Role of blood urea nitrogen in predicting the post-discharge prognosis in elderly patients with acute decompensated heart failure

Blood Urea Nitrogen to Left Ventricular Ejection Ratio as a Predictor of Short-Term Outcome in Acute Myocardial Infarction Complicated by Cardiogenic Shock

INTRODUCTION

Cardiogenic shock (CS) is the most critical complication after acute myocardial infarction (AMI) with mortality above 50%. Both blood urea nitrogen and left ventricular ejection fraction were important prognostic indicators. We aimed to evaluate the prognostic value of admission blood urea nitrogen to left ventricular ejection fraction ratio (BUNLVEFr) in patients with AMI complicated by CS (AMI-CS).

METHODS

268 consecutive patients with AMI-CS were divided into two groups according to the admission BUNLVEFr cut-off value determined by Youden index. The primary endpoint was 30-day all-cause mortality and the secondary endpoint was the composite events of major adverse cardiovascular events (MACEs). Cox proportional hazard models were performed to analyze the association of BUNLVEFr with the outcome.

RESULTS

The optimal cut-off value of BUNLVEFr is 16.63. The 30-day all-cause mortality and MACEs in patients with BUNLVEFr≥16.63 was significantly higher than in patients with BUNLVEFr<16.63 (30-day all-cause mortality: 66.2% vs. 17.1%, p < 0.001; 30-day MACEs: 80.0% vs. 48.0%, p < 0.001). After multivariable adjustment, BUNLVEFr≥16.63 remained an independent predictor for higher risk of 30-day all-cause mortality (HR = 3.553, 95% CI: 2.125-5.941, p < 0.001) and MACEs (HR = 2.026, 95% CI: 1.456-2.820, p < 0.001). Subgroup analyses found that the effect of BUNLVEFr was consistent in different subgroups (all p-interaction>0.05).

CONCLUSION

The admission BUNLVEFr provided important prognostic information for AMI-CS patients.

A Framework for an Effective Healthy Longevity Clinic

In the context of an aging global population and the imperative for innovative healthcare solutions, the concept of longevity clinics emerges as a timely and vital area of exploration. Unlike traditional medical facilities, longevity clinics offer a unique approach to preclinical prevention, focusing on "prevention of prevention" through the utilization of aging clocks and biomarkers from healthy individuals. This article presents a comprehensive overview of longevity clinics, encompassing descriptions of existing models, the development of a proposed framework, and insights into biomarkers, wearable devices, and therapeutic interventions. Additionally, economic justifications for investing in longevity clinics are examined, highlighting the significant growth potential of the global biotechnology market and its alignment with the goals of achieving active longevity. Anchored by an Analytical Center, the proposed framework underscores the importance of data-driven decision-making and innovation in promoting prolonged and enhanced human life. At present, there is no universally accepted standard model for longevity clinics. This absence highlights the need for additional research and ongoing improvements in this field. Through a synthesis of scientific research and practical considerations, this article aims to stimulate further discussion and innovation in the field of longevity clinics, ultimately contributing to the advancement of healthcare practices aimed at extending and enhancing human life.

Association between the red cell distribution width and mortality in elderly patients with non-traumatic coma: An observational cohort study

Elevated red blood cell distribution width (RDW) can be associated with disease severity. However, studies on RDW for the prognosis of elderly patients with non-traumatic coma (NTC) are lacking. This study aims to examine the relationship between RDW and outcomes in elderly patients with NTC. This observational cohort study included elderly patients (aged ≥ 65 years) with NTC between January 2022 and December 2022. We measured RDW upon patient arrival at the emergency department (ED). We conducted a multivariable analysis using logistic regression of relevant covariates to predict in-hospital mortality. Survival curves based on 30-day mortality were designed using the Kaplan-Meier method. The primary outcome was in-hospital mortality, and the secondary outcome was 30-day mortality. A total of 689 patients were included in the study, and in-hospital mortality was 29.6% (n = 204). Our results found that the RDWs of non-survivors were significantly greater than those of survivors (14.6% vs 13.6%). Multivariable analysis showed that RDWs at ED arrival were independently associated with in-hospital mortality (odds ratio, 1.126; 95% confidence interval, 1.047-1.212; P < .001). The Kaplan-Meier curve indicated that the survival probability of patients with a low RDW was greater than those with a high RDW. Having a high RDW at ED arrival was associated with in-hospital mortality in elderly patients with NTC.

A prediction model for prognosis of nephrotic syndrome with tuberculosis in intensive care unit patients: a nomogram based on the MIMIC-IV v2.2 database

Background

Currently, a scarcity of prognostic research exists that concentrates on patients with nephrotic syndrome (NS) who also have tuberculosis. The purpose of this study was to assess the in-hospital mortality status of NS patients with tuberculosis, identify crucial risk factors, and create a sturdy prognostic prediction model that can improve disease evaluation and guide clinical decision-making.

Methods

We utilized the Medical Information Mart for Intensive Care IV version 2.2 (MIMIC-IV v2.2) database to include 1,063 patients with NS complicated by TB infection. Confounding factors included demographics, vital signs, laboratory indicators, and comorbidities. The Least Absolute Shrinkage and Selection Operator (LASSO) regression and the diagnostic experiment the receiver operating characteristic (ROC) curve analyses were used to select determinant variables. A nomogram was established by using a logistic regression model. The performance of the nomogram was tested and validated using the concordance index (C-index) of the ROC curve, calibration curves, internal cross-validation, and clinical decision curve analysis.

Results

The cumulative in-hospital mortality rate for patients with NS and TB was 18.7%. A nomogram was created to predict in-hospital mortality, utilizing Alb, Bun, INR, HR, Abp, Resp., Glu, CVD, Sepsis-3, and AKI stage 7 days. The area under the curve of the receiver operating characteristic evaluation was 0.847 (0.812-0.881), with a calibration curve slope of 1.00 (0.83-1.17) and a mean absolute error of 0.013. The cross-validated C-index was 0.860. The decision curves indicated that the patients benefited from this model when the risk threshold was 0.1 and 0.81.

Conclusion

Our clinical prediction model nomogram demonstrated a good predictive ability for in-hospital mortality among patients with NS combined with TB. Therefore, it can aid clinicians in assessing the condition, judging prognosis, and making clinical decisions for such patients.

The association of blood urea nitrogen to serum albumin ratio with short-term outcomes in Chinese patients with congestive heart failure: A retrospective cohort study

BACKGROUND AND AIMS

Limited evidence exists on the prognostic outcomes of the blood urea nitrogen to serum albumin ratio (B/A ratio) in congestive heart failure (CHF), particularly in developing countries with scarce heart failure epidemiological data. We aimed to investigate the association between B/A ratio and short-term outcomes in Chinese patients with CHF.

METHODS AND RESULTS

We included 1761 CHF patients with available B/A ratio data from a cohort of 2008 patients. Patients were categorized into three groups based on B/A ratio (low to high). The primary endpoint was death or readmission within 28 days, and the secondary endpoint was death or readmission within 90 days. We employed restricted cubic spline analysis, Cox proportional hazards regression, and Kaplan-Meier curves to evaluate the relationship between B/A ratio at admission and the endpoints. Even after adjusting for other variables, higher B/A ratios were associated with increased rates of 28 days and 90 days mortality or readmission (HR: 2.4, 95% CI: 1.81-3.18 and HR: 1.74, 95% CI: 1.48-2.05). Significant differences in the risks of both primary and secondary endpoints were observed among the three B/A ratio groups. The association between B/A ratio and CHF was stable in the different subgroups (all P for interaction＞0.05).

CONCLUSION

Higher B/A ratios are associated with an increased risk of short-term mortality or readmission in Chinese patients with CHF. The B/A ratio shows promise as a prognostic indicator for short-term outcomes in CHF patients.

Prognostic Value of Blood Urea Nitrogen for Short-Term Mortality in Patients with Infective Endocarditis

INTRODUCTION

Blood urea nitrogen (BUN) is a metabolic product validated to be an independent risk factor in the prognosis of several diseases. However, the prognostic value of BUN in patients with infective endocarditis (IE) remains unevaluated.

METHODS

A total of 1371 patients with a diagnosis of IE were included and divided into four groups according to BUN (mmol/L) at admission: < 3.5 (n = 343), 3.5-4.8 (n = 343), 4.8-6.8 (n = 341), and ≥ 6.8 (n = 344). Restricted cubic spline was used to assess the association of BUN with in-hospital mortality. Multivariate analysis was performed to identify the independent risk factors for adverse outcomes.

RESULTS

The in-hospital mortality reached 7.4%, while the 6-month mortality was 9.8%. The restricted cubic spline plot exhibited an approximately linear relationship between BUN and in-hospital mortality. Receiver operating characteristics curve analysis showed that the optimal cut-off of BUN for predicting in-hospital death was 6.8 mmol/L. Kaplan-Meier analysis showed that patients with BUN > 6.8 mmol/L had a higher 6-month mortality than other groups (log rank = 97.9, P < 0.001). Multivariate analysis indicated that BUN > 6.8 mmol/L was an independent predictor indicator for both in-hospital [adjusted odds ratio (aOR) = 2.365, 95% confidence interval (CI) 1.292-4.328, P = 0.005] and 6-month mortality [adjusted hazard ratio (aHR) = 2.171, 95% CI 1.355-3.479, P = 0.001].

CONCLUSIONS

BUN is suitable for independently predicting short-term mortality in patients with IE.

Predictive value of blood urea nitrogen in heart failure: a systematic review and meta-analysis

Background

The mortality rate of patients with heart failure (HF) remains high, and when heart failure occurs, blood urea nitrogen (BUN) is involved in the perfusion of renal blood flow. Some studies have shown an association between heart failure prognosis and blood urea nitrogen, but the results of some other studies were inconsistent. Therefore, we conducted a comprehensive meta-analysis to investigate the value of BUN on the prognosis of patients with heart failure.

Methods

A computerized systematic search of all English literature was performed in four databases, PubMed, Cochrane, Embase and Web of Science, from their inception to May 2022. The data of BUN were classified into continuous and categorical variables after passing the inclusion and exclusion criteria. The BUN data of both types were extracted separately into stata15.0 for statistical analysis.

Results

A total of 19 cohort studies involving 56,003 patients were included. When BUN was used as a categorical variable, the risk of death in heart failure was 2.29 times higher for high levels of BUN than for low levels of BUN (RR = 2.29, 95% CI:1.42-3.70, P < 0.001). The results showed statistical significance in multifactorial and univariate groups, the prospective cohort, and European and Asian groups. When BUN was used as a continuous variable, the risk of death in heart failure was 1.02 times higher for each unit increase in BUN (RR = 1.02, 95% CI:1.01-1.03, p < 0.001). Subgroup analysis showed statistical significance in retrospective cohort, American and Asian.

Conclusion

High BUN is an independent predictor of all-cause mortality in heart failure. Lower BUN was associated with better prognosis in patients with heart failure.

The prognostic utility of GRACE risk score in predictive adverse cardiovascular outcomes in patients with NSTEMI and multivessel disease

BACKGROUND

GRACE risk score models are capable of predicting all-cause mortality of non-ST elevation myocardial infarction (NSTEMI) patients. However, its utility for evaluating major adverse cardiovascular events (MACE) in NSTEMI patients with multivessel disease (MVD) remains unclear.

METHODS AND RESULTS

This study was designed as a retrospective cohort study that recruited patients with NSTEMI and multivessel disease between September 2013 and December 2018 in Daping Hospital, Chongqing, China. The primary outcome was a composite outcome that included all-cause mortality, recurrent angina, non-fatal myocardial infarction, coronary re-vascularization, and non-fatal strokes. Of the 827 patients with NSTEMI, 32 did not complete follow-up and 430 were excluded because of single-vessel disease. The remaining 365 NSTEMI patients with MVD had a median follow-up of 3.0 (IQR 2.6-3.3) years, 78 patients experienced outcomes. The GRACE risk score predicted the MACE (hazard ratio 1.014, 95% CI 1.006-1.021, P < 0.001). The GRACE risk score performed well in predicting all-cause mortality (c-statistic 0.72, 95% CI 0.59-0.85, P = 0.001) in MVD but was less powerful in predicting MACE (c-statistic 0.69, 95% CI 0.62-0.75, P < 0.001). When combining the GRACE risk score with the SYNTAX score, and blood urea nitrogen for predicting all-cause mortality and MACE events, the c-statistic value increased to 0.82 and 0.81 (P < 0.001).

CONCLUSION

In NSTEMI patients with MVD, the GRACE score showed an acceptable predictive value for all-cause mortality, but it was less powerful in predicting MACE. Blood urea nitrogen may be valuable in assessing long-term cardiovascular events in patients with MVD.

Validation and derivation of short-term prognostic risk score in acute decompensated heart failure in China

Background

Few prognostic risk scores (PRSs) have been routinely used in acute decompensated heart failure (ADHF). We, therefore, externally validated three published PRSs (3A3B, AHEAD, and OPTIME-CHF) and derived a new PRS to predict the short-term prognosis in ADHF.

Methods

A total of 4550 patients from the Heb-ADHF registry in China were randomly divided into the derivation and validation cohorts (3:2). Discrimination of each PRS was assessed by the area under the receiver operating characteristic curve (AUROC). Logistic regression was exploited to select the predictors and create the new PRS. The Hosmer–Lemeshow goodness-of-fit test was used to assess the calibration of the new PRS.

Results

The AUROCs of the 3A3B, AHEAD, and OPTIME-CHF score in the derivation cohort were 0.55 (95% CI 0.53–0.57), 0.54 (95% CI 0.53–0.56), and 0.56 (95% CI 0.54–0.57), respectively. After logistic regression analysis, the new PRS computed as 1 × (diastolic blood pressure < 80 mmHg) + 2 × (lymphocyte > 1.11 × 10⁹/L) + 1 × (creatinine > 80 μmol/L) + 2 × (blood urea nitrogen > 21 mg/dL) + 1 × [BNP 500 to < 1500 pg/mL (NT-proBNP 2500 to < 7500 pg/mL)] or 3 × [BNP ≥ 1500 (NT-proBNP ≥ 7500) pg/mL] + 3 × (QRS fraction of electrocardiogram < 55%) + 4 × (ACEI/ARB not used) + 1 × (rhBNP used), with a better AUROC of 0.67 (95% CI 0.64–0.70) and a good calibration (Hosmer–Lemeshow χ² = 3.366, P = 0.186). The results in validation cohort verified these findings.

Conclusions

The short-term prognostic values of 3A3B, AHEAD, and OPTIME-CHF score in ADHF patients were all poor, while the new PRS exhibited potential predictive ability. We demonstrated the QRS fraction of electrocardiogram as a novel predictor for the short-term outcomes of ADHF for the first time. Our findings might help to recognize high-risk ADHF patients.

Coexisting Morbidity Burden in Hospitalized Elderly Patients with New-Onset Heart Failure vs Acutely Decompensated Chronic Heart Failure

Coexisting morbidities (CM) are common in patients with heart failure (HF). This study evaluated the CM burden and its clinical significance in elderly hospitalized patients with new-onset (De-novo) HF (n = 84) and acutely decompensated chronic HF (ADCHF) (n = 122). All had HF symptoms associated with: (a) LVEF <50%, or, (b) left ventricular ejection fraction (LVEF) ≥50% and NT-proBNP ≥300 pg/mL. The primary endpoint was the composite of all-cause death/HF rehospitalization at 6 months. Age was similar between patients with new-onset HF and ADCHF [82 (12.5) vs 80 (11) years, respectively; P = .549]. The CM burden was high in both groups. However, the number of CM [3 (2) vs 4 (1.75)] and the prevalence of multimorbidity [CM ≥2; 65 (77.4%) vs 108 (88.5%)] were lower in new-onset HF ( P = .016 and P = .035, respectively). The survival probability without the primary endpoint was higher in new-onset HF than in ADCHF ( P = .001) driven by less rehospitalizations ( P = .001). In the total study population significant primary endpoint predictors were red blood cell distribution width (RDW), urea, and coronary artery disease (CAD) prevalence (AUC of the model =.7685), whereas significant death predictors were RDW, urea, and the number of CM (AUC = .7859), all higher in ADCHF. Thus, the higher CM burden in ADCHF than in new-onset HF most likely contributed to the worse outcome.

Development and validation of a prediction model for in-hospital mortality of patients with severe thrombocytopenia

Risk stratification and prognosis evaluation of severe thrombocytopenia are essential for clinical treatment and management. Currently, there is currently no reliable predictive model to identify patients at high risk of severe thrombocytopenia. This study aimed to develop and validate a prognostic nomogram model to predict in-hospital mortality in patients with severe thrombocytopenia in the intensive care unit. Patients diagnosed with severe thrombocytopenia (N = 1561) in the Medical Information Mart for Intensive Care IV database were randomly divided into training (70%) and validation (30%) cohorts. In the training cohort, univariate and multivariate logistic regression analyses with positive stepwise selection were performed to screen the candidate variables, and variables with p < 0.05 were included in the nomogram model. The nomogram model was compared with traditional severity assessment tools and included the following 13 variables: age, cerebrovascular disease, malignant cancer, oxygen saturation, heart rate, mean arterial pressure, respiration rate, mechanical ventilation, vasopressor, continuous renal replacement therapy, prothrombin time, partial thromboplastin time, and blood urea nitrogen. The nomogram was well-calibrated. According to the area under the receiver operating characteristics, reclassification improvement, and integrated discrimination improvement, the nomogram model performed better than the traditional sequential organ failure assessment (SOFA) score and simplified acute physiology score II (SAPS II). Additionally, according to decision curve analysis, a threshold probability between 0.1 and 0.75 indicated that our constructed nomogram model showed more net benefits than the SOFA score and SAPS II. The nomogram model we established showed superior predictive performance and can assist in the quantitative assessment of the prognostic risk in patients with severe thrombocytopenia.

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.

Blood Urea Nitrogen for Short-Term Prognosis in Patients with Cardiogenic Shock Complicating Acute Myocardial Infarction

PURPOSE

Cardiogenic shock (CS) is the leading cause of death in patients with acute myocardial infarction (AMI). Our study aimed to evaluate the short-term prognostic value of admission blood urea nitrogen (BUN) in patients with CS complicating AMI.

MATERIALS AND METHODS

218 consecutive patients with CS after AMI were enrolled. The primary endpoint was 30-day mortality. The association of admission BUN and 30-day mortality and major adverse cardiovascular event (MACE) was investigated by Cox regression. The integrated discrimination improvement (IDI) and net reclassification improvement (NRI) further examined the predictive value of BUN.

RESULTS

During a period of 30-day follow-up, 105 deaths occurred. Compared to survivors, nonsurvivors had significantly higher admission BUN (p < 0.001), creatinine (p < 0.001), BUN/creatinine (p = 0.03), and a lower glomerular filtration rate (p < 0.001). The area under the curve (AUC) of the 4 indices for predicting 30-day mortality was 0.781, 0.734, 0.588, and 0.773, respectively. When compared to traditional markers associated with CS, the AUC for predicting 30-day mortality of BUN, lactate, and left ventricular ejection fraction were 0.781, 0.776, and 0.701, respectively. The optimal cut-off value of BUN for predicting 30-day mortality was 8.95 mmol/L with Youden-Index analysis. Multivariate Cox analysis indicated BUN >8.95 mmol/L was an important independent predictor for 30-day mortality (HR 2.08, 95%CI 1.28-3.36, p = 0.003) and 30-day MACE (HR 1.85, 95%CI 1.29-2.66, p = 0.001). IDI (0.053, p = 0.005) and NRI (0.135, p = 0.010) showed an improvement in the accuracy for mortality prediction of the new model when BUN was included compared with the standard model of predictors in previous scores.

CONCLUSION

An admission BUN >8.95 mmol/L was robustly associated with increased short-term mortality and MACE in patients with CS after AMI. The prognostic value of BUN was superior to other renal markers and comparable to traditional markers. This easily accessible index might be promising for early risk stratification in CS patients following AMI.

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.

Factors associated with early improvement after intravenous thrombolytic treatment in acute ischemic stroke

OBJECTIVE

: The aim of this study was to determine the factors associated with early neurological improvement (ENI) in patients who experienced acute ischemic stroke and were treated with intravenous recombinant tissue plasminogen activator (IV rt-PA), and determine the relationship with the outcome at the first control.

METHOD

: This study included 377 patients who were treated with IV rt-PA in Izmir Dokuz Eylül University Hospital between January 2010 and October 2018. ENI was defined as a 4 or more improvement in the National Institutes of Health Stroke Scale (NIHSS) score in the first hour, the twenty-fourth hour and the seventh day when compared to the pretreatment phase. The modified Rankin Scale (mRS) 0-1 score was defined as 'very good outcome'.

RESULTS

: The basal NIHSS (p=0.003, p=0.003, p=0.022) was high in the first hour, twenty-fourth hour, and seventh day ENI groups. Blood urea nitrogen (BUN) level was low in the first- and twenty-fourth-hour ENI groups (p=0.007, p=0.020). Furthermore, admission glucose was low at the twenty-fourth hour and on the seventh day ENI groups (p=0.005, p=0.048). A high infarct volume was observed on magnetic resonance imaging (MRI) at the twenty-fourth hour and on the seventh day non-ENI groups (p= <0.001, p= <0.001).

CONCLUSION

: Management of factors associated with ENI and determination of treatment strategies accordingly are important for obtaining a better clinical outcome. It can help quickly select patients, who, even though they will not respond to rt-PA, may be appropriate candidates for bridging therapy.

Time-to-event prediction analysis of patients with chronic heart failure comorbid with atrial fibrillation: a LightGBM model

Background

Chronic heart failure (CHF) comorbid with atrial fibrillation (AF) is a serious threat to human health and has become a major clinical burden. This prospective cohort study was performed to design a risk stratification system based on the light gradient boosting machine (LightGBM) model to accurately predict the 1- to 3-year all-cause mortality of patients with CHF comorbid with AF.

Methods

Electronic medical records of hospitalized patients with CHF comorbid with AF from January 2014 to April 2019 were collected. The data set was randomly divided into a training set and test set at a 3:1 ratio. In the training set, the synthetic minority over-sampling technique (SMOTE) algorithm and fivefold cross validation were used for LightGBM model training, and the model performance was performed on the test set and compared using the logistic regression method. The survival rate was presented on a Kaplan–Meier curve and compared by a log-rank test, and the hazard ratio was calculated by a Cox proportional hazard model.

Results

Of the included 1796 patients, the 1-, 2-, and 3-year cumulative mortality rates were 7.74%, 10.63%, and 12.43%, respectively. Compared with the logistic regression model, the LightGBM model showed better predictive performance, the area under the receiver operating characteristic curve for 1-, 2-, and 3-year all-cause mortality was 0.718 (95%CI, 0.710–0.727), 0.744(95%CI, 0.737–0.751), and 0.757 (95%CI, 0.751–0.763), respectively. The net reclassification index was 0.062 (95%CI, 0.044–0.079), 0.154 (95%CI, 0.138–0.172), and 0.148 (95%CI, 0.133–0.164), respectively. The differences between the two models were statistically significant (P < 0.05). Patients in the high-risk group had a significantly higher hazard of death than those in the low-risk group (hazard ratios: 12.68, 13.13, 14.82, P < 0.05).

Conclusion

Risk stratification based on the LightGBM model showed better discriminative ability than traditional model in predicting 1- to 3-year all-cause mortality of patients with CHF comorbid with AF. Individual patients’ prognosis could also be obtained, and the subgroup of patients with a higher risk of mortality could be identified. It can help clinicians identify and manage high- and low-risk patients and carry out more targeted intervention measures to realize precision medicine and the optimal allocation of health care resources.

Blood Urea Nitrogen and In-Hospital Mortality in Critically Ill Patients with Cardiogenic Shock: Analysis of the MIMIC-III Database

The association between blood urea nitrogen (BUN) and prognosis has been the focus of recent research. Therefore, the objective of this study was to investigate the association between BUN and hospital mortality in critically ill patients with cardiogenic shock (CS). This was a retrospective cohort study, in which data were obtained from the Medical Information Mart for Intensive Care III V1.4 database. Data from 697 patients with CS were analyzed. Logistic regression and subgroup analyses were used to assess the association between BUN and hospital mortality in patients with CS. The average age of the 697 participants was 71.14 years, and approximately 42.18% were men. In the multivariate logistic regression model, after adjusting for age, sex, diabetes, cardiac arrhythmias, urine output, simplified acute physiology score II, sequential organ failure assessment, creatinine, anion gap, and heart rate, high BUN demonstrated strong associations with increased in-hospital mortality (per standard deviation increase: odds ratio [OR] 1.47, 95% confidence interval [CI] 1.13–1.92). A similar result was observed in BUN tertile groups (BUN 23–37 mg/dL versus 6–22 mg/dL: OR [95% CI], 1.42 [0.86–2.34]; BUN 38–165 mg/dL versus 6–22 mg/dL: OR [95% CI], 1.99 [1.10–3.62]; P trend 0.0272). Subgroup analysis did not reveal any significant interactions among various subgroups, and higher BUN was associated with adverse clinical outcomes in patients with CS.

The Effect of High Lactate Level on Mortality in Acute Heart Failure Patients With Reduced Ejection Fraction Without Cardiogenic Shock

BACKGROUND

We aimed to determine the effect of blood lactate levels on cardiovascular (CV) death and hospitalization for heart failure (HF) in acute HF patients with reduced left ventricular ejection fraction (EF).

METHODS

Eighty-five acute HF patients with reduced ejection fraction were divided into two groups according to admission blood lactate levels. 48 of them had low blood lactate levels (< 2 mmol/l) and 37 of them had high blood lactate levels (≥ 2 mmol/l). Patients with acute coronary syndrome, cardiogenic shock, sepsis and low blood pressure at admission were excluded from the study. Primary endpoint is the composite of cardiovascular (CV) death and hospitalization for heart failure (HHF) in 6-month follow-up. Secondary endpoint is the change in NT-proBNP levels from admission to 72 h.

RESULTS

Baseline characteristics of patients were similar in two groups. On baseline echocardiographic evaluation; patients with high lactate revealed a higher mitral E/A ratio (2.34 [0.43-3.31], p = 0.008) and a lower TAPSE ratio (14 [10-27], p = 0.008) than patients with low lactate levels. Over a median follow-up period of 6 months, the primary end point occurred in 28 (75.7%) of 37 patients assigned to high lactate group and in 20 (41.7%) of 48 patients assigned to low lactate group (p = 0.006). High lactate levels significantly increased the risk of CV death and HHF at 6 months by nearly 5.35-fold in acute HF patients with reduced EF. The change in NT-proBNP levels at 72nd hour after admission were similar between two groups.

CONCLUSION

Higher lactate levels at admission related with higher HHF at 6 months and may be related with higher risk of CV death in acute HF patients with reduced EF.

Urea level is an independent predictor of mortality in patients with severe aortic valve stenosis

Introduction

Severe aortic stenosis (AS) is the most common valvular heart disease in the western world. Various factors are related to severe AS prognosis, including chronic kidney disease. The aim of this study was to evaluate the prognostic value of urea level in patients with severe AS.

Methods

We prospectively enrolled 142 patients (79.1±9.4 years, 88 women) with severe AS (mean valve area 0.67± 0.17 cm²). Clinical assessment, blood tests and echocardiography were performed at enrollment and follow up. The patient population was divided into low and high urea level groups, according to the median urea level at enrollment (72 patients, mean urea 35.5±6.2 mg/dL and 70 patients, mean urea 61.1±17.8 mg/dL, respectively). Hundred and twelve patients (79%) underwent aortic valve intervention. The primary endpoint was all-cause and cardiovascular mortality.

Outcomes

During follow-up of 37±19.5 months, 56 (37.1%) patients died, 39 due to cardiovascular causes. In univariate analysis, age, urea level, creatinine, New York Heart Association (NYHA) class and aortic valve intervention were associated with all-cause mortality. However, in multivariate analysis only aortic valve intervention and blood urea were independent predictors of all-cause mortality (HR 0.494; 95% CI 0.226–0.918, P = 0.026 and HR 1.015; 95% CI 1.003–1.029, P = 0.046 respectively). Urea level, NYHA class and age were also significant predictors of cardiovascular mortality. Whereas, in multivariate analysis, only urea level predicted cardiovascular mortality in these patients (HR 1.017; CI 1.003–1.031 P = 0.019).

Conclusions

Blood urea, a generally readily available and routinely determined marker of renal function, is an independent prognostic factor in patients with severe AS.