Association Between Albumin Level at Admission to the Chinese Pediatric Intensive Care Unit and In-Hospital All-Cause Mortality

Association Between Albumin Level at Admission to the Chinese Pediatric Intensive Care Unit and In-Hospital All-Cause Mortality | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Association Between Albumin Level at Admission to the Chinese Pediatric Intensive Care Unit and In-Hospital All-Cause Mortality Wei Liu, Li Zhou This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8101330/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Objective This study investigated the association between albumin level upon admission to the pediatric intensive care unit (PICU)and in-hospital all-cause mortality. Methods A retrospective cohort study was conducted using data from a large pediatric electronic database that included 9,689 critically ill children. The primary exposure variable was the first albumin level , which was analyzed as a continuous variable, while the outcome variable was in-hospital mortality. Multiple regression was employed to assess the relationship between albumin level and mortality, adjusting for potential confounders, such as length of hospital stay, sex, and other laboratory indicators. Results The results of the study showed that the association between serum albumin levels and the risk of mortality followed a U-shape. The risk of mortality decreased with increasing serum albumin levels (OR = 0.93; 95% CI: 0.91, 0.95) in children with serum albumin levels < 34.6 g/L and increased with increasing serum albumin levels (OR = 1.05; 95% CI: 1.002, 1.08) in children with serum albumin levels ≥ 34.6 g/L. Conclusion There was a U-shaped association between serum albumin levels and mortality in critically ill children admitted to the intensive care unit( ICU). albumin mortality ICU pediatric Figures Figure 1 Figure 2 Introduction Serum albumin levels serve as crucial indicator s in critically ill patients and are closely associated with unfavorable prognoses [ 1 ] . Reduced albumin levels are widely acknowledged as a physiological marker of tissue hypoperfusion and have significant prognostic implications in the clinical setting . This is attributed to the multifaceted roles of albumin, including the maintenance of colloidal osmotic pressure, antioxidant and anti-inflammatory functions, regulation of acid-base equilibrium, and facilitation of nutrient transport and metabolism. Consequently, albumin plays a pivotal role in the evaluation and treatment of patients [ 2 , 3 ] . In acute conditions, particularly within the intensive care unit (ICU) setting, albumin level is recognized as a valuable biomarker for predicting patient survival and clinical outcomes [ 4 ] . While the association between albumin level at admission and mortality has been established in adult studies, evidence in pediatric populations remains inconclusive and underexplored [ 5 ] . Some studies on critically ill pediatric patients have proposed a link between low albumin levels and adverse clinical outcomes [ 6 , 7 ] . However, other studies have indicated that albumin levels do not significantly impact survival in pediatric ICU patients, highlighting the insufficient and inconsistent nature of the current data in this population [ 8 , 9 ] . Moreover, there is a scarcity of clinical data and research on children, creating critical knowledge gaps that require immediate attention. This study aimed to evaluate the correlation between serum albumin levels at admission and all-cause mortality among chinese pediatric ICU patients. By investigating the relationship between albumin levels at admission and clinical outcomes in pediatric ICU patients, th is study sought to offer insights for enhancing early diagnosis and treatment in pediatric intensive care settings. The findings of this study have the potential to advance the comprehension of critically ill pediatric patients, impact clinical practices, and offer novel insights and empirical support for future research. Research methods Research Design and Data Sources This study utilized a retrospective cohort design to meticulously examine the intricate relationship between initial laboratory albumin levels and mortality rates among patients admitted to the pediatric intensive care unit. This area of research is critical as it has the potential to significantly influence clinical practices and patient outcomes. In addition to evaluating albumin levels, the study also aimed to investigate the impact of various factors, such as sex and specific ICU type, on this association, thereby providing a more nuanced understanding of how these variables may interact and affect patient prognosis [ 10 ] . The data for this research were sourced from a large-scale pediatric electronic database developed by the esteemed Children's Hospital at Zhejiang University School of Medicine. This comprehensive database systematically records all clinical information related to patients admitted to the pediatric intensive care unit beginning at the time of admission. It encompasses a wide array of relevant data points, and thus serv es as a reliable foundation for this study. This thorough approach ensures that the findings are both valid and applicable to real-world clinical scenarios, ultimately contributing to the body of knowledge that informs the best practices in pediatric critical care. Study Population The study population comprised pediatric patients admitted to the pediatric intensive care unit at Zhejiang University Children's Hospital from 2010 to 2018. Eligible participants were those age d < 18 years who underwent initial albumin assessment within 24 h of hospitalization. Individuals with incomplete medical records were excluded from analysis. Ultimately, the final dataset included 9,689 patients qualified for comprehensive analysis. Variable Definitions Exposure Variable: The primary variable of interest was the initial laboratory albumin level, which was treated as a continuous variable. Outcome Variable: The outcome of interest was the in-hospital all-cause mortality rate, which was represented as a binary variable. Patients who passed away were assigned a value of 1 , whereas those who survived were assigned a value of 0. Covariates: Other variables considered in the analysis included patient sex (male/female), length of hospital stay, additional laboratory indicators (such as white blood cell count, platelet count, and lactate levels), and type of ICU (including cardiac ICU, general PICU, etc.). All laboratory test results were obtained during the first 24 h of admission. Statistical Analysis We used weighted multivariate linear regression models and smooth curve fitting to evaluate the associations between serum albumin levels and mortality. The other variables were considered potential effect modifiers. For continuous variables, a weighted linear regression model was used to calculate the differences among the different groups. For categorical variables, the weighted chi-squared test was used. Significance value was set at p < 0.05. A weighted generalized additive model and smooth curve fitting were conducted to address the nonlinearity . When nonlinearity was uncovered, we first calculated the vital inflection point using a recursive algorithm, and then conducted a weighted two-piecewise linear regression model on both sides of the inflection point. All statistical analyses were performed using R ( http://www.R-project.org , The R Foundation) and EmpowerStats software ( http://www.empowerstats.com , X&Y Solutions, Inc., Boston, MA). Results Table 1 presents a comparison of baseline characteristics between the two study populations : survival group (N = 9085) and death group (N = 604). The authors analyzed various laboratory and clinical parameters to assess differences between the groups. The findings revealed that individuals in the death group exhibited significantly elevated WBC count, RBC distribution width, serum albumin, serum potassium, total calcium, lactate, ALT, and AST levels compared to those in the survival group (P < .01). Table 1 Description of Study Population DEAD 0 1 P-value* Number 9085 604 WBC(10 9 /L) 12.10 ± 20.47 16.22 ± 36.43 < 0.01 RBC(10 12 /L) 3.91 ± 0.84 3.89 ± 1.05 0.58 NEUTROPHILCOUNT(10 9 /L) 63.85 ± 18.62 57.50 ± 22.21 < 0.01 RDW(%) 14.82 ± 2.50 15.54 ± 2.53 < 0.01 ALBUMIN(g/L) 35.85 ± 6.13 33.48 ± 8.06 < 0.01 POTASSIUM(mmol/L) 3.78 ± 0.76 4.12 ± 1.14 < 0.01 CALCIUMTOTAL(mmol/L) 1.18 ± 0.14 1.12 ± 0.20 < 0.01 LACTATE(mmol/L) 2.44 ± 2.23 5.09 ± 5.11 < 0.01 ALT(U/L) 54.85 ± 287.77 139.74 ± 598.89 < 0.01 AST(U/L) 119.61 ± 647.15 372.56 ± 1442.71 < 0.01 HOSPTL-DAY(day) 19.64 ± 20.24 14.24 ± 22.16 < 0.01 Age(day) 858.28 ± 1281.52 752.91 ± 1266.37 < 0.01 MICU_CODE - CICU 2004 (22.06%) 42 (6.95%) General ICU 1133 (12.47%) 190 (31.46%) NICU 2458 (27.06%) 179 (29.64%) PICU 1408 (15.50%) 143 (23.68%) SICU 2082 (22.92%) 50 (8.28%) Figure 1 detailed association between serum albumin levels and the risk of mortality followed a U-shape. Table 2 : Displays the findings of threshold effect models that revealed a nonlinear association between serum albumin levels and the risk of mortality, identifying a breakpoint at around 34.6 g/L. Below this threshold, higher serum albumin levels were significantly associated with a reduced risk of death (OR = .93, P < .01), whereas above the threshold, elevated serum albumin levels were linked to an increased risk of mortality (OR = 1.05, P < .01). The observed two-stage effect was statistically significant (P < .01), underscoring the presence of a threshold effect of serum albumin on the risk of mortality. Table 2 Threshold effect analysis The associations between albumin and all-cause mortality For exposure: ABALBUMIN Outcome: DEAD model I A straight line effect 0.98 (0.97, 0.99) 0.0049 model II Breakpoint (K) 34.6 < K segment effect1 0.93 (0.91, 0.95) K segment effect2 1.05 (1.02, 1.08) 0.0002 The difference between 2 and 1 1.13 (1.09, 1.18) < 0.0001 Predicted value of equation at vertex -3.13 (-3.27, -2.99) log-likelihood ratio test < 0.001 Table Data: β (95%CI) Pvalue / OR (95%CI) Pvalue Adjusted for: WBC, RDW, NEUTROPHILCOUNT,WBC, POTASSIUM, LACTATE, CALCIUM; TOTALHOLESTEROLTOTAL; ALT; AST; CREATININE;DAYS, SEX Figure 2 Displays a smoothed spline plot illustrating the relationship between albumin level and in-hospital all-cause mortality. Table 3 、 Table 4 The plot revealed a L-shaped pattern in male patients across all age groups. To further explore this relationship, a two-stage linear regression model was employed to address the potential threshold effects. Specifically, serum albumin concentration exhibited a U-shaped correlation with mortality in male patients, with a critical point of 35.8 g/L. Conversely, female patients showed an L-shaped association with mortality. Overall, a U-shaped correlation was observed between albumin level and mortality in all patients, with critical points identified at 33.1 g/L for ≤ 28 days and 35.9 g/L for > 28 days. Table 3 Threshold effect analysis The associations between albumin and all-cause mortality by age. For exposure: ABALBUMIN Outcome: DEAD DAYS 分组 > 28 days <=28 days model I A straight line effect 0.98 (0.97, 1.00) 0.0461 0.96 (0.93, 0.99) 0.0059 model II Breakpoint (K) 35.9 33.1 < K segment effect1 0.94 (0.92, 0.97) < 0.0001 0.91 (0.87, 0.95) K segment effect2 1.04 (1.01, 1.08) 0.0074 1.07 (1.01, 1.15) 0.0322 The difference between 2 and 1 1.11 (1.06, 1.16) < 0.0001 1.18 (1.08, 1.30) 0.0003 Predicted value of equation at vertex -3.22 (-3.39, -3.05) -3.07 (-3.32, -2.82) log-likelihood ratio test < 0.001 < 0.001 Table 4 Threshold effect analysis The associations between albumin and all-cause mortality by sex. For exposure: ABALBUMIN Outcome: DEAD Gender 0(female) 1(male) model I A straight line effect 0.98 (0.96, 1.00) 0.0760 0.98 (0.96, 1.00) 0.0307 model II Breakpoint (K) 33.5 35.8 < K segment effect1 0.94 (0.90, 0.97) 0.0010 0.92 (0.90, 0.95) K segment effect2 1.02 (0.99, 1.06) 0.2284 1.08 (1.04, 1.12) < 0.0001 The difference between 2 and 1 1.09 (1.02, 1.16) 0.0073 1.17 (1.11, 1.23) < 0.0001 Predicted value of equation at vertex -3.13 (-3.36, -2.90) -3.16 (-3.34, -2.98) log-likelihood ratio test 0.008 < 0.001 Discussion In a study examining in-hospital mortality among pediatric intensive care unit patients, the focus was on evaluating the correlation between serum albumin levels upon admission and overall mortality. The cohort comprised 9085 patients, with 604 fatalities. The findings revealed a U-shaped relationship between serum albumin levels and mortality risk. Specifically, mortality risk decreased as serum albumin levels rose (OR = 0.93; 95% CI: .91, .95) in children with levels below 34.6 g/L, whereas it increased with higher serum albumin levels (OR = 1.05; 95% CI: 1.002, 1.08) in children with levels at or above 34.6 g/L. The association between serum albumin levels and in-hospital all-cause mortality involves various factors highlighting the significance of albumin. As the primary plasma protein synthesized by the liver, albumin serves multiple functions including the maintenance of plasma colloid osmotic pressure, nutrient transport, and regulation of inflammatory responses [ 11 ] . Hypoalbuminemia, characterized by decreased albumin levels, is commonly linked to conditions such as malnutrition, chronic diseases, and severe infections. Notably, low albumin levels are strongly correlated with poor nutritional status, which can compromise immune function, thereby elevating the susceptibility to infections and mortality [ 12 , 13 ] . For instance, demonstrated that a 1 g/L increase in serum albumin reduced the odds of death in hospitalized patients by 73%, emphasizing the potential of optimizing patients' nutritional status to enhance clinical outcomes [ 14 ] . Additionally, serum albumin plays a crucial role in modulating inflammatory responses. Apart from its role as a nutritional indicator, albumin is implicated in anti-inflammatory responses and the regulation of cellular immune function. Moreover, albumin levels are closely linked to the function of multiple organs. Elevated serum albumin levels typically signify robust organ function, whereas low levels may indicate a heightened risk of liver damage or multiple organ failure, particularly significant in intensive care settings. For instance, Study highlighted the impact of albumin levels on organ dysfunction [ 15 ] . Furthermore, Study demonstrated that reduced albumin levels were associated with decreased survival rates in heart transplant patients, further emphasizing the prognostic value of albumin in clinical outcomes [ 16 ] . The study revealed a U-shaped correlation between albumin levels and mortality among chinese pediatric intensive care unit patients, aligning with prior research findings. For instance, individuals with chronic kidney disease (CKD) and diabetic nephropathy (DKD) exhibited a U-shaped link between serum albumin levels and both all-cause mortality and cardiovascular mortality, with optimal risk thresholds at 0.923 and 1.026, respectively [ 17 ] . Similarly, patients with coronary artery disease (CAD) displayed a U-shaped association between albumin levels and major adverse cardiovascular events (MACE) as well as composite cardiovascular endpoints (MACCE), with a minimum risk point at 45 g/L [ 18 ] . In individuals with type 2 diabetes mellitus (T2DM) and CAD, the significant U-shaped relationship between free fatty acids (FFA) and ischemic events like MACE was observed primarily at low albumin levels, indicating that albumin might influence this connection through nutritional status [ 19 ] . This U-shaped pattern could signify a dual risk scenario: low albumin levels indicating malnutrition or inflammation (as suggested in the literature [9] where hypokalemia influences the risk of death through low albumin), while very high albumin levels may be linked to dehydration or hemoconcentration [ 17 , 18 ] . The association between albumin levels and mortality exhibits diverse patterns across different populations, including J-shaped, L-shaped, and linear negative correlations. For instance, albumin-related parameters like SMI demonstrate an inverse J-shaped relationship with mortality in prediabetic cohorts and a U-shaped association in individuals with type 2 diabetes [ 20 ] . Linear negative correlations are more prevalent in the general population or specific conditions such as cirrhosis, implying a protective function for albumin as a marker of nutritional status and inflammation [ 21 ] . In our female patients showed an L-shaped association with mortality. In contrast to prior research, our study introduces several novel approaches. Initially, we determined an overarching optimal threshold of 34.6 mmol/L for children and observed notable gender variances, pinpointing optimal thresholds of 35.8 mmol/L for males. Additionally, we employed a robust large cohort design to thoroughly control for significant confounders, thereby offering more dependable evidence supporting a U-shaped correlation between albumin levels and mortality. These discoveries carry substantial clinical significance.This study is constrained by its retrospective design and potential selection bias. Despite controlling for various confounding variables, the findings may have limited generalizability due to the geographical constraints of the sample and the diverse sources of data. Hence, integrating clinical follow-up and external verification outcomes is advisable to enhance the robustness and utility of the conclusions in practical settings. In conclusion, the serum albumin levels upon admission exhibit a significant association with in-hospital mortality among patients in the pediatric intensive care unit (PICU), thus serving as a crucial prognostic indicator in clinical settings. Subsequent research endeavors should explore the combined impact of albumin with other biomarkers to enhance the precision of prognostic assessments and intervention approaches in pediatric intensive care. Declarations Funding This work has no financial support Clinical trial number Not applicable Data Availability Statement Publicly available datasets were analyzed in this study. These data are available at http://pic.nbscn.org// Ethics statement Studies involving human participants were reviewed and approved by the Approval Committee of the West China Hospital of Sichuan University. Written informed consent for participation was not provided by the participants’ legal guardians/next of kin because: The requirement for informed consent was not required due to the retrospective nature of the study and containing no individual information. Participate declaration Not applicable Authors' contributions Wei Liu analyzed the data, drafted the manuscript, contributed to the study design, and revised the article. Wei Liu and Li Zhou contributed to the conception, design, and revision of the manuscript. All the authors have read and approved the final manuscript. Compliance with Ethical Standards2 Competing interests The authors have no relevant financial or non-financial interests to disclose. References Ghimire B, Shah S, Paudyal MB, et al. Serial estimations of serum albumin levels as a prognostic marker in critically ill patients admitted in ICU in tertiary center: An observational study[J]. Med (Baltim). 2023;102(45):e35979. https://pubmed.ncbi.nlm.nih.gov/37960756/ . Kim YS, Sol IS, Kim MJ, et al. Serum Albumin as a Biomarker of Poor Prognosis in the Pediatric Patients in Intensive Care Unit[J]. Korean J Crit Care Med. 2017;32(4):347–55. https://pubmed.ncbi.nlm.nih.gov/31723656/ . Tie X, Zhao Y, Sun T et al. Associations between serum albumin level trajectories and clinical outcomes in sepsis patients in ICU: insights from longitudinal group trajectory modeling[J]. Front Nutr, 2024,111433544 https://pubmed.ncbi.nlm.nih.gov/39101009/ Yue C, Zhang C, Ying C, et al. Reduced serum cholinesterase is an independent risk factor for all-cause mortality in the pediatric intensive care unit[J]. Front Nutr. 2022;9:809449. https://pubmed.ncbi.nlm.nih.gov/36505241/ . Leite HP, Rodrigues DSA, de Oliveira IS, et al. Serum Albumin Is an Independent Predictor of Clinical Outcomes in Critically Ill Children[J]. Pediatr Crit Care Med. 2016;17(2):e50–7. https://pubmed.ncbi.nlm.nih.gov/26695729/ . Gowa MA, Tauseef U, Ahmed SH. A relation between serum albumin level and prognosis of critically ill children admitted to the paediatric Intensive Care Unit[J]. J Pak Med Assoc. 2023;73(5):1034–42. Ventura JC, Oliveira L, Silveira TT, et al. Admission factors associated with nutritional status deterioration and prolonged pediatric intensive care unit stay in critically ill children: PICU-ScREEN multicenter study[J]. JPEN J Parenter Enter Nutr. 2022;46(2):330–8. Qian SY, Liu J. [Relationship between serum albumin level and prognosis in children with sepsis, severe sepsis or septic shock][J]. Zhonghua Er Ke Za Zhi. 2012;50(3):184–7. Ari HF, Turanli EE, Yavuz S, et al. Association between serum albumin levels at admission and clinical outcomes in pediatric intensive care units: a multi-center study[J]. 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Comparison of serum albumin, serum C-reactive protein, and pulse wave velocity as predictors of the 4-year mortality of chronic hemodialysis patients[J]. J Atheroscler Thromb. 2011;18(12):1071–9. Kato TS, Cheema FH, Yang J, et al. Preoperative serum albumin levels predict 1-year postoperative survival of patients undergoing heart transplantation[J]. Circ Heart Fail. 2013;6(4):785–91. Cao B, Guo Z, Li DT, et al. The association between stress-induced hyperglycemia ratio and cardiovascular events as well as all-cause mortality in patients with chronic kidney disease and diabetic nephropathy[J]. Cardiovasc Diabetol. 2025;24(1):55. Zheng YY, Wu TT, Hou XG, et al. The higher the serum albumin, the better? Findings from the PRACTICE study[J]. Eur J Intern Med. 2023;116:162–7. Pan Y, Wu TT, Mao XF, et al. Decreased free fatty acid levels associated with adverse clinical outcomes in coronary artery disease patients with type 2 diabetes: findings from the PRACTICE study[J]. Eur J Prev Cardiol. 2023;30(8):730–9. Zhao J, Lu Q, Cong XX, et al. The skeletal muscle mass index is a predictor for all-cause mortality in US adults with type 2 diabetes or pre-diabetes[J]. Diabetes Res Clin Pract. 2025;225:112254. Leache L, Gutierrez-Valencia M, Saiz LC, et al. Meta-analysis: Efficacy and safety of albumin in the prevention and treatment of complications in patients with cirrhosis[J]. Aliment Pharmacol Ther. 2023;57(6):620–34. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 07 Jan, 2026 Editor invited by journal 19 Nov, 2025 Editor assigned by journal 17 Nov, 2025 Submission checks completed at journal 17 Nov, 2025 First submitted to journal 12 Nov, 2025 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. 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1","display":"","copyAsset":false,"role":"figure","size":67803,"visible":true,"origin":"","legend":"\u003cp\u003eThe associations between albumin and all-cause mortality\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8101330/v1/c7ad356333a7034451c6645c.png"},{"id":100009417,"identity":"1b543206-5c15-45f4-89d8-a0e6341b7894","added_by":"auto","created_at":"2026-01-12 06:02:14","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":81809,"visible":true,"origin":"","legend":"\u003cp\u003eDisplays a smoothed spline plot illustrating the relationship between albumin level and in-hospital all-cause mortality\u003c/p\u003e\n\u003cp\u003ea, b Associations between albumin level and all-cause mortality stratified by sex and age.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8101330/v1/ef9b70fbcfbaa918227b76f1.png"},{"id":100381298,"identity":"ab93d7f8-53d4-4a2c-9f1d-15dba3afd940","added_by":"auto","created_at":"2026-01-16 10:37:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":642136,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8101330/v1/68c7bf46-9eec-49f8-8196-933821467de5.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association Between Albumin Level at Admission to the Chinese Pediatric Intensive Care Unit and In-Hospital All-Cause Mortality","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSerum albumin levels serve as crucial indicator\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003es in critically ill patients and are closely associated with unfavorable prognoses\u003c/span\u003e\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eReduced albumin levels are widely acknowledged as a physiological marker of tissue hypoperfusion and\u003c/span\u003e have significant prognostic implications in \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ethe clinical setting\u003c/span\u003e. This is attributed to the multifaceted roles of albumin, including the maintenance of colloidal osmotic pressure, antioxidant and anti-inflammatory functions, regulation of acid-base equilibrium, \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eand facilitation of nutrient transport and metabolism. Consequently, albumin plays a pivotal role in the evaluation and treatment of patients\u003c/span\u003e\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. In acute conditions, particularly within the intensive care unit (ICU) setting, albumin level is recognized as a valuable biomarker for predicting patient survival and clinical outcomes \u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWhile the association between albumin level \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eat admission and mortality has been established in adult studies, evidence in pediatric populations remains inconclusive and underexplored\u003c/span\u003e\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eSome studies on critically ill pediatric patients have proposed a link between low albumin levels and adverse clinical outcomes\u003c/span\u003e\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eHowever, other\u003c/span\u003e studies have indicated that albumin levels do not significantly impact survival in pediatric ICU patients, highlighting the insufficient and inconsistent nature of \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ethe current data in this population\u003c/span\u003e\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eMoreover, there is a scarcity of clinical data and research\u003c/span\u003e on children, creating critical knowledge gaps that require immediate attention.\u003c/p\u003e \u003cp\u003eThis study aimed to evaluate the correlation between serum albumin levels \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eat admission and all-cause mortality among chinese pediatric ICU patients. By investigating the relationship between albumin levels at admission and clinical outcomes in pediatric ICU patients, th\u003c/span\u003eis study sought to offer insights for enhancing early diagnosis and treatment in pediatric intensive care settings. The findings of this study have the potential to advance \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ethe comprehension of critically ill pediatric patients, impact clinical practices, and offer novel insights and empirical support for future\u003c/span\u003e research.\u003c/p\u003e"},{"header":"Research methods","content":"\u003cp\u003eResearch Design and Data Sources\u003c/p\u003e \u003cp\u003eThis study utilized a retrospective cohort design to meticulously examine the intricate relationship between initial laboratory albumin levels and mortality rates among patients admitted to the pediatric intensive care unit. This area of research is critical as it has the potential to significantly influence clinical practices and patient outcomes. In addition to evaluating albumin levels, the study also aimed to investigate the impact of various factors, such as sex and specific ICU type, on this association, thereby providing a more nuanced understanding of how these variables may interact and affect patient prognosis\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe data for this research were sourced from a large-scale pediatric electronic database developed by the esteemed Children's Hospital at Zhejiang University School of Medicine. This comprehensive database systematically records all clinical information related to patients admitted to the \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003epediatric intensive care unit\u003c/span\u003e beginning at the time of admission. It encompasses a wide array of relevant data points, \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eand thus serv\u003c/span\u003ees as a reliable foundation for this study. This thorough approach ensures that the findings are both valid and applicable to real-world clinical scenarios, ultimately contributing to the body of knowledge that informs \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ethe best practices in pediatric critical care.\u003c/span\u003e\u003c/p\u003e \u003cp\u003eStudy Population\u003c/p\u003e \u003cp\u003eThe study population comprised pediatric patients admitted to the pediatric intensive care unit at Zhejiang University Children's Hospital from 2010 to 2018. Eligible participants were those age\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ed\u003c/span\u003e\u0026thinsp;\u0026lt;\u0026thinsp;18 \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eyears who underwent\u003c/span\u003e initial albumin assessment within 24 h of hospitalization. Individuals with incomplete medical records were excluded from analysis. Ultimately, the final dataset included 9,689 \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003epatients qualified\u003c/span\u003e for comprehensive analysis.\u003c/p\u003e \u003cp\u003eVariable Definitions\u003c/p\u003e \u003cp\u003eExposure Variable: The primary variable of interest was the initial laboratory albumin level, which was treated as a continuous variable.\u003c/p\u003e \u003cp\u003eOutcome Variable: The outcome of interest was the in-hospital all-cause mortality rate, \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ewhich was represented as a binary variable. Patients who passed away were assigned a value of 1\u003c/span\u003e, whereas those who survived were assigned a value of 0.\u003c/p\u003e \u003cp\u003eCovariates: Other variables considered in the analysis included patient sex (male/female), length of hospital stay, additional laboratory indicators (such as white blood cell count, platelet count, and lactate levels), and type of ICU (including cardiac ICU, general \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ePICU, etc.). All laboratory test results were obtained during the first 24 h of admission.\u003c/span\u003e\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eWe used weighted multivariate linear regression models and smooth curve fitting to evaluate the associations between serum albumin levels and mortality. The other variables were considered potential effect modifiers. For continuous variables, a weighted linear regression model was used to calculate the differences among \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ethe different groups. For categorical variables, the weighted chi-squared test was used.\u003c/span\u003e Significance value was \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eset at\u003c/span\u003e p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. A weighted generalized additive model and smooth curve fitting were conducted to address \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ethe nonlinearity\u003c/span\u003e. When nonlinearity was uncovered, we first calculated the vital inflection point using a recursive algorithm, \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eand then conducted a weighted two-piecewise linear regression model on both sides of the inflection point. All statistical analyses were\u003c/span\u003e performed using R (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.R-project.org\u003c/span\u003e\u003cspan address=\"http://www.R-project.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, The R Foundation) and EmpowerStats software (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.empowerstats.com\u003c/span\u003e\u003cspan address=\"http://www.empowerstats.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, X\u0026amp;Y Solutions, Inc., Boston, MA).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e presents a comparison of baseline characteristics between \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ethe two study populations\u003c/span\u003e: survival group (N\u0026thinsp;=\u0026thinsp;9085) and death group (N\u0026thinsp;=\u0026thinsp;604). The authors analyzed various laboratory and clinical parameters to assess differences between the groups. The findings revealed that individuals in the death group exhibited significantly elevated WBC count, RBC distribution width, serum albumin, serum potassium, total calcium, lactate, ALT, and AST \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003elevels compared to those in the survival group (P\u0026thinsp;\u0026lt;\u0026thinsp;.01).\u003c/span\u003e\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDescription of Study Population\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDEAD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value*\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e604\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWBC(10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.10\u0026thinsp;\u0026plusmn;\u0026thinsp;20.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16.22\u0026thinsp;\u0026plusmn;\u0026thinsp;36.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRBC(10\u003csup\u003e12\u003c/sup\u003e/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.89\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNEUTROPHILCOUNT(10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63.85\u0026thinsp;\u0026plusmn;\u0026thinsp;18.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57.50\u0026thinsp;\u0026plusmn;\u0026thinsp;22.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRDW(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.82\u0026thinsp;\u0026plusmn;\u0026thinsp;2.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.54\u0026thinsp;\u0026plusmn;\u0026thinsp;2.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eALBUMIN(g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35.85\u0026thinsp;\u0026plusmn;\u0026thinsp;6.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.48\u0026thinsp;\u0026plusmn;\u0026thinsp;8.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePOTASSIUM(mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.12\u0026thinsp;\u0026plusmn;\u0026thinsp;1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCALCIUMTOTAL(mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLACTATE(mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.44\u0026thinsp;\u0026plusmn;\u0026thinsp;2.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.09\u0026thinsp;\u0026plusmn;\u0026thinsp;5.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eALT(U/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54.85\u0026thinsp;\u0026plusmn;\u0026thinsp;287.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e139.74\u0026thinsp;\u0026plusmn;\u0026thinsp;598.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAST(U/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e119.61\u0026thinsp;\u0026plusmn;\u0026thinsp;647.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e372.56\u0026thinsp;\u0026plusmn;\u0026thinsp;1442.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHOSPTL-DAY(day)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.64\u0026thinsp;\u0026plusmn;\u0026thinsp;20.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.24\u0026thinsp;\u0026plusmn;\u0026thinsp;22.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge(day)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e858.28\u0026thinsp;\u0026plusmn;\u0026thinsp;1281.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e752.91\u0026thinsp;\u0026plusmn;\u0026thinsp;1266.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMICU_CODE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCICU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2004 (22.06%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42 (6.95%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGeneral ICU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1133 (12.47%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e190 (31.46%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNICU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2458 (27.06%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e179 (29.64%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePICU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1408 (15.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e143 (23.68%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSICU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2082 (22.92%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50 (8.28%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e detailed association between serum albumin levels and the risk of mortality followed a U-shape. Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e: Displays the findings of threshold effect models that revealed a nonlinear association between serum albumin levels and the risk of mortality, identifying a breakpoint at around 34.6 g/L. Below this threshold, higher serum albumin levels were significantly associated with a reduced risk of death (OR\u0026thinsp;=\u0026thinsp;.93, P\u0026thinsp;\u0026lt;\u0026thinsp;.01), whereas above the threshold, elevated serum albumin levels were linked to an increased risk of mortality (OR\u0026thinsp;=\u0026thinsp;1.05, P\u0026thinsp;\u0026lt;\u0026thinsp;.01). The observed two-stage effect was statistically significant (P\u0026thinsp;\u0026lt;\u0026thinsp;.01), underscoring the presence of a threshold effect of serum albumin on the risk of mortality.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThreshold effect analysis The associations between albumin and all-cause mortality\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"2\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFor exposure: ABALBUMIN\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOutcome:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDEAD\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emodel I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eA straight line effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98 (0.97, 0.99) 0.0049\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emodel II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBreakpoint (K)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt; K segment effect1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.93 (0.91, 0.95)\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt; K segment effect2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.05 (1.02, 1.08) 0.0002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe difference between 2 and 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.13 (1.09, 1.18)\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePredicted value of equation at vertex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3.13 (-3.27, -2.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003elog-likelihood ratio test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eTable Data: \u0026beta; (95%CI) Pvalue / OR (95%CI) Pvalue\u003c/p\u003e\n\u003cp\u003eAdjusted for: WBC, RDW, NEUTROPHILCOUNT,WBC, POTASSIUM, LACTATE, CALCIUM; TOTALHOLESTEROLTOTAL; ALT; AST; CREATININE;DAYS, SEX\u003c/p\u003e\n\u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e Displays a smoothed spline plot illustrating the relationship between albumin level and in-hospital all-cause mortality. Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cstrong\u003e、\u003c/strong\u003eTable \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e The plot revealed a L-shaped pattern in male patients across all age groups. To further explore this relationship, a two-stage linear regression model was employed to address the potential threshold effects. Specifically, serum albumin concentration exhibited a U-shaped correlation with mortality in male patients, with a critical point of 35.8 g/L. Conversely, female patients showed an L-shaped association with mortality. Overall, a U-shaped correlation was observed between albumin level and mortality in all patients, with critical points identified at 33.1 g/L for \u0026le;\u0026thinsp;28 days and 35.9 g/L for \u0026gt;\u0026thinsp;28 days.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThreshold effect analysis The associations between albumin and all-cause mortality by age.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFor exposure: ABALBUMIN\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOutcome:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDEAD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDAYS 分组\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;28 days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;=28 days\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emodel I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eA straight line effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98 (0.97, 1.00) 0.0461\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.96 (0.93, 0.99) 0.0059\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emodel II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBreakpoint (K)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt; K segment effect1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.94 (0.92, 0.97)\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.91 (0.87, 0.95)\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt; K segment effect2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.04 (1.01, 1.08) 0.0074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.07 (1.01, 1.15) 0.0322\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe difference between 2 and 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.11 (1.06, 1.16)\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.18 (1.08, 1.30) 0.0003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePredicted value of equation at vertex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3.22 (-3.39, -3.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3.07 (-3.32, -2.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003elog-likelihood ratio test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThreshold effect analysis The associations between albumin and all-cause mortality by sex.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFor exposure: ABALBUMIN\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOutcome:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDEAD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1(male)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emodel I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eA straight line effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98 (0.96, 1.00) 0.0760\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98 (0.96, 1.00) 0.0307\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emodel II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBreakpoint (K)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt; K segment effect1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.94 (0.90, 0.97) 0.0010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.92 (0.90, 0.95)\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt; K segment effect2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.02 (0.99, 1.06) 0.2284\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.08 (1.04, 1.12)\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe difference between 2 and 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.09 (1.02, 1.16) 0.0073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.17 (1.11, 1.23)\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePredicted value of equation at vertex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3.13 (-3.36, -2.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-3.16 (-3.34, -2.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003elog-likelihood ratio test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn a study examining in-hospital mortality among pediatric intensive care unit patients, the focus was on evaluating the correlation between serum albumin levels upon admission and overall mortality. The cohort comprised 9085 patients, with 604 fatalities. The findings revealed a U-shaped relationship between serum albumin levels and mortality risk. Specifically, mortality risk decreased as serum albumin levels rose (OR\u0026thinsp;=\u0026thinsp;0.93; 95% CI: .91, .95) in children with levels below 34.6 g/L, whereas it increased with higher serum albumin levels (OR\u0026thinsp;=\u0026thinsp;1.05; 95% CI: 1.002, 1.08) in children with levels at or above 34.6 g/L.\u003c/p\u003e \u003cp\u003eThe association between serum albumin levels and in-hospital all-cause mortality involves various factors highlighting the significance of albumin. As the primary plasma protein synthesized by the liver, albumin serves multiple functions including the maintenance of plasma colloid osmotic pressure, nutrient transport, and regulation of inflammatory responses\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. Hypoalbuminemia, characterized by decreased albumin levels, is commonly linked to conditions such as malnutrition, chronic diseases, and severe infections. Notably, low albumin levels are strongly correlated with poor nutritional status, which can compromise immune function, thereby elevating the susceptibility to infections and mortality\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. For instance, demonstrated that a 1 g/L increase in serum albumin reduced the odds of death in hospitalized patients by 73%, emphasizing the potential of optimizing patients' nutritional status to enhance clinical outcomes\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. Additionally, serum albumin plays a crucial role in modulating inflammatory responses. Apart from its role as a nutritional indicator, albumin is implicated in anti-inflammatory responses and the regulation of cellular immune function. Moreover, albumin levels are closely linked to the function of multiple organs. Elevated serum albumin levels typically signify robust organ function, whereas low levels may indicate a heightened risk of liver damage or multiple organ failure, particularly significant in intensive care settings. For instance, Study highlighted the impact of albumin levels on organ dysfunction\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. Furthermore, Study demonstrated that reduced albumin levels were associated with decreased survival rates in heart transplant patients, further emphasizing the prognostic value of albumin in clinical outcomes\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe study revealed a U-shaped correlation between albumin levels and mortality among chinese pediatric intensive care unit patients, aligning with prior research findings. For instance, individuals with chronic kidney disease (CKD) and diabetic nephropathy (DKD) exhibited a U-shaped link between serum albumin levels and both all-cause mortality and cardiovascular mortality, with optimal risk thresholds at 0.923 and 1.026, respectively\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. Similarly, patients with coronary artery disease (CAD) displayed a U-shaped association between albumin levels and major adverse cardiovascular events (MACE) as well as composite cardiovascular endpoints (MACCE), with a minimum risk point at 45 g/L\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. In individuals with type 2 diabetes mellitus (T2DM) and CAD, the significant U-shaped relationship between free fatty acids (FFA) and ischemic events like MACE was observed primarily at low albumin levels, indicating that albumin might influence this connection through nutritional status\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. This U-shaped pattern could signify a dual risk scenario: low albumin levels indicating malnutrition or inflammation (as suggested in the literature [9] where hypokalemia influences the risk of death through low albumin), while very high albumin levels may be linked to dehydration or hemoconcentration\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe association between albumin levels and mortality exhibits diverse patterns across different populations, including J-shaped, L-shaped, and linear negative correlations. For instance, albumin-related parameters like SMI demonstrate an inverse J-shaped relationship with mortality in prediabetic cohorts and a U-shaped association in individuals with type 2 diabetes\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. Linear negative correlations are more prevalent in the general population or specific conditions such as cirrhosis, implying a protective function for albumin as a marker of nutritional status and inflammation\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e. In our female patients showed an L-shaped association with mortality.\u003c/p\u003e \u003cp\u003eIn contrast to prior research, our study introduces several novel approaches. Initially, we determined an overarching optimal threshold of 34.6 mmol/L for children and observed notable gender variances, pinpointing optimal thresholds of 35.8 mmol/L for males. Additionally, we employed a robust large cohort design to thoroughly control for significant confounders, thereby offering more dependable evidence supporting a U-shaped correlation between albumin levels and mortality.\u003c/p\u003e \u003cp\u003eThese discoveries carry substantial clinical significance.This study is constrained by its retrospective design and potential selection bias. Despite controlling for various confounding variables, the findings may have limited generalizability due to the geographical constraints of the sample and the diverse sources of data. Hence, integrating clinical follow-up and external verification outcomes is advisable to enhance the robustness and utility of the conclusions in practical settings.\u003c/p\u003e \u003cp\u003eIn conclusion, the serum albumin levels upon admission exhibit a significant association with in-hospital mortality among patients in the pediatric intensive care unit (PICU), thus serving as a crucial prognostic indicator in clinical settings. Subsequent research endeavors should explore the combined impact of albumin with other biomarkers to enhance the precision of prognostic assessments and intervention approaches in pediatric intensive care.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work has no financial support\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePublicly available datasets were analyzed in this study. These data are available at http://pic.nbscn.org//\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudies involving human participants were reviewed and approved by the Approval Committee of the West China Hospital of Sichuan University. Written informed consent for participation was not provided by the participants\u0026rsquo; legal guardians/next of kin because: The requirement for informed consent was not required due to the retrospective nature of the study and containing no individual information.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParticipate declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWei Liu\u0026nbsp;analyzed the data, drafted the manuscript, contributed to the study design, and revised the article. \u0026nbsp;Wei Liu and\u0026nbsp;Li Zhou\u0026nbsp;contributed to the conception, design, and revision of the manuscript. All the authors have read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003eCompliance with Ethical Standards2\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGhimire B, Shah S, Paudyal MB, et al. Serial estimations of serum albumin levels as a prognostic marker in critically ill patients admitted in ICU in tertiary center: An observational study[J]. Med (Baltim). 2023;102(45):e35979. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubmed.ncbi.nlm.nih.gov/37960756/\u003c/span\u003e\u003cspan address=\"https://pubmed.ncbi.nlm.nih.gov/37960756/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim YS, Sol IS, Kim MJ, et al. Serum Albumin as a Biomarker of Poor Prognosis in the Pediatric Patients in Intensive Care Unit[J]. Korean J Crit Care Med. 2017;32(4):347\u0026ndash;55. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubmed.ncbi.nlm.nih.gov/31723656/\u003c/span\u003e\u003cspan address=\"https://pubmed.ncbi.nlm.nih.gov/31723656/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTie X, Zhao Y, Sun T et al. Associations between serum albumin level trajectories and clinical outcomes in sepsis patients in ICU: insights from longitudinal group trajectory modeling[J]. Front Nutr, 2024,111433544\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubmed.ncbi.nlm.nih.gov/39101009/\u003c/span\u003e\u003cspan address=\"https://pubmed.ncbi.nlm.nih.gov/39101009/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYue C, Zhang C, Ying C, et al. Reduced serum cholinesterase is an independent risk factor for all-cause mortality in the pediatric intensive care unit[J]. Front Nutr. 2022;9:809449. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubmed.ncbi.nlm.nih.gov/36505241/\u003c/span\u003e\u003cspan address=\"https://pubmed.ncbi.nlm.nih.gov/36505241/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeite HP, Rodrigues DSA, de Oliveira IS, et al. Serum Albumin Is an Independent Predictor of Clinical Outcomes in Critically Ill Children[J]. Pediatr Crit Care Med. 2016;17(2):e50\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubmed.ncbi.nlm.nih.gov/26695729/\u003c/span\u003e\u003cspan address=\"https://pubmed.ncbi.nlm.nih.gov/26695729/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGowa MA, Tauseef U, Ahmed SH. A relation between serum albumin level and prognosis of critically ill children admitted to the paediatric Intensive Care Unit[J]. J Pak Med Assoc. 2023;73(5):1034\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVentura JC, Oliveira L, Silveira TT, et al. Admission factors associated with nutritional status deterioration and prolonged pediatric intensive care unit stay in critically ill children: PICU-ScREEN multicenter study[J]. JPEN J Parenter Enter Nutr. 2022;46(2):330\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQian SY, Liu J. [Relationship between serum albumin level and prognosis in children with sepsis, severe sepsis or septic shock][J]. Zhonghua Er Ke Za Zhi. 2012;50(3):184\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAri HF, Turanli EE, Yavuz S, et al. Association between serum albumin levels at admission and clinical outcomes in pediatric intensive care units: a multi-center study[J]. BMC Pediatr. 2024;24(1):844.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZeng X, Yu G, Lu Y, et al. PIC, a paediatric-specific intensive care database[J]. Sci Data. 2020;7(1):14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhu L, Chen M, Lin X. Serum albumin level for prediction of all-cause mortality in acute coronary syndrome patients: a meta-analysis[J]. Biosci Rep, 2020,40(1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLevitt DG, Levitt MD. Human serum albumin homeostasis: a new look at the roles of synthesis, catabolism, renal and gastrointestinal excretion, and the clinical value of serum albumin measurements[J]. Int J Gen Med. 2016;9:229\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBretschera C, Boesiger F, Kaegi-Braun N, et al. Admission serum albumin concentrations and response to nutritional therapy in hospitalised patients at malnutrition risk: Secondary analysis of a randomised clinical trial[J]. EClinicalMedicine. 2022;45:101301.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbdeen Y, Kaako A, Ahmad AZ, et al. The Prognostic Effect of Serum Albumin Level on Outcomes of Hospitalized COVID-19 Patients[J]. Crit Care Res Pract. 2021;2021:9963274.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmemiya N, Ogawa T, Otsuka K, et al. Comparison of serum albumin, serum C-reactive protein, and pulse wave velocity as predictors of the 4-year mortality of chronic hemodialysis patients[J]. J Atheroscler Thromb. 2011;18(12):1071\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKato TS, Cheema FH, Yang J, et al. Preoperative serum albumin levels predict 1-year postoperative survival of patients undergoing heart transplantation[J]. Circ Heart Fail. 2013;6(4):785\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCao B, Guo Z, Li DT, et al. The association between stress-induced hyperglycemia ratio and cardiovascular events as well as all-cause mortality in patients with chronic kidney disease and diabetic nephropathy[J]. Cardiovasc Diabetol. 2025;24(1):55.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZheng YY, Wu TT, Hou XG, et al. The higher the serum albumin, the better? Findings from the PRACTICE study[J]. Eur J Intern Med. 2023;116:162\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePan Y, Wu TT, Mao XF, et al. Decreased free fatty acid levels associated with adverse clinical outcomes in coronary artery disease patients with type 2 diabetes: findings from the PRACTICE study[J]. Eur J Prev Cardiol. 2023;30(8):730\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao J, Lu Q, Cong XX, et al. The skeletal muscle mass index is a predictor for all-cause mortality in US adults with type 2 diabetes or pre-diabetes[J]. Diabetes Res Clin Pract. 2025;225:112254.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeache L, Gutierrez-Valencia M, Saiz LC, et al. Meta-analysis: Efficacy and safety of albumin in the prevention and treatment of complications in patients with cirrhosis[J]. Aliment Pharmacol Ther. 2023;57(6):620\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"albumin, mortality, ICU, pediatric","lastPublishedDoi":"10.21203/rs.3.rs-8101330/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8101330/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eThis study investigated the association between albumin level upon admission to the pediatric intensive care unit (PICU)and in-hospital all-cause mortality.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA retrospective cohort study was conducted using data from a large pediatric electronic database that included 9,689 critically ill children. The primary exposure variable was the first albumin \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003elevel\u003c/span\u003e, \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003ewhich was analyzed as a continuous variable, while the outcome variable was in-hospital mortality.\u003c/span\u003e Multiple regression was employed to assess the relationship between albumin \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003elevel\u003c/span\u003e and mortality, adjusting for potential confounders, \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003esuch as\u003c/span\u003e length of hospital stay, sex, and other laboratory indicators.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe results of the study showed that the association between serum albumin levels and the risk of mortality followed a U-shape. The risk of mortality decreased with increasing serum albumin levels (OR\u0026thinsp;=\u0026thinsp;0.93; 95% CI: 0.91, 0.95) in children with serum albumin levels\u0026thinsp;\u0026lt;\u0026thinsp;34.6 g/L and increased with increasing serum albumin levels (OR\u0026thinsp;=\u0026thinsp;1.05; 95% CI: 1.002, 1.08) in children with serum albumin levels\u0026thinsp;\u0026ge;\u0026thinsp;34.6 g/L.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThere was a U-shaped association between serum albumin levels and mortality in critically ill children admitted to the intensive care unit(\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eICU).\u003c/span\u003e\u003c/p\u003e","manuscriptTitle":"Association Between Albumin Level at Admission to the Chinese Pediatric Intensive Care Unit and In-Hospital All-Cause Mortality","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-12 06:02:09","doi":"10.21203/rs.3.rs-8101330/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-01-07T07:03:23+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-11-19T08:02:01+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-18T02:45:12+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-18T02:43:58+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pediatrics","date":"2025-11-13T04:12:45+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"615f24c2-bc56-4095-bece-1ef3c2a052bd","owner":[],"postedDate":"January 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-01-12T06:02:09+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-12 06:02:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8101330","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8101330","identity":"rs-8101330","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}