Association between blood urea nitrogen to serum albumin ratio and in-hospital mortality of patients with sepsis in intensive care: A retrospective analysis of the fourth-generation Medical Information Mart for Intensive Care database

Association of blood urea nitrogen to glucose ratio with 365-day mortality in critically ill patients with chronic kidney disease: a retrospective study

Low blood glucose levels and high urea nitrogen levels affect patient prognosis, but few studies have investigated whether the blood urea nitrogen to glucose (BGR) ratio predicts the risk of death.This retrospective research examined the connection between the BGR and 365-day mortality in patients with chronic kidney disease (CKD) stages 1-4 admitted to an intensive care unit (ICU). The study utilized data from 6,380 patients in the Medical Information Mart for Intensive Care IV version 2.2 (MIMIC-IV v2.2), taking into account confounding factors such as demographics, vital signs, laboratory indicators, and comorbidities. The study employed both univariate and multivariate Cox regression analyses stratified by BGR quartiles. Additionally, restricted cubic spline regression and inflection point analysis were used to explore the linear relationship between BGR and 365-day mortality, while Kaplan-Meier curve analysis was used to observe mortality changes under different BGR stratifications. Subgroup and mediating effect analyses were performed to evaluate the robustness of BGR's effect on 365-day mortality. The study found a cumulative 365-day mortality rate of 34.2% among CKD stages 1-4 patients, with a 2.43-fold increase in the risk of death associated with BGR and at least a 44% increase in the risk of death for each unit increase in BGR (P = 0.022). A significant nonlinear relationship was identified, showing a stepwise change in the risk of death with a marked increase in the slope of the curve for BGR values below 0.52 and above 0.9 (P < 0.001). Subgroup analyses indicated interactions between BGR and factors such as age, sepsis, first-day antibiotic use, and cerebrovascular disease (P < 0.05). In conclusion, this study confirms that BGR is a significant and stable predictor of 1-year mortality risk in patients with CKD stages 1-4. Interventions aimed at timely adjustment, correction of metabolic imbalances, reduction of inflammation, and management of BGR levels are beneficial for reducing mortality in this patient population.

Association between blood-urea-nitrogen-to-albumin ratio and in-hospital mortality in patients diagnosed with coronavirus disease 2019: a retrospective cohort study

BACKGROUND

The blood-urea-nitrogen-to-albumin ratio (BAR) is recognized as a novel prognostic indicator; however, there is a limited number of studies investigating the relationship between BAR and in-hospital mortality associated with coronavirus disease 2019 (COVID-19). Therefore, the present investigation aims to explore the correlation between BAR and in-hospital mortality in patients with COVID-19 in China.

METHODS

This retrospective observational study enrolled a cohort of 1027 patients diagnosed with COVID-19 between December 2022 and March 2023. Multivariate Cox regression analyses were used to ascertain the independent association between BAR and in-hospital mortality among patients with COVID-19. Furthermore, stratified analyses were used to investigate potential interaction effects with variables, such as age, sex, COVID-19 Severity, hypertension, coronary artery disease, and diabetes mellitus.

RESULTS

A total of 117 patients (11.4%) died from various causes during hospitalization. Subsequent to adjustment for confounding variables, patients in the highest BAR tertile exhibited an elevated risk for in-hospital mortality relative to those in the lowest tertile (hazard ratio [HR] 2.44 [95% confidence interval CI 1.24-4.79]) when BAR was treated as a categorical variable. When considering BAR as a continuous variable, a 6% increase in the prevalence of in-hospital mortality was observed for each 1-unit increase in BAR (adjusted HR 1.06 [95% CI 1.03-1.08]; P < 0.001). Stratified analyses revealed a consistent association between BAR and in-hospital mortality due to COVID-19.

CONCLUSIONS

BAR exhibited a significant relationship with in-hospital mortality in patients with COVID-19, suggesting that a higher BAR is associated with a poorer prognosis. However, further research is required to confirm these findings.

Association of the blood urea nitrogen to serum albumin ratio and all-cause mortality in critical ill acute ischemic stroke patients: a retrospective cohort study of MIMIC-IV database 3.0

Purpose

We aim to ascertain the extent to which the blood urea nitrogen (BUN) to serum albumin (ALB) ratio (BAR) could be implemented to anticipate the short- and long-term prognosis of acute ischemic stroke (AIS) patients in intensive care units (ICUs).

Methods

The data was derived from the Marketplace for Intensive Care Medical Information-IV (MIMIC-IV v3.0) database, primarily pertaining to AIS patients as categorized by the International Classification of Diseases (ICD)-9 and ICD-10. The outcomes encompassed short-term ACM incorporating ICM admissions and 30-day, as well as longer-term ACM involving 90-day and 365-day. Any confounding effects were mitigated with a 1:1 propensity score matching (PSM) approach. We determined the critical BAR level affecting patient survival with the use of maximum chosen rank statistics. The connection between BAR and ACM at various time intervals was ascertained with the multivariate Cox regression (MCR) models after the adjustment for covariates. Kaplan-Meier (KM) survival curves were generated to illustrate variations in BAR and death over various time intervals. Additionally, the linear or non-linear connection between BAR and ACM was ascertained with restricted cubic spline (RCS) approaches, supplemented by interaction and subgroup analyses.

Results

Prior to PSM, we incorporated 1,764 suitable subjects with a median BAR of 5.52 mg/g. This cohort was composed of 1,395 and 369 patients in the BAR <10.42 and ≥10.42 groups, respectively. The ICU ACM rates were 9.53 and 19.24% (p < 0.001), respectively, while the 30-day ACM rates were 19.00 and 40.11% (p < 0.001). The 90- and 365-day ACM rates were 26.95 and 52.57% (p < 0.001), and 33.12 and 62.87%, respectively (p < 0.001). After fully adjustment, MCR models indicated a heightened mortality risk for the ICU (hazard ratio [HR] = 1.55, 95% confidence interval [CI]: 1.08-2.22; p = 0.02), 30-day (HR = 1.87, 95% CI: 1.46-2.38; p < 0.001), 90-day (HR = 1.75, 95% CI: 1.42-2.15; p < 0.001), and 365-day (HR = 1.81, 95% CI: 1.50-2.19; p < 0.001) in the high BAR group as opposed to the low BAR group. Following PSM, the analysis included 352 matched patient pairs, revealing persistent links between the higher BAR group and increased ACM risk throughout ICU, 30-, 90-, and 365-day intervals. Subsequent RCS studies before and after PSM highlighted a positive non-linear correlation between BAR and ACM in the short and long-term. In the subgroup investigation of ICU ACM, a subgroup of diabetes had an interaction effect (P for interaction = 0.02). In the subgroup analysis of 90-day ACM, subgroups of hypertension and CRRT had an interaction effect (all P for interaction < 0.05). In the subgroup analysis of 365-day ACM, subgroups of HTN, CRRT, and malignancy tumor had an interaction effect (all P for interaction < 0.05).

Conclusion

In this retrospective cohort study, our findings reveal that a confluence of deteriorated nutritional and renal function is significantly linked to heightened risks of ACM, and BAR may operate as an effective predictive indicator for AIS patients in ICUs. These findings have substantial importance for public health policy and practice. A comprehensive knowledge of these linkages may enable public health specialists and researchers to formulate more precisely targeted drugs and policies tailored to the unique requirements of the AIS patient group, hence improving their health outcomes. We reveal a significant link between the BAR and ACM in persons with AIS, highlighting the BAR's potential as an innovative, economical, and accessible measure for forecasting ACM in this demographic. However, further research is needed on other racial and ethnic groups before these findings can be widely applied in clinical practice.

Predicting survival in sepsis: The prognostic value of NLR and BAR ratios

BACKGROUND

Due to the high-risk nature of sepsis, emergency departments urgently need a simple evaluation method to assess the degree of inflammation and prognosis in sepsis patients, providing a reference for diagnosis and treatment.

OBJECTIVE

To investigate the prognostic value of the neutrophil-to-lymphocyte ratio (NLR) combined with the blood urea nitrogen-to-serum albumin ratio (BAR) in sepsis.

METHODS

A total of 377 sepsis patients admitted to Lishui People's Hospital from June 2022 to June 2023 were selected as the study subjects. Based on their prognosis, they were divided into a survival group (255 cases) and a death group (82 cases). The clinical data of the two groups were compared. Multivariate logistic analysis was used to identify factors influencing sepsis prognosis, and ROC curve analysis was used to assess the predictive efficacy of NLR, BAR, and their combination.

RESULTS

Compared with survivors, non-survivors had higher NLR and BAR, with statistically significant differences (p< 0.05). After adjusting for confounding factors, NLR (OR = 1.052) and BAR (OR = 1.095) were found to be independent prognostic factors for sepsis patients (both p< 0.05). The AUC of NLR combined with BAR was 0.798 (95% CI 0.745-0.850, p< 0.05), higher than the AUC of NLR alone (0.776) and BAR alone (0.701).

CONCLUSIONS

The combination of NLR and BAR has a high predictive value for the prognosis of sepsis patients. Its simple calculation makes it particularly suitable for use in emergency departments.

Acute kidney injury and COVID-19: the predictive power of BUN/albumin ratio for renal replacement therapy requirement

OBJECTIVE

To investigate the predictive power of the BUN/albumin ratio (BAR) measured in the emergency department (ED) for the requirement of renal replacement therapy (RRT) in patients admitted to the intensive care unit (ICU) with severe COVID-19 pneumonia and acute kidney injury (AKI).

MATERIALS AND METHODS

The study included 117 patients with AKI who were admitted to the ICU and had COVID-19 pneumonia detected on chest computed tomography (CT) taken in the ED's pandemic area between November 1, 2020, and June 1, 2021. The predictive power of laboratory values measured at the time of ED admission for the requirement of RRT was analyzed.

RESULTS

Of the patients, 59.8% (n = 70) were male, with an average age of 71.7 ± 14.8 years. The mortality rate of the study was 35% (n = 41). During follow-up, 23.9% (n = 28) of the patients required RRT. Laboratory parameters measured at the time of ED admission showed that patients who required RRT had significantly higher BAR, BUN, and creatinine levels, and significantly lower albumin levels (all p < 0.001). ROC analysis to determine the predictive characteristics for RRT requirement revealed that the BAR had the highest AUC value (AUC, 0.885; 95% CI 0.825-0.945; p < 0.001). According to the study data, for BAR, a cut-off value of 1.7 resulted in a sensitivity of 96.4% and a specificity of 71.9%.

CONCLUSION

In patients with severe pneumonia who develop acute kidney injury, the BUN/albumin ratio may guide clinicians early in predicting the need for renal replacement therapy.

The Interrelation of Blood Urea Nitrogen-to-Albumin Ratio with Three-Month Clinical Outcomes in Acute Ischemic Stroke Cases: A Secondary Analytical Exploration Derived from a Prospective Cohort Study

Objective

This study targeted elucidating the intricate correlation of the blood urea nitrogen (BUN)-to-albumin (BUN/Alb) ratio with adverse outcomes (AOs) at 3-month in acute ischemic stroke (AIS) cases within a Korean cohort.

Methods

The cohort involved a comprehensive dataset of 1850 AIS cases from a South Korean hospital, spanning from January 2010 to December 2016. To discern the linear relationship of the BUN/Alb ratio with AOs in AIS cases, utilization of a binary logistic regression model (BLRM) was implemented. Additionally, it was attempted to utilize sophisticated statistical techniques, such as generalized additive models (GAMs) and smooth curve fitting methods, to unravel the nonlinear association of the BUN/Alb ratio with AOs in such patients.

Results

The incidence of AOs was determined to be 28.49%, with the median BUN/Alb ratio being 3.85. After adjusting for a number of covariates, the BLRM disclosed that the linear association of BUN/Alb ratio with the risk of AOs particularly in AIS cases did not achieve statistical significance. However, a noticeable nonlinear relationship emerged, with an inflection point identified at 2.86. To the left of this inflection point, the relationship is not statistically significant. On the right side of the inflection point, there was a remarkable 9.47% rise in the risk of AOs (odds ratio (OR) = 1.09, 95% confidence interval (CI): 1.00, 1.19, P = 0.04).

Conclusion

The outcomes illuminate the complex and nonlinear relationship of the BUN/Alb ratio with 3-month AOs in AIS cases. This study established a robust groundwork for the future research, underscoring the potential clinical utility of monitoring the BUN/Alb ratio to enhance the prognostic assessment and management of AIS cases.

Blood urea nitrogen to albumin ratio is a novel predictor of fatal outcome for patients with severe fever with thrombocytopenia syndrome

Severe fever with thrombocytopenia syndrome (SFTS) is associated with a high death rate and lacks a targeted therapy plan. The ratio of blood urea nitrogen to albumin, known as BAR, is a valuable method for assessing the outlook of various infectious diseases. The objective of this research was to evaluate the effectiveness of BAR in forecasting the outcome of individuals with SFTS. Four hundred and thirty-seven patients with SFTS from two clinical centers were included in this study according to inclusion and exclusion criteria. Clinical characteristics and test parameters of SFTS patients were analyzed between survival and fatal groups. Least absolute shrinkage and selection operator (LASSO) regression and Cox regression suggested that BAR might serve as a standalone prognostic indicator for patients with SFTS in the initial phase (hazard ratio = 18.669, 95% confidence interval [CI]: 8.558-40.725, p < 0.001). And BAR had a better predictive effectiveness in clinical outcomes in patients with SFTS with an AUC of 0.832 (95% CI: 0.788-0.876, p < 0.001), a cutoff value of 0.19, a sensitivity of 0.812, and a specificity of 0.726 compared to C-reactive protein, procalcitonin, and platelet to lymphocyte ratio via receiver operating characteristic curve. KM (Kaplan Meier) curves demonstrated that high level of BAR was associated with poor survival condition in patients with SFTS. Furthermore, the high level of BAR was associated with long hospital stays and test paraments of kidney, liver, and coagulation function in survival patients. So, BAR could be used as a promising early warning biomarker of adverse outcomes in patients with SFTS.

Blood urea nitrogen to serum albumin ratio: a novel mortality indicator in intensive care unit patients with coronary heart disease

The blood urea nitrogen to albumin ratio (BAR) has been demonstrated as a prognostic factor in sepsis and respiratory diseases, yet its role in severe coronary heart disease (CHD) remains unexplored. This retrospective study, utilizing data from the Medical Information Mart for Intensive Care-IV database, included 4254 CHD patients, predominantly male (63.54%), with a median age of 74 years (IQR 64-83). Primary outcomes included in-hospital, 28-day and 1-year all-cause mortality after ICU admission. The Kaplan-Meier curves, Cox regression analysis, multivariable restricted cubic spline regression were employed to assess association between BAR index and mortality. In-hospital, within 28-day and 1-year mortality rates were 16.93%, 20.76% and 38.11%, respectively. Multivariable Cox proportional hazards analysis revealed associations between the increased BAR index and higher in-hospital mortality (HR 1.11, 95% CI 1.02-1.21), 28-day mortality (HR 1.17, 95% CI 1.08-1.27) and 1-year mortality (HR 1.23, 95% CI 1.16-1.31). Non-linear relationships were observed for 28-day and 1-year mortality with increasing BAR index (both P for non-linearity < 0.05). Elevated BAR index was a predictor for mortality in ICU patients with CHD, offering potential value for early high-risk patient identification and proactive management by clinicians.

Predicting sepsis in-hospital mortality with machine learning: a multi-center study using clinical and inflammatory biomarkers

BACKGROUND

This study aimed to develop and validate an interpretable machine-learning model that utilizes clinical features and inflammatory biomarkers to predict the risk of in-hospital mortality in critically ill patients suffering from sepsis.

METHODS

We enrolled all patients diagnosed with sepsis in the Medical Information Mart for Intensive Care IV (MIMIC-IV, v.2.0), eICU Collaborative Research Care (eICU-CRD 2.0), and the Amsterdam University Medical Centers databases (AmsterdamUMCdb 1.0.2). LASSO regression was employed for feature selection. Seven machine-learning methods were applied to develop prognostic models. The optimal model was chosen based on its accuracy, F1 score and area under curve (AUC) in the validation cohort. Moreover, we utilized the SHapley Additive exPlanations (SHAP) method to elucidate the effects of the features attributed to the model and analyze how individual features affect the model's output. Finally, Spearman correlation analysis examined the associations among continuous predictor variables. Restricted cubic splines (RCS) explored potential non-linear relationships between continuous risk factors and in-hospital mortality.

RESULTS

3535 patients with sepsis were eligible for participation in this study. The median age of the participants was 66 years (IQR, 55-77 years), and 56% were male. After selection, 12 of the 45 clinical parameters collected on the first day after ICU admission remained associated with prognosis and were used to develop machine-learning models. Among seven constructed models, the eXtreme Gradient Boosting (XGBoost) model achieved the best performance, with an AUC of 0.94 and an F1 score of 0.937 in the validation cohort. Feature importance analysis revealed that Age, AST, invasive ventilation treatment, and serum urea nitrogen (BUN) were the top four features of the XGBoost model with the most significant impact. Inflammatory biomarkers may have prognostic value. Furthermore, SHAP force analysis illustrated how the constructed model visualized the prediction of the model.

CONCLUSIONS

This study demonstrated the potential of machine-learning approaches for early prediction of outcomes in patients with sepsis. The SHAP method could improve the interoperability of machine-learning models and help clinicians better understand the reasoning behind the outcome.

Blood urea nitrogen to serum albumin ratio is associated with all-cause mortality in patients with AKI: a cohort study

Background

This study aims to investigate the relationship between blood urea nitrogen to serum albumin ratio (BAR) and all-cause mortality in patients with acute kidney injury (AKI) and evaluate the effect of BAR on the prognosis of AKI.

Methods

Adult patients with AKI admitted to the ICU in the Medical Information Mart for Intensive Care IV (MIMIC-IV) were selected in a retrospective cohort study. BAR (mg/g) was calculated using initial blood urea nitrogen (mg/dl)/serum albumin (g/dl). According to the BAR, these patients were divided into quartiles (Q1-Q4). Kaplan-Meier analysis was used to compare the mortality of the above four groups. Multivariate Cox regression analysis was used to evaluate the association between BAR and 28-day mortality and 365-day mortality. The receiver operating characteristic (ROC) curve was plotted and the area under the curve (AUC) was calculated, and the subgroup analysis was finally stratified by relevant covariates.

Results

A total of 12,125 patients with AKI were included in this study. The 28-day and 365-day mortality rates were 23.89 and 39.07%, respectively. Kaplan-Meier analysis showed a significant increase in all-cause mortality in patients with high BAR (Log-rank p < 0.001). Multivariate Cox regression analysis showed that BAR was an independent risk factor for 28-day mortality (4.32 < BAR≤7.14: HR 1.12, 95% CI 0.97-1.30, p = 0.114; 7.14 < BAR≤13.03: HR 1.51, 95% CI 1.31-1.75, p < 0.001; BAR>13.03: HR 2.07, 95% CI 1.74-2.47, p < 0.001; Reference BAR≤4.32) and 365-day mortality (4.32 < BAR≤7.14: HR 1.22, 95% CI 1.09-1.36, p < 0.001; 7.14 < BAR≤13.03: HR 1.63, 95% CI 1.46-1.82, p < 0.001; BAR>13.03: HR 2.22, 95% CI 1.93-2.54, p < 0.001; Reference BAR ≤ 4.32) in patients with AKI. The AUC of BAR for predicting 28-day mortality and 365-day mortality was 0.649 and 0.662, respectively, which is better than that of blood urea nitrogen and sequential organ failure assessment. In addition, subgroup analysis showed a stable relationship between BAR and adverse outcomes in patients with AKI.

Conclusion

BAR is significantly associated with increased all-cause mortality in patients with AKI. This finding suggests that BAR may help identify people with AKI at high risk of mortality.

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.

Role of serum biomarkers in predicting management strategies for acute pulmonary embolism

Background

Acute pulmonary embolism (APE) is a condition that can be fatal. The severity of the disease influences therapeutic decisions, and mortality varies significantly depending on the condition's severity. Identification of patients with a high mortality risk is crucial. Since inflammation, hemostatic, and coagulation abnormalities are linked to APE, serum biomarkers may be helpful for prognostication.

Aim

To evaluate the significance of serum biomarkers in APE risk assessment and the suitability of these biomarkers for management and decision-making.

Methods

This study involved 60 adult patients with APE who were divided according to risk categorization. It was conducted in Chest, Cardiology and Internal Medicine department, Zagazig University Hospitals from December 2022 to May 2023. Several hematological biomarkers and their significance in APE risk assessment were measured with a comparison with the latest risk stratification methods which include haemodynamic measures and right ventricular (RV) dysfunction echocardiographic markers.

Results

Each risk group involved 20 patients (high, intermediate (10 were intermediate-high and 10 were intermediate-low) and low risk group). They were 34 females and 26 males with the mean ± SD of their age was 59.25 ± 13.06 years. Regarding hematological biomarkers, there were statistically significant differences as regards; lymphocytes, platelet to lymphocyte ratio (PLR), albumin, blood urea nitrogen (BUN), C-reactive protein (CRP) and D-dimer with highly statistically significant differences as regards; neutrophil to lymphocyte ratio (NLR), BUN to albumin (B/A) ratio, troponin I (TnI), and brain natriuretic peptide (BNP). TnI had the highest specificity and predictive value positive (PVP) and BNP had the highest sensitivity and predictive value negative (PVN) in predicting high risk groups. The Lymphocyte and NLR showed the lowest sensitivity and the albumin and B/A ratio had the lowest specificity. Regarding transthoracic echocardiography (TEE); there was a statistically significant increase regarding pulmonary artery systolic pressure (PASP) and a highly statistically significant increase regarding the right ventricle/left ventricle (RV/LV) ratio. There were statistically significant decreases regarding tricuspid annular plane systolic excursion (TAPSE) and peak systolic velocity of tricuspid annulus (S') among risk groups.

Conclusion

APE prognosis can be judged accurately by simultaneously measuring a few biomarkers along with haemodynamic variables and echocardiographic parameters of RV dysfunction.

An analysis of lactate/albumin, procalcitonin/albumin, and blood urea nitrogen/albumin ratios as a predictor of mortality in uroseptic patients

OBJECTIVE

The aim of this study was to investigate the ratios of lactate/albumin, procalcitonin/albumin, and blood urea nitrogen/albumin to predict 14- and 28-day mortality in uroseptic patients. Urosepsis is a disease with high mortality, and early diagnosis and treatment are important.

METHODS

Patients with urosepsis who were admitted to the intensive care unit between January 2021 and September 2022, had a follow-up of at least 28 days, and met the inclusion criteria were evaluated retrospectively.

RESULTS

The mean age was 70.23 (15.66) years and 84 (53.85%) were males. The number of non-survivors were 75 (48%) in the 14-day mortality group and 97 (62.1%) in the 28-day mortality group. Based on the 14-day mortality data, the blood urea nitrogen/albumin ratio was higher in non-survivors vs. survivors (median, 15.88 vs. 9.62), and the lactate/albumin ratio was higher (median, 0.96 vs. 0.52, p<0.01, all). Based on the 28-day mortality data, the blood urea nitrogen/albumin ratio was higher in non-survivors vs. survivors (median, 14.78 vs. 8.46), and the lactate/albumin ratio was higher (median, 0.90 vs. 0.50, p<0.01, all).

CONCLUSION

It is very difficult to determine the prognosis of patients admitted to the emergency department with the diagnosis of urosepsis. The lactate/albumin ratio and the blood urea nitrogen/albumin ratio can be used as early prognostic markers for both 14-day and 28-day mortality until more reliable markers are identified.

The National Early Warning Score 2(NEWS2) to Predict Early Progression to Severe Community-Acquired Pneumonia

This study aimed to assess the predictive performance of the National Early Warning Score 2 (NEWS2) to identify the early progression to severe disease in patients with community-acquired pneumonia (CAP). A prospective-cohort study was conducted among patients with CAP admitted to a university hospital between October 2020 and December 2021. The endpoint of interest was the progression to severe CAP, defined as the requirement for a mechanical ventilator, a vasopressor, or death within 72 h after hospital admission. Among 260 patients, 53 (25.6%) had early progression to severe CAP. The median NEWS2 of the early progression group was higher than that of the non-progression group [8 (6-9) vs. 7 (5-8), p = 0.015, respectively]. The AUROC of NEWS2 to predict early progression to severe CAP was 0.61 (95% CI: 0.52-0.70), while IDSA/ATS minor criteria ≥ 3 had AUROC 0.56 (95% CI 0.48-0.65). The combination of NEWS2 ≥ 8, albumin level < 3 g/dL and BUN ≥ 30 mg/dL improved AUROC from 0.61 to 0.71 (p = 0.015). NEWS2 and IDSA/ATS minor criteria showed fair predictive-accuracy in predicting progression to severe CAP. The NEWS2 cut-off ≥ 8 in combination with low albumin and uremia improved predictive-accuracy, and could be easily used in general practice.