Postoperative Blood Urea Nitrogen Is Associated With Stroke in Cardiac Surgical Patients

Increased brain fractional perfusion in obesity using intravoxel incoherent motion (IVIM) MRI metrics

OBJECTIVE

This research seeks to shed light on the associations between brain perfusion, cognitive function, and mental health in individuals with and without obesity.

METHODS

In this study, we employed the noninvasive intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) technique to examine brain fractional perfusion (FP) in two groups: individuals with obesity (N = 72) and healthy controls (N = 66). Additionally, we investigated potential associations between FP, cognitive function, and depressive symptoms in the participants with and without obesity. Finally, artificial intelligence algorithms (Boruta analysis) were also used.

RESULTS

Participants with obesity exhibited increased FP within dopaminergic brain circuits, particularly involving prefrontal cortex areas, anterior and posterior sections of the cingulate cortex, the right striatum, and the midbrain. Additionally, these individuals demonstrated lower working memory and higher depressive symptoms compared to the control group. Notably, higher FP in the inferior temporal and occipital cortices correlated with greater depressive symptoms, whereas increased FP in the right ventral caudate and the midbrain was associated with better working memory performance. A link between inflammatory and metabolic variables, with a particular emphasis on monocytes, and FP in obesity was also evidenced by Boruta analysis.

CONCLUSIONS

Increased brain perfusion in individuals with obesity is associated with cognitive function and mental health through interaction with metabolic and inflammatory factors.

Machine learning-based models for prediction of the risk of stroke in coronary artery disease patients receiving coronary revascularization

BACKGROUND

To construct several prediction models for the risk of stroke in coronary artery disease (CAD) patients receiving coronary revascularization based on machine learning methods.

METHODS

In total, 5757 CAD patients receiving coronary revascularization admitted to ICU in Medical Information Mart for Intensive Care IV (MIMIC-IV) were included in this cohort study. All the data were randomly split into the training set (n = 4029) and testing set (n = 1728) at 7:3. Pearson correlation analysis and least absolute shrinkage and selection operator (LASSO) regression model were applied for feature screening. Variables with Pearson correlation coefficient<9 were included, and the regression coefficients were set to 0. Features more closely related to the outcome were selected from the 10-fold cross-validation, and features with non-0 Coefficent were retained and included in the final model. The predictive values of the models were evaluated by sensitivity, specificity, area under the curve (AUC), accuracy, and 95% confidence interval (CI).

RESULTS

The Catboost model presented the best predictive performance with the AUC of 0.831 (95%CI: 0.811-0.851) in the training set, and 0.760 (95%CI: 0.722-0.798) in the testing set. The AUC of the logistic regression model was 0.789 (95%CI: 0.764-0.814) in the training set and 0.731 (95%CI: 0.686-0.776) in the testing set. The results of Delong test revealed that the predictive value of the Catboost model was significantly higher than the logistic regression model (P<0.05). Charlson Comorbidity Index (CCI) was the most important variable associated with the risk of stroke in CAD patients receiving coronary revascularization.

CONCLUSION

The Catboost model was the optimal model for predicting the risk of stroke in CAD patients receiving coronary revascularization, which might provide a tool to quickly identify CAD patients who were at high risk of postoperative stroke.

Relationship between blood urea nitrogen to serum albumin ratio and short-term mortality among patients from the surgical intensive care unit: a population-based real-world study

BACKGROUND

Patients admitted to the surgical intensive care unit (SICU) often suffer from multi-organ dysfunction and have a high mortality rate. Therefore, finding a simple but effective clinical indicator to predict the prognosis of patients is essential to improve their survival. The aim of this study was to investigate the relationship between blood urea nitrogen to serum albumin ratio (B/A) and short-term mortality among patients from the SICU.

METHODS

All eligible adult patients admitted to the SICU from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database were recruited for this study. Participants were divided into a death group (n = 638) and a survival group (n = 2,048) based on the 90-day prognosis, and then grouped by B/A quartiles. We used restricted cubic splines (RCS) to visually analyze the correlation of B/A with 30- and 90-day risk of death. Cumulative survival rates were estimated using Kaplan-Meier survival curves according to B/A quartiles and evaluated using the log-rank test. Cox proportional risk models were developed and sensitivity analyses were performed to explore whether B/A was independently associated with short-term outcomes in SICU patients. Receiver operating characteristic (ROC) curves were analyzed to ascertain the value of B/A for prognosticating 90-day outcome.

RESULTS

A total of 2686 participants were included in the final study, and their 30-day and 90-day all-cause mortality rates were 17.61% and 23.75%, respectively. The differences in 30-day and 90-day mortality rates were statistically significant among the four groups of patients (all p < 0.001). RCS curves showed that B/A was linearly associated with the risk of 30-day and 90-day all-cause mortality in SICU patients (χ2 = 0.960, p = 0.811; χ2 = 1.940, p = 0.584). Kaplan-Meier analysis showed that the 90-day cumulative survival rate gradually decreased as B/A increased, with patients in the highest quartile of B/A having the lowest survival rate (p < 0.001). Cox regression indicated that elevated B/A (> 9.69) was an independent risk factor for 30-day and 90-day all-cause mortality in SICU patients. The analysis of ROC curves demonstrated that B/A exhibited a significant predictive ability for 90-day mortality, with an optimal threshold of 6.587, a sensitivity of 56.9%, and a specificity of 64.8%.

CONCLUSIONS

Elevated B/A (> 9.69) on admission was an independent risk factor for short-term mortality in SICU patients, and clinicians should pay more attention to this group of patients and intervene clinically at an early stage to reduce mortality.

Searching for Metabolic Markers of Stroke in Human Plasma via NMR Analysis

More than 12 million people around the world suffer a stroke every year, one every 3 s. Stroke has a variety of causes and is often the result of a complex interaction of risk factors related to age, genetics, gender, lifestyle, and some cardiovascular and metabolic diseases. Despite this evidence, it is not possible to prevent the onset of stroke. The use of innovative methods for metabolite analysis has been explored in the last years to detect new stroke biomarkers. We use NMR spectroscopy to identify small molecule variations between different stages of stroke risk. The Framingham Stroke Risk Score was used in people over 63 years of age living in long-term care facilities (LTCF) to calculate the probability of suffering a stroke. Using this parameter, three study groups were formed: low stroke risk (LSR, control), moderate stroke risk (MSR) and high stroke risk (HSR). Univariate statistical analysis showed seven metabolites with increasing plasma levels across different stroke risk groups, from LSR to HSR: isoleucine, asparagine, formate, creatinine, dimethylsulfone and two unidentified molecules, which we termed "unknown-1" and "unknown-3". These metabolic markers can be used for early detection and to detect increasing stages of stroke risk more efficiently.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

Objective

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

Methods

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

Results

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

Conclusion

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

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

Background

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

Methods

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

Results

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

Conclusion

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

Blood urea nitrogen, blood urea nitrogen to creatinine ratio and incident stroke: The Dongfeng-Tongji cohort

BACKGROUND AND AIMS

It remains unclear whether extreme levels of blood urea nitrogen (BUN) and BUN to creatinine ratio (BUN/Cr) can increase future risk of stroke. We conducted this study to investigate the associations of BUN and BUN/Cr with incident stroke and its subtypes.

METHODS

A total of 26,835 and 26,379 participants with a mean follow-up of 7.9 years were included to investigate the associations of BUN and BUN/Cr with incident stroke, respectively. Cox proportional hazard models were used to evaluate hazard ratios (HRs) and 95% confidence intervals (CIs) for incident stroke and its subtypes.

RESULTS

Compared with participants in the third quintile of BUN, the adjusted HRs (95% CIs) for participants in the lowest quintile were 1.21 (1.04-1.40), 1.41 (1.18-1.68) and 1.36 (0.97-1.91) for total, ischemic and hemorrhagic stroke, respectively; while for those in the highest quintile, the corresponding HRs (95% CIs) were 1.16 (1.01-1.32), 1.30 (1.11-1.53), and 1.24 (0.90-1.71). The associations remained robust when restricting the analyses to participants within clinically normal range of BUN. For BUN/Cr, compared with participants in the third quintile, participants in the lowest quintile had significant higher risks of stroke (HRs [95% CIs] were 1.19 [1.04-1.37], 1.26 [1.07-1.48], and 1.22 [0.90-1.67] for total, ischemic and hemorrhagic stroke).

CONCLUSIONS

Both high and low levels of BUN were associated with higher risks of total and ischemic stroke. Low level of BUN/Cr was associated with excess risks of total and ischemic stroke.

A non-linear ensemble model-based surgical risk calculator for mixed data from multiple surgical fields

BACKGROUND

The misestimation of surgical risk is a serious threat to the lives of patients when implementing surgical risk calculator. Improving the accuracy of postoperative risk prediction has received much attention and many methods have been proposed to cope with this problem in the past decades. However, those linear approaches are inable to capture the non-linear interactions between risk factors, which have been proved to play an important role in the complex physiology of the human body, and thus may attenuate the performance of surgical risk calculators.

METHODS

In this paper, we presented a new surgical risk calculator based on a non-linear ensemble algorithm named Gradient Boosting Decision Tree (GBDT) model, and explored the corresponding pipeline to support it. In order to improve the practicability of our approach, we designed three different modes to deal with different data situations. Meanwhile, considering that one of the obstacles to clinical acceptance of surgical risk calculators was that the model was too complex to be used in practice, we reduced the number of input risk factors according to the importance of them in GBDT. In addition, we also built some baseline models and similar models to compare with our approach.

RESULTS

The data we used was three-year clinical data from Surgical Outcome Monitoring and Improvement Program (SOMIP) launched by the Hospital Authority of Hong Kong. In all experiments our approach shows excellent performance, among which the best result of area under curve (AUC), Hosmer-Lemeshow test ([Formula: see text]) and brier score (BS) can reach 0.902, 7.398 and 0.047 respectively. After feature reduction, the best result of AUC, [Formula: see text] and BS of our approach can still be maintained at 0.894, 7.638 and 0.060, respectively. In addition, we also performed multiple groups of comparative experiments. The results show that our approach has a stable advantage in each evaluation indicator.

CONCLUSIONS

The experimental results demonstrate that NL-SRC can not only improve the accuracy of predicting the surgical risk of patients, but also effectively capture important risk factors and their interactions. Meanwhile, it also has excellent performance on the mixed data from multiple surgical fields.

Blood urea nitrogen is associated with long-term all-cause mortality in stable angina pectoris patients: 8-year follow-up results

Background    Elevation of blood urea nitrogen (BUN) indicates renal dysfunction and is associated with increased mortality in cardiovascular diseases. We investigated the relationship between the BUN concentration measured at hospital admission and the long-term all-cause mortality in patients with stable angina pectoris (SAP).Methods    The mortality rate of 344 patients who underwent coronary angiography (CAG) in our clinic due to SAP was analyzed during a mean follow-up period of 8 yrs.Results    Age (p&lt;0.001), male gender (p=0.020), waist circumference (p=0.007), body-mass index (p=0.002), fasting glucose (p=0.004), BUN (p&lt;0.001), serum creatinine (Cr) (p&lt;0.001), hemoglobin (p=0.015), triglyceride concentrations (p=0.033), and the Gensini score (p&lt;0.001) were related to all-cause mortality as shown by univariate Cox regression analysis. Age (OR 1.056, 95 % CI 1.015-1.100, p=0.008), fasting glucose (OR 1.006, 95 % CI 1.001-1.011, p=0.018), BUN, (OR 1.077, 95 % CI 1.026-1.130, p=0.003), and the Gensini score (OR 2.269, 95 % CI 1.233-4.174, p=0.008) were significantly related with mortality as shown by multivariate Cox regression analysis. According to receiver operating characteristic analysis ofthe sensitivity and specificity of BUN and Cr for predicting mortality, the area under the curve values of BUN and Cr were 0.789 (p&lt;0.001) and 0.652 (p=0.001), respectively. BUN had a stronger relationship with mortality than Cr. A concentration of BUN above 16.1 mg / dl had 90.1 % sensitivity and 60 % specificity for predicting mortality (OR=2.23).Conclusion    In patients who underwent CAG due to SAP, the BUN concentration was associated with all-cause mortality during a mean follow-up period of 8 yrs.

Ensemble machine learning prediction and variable importance analysis of 5-year mortality after cardiac valve and CABG operations

Despite having a similar post-operative complication profile, cardiac valve operations are associated with a higher mortality rate compared to coronary artery bypass grafting (CABG) operations. For long-term mortality, few predictors are known. In this study, we applied an ensemble machine learning (ML) algorithm to 88 routinely collected peri-operative variables to predict 5-year mortality after different types of cardiac operations. The Super Learner algorithm was trained using prospectively collected peri-operative data from 8241 patients who underwent cardiac valve, CABG and combined operations. Model performance and calibration were determined for all models, and variable importance analysis was conducted for all peri-operative parameters. Results showed that the predictive accuracy was the highest for solitary mitral (0.846 [95% CI 0.812–0.880]) and solitary aortic (0.838 [0.813–0.864]) valve operations, confirming that ensemble ML using routine data collected perioperatively can predict 5-year mortality after cardiac operations with high accuracy. Additionally, post-operative urea was identified as a novel and strong predictor of mortality for several types of operation, having a seemingly additive effect to better known risk factors such as age and postoperative creatinine.

Preoperative blood urea nitrogen-to-left ventricular ejection fraction ratio is an independent predictor of long-term major adverse cardiac events in patients undergoing coronary artery bypass grafting surgery

Background

Long-term mortality rate following coronary artery bypass grafting (CABG) procedure is still considered to be high despite advances in surgical techniques and perioperative management. Identifying high-risk patients by using cost-effective and clinically useful parameters is needed.

Methods

Patients who were admitted to our cardiology clinic with the diagnosis of coronary artery disease and underwent CABG between January 2008 and August 2010 were included. Study patients were followed-up for 112.6 ± 17.8 months for major adverse cardiac events (MACE) which were defined as all-cause mortality and new-onset decompensated heart failure (HF).

Results

Patients in MACE (+) group were older (p < 0.001), had higher additive Euroscore (p < 0.001), and lower left ventricular ejection fraction (p < 0.001). Multivariate Cox regression analysis showed that additive Euroscore [odds ratio (OR) = 1.601; 95% confidence interval (CI) = 1.374–1.864; p < 0.001)] and blood urea nitrogen-to-left ventricular ejection fraction ratio (BUNEFr; OR = 1.028; 95% CI = 1.006–1.050; p = 0.011) independently predicted MACE. Receiver operating characteristic curve analysis demonstrated that BUNEFr had an area under curve of 0.794 and BUNEFr >33 had a sensitivity and specificity of 74% and 64%, respectively.

Conclusion

BUNEFr is a clinically useful and cost-effective parameter for the prediction of long-term mortality and new-onset decompensated HF in patients undergoing CABG.

First-trimester blood urea nitrogen and risk of gestational diabetes mellitus

Prior studies indicated that urea increased insulin resistance and higher blood urea nitrogen (BUN) was associated with incident diabetes mellitus. However, it remains unclear whether BUN during the first trimester of pregnancy increases risk of gestational diabetes mellitus (GDM). We aimed to investigate the association between first‐trimester BUN and risk of incident GDM. We conducted a prospective, multicenter cohort study of pregnant women. A total of 13 448 eligible pregnant women with measured first‐trimester BUN levels were included in this analysis. Logistic regression analysis was used to estimate the relationship between BUN and GDM. Discrimination and reclassification for GDM by BUN were analysed. A total of 2973 (22.1%) women developed GDM. Compared with the lowest quartile of BUN, the third and fourth quartiles were associated with increased risk of GDM (adjusted odds ratios 1.21 [95% CI 1.07‐1.37] and 1.50 [95% CI 1.33‐1.69], respectively, P for trend <.001). The addition of BUN to conventional factor model improved discrimination (C statistic 0.2%, P = .003) and reclassification (net reclassification index 14.67%, P < .001; integrated discrimination improvement 0.12%, P < .001) for GDM. In conclusion, higher BUN concentrations during the first trimester of pregnancy were associated with increased risk of GDM, suggesting that BUN could be a potential predictor for GDM.

Performance and validation of R-CHA2DS2VASc score for thromboembolism in patients with hypertrophic cardiomyopathy

OBJECTIVE

To validate the modified R-CHA₂DS₂VASc score as a predictor of thromboembolism in HCM patients.

METHODS

A total of 446 HCM patients were enrolled in our study, thirty-one (6.95%) patients experienced thromboembolic events during the follow-up time of 1786.7 person-years. The association between R-CHA₂DS₂VASc score and risk of thromboembolism was assessed by Cox's proportional hazard analysis. The discriminatory power of R-CHA₂DS₂VASc score for thromboembolism prediction was assessed by Harrell's C-statistic and validated internally by bootstrapping methods. Calibration plot was plotted by observed versus expected probabilities of thromboembolism.

RESULTS

The R-CHA₂DS₂VASc score was well calibrated with 0.84 thromboembolic events per 100 person-years in the predefined low risk (R-CHA₂DS₂VASc score ≤2) group, 1.84 in the low to moderate risk (R-CHA₂DS₂VASc score 3-4) group, 4.67 in the moderate to high risk (R-CHA₂DS₂VASc score 5-7) group, and 17.54 in the high risk (R-CHA₂DS₂VASc score ≥8) group. Hazard ratios for thromboembolism were 2.88 (95%CI: 1.06-7.82, P=0.038) for low to moderate versus low risk group, 5.30 (95%CI: 2.14-13.12, P=0.0003) for moderate to high versus low risk group, and 16.57 5.30 (95%CI: 4.96-55.33, P<0.0001) for high versus low risk group after adjusting left atria size. The Harrell's C statistic was 0.7737 (95% CI: 0.65-0.89) for R-CHA₂DS₂VASc score.

CONCLUSION

The R-CHA₂DS₂VASc score has shown good calibration and discriminative power in the prediction of thromboembolism for HCM patients. It should be considered as a potential decision support tool for HCM patients during clinical practice.