Blood urea nitrogen to albumin ratio is a predictor of in-hospital mortality in older emergency department patients

Risk factors and prediction model for mortality in HIV/Talaromyces marneffei co-infection: A retrospective cohort study

Background

This study aimed to identify the risk factors associated with mortality among patients co-infected with human immunodeficiency virus (HIV) and Talaromyces marneffei (TM) in China, and develop a risk prediction model.

Methods

In this retrospective cohort analysis conducted from 2013 to 2024, comprehensive clinical data from 160 patients were analyzed using a logistic regression model to identify mortality predictors and construct a predictive model. An additional 36 patients constituted the validation cohort, which was specifically designed to evaluate the predictive value of the model. Model performance was assessed using the area under the curve (AUC).

Results

The overall mortality rate for hospitalized patients with HIV/TM co-infection was 17.35 %. The median age was 35.0 years, and 89.30 % were male. Additionally, 89.80 % of the patients reported fever and 87.76 % presented with lymphadenopathy. Key independent risk factors associated with mortality included age (odds ratio (OR): 1.103, 95 % confidence interval (CI) = 1.033-1.178, P = 0.003), procalcitonin (PCT) levels (OR: 1.270, 95 % CI = 1.052-1.534, P = 0.013), and urea to albumin ratio (UAR) (OR: 1.491, 95 % CI = 1.175-1.892, P < 0.001). Advanced age, elevated PCT levels, and increased UAR were identified as independent risk factors of mortality. Furthermore, the mortality prediction probability combining age, PCT, and UAR exhibited a high predictive value in patients with HIV/TM co-infection. Additionally, the AUC showed a good discrimination ability in the validation group (AUC, 0.898).

Conclusions

Advanced age, elevated PCT levels, and increased UAR significantly determine mortality in patients with HIV/TM co-infection. These findings underscore the potential of using laboratory parameters as predictive indicators of mortality, facilitating the early identification of HIV/TM co-infection cases in clinical practice.

Clinical relevance of blood urea nitrogen to serum albumin ratio for predicting bacteremia in very young children with febrile urinary tract infection

BACKGROUND

Urinary tract infections (UTIs) are one of the most common bacterial infections in febrile children and a common cause of hospitalization, especially in very young children. We examined the clinical characteristics and predictive factors of concomitant bacteremia in pediatric patients with febrile UTI aged ≤24 months.

METHODS

This retrospective multicenter study reviewed medical data from 2,141 patients from three centers from January 2000 to December 2019. Enrolled cases were classified into the bacteremic UTI and non-bacteremic UTI groups according to the presence of blood culture pathogens.

RESULTS

Among 2,141 patients with febrile UTI, 40 (1.9%) had concomitant bacteremia. All patients in the bacterial group were aged ≤6 months. Multivariate analysis revealed that younger age, lower blood lymphocyte counts and serum albumin levels, higher C-reactive protein (CRP) levels, blood urea nitrogen (BUN) levels, and BUN/serum albumin ratio were independent risk factors of concomitant bacteremia. The area under the receiver-operating characteristic curves predicting bacteremia were 0.668 for CRP, 0.673 for lymphocytes, and 0.759 for the BUN/albumin ratio.

CONCLUSION

The present study identified the BUN/albumin ratio and lower blood lymphocyte counts as novel predictive factors for bacteremia in young infants with febrile UTI in addition to the previously identified factors of younger age and higher CRP levels. Our findings could help to identify patients at high risk of bacteremia and benefit decision-making in the management of infants with febrile UTI.

Clinical Utility of the Tokyo Guidelines 2018 for Acute Cholangitis in the Emergency Department and Comparison with Novel Markers (Neutrophil-to-Lymphocyte and Blood Nitrogen Urea-to-Albumin Ratios)

Introduction: The Tokyo Guidelines 2018 (TG2018) is a scoring system used to recommend the clinical management of AC. However, such a scoring system must incorporate a variety of clinical outcomes of acute cholangitis (AC). In an emergency department (ED)-based setting, where efficiency and practicality are highly desired, clinicians may find the application of various parameters challenging. The neutrophil-to-lymphocyte ratio (NLR) and blood urea nitrogen-to-albumin ratio (BAR) are relatively common biomarkers used to assess disease severity. This study evaluated the potential value of TG2018 scores measured in an ED to predict a variety of clinical outcomes. Furthermore, the study also compared TG2018 scores with NLR and BAR scores to demonstrate their usefulness. Methods: This retrospective observational study was performed in an ED. In total, 502 patients with AC visited the ED between January 2016 and December 2021. The primary endpoint was to evaluate whether the TG2018 scoring system measured in the ED was a predictor of intensive care, long-term hospital stays (≥14 days), percutaneous transhepatic biliary drainage (PTBD) during admission care, and endotracheal intubation (ETI). Results: The analysis included 81 patients requiring intensive care, 111 requiring long-term hospital stays (≥14 days), 49 requiring PTBD during hospitalization, and 14 requiring ETI during hospitalization. For the TG2018 score, the adjusted OR (aOR) using (1) as a reference was 23.169 (95% CI: 9.788-54.844) for (3) compared to (1). The AUC of the TG2018 for the need for intensive care was 0.850 (95% CI: 0.815-0.881) with a cutoff of >2. The AUC for long-term hospital stays did not exceed 0.7 for any of the markers. the AUC for PTBD also did not exceed 0.7 for any of the markers. The AUC for ETI was the highest for BAR at 0.870 (95% CI: 0.837-0.899) with a cutoff value of >5.2. Conclusions: The TG2018 score measured in the ED helps predict various clinical outcomes of AC. Other novel markers such as BAR and NLR are also associated, but their explanatory power is weak.

An Evaluation of the National Early Warning Score 2 and the Laboratory Data Decision Tree Early Warning Score in Predicting Mortality in Geriatric Patients

BACKGROUND

Due to the high rate of geriatric patient visits, scoring systems are needed to predict increasing mortality rates.

OBJECTIVE

In this study, we aimed to investigate the in-hospital mortality prediction power of the National Early Warning Score 2 (NEWS2) and the Laboratory Data Decision Tree Early Warning Score (LDT-EWS), which consists of frequently performed laboratory parameters.

METHODS

We retrospectively analyzed 651 geriatric patients who visited the emergency department (ED), were not discharged on the same day from ED, and were hospitalized. The patients were categorized according to their in-hospital mortality status. The NEWS2 and LDT-EWS values of these patients were calculated and compared on the basis of deceased and living patients.

RESULTS

Median (interquartile range [IQR]) NEWS2 and LDT-EWS values of the 127 patients who died were found to be statistically significantly higher than those of the patients who survived (NEWS2: 5 [3-8] vs. 3 [1-5]; p < 0.001; LDT-EWS: 8 [7-10] vs. 6 [5-8]; p < 0.001). In the receiver operating characteristic curve analysis, the NEWS2, LDT-EWS, and NEWS2+LDT-EWS-formed by the sum of the two scoring systems-resulted in 0.717, 0.705, and 0.775 area under curve values, respectively.

CONCLUSIONS

The NEWS2 and LDT-EWS were found to be valuable for predicting in-hospital mortality in geriatric patients. The power of the NEWS2 to predict in-hospital mortality increased when used with the LDT-EWS.

Blood Urea Nitrogen-to-Albumin Ratio May Predict Mortality in Patients with Traumatic Brain Injury from the MIMIC Database: A Retrospective Study

Traumatic brain injury (TBI), a major global health burden, disrupts the neurological system due to accidents and other incidents. While the Glasgow coma scale (GCS) gauges neurological function, it falls short as the sole predictor of overall mortality in TBI patients. This highlights the need for comprehensive outcome prediction, considering not just neurological but also systemic factors. Existing approaches relying on newly developed biomolecules face challenges in clinical implementation. Therefore, we investigated the potential of readily available clinical indicators, like the blood urea nitrogen-to-albumin ratio (BAR), for improved mortality prediction in TBI. In this study, we investigated the significance of the BAR in predicting all-cause mortality in TBI patients. In terms of research methodologies, we gave preference to machine learning methods due to their exceptional performance in clinical support in recent years. Initially, we obtained data on TBI patients from the Medical Information Mart for Intensive Care database. A total of 2602 patients were included, of whom 2260 survived and 342 died in hospital. Subsequently, we performed data cleaning and utilized machine learning techniques to develop prediction models. We employed a ten-fold cross-validation method to obtain models with enhanced accuracy and area under the curve (AUC) (Light Gradient Boost Classifier accuracy, 0.905 ± 0.016, and AUC, 0.888; Extreme Gradient Boost Classifier accuracy, 0.903 ± 0.016, and AUC, 0.895; Gradient Boost Classifier accuracy, 0.898 ± 0.021, and AUC, 0.872). Simultaneously, we derived the importance ranking of the variable BAR among the included variables (in Light Gradient Boost Classifier, the BAR ranked fourth; in Extreme Gradient Boost Classifier, the BAR ranked sixth; in Gradient Boost Classifier, the BAR ranked fifth). To further evaluate the clinical utility of BAR, we divided patients into three groups based on their BAR values: Group 1 (BAR < 4.9 mg/g), Group 2 (BAR ≥ 4.9 and ≤10.5 mg/g), and Group 3 (BAR ≥ 10.5 mg/g). This stratification revealed significant differences in mortality across all time points: in-hospital mortality (7.61% vs. 15.16% vs. 31.63%), as well as one-month (8.51% vs. 17.46% vs. 36.39%), three-month (9.55% vs. 20.14% vs. 41.84%), and one-year mortality (11.57% vs. 23.76% vs. 46.60%). Building on this observation, we employed the Cox proportional hazards regression model to assess the impact of BAR segmentation on survival. Compared to Group 1, Groups 2 and 3 had significantly higher hazard ratios (95% confidence interval (CI)) for one-month mortality: 1.77 (1.37-2.30) and 3.17 (2.17-4.62), respectively. To further underscore the clinical potential of BAR as a standalone measure, we compared its performance to established clinical scores, like sequential organ failure assessment (SOFA), GCS, and acute physiology score III(APS-III), using receiver operator characteristic curve (ROC) analysis. Notably, the AUC values (95%CI) of the BAR were 0.67 (0.64-0.70), 0.68 (0.65-0.70), and 0.68 (0.65-0.70) for one-month mortality, three-month mortality, and one-year mortality. The AUC value of the SOFA did not significantly differ from that of the BAR. In conclusion, the BAR is a highly influential factor in predicting mortality in TBI patients and should be given careful consideration in future TBI prediction research. The blood urea nitrogen-to-albumin ratio may predict mortality in TBI patients.

A High Preoperative Blood Urea Nitrogen to Serum Albumin Ratio Does Not Predict Worse Outcomes Following the Robotic-Assisted Pulmonary Lobectomy for Lung Cancer

BACKGROUND

 The blood urea nitrogen to serum albumin ratio (BAR) is an emerging prognostic parameter of interest. The utility of BAR as a prognostic factor has not been analyzed in lung cancer patients undergoing pulmonary lobectomy. We evaluated the ability of High BAR to predict worse outcomes after robotic-assisted pulmonary lobectomy (RAPL) for lung cancer.

METHODS

 We retrospectively analyzed 400 patients who underwent RAPL from September 2010 to March 2022 by one surgeon. Patients were stratified by Low BAR (<6.25 mg/g) and High BAR (≥6.25 mg/g). Patients' demographics, tumor characteristics, comorbidities, surgical complications, outcomes, and survival were collected and compared by High and Low BAR groups. The primary outcome of interest was 30-day mortality.

RESULTS

 Receiver operator curves (ROC) confirmed that 6.25 was an optimal threshold for estimating mortality based on Low and High BAR. There were no differences in surgical complications or outcomes between the Low and High BAR groups. The ability of BAR to predict 30-day mortality was evaluated with the area under the curve (AUC) analysis, which showed that higher BAR could not predict mortality (AUC=0.655; 95% CI, 0.435-0.875; p=0.166). Similarly, survival analysis revealed no difference in five-year overall survival between the Low and High BAR groups (p=0.079).

CONCLUSION

 High BAR did not predict worse outcomes after RAPL for lung cancer in our study. Further studies are needed to better determine the prognostic ability of BAR in lower-risk populations.

Finding the best trade-off between performance and interpretability in predicting hospital length of stay using structured and unstructured data

OBJECTIVE

This study aims to develop high-performing Machine Learning and Deep Learning models in predicting hospital length of stay (LOS) while enhancing interpretability. We compare performance and interpretability of models trained only on structured tabular data with models trained only on unstructured clinical text data, and on mixed data.

METHODS

The structured data was used to train fourteen classical Machine Learning models including advanced ensemble trees, neural networks and k-nearest neighbors. The unstructured data was used to fine-tune a pre-trained Bio Clinical BERT Transformer Deep Learning model. The structured and unstructured data were then merged into a tabular dataset after vectorization of the clinical text and a dimensional reduction through Latent Dirichlet Allocation. The study used the free and publicly available Medical Information Mart for Intensive Care (MIMIC) III database, on the open AutoML Library AutoGluon. Performance is evaluated with respect to two types of random classifiers, used as baselines.

RESULTS

The best model from structured data demonstrates high performance (ROC AUC = 0.944, PRC AUC = 0.655) with limited interpretability, where the most important predictors of prolonged LOS are the level of blood urea nitrogen and of platelets. The Transformer model displays a good but lower performance (ROC AUC = 0.842, PRC AUC = 0.375) with a richer array of interpretability by providing more specific in-hospital factors including procedures, conditions, and medical history. The best model trained on mixed data satisfies both a high level of performance (ROC AUC = 0.963, PRC AUC = 0.746) and a much larger scope in interpretability including pathologies of the intestine, the colon, and the blood; infectious diseases, respiratory problems, procedures involving sedation and intubation, and vascular surgery.

CONCLUSIONS

Our results outperform most of the state-of-the-art models in LOS prediction both in terms of performance and of interpretability. Data fusion between structured and unstructured text data may significantly improve performance and interpretability.

Higher urea-to-albumin ratio is associated with mortality risk in critically ill COVID-19 patients

BACKGROUND

This study aimed to evaluate the ability of the urea-to-albumin ratio (UAR) to predict mortality in critically ill coronavirus disease 2019 (COVID-19) patients.

METHODS

This retrospective study included adult patients admitted with COVID-19 at two intensive care units (ICUs) at the University Hospital. Serum urea and albumin concentrations at ICU admission were used to calculate the UAR. All patients were followed up during hospitalization, and the ICU mortality rate was recorded.

RESULTS

Two hundred and eleven patients were evaluated. The mean age was 57.8 ± 15.5 years, and 54% were male. Approximately 84.4% of patients were considered to be at nutritional risk by the NRS 2002, and the median UAR was 18.3 (10.5-34.8). The length of stay in the ICU was 10 (6-16) days, 38.4% of the patients required dialysis, and 64.9% died. Age, male sex, need of hemodialysis, lactate level, and inflammatory parameters were associated with higher mortality. Patients non-survivors had a higher UAR (23.7 [13.6-41.8] vs. 10.9 [8.5-16.8]; p < 0.001). The cutoff point with the best performance of UAR in the ROC curve for predicting mortality was ≥12.17 (AUC: 0.7201; CI 95%: 0.656-0.784). Additionally, the risk of mortality was 2.00-fold in the group of patients with UAR ≥12.17 (HR: 2.00 CI: 1.274-3.149; p = 0.003) and remained significant after adjusted analyzes (models 1 and 2).

CONCLUSION

Our data suggest that a UAR ≥12.17 increased the risk of mortality by 2.00-fold in critically ill COVID-19 patients.

Association between early blood urea nitrogen-to-albumin ratio and one-year post-hospital mortality in critically ill surgical patients: a propensity score-matched study

BACKGROUND

Blood urea nitrogen to albumin ratio (BAR) is increasingly recognized as an early predictor for short-term outcomes in critically ill patients, but the association of BAR with long-term outcomes in critically ill surgical patients remains underexplored.

METHODS

We enrolled consecutive patients who were admitted to surgical intensive care units (ICUs) at Taichung Veterans General Hospital between 2015 and 2020, and the dates of death were retrieved from Taiwan's National Health Insurance Research Database. In addition to Cox regression, we also used propensity score matching to determine the hazard ratios (HRs) and 95% confidence intervals (CIs) for one-year post-hospital mortality of the variables.

RESULTS

A total of 8,073 eligible subjects were included for analyses. We found that age, male gender, high Charlson Comorbidity Index, high Acute Physiology and Chronic Health Evaluation II score, positive microbial culture, and leukocytosis were predictors for mortality, whereas high body mass index, scheduled surgery, and high platelet counts were protective factors against long-term mortality. The high BAR was independently associated with increased post-hospital mortality after adjustment for the aforementioned covariates (adjHR 1.258, 95% CI, 1.127-1.405). Notably, the association tended to be stronger in females and patients with fewer comorbidities and lower disease severity of critical illness. The propensity score matching, dividing subjects by BAR higher or lower than 6, showed a consistent association between week-one BAR and post-hospital mortality (adjHR 1.503, 95% CI 1.247-1.811).

CONCLUSIONS

BAR is a newly identified predictor of short-term outcome, and we identified long-term outcome-relevant factors, including BAR, and the identified factors may be useful for risk stratification of long-term outcomes in patients discharged from surgical ICUs.

BUN level is associated with cancer prevalence

Blood urea nitrogen (BUN) was an important biomarker for the development and prognosis of many diseases. Numerous studies had demonstrated that BUN had a strong relationship with long-term mortality, survival and the prevalence of some diseases. The diagnosis and treatment, prognosis and long-term survival rate of cancer were the focus of clinical research at present. However, the relationship between BUN level and cancer prevalence was not clear. To investigate the relationship between BUN level and cancer prevalence, we performed a statistical analysis of population data from the National Health and Nutrition Examination Survey (NHANES) database. The results of the study showed that BUN level were positively correlated with cancer prevalence, and the correlation was more pronounced in breast cancer.

Comparison of the Predictive Ability of the Blood Urea Nitrogen/Albumin, C-Reactive Protein/Albumin, and Lactate/Albumin Ratios for Short-Term Mortality in SARS-CoV-2-Infected Patients

Background  Hematological parameters and their ratios are the most studied biomarkers for prediction of mortality or severe illness in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. This study aims to compare the power of the blood urea nitrogen (BUN)/albumin ratio, lactate/albumin ratio, and C-reactive protein (CRP)/albumin ratio, measured at the time of admission, in predicting 30-day mortality in SARS-CoV-2-infected patients presenting to the emergency department (ED). Materials and Methods  This retrospectively designed, single-center, observational study was performed in the ED of a tertiary education health care center. We documented the data of patients admitted with a confirmed SARS-CoV-2 infection between September 1, 2020, and January 1, 2021. Results  Of the 470 patients included in the study, 232 (49.4%) were female. The all-cause 30-day mortality rate was 23.8%. The area under the curve values for the BUN/albumin ratio, lactate/albumin ratio, and CRP/albumin ratio in the prediction of 30-day mortality were 0.725, 0.641, and 0.749, respectively. Sensitivity and negative predictive value for CRP/albumin ratio (≥0.049) and specificity for BUN/albumin ratio (≥1.17) were 92.86, 94.9, and 71.23, respectively. The odds ratio values of the BUN/albumin ratio (≥1.17), CRP/albumin ratio (≥0.049), and lactate/albumin ratio (≥0.046) for 30-day mortality were determined as 4.886, 9.268, and 2.518, respectively. Conclusion  The BUN/albumin ratio and CRP/albumin ratio can be used to predict 30-day mortality in SARS-CoV-2-infected patients admitted to ED. Furthermore, CRP/albumin ratio had the highest sensitivity and negative predictive value, while BUN/albumin ratio had the highest specificity.

The correlation study between blood urea nitrogen to serum albumin ratio and prognosis of patients with sepsis during hospitalization

BACKGROUND

Sepsis is a common critical illness in intensive care unit (ICU) and seriously threatens the life of patients. Therefore, to identify a simple and effective clinical indicator to determine prognosis is essential for the management of sepsis patients. This study was mainly based on blood urea nitrogen to albumin ratio (B/A), a comprehensive index, to explore its correlation with the prognosis of sepsis patients during hospitalization.

METHODS

Totally, adult patients in ICU who were diagnosed with sepsis in Medical Information Mart for Intensive Care IV(MIMIC-IV) database from 2008 to 2019 were involved in this study. The study population were divided into survivors group and non-survivors group based on the prognosis during hospitalization. Restricted cubic spline (RCS) was utilized to analyze the association between B/A level and the risk of ICU all-cause mortality in patients with sepsis and determine the optimal cut-off value of B/A. The study population was divided into low B/A group and high B/A group based on the optimal cut-off value. The survival curve of ICU cumulative survival rate was draw through Kaplan-Meier method. The correlation between B/A and the prognosis of patients was conducted by multivariate Cox regression analysis. Furthermore, we performed sensitivity analyses to assess the robustness of the results.

RESULTS

A total of 10,578 patients with sepsis were enrolled, and the ICU all-cause mortality was 15.89%. The patients in the non-survivors group had higher B/A values and more comorbidities than those in the survivors group. RCS showed that the risk of ICU all-cause mortality increased with the B/A level, showing a non-linear trend (χ2 = 66.82, p < 0.001). The mortality rate in the high B/A group was significantly higher than that in the low B/A group (p < 0.001). Kaplan-Meier curves revealed that compared with the low B/A group, the ICU cumulative survival rate of patients with sepsis was significantly lower in the high B/A group (log-rank test, χ2 = 148.620, p < 0.001). Further analysis of multivariate Cox proportional hazards regression showed that an elevated B/A (≥ 7.93) was an independent factor associated with ICU mortality among patients with sepsis.

CONCLUSIONS

An elevated B/A might be a useful prognostic indicator in patients with sepsis. This study could offer a deeper insight into treating sepsis.

Association Between Blood Urea Nitrogen Levels and Length of Stay in Patients with Pneumonic Chronic Obstructive Pulmonary Disease Exacerbation: A Secondary Analysis Based on a Multicentre, Retrospective Cohort Study

Purpose

High blood urea nitrogen (BUN) is associated with an elevated risk of mortality in various diseases, such as heart failure and pneumonia. Heart failure and pneumonia are common comorbidities of chronic obstructive pulmonary disease (COPD) exacerbation. However, data on the relationship of BUN levels with length of stay (LOS) in patients with pneumonic COPD exacerbation are sparse. The purpose of this study was to evaluate the correlation between BUN levels and LOS in a cohort of patients with pneumonic COPD exacerbation.

Patients and Methods

The present study was a multicentre, retrospective cohort study. A total of 1226 patients with pneumonic COPD exacerbation were included through a validated algorithm derived from the 10th revision of the International Classification of Diseases and Related Health Problems (ICD-10). It should be noted that the entire study was completed by Shiroshita et al, who uploaded the data to the DATADRYAD website. The author only used these data for secondary analysis.

Results

After adjusting for potential confounders (age, gender), a nonlinear relationship was detected between BUN levels less than 40 mg/dl and LOS. The effect sizes and the confidence intervals on the left and right sides of the inflection point were 0.27 (0.16, 0.39) and −0.17 (−0.34, 0.01), respectively.

Conclusion

High levels of BUN in the hospital may be associated with increased LOS. BUN was positively related to LOS when BUN was less than 40 mg/dl.

Prognostic significance of the blood urea nitrogen to creatinine ratio in in-hospital cardiac arrest after targeted temperature management

BACKGROUND

Targeted temperature management (TTM) has been reported to improve outcomes in in-hospital cardiac arrest (IHCA) patients but little has been investigated into the relationship between prognoses and the blood urea nitrogen to creatinine ratio (BCR).

METHODS

A retrospective analysis of data from IHCA survivors treated with TTM between 2011 and 2018 was conducted based on the Research Patient Database Registry of the Partners HealthCare system in Boston. Serum laboratory data were measured during IHCA and within 24 hours after TTM completion. Intra-arrest and post-TTM BCRs were calculated, respectively. The primary outcome was neurologic status at discharge. The secondary outcome was in-hospital mortality.

RESULTS

The study included 84 patients; 63 (75%) were discharged with a poor neurologic status and 40 (47.6%) died. Regarding poor neurological outcome at discharge, multivariate analysis revealed that post-TTM BCR was a significant predictor (adjusted OR, 1.081; 95% CI, 1.002-1.165; p = 0.043) and intra-arrest BCR was a marginal predictor (adjusted OR, 1.067; 95% CI, 1.000-1.138; p = 0.050). Post-TTM BCR had an acceptably predictive ability to discriminate neurological status at discharge, with an area under the receiver-operating characteristic curve of 0.644 (95% CI, 0.516-0.773) and a post-TTM BCR cutoff value of 16.7 had a sensitivity of 61.9% and a specificity of 70.0%.

CONCLUSION

Post-TTM BCR was a significant predictor of the neurologic outcome at discharge among IHCA patients receiving TTM. IHCA patients with elevated intra-arrest BCR also had a borderline poor neurological prognosis at discharge.

Fibrinogen-to-Albumin Ratio and Blood Urea Nitrogen-to-Albumin Ratio in COVID-19 Patients: A Systematic Review and Meta-Analysis

Fibrinogen-to-albumin ratio (FAR) and blood urea nitrogen-to-albumin ratio (BAR) are inflammatory biomarkers that have been associated with clinical outcomes of multiple diseases. The objective of this study is to evaluate the association of these biomarkers with the severity and mortality of COVID-19 patients. A systematic search was performed in five databases. Observational studies that reported the association between FAR and BAR values with the severity and mortality of COVID-19 patients were included. Random-effects models were used for meta-analyses, and effects were expressed as Odds Ratio (OR) and their 95% confidence intervals (CI). Publication bias was assessed using the Begg test, while the quality assessment was assessed using the Newcastle Ottawa Scale. A total of 21 studies (n = 7949) were included. High FAR values were associated with a higher risk of severity (OR: 2.41; 95% CI 1.41−4.12; p < 0.001) and mortality (OR: 2.05; 95% CI 1.66−2.54; p < 0.001). High BAR values were associated with higher risk of mortality (OR: 4.63; 95% CI 2.11−10.15; p < 0.001). However, no statistically significant association was found between BAR values and the risk of severity (OR: 1.16; 95% CI 0.83−1.63; p = 0.38). High FAR and BAR values were associated with poor clinical outcomes.

Association Between Pre-operative BUN and Post-operative 30-Day Mortality in Patients Undergoing Craniotomy for Tumors: Data From the ACS NSQIP Database

Objective

There is limited evidence to clarify the specific relationship between pre-operative blood urea nitrogen (BUN) and post-operative 30-day mortality in patients undergoing craniotomy for tumors. Therefore, we aimed to investigate this relationship in detail.

Methods

Electronic medical records of 18,642 patients undergoing craniotomy for tumors in the ACS NSQIP from 2012 to 2015 were subjected to secondary retrospective analysis. The principal exposure was pre-operative BUN. Outcome measures were post-operative 30-day mortality. We used binary logistic regression modeling to evaluate the association between them and conducted a generalized additive model and smooth curve fitting (penalized spline method) to explore the potential relationship and its explicit curve shape. We also conducted sensitivity analyses to ensure the robustness of the results and performed subgroup analyses.

Results

A total of 16,876 patients were included in this analysis. Of these, 47.48% of patients were men. The post-operative 30-day mortality of the included cases was 2.49% (420/16,876), and the mean BUN was 16.874 ± 6.648 mg/dl. After adjusting covariates, the results showed that pre-operative BUN was positively associated with post-operative 30-day mortality (OR = 1.020, 95% CI: 1.004, 1.036). There was also a non-linear relationship between BUN and post-operative 30-day mortality, and the inflection point of the BUN was 9.804. For patients with BUN < 9.804 mg/dl, a 1 unit decrease in BUN was related to a 16.8% increase in the risk of post-operative 30-day mortality (OR = 0.832, 95% CI: 0.737, 0.941); for patients with BUN > 9.804 mg/dl, a 1 unit increase in BUN was related to a 2.8% increase in the risk of post-operative 30-day mortality (OR = 1.028, 95% CI: 1.011, 1.045). The sensitivity analysis proved that the results were robust. The subgroup analysis revealed that all listed subgroups did not affect the relationship between pre-operative BUN and post-operative 30-day mortality (P > 0.05).

Conclusion

Our study demonstrated that pre-operative BUN (mg/dl) has specific linear and non-linear relationships with post-operative 30-day mortality in patients over 18 years of age who underwent craniotomy for tumors. Proper pre-operative management of BUN and maintenance of BUN near the inflection point (9.804 mg/dl) could reduce the risk of post-operative 30-day mortality in these cases.

Blood Urea Nitrogen/Albumin Ratio and Mortality Risk in Patients with COVID-19

Introduction

We researched blood urea nitrogen (BUN), albumin and their ratio (BAR), and compared them with C-reactive protein (CRP), D-dimer, and computed tomography severity scores (CT-SS), to predict in-hospital mortality.

Methods

One-hundred and thirty-one coronavirus disease-2019 (COVID-19) confirmed patients brought to the emergency department (ED) were dispensed to the survivor or non-survivor group, in light of in-hospital mortality. Information on age, gender, complaints, comorbidities, laboratory parameters, and outcome were gathered from the patient's record files.

Results

The median BUN, mean total protein, mean albumin, median BAR, median creatinine, median CRP, and median D-dimer were recorded. CT-SS were utilized in categorizing the patient as mild, moderate, and severe. In-hospital mortality occurred in 42 (32.06%) patients (non-survivor group) and did not occur in 89 (67.94%) patients (survivor group). The median BUN (mg/dL) and BAR (mg/gm) values were significantly raised in the non-survivor group than in the survivor group [BUN: 23.48 (7.51–62.75) and 20.66 (4.07–74.67), respectively (p = 0.009); BAR: 8.33 mg/g (2.07–21.86) and 6.11 mg/g (1.26–23.33); (p = 0.0003)]. The mean albumin levels (gm/dL) in the non-survivor group were significantly lower than in the survivor group [2.96 ± 0.35 and 3.27 ± 0.35, respectively (p <0.0001)]. Albumin with an odd's ratio of 6.14 performed the best in predicting in-hospital mortality, followed by D-dimer (4.98). BAR and CRP had similar outcome of 3.75; BUN showed an OR of 3.13 at the selected cutoff value.

Conclusion

The BUN, albumin, and BAR were found to be dependable predictors of in-hospital mortality in COVID-19 patients, with albumin (hypoalbuminemia) performing even better.

How to cite this article

Singh S, Singh K. Blood Urea Nitrogen/Albumin Ratio and Mortality Risk in Patients with COVID-19. Indian J Crit Care Med 2022;26(5):626–631.

Blood Urea Nitrogen-to-Albumin Ratio in Predicting Long-Term Mortality in Patients Following Coronary Artery Bypass Grafting: An Analysis of the MIMIC-III Database

Background

This study examined the role of blood urea nitrogen-to-albumin ratio (BAR) in predicting long-term mortality in patients undergoing coronary artery bypass grafting (CABG).

Methods

In this retrospective cohort study, patients undergoing CABG were enrolled from the Medical Information Mart for Intensive Care III (MIMIC III) database. Patients were divided into the three groups according to the optimal cutoff values of BAR determined by X-tile software. The survival curve was constructed by the Kaplan–Meier method and multivariate Cox regression analysis was performed to explore the independent prognostic factors of 1- and 4-year mortality after CABG. The receiver operating characteristic (ROC) curves and the areas under the ROC curves (AUCs) were calculated to estimate the accuracy of BAR in predicting the outcomes. Subgroup analyses were also carried out.

Results

A total of 1,462 patients at 4-year follow-up were included, of which 933, 293, and 236 patients were categorized into the group 1 (≤ 6.45 mg/g), group 2 (>6.45 and ≤ 10.23 mg/g), and group 3 (>10.23 mg/g), respectively. Non-survivors showed an increased level of BAR at both 1- (p < 0.001) and 4-year (p < 0.001) follow-up compared with the survivors. The patients with a higher BAR had a higher risk of 1- and 4-year mortality following CABG (33.05 vs. 14.33 vs. 5.14%, p < 0.001 and 52.97 vs. 30.72 vs. 13.08%, p < 0.001, respectively). Cox proportional hazards regression model suggested a higher BAR as an independent risk factor of 1-year mortality (HR 3.904; 95% CI 2.559–5.956; P < 0.001) and 4-year mortality (HR 2.895; 95% CI 2.138–3.921; P < 0.001) after adjusting for confounders. Besides, the receiver operating characteristic (ROC) curves showed the better predictive ability of BAR compared to other grading scores at both 1- (0.7383, 95% CI: 0.6966–0.7800) and 4-year mortality (0.7189, 95% CI: 0.6872–0.7506). Subgroup analysis demonstrated no heterogeneous results of BAR in 4-year mortality in particular groups of patient.

Conclusion

This report provided evidence of an independent association between 1- and 4-year mortality after CABG and BAR. A higher BAR was associated with a higher risk of long-term mortality and could serve as a prognostic predictor in patients following CABG.

Analysis of the Value of the Blood Urea Nitrogen to Albumin Ratio as a Predictor of Mortality in Patients with Sepsis

Purpose

At present, simple, accurate, and efficient prognostic tools for the evaluation of cases with early-stage sepsis in the emergency department (ED) are lacking. An increased blood urea nitrogen to albumin ratio (BAR) has previously been shown to be a valuable biomarker with predictive utility in several diseases. The relationship between BAR and sepsis patient outcomes, however, is not well-understood. This exploration was thus developed for the exploration of the link between BAR values and the short-term prognosis of cases with sepsis.

Methods

This was a retrospective cohort research of sepsis cases admitted to the West China Hospital of Sichuan University ED from July 2015 to June 2016. Laboratory data were collected upon ED admission, and 7-day all-cause mortality was the primary study endpoint. Relationships between BAR values and APACE II and SOFA scores were generated assessed with correlation coefficient heatmaps. Independent risk factors were identified through multivariate analyses, with the curves of receiver operating characteristic (ROC) being employed to gauge the value of BAR as a predictor of the risk of mortality in sepsis cases.

Results

In sum, 801 patients participated in the present investigation. BAR values were strongly correlated with APACHE II and SOFA scores. In a multivariate logistic regression assessment, BAR was identified as an independent predictor of mortality among patients with sepsis (HR=1.032, 95% CI: 1.010–1.055, P=0.004). BAR exhibited an AUC of 0.741 (95% CI: 0.688–0.793, P<0.001) when used to predict patient mortality risk, with 5.27 being the optimal BAR cut-off.

Conclusion

We found that BAR can be used as a reliable biomarker to predict mortality in patients with sepsis.

Blood Urea Nitrogen to Serum Albumin Ratio in the Prediction of Acute Kidney Injury of Patients with Rib Fracture in Intensive Care Unit

Background

We hypothesized that the blood urea nitrogen (BUN) to serum albumin ratio (BAR) could serve as an independent predictor for incident acute kidney injury (AKI) in intensive care unit (ICU) patients with rib fracture.

Methods

Rib fracture patients in ICU were extracted from Medical Information Mart for Intensive Care IV (MIMIC-IV v1.0) database. The primary outcome in this study was the incidence of AKI. Univariate and multivariate logistic regression analyses were used to determine the relationship between BAR and AKI and propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) were also applied to assure the robustness of our results.

Results

The optimal cut-off value for BAR was 5.26 based on receiver operator characteristic curve. Among the 953 patients who diagnosed with rib fracture, 197 high-BAR group (≥5.26) patients and 197 low-BAR group (<5.26) patients who had similar propensity scores were finally included in the matched cohort. High-BAR group patients had a significantly higher incidence of AKI (odds ratio, OR, 3.85, 95% confidence index, 95% CI, 2.58–5.79, P<0.001) in the original cohort, in the matched cohort (OR, 4.47, 95% CI 2.71–7.53, P<0.001), and in the weighted cohort (OR, 4.28, 95% CI 2.80–6.53, P<0.001). Furthermore, BAR was superior to that of acute physiology score III for predicting AKI and could add more net benefit for incident AKI in critical care patients with rib fracture.

Conclusion

As an easily access and cost-effective parameter, BAR could serve as a good diagnostic predictor for AKI in ICU patients with rib fracture.

Do biomarkers have predictive value in the treatment modality of the patients diagnosed with bowel obstruction?

OBJECTIVES

This study aimed to investigate the ability of the biomarkers to predict the surgery treatment and mortality in patients above 18 years of age who were hospitalized with the diagnosis of bowel obstruction from the emergency department.

METHODS

This is a 2-year retrospective study. The patients' demographic data, laboratory parameters on admission to emergency department, treatment modalities, and the length of hospital stay were recorded. Patients were divided into two groups: conservative and surgical treatment. Statistical analysis was performed to investigate the value of biomarkers in predicting mortality and the need for surgery. Data were analyzed using IBM SPSS version 22.

RESULTS

A total of 179 patients were included in this study. Of these, 105 (58.7%) patients were treated conservative and 74 (41.3%) were treated operatively. The elevated procalcitonin (PCT) level, C-reactive protein, blood urea nitrogen-to-albumin ratio, and lactate-to-albumin ratio were significantly correlated with surgical treatment, length of hospital stay, and mortality. procalcitonin threshold value of 0.13 ng/mL was able to predict the need for surgical treatment, with a sensitivity of 79% and a specificity of 70.3%. Procalcitonin threshold value of 0.65 ng/mL was able to predict the mortality rate of the patients, with a sensitivity of 92.9% and a specificity of 78.1%.

CONCLUSIONS

Biomarkers, especially procalcitonin, may be useful in bowel obstruction treatment management and may predict mortality.

The association of blood urea nitrogen levels upon emergency admission with mortality in acute exacerbation of chronic obstructive pulmonary disease

Background and purpose

High blood urea nitrogen (BUN) is associated with an elevated risk of mortality in various diseases, such as heart failure and pneumonia. Heart failure and pneumonia are common comorbidities of acute exacerbation of chronic obstructive pulmonary disease (AECOPD). However, data on the relationship of BUN levels with mortality in patients with AECOPD are sparse. The purpose of this study was to evaluate the correlation between BUN level and in-hospital mortality in a cohort of patients with AECOPD who presented at the emergency department (ED).

Methods

A total of 842 patients with AECOPD were enrolled in the retrospective observational study from January 2018 to September 2020. The outcome was all-cause in-hospital mortality. Receiver operating characteristic (ROC) curve analysis and logistic regression models were performed to evaluate the association of BUN levels with in-hospital mortality in patients with AECOPD. Propensity score matching was used to assemble a cohort of patients with similar baseline characteristics, and logistic regression models were also performed in the propensity score matching cohort.

Results

During hospitalization, 26 patients (3.09%) died from all causes, 142 patients (16.86%) needed invasive ventilation, and 190 patients (22.57%) were admitted to the ICU. The mean level of blood urea nitrogen was 7.5 ± 4.5 mmol/L. Patients in the hospital non-survivor group had higher BUN levels (13.48 ± 9.62 mmol/L vs. 7.35 ± 4.14 mmol/L, p < 0.001) than those in the survivor group. The area under the curve (AUC) was 0.76 (95% CI 0.73–0.79, p < 0.001), and the optimal BUN level cutoff was 7.63 mmol/L for hospital mortality. As a continuous variable, BUN level was associated with hospital mortality after adjusting respiratory rate, level of consciousness, pH, PCO_2, lactic acid, albumin, glucose, CRP, hemoglobin, platelet distribution width, D-dimer, and pro-B-type natriuretic peptide (OR 1.10, 95% CI 1.03–1.17, p=0.005). The OR of hospital mortality was significantly higher in the BUN level ≥7.63 mmol/L group than in the BUN level <7.63 mmol/L group in adjusted model (OR 3.29, 95% CI 1.05–10.29, p=0.041). Similar results were found after multiple imputation and in the propensity score matching cohort.

Conclusions

Increased BUN level at ED admission is associated with hospital mortality in patients with AECOPD who present at the ED. The level of 7.63 mmol/L can be used as a cutoff value for critical stratification.

Urea-to-Albumin Ratio and In-Hospital Mortality in Severe Pneumonia Patients

Objective

The urea-to-albumin ratio (UAR), as a new marker of the systemic inflammatory response, is associated with the mortality in pneumonia patients. However, the association between the UAR and in-hospital mortality in severe pneumonia (SP) has received little attention.

Methods

In this single-center retrospective cohort study, 212 SP patients in intensive care unit (ICU) from June 1, 2016, to June 1st, 2020, with baseline UAR were enrolled. The primary outcome was in-hospital mortality. The association of UAR with in-hospital mortality was assessed using a multivariable-adjusted Cox model.

Results

Of 212 patients, the median age was 73.0 (61.0, 82.8) years, 70.8% of patients were male, and the APACHE II score was 20.0 (16.0, 26.0). During the hospital period, 101 (47.6%) patients died. In-hospital mortality rates for the lower and higher UAR were 16 (27.6%) and 85 (55.2%), respectively (P < 0.001). Kaplan–Meier analysis revealed that survival rates were significantly different between the two groups (log rank = 13.71, P < 0.001). After adjusted for confounding factors, the higher UAR group was significantly associated with a hazard ratio (HR) for in-hospital mortality of 2.234 (95% confidence interval: 1.146–4.356, P=0.018). Besides, this pattern persisted in subgroup analyses considering sex (HR = 9.380; 95% CI: 2.248–39.138; P=0.002).

Conclusions

Higher UAR levels at the commencement of admission to ICU may be independently associated with increased in-hospital mortality in SP patients.

Blood Urea Nitrogen to Serum Albumin Ratio (BAR) Predicts Critical Illness in Patients with Coronavirus Disease 2019 (COVID-19)

Purpose

We sought to explore the prognostic value of blood urea nitrogen (BUN) to serum albumin ratio (BAR) and further develop a prediction model for critical illness in COVID-19 patients.

Patients and Methods

This was a retrospective, multicenter, observational study on adult hospitalized COVID-19 patients from three provinces in China between January 14 and March 9, 2020. Primary outcome was critical illness, including admission to the intensive care unit (ICU), need for invasive mechanical ventilation (IMV), or death. Clinical data were collected within 24 hours after admission to hospitals. The predictive performance of BAR was tested by multivariate logistic regression analysis and receiver operating characteristic (ROC) curve and then a nomogram was developed.

Results

A total of 1370 patients with COVID-19 were included and 113 (8.2%) patients eventually developed critical illness in the study. Baseline age (OR: 1.031, 95% CI: 1.014, 1.049), respiratory rate (OR: 1.063, 95% CI: 1.009, 1.120), unconsciousness (OR: 40.078, 95% CI: 5.992, 268.061), lymphocyte counts (OR: 0.352, 95% CI: 0.204, 0.607), total bilirubin (OR: 1.030, 95% CI: 1.001, 1.060) and BAR (OR: 1.319, 95% CI: 1.183, 1.471) were independent risk factors for critical illness. The predictive AUC of BAR was 0.821 (95% CI: 0.784, 0.858; P<0.01) and the optimal cut-off value of BAR was 3.7887 mg/g (sensitivity: 0.690, specificity: 0.786; positive predictive value: 0.225, negative predictive value: 0.966; positive likelihood ratio: 3.226, negative likelihood ratio: 0.394). The C index of nomogram including above six predictors was 0.9031125 (95% CI: 0.8720542, 0.9341708).

Conclusion

Elevated BAR at admission is an independent risk factor for critical illness of COVID-19. The novel predictive nomogram including BAR has superior predictive performance.