et al. A Genetic Variation of Lipopolysaccharide Binding Protein Affects the Inflammatory Response and Is Associated with Improved Outcome during Sepsis. Immunohorizons. 2021;5(12):972\\u0026ndash;82.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCochet F, Peri F. The Role of Carbohydrates in the Lipopolysaccharide(LPS)Toll-Like Receptor 4 (TLR4) Signalling. Int J Mol Sci. 2017;18(11):2318.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eEvans L, Rhodes A, Alhazzani W, et al. Surviving sepsis campaign: international guidelines for management of sepsis and septic shock. Intensive Care Med. 2021;47(11):1181\\u0026ndash;247.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBarichello T, Generoso JS, Singer M, et al. Biomarkers for sepsis: more than just fever and leukocytosis \\u0026mdash; a narrative review. Crit Care. 2022;26(1):14.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCantey JB, Lee JH. Biomarkers for the Diagnosis of Neonatal Sepsis.Clinics in Perinatology. 2021; 48(2):215\\u0026ndash;27.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eP\\u0026oacute;voa P, Coelho L, Dal-Pizzol F, et al. How to use biomarkers of infection or sepsis at the bedside: guide to clinicians. Intensive Care Med. 2023;49(2):142\\u0026ndash;53.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eChen KF, Chaou CH, Jiang JY, et al. Diagnostic accuracy of lipopolysaccharide-binding protein as biomarker for sepsis in adult patients: a systematic review and meta-analysis. PLoS ONE. 2016;11(4):e0153188.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBertani B, Ruiz N. Function and Biogenesis of Lipopolysaccharides. EcoSal Plus. 2018;8(1):101128.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eJackie J, Lau WK, Feng HT, et al. Detection of Endotoxins: From Inferring the Responses of Biological Hosts to the Direct Chemical Analysis of Lipopolysaccharides. Crit Rev Anal Chem. 2019;49(2):126\\u0026ndash;37.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLassenius MI, Pietil\\u0026auml;inen KH, Kaartinen K, et al. Bacterial endotoxin activity in human serum is associated with dyslipidemia, insulin resistance, obesity, and chronic inflammation. Diabetes Care. 2011;34(8):1809\\u0026ndash;15.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eTrent MS, Stead CM, Tran AX, et al. Diversity of endotoxin and its impact on pathogenesis. J Endotoxin Res. 2006;12(4):205\\u0026ndash;23.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eChen KF, Chaou CH, Jiang JY, et al. Diagnostic Accuracy of Lipopolysaccharide-Binding Protein as Biomarker for Sepsis in Adult Patients: A Systematic Review and Meta-Analysis. PLoS ONE. 2016;11(4):e0153188.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGarc\\u0026iacute;a de Guadiana Romualdo L, Albaladejo Ot\\u0026oacute;n MD, Rebollo Acebes S, et al. Diagnostic accuracy of lipopolysaccharide-binding protein for sepsis in patients with suspected infection in the emergency department. Ann Clin Biochem. 2018;55(1):143\\u0026ndash;8.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWon Y, Yang J, Park S, et al. Lipopolysaccharide Binding Protein and CD14, Cofactors of Toll-like Receptors, Are Essential for Low-Grade Inflammation-Induced Exacerbation of Cartilage Damage in Mouse Models of Posttraumatic Osteoarthritis. Arthritis Rheumatol. 2021;73(8):1451\\u0026ndash;60.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eChalubinska-Fendler J, Graczyk L, Piotrowski G, et al. Lipopolysaccharide-Binding Protein Is an Early Biomarker of Cardiac Function After Radiation Therapy for Breast Cancer. Int J Radiation Oncology*Biology*Physics. 2019;104(5):1074\\u0026ndash;83.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eStasi A, Intini A, Divella C, et al. Emerging role of Lipopolysaccharide binding protein in sepsis-induced acute kidney injury. Nephrol Dialysis Transplantation. 2017;32(1):24\\u0026ndash;31.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eZweigner J, Schumann RR. Weber JR.The role of lipopolysaccharide-binding protein in modulating the innate immune response. Microbes Infect. 2006;8(3):946\\u0026ndash;52.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eJabandziev P, Smerek M, Michalek J, et al. Multiple gene-to-gene interactions in children with sepsis: a combination of five gene variants predicts outcome of life-threatening sepsis. Crit Care. 2014;18(1):R1.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eJung AL, Han M, Griss K, et al. Novel protein biomarkers for pneumonia and acute exacerbations in COPD: a pilot study. Front Med. 2023;10:1180746.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGarc\\u0026iacute;a de Guadiana-Romualdo LM, Rebollo-Acebes S, Esteban-Torrella P, et al. Prognostic value of lipopolysaccharide-binding protein and procalcitonin in patients with severe sepsis and septic shock admitted to intensive care. Med Intensiva. 2015;39(4):207\\u0026ndash;12.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eDjordjevic D, Pejovic J, Surbatovic M, et al. Prognostic Value and Daily Trend of Interleukin-6, Neutrophil CD64 Expression, C-Reactive Protein and Lipopolysaccharide-Binding Protein in Critically Ill Patients: Reliable Predictors of Outcome or Not? J Med Biochem. 2015;34(4):431\\u0026ndash;9.\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-emergency-medicine\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"emmd\",\"sideBox\":\"Learn more about [BMC Emergency Medicine](http://bmcemergmed.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/emmd\",\"title\":\"BMC Emergency Medicine\",\"twitterHandle\":\"@BMC_series\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"lipopolysaccharide-binding protein, LBP, sepsis, mortality, prognosis\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-4209402/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-4209402/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003ch2\\u003eObjective\\u003c/h2\\u003e \\u003cp\\u003eTo explore the predictive value of lipopolysaccharide-binding protein (LBP) in assessing the risk of death in septic patients, to provide a reference for clinical work.\\u003c/p\\u003e\\u003ch2\\u003eMethods\\u003c/h2\\u003e \\u003cp\\u003eData from 168 septic patients who were admitted to the emergency department of Beijing Chaoyang Hospital from September 2021 to September 2022 were retrospectively analyzed. SPSS25.0 software was used for data analysis and MedCalc 22.013 was applied to generate receiver operating characteristics (ROC) curves.\\u003c/p\\u003e\\u003ch2\\u003eResults\\u003c/h2\\u003e \\u003cp\\u003eA total of 54 patients were included in the non-survival group and 114 were included in the survival group. Age, respiratory rate, Acute Physiology and Chronic Health Evaluation II (APACHE II) score, Sequential Organ Failure Assessment (SOFA) score, LBP and lactate values were higher and the Glasgow Coma Scale (GCS) score and albumin were lower in the non-survival group than in the surviving group (all P\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001). Multivariate regression analysis showed that the APACHE II score, SOFA score, LBP and albumin were independent risk factors affecting the prognosis of septic patients. The area under the receiver operating characteristic curve (AUC) values were 0.801, 0.874 and 0.82 for LBP, APACHE II score and SOFA score, respectively, which better predicted the prognosis of septic patients. The AUC value of LBP and APACHE II score was 0.936, which was better than that of APACHE II score, SOFA score and LBP alone (P\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001). APACHE II\\u0026thinsp;+\\u0026thinsp;LBP had a sensitivity of 0.963 and a specificity of 0.798.\\u003c/p\\u003e\\u003ch2\\u003eConclusion\\u003c/h2\\u003e \\u003cp\\u003eLBP is an independent risk factor affecting the outcome of septic patients and has a moderate predictive power of mortality outcome. APACHE II\\u0026thinsp;+\\u0026thinsp;LBP score has better predictive performance.\\u003c/p\\u003e\",\"manuscriptTitle\":\"A correlational study of lipopolysaccharide-binding protein on the prognosis of septic patients in the emergency department\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2024-04-09 13:15:27\",\"doi\":\"10.21203/rs.3.rs-4209402/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2024-04-04T08:27:02+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2024-04-04T08:27:02+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"BMC Emergency Medicine\",\"date\":\"2024-04-03T02:26:12+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-emergency-medicine\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"emmd\",\"sideBox\":\"Learn more about [BMC Emergency Medicine](http://bmcemergmed.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/emmd\",\"title\":\"BMC Emergency Medicine\",\"twitterHandle\":\"@BMC_series\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"63caaf87-b8bb-4af2-a261-71a1a452a0a6\",\"owner\":[],\"postedDate\":\"April 9th, 2024\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"under-review\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2024-04-09T13:15:27+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2024-04-09 13:15:27\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-4209402\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-4209402\",\"identity\":\"rs-4209402\",\"version\":[\"v1\"]},\"buildId\":\"qtupq5eGEP_6zYnWcrvyt\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}