The Role of the Lactate-to-Albumin Ratio in Predicting In-Hospital Mortality in Patients with Heart Failure with Preserved Ejection Fraction Presenting to the Emergency Department

The Role of the Lactate-to-Albumin Ratio in Predicting In-Hospital Mortality in Patients with Heart Failure with Preserved Ejection Fraction Presenting to the Emergency Department | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Role of the Lactate-to-Albumin Ratio in Predicting In-Hospital Mortality in Patients with Heart Failure with Preserved Ejection Fraction Presenting to the Emergency Department Sibel Güçlü Utlu, Muhammed Cüneyt Şeker, Murat Özmen, Fadime Kılınç Şeker This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8595219/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background Heart failure with preserved ejection fraction (HFpEF) is an important form of heart failure associated with high mortality rates. Identifying risk factors is crucial for improving hospital mortality rates. The lactate/albumin ratio (LAR) has been found to be associated with adverse clinical outcomes in conditions such as sepsis and myocardial infarction. In this study, we aim to evaluate the potential of LAR as a prognostic marker for mortality in patients with HFpEF. Methods In this retrospective study, patients diagnosed with HFpEF were included. Data from patients who were admitted to the emergency department or cardiology clinic between January 1, 2023, and June 1, 2024, were used from the hospital information system database. Results A total of 503 patients were included in the study, of whom 74 died during hospitalization. Univariate and multivariate Cox regression analyses were performed to determine the relationship between LAR at admission and hospital mortality. The LAR value was significantly higher in the group of patients who died during hospitalization compared to survivors (0.07 vs 0.05, p < 0.05). The area under the ROC curve was 0.636 (95% CI: 0.520–0.752), and the optimal cut-off value for LAR was 0.48. Conclusion An elevated LAR is significantly associated with mortality in HFpEF and can be used as an early prognostic marker for mortality in these patients. Biomarkers Heart Failure with Preserved Ejection Fraction Lactate/Albumin Ratio Mortality Retrospective Study Figures Figure 1 Background Heart failure is not a pathological diagnosis per se, but rather a clinical syndrome characterized by signs and symptoms of central and/or peripheral congestion arising from structural and/or functional abnormalities of the heart [ 1 ]. Although heart failure may arise from conditions such as valvular, pericardial, or endocardial diseases, it most commonly develops as a consequence of myocardial dysfunction. Additionally, arrhythmias and conduction system disorders can also precipitate heart failure. Identifying the underlying etiology is essential for the implementation of targeted, etiology-specific therapies. The classification most widely accepted in recent years is based on left ventricular ejection fraction. This categorization provides a clinically practical approach for guiding medical therapy. According to this system, patients who exhibit signs and/or symptoms of heart failure are classified as having reduced ejection fraction heart failure (HFrEF) if the left ventricular EF is ≤ 40%, mildly reduced ejection fraction heart failure (HFmrEF) if the EF ranges between 41–49%, and preserved ejection fraction heart failure (HFpEF) if the EF is ≥ 50%. [ 1 ]. The concepts of acute heart failure and chronic heart failure are also frequently used in clinical practice, reflecting the onset and progression of heart failure symptoms. Chronic HF refers to patients with an established diagnosis of heart failure or those with a more slowly progressive clinical course, whereas acute heart failure is used for rapidly developing clinical presentations (over minutes, hours, or days). For functional classification of heart failure, systems based solely on symptom severity—such as the NYHA classification—may be employed [ 2 ]. Despite advances in the prevention and treatment of cardiovascular diseases, the incidence of heart failure continues to increase in parallel with rising life expectancy [ 2 , 3 ]. The prevalence of heart failure in adults is estimated to range between 1% and 2% [ 4 – 6 ]. In addition, the age-related increase in prevalence is noteworthy [ 4 , 7 , 8 ]. Among the various types of heart failure, HFpEF is the most frequently encountered in people over 65 years old, reflecting its growing clinical importance in the aging population [ 9 ]. It is estimated that patients with reduced ejection fraction heart failure account for approximately 50% of all heart failure cases [ 7 , 8 , 10 ]. According to long-term follow-up data from the European Society of Cardiology, 60% of ambulatory heart failure patients were found to have HFrEF, whereas 16% had HFpEF [ 11 ]. HFpEF patients show notable differences when compared with those having reduced ejection fraction. HFpEF patients are generally older, predominantly female, and more likely to suffer from a range of non-cardiac health issues. Women constitute more than 50% of patients with heart failure [ 5 , 12 ]. This population exhibits a lower frequency of coronary artery disease [ 13 ]. Although the exact pathophysiology remains uncertain, numerous studies indicate that patients with HFpEF exhibit elevated levels of pro-inflammatory markers both in the heart and peripheral circulation. These studies also highlight the significant link between chronic, recurring immune-inflammatory activation and the worsening of ventricular diastolic dysfunction, as well as the progression of HFpEF [ 14 , 15 ]. The development of preserved ejection fraction heart failure is influenced by various factors, including advanced age, systemic hypertension (HT), obesity, physical inactivity, myocardial ischemia, and diabetes mellitus (DM), all of which complicate treatment strategies. Effectively identifying and managing underlying risk factors, causes, and coexisting health conditions can improve patient outcomes [ 16 ]. In patients hospitalized with HFpEF, the estimated annual mortality is approximately 15%, and long-term prognosis remains poor, with only about 35% surviving beyond five years (Borlaug BA). This prognosis is notably worse than many types of cancer [ 17 ]. Several scoring systems have been proposed for the diagnosis of heart failure with preserved ejection fraction, although none has demonstrated clear superiority over the others. In establishing the diagnosis of heart failure with preserved ejection fraction, evidence of elevated left ventricular filling pressures, diastolic dysfunction, or increased levels of natriuretic peptides may be used as indicators of underlying structural and/or functional cardiac abnormalities. An increasing number of these abnormalities proportionally raises the likelihood of a diagnosis of HFpEF [ 1 ]. Certain biochemical markers are crucial in optimizing the treatment of critically ill those suffering from cardiac insufficiency. A significant relationship has been observed between elevated lactate levels and mortality, which is commonly seen in critical patients [ 18 , 19 ]. Additionally, in cases of liver or kidney dysfunction, a series of complex changes can occur in the body (such as reduced lactate clearance and accelerated glycolysis), which may initially result in lower lactate levels. Lactate serves as a valuable tool in the early identification and therapeutic decision-making for patients with or at risk of infectious shock [ 20 , 21 ]. In the context of sepsis, serum albumin functions not only as a negative acute phase protein but also as an important indicator of disease severity and prognosis [ 22 ]. Various pathological factors, including nutritional insufficiencies and inflammatory responses, can influence the levels of both lactate and serum albumin in the body [ 23 ]. Research has shown that the lactate-to-albumin ratio (LAR) serves as a reliable biomarker used to assess survival chances in sepsis or septic shock patients [ 24 , 25 ]. Another study revealed that LAR performed better than lactate in severe sepsis [ 24 ]. According to one study, the lactate/albumin ratio was found to be a better predictor of both survival and favorable neurological recovery compared to lactate levels alone [ 26 ]. It is still unclear whether the lactate/albumin ratio is an effective predictor of clinical outcomes in patients with HFpEF. This study intends to investigate how well the LAR can predict mortality in HFpEF patients admitted to the emergency department or cardiology unit. Methods A retrospective investigation was carried out on individuals who sought care at the emergency department or cardiology clinic during the period from January 1, 2023, to June 1, 2024. According to the 2021 ESC Heart Failure Guidelines, the diagnosis of HFpEF requires: (1) the presence of clinical signs and/or symptoms of heart failure, (2) a left ventricular ejection fraction of ≥ 50%, and (3) objective evidence of structural and/or functional cardiac abnormalities consistent with left ventricular diastolic dysfunction and/or elevated left ventricular filling pressures [ 1 ]. Only patients over the age of 18 who fulfilled all of participants who fulfilled the following conditions were included in the study: clinical signs and symptoms of heart failure, left ventricular ejection fraction (EF) ≥ 50%, an N-terminal probrain natriuretic peptide (NT-proBNP) level exceeding 125 pg/mL, and at least one of the following findings detected by echocardiography: Left ventricular enlargement, dilation of the left atrium or impaired diastolic function. Only the data from the initial admission were included for patients with multiple hospital visits. Exclusion criteria for the patients were incomplete or unavailable data, length of stay less than 3 days, history of malignancy, detection of arrhythmia on electrocardiography during hospitalization, and the presence of valve pathology on conventional echocardiography (ECHO). Transthoracic echocardiograms (TTE), interpreted by a cardiology specialist, were retrospectively reviewed in compliance with the American Society of Echocardiography's established protocols [ 27 ]. Clinical parameters, including age, gender, comorbidities, laboratory values, LAR, and the mortality status of the patients, which was the final outcome of the study, were evaluated. Laboratory data were obtained frrom venous and artery blood samples at admission. GE vivid T8 (Vingmed Ultrasound AS, Horten, Norway) was used for TTE imaging. The Institutional Ethics Committee granted approval for this study (Approval Date: June 12, 2024; Decision No: 2024/06-118), and it was conducted following the ethical guidelines set by the Declaration of Helsinki. Statistical Analysis SPSS version 23.0 (Chicago, Illinois, USA) was used for the data analysis. A comparison was made between the baseline characteristics of survivors and non-survivors. The Kolmogorov-Smirnov test was performed to evaluate the normality of the data. For continuous variables with a normal distribution, the mean and standard deviation were used, while for variables that did not follow a normal distribution, the median and interquartile range were presented. Categorical variables were expressed as frequencies and percentages. For numerical data, either Student's t-test or Mann-Whitney U test was employed, depending on the data distribution. The chi-square test was applied for categorical variables. Both univariate and multivariate regression analyses were performed. ROC curve analysis was used to assess the relationship between HFpEF and the LAR across the entire study population. Statistical significance was defined as p-values below 0.05. Results Study group data were obtained from the hospital patient information database. Data from 1,910 heart failure patients, who either visited the emergency department or were sent to the cardiology clinic, were utilized in this study. According to the variables determined for the study, 110 patients had missing data. The remaining 1297 patients were excluded as they have at least one of the exclusion criterias. 503 patients were selected for inclusion in the study based on meeting the study’s criteria. A total of 74 patients (6.9% of those included) died while hospitalized during the course of the study (Table-1). Among the patients who died in the hospital, the admission LAR was significantly higher. Significant differences were found in additional variables when comparing the groups. The average age of the deceased patients was 77.5 ± 5 years (p < 0.001). The group with in-hospital mortality had a notably higher comorbidity rate compared to the other group. Although lactate levels were similar between the two groups, albumin levels showed a significant difference. Sodium and potassium levels did not show significant differences between the deceased and surviving patients, creatinine levels were markedly higher in the deceased patients (p < 0.001). Table-1 Demographic and Clinical Data N (%) All Patients N = 503 (%) Survivors N = 429 (%) Deceased N = 74 (%) P-value Gender (F) 259 (51.5) 224 (52.2) 35 (47.3) 0.43 Age 58 ± 12 55 ± 10 77.5 ± 5 < 0.001 Coronary Artery Disease (CAD) 185 (36.8) 123 (28.7) 62 (83.8) < 0.001 Diabetes Mellitus (DM) 102 (20.3) 73 (17) 29 (39.2) < 0.001 Atrial Fibrillation (AF) 38 (7.6) 21 (4.9) 17 (23) < 0.001 Hypertension (HT) 288 (57.3) 233 (54.4) 55 (74.3) 0.01 Stroke (SVO) 11 (2.2) 9 (2.1) 2 (2.7) 0.74 Hemoglobin (HGB) 15 ± 1.6 15.1 ± 1.6 14 ± 1.7 < 0.001 White Blood Cell (WBC) 9.4 ± 3.2 9.3 ± 3 9.8 ± 3.9 0.58 Platelet (PLT) 291 ± 89 293 ± 80 281 ± 128 0.67 Lactate 2.6 ± 1.7 2.5 ± 1.7 2.9 ± 1.4 0.07 Albumin 44 ± 6 45 ± 5.6 42 ± 7.4 < 0.001 Aspartate Aminotransferase (AST) 28 ± 16 27 ± 15 30 ± 19 0.82 Alanine Aminotransferase (ALT) 32 ± 18 33 ± 18 25 ± 17 < 0.001 Glucose 117 ± 69 119 ± 73 105 ± 41 0.65 Cholesterol 192 ± 44 170 ± 40 190 ± 51 0.81 Low-Density Lipoprotein (LDL) 124 ± 43 120 ± 41 121 ± 52 0.42 High-Density Lipoprotein (HDL) 45 ± 11 44 ± 10 47 ± 14 0.49 Triglycerides 185 ± 118 188 ± 116 169 ± 125 0.05 Creatinine 0.9 ± 0.5 0.9 ± 0.5 1.9 ± 0.3 < 0.001 Sodium 142 ± 3.1 141 ± 3 142 ± 3 0.32 Potassium 4.5 ± 0.4 4.5 ± 0.4 4.6 ± 0.5 0.22 Magnesium 2.5 ± 1.9 2.6 ± 1.9 1.9 ± 0.3 < 0.001 C-Reactive Protein (CRP) 6.1 ± 1.9 1.4 ± 0.7 1.5 ± 0.8 0.15 Uric Acid 5.6 ± 1.6 5.5 ± 1.6 6 ± 1.7 0.01 Lactate/Albumin Ratio (LAR) 0.05 ± 0.04 0.05 ± 0.03 0.07 ± 0.05 0.03 In the study, statistically significant variables were included in both univariate and multivariate regression analysis (Table-2). In this analysis, higher admission LAR (OR, 1.59; 95% CI, 1.23–2.05; P < 0.001), older age (OR, 1.46; 95% CI, 1.318–1.617; P < 0.001), presence of coronary artery disease (CAD) (OR, 0.351; 95% CI, 0.140–0.883; P < 0.026), presence of diabetes mellitus (DM) (OR, 0.267; 95% CI, 0.108–0.661; P < 0.004), and presence of atrial fibrillation (AF) (OR, 0.018; 95% CI, 0.003–0.106; P < 0.001) were found to be independent factors associated with in-hospital mortality. Table-2 The effects of different prognostic variables on mortality in univariate and multivariate logistic regression analyses. Prognostic Variables Univariate OR 95% CI p-value Multivariate OR 95% CI p-value Age 2.030 1.645–2.505 < 0.001 1.460 1.318–1.617 < 0.001 CAD 0.078 0.041–0.149 < 0.001 0.351 0.140–0.883 0.026 DM 0.318 0.187–0.541 < 0.001 0.267 0.108–0.661 0.004 AF 0.173 0.086–0.346 < 0.001 0.018 0.003–0.106 < 0.001 HT 0.411 0.236–0.715 0.002 0.251 0.061–1.037 0.560 HGB 0.770 0.661–0.898 < 0.001 1.226 0.829–1.812 0.307 ALT 0.971 0.953–0.988 < 0.001 0.935 0.892–0.980 0.005 Magnesium 0.193 0.067–0.561 0.003 0.779 0.142–4.264 0.774 Uric Acid 1.212 1.047–1.404 0.010 1.020 0.724–1.736 0.910 LAR 1.460 1.15–1.85 0.002 1.59 1.23–2.05 < 0.001 ( Abbreviations: OR: Odds Ratio, CI: Confidence Interval, CAD: Coronary Artery Disease, DM: Diabetes Mellitus, AF: Atrial Fibrillation, HT: Hypertension, HGB: Hemoglobin, ALT: Alanine Aminotransferase, LAR: Lactate/Albumin Ratio ) The ROC curve for predicting hospital mortality with LAR is shown in Figure-1. The AUC value of LAR at admission was 0.636; 95% CI (0.520–0.752); p = 0.035, with a sensitivity of 66% and specificity of 60% at a cutoff value of 0.48, making L/A a predictor for mortality in HFpEF (Figure-1). Discussion In this study, we assessed the prognostic significance of the LAR in HF patients whose data were available through the hospital information system. The data obtained indicate that a higher LAR at admission can predict the mortality level of hospitalized patients in a linear fashion. The prognosis of such patients is poor and, at the same time, poses significant economic and public health burdens [ 28 ]. As a result, the LAR could be employed as an easy-to-use and practical tool for risk assessment, aiding clinicians in forecasting the outcomes for these patients. Elevated LAR is linked to high lactate and low albumin levels. Initially, it was observed that LAR was more valuable than lactate or albumin on its own in forecasting mortality in critically ill patients such as sepsis [ 24 ]. However, both lactate and albumin levels can vary in many cases. Since we know that lactate metabolic levels are influenced by various mechanisms [ 21 ], it may not play a determining role for a disease in isolation. On the other hand, serum albumin is frequently employed for the clinical assessment and monitoring of diseases [ 29 ]. Due to its anti-inflammatory, anticoagulant preventing coagulation and inhibiting clot formation, serum albumin may have a potential role in cardiovascular diseases [ 30 ]. Low albumin levels are known to indicate poor prognosis in many diseases. Due to the reverse changes in lactate and albumin induced by different mechanisms, the LAR allows for more accurate predictions in determining the prognosis of heart failure patients [ 31 ]. In HFpEF patients, hypoalbuminemia, which develops due to causes such as proteinuria, liver dysfunction, malnutrition, and chronic inflammation, in addition to the increase in lactate caused by inadequate perfusion, hypoxia, peripheral congestion, and renal dysfunction, can help identify mortality risk early in this group. When lactate was first discovered, it was considered a metabolic by product of glycolysis with no significant physiological purpose [ 32 ]. In addition to being a metabolic waste, lactate plays an essential role in the development of organs and the coordination of cellular activities [ 33 ]. Lactate serves not only as a metabolic by product but also as a crucial signaling molecule involved in maintaining cellular homeostasis, inter-neuronal signaling, immune modulation, and regulation of proliferation-related protein functions [ 34 , 35 ]. It is now understood that the mechanisms involving lactate transport and signaling play a pivotal part in the emergence and escalation of diverse pathologies, notably cancer [ 36 , 37 ]. Alterations in lactate concentrations have been documented across a range of cardiovascular diseases, such as AF, including ischemic heart events, chronic heart dysfunction, and vascular hardening, based on findings from both basic and clinical research [ 38 ]. Numerous clinical studies have further emphasized the significance of lactate as a prognostic marker in cardiovascular diseases [ 39 ]. Emerging data indicate that increased levels of blood lactate may be linked to poorer clinical outcomes in individuals with heart failure [ 40 ]. In conditions like heart failure, which are classified as cardiovascular diseases, increased lactate levels and hypoalbuminaemia are present [ 41 ]. The evaluation of lactate and albumin levels is crucial in cardiovascular diseases. Studies have shown that lactate levels are linked to survival in heart failure [ 42 ]. Furthermore, in individuals who exhibit comparable lactate concentrations, the lactate/albumin ratio has been found to more clearly determine the high risk of mortality [ 24 ]. In particular, by evaluating using lactate and albumin in conjunction, the LAR can be utilized as a potential biomarker to predict fatality risk associated with heart failure [ 43 ]. In a retrospective study, the importance of a high LAR in determining mortality in heart failure was emphasized [ 44 ]. In another study involving heart failure patients, it was found that the LAR could be an early predictor of prognosis [ 45 ]. Furthermore, a different study showed that, in predicting mortality, the LAR was more valuable than lactate alone [ 46 ]. Conclusion Our findings indicated that a higher LAR significantly contributed to increased mortality risk in patients diagnosed with HFpEF. This predictive value arises from the increase in lactate levels and the decrease in albumin. In conclusion, in this study, the LAR, which is inexpensive, easily accessible, and applicable, was found to be a significant biochemical parameter in predicting mortality in HFpEF. Close monitoring should be ensured in HFpEF patients with LAR during hospital admission. Limitations First, while our study demonstrated that the LAR is a dependable early indicator of mortality in HFpEF patients, the retrospective and single-center nature of our study limits our ability to establish causal relationships with certainty. Although multivariable adjustments and subgroup analyses were applied, potential confounders may still influence the clinical prognosis. The authors acknowledge this and have exercised caution in interpreting the results. Secondly, in our study, the patient's admission lactate and albumin levels were recorded, and the relationship between these values and prognosis was investigated. In conclusion, it was not possible to evaluate the effect of dynamic lactate and albumin changes on prognosis during the follow-up of the patient. Conducting more comprehensive evaluations alongside these data may yield much stronger results in the future. Abbreviations HFrEF Heart failure with reduced ejection fraction HFmrEF Heart failure with mildly reduced ejection fraction HFpEF Heart failure with preserved ejection fraction NYHA New Yor Heart Association DM Dİyabetes mellitus NT-proBNP N-terminal pro-natriuretic peptide TTE Transthoracic Echocardiography LAR Lactat/Albumin ratio Declarations Financial support This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Competing Interests The authors have no financial or proprietary interests in any material discussed in this article. Ethics approval and consent to participate This study was approved by the Erzurum Faculty of Medicine Scientific Research Ethics Committee (Approval Date: June 12, 2024; Decision No: 2024/06-118). Due to the retrospective study design and the use of anonymized patient data, the requirement for obtaining individual informed consent was waived. Author contributions: CRediT SGU: Writing – review & editing, Writing – original draft, Project administration, Methodology, Formal analysis, Conceptualization. MCŞ: Writing – review & editing, Methodology, Data curation, Conceptualization. MÖ : Writing – review & editing, Methodology, Data curation, Conceptualization. FKŞ: Writing – review & editing, Methodology, Conceptualization . Aknowledgement We thank the clinic staff for their assistance throughout the study. 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Am J Emerg Med. 2020;38(10):2088–95. Chen Y, et al. Association between lactate/albumin ratio and mortality in patients with heart failure after myocardial infarction. ESC Heart Fail. 2023;10(3):1928–36. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 06 Mar, 2026 Reviewers agreed at journal 05 Mar, 2026 Reviews received at journal 03 Mar, 2026 Reviewers agreed at journal 03 Mar, 2026 Reviewers agreed at journal 24 Feb, 2026 Reviewers invited by journal 24 Feb, 2026 Editor assigned by journal 23 Feb, 2026 Editor invited by journal 03 Feb, 2026 Submission checks completed at journal 02 Feb, 2026 First submitted to journal 02 Feb, 2026 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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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-8595219","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":596610752,"identity":"3ce3e43a-c9ea-44a7-9338-17f0c88daffd","order_by":0,"name":"Sibel Güçlü Utlu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3klEQVRIiWNgGAWjYDACCeYGBoYCm3p+ECehgCgtjEAtBmkJkg0gLQbEazmcYHAAxCNGi/zsxuYXPwyY84zPr0788MCAQZ5f7AB+LQZ3DrZZ9hiwFZvdeLtZAugww5mzEwhokUhsM2Yw4GHcduPsBpCWBIPbBLTIzwBrkWDcPOPs5h9EaWG4kdj8mMHAIHEDf+824mwB+YWxxyDBWOIG7zaLBAMJwn6Rn918+MOPiv9y/P1nN9/8UWEjzy9NyGEMDGwSYEoCrFKCoHIQYP4ApvgPEKV6FIyCUTAKRiAAAH0ARvW9hT66AAAAAElFTkSuQmCC","orcid":"","institution":"Erzurum Regional Training and Research Hospital","correspondingAuthor":true,"prefix":"","firstName":"Sibel","middleName":"Güçlü","lastName":"Utlu","suffix":""},{"id":596610753,"identity":"52cf322b-0b1d-485e-b26f-ac74c838a657","order_by":1,"name":"Muhammed Cüneyt Şeker","email":"","orcid":"","institution":"Erzurum Regional Training and Research Hospital","correspondingAuthor":false,"prefix":"","firstName":"Muhammed","middleName":"Cüneyt","lastName":"Şeker","suffix":""},{"id":596610756,"identity":"0d877f11-e148-43a6-8283-8c7998ded352","order_by":2,"name":"Murat Özmen","email":"","orcid":"","institution":"Erzurum Regional Training and Research Hospital","correspondingAuthor":false,"prefix":"","firstName":"Murat","middleName":"","lastName":"Özmen","suffix":""},{"id":596610757,"identity":"1ff10017-0a77-498d-81af-e1f5b459ce64","order_by":3,"name":"Fadime Kılınç Şeker","email":"","orcid":"","institution":"Erzurum Regional Training and Research Hospital","correspondingAuthor":false,"prefix":"","firstName":"Fadime","middleName":"Kılınç","lastName":"Şeker","suffix":""}],"badges":[],"createdAt":"2026-01-13 19:23:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8595219/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8595219/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103595631,"identity":"9cbd8e7b-9eba-4688-a52e-1d65d7c6c995","added_by":"auto","created_at":"2026-02-27 13:04:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":12406,"visible":true,"origin":"","legend":"\u003cp\u003eROC curve analysis of L/A for predicting mortality in HFpEF.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8595219/v1/72622851e4b48be175a1f0bd.png"},{"id":104398517,"identity":"7840c3fd-db19-4e1f-b3a7-d4f546867834","added_by":"auto","created_at":"2026-03-11 12:02:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":898941,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8595219/v1/d74a1aaf-f1f2-4afd-a658-c32d74a2b291.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Role of the Lactate-to-Albumin Ratio in Predicting In-Hospital Mortality in Patients with Heart Failure with Preserved Ejection Fraction Presenting to the Emergency Department","fulltext":[{"header":"Background","content":"\u003cp\u003eHeart failure is not a pathological diagnosis per se, but rather a clinical syndrome characterized by signs and symptoms of central and/or peripheral congestion arising from structural and/or functional abnormalities of the heart [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Although heart failure may arise from conditions such as valvular, pericardial, or endocardial diseases, it most commonly develops as a consequence of myocardial dysfunction. Additionally, arrhythmias and conduction system disorders can also precipitate heart failure. Identifying the underlying etiology is essential for the implementation of targeted, etiology-specific therapies.\u003c/p\u003e \u003cp\u003eThe classification most widely accepted in recent years is based on left ventricular ejection fraction. This categorization provides a clinically practical approach for guiding medical therapy. According to this system, patients who exhibit signs and/or symptoms of heart failure are classified as having reduced ejection fraction heart failure (HFrEF) if the left ventricular EF is \u0026le;\u0026thinsp;40%, mildly reduced ejection fraction heart failure (HFmrEF) if the EF ranges between 41\u0026ndash;49%, and preserved ejection fraction heart failure (HFpEF) if the EF is \u0026ge;\u0026thinsp;50%. [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe concepts of acute heart failure and chronic heart failure are also frequently used in clinical practice, reflecting the onset and progression of heart failure symptoms. Chronic HF refers to patients with an established diagnosis of heart failure or those with a more slowly progressive clinical course, whereas acute heart failure is used for rapidly developing clinical presentations (over minutes, hours, or days). For functional classification of heart failure, systems based solely on symptom severity\u0026mdash;such as the NYHA classification\u0026mdash;may be employed [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite advances in the prevention and treatment of cardiovascular diseases, the incidence of heart failure continues to increase in parallel with rising life expectancy [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The prevalence of heart failure in adults is estimated to range between 1% and 2% [\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In addition, the age-related increase in prevalence is noteworthy [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Among the various types of heart failure, HFpEF is the most frequently encountered in people over 65 years old, reflecting its growing clinical importance in the aging population [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. It is estimated that patients with reduced ejection fraction heart failure account for approximately 50% of all heart failure cases [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. According to long-term follow-up data from the European Society of Cardiology, 60% of ambulatory heart failure patients were found to have HFrEF, whereas 16% had HFpEF [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHFpEF patients show notable differences when compared with those having reduced ejection fraction. HFpEF patients are generally older, predominantly female, and more likely to suffer from a range of non-cardiac health issues. Women constitute more than 50% of patients with heart failure [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. This population exhibits a lower frequency of coronary artery disease [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Although the exact pathophysiology remains uncertain, numerous studies indicate that patients with HFpEF exhibit elevated levels of pro-inflammatory markers both in the heart and peripheral circulation. These studies also highlight the significant link between chronic, recurring immune-inflammatory activation and the worsening of ventricular diastolic dysfunction, as well as the progression of HFpEF [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The development of preserved ejection fraction heart failure is influenced by various factors, including advanced age, systemic hypertension (HT), obesity, physical inactivity, myocardial ischemia, and diabetes mellitus (DM), all of which complicate treatment strategies. Effectively identifying and managing underlying risk factors, causes, and coexisting health conditions can improve patient outcomes [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In patients hospitalized with HFpEF, the estimated annual mortality is approximately 15%, and long-term prognosis remains poor, with only about 35% surviving beyond five years (Borlaug BA). This prognosis is notably worse than many types of cancer [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSeveral scoring systems have been proposed for the diagnosis of heart failure with preserved ejection fraction, although none has demonstrated clear superiority over the others. In establishing the diagnosis of heart failure with preserved ejection fraction, evidence of elevated left ventricular filling pressures, diastolic dysfunction, or increased levels of natriuretic peptides may be used as indicators of underlying structural and/or functional cardiac abnormalities. An increasing number of these abnormalities proportionally raises the likelihood of a diagnosis of HFpEF [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCertain biochemical markers are crucial in optimizing the treatment of critically ill those suffering from cardiac insufficiency. A significant relationship has been observed between elevated lactate levels and mortality, which is commonly seen in critical patients [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Additionally, in cases of liver or kidney dysfunction, a series of complex changes can occur in the body (such as reduced lactate clearance and accelerated glycolysis), which may initially result in lower lactate levels. Lactate serves as a valuable tool in the early identification and therapeutic decision-making for patients with or at risk of infectious shock [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In the context of sepsis, serum albumin functions not only as a negative acute phase protein but also as an important indicator of disease severity and prognosis [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Various pathological factors, including nutritional insufficiencies and inflammatory responses, can influence the levels of both lactate and serum albumin in the body [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Research has shown that the lactate-to-albumin ratio (LAR) serves as a reliable biomarker used to assess survival chances in sepsis or septic shock patients [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Another study revealed that LAR performed better than lactate in severe sepsis [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. According to one study, the lactate/albumin ratio was found to be a better predictor of both survival and favorable neurological recovery compared to lactate levels alone [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIt is still unclear whether the lactate/albumin ratio is an effective predictor of clinical outcomes in patients with HFpEF. This study intends to investigate how well the LAR can predict mortality in HFpEF patients admitted to the emergency department or cardiology unit.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eA retrospective investigation was carried out on individuals who sought care at the emergency department or cardiology clinic during the period from January 1, 2023, to June 1, 2024. According to the 2021 ESC Heart Failure Guidelines, the diagnosis of HFpEF requires: (1) the presence of clinical signs and/or symptoms of heart failure, (2) a left ventricular ejection fraction of \u0026ge;\u0026thinsp;50%, and (3) objective evidence of structural and/or functional cardiac abnormalities consistent with left ventricular diastolic dysfunction and/or elevated left ventricular filling pressures [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Only patients over the age of 18 who fulfilled all of participants who fulfilled the following conditions were included in the study: clinical signs and symptoms of heart failure, left ventricular ejection fraction (EF)\u0026thinsp;\u0026ge;\u0026thinsp;50%, an N-terminal probrain natriuretic peptide (NT-proBNP) level exceeding 125 pg/mL, and at least one of the following findings detected by echocardiography: Left ventricular enlargement, dilation of the left atrium or impaired diastolic function. Only the data from the initial admission were included for patients with multiple hospital visits. Exclusion criteria for the patients were incomplete or unavailable data, length of stay less than 3 days, history of malignancy, detection of arrhythmia on electrocardiography during hospitalization, and the presence of valve pathology on conventional echocardiography (ECHO). Transthoracic echocardiograms (TTE), interpreted by a cardiology specialist, were retrospectively reviewed in compliance with the American Society of Echocardiography's established protocols [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Clinical parameters, including age, gender, comorbidities, laboratory values, LAR, and the mortality status of the patients, which was the final outcome of the study, were evaluated. Laboratory data were obtained frrom venous and artery blood samples at admission. GE vivid T8 (Vingmed Ultrasound AS, Horten, Norway) was used for TTE imaging. The Institutional Ethics Committee granted approval for this study (Approval Date: June 12, 2024; Decision No: 2024/06-118), and it was conducted following the ethical guidelines set by the Declaration of Helsinki.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eSPSS version 23.0 (Chicago, Illinois, USA) was used for the data analysis. A comparison was made between the baseline characteristics of survivors and non-survivors. The Kolmogorov-Smirnov test was performed to evaluate the normality of the data. For continuous variables with a normal distribution, the mean and standard deviation were used, while for variables that did not follow a normal distribution, the median and interquartile range were presented. Categorical variables were expressed as frequencies and percentages. For numerical data, either Student's t-test or Mann-Whitney U test was employed, depending on the data distribution. The chi-square test was applied for categorical variables. Both univariate and multivariate regression analyses were performed. ROC curve analysis was used to assess the relationship between HFpEF and the LAR across the entire study population. Statistical significance was defined as p-values below 0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eStudy group data were obtained from the hospital patient information database. Data from 1,910 heart failure patients, who either visited the emergency department or were sent to the cardiology clinic, were utilized in this study. According to the variables determined for the study, 110 patients had missing data. The remaining 1297 patients were excluded as they have at least one of the exclusion criterias. 503 patients were selected for inclusion in the study based on meeting the study\u0026rsquo;s criteria. A total of 74 patients (6.9% of those included) died while hospitalized during the course of the study (Table-1). Among the patients who died in the hospital, the admission LAR was significantly higher. Significant differences were found in additional variables when comparing the groups. The average age of the deceased patients was 77.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5 years (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The group with in-hospital mortality had a notably higher comorbidity rate compared to the other group. Although lactate levels were similar between the two groups, albumin levels showed a significant difference. Sodium and potassium levels did not show significant differences between the deceased and surviving patients, creatinine levels were markedly higher in the deceased patients (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003cb\u003eTable-1 Demographic and Clinical Data\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll Patients N\u0026thinsp;=\u0026thinsp;503 (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSurvivors N\u0026thinsp;=\u0026thinsp;429 (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDeceased N\u0026thinsp;=\u0026thinsp;74 (%)\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\u003e\u003cb\u003eGender (F)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e259 (51.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e224 (52.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35 (47.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58\u0026thinsp;\u0026plusmn;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55\u0026thinsp;\u0026plusmn;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCoronary Artery Disease (CAD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e185 (36.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e123 (28.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62 (83.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiabetes Mellitus (DM)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e102 (20.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73 (17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29 (39.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAtrial Fibrillation (AF)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38 (7.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (4.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 (23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHypertension (HT)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e288 (57.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e233 (54.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55 (74.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStroke (SVO)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHemoglobin (HGB)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWhite Blood Cell (WBC)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.3\u0026thinsp;\u0026plusmn;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePlatelet (PLT)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e291\u0026thinsp;\u0026plusmn;\u0026thinsp;89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e293\u0026thinsp;\u0026plusmn;\u0026thinsp;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e281\u0026thinsp;\u0026plusmn;\u0026thinsp;128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLactate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlbumin\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44\u0026thinsp;\u0026plusmn;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45\u0026thinsp;\u0026plusmn;\u0026thinsp;5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42\u0026thinsp;\u0026plusmn;\u0026thinsp;7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAspartate Aminotransferase (AST)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28\u0026thinsp;\u0026plusmn;\u0026thinsp;16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27\u0026thinsp;\u0026plusmn;\u0026thinsp;15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlanine Aminotransferase (ALT)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32\u0026thinsp;\u0026plusmn;\u0026thinsp;18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33\u0026thinsp;\u0026plusmn;\u0026thinsp;18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25\u0026thinsp;\u0026plusmn;\u0026thinsp;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGlucose\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e117\u0026thinsp;\u0026plusmn;\u0026thinsp;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e119\u0026thinsp;\u0026plusmn;\u0026thinsp;73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e105\u0026thinsp;\u0026plusmn;\u0026thinsp;41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCholesterol\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e192\u0026thinsp;\u0026plusmn;\u0026thinsp;44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e170\u0026thinsp;\u0026plusmn;\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e190\u0026thinsp;\u0026plusmn;\u0026thinsp;51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLow-Density Lipoprotein (LDL)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e124\u0026thinsp;\u0026plusmn;\u0026thinsp;43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e120\u0026thinsp;\u0026plusmn;\u0026thinsp;41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e121\u0026thinsp;\u0026plusmn;\u0026thinsp;52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHigh-Density Lipoprotein (HDL)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45\u0026thinsp;\u0026plusmn;\u0026thinsp;11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44\u0026thinsp;\u0026plusmn;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47\u0026thinsp;\u0026plusmn;\u0026thinsp;14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTriglycerides\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e185\u0026thinsp;\u0026plusmn;\u0026thinsp;118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e188\u0026thinsp;\u0026plusmn;\u0026thinsp;116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e169\u0026thinsp;\u0026plusmn;\u0026thinsp;125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCreatinine\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSodium\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e142\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e141\u0026thinsp;\u0026plusmn;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e142\u0026thinsp;\u0026plusmn;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePotassium\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMagnesium\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eC-Reactive Protein (CRP)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUric Acid\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLactate/Albumin Ratio (LAR)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the study, statistically significant variables were included in both univariate and multivariate regression analysis (Table-2). In this analysis, higher admission LAR (OR, 1.59; 95% CI, 1.23\u0026ndash;2.05; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), older age (OR, 1.46; 95% CI, 1.318\u0026ndash;1.617; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), presence of coronary artery disease (CAD) (OR, 0.351; 95% CI, 0.140\u0026ndash;0.883; P\u0026thinsp;\u0026lt;\u0026thinsp;0.026), presence of diabetes mellitus (DM) (OR, 0.267; 95% CI, 0.108\u0026ndash;0.661; P\u0026thinsp;\u0026lt;\u0026thinsp;0.004), and presence of atrial fibrillation (AF) (OR, 0.018; 95% CI, 0.003\u0026ndash;0.106; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were found to be independent factors associated with in-hospital mortality.\u003c/p\u003e \u003cp\u003e \u003cb\u003eTable-2\u003c/b\u003e The effects of different prognostic variables on mortality in univariate and multivariate logistic regression analyses.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrognostic Variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnivariate OR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMultivariate OR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\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\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.645\u0026ndash;2.505\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.460\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.318\u0026ndash;1.617\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCAD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.041\u0026ndash;0.149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.351\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.140\u0026ndash;0.883\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.187\u0026ndash;0.541\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.108\u0026ndash;0.661\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.086\u0026ndash;0.346\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.003\u0026ndash;0.106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.411\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.236\u0026ndash;0.715\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.061\u0026ndash;1.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.560\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHGB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.770\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.661\u0026ndash;0.898\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.829\u0026ndash;1.812\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.307\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.971\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.953\u0026ndash;0.988\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.935\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.892\u0026ndash;0.980\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMagnesium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.067\u0026ndash;0.561\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.779\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.142\u0026ndash;4.264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.774\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUric Acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.047\u0026ndash;1.404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.724\u0026ndash;1.736\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.910\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLAR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.460\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.15\u0026ndash;1.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.23\u0026ndash;2.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e(\u003cem\u003eAbbreviations: OR: Odds Ratio, CI: Confidence Interval, CAD: Coronary Artery Disease, DM: Diabetes Mellitus, AF: Atrial Fibrillation, HT: Hypertension, HGB: Hemoglobin, ALT: Alanine Aminotransferase, LAR: Lactate/Albumin Ratio\u003c/em\u003e)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe ROC curve for predicting hospital mortality with LAR is shown in Figure-1. The AUC value of LAR at admission was 0.636; 95% CI (0.520\u0026ndash;0.752); p\u0026thinsp;=\u0026thinsp;0.035, with a sensitivity of 66% and specificity of 60% at a cutoff value of 0.48, making L/A a predictor for mortality in HFpEF (Figure-1).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we assessed the prognostic significance of the LAR in HF patients whose data were available through the hospital information system. The data obtained indicate that a higher LAR at admission can predict the mortality level of hospitalized patients in a linear fashion.\u003c/p\u003e \u003cp\u003eThe prognosis of such patients is poor and, at the same time, poses significant economic and public health burdens [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. As a result, the LAR could be employed as an easy-to-use and practical tool for risk assessment, aiding clinicians in forecasting the outcomes for these patients. Elevated LAR is linked to high lactate and low albumin levels. Initially, it was observed that LAR was more valuable than lactate or albumin on its own in forecasting mortality in critically ill patients such as sepsis [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. However, both lactate and albumin levels can vary in many cases. Since we know that lactate metabolic levels are influenced by various mechanisms [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], it may not play a determining role for a disease in isolation. On the other hand, serum albumin is frequently employed for the clinical assessment and monitoring of diseases [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Due to its anti-inflammatory, anticoagulant preventing coagulation and inhibiting clot formation, serum albumin may have a potential role in cardiovascular diseases [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Low albumin levels are known to indicate poor prognosis in many diseases. Due to the reverse changes in lactate and albumin induced by different mechanisms, the LAR allows for more accurate predictions in determining the prognosis of heart failure patients [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In HFpEF patients, hypoalbuminemia, which develops due to causes such as proteinuria, liver dysfunction, malnutrition, and chronic inflammation, in addition to the increase in lactate caused by inadequate perfusion, hypoxia, peripheral congestion, and renal dysfunction, can help identify mortality risk early in this group.\u003c/p\u003e \u003cp\u003eWhen lactate was first discovered, it was considered a metabolic by product of glycolysis with no significant physiological purpose [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In addition to being a metabolic waste, lactate plays an essential role in the development of organs and the coordination of cellular activities [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Lactate serves not only as a metabolic by product but also as a crucial signaling molecule involved in maintaining cellular homeostasis, inter-neuronal signaling, immune modulation, and regulation of proliferation-related protein functions [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. It is now understood that the mechanisms involving lactate transport and signaling play a pivotal part in the emergence and escalation of diverse pathologies, notably cancer [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Alterations in lactate concentrations have been documented across a range of cardiovascular diseases, such as AF, including ischemic heart events, chronic heart dysfunction, and vascular hardening, based on findings from both basic and clinical research [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Numerous clinical studies have further emphasized the significance of lactate as a prognostic marker in cardiovascular diseases [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Emerging data indicate that increased levels of blood lactate may be linked to poorer clinical outcomes in individuals with heart failure [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn conditions like heart failure, which are classified as cardiovascular diseases, increased lactate levels and hypoalbuminaemia are present [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. The evaluation of lactate and albumin levels is crucial in cardiovascular diseases. Studies have shown that lactate levels are linked to survival in heart failure [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Furthermore, in individuals who exhibit comparable lactate concentrations, the lactate/albumin ratio has been found to more clearly determine the high risk of mortality [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn particular, by evaluating using lactate and albumin in conjunction, the LAR can be utilized as a potential biomarker to predict fatality risk associated with heart failure [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. In a retrospective study, the importance of a high LAR in determining mortality in heart failure was emphasized [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. In another study involving heart failure patients, it was found that the LAR could be an early predictor of prognosis [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Furthermore, a different study showed that, in predicting mortality, the LAR was more valuable than lactate alone [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e].\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur findings indicated that a higher LAR significantly contributed to increased mortality risk in patients diagnosed with HFpEF. This predictive value arises from the increase in lactate levels and the decrease in albumin.\u003c/p\u003e \u003cp\u003eIn conclusion, in this study, the LAR, which is inexpensive, easily accessible, and applicable, was found to be a significant biochemical parameter in predicting mortality in HFpEF. Close monitoring should be ensured in HFpEF patients with LAR during hospital admission.\u003c/p\u003e\n\u003ch3\u003eLimitations\u003c/h3\u003e\n\u003cp\u003eFirst, while our study demonstrated that the LAR is a dependable early indicator of mortality in HFpEF patients, the retrospective and single-center nature of our study limits our ability to establish causal relationships with certainty. Although multivariable adjustments and subgroup analyses were applied, potential confounders may still influence the clinical prognosis. The authors acknowledge this and have exercised caution in interpreting the results. Secondly, in our study, the patient's admission lactate and albumin levels were recorded, and the relationship between these values and prognosis was investigated. In conclusion, it was not possible to evaluate the effect of dynamic lactate and albumin changes on prognosis during the follow-up of the patient. Conducting more comprehensive evaluations alongside these data may yield much stronger results in the future.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eHFrEF\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHeart failure with reduced ejection fraction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eHFmrEF\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHeart failure with mildly reduced ejection fraction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eHFpEF\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHeart failure with preserved ejection fraction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eNYHA\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNew Yor Heart Association\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eDM\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDİyabetes mellitus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eNT-proBNP\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eN-terminal pro-natriuretic peptide\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eTTE\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTransthoracic Echocardiography\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eLAR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLactat/Albumin ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch3\u003eFinancial support\u003c/h3\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no financial or proprietary interests in any material discussed in this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Erzurum Faculty of Medicine Scientific Research Ethics Committee (Approval Date: June 12, 2024; Decision No: 2024/06-118).\u003cbr\u003e\u0026nbsp;Due to the retrospective study design and the use of anonymized patient data, the requirement for obtaining individual informed consent was waived.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions: CRediT\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSGU:\u003c/strong\u003e Writing \u0026ndash; review \u0026amp; editing, Writing \u0026ndash; original draft, Project administration, Methodology, Formal analysis, Conceptualization. \u003cstrong\u003eMCŞ:\u0026nbsp;\u003c/strong\u003eWriting \u0026ndash; review \u0026amp; editing, Methodology, Data curation, Conceptualization.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eM\u0026Ouml;\u003c/strong\u003e: Writing \u0026ndash; review \u0026amp; editing, Methodology, Data curation, Conceptualization. \u003cstrong\u003eFKŞ:\u003c/strong\u003e Writing \u0026ndash; review \u0026amp; editing, Methodology, Conceptualization\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the clinic staff for their assistance throughout the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData that support the findings of this study are available from the authors upon request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMcDonagh TA, et al. 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure. Eur Heart J. 2021;42(36):3599\u0026ndash;726.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoldman L, et al. Comparative reproducibility and validity of systems for assessing cardiovascular functional class: advantages of a new specific activity scale. Circulation. 1981;64(6):1227\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoth GA, et al. Demographic and epidemiologic drivers of global cardiovascular mortality. N Engl J Med. 2015;372(14):1333\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBenjamin EJ, et al. Heart Disease and Stroke Statistics-2018 Update: A Report From the American Heart Association. Circulation. 2018;137(12):e67\u0026ndash;492.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eConrad N, et al. Temporal trends and patterns in heart failure incidence: a population-based study of 4 million individuals. Lancet. 2018;391(10120):572\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGlobal., \u003cem\u003eregional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990\u0026ndash;2017: a systematic analysis for the Global Burden of Disease Study 2017.\u003c/em\u003e Lancet, 2018. 392(10159): pp. 1789\u0026ndash;1858.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCeia F, et al. Prevalence of chronic heart failure in Southwestern Europe: the EPICA study. Eur J Heart Fail. 2002;4(4):531\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan Riet EE, et al. Epidemiology of heart failure: the prevalence of heart failure and ventricular dysfunction in older adults over time. A systematic review. Eur J Heart Fail. 2016;18(3):242\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBorlaug BA, Paulus WJ. Heart failure with preserved ejection fraction: pathophysiology, diagnosis, and treatment. Eur Heart J. 2011;32(6):670\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKoh AS, et al. A comprehensive population-based characterization of heart failure with mid-range ejection fraction. Eur J Heart Fail. 2017;19(12):1624\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChioncel O, et al. Epidemiology and one-year outcomes in patients with chronic heart failure and preserved, mid-range and reduced ejection fraction: an analysis of the ESC Heart Failure Long-Term Registry. Eur J Heart Fail. 2017;19(12):1574\u0026ndash;85.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShah RU, Klein L, Lloyd-Jones DM. Heart failure in women: epidemiology, biology and treatment. Womens Health (Lond). 2009;5(5):517\u0026ndash;27.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThe survival of patients with heart failure with preserved or reduced left ventricular ejection fraction: an individual patient data meta-analysis. Eur Heart J, 2012. 33(14): pp. 1750\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTorre-Amione G. Immune activation in chronic heart failure. Am J Cardiol, 2005. 95(11a): p. 3C-8C; discussion 38C-40C.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTsch\u0026ouml;pe C, et al. Heart failure with preserved ejection fraction: current management and future strategies: Expert opinion on the behalf of the Nucleus of the Heart Failure Working Group of the German Society of Cardiology (DKG). Clin Res Cardiol. 2018;107(1):1\u0026ndash;19.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNair N. Epidemiology and pathogenesis of heart failure with preserved ejection fraction. Rev Cardiovasc Med. 2020;21(4):531\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOwan TE, et al. Trends in prevalence and outcome of heart failure with preserved ejection fraction. N Engl J Med. 2006;355(3):251\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRhodes A, et al. Surviving Sepsis Campaign: International Guidelines for Management of Sepsis and Septic Shock: 2016. Crit Care Med. 2017;45(3):486\u0026ndash;552.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDuchnowski P, et al. The usefulness of perioperative lactate blood levels in patients undergoing heart valve surgery. Kardiochir Torakochirurgia Pol. 2019;16(3):114\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePark J, et al. Impact of Metformin Use on Lactate Kinetics in Patients with Severe Sepsis and Septic Shock. Shock. 2017;47(5):582\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSterling SA, Puskarich MA, Jones AE. The effect of liver disease on lactate normalization in severe sepsis and septic shock: a cohort study. Clin Exp Emerg Med. 2015;2(4):197\u0026ndash;202.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYin M, et al. Predictive Value of Serum Albumin Level for the Prognosis of Severe Sepsis Without Exogenous Human Albumin Administration: A Prospective Cohort Study. J Intensive Care Med. 2018;33(12):687\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCaironi P, Langer T, Gattinoni L. Albumin in critically ill patients: the ideal colloid? Curr Opin Crit Care. 2015;21(4):302\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShin J, et al. Prognostic Value of The Lactate/Albumin Ratio for Predicting 28-Day Mortality in Critically ILL Sepsis Patients. Shock. 2018;50(5):545\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang B, et al. Correlation of lactate/albumin ratio level to organ failure and mortality in severe sepsis and septic shock. J Crit Care. 2015;30(2):271\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKong T, et al. The Prognostic Usefulness of the Lactate/Albumin Ratio for Predicting Clinical Outcomes in Out-of-Hospital Cardiac Arrest: a Prospective, Multicenter Observational Study (koCARC) Study. Shock. 2020;53(4):442\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLang RM, et al. Recommendations for cardiac chamber quantification by echocardiography in adults: an update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging. J Am Soc Echocardiogr. 2015;28(1):1\u0026ndash;e3914.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGreene SJ, et al. The vulnerable phase after hospitalization for heart failure. Nat Rev Cardiol. 2015;12(4):220\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFanali G, et al. Human serum albumin: from bench to bedside. Mol Aspects Med. 2012;33(3):209\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArques S. Human serum albumin in cardiovascular diseases. Eur J Intern Med. 2018;52:8\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSun H, et al. Association of lactate/albumin ratio with 3-month readmission risk in heart failure patients: a retrospective study. ESC Heart Fail. 2024;11(4):2182\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFerguson BS, et al. Lactate metabolism: historical context, prior misinterpretations, and current understanding. Eur J Appl Physiol. 2018;118(4):691\u0026ndash;728.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDong X, et al. Metabolic lactate production coordinates vasculature development and progenitor behavior in the developing mouse neocortex. Nat Neurosci. 2022;25(7):865\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrooks GA. The Science and Translation of Lactate Shuttle Theory. Cell Metab. 2018;27(4):757\u0026ndash;85.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu W, et al. Lactate regulates cell cycle by remodelling the anaphase promoting complex. Nature. 2023;616(7958):790\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKennedy KM, Dewhirst MW. Tumor metabolism of lactate: the influence and therapeutic potential for MCT and CD147 regulation. Future Oncol. 2010;6(1):127\u0026ndash;48.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiranda-Gon\u0026ccedil;alves V, et al. Monocarboxylate transporters (MCTs) in gliomas: expression and exploitation as therapeutic targets. Neuro Oncol. 2013;15(2):172\u0026ndash;88.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBiegus J, et al. Elevated lactate in acute heart failure patients with intracellular iron deficiency as identifier of poor outcome. Kardiol Pol. 2019;77(3):347\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVermeulen RP, et al. Clinical correlates of arterial lactate levels in patients with ST-segment elevation myocardial infarction at admission: a descriptive study. Crit Care. 2010;14(5):R164.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZymliński R, et al. Increased blood lactate is prevalent and identifies poor prognosis in patients with acute heart failure without overt peripheral hypoperfusion. Eur J Heart Fail. 2018;20(6):1011\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eManolis AA, et al. Low serum albumin: A neglected predictor in patients with cardiovascular disease. Eur J Intern Med. 2022;102:24\u0026ndash;39.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUyar H, et al. The Effect of High Lactate Level on Mortality in Acute Heart Failure Patients With Reduced Ejection Fraction Without Cardiogenic Shock. Cardiovasc Toxicol. 2020;20(4):361\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuo W, et al. The value of lactate/albumin ratio for predicting the clinical outcomes of critically ill patients with heart failure. Ann Transl Med. 2021;9(2):118.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen W, Chen M, Qiao X. Interaction of lactate/albumin and geriatric nutritional risk index on the all-cause mortality of elderly patients with critically ill heart failure: A cohort study. Clin Cardiol. 2023;46(7):745\u0026ndash;56.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGharipour A, et al. Lactate/albumin ratio: An early prognostic marker in critically ill patients. Am J Emerg Med. 2020;38(10):2088\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen Y, et al. Association between lactate/albumin ratio and mortality in patients with heart failure after myocardial infarction. ESC Heart Fail. 2023;10(3):1928\u0026ndash;36.\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-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Biomarkers, Heart Failure with Preserved Ejection Fraction, Lactate/Albumin Ratio, Mortality, Retrospective Study","lastPublishedDoi":"10.21203/rs.3.rs-8595219/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8595219/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eHeart failure with preserved ejection fraction (HFpEF) is an important form of heart failure associated with high mortality rates. Identifying risk factors is crucial for improving hospital mortality rates. The lactate/albumin ratio (LAR) has been found to be associated with adverse clinical outcomes in conditions such as sepsis and myocardial infarction. In this study, we aim to evaluate the potential of LAR as a prognostic marker for mortality in patients with HFpEF.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn this retrospective study, patients diagnosed with HFpEF were included. Data from patients who were admitted to the emergency department or cardiology clinic between January 1, 2023, and June 1, 2024, were used from the hospital information system database.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 503 patients were included in the study, of whom 74 died during hospitalization. Univariate and multivariate Cox regression analyses were performed to determine the relationship between LAR at admission and hospital mortality. The LAR value was significantly higher in the group of patients who died during hospitalization compared to survivors (0.07 vs 0.05, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The area under the ROC curve was 0.636 (95% CI: 0.520\u0026ndash;0.752), and the optimal cut-off value for LAR was 0.48.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eAn elevated LAR is significantly associated with mortality in HFpEF and can be used as an early prognostic marker for mortality in these patients.\u003c/p\u003e","manuscriptTitle":"The Role of the Lactate-to-Albumin Ratio in Predicting In-Hospital Mortality in Patients with Heart Failure with Preserved Ejection Fraction Presenting to the Emergency Department","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-27 13:04:33","doi":"10.21203/rs.3.rs-8595219/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-03-06T22:45:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"10680022103066549765883959803095659283","date":"2026-03-05T21:06:38+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-03T18:08:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"6385160333597309492021300444616108569","date":"2026-03-03T13:27:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"68394598575719804308585029340119933917","date":"2026-02-24T14:47:11+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-24T14:30:15+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-23T07:56:26+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-03T10:00:02+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-02T18:39:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cardiovascular Disorders","date":"2026-02-02T18:26:44+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2958060c-67b8-4b2e-8c79-e3ee8ad8ccd6","owner":[],"postedDate":"February 27th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-27T13:04:34+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-27 13:04:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8595219","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8595219","identity":"rs-8595219","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}