Thymosin Beta 4 as an Early Biomarker in Sepsis Induced Acute Kidney Injury

Thymosin Beta 4 as an Early Biomarker in Sepsis Induced Acute Kidney Injury | 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 Thymosin Beta 4 as an Early Biomarker in Sepsis Induced Acute Kidney Injury Jiahao Zhang, Minghui Long, Zhongyi Sun, Cheng Yang, Xiaofang Jiang, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-486278/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: The incidence of sepsis is high among patients in the intensive care units (ICU) and acute kidney injury (AKI) is a common complication of sepsis that contributes to increased mortality. Thymosin beta-4 (Tβ4) is an actin-sequestering protein that can prevent inflammation and fibrosis in several tissues. However, its functions in septic AKI remain unknown. Methods: 98 consecutive hospitalized patients with confirmed sepsis were enrolled. Demographics, comorbidities, laboratory findings, and outcomes were collected and analyzed. Serum Tβ4 levels at ICU admission were measured and analyzed for evaluating the probability of AKI using the logistic regression. In addition, the effects of exogenous Tβ4 on kidney injury was also conducted in mice where a sepsis model was induced by lipopolysaccharide (LPS) intraperitoneal injection. Results: Of the 98 patients with sepsis, 47 (48%) developed AKI. Patients with hypertension, diabetes, higher body mass index (BMI) and Sequential Organ Failure Assessment (SOFA) score were more likely to develop AKI. Among patients with AKI, hemoglobin, and Tβ4 were significantly decreased. Multivariate analysis showed decreased Tβ4, high SOFA, and high BMI to be independent risk factors for AKI in patients with sepsis. The overall mortality rate of the 98 septic patients was 20.4%, and the mortality rate of those with AKI was 29.8%. Kaplan-Meier analysis demonstrated that patients with AKI had a significantly higher risk of death. In particular, increasing AKI severity was associated with an increased risk of death. Furthermore, exogenous Tβ4 could reduce renal apoptosis and attenuated renal dysfunction, as well as reducing systemic inflammatory response through the prevention of the activation of NF-κB pathway in the sepsis model. Conclusions: The combination of Tβ4, SOFA, and BMI could allow for timely detection of septic AKI. Exogenous Tβ4 could prevent kidney injury in sepsis. Biomaterials thymosin beta-4 acute kidney injury biomarker sepsis Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Sepsis is a systemic inflammatory response syndrome (SIRS) that is caused by infection[ 1 ] and is one of the leading causes of death in intensive care unit (ICU) patients[ 2 ]. Acute kidney injury (AKI) is a series of pathophysiological changes caused by the sudden decline of renal function and the inability to exclude metabolic waste from the body, which is one of the most common complications of sepsis[ 3 ]. In the ICU, almost 50% of sepsis patients will develop AKI, thereby increasing the mortality rate of sepsis patients by 30–50%[ 4 ]. Up to now, the updates of diagnosis and treatment of septic AKI remain quite limited[ 5 ]. The traditional diagnostic criteria based on creatinine and urine volume are lack of sensitivity, and the damage of renal function may occur earlier than the changes of conventional markers[ 6 ]. In survival patients with septic AKI, almost 70% of the patients progress to chronic kidney disease and renal failure, which results in poor prognosis[ 7 ]. There is therefore an urgent clinical need for novel biomarkers for the timely diagnosis and detection of septic AKI in its early stages. Thymosin beta-4 (Tβ4) is a natural peptide encoded by the TMSB4X gene on the X-chromosome. It has been proven that Tβ4 regulates a series of cellular functions that include cell motility, differentiation, apoptosis, angiogenesis, anti-inflammatory, and fibrosis[ 8 ]. Tβ4 has attracted significant attention in the regenerative medicine field[ 9 ]. Tβ4 promotes the regeneration of eyes, skin, heart, and other tissues[ 10 – 13 ]. As an immune regulatory molecule, Tβ4 has the ability to reduce oxidative stress and block the secretion of inflammatory cytokines in many disease models[ 14 ]. In addition, the ratio of G-actin and F-actin, which are closely regulated by Tβ4, has proven to be significantly different in patients with septic shock[ 15 ]. Tβ4 has not yet been investigated as a potential biomarker for septic AKI. Thus, this study explores the relationship between Tβ4 and septic AKI in ICU patients, and evaluates the efficacy of exogenous Tβ4 against septic AKI in mice. 2. Materials And Methods 2.1 Observation study in patients with sepsis 2.1.1 Study design and participants This study was a prospective observational research study performed in a 58-bed closed intensive care unit of a 3300-bed tertiary center. With the approval of the Ethics Committee at Zhongnan Hospital of Wuhan University, patients in the ICU diagnosed with sepsis between January 1st and June 30th, 2019 were enrolled in the study. Patients with pre-existing AKI, chronic kidney disease, renal replacement therapy, end-stage renal disease, and organ transplantation were all excluded from the study. Patients who were aged below 18 or over 80 years old, and those who did not complete the consent form were also excluded. 2.1.2 Data collection Upon the ICU admission with diagnosis of sepsis, patients’ relevant information, including demographics, laboratory findings, management or treatment strategies, and outcomes were recorded. Blood and urine samples were obtained as soon as possible. Blood samples were centrifuged at 1500g for 10 min, while urine samples were centrifuged at 500g for 10 min; both were stored at − 80°C for analysis. 2.1.3 AKI diagnostic criteria According to the diagnostic criteria of Kidney Disease Improving Global Outcomes (KDIGO)[ 16 ], AKI can be diagnosed if it meets one of the following criteria: an increase in serum creatinine by ≥ 0.3 mg/dl (≥ 26.5 µmol/l) within 48 h; an increase in serum creatinine to ≥ 1.5 times baseline within the previous 7 days; urine volume ≤ 0.5 ml/kg/h for 6 h. AKI stage 1 is defined by an increase in serum creatinine of 50%-100% within 7 days or to 26.5 µmol/L or even greater than baseline within 48 hours, or urine output less than 0.5 ml/kg/h for 6–12 h; AKI stage 2 is defined by an increase of serum creatinine in 100%-200% from baseline, or urine output less than 0.5 ml/kg/h for more than 12 h; AKI stage 3 is defined by a an increase of 200% or more in serum creatinine, an increase to 353.6 µmol/L or more, urine output less than 0.3 ml/kg/h for more than 24 h or anuria for more than 12 h, or initiation of renal replacement therapy. 2.2 Study on septic AKI in mice 2.2.1 Animal model of septic AKI All experiments were performed in accordance with Chinese legislation on the use and care of laboratory animals and were approved by the Animal Care and Use Committee of Wuhan University. Male C57BL/6 mice weighing between 18 and 22 g were obtained from the Animal Center of Wuhan University. A sepsis model was created by injecting lipopolysaccharide (LPS, Sigma Chemical, St.Louis, Mo, USA) at the dose of 10mg/kg intraperitoneally. Mice in the LPS + Tβ4 group were pretreated with a Tβ4 solution (10 mg/kg) via abdominal injection 15 minutes prior to LPS administration. Mice in the normal control (NC) group were only treated with saline. 24 hours after injection, blood was collected by intracardiac puncture. Heparinized blood was centrifuged for 10 min to separate the plasma. Kidneys were harvested for tissue analysis, and half of the harvested kidneys were fixed in 4% paraformaldehyde and processed for hematoxylin and eosin (H&E)-stained analysis, while the other half were snap-frozen in liquid nitrogen and stored at − 80°C for protein analysis. 2.2.2 Western blot analysis Total protein was extracted from the kidney tissue of mice. Equal amounts of proteins were separated using sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and then transferred to a nitrocellulose membrane (Millipore). Following blocking with 5% non-fat milk, the membrane was incubated with anti-T-P65 (1:1000, Proteintech, 10745-1-AP), P-P65 (1:1000, Bioswamp, PAB36317-P), T-IκBα (1:1000, Bioswamp, PAB43967), P-IκBα (1:1000, Bioswamp, PAB43574-P), BCL2 (1:2000, Proteintech, 12789-1-AP), Caspase-3 (1:500, Proteintech, 19677-1-AP), or anti-GAPDH (1:5000, Bioswamp, PAB45851). 2.2.3 Enzyme linked immunosorbent assay The concentration of human Tβ4 were determined by commercially available ELISA kits (Jymbio, Colorful Gene Biological Technology Co. Ltd., Wuhan, China) according to the manufacturer’s instructions. Mice serum cytokines interleukin-1β (IL-1β), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α) were measured by commercial ELISA kits (Jymbio, Colorful Gene Biological Technology Co. Ltd., Wuhan, China). All samples were measured in triplicate. 2.2.4 TUNEL assay In order to detect TUNEL-positive cells, an ApopTag Peroxidase In Situ Apoptosis Detection Kit was used in accordance with the manufacturer’s instructions (S7100; Serologicals, Millipore). 2.3 Statistical analysis All numerical data was expressed as mean ± standard error or median and interquartile range. Independent sample t-tests and Mann Whitney U tests were used to compare the continuous variables. In order to determine the discriminative power of Tβ4, Sequential Organ Failure Assessment (SOFA), and body mass index (BMI) for septic AKI occurrence, receiver-operating characteristic (ROC) curves were constructed and the area under the curve (AUC) was determined with its 95% confidence interval (CI). Statistical analyses were performed using Statistical Package for the Social Sciences (version 22.0) and GraphPad Prism software (version 8.0). P < 0.05 was considered to be statistically significant. 3. Results 3.1 Characteristics of the Patients 98 patients were enrolled in this study, whereby 47 (48%) developed AKI (Table 1 ). In addition, 22 patients of them (46.8%) complicated with AKI stage 1, 11 patients (23.4%) AKI stage 2, and 14 patients (29.8%) AKI stage 3 (Supplementary table 1). Table 1 Characteristics of the Patients with Sepsis Between NAKI and AKI Factors All (n = 47) Survivors (n = 33) Non-survivors (n = 14) P value Stage of AKI 0.020 AKI stage 1 22(46.8) 19(57.6) 3(21.4) AKI stage 2 11(23.4) 8(24.2) 3(21.4) AKI stage 3 14(29.8) 6(18.2) 8(57.1) Treatment n(%) Mechanical ventilation 24(51.1) 11(33.3) 13(92.9) ༜0.001 Vasopressor 33(70.2) 20(60.6) 13(92.9) 0.027 Diuretic 38(80.9) 27(81.8) 11(78.6) 0.796 Renal replacement therapy 9(19.1) 6(18.2) 3(21.4) 0.796 Factors All (n = 98) NAKI (n = 51) AKI (n = 47) P value Age (IQR) 63(51–71) 63(49–71) 63(52–73) 0.790 Gender n(%) Male 63(64.3) 34(66.7) 29(61.7) 0.608 Female 35(35.7) 17(33.3) 18(38.3) 0.608 Comorbidities n(%) Hypertension 43(43.9) 16(31.4) 27(57.4) 0.009 Diabetes 18(18.4) 5(9.8) 13(27.7) 0.023 Cardiovascular disease 20(20.4) 7(13.7) 13(27.7) 0.087 Cerebrovascular disease 19(19.4) 10(19.6) 9(19.1) 0.954 Chronic obstructive pulmonary disease 8(8.2) 4(7.8) 4(8.5) 0.904 Malignancy 22(22.4) 11(21.6) 11(23.4) 0.828 Body mass index (IQR) 22.49(20.35–24.50) 21.10(19.38–23.44) 23.03(21.81–25.74) 0.002 Sequential Organ Failure Assessment (IQR) 6(5–9) 6(4–7) 9(6–11) ༜0.001 Laboratory data White blood cell count, ×109/L (IQR) 12.11(7.24–17.77) 11.42(7.14-15.00) 13.28(7.87–20.18) 0.099 Neutrophil count, ×109/L (IQR) 10.63(5.92–14.32) 10.26(5.84–13.72) 11.19(6.03–17.76) 0.198 Lymphocyte count, ×109/L (IQR) 1.18(0.73–1.73) 1.23(0.74–1.81) 1.08(0.72–1.63) 0.378 Platelet count, ×109/L (IQR) 133.0(84.3-174.8) 135.0(93.0-163.0) 109(77.0-202.0) 0.817 Hemoglobin g/L (IQR) 103.8(86.5-123.9) 109.0(95.0-127.5) 99.5(79.5–116.0) 0.046 Alanine aminotransferase, U/L (IQR) 31.5(18.0-78.7) 32.0(18.0–88.0) 31.0(18.0–77.0) 0.787 Aspartate aminotransferase, U/L (IQR) 51.0(31.2-101.7) 49.0(32.0–91.0) 56.0(29.0-158.0) 0.481 Abumin, g/L (IQR) 27.7(24.4–30.8) 27.6(23.8–30.3) 27.8(24.9–32.0) 0.325 Creatinine,µmol/L (IQR) 68.8(56.6–84.8) 67.0(53.1–81.7) 70.1(58.8-85.65) 0.260 Urea, mmol/L (IQR) 6.42(5.40–7.70) 5.81(5.10–7.72) 6.76(5.90–7.30) 0.051 Procalcitonin, ug/L (IQR) 8.47(1.95–51.27) 6.54(2.90-29.34) 10.33(1.22–65.33) 0.136 Lactic acid, mmol/L (IQR) 2.40(1.20–3.80) 2.10(0.95–3.25) 2.80(1.50–5.80) 0.077 Thymosin beta 4, ng/ml (IQR) 4.41(1.65–9.74) 7.23(3.32-113.28) 2.03(1.29–4.91) ༜0.001 Outcome Death n(%) 20(20.4) 6(11.8) 14(29.8) 0.027 ICU stay (IQR)* 5(3–7) 4(2–7) 5(4–8) 0.023 Hospital stay (IQR)* 12(9–14) 11(9–14) 12(10–16) 0.049 * Only 78 survival patients were collected and analyzed. There was no significant difference in age and gender between the AKI and non-AKI. However, patients with hypertension and diabetes had a greater likelihood of developing AKI. In particular, patients with a high BMI and SOFA score were more likely of developing AKI. Besides, the hemoglobin and Tβ4 in patients with AKI were significantly decreased. 3.2 Outcome of patients in sepsis with or without AKI Of the 98 patients included in this study, 78 were discharged and 20 died. The overall mortality rate was 20.4%, with 29.8% in AKI and 11.8% in non-AKI (Table 1 ). Kaplan-Meier survival curve showed that the survival rate in the AKI was lower than that in non-AKI (P = 0.032) (Fig. 1 . A). Cox proportional hazard regression also revealed that the hazard ratio of AKI to mortality was 2.674 with 95% CI (1.027–6.960, P = 0.044). Furthermore, the ICU stay and hospital stay for patients with septic AKI was significantly increased (Table 1 ). In addition, increasing AKI severity was associated with increased mortality (Table 2 and Fig. 1 . B). Of the 47 patients with septic AKI, 24 (51.1%) received mechanical ventilation, 33 (70.2%) received vasopressor, 38 (80.9%) received diuretics, and 9 (19.1%) received renal replacement therapy (Supplementary table 1). Table 2 Multivariate analysis of independent risk factors of Septic AKI Factor OR(95% CI) P value Adjust OR(95% CI) P value Tβ4 0.869(0.800-0.945) 0.001 0.872(0.792–0.961) 0.006 SOFA 1.321(1.134–1.537) ༜0.001 1.392(1.155–1.676) 0.001 BMI 1.257(1.084–1.458) 0.003 1.227(1.009–1.491) 0.040 Hypertension 2.953(1.291–6.753) 0.009 - 0.326 Diabetes 3.518(1.145–10.809) 0.023 - 0.077 Hemoglobin 1.015(1.001–1.030) 0.046 - 0.408 3.3 Multivariate analysis of the risk factors of septic AKI Factors with statistical significance from the results of univariate analysis were included in the logistic regression model as covariates. Adjustments were made for the following confounders: hypertension, diabetes, and hemoglobin. Multivariate analysis found Tβ4, SOFA, and BMI to be the independent risk factors for AKI in patients with sepsis. The adjusted OR of Tβ4 was 0.872 (95% CI,0.792–0.961). The adjusted OR of SOFA was 1.392 (95% CI, 1.155–1.676). The adjusted OR of BMI was 1.218 (95% CI, 1.009–1.491). (Table 2 ) 3.4 The clinical role of Tβ4, SOFA, and BMI in the prediction of septic AKI occurrence ROC curve analysis was performed in order to determine the performance of Tβ4, SOFA, BMI, and combinations of Tβ4, SOFA, and BMI in the prediction of septic AKI (Fig. 2 ). The AUC of Tβ4 was 0.746, best cut off of Tβ4 was 5.247 with sensitivity of 76.6% and specificity of 68.6%. The AUC of SOFA was 0.727, best cut off of SOFA was 9 with sensitivity of 55.3% and specificity of 82.4%. The AUC of BMI was 683, best cut off of BMI was 21.58 with sensitivity of 78.7% and specificity of 58.8%. Interestingly, the combination of Tβ4, SOFA, and BMI presented an AUC of 0.852 (P value < 0.001) for septic AKI (Table 3 ). Table 3 ROC curve of variables in the prediction of septic AKI Factor AUC P value Best cut off Sensitivity Specificity Tβ4 0.746 ༜0.001 5.247 0.766 0.686 SOFA 0.727 ༜0.001 9 0.553 0.824 BMI 0.683 0.002 21.58 0.787 0.588 Combination of Tβ4, SOFA and BMI 0.852 ༜0.001 - - - 3.5 Tβ4 pretreatment alleviated kidney injury in the sepsis mice To further elucidate the effects of Tβ4 in septic AKI, we designed this animal experiment. The serum creatinine increased significantly in the sepsis model group compared to that of the NC group at 24 hours. In addition, the increased serum creatinine was significantly improved with Tβ4 pretreatment (Fig. 3 . A). Inflammatory infiltration and vacuolization in tubules were showed in the kidney tissue with LPS injection using H&E-stain. The histopathological changes were ameliorated by Tβ4 pretreatment (Fig. 3 . B). For analysis of apoptosis of the kidneys, TUNEL assay was performed in the kidney tissue of the mice. The apoptosis percentage was also decreased with Tβ4 pretreatment (Fig. 3 . C). In addition, Tβ4 could inhibit the activation of Caspase-3 and slow down the inactivation of BCL-2 (Fig. 3 . D). 3.6 Tβ4 prevents the LPS-induced activation of NF-κB and the induction of proinflammatory cytokines The levels of plasma IL-1β, IL-6, and TNF-α were significantly increased after LPS injection, and these effects was markedly reduced with Tβ4 pretreatment (Fig. 4 . A). To explore the mechanism of regulating inflammatory cytokines, the effects of Tβ4 on NF-κB pathway, an essential step for the activation of Kupffer cells and the production of proinflammatory cytokines, were studied. Tβ4 significantly blocked the activation of the NF-κB pathway with respect to regarding the level of P-P65. These changes were also concomitantly associated with a change in the P-IκBα (Fig. 4 . B). 4. Discussion This study revealed the proportion of septic patients developing AKI in ICU to be 48%. The development of AKI could significantly increase the mortality of patients with sepsis, and the risk of death increased with the grade of AKI. Multivariate regression analysis revealed Tβ4, SOFA, and BMI at ICU admission to be independent risk factors for AKI in ICU patients with sepsis. In addition, Tβ4, SOFA, and BMI at ICU admission can predict the occurrence of AKI in patients with sepsis. The ROC curve curve showed Tβ4, SOFA, and BMI to be reliable in the prediction of septic AKI. Besides, this study proved that exogenous Tβ4 could not only improves renal function and reduce renal apoptosis, but also reduces inflammatory factors by down-regulating the activity of NF-κB pathway so as to improve the systemic inflammatory response of sepsis model mice. Related studies have shown Tβ4 reduces kidney injury by reducing inflammatory reaction and oxidative stress[ 17 ]. In sepsis patients, Tβ4 decreased significantly[ 18 ], leading to changes in the podocyte distribution within the glomerulus, increased periglomerular macrophage accumulation, and enhanced fibrosis, which results in progressive deterioration of renal function[ 19 ]. A study of 184875 people showed that the prognostic accuracy of the SOFA score was superior to SIRS criteria and qSOFA score among patients with suspected infection admitted to the ICU[ 20 ]. SOFA score combined with biomarkers have shown favorable results in predicting the development of septic AKI[ 21 ]. In addition, high BMI has been proven to be an independent risk factor for AKI in ICU patients. Obesity can cause some hemodynamic changes in the glomerulus, which will lead to glomerular injury. Furthermore, increased oxidative stress in obese patients can contribute to detrimental changes in the glomeruli[ 22 ]. In animal studies, exogenous Tβ4 were reported beneficial effects in diverse pathologies including myocardial infarction[ 23 ], stroke[ 24 ], dry eye[ 25 ], and inflammatory lung disease[ 26 ]. Clinical studies also assessed the efficacy of Tβ4 treatment in wound healing and cardioprotection[ 27 ]. Furthermore, exogenous Tβ4 demonstrated good therapeutic effect in the experimental model of kidney disease, such as reducing proteinuria, albumin to creatinine ratio, plasma creatinine, blood urea nitrogen, and creatinine clearance rate[ 8 ]. This study proved that exogenous Tβ4 could reduce renal apoptosis and attenuate renal dysfunction in septic mice. In addition, it was also demonstrated that Tβ4 could reduce systemic inflammatory response through the prevention of the activation of the NF-κB pathway, which was similar to previous study [ 28 ]. Our study has several limitations. First, we didn’t assessed factors of drug-induced kidney dysfunction. Second, the long-term outcome of patients was not followed up, especially the incidence of chronic kidney disease. Third, the effect of endogenous Tβ4 in animal model of septic AKI can not be ruled out. 5. Conclusions In general, AKI is a common complication in patients with sepsis, which worsened the outcome. The prediction model of Tβ4 combined with SOFA and BMI can be used for prediction of the risk of septic AKI. Furthermore, exogenous Tβ4 can protect renal function and reduce inflammatory reaction in the sepsis mice model, which may be developed as a promising potential drug against septic AKI. Abbreviations ICU Intensive care units; AKI Acute kidney injury; Tβ4 Thymosin beta-4; LPS Lipopolysaccharide; BMI Body mass index; SOFA Sequential Organ Failure Assessment score; IL-1β Interleukin-1β; IL-6 Interleukin-6; TNF-α Tumor necrosis factor-α; OR Odds ratio; ROC Receiver-operating characteristic AUC Area under the curve CI Confidence interval; Declarations Statements Statement of Ethics Consent for publication All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved by the Bioethics Committee of the Ethic Committee of Zhongnan Hospital of Wuhan University (No. 2017004). All animal performed procedures were previously reviewed and approved by the Animal Care and Use Committee of Wuhan University and carried out according to the recommendations in the guide for the care and use of laboratory animals (No. 2018024). Consent for publication Not applicable. Availability of data and materials All data generated or analysed during this study are included in this published article [and its supplementary information files]. Conflict of Interest Statement : The authors declare that they have no competing interests. Funding Sources This work was supported by the National Natural Science Foundation (grants 81772046 and 81971816 to Dr Peng) and the Special Project for Significant New Drug Research and Development in the Major National Science and Technology Projects of China (2020ZX09201007 to Dr Peng). Authors' contributions Conceived the project, designed the project, analyzed data, and drafted the manuscript: J.Z., M.H., and Z.S. 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Plasma levels of F-actin and F:G-actin ratio as potential new biomarkers in patients with septic shock. Biomarkers. 2016;21(2):180–5. doi: 10.3109/1354750X.2015.1126646 . Edmonston DL, Pun PH. Coronary artery disease in chronic kidney disease: highlights from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference. Kidney Int. 2020;97(4):642-4. doi: 10.1016/j.kint.2019.12.010 . Aksu U, Yaman OM, Guner I, Guntas G, Sonmez F, Tanriverdi G, et al. The Protective Effects of Thymosin-beta-4 in a Rat Model of Ischemic Acute Kidney Injury. J Invest Surg. 2019:1–9. doi: 10.1080/08941939.2019.1672841 . Badamchian M, Fagarasan MO, Danner RL, Suffredini AF, Damavandy H, Goldstein AL. Thymosin beta(4) reduces lethality and down-regulates inflammatory mediators in endotoxin-induced septic shock. Int Immunopharmacol. 2003;3(8):1225–33. doi: 10.1016/S1567-5769(03)00024-9 . Vasilopoulou E, Kolatsi-Joannou M, Lindenmeyer MT, White KE, Robson MG, Cohen CD, et al. Loss of endogenous thymosin beta4 accelerates glomerular disease. Kidney Int. 2016;90(5):1056–70. doi: 10.1016/j.kint.2016.06.032 . Raith EP, Udy AA, Bailey M, McGloughlin S, MacIsaac C, Bellomo R, et al. Prognostic Accuracy of the SOFA Score, SIRS Criteria, and qSOFA Score for In-Hospital Mortality Among Adults With Suspected Infection Admitted to the Intensive Care Unit. JAMA. 2017;317(3):290–300. doi: 10.1001/jama.2016.20328 . Lee CW, Kou HW, Chou HS, Chou HH, Huang SF, Chang CH, et al. A combination of SOFA score and biomarkers gives a better prediction of septic AKI and in-hospital mortality in critically ill surgical patients: a pilot study. World J Emerg Surg. 2018;13:41. doi: 10.1186/s13017-018-0202-5 . Ju S, Lee TW, Yoo JW, Lee SJ, Cho YJ, Jeong YY, et al. Body Mass Index as a Predictor of Acute Kidney Injury in Critically Ill Patients: A Retrospective Single-Center Study. Tuberc Respir Dis (Seoul). 2018;81(4):311–8. doi: 10.4046/trd.2017.0081 . Smart N, Bollini S, Dube KN, Vieira JM, Zhou B, Davidson S, et al. De novo cardiomyocytes from within the activated adult heart after injury. Nature. 2011;474(7353):640–4. doi: 10.1038/nature10188 . Morris DC, Cui Y, Cheung WL, Lu M, Zhang L, Zhang ZG, et al. A dose-response study of thymosin beta4 for the treatment of acute stroke. J Neurol Sci. 2014;345(1–2):61–7. doi: 10.1016/j.jns.2014.07.006 . Sosne G, Qiu P, Ousler GW 3rd, Dunn SP, Crockford D. Thymosin beta4: a potential novel dry eye therapy. Ann N Y Acad Sci. 2012;1270:45–50. doi: 10.1111/j.1749-6632.2012.06682.x . Conte E, Genovese T, Gili E, Esposito E, Iemmolo M, Fruciano M, et al. Thymosin beta4 protects C57BL/6 mice from bleomycin-induced damage in the lung. Eur J Clin Invest. 2013;43(3):309–15. doi: 10.1111/eci.12048 . Goldstein AL, Hannappel E, Sosne G, Kleinman HK. Thymosin beta4: a multi-functional regenerative peptide. Basic properties and clinical applications. Expert Opin Biol Ther. 2012;12(1):37–51. doi: 10.1517/14712598.2012.634793 . Shah R, Reyes-Gordillo K, Cheng Y, Varatharajalu R, Ibrahim J, Lakshman MR. Thymosin beta4 Prevents Oxidative Stress, Inflammation, and Fibrosis in Ethanol- and LPS-Induced Liver Injury in Mice. Oxid Med Cell Longev. 2018;2018:9630175. doi: 10.1155/2018/9630175 . 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-486278","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research","associatedPublications":[],"authors":[{"id":25862378,"identity":"396f6db6-8d45-4ff0-99f4-c0289bd3aecb","order_by":0,"name":"Jiahao Zhang","email":"","orcid":"","institution":"Wuhan University Zhongnan Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jiahao","middleName":"","lastName":"Zhang","suffix":""},{"id":25862379,"identity":"a98ec769-c082-4044-8ba5-b1280ca10ba1","order_by":1,"name":"Minghui Long","email":"","orcid":"","institution":"Wuhan University Zhongnan Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Minghui","middleName":"","lastName":"Long","suffix":""},{"id":25862380,"identity":"3046b823-da0c-4204-b81e-d3697892fd8d","order_by":2,"name":"Zhongyi Sun","email":"","orcid":"","institution":"Wuhan University Zhongnan Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zhongyi","middleName":"","lastName":"Sun","suffix":""},{"id":25862381,"identity":"e941f6b9-984d-4105-a400-1a661497ed38","order_by":3,"name":"Cheng Yang","email":"","orcid":"","institution":"Wuhan University Zhongnan Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Cheng","middleName":"","lastName":"Yang","suffix":""},{"id":25862382,"identity":"8c0bc3fb-b817-467a-a0af-469bcc418f39","order_by":4,"name":"Xiaofang Jiang","email":"","orcid":"","institution":"Wuhan University Zhongnan Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiaofang","middleName":"","lastName":"Jiang","suffix":""},{"id":25862383,"identity":"2a70c240-96ea-4347-867d-eac097beb4e9","order_by":5,"name":"Li He","email":"","orcid":"","institution":"Wuhan University Zhongnan Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"He","suffix":""},{"id":25862384,"identity":"56755d39-889f-40fe-af96-33c8a82fd074","order_by":6,"name":"Lianjiu Su","email":"","orcid":"","institution":"Wuhan University Zhongnan Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lianjiu","middleName":"","lastName":"Su","suffix":""},{"id":25862385,"identity":"b8352e3d-9168-4a8a-94c1-0b144e811164","order_by":7,"name":"Zhiyong Peng","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3ElEQVRIiWNgGAWjYBAC+wYw9U/OAEwbWBDWYnAATB0wNmBgBnEliNeSuAGshYEYLcd7D7/82XYnfTt7/9ENPwokGPjbuxPwarHvOZdmIdn2LHdnz2G2mz1Ah0mcObsBvy0SOWYGhm3MuRtuJLPd4AFqMZDIJaBF/o2ZQWIbc7oBUMvNP0RpkeAxfnCw7XACSMtt4mzhyTFjbDiXZrjhzGGz2zJAEwj7hf2M8ccfZTbyBscbn91888dGjr+9F78WIGCTYGRD8HgIKQcB5g8Mf4hRNwpGwSgYBSMWAABC7UpndkwsuAAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-3873-9607","institution":"Wuhan University Zhongnan Hospital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Zhiyong","middleName":"","lastName":"Peng","suffix":""}],"badges":[],"createdAt":"2021-05-01 21:09:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-486278/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-486278/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":9044012,"identity":"31f748c3-89ab-4a95-935d-3b037c75f5c3","added_by":"auto","created_at":"2021-05-11 13:40:30","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":56863,"visible":true,"origin":"","legend":"Kaplan-Meier survival curves.\nA Kaplan-Meier survival curves of AKI on overall survival in patients with sepsis.\nB Kaplan-Meier survival curves of AKI stage on survival in patients with septic AKI.\n","description":"","filename":"fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-486278/v1/7776333a7ec1b75db72da2ab.png"},{"id":9044258,"identity":"30c08a29-98be-49c3-b594-7bd0891b45f7","added_by":"auto","created_at":"2021-05-11 13:43:30","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":48846,"visible":true,"origin":"","legend":"ROC curves of variables in predicting septic AKI.","description":"","filename":"fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-486278/v1/4feb8d870a13d6e93e7fac57.png"},{"id":9044010,"identity":"25702341-d783-4255-828f-2d44b5f6f483","added_by":"auto","created_at":"2021-05-11 13:40:30","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1610382,"visible":true,"origin":"","legend":"Exogenous Tβ4 alleviated kidney injury in sepsis model.\nA. Serum creatinine was measured in each group to confirm the severity of AKI.\nB. H\u0026E staining of kidney sections in each group. Inflammatory infiltration and vacuolization in tubules were indicated in the insets by arrows. Bar represents 50µm.\nC. Apoptosis rate was analysis by TUNEL in the kidney of mice.\nD. Western blot assay was utilized to detect apoptosis related protein expression in mice kidney.\n","description":"","filename":"fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-486278/v1/8697e83873fef216987d4998.png"},{"id":9044257,"identity":"c19d2732-8a0e-4bd1-a78a-b51a6e5fc537","added_by":"auto","created_at":"2021-05-11 13:43:30","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":445089,"visible":true,"origin":"","legend":"Exogenous Tβ4 attenuated cytokine secretion via the NF-κB pathway.\nA. The cytokine TNF-α, IL-1β, and IL-6 in the serum of mice were detected by ELISA. \nB. Western blot analysis of P-P65, T-P65, P-IκBα, and T-IκBα protein expression in mice kidney tissues. Protein levels were determined after normalization to GAPDH.\n","description":"","filename":"fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-486278/v1/1b774d813659f534d44db57b.png"},{"id":13692711,"identity":"56aef6a6-147a-4a4e-bd75-c7f34d3c483e","added_by":"auto","created_at":"2021-09-17 12:44:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1460748,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-486278/v1/76c8e78e-791f-41e5-9dd7-adcabf883ab5.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eThymosin Beta 4 as an Early Biomarker in Sepsis Induced Acute Kidney Injury\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":" \u003cp\u003eSepsis is a systemic inflammatory response syndrome (SIRS) that is caused by infection[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] and is one of the leading causes of death in intensive care unit (ICU) patients[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Acute kidney injury (AKI) is a series of pathophysiological changes caused by the sudden decline of renal function and the inability to exclude metabolic waste from the body, which is one of the most common complications of sepsis[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In the ICU, almost 50% of sepsis patients will develop AKI, thereby increasing the mortality rate of sepsis patients by 30\u0026ndash;50%[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Up to now, the updates of diagnosis and treatment of septic AKI remain quite limited[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The traditional diagnostic criteria based on creatinine and urine volume are lack of sensitivity, and the damage of renal function may occur earlier than the changes of conventional markers[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In survival patients with septic AKI, almost 70% of the patients progress to chronic kidney disease and renal failure, which results in poor prognosis[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. There is therefore an urgent clinical need for novel biomarkers for the timely diagnosis and detection of septic AKI in its early stages.\u003c/p\u003e \u003cp\u003eThymosin beta-4 (Tβ4) is a natural peptide encoded by the TMSB4X gene on the X-chromosome. It has been proven that Tβ4 regulates a series of cellular functions that include cell motility, differentiation, apoptosis, angiogenesis, anti-inflammatory, and fibrosis[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Tβ4 has attracted significant attention in the regenerative medicine field[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Tβ4 promotes the regeneration of eyes, skin, heart, and other tissues[\u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. As an immune regulatory molecule, Tβ4 has the ability to reduce oxidative stress and block the secretion of inflammatory cytokines in many disease models[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In addition, the ratio of G-actin and F-actin, which are closely regulated by Tβ4, has proven to be significantly different in patients with septic shock[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTβ4 has not yet been investigated as a potential biomarker for septic AKI. Thus, this study explores the relationship between Tβ4 and septic AKI in ICU patients, and evaluates the efficacy of exogenous Tβ4 against septic AKI in mice.\u003c/p\u003e "},{"header":"2. Materials And Methods","content":" \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Observation study in patients with sepsis\u003c/h2\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003e2.1.1 Study design and participants\u003c/h2\u003e \u003cp\u003eThis study was a prospective observational research study performed in a 58-bed closed intensive care unit of a 3300-bed tertiary center. With the approval of the Ethics Committee at Zhongnan Hospital of Wuhan University, patients in the ICU diagnosed with sepsis between January 1st and June 30th, 2019 were enrolled in the study. Patients with pre-existing AKI, chronic kidney disease, renal replacement therapy, end-stage renal disease, and organ transplantation were all excluded from the study. Patients who were aged below 18 or over 80 years old, and those who did not complete the consent form were also excluded.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.1.2 Data collection\u003c/h2\u003e \u003cp\u003eUpon the ICU admission with diagnosis of sepsis, patients\u0026rsquo; relevant information, including demographics, laboratory findings, management or treatment strategies, and outcomes were recorded. Blood and urine samples were obtained as soon as possible. Blood samples were centrifuged at 1500g for 10 min, while urine samples were centrifuged at 500g for 10 min; both were stored at \u0026minus;\u0026thinsp;80\u0026deg;C for analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.1.3 AKI diagnostic criteria\u003c/h2\u003e \u003cp\u003eAccording to the diagnostic criteria of Kidney Disease Improving Global Outcomes (KDIGO)[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], AKI can be diagnosed if it meets one of the following criteria: an increase in serum creatinine by \u0026ge;\u0026thinsp;0.3 mg/dl (\u0026ge;\u0026thinsp;26.5 \u0026micro;mol/l) within 48 h; an increase in serum creatinine to \u0026ge;\u0026thinsp;1.5 times baseline within the previous 7 days; urine volume\u0026thinsp;\u0026le;\u0026thinsp;0.5 ml/kg/h for 6 h. AKI stage 1 is defined by an increase in serum creatinine of 50%-100% within 7 days or to 26.5 \u0026micro;mol/L or even greater than baseline within 48 hours, or urine output less than 0.5 ml/kg/h for 6\u0026ndash;12 h; AKI stage 2 is defined by an increase of serum creatinine in 100%-200% from baseline, or urine output less than 0.5 ml/kg/h for more than 12 h; AKI stage 3 is defined by a an increase of 200% or more in serum creatinine, an increase to 353.6 \u0026micro;mol/L or more, urine output less than 0.3 ml/kg/h for more than 24 h or anuria for more than 12 h, or initiation of renal replacement therapy.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Study on septic AKI in mice\u003c/h2\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1 Animal model of septic AKI\u003c/h2\u003e \u003cp\u003e All experiments were performed in accordance with Chinese legislation on the use and care of laboratory animals and were approved by the Animal Care and Use Committee of Wuhan University.\u003c/p\u003e \u003cp\u003e Male C57BL/6 mice weighing between 18 and 22 g were obtained from the Animal Center of Wuhan University. A sepsis model was created by injecting lipopolysaccharide (LPS, Sigma Chemical, St.Louis, Mo, USA) at the dose of 10mg/kg intraperitoneally. Mice in the LPS\u0026thinsp;+\u0026thinsp;Tβ4 group were pretreated with a Tβ4 solution (10 mg/kg) via abdominal injection 15 minutes prior to LPS administration. Mice in the normal control (NC) group were only treated with saline. 24 hours after injection, blood was collected by intracardiac puncture. Heparinized blood was centrifuged for 10 min to separate the plasma. Kidneys were harvested for tissue analysis, and half of the harvested kidneys were fixed in 4% paraformaldehyde and processed for hematoxylin and eosin (H\u0026amp;E)-stained analysis, while the other half were snap-frozen in liquid nitrogen and stored at \u0026minus;\u0026thinsp;80\u0026deg;C for protein analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2 Western blot analysis\u003c/h2\u003e \u003cp\u003eTotal protein was extracted from the kidney tissue of mice. Equal amounts of proteins were separated using sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and then transferred to a nitrocellulose membrane (Millipore). Following blocking with 5% non-fat milk, the membrane was incubated with anti-T-P65 (1:1000, Proteintech, 10745-1-AP), P-P65 (1:1000, Bioswamp, PAB36317-P), T-IκBα (1:1000, Bioswamp, PAB43967), P-IκBα (1:1000, Bioswamp, PAB43574-P), BCL2 (1:2000, Proteintech, 12789-1-AP), Caspase-3 (1:500, Proteintech, 19677-1-AP), or anti-GAPDH (1:5000, Bioswamp, PAB45851).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.2.3 Enzyme linked immunosorbent assay\u003c/h2\u003e \u003cp\u003eThe concentration of human Tβ4 were determined by commercially available ELISA kits (Jymbio, Colorful Gene Biological Technology Co. Ltd., Wuhan, China) according to the manufacturer\u0026rsquo;s instructions. Mice serum cytokines interleukin-1β (IL-1β), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α) were measured by commercial ELISA kits (Jymbio, Colorful Gene Biological Technology Co. Ltd., Wuhan, China). All samples were measured in triplicate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e2.2.4 TUNEL assay\u003c/h2\u003e \u003cp\u003eIn order to detect TUNEL-positive cells, an ApopTag Peroxidase In Situ Apoptosis Detection Kit was used in accordance with the manufacturer\u0026rsquo;s instructions (S7100; Serologicals, Millipore).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Statistical analysis\u003c/h2\u003e \u003cp\u003eAll numerical data was expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error or median and interquartile range. Independent sample t-tests and Mann Whitney U tests were used to compare the continuous variables. In order to determine the discriminative power of Tβ4, Sequential Organ Failure Assessment (SOFA), and body mass index (BMI) for septic AKI occurrence, receiver-operating characteristic (ROC) curves were constructed and the area under the curve (AUC) was determined with its 95% confidence interval (CI). Statistical analyses were performed using Statistical Package for the Social Sciences (version 22.0) and GraphPad Prism software (version 8.0). P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered to be statistically significant.\u003c/p\u003e \u003c/div\u003e "},{"header":"3. Results","content":" \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Characteristics of the Patients\u003c/h2\u003e \u003cp\u003e98 patients were enrolled in this study, whereby 47 (48%) developed AKI (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In addition, 22 patients of them (46.8%) complicated with AKI stage 1, 11 patients (23.4%) AKI stage 2, and 14 patients (29.8%) AKI stage 3 (Supplementary table 1).\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\u003eCharacteristics of the Patients with Sepsis Between NAKI and AKI\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll (n\u0026thinsp;=\u0026thinsp;47)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSurvivors (n\u0026thinsp;=\u0026thinsp;33)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNon-survivors (n\u0026thinsp;=\u0026thinsp;14)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage of AKI\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=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAKI stage 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22(46.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19(57.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3(21.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAKI stage 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11(23.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8(24.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3(21.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAKI stage 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14(29.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6(18.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8(57.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment n(%)\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 \u003cp\u003eMechanical ventilation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24(51.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11(33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13(92.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e༜0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVasopressor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33(70.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20(60.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13(92.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiuretic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38(80.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27(81.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11(78.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.796\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRenal replacement therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9(19.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6(18.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3(21.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.796\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ccolgroup cols=\"5\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll (n\u0026thinsp;=\u0026thinsp;98)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNAKI (n\u0026thinsp;=\u0026thinsp;51)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAKI (n\u0026thinsp;=\u0026thinsp;47)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63(51\u0026ndash;71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63(49\u0026ndash;71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63(52\u0026ndash;73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.790\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender n(%)\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 \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63(64.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34(66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29(61.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.608\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35(35.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17(33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18(38.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.608\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbidities n(%)\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 \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43(43.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16(31.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27(57.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18(18.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(9.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13(27.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiovascular disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20(20.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(13.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13(27.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.087\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCerebrovascular disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19(19.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(19.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9(19.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.954\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic obstructive pulmonary disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8(8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4(7.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.904\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMalignancy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22(22.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(21.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11(23.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.828\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody mass index (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.49(20.35\u0026ndash;24.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.10(19.38\u0026ndash;23.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.03(21.81\u0026ndash;25.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSequential Organ Failure Assessment (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6(5\u0026ndash;9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(4\u0026ndash;7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9(6\u0026ndash;11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e༜0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLaboratory data\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 \u003cp\u003eWhite blood cell count, \u0026times;109/L (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.11(7.24\u0026ndash;17.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.42(7.14-15.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.28(7.87\u0026ndash;20.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.099\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophil count, \u0026times;109/L (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.63(5.92\u0026ndash;14.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.26(5.84\u0026ndash;13.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.19(6.03\u0026ndash;17.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.198\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocyte count, \u0026times;109/L (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.18(0.73\u0026ndash;1.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.23(0.74\u0026ndash;1.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.08(0.72\u0026ndash;1.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.378\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet count, \u0026times;109/L (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e133.0(84.3-174.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e135.0(93.0-163.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e109(77.0-202.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.817\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin g/L (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e103.8(86.5-123.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e109.0(95.0-127.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99.5(79.5\u0026ndash;116.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlanine aminotransferase, U/L (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.5(18.0-78.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.0(18.0\u0026ndash;88.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.0(18.0\u0026ndash;77.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.787\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAspartate aminotransferase, U/L (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51.0(31.2-101.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.0(32.0\u0026ndash;91.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56.0(29.0-158.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.481\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbumin, g/L (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27.7(24.4\u0026ndash;30.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.6(23.8\u0026ndash;30.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.8(24.9\u0026ndash;32.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.325\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine,\u0026micro;mol/L (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68.8(56.6\u0026ndash;84.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67.0(53.1\u0026ndash;81.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70.1(58.8-85.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.260\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrea, mmol/L (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.42(5.40\u0026ndash;7.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.81(5.10\u0026ndash;7.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.76(5.90\u0026ndash;7.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProcalcitonin, ug/L (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.47(1.95\u0026ndash;51.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.54(2.90-29.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.33(1.22\u0026ndash;65.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.136\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLactic acid, mmol/L (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.40(1.20\u0026ndash;3.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.10(0.95\u0026ndash;3.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.80(1.50\u0026ndash;5.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThymosin beta 4, ng/ml (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.41(1.65\u0026ndash;9.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.23(3.32-113.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.03(1.29\u0026ndash;4.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e༜0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcome\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 \u003cp\u003eDeath n(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20(20.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(11.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14(29.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICU stay (IQR)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5(3\u0026ndash;7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4(2\u0026ndash;7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5(4\u0026ndash;8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital stay (IQR)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12(9\u0026ndash;14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(9\u0026ndash;14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12(10\u0026ndash;16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e* Only 78 survival patients were collected and analyzed.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThere was no significant difference in age and gender between the AKI and non-AKI. However, patients with hypertension and diabetes had a greater likelihood of developing AKI. In particular, patients with a high BMI and SOFA score were more likely of developing AKI. Besides, the hemoglobin and Tβ4 in patients with AKI were significantly decreased.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Outcome of patients in sepsis with or without AKI\u003c/h2\u003e \u003cp\u003eOf the 98 patients included in this study, 78 were discharged and 20 died. The overall mortality rate was 20.4%, with 29.8% in AKI and 11.8% in non-AKI (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Kaplan-Meier survival curve showed that the survival rate in the AKI was lower than that in non-AKI (P\u0026thinsp;=\u0026thinsp;0.032) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. A). Cox proportional hazard regression also revealed that the hazard ratio of AKI to mortality was 2.674 with 95% CI (1.027\u0026ndash;6.960, P\u0026thinsp;=\u0026thinsp;0.044). Furthermore, the ICU stay and hospital stay for patients with septic AKI was significantly increased (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn addition, increasing AKI severity was associated with increased mortality (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. B). Of the 47 patients with septic AKI, 24 (51.1%) received mechanical ventilation, 33 (70.2%) received vasopressor, 38 (80.9%) received diuretics, and 9 (19.1%) received renal replacement therapy (Supplementary table 1).\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\u003eMultivariate analysis of independent risk factors of Septic AKI\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdjust OR(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTβ4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.869(0.800-0.945)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.872(0.792\u0026ndash;0.961)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.321(1.134\u0026ndash;1.537)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e༜0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.392(1.155\u0026ndash;1.676)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.257(1.084\u0026ndash;1.458)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.227(1.009\u0026ndash;1.491)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.040\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.953(1.291\u0026ndash;6.753)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.326\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.518(1.145\u0026ndash;10.809)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.015(1.001\u0026ndash;1.030)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.408\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=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Multivariate analysis of the risk factors of septic AKI\u003c/h2\u003e \u003cp\u003eFactors with statistical significance from the results of univariate analysis were included in the logistic regression model as covariates. Adjustments were made for the following confounders: hypertension, diabetes, and hemoglobin. Multivariate analysis found Tβ4, SOFA, and BMI to be the independent risk factors for AKI in patients with sepsis. The adjusted OR of Tβ4 was 0.872 (95% CI,0.792\u0026ndash;0.961). The adjusted OR of SOFA was 1.392 (95% CI, 1.155\u0026ndash;1.676). The adjusted OR of BMI was 1.218 (95% CI, 1.009\u0026ndash;1.491). (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.4 The clinical role of Tβ4, SOFA, and BMI in the prediction of septic AKI occurrence\u003c/h2\u003e \u003cp\u003eROC curve analysis was performed in order to determine the performance of Tβ4, SOFA, BMI, and combinations of Tβ4, SOFA, and BMI in the prediction of septic AKI (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe AUC of Tβ4 was 0.746, best cut off of Tβ4 was 5.247 with sensitivity of 76.6% and specificity of 68.6%. The AUC of SOFA was 0.727, best cut off of SOFA was 9 with sensitivity of 55.3% and specificity of 82.4%. The AUC of BMI was 683, best cut off of BMI was 21.58 with sensitivity of 78.7% and specificity of 58.8%. Interestingly, the combination of Tβ4, SOFA, and BMI presented an AUC of 0.852 (P value\u0026thinsp;\u0026lt;\u0026thinsp;0.001) for septic AKI (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\u003eROC curve of variables in the prediction of septic AKI\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBest cut off\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTβ4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.746\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e༜0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.247\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.766\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.686\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.727\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e༜0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.553\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.824\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.683\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.588\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCombination of Tβ4, SOFA and BMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.852\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e༜0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\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 \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Tβ4 pretreatment alleviated kidney injury in the sepsis mice\u003c/h2\u003e \u003cp\u003eTo further elucidate the effects of Tβ4 in septic AKI, we designed this animal experiment. The serum creatinine increased significantly in the sepsis model group compared to that of the NC group at 24 hours. In addition, the increased serum creatinine was significantly improved with Tβ4 pretreatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. A). Inflammatory infiltration and vacuolization in tubules were showed in the kidney tissue with LPS injection using H\u0026amp;E-stain. The histopathological changes were ameliorated by Tβ4 pretreatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. B). For analysis of apoptosis of the kidneys, TUNEL assay was performed in the kidney tissue of the mice. The apoptosis percentage was also decreased with Tβ4 pretreatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. C). In addition, Tβ4 could inhibit the activation of Caspase-3 and slow down the inactivation of BCL-2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. D).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Tβ4 prevents the LPS-induced activation of NF-κB and the induction of proinflammatory cytokines\u003c/h2\u003e \u003cp\u003eThe levels of plasma IL-1β, IL-6, and TNF-α were significantly increased after LPS injection, and these effects was markedly reduced with Tβ4 pretreatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. A).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo explore the mechanism of regulating inflammatory cytokines, the effects of Tβ4 on NF-κB pathway, an essential step for the activation of Kupffer cells and the production of proinflammatory cytokines, were studied. Tβ4 significantly blocked the activation of the NF-κB pathway with respect to regarding the level of P-P65. These changes were also concomitantly associated with a change in the P-IκBα (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. B).\u003c/p\u003e \u003c/div\u003e "},{"header":"4. Discussion","content":" \u003cp\u003eThis study revealed the proportion of septic patients developing AKI in ICU to be 48%. The development of AKI could significantly increase the mortality of patients with sepsis, and the risk of death increased with the grade of AKI. Multivariate regression analysis revealed Tβ4, SOFA, and BMI at ICU admission to be independent risk factors for AKI in ICU patients with sepsis. In addition, Tβ4, SOFA, and BMI at ICU admission can predict the occurrence of AKI in patients with sepsis. The ROC curve curve showed Tβ4, SOFA, and BMI to be reliable in the prediction of septic AKI. Besides, this study proved that exogenous Tβ4 could not only improves renal function and reduce renal apoptosis, but also reduces inflammatory factors by down-regulating the activity of NF-κB pathway so as to improve the systemic inflammatory response of sepsis model mice.\u003c/p\u003e \u003cp\u003eRelated studies have shown Tβ4 reduces kidney injury by reducing inflammatory reaction and oxidative stress[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In sepsis patients, Tβ4 decreased significantly[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], leading to changes in the podocyte distribution within the glomerulus, increased periglomerular macrophage accumulation, and enhanced fibrosis, which results in progressive deterioration of renal function[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. A study of 184875 people showed that the prognostic accuracy of the SOFA score was superior to SIRS criteria and qSOFA score among patients with suspected infection admitted to the ICU[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. SOFA score combined with biomarkers have shown favorable results in predicting the development of septic AKI[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In addition, high BMI has been proven to be an independent risk factor for AKI in ICU patients. Obesity can cause some hemodynamic changes in the glomerulus, which will lead to glomerular injury. Furthermore, increased oxidative stress in obese patients can contribute to detrimental changes in the glomeruli[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn animal studies, exogenous Tβ4 were reported beneficial effects in diverse pathologies including myocardial infarction[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], stroke[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], dry eye[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], and inflammatory lung disease[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Clinical studies also assessed the efficacy of Tβ4 treatment in wound healing and cardioprotection[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Furthermore, exogenous Tβ4 demonstrated good therapeutic effect in the experimental model of kidney disease, such as reducing proteinuria, albumin to creatinine ratio, plasma creatinine, blood urea nitrogen, and creatinine clearance rate[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. This study proved that exogenous Tβ4 could reduce renal apoptosis and attenuate renal dysfunction in septic mice. In addition, it was also demonstrated that Tβ4 could reduce systemic inflammatory response through the prevention of the activation of the NF-κB pathway, which was similar to previous study [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur study has several limitations. First, we didn\u0026rsquo;t assessed factors of drug-induced kidney dysfunction. Second, the long-term outcome of patients was not followed up, especially the incidence of chronic kidney disease. Third, the effect of endogenous Tβ4 in animal model of septic AKI can not be ruled out.\u003c/p\u003e "},{"header":"5. Conclusions","content":" \u003cp\u003eIn general, AKI is a common complication in patients with sepsis, which worsened the outcome. The prediction model of Tβ4 combined with SOFA and BMI can be used for prediction of the risk of septic AKI. Furthermore, exogenous Tβ4 can protect renal function and reduce inflammatory reaction in the sepsis mice model, which may be developed as a promising potential drug against septic AKI.\u003c/p\u003e "},{"header":"Abbreviations","content":" \u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eICU\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIntensive care units;\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAKI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAcute kidney injury;\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTβ4\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eThymosin beta-4;\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLPS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLipopolysaccharide;\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBMI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBody mass index;\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSOFA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSequential Organ Failure Assessment score;\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIL-1β\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterleukin-1β;\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIL-6\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterleukin-6;\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTNF-α\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTumor necrosis factor-α;\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOdds ratio;\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\u003eArea under the curve\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence interval;\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eStatements \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatement of Ethics\u003c/strong\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved by the Bioethics Committee of the Ethic Committee of Zhongnan Hospital of Wuhan University (No. 2017004). All animal performed procedures were previously reviewed and approved by the Animal Care and Use Committee of Wuhan University and carried out according to the recommendations in the guide for the care and use of laboratory animals (No. 2018024).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication \u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials \u003c/strong\u003eAll data generated or analysed during this study are included in this published article [and its supplementary information files].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest Statement\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e The authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Sources\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation (grants 81772046 and 81971816 to Dr Peng) and the Special Project for Significant New Drug Research and Development in the Major National Science and Technology Projects of China (2020ZX09201007 to Dr Peng).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceived the project, designed the project, analyzed data, and drafted the manuscript: J.Z., M.H., and Z.S. Extract and analyzed data: C.Y., X.J., and L.H. Designed the project, edited the manuscript and approved the final version: J.S., and Z.P.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment: \u003c/strong\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRello J, Valenzuela-Sanchez F, Ruiz-Rodriguez M, Moyano S. Sepsis. A Review of Advances in Management. Adv Ther. 2017;34(11):2393\u0026ndash;411. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s12325-017-0622-8\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCecconi M, Evans L, Levy M, Rhodes A. Sepsis and septic shock. 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Eur J Clin Invest. 2013;43(3):309\u0026ndash;15. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/eci.12048\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoldstein AL, Hannappel E, Sosne G, Kleinman HK. Thymosin beta4: a multi-functional regenerative peptide. Basic properties and clinical applications. Expert Opin Biol Ther. 2012;12(1):37\u0026ndash;51. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1517/14712598.2012.634793\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShah R, Reyes-Gordillo K, Cheng Y, Varatharajalu R, Ibrahim J, Lakshman MR. Thymosin beta4 Prevents Oxidative Stress, Inflammation, and Fibrosis in Ethanol- and LPS-Induced Liver Injury in Mice. Oxid Med Cell Longev. 2018;2018:9630175. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1155/2018/9630175\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"thymosin beta-4, acute kidney injury, biomarker, sepsis","lastPublishedDoi":"10.21203/rs.3.rs-486278/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-486278/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e The incidence of sepsis is high among patients in the intensive care units (ICU) and acute kidney injury (AKI) is a common complication of sepsis that contributes to increased mortality. Thymosin beta-4 (Tβ4) is an actin-sequestering protein that can prevent inflammation and fibrosis in several tissues. However, its functions in septic AKI remain unknown.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003e98 consecutive hospitalized patients with confirmed sepsis were enrolled. Demographics, comorbidities, laboratory findings, and outcomes were collected and analyzed. Serum Tβ4 levels at ICU admission were measured and analyzed for evaluating the probability of AKI using the logistic regression. In addition, the effects of exogenous Tβ4 on kidney injury was also conducted in mice where a sepsis model was induced by lipopolysaccharide (LPS) intraperitoneal injection. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eOf the 98 patients with sepsis, 47 (48%) developed AKI. Patients with hypertension, diabetes, higher body mass index (BMI) and Sequential Organ Failure Assessment (SOFA) score were more likely to develop AKI. Among patients with AKI, hemoglobin, and Tβ4 were significantly decreased. Multivariate analysis showed decreased Tβ4, high SOFA, and high BMI to be independent risk factors for AKI in patients with sepsis. The overall mortality rate of the 98 septic patients was 20.4%, and the mortality rate of those with AKI was 29.8%. Kaplan-Meier analysis demonstrated that patients with AKI had a significantly higher risk of death. In particular, increasing AKI severity was associated with an increased risk of death. Furthermore, exogenous Tβ4 could reduce renal apoptosis and attenuated renal dysfunction, as well as reducing systemic inflammatory response through the prevention of the activation of NF-κB pathway in the sepsis model.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eThe combination of Tβ4, SOFA, and BMI could allow for timely detection of septic AKI. Exogenous Tβ4 could prevent kidney injury in sepsis.\u003c/p\u003e","manuscriptTitle":"Thymosin Beta 4 as an Early Biomarker in Sepsis Induced Acute Kidney Injury","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-05-11 13:40:28","doi":"10.21203/rs.3.rs-486278/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c798b5c3-3ce7-4247-ad95-6d3affa27f8f","owner":[],"postedDate":"May 11th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":4229891,"name":"Biomaterials"}],"tags":[],"updatedAt":"2021-06-05T23:44:52+00:00","versionOfRecord":[],"versionCreatedAt":"2021-05-11 13:40:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-486278","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-486278","identity":"rs-486278","version":["v1"]},"buildId":"rHA-KDH7Qsr4HCuvH75dn","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}