BUN as an Independent Predictor of Post-Hospital-Discharge Mortality among Older Veterans

Blood Profiles of Community-Dwelling People with Sarcopenia: Analysis Based on the China Health and Retirement Longitudinal Study

INTRODUCTION

Routine blood factors can be economical and easily accessible candidates for sarcopenia screening and monitoring. The associations between sarcopenia and routine blood factors remain unclear. This study aimed to examine sarcopenia and blood factor associations based on a nation-wide cohort in China.

METHODS

A total of 1,307 participants and 17 routine blood indices were selected from two waves (year 2011 and year 2015) of the China Health and Retirement Longitudinal Study (CHARLS). The diagnosis of sarcopenia was based on the criteria proposed by the Asian Working Group for Sarcopenia (AWGS 2019). Generalized mixed-effects models were performed for association analyses. A logistic regression (LR) model was conducted to examine the predictive power of identifying significant blood factors for sarcopenia.

RESULTS

A higher sarcopenia risk was cross-sectionally associated with elevated blood concentrations of high-sensitivity C-reactive protein (hsCRP) (OR = 1.030, 95% CI [1.007, 1.053]), glycated hemoglobin (HbA1c) (OR = 1.407, 95% CI [1.126, 1.758]) and blood urea nitrogen (BUN) (OR = 1.044, 95% CI [1.002, 1.089]), and a decreased level of glucose (OR = 0.988, 95% CI [0.979, 0.997]). A higher baseline hsCRP value (OR = 1.034, 95% CI [1.029, 1.039]) and a greater over time change in hsCRP within 4 years (OR = 1.034, 95% CI [1.029, 1.039]) were associated with a higher sarcopenia risk. A higher BUN baseline value was related to a decreased sarcopenia risk over time (OR = 0.981, 95% CI [0.976, 0.986]), while a greater over time changes in BUN (OR = 1.034, 95% CI [1.029, 1.040]) and a smaller over time change in glucose (OR = 0.992, 95% CI [0.984, 0.999]) within 4 years were also related to a higher sarcopenia risk. LR based on significant blood factors (i.e., hsCRP, HbA1c, BUN, and glucose), and sarcopenia status in year 2015 yielded an area under the curve of 0.859 (95% CI: 0.836-0.882).

CONCLUSION

Routine blood factors involved in inflammation, protein metabolism, and glucose metabolism are significantly associated with sarcopenia. In clinical practice, plasma hsCRP, BUN, blood sugar levels, sex, age, marital status, height, and weight might be helpful for sarcopenia evaluation and monitoring.

Risk Factors for Death Among Veterans Following Acute Kidney Injury

BACKGROUND

Acute kidney injury is prevalent among hospitalized veterans, and associated with increased risk of death following discharge. However, risk factors for death following acute kidney injury have not been well defined. We developed a mortality prediction model using Veterans Health Administration data.

METHODS

This retrospective cohort study included inpatients from 2013 through 2018 with a creatinine increase of ≥0.3 mg/dL. We evaluated 45 variables for inclusion in our final model, with a primary outcome of 1-year mortality. Bootstrap sampling with replacement was used to identify variables selected in >60% of models using stepwise selection. Best sub-sets regression using Akaike information criteria was used to identify the best-fitting parsimonious model.

RESULTS

A total of 182,683 patients were included, and 38,940 (21.3%) died within 1 year of discharge. The 10-variable model to predict mortality included age, chronic lung disease, cancer within 5 years, unexplained weight loss, dementia, congestive heart failure, hematocrit, blood urea nitrogen, bilirubin, and albumin. Notably, acute kidney injury stage, chronic kidney disease, discharge creatinine, and proteinuria were not selected for inclusion. C-statistics in the primary validation cohorts were 0.77 for the final parsimonious model, compared with 0.52 for acute kidney injury stage alone.

CONCLUSION

We identified risk factors for long-term mortality following acute kidney injury. Our 10-variable model did not include traditional renal variables, suggesting that non-kidney factors contribute to the risk of death more than measures of kidney disease in this population, a finding that may have implications for post-acute kidney injury care.

Blood urea nitrogen - independent marker of mortality in sepsis

BACKGROUND

This retrospective study examines the relationship between admission Blood Urea Nitrogen (BUN) levels and clinical outcomes in patients with sepsis from two separate cohorts in the Czech Republic and the United States.

METHODS

The study included 9126 patients with sepsis between January 2014 and December 2018. Kaplan-Meier survival curves and Cox regression were used to analyse the data. An optimal cut-off was calculated by means of the Youden-Index.

RESULTS

BUN at ICU admission was categorized as 10-20, 20-40 and >40 mg/dL. Comparing the group with the highest BUN levels to the one with lowest levels, we found HR for 28 days mortality 2.764 (CI 95% 2.37-3.20; P<0.001). We derived an optimal cut-off for prediction of 28 days mortality of 23 mg/dL. The association between BUN and 28 days mortality remained significant after adjusting for potential confounders - for APACHE IV (HR 1.374; 95%CI 1.20-1.58; P<0.001), SAPS2 (HR 1.545; 95%CI 1.35-1.77; P<0.001), eGFR (HR 1.851; 95%CI 1.59-2.16; P<0.001) and several other variables in an integrative model.

CONCLUSIONS

Our findings support the BUN level as an independent and easily available predictor of 28 days mortality in septic critically ill patients admitted to an ICU.

Blood urea nitrogen to serum albumin ratio: a good predictor of in-hospital and 90-day all-cause mortality in patients with acute exacerbations of chronic obstructive pulmonary disease

BACKGROUND

Previous studies on acute exacerbation of chronic obstructive pulmonary disease (AECOPD) have found that those who died in hospital had higher blood urea nitrogen levels and a worse nutritional status compared to survivors. However, the association between the blood urea nitrogen to serum albumin ratio (BUN/ALB ratio) and in-hospital and short-term prognosis in patients with AECOPD remains unclear. The aim of this study was to explore the usefulness of BUN/ALB ratio in AECOPD as an objective predictor for in-hospital and 90-day all-cause mortality.

METHODS

We recorded the laboratory and clinical data in patients with AECOPD on admission. By drawing the ROC curve for the patients, we obtained the cut-off point for the BUN/ALB ratio for in-hospital death. Multivariate logistic regression was used for analyses of the factors of in-hospital mortality and multivariate Cox regression was used to analyze the factors of 90-day all-cause mortality.

RESULTS

A total of 362 patients were recruited and 319 patients were finally analyzed. Twenty-three patients died during hospitalization and the fatality rate was 7.2%. Furthermore, 14 patients died by the 90-day follow-up. Compared with in-hospital survivors, patients who died in hospital were older (80.78 ± 6.58 vs. 75.09 ± 9.73 years old, P = 0.001), had a higher prevalence of congestive heart failure(69.6% vs. 27.4%, P < 0.001), had a higher BUN/ALB ratio [0.329 (0.250-0.399) vs. 0.145 (0.111-0.210), P < 0.001], had higher neutrophil counts [10.27 (7.21-14.04) vs. 6.58 (4.58-9.04), P < 0.001], higher blood urea nitrogen levels [10.86 (7.10-12.25) vs. 5.35 (4.14-7.40), P < 0.001], a lower albumin level (32.58 ± 3.72 vs. 36.26 ± 4.53, P < 0.001) and a lower lymphocyte count [0.85 (0.58-1.21) vs. 1.22 (0.86-1.72), P = 0.001]. The ROC curve showed that the area under the curve (AUC) of BUN/ALB ratio for in-hospital death was 0.87, (95%CI 0.81-0.93, P < 0.001), the best cut-off point value to discriminate survivors from non-survivors in hospital was 0.249, the sensitivity was 78.3%, the specificity was 86.5%, and Youden's index was 0.648. Having a BUN/ALB ratio ≥ 0.249 was an independent risk factor for both in-hospital and 90-day all-cause mortality after adjustment for relative risk (RR; RR = 15.08, 95% CI 3.80-59.78, P < 0.001 for a multivariate logistic regression analysis) and hazard ratio (HR; HR = 5.34, 95% CI 1.62-17.57, P = 0.006 for a multivariate Cox regression analysis).

CONCLUSION

An elevated BUN/ALB ratio was a strong and independent predictor of in-hospital and 90-day all-cause mortality in patients with AECOPD.

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.

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.

Development, validation, and visualization of a web-based nomogram to predict 5-year mortality risk in older adults with hypertension

Background

Hypertension-related mortality has been increasing in older adults, resulting in serious burden to society and individual. However, how to identify older adults with hypertension at high-risk mortality remains a great challenge. The purpose of this study is to develop and validate the prediction nomogram for 5-year all-cause mortality in older adults with hypertension.

Methods

Data were extracted from National Health and Nutrition Examination Survey (NHANES). We recruited 2691 participants aged 65 years and over with hypertension in the NHANES 1999-2006 cycles (training cohort) and 1737 participants in the NHANES 2007-2010 cycles (validation cohort). The cohorts were selected to provide at least 5 years follow-up for evaluating all-cause mortality by linking National Death Index through December 31, 2015. We developed a web-based dynamic nomogram for predicting 5-year risk of all-cause mortality based on a logistic regression model in training cohort. We conducted internal validation by 1000 bootstrapping resamples and external validation in validation cohort. The discrimination and calibration of nomogram were evaluated using concordance index (C-index) and calibration curves.

Results

The final model included eleven independent predictors: age, sex, diabetes, cardiovascular disease, body mass index, smoking, lipid-lowering drugs, systolic blood pressure, hemoglobin, albumin, and blood urea nitrogen. The C-index of model in training and validation cohort were 0.759 (bootstrap-corrected C-index 0.750) and 0.740, respectively. The calibration curves also indicated that the model had satisfactory consistence in two cohorts. A web-based nomogram was established (https://hrzhang1993.shinyapps.io/dynnomapp).

Conclusions

The novel developed nomogram is a useful tool to accurately predict 5-year all-cause mortality in older adults with hypertension, and can provide valuable information to make individualized intervention.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-03087-3.

Respiratory failure and bioelectrical phase angle are independent predictors for long-term survival in acute heart failure

Background. The assessment of long-term mortality in acute decompensated heart failure (ADHF) is challenging. Respiratory failure and congestion play a fundamental role in risk stratification of ADHF patients. The aim of this study was to investigate the impact of arterial blood gases (ABG) and congestion on long-term mortality in patients with ADHF. Methods and results. We enrolled 252 patients with ADHF. Brain natriuretic peptide (BNP), blood urea nitrogen (BUN), phase angle as assessed by means of bioimpedance vector analysis, and ABG analysis were collected at admission. The endpoint was all-cause mortality. At a median follow-up of 447 d (interquartile range [IQR]: 248-667), 72 patients died 1-840 d (median 106, IQR: 29-233) after discharge. Respiratory failure types I and II were observed in 78 (19%) and 53 (20%) patients, respectively. The ROC analyses revealed that the cut-off points for predicting death were: BNP > 441 pg/mL, BUN > 1.67 mmol/L, partial pressure in oxygen (PaO₂) ≤69.7 mmHg_, and phase angle ≤4.9°. Taken together, these four variables proved to be good predictors for long-term mortality in ADHF (area under the curve [AUC] 0.78, 95% CI 0.72-0.78), thus explaining 60% of all deaths. A multiparametric score based on these variables was determined: each single-unit increase promoted a 2.2-fold augmentation of the risk for death (hazard ratio [HR] 2.2, 95% CI 1.8-2.8, p< .0001). Conclusions. A multiparametric approach based on measurements of BNP, BUN, PaO_2, and phase angle is a reliable approach for long-term prediction of mortality risk in patients with ADHF.

A Novel Formula Comprising Wolfberry, Figs, White Lentils, Raspberries, and Maca (WFWRM) Induced Antifatigue Effects in a Forced Exercise Mouse Model

Long-term body fatigue poses a threat to human health. To explore novel sources of antifatigue medicine and food, we developed a novel formula composed of wolfberry, figs, white lentils, raspberries, and maca (WFWRM) according to the theory of traditional Chinese medicine. In this study, we explored whether the administration of the WFWRM relieves fatigue. Thirty male Kunming mice were divided into three groups, which received either intragastric administration of saline, vitamin C (100 mg/kg), or WFWRM (1.00 g/kg) every day. After 30 days of treatment, all mice exhaustively performed weight-bearing swimming. Another ten mice that did not perform swimming were treated with saline for 30 days and used as sedentary control. The antifatigue effect and biochemical oxidation phenomena were assessed in the exercise-exhausted model and sedentary controls. The histopathological changes in the liver and kidney tissues of mice were observed by performing hematoxylin-eosin (HE) staining. After 30 days of oral administration, the liver and kidney tissues of mice were healthy and show no pathological changes. Compared to the fatigue model group, WFWRM significantly increased the rota-rod time of the mice. Also, the concentrations of lactic acid (LA), blood urea nitrogen (BUN), creatine kinase (CK), and lactate dehydrogenase (LDH) in the WFWRM group significantly reduced. On the contrary, the levels of hepatic glycogen (LG), muscle glycogen (MG), and serum glucose (GLU) increased in the WFWRM group. Besides, WFWRM markedly reduced the levels of malondialdehyde (MDA) but increased the levels of glutathione peroxidase (GSH-PX) and superoxide dismutase (SOD). Pearson correlation analysis indicated that the concentrations of the sources of energy (LG, MG, and GLU) significantly correlated with those of metabolites (BLA, BUN, CK, and LDH) and antioxidant levels (SOD, GSH-PX, and MDA). Overall, our results suggested that the supplementation of WFWRM could improve exercise capacity and relieve fatigue probably by normalizing energy metabolism and attenuating oxidation.

Composite Biomarkers for Assessing Frailty Status in Stable Older Adults With Cardiovascular Disease

Background: The relationship between frailty status and laboratory measurements in cardiovascular disease (CVD) remains unclear. We investigated which laboratory measurements indicated frailty in stable older CVD patients.

Methods and Results: One-hundred thirty-eight stable older CVD patients were evaluated by laboratory measurements, with frailty assessed using the Kihon Checklist (KCL). Laboratory measurements were compared between frail and non-frail groups. Across the entire cohort, mean age was 81.7 years, mean left ventricular ejection fraction was 57.8%, and mean plasma B-type natriuretic peptide was 182 pg/mL. KCL scores were used to divide patients into non-frail (n=43; KCL <8) and frail (n=95; KCL ≥8) groups. Serum iron was significantly lower in the frail than non-frail group (mean [±SD] 61.2±30.3 vs. 89.5±26.1 μg/dL, respectively; P<0.001). Blood urea nitrogen (BUN; 27.3±16.5 vs. 19.7±8.2 mg/dL; P=0.013) and C-reactive protein (CRP; 1.05±1.99 vs. 0.15±0.21 mg/dL; P=0.004) were significantly higher in the frail than non-frail group. Multivariate analysis revealed that serum iron, CRP, and BUN were significant independent predictors of frailty (β=−0.069, 0.917, and 0.086, respectively).

Conclusions: Frailty status was significantly associated with iron, CRP, and BUN in stable older CVD patients. Composite biomarkers (inflammation, iron deficiency, and renal perfusion) may be useful for assessing frailty in these patients.

The BISAP score, NLR, CRP, or BUN: Which marker best predicts the outcome of acute pancreatitis?

Acute pancreatitis is a common disease, and the mortality rate can be high. Thus, a risk assessment should be performed early to optimize treatment. We compared simple prognostic markers with the bedside index for severity in acute pancreatitis (BISAP) scoring system to identify the best predictors of severity and mortality.This retrospective study stratified disease severity based on the revised Atlanta criteria. The accuracies of the markers for predicting severe AP (SAP) were assessed using receiver operating characteristic curves. The sensitivity, specificity, positive predictive value, and negative predictive value were calculated for each marker. Multivariate logistic regression analyses were used to identify independent predictors of SAP and mortality.The area under the curve (AUC) for the BISAP score was classified as fair for predicting SAP. The neutrophil-to-lymphocyte ratio at 48 hours (NLR48 h) and the C-reactive protein level at 48 hours (CRP48 h) had the best AUCs and were independently associated with SAP. When both criteria were met, the AUC was 0.89, sensitivity was 68%, and specificity was 92%. CRP48 h and hematocrit at 48 hours were independently associated with mortality.NLR48 h and CRP48 h were independently associated with SAP but not superior to the BISAP score at admission. Assessing NLR48 h and CRP48H together was most suitable for predicting SAP. The CRP level was a good predictive marker for mortality.

A nomogram to predict in-hospital mortality for post-gastrointestinal resection surgery patients in intensive care units: A retrospective cohort study

BACKGROUND

The global volume of gastrointestinal surgery has increased steadily. However, there is still a lack of studies focused on the risk factors for post-gastrointestinal resection surgery patients in the intensive care units.

METHODS

Post gastrointestinal resection surgery patient data were collected from the Medical Information Mart for Intensive Care (MIMIC-III) database and divided into training set and validation set, then analyzed by Univariate and multiple logistic regression.

RESULTS

795 patients were finally enrolled in our cohort. Multiple logistic regression showed that age (1.029 [1.006-1.053]), temperature (0.337 [0.207-0.547]), respiratory rate (1.133 [1.053-1.218]), mean arterial pressure (1.204 [1.039-1.396]), lactate (1.288 [1.112-1.493]), BUN (1.025 [1.010-1.040]) and vasopressor use (4.777 [2.499-9.130]) were independent factors associated with in-hospital mortality. Our new predicted nomogram achieved a better accuracy than SOFA score, SAPS-Ⅱ score, APACHE-Ⅲ score, and Elixhauser score.

CONCLUSION

Our nomogram model could well predict in-hospital mortality for post-GI resection surgery patients receiving intensive care.

Prediction of 72-hour mortality in patients with extremely high serum C-reactive protein levels using a novel weighted average of risk scores

The risk factors associated with mortality in patients with extremely high serum C-reactive protein (CRP) levels are controversial. In this retrospective single-center cross-sectional study, the clinical and laboratory data of patients with CRP levels ≥40 mg/dL treated in Saitama Medical Center, Japan from 2004 to 2017 were retrieved from medical records. The primary outcome was defined as 72-hour mortality after the final CRP test. Forty-four mortal cases were identified from the 275 enrolled cases. Multivariate logistic regression analysis (MLRA) was performed to explore the parameters relevant for predicting mortality. As an alternative method of prediction, we devised a novel risk predictor, “weighted average of risk scores” (WARS). WARS features the following: (1) selection of candidate risk variables for 72-hour mortality by univariate analyses, (2) determination of C-statistics and cutoff value for each variable in predicting mortality, (3) 0–1 scoring of each risk variable at the cutoff value, and (4) calculation of WARS by weighted addition of the scores with weights assigned according to the C-statistic of each variable. MLRA revealed four risk variables associated with 72-hour mortality—age, albumin, inorganic phosphate, and cardiovascular disease—with a predictability of 0.829 in C-statistics. However, validation by repeated resampling of the 275 records showed that a set of predictive variables selected by MLRA fluctuated occasionally because of the presence of closely associated risk variables and missing data regarding some variables. WARS attained a comparable level of predictability (0.837) by combining the scores for 10 risk variables, including age, albumin, electrolytes, urea, lactate dehydrogenase, and fibrinogen. Several mutually related risk variables are relevant in predicting 72-hour mortality in patients with extremely high CRP levels. Compared to conventional MLRA, WARS exhibited a favorable performance with flexible coverage of many risk variables while allowing for missing data.

Efficacy of blood urea nitrogen and the neutrophil-to-lymphocyte ratio as predictors of mortality among elderly patients with genitourinary tract infections: A retrospective multicentre study

OBJECTIVES

To investigate whether initial blood urea nitrogen (BUN) and the neutrophil-to-lymphocyte ratio (NLR) in the emergency department (ED) are associated with mortality in elderly patients with genitourinary tract infections.

METHODS

A total of 541 patients with genitourinary tract infections in 5 EDs between November 2016 and February 2017 were included and retrospectively reviewed. We assessed age, sex, comorbidities, vital signs, and initial laboratory results, including BUN, NLR and the SOFA criteria. The primary outcome was all-cause in-hospital mortality.

RESULTS

The nonsurvivor group included 32 (5.9%) elderly patients, and the mean arterial pressure (MAP), NLR and BUN were significantly higher in this group than in the survivor group (p < 0.001, p = 0.003, p < 0.001). In multivariate analysis, MAP <70 mmHg, NLR ≥23.8 and BUN >28 mg/dl were shown to be independent risk factors for in-hospital mortality (OR 3.62, OR 2.51, OR 2.76: p = 0.002, p = 0.033, p = 0.038, respectively). Additionally, NLR ≥23.8 and BUN >28 were shown to be independent risk factors for mortality in admitted elderly with complicated UTI (p = 0.030, p = 0.035). When BUN and NLR were combined with MAP, the area under the ROC curve (AUROC) value was 0.807 (0.771-0.839) for the prediction of mortality, the sensitivity was 87.5% (95% CI 71.0-96.5), and the specificity was 61.3% (95% CI 56.9-65.5%).

CONCLUSION

The initial BUN and NLR values with the MAP were good predictors associated with all-cause in-hospital mortality among elderly genitourinary tract infections visiting the ED.

Commonly used clinical chemistry tests as mortality predictors: Results from two large cohort studies

Background

The normal ranges for clinical chemistry tests are usually defined by cut-offs given by the distribution in healthy individuals. This approach does however not indicate if individuals outside the normal range are more prone to disease.

Methods

We studied the associations and risk prediction of 11 plasma and serum biomarkers with all-cause mortality in two population-based cohorts: a Swedish cohort (X69) initiated in 1969, and the UK Biobank (UKB) initiated in 2006–2010, with up to 48- and 9-years follow-up, respectively.

Results

In X69 and in UKB, 18,529 and 425,264 individuals were investigated, respectively. During the follow-up time, 14,475 deaths occurred in X69 and 17,116 in UKB. All evaluated tests were associated with mortality in X69 (P<0.0001, except bilirubin P<0.005). For calcium, blood urea nitrogen, bilirubin, hematocrit, uric acid, and iron, U-shaped associations were seen (P<0.0001). For leukocyte count, gamma-glutamyl transferase, alkaline phosphatases and lactate dehydrogenase, linear positive associations were seen, while for albumin the association was negative. Similar associations were seen in UKB. Addition of all biomarkers to a model with classical risk factors improved mortality prediction (delta C-statistics: +0.009 in X69 and +0.023 in UKB, P<0.00001 in both cohorts).

Conclusions

Commonly used clinical chemistry tests were associated with all-cause mortality both in the medium- and long-term perspective, and improved mortality prediction beyond classical risk factors. Since both linear and U-shaped relationships were found, we propose to define the normal range of a clinical chemistry test based on its association with mortality, rather than from the distribution.

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

INTRODUCTION

In this study, we aimed to evaluate the first measured blood urea nitrogen (BUN)/albumin ratio in the emergency department (ED) as a predictor of in-hospital mortality in older ED patients.

METHODS

This retrospective observational study was conducted at a university hospital ED. Consecutive patients aged 65 and over who visited the ED in a three-month period were included in the study. The BUN, albumin, creatinine, and estimated glomerular filtration rate (eGFR) of patients were recorded. The primary end point of the study was in-hospital mortality.

RESULTS

A total of 1253 patients were included in the statistical analyses of the study. Non-survivors had increased BUN levels (32.9 (23.3-55.4) vs. 20.2 (15.4-28.3) mg/dL, p < 0.001), decreased albumin levels (3.27 (2.74-3.75) vs. 3.96 (3.52-4.25) g/dL, p < 0.001), and increased BUN/albumin ratios (10.19 (6.56-18.94) vs. 5.21 (3.88-7.72) mg/g, p < 0.001) compared to survivors. An increased BUN/albumin ratio was a powerful predictor of in-hospital mortality with an area under the curve of 0.793 (95% CI: 0.753-0.833). Malignancy (OR: 2.39; 95% CI: 1.59-3.74, p < 0.001), albumin level < 3.5 g/dL (OR: 2.75; 95% CI: 1.74-4.36, p < 0.001), and BUN/albumin ratio > 6.25 (OR: 2.82; 95% CI: 1.22-6.50, p < 0.015) were found to be independent predictors of in-hospital mortality in older ED patients.

CONCLUSION

According to our findings, older patients with a BUN level > 23 mg/dL, an albumin level < 3.5 g/dL, and a BUN/albumin ratio > 6.25 mg/g in the ED have a higher risk of in-hospital mortality. Additionally, the BUN/albumin ratio is a more powerful independent predictor of in-hospital mortality than the BUN level, albumin level, creatinine level, and eGFR in older ED patients.