Two novel nomograms predict 30-day mortality after off-pump coronary artery bypass grafting.

Background: With the development of surgical techniques and medical equipment, the mortality rate of off-pump coronary artery bypass grafting (CABG) has been declining year by year, but there is a lack of convenient and accurate predictive models. This study aims to use two nomograms to predict 30-day mortality after off-pump CABG. Methods: Patients with isolated off-pump CABG from January 2016 to January 2021 were consecutively enrolled. Potential predictive factors were first screened by lasso regression, and then predictive models were constructed by multivariate logistic regression. To earlier identify high-risk patients, two nomograms were constructed for predicting mortality risk before and after surgery. Results: A total of 1840 patients met the inclusion and exclusion criteria. The 30-day mortality was 3.97 % (73/1840) in this cohort. Multivariate logistic analysis showed that age, BMI<18.5 kg/m2, surgical time, creatinine, LVEF, history of previous stroke, and major adverse intraoperative events (including conversion to cardiopulmonary bypass or implantation of intra-aortic balloon pump) were independently associated with 30-day mortality. Model 1 contained preoperative and intraoperative variables, and the AUC was 0.836 (p < 0.001). The AUC of the K-fold validation was 0.819. Model 2 was only constructed by preoperative information. The AUC was 0.745 (p < 0.001). The AUC of the K-fold validation was 0.729. The predictive power of Model 1 was significantly higher than the SinoScore (DeLong's test p < 0.001). Conclusions: The two novel nomograms could be conveniently and accurately used to predict the risk of 30-day mortality after isolated off-pump CABG.

Building a nomogram plot based on the nanopore targeted sequencing for predicting urinary tract pathogens and differentiating from colonizing bacteria.

Background: The identification of uropathogens (UPBs) and urinary tract colonizing bacteria (UCB) conduces to guide the antimicrobial therapy to reduce resistant bacterial strains and study urinary microbiota. This study established a nomogram based on the nanopore-targeted sequencing (NTS) and other infectious risk factors to distinguish UPB from UCB. Methods: Basic information, medical history, and multiple urine test results were continuously collected and analyzed by least absolute shrinkage and selection operator (LASSO) regression, and multivariate logistic regression was used to determine the independent predictors and construct nomogram. Receiver operating characteristics, area under the curve, decision curve analysis, and calibration curves were used to evaluate the performance of the nomogram. Results: In this study, the UPB detected by NTS accounted for 74.1% (401/541) of all urinary tract microorganisms. The distribution of ln(reads) between UPB and UCB groups showed significant difference (OR = 1.39; 95% CI, 1.246-1.551, p < 0.001); the reads number in NTS reports could be used for the preliminary determination of UPB (AUC=0.668) with corresponding cutoff values being 7.042. Regression analysis was performed to determine independent predictors and construct a nomogram, with variables ranked by importance as ln(reads) and the number of microbial species in the urinary tract of NTS, urine culture, age, urological neoplasms, nitrite, and glycosuria. The calibration curve showed an agreement between the predicted and observed probabilities of the nomogram. The decision curve analysis represented that the nomogram would benefit clinical interventions. The performance of nomogram with ln(reads) (AUC = 0.767; 95% CI, 0.726-0.807) was significantly better (Z = 2.304, p-value = 0.021) than that without ln(reads) (AUC = 0.727; 95% CI, 0.681-0.772). The rate of UPB identification of nomogram was significantly higher than that of ln(reads) only (χ2 = 7.36, p-value = 0.009). Conclusions: NTS is conducive to distinguish uropathogens from colonizing bacteria, and the nomogram based on NTS and multiple independent predictors has better prediction performance of uropathogens.

Effects of Recombinant Human Brain Natriuretic Peptide on Atrial Fibrillation After Coronary Artery Bypass Grafting.

ABSTRACT: Previous studies reported that the use of natriuretic peptides (NPs) can effectively decrease arrhythmias. However, there is a lack of clinical evidence that recombinant human brain natriuretic peptide (rh-BNP) inhibits postoperative atrial fibrillation (POAF). This cohort aims to assess the effect of rh-BNP on POAF. This study retrospectively reviewed patients who underwent isolated coronary artery bypass grafting from January 2018 to January 2021. Patients were divided into 2 groups according to whether they received rh-BNP therapy within 5 days after surgery. A total of 1153 patients met the inclusion and exclusion criteria, of which 54 received rh-BNP therapy within 5 days. After propensity score matching, 53 patients were treated with rh-BNP, and 148 patients were not treated with rh-BNP. The incidence of POAF was lower in rh-BNP group than non-rh-BNP group (18.9% vs. 37.2%, odds ratio = 0.393, 95% confidence interval, 0.183-0.845, P = 0.017). There was no significant difference in the occurrence of ventricular arrhythmia ( P = 0.4), hypotension ( P = 0.763), and the risk of death ( P = 0.14). rh-BNP could significantly reduce the occurrence of POAF after coronary artery bypass grafting, and rh-BNP did not increase the risk of ventricular arrhythmia, hypotension, and death. Accordingly, rh-BNP could be a potential safe medicine for preventing POAF.

Effect of recombinant human brain natriuretic peptide on acute kidney injury after coronary artery bypass grafting: a retrospective comparative cohort study.

Background: Acute kidney injury (AKI) is a common complication of coronary artery bypass grafting (CABG) that results in worse prognosis. Studies have shown that recombinant human brain natriuretic peptide (rh-BNP) reduces renal injury. However, its treatment effects for AKI in patients underwent cardiac surgery are unclear. This study sought to explore the efficacy of rh-BNP in patients with AKI after bypass surgery. Methods: This study included patients with AKI diagnosed within 4 days after CABG during the period January 2016 to December 2020. AKI was defined according to the Kidney Disease Improving Global Outcomes (KDIGO) criteria. The clinical characteristics and outcomes were collected. Patients were divided into BNP and non-BNP groups according to whether rh-BNP was injected intravenously after the operation. Multivariable logistic regression was adjusted the confounding effects between clinical characteristics and rh-BNP. Propensity score matching (PSM) was used to perform a sensitivity analysis. Results: A total of 395 patients, including 56 and 339 patients in the BNP and non-BNP groups, respectively, were included in this study. The decreasing trend of postoperative serum creatinine levels (P<0.001) and postoperative urine volume (P=0.001) within 4 days of surgery were independent associated with rh-BNP. From PSM, 175 patients, including 44 and 131 patients in the BNP and non-BNP groups, respectively, were included in this study. The decreasing trend of postoperative serum creatinine levels in the BNP group was significantly stronger than that in the non-BNP group (0.04±0.28 vs. -0.16±0.36, P=0.001). The postoperative urine volume within 4 days of surgery of the BNP group was higher than that of the non-BNP group (11.3±2.8 vs. 9.11±2.66, P<0.001). The cumulative dosage of diuretics after the procedure did not differ between the BNP and non-BNP groups {60 [40, 80] vs. 60 [40, 120], P=0.852}. Conclusions: Rh-BNP can reduce creatinine levels and increases postoperative urine volume to improve renal function in patients.

Nomogram predicts atrial fibrillation after coronary artery bypass grafting.

OBJECTIVE: Using the nomogram to intuitively predict atrial fibrillation after coronary artery bypass grafting. Identify high-risk patients with atrial fibrillation and provide preoperative protective therapy. METHODS: A total of 397 patients that underwent coronary artery bypass grafting were consecutively enrolled. Independent predictors of patients were analyzed by multivariate logistic regression. Two nomograms were constructed to predict postoperative atrial fibrillation. RESULTS: The incidence of postoperative atrial fibrillation in this study was 29% (115/397). Multivariate Logistic showed that Age, Operative Time > 4 h, Left Atrial Diameter > 40 mm, Mean Arterial Pressure, Body Mass Index > 23 kg/m2, Insulins, and Statins were independently associated with atrial fibrillation after isolated coronary artery bypass grafting. The nomogram of postoperative atrial fibrillation in patients was constructed using total predictor variables (AUC = 0.727, 95% CI 0.673-0.781). The model was internally validated (AUC = 0.701) by K-fold Cross-validation resampling (K = 5, Times = 400). To make an early intervention, the intraoperative information of the patients was excluded. Only 6 variables before surgery were used to establish the brief nomogram to predict postoperative atrial fibrillation (AUC = 0.707, 95% CI 0.651-0.764). The brief model was internally validated (AUC = 0.683) by resampling with K-fold Cross-validation resampling. CONCLUSIONS: These two nomograms could be used to predict patients at high risk for atrial fibrillation after isolated coronary artery bypass grafting.

The Effect of Preoperative and Postoperative Glycemic Control on Acute Kidney Injury After Off-Pump Coronary Artery Bypass Grafting: A Case-Control Study.

BACKGROUND: Acute kidney injury (AKI) is a common complication after cardiac surgery. It is closely related to poor perioperative glycemic control. We aimed to explore the relationship between preoperative hemoglobin A1c (HbA1c) levels and cumulative postoperative insulin usage and AKI after off-pump coronary artery bypass grafting (OPCABG). METHOD: The included a total of 284 patients undergoing isolated OPCABG from 2018 to 2020. According to KDIGO's diagnostic criteria, patients were divided into the AKI group and the non-AKI group. Methods included ① increase in SCr by ≥0.3 mg/dl (≥26.5 µmol/l) within 48 hours; ② increase in SCr to ≥1.5 times baseline, which is known or presumed to have occurred within the prior 7 days; ③ urine volume <0.5 ml/kg/hour for 6 hours. RESULTS: Fifty-one patients (17.9%) had postoperative AKI. HbA1c levels (non-AKI group 6.1 (5.8, 7.1) vs. the AKI group 7.1 (5.9, 8.6) (P = 0.014, cut-off=7.2, AUC=0.61, sensitivity 49%, specificity 76.4%) and postoperative insulin usage (non-AKI group 16.0 (4.0, 36.0) vs. the AKI group 56.0 (11.0, 132.0), P < 0.001, cut-off=39.5, AUC=0.673, sensitivity 60.8%, specificity 76.8%) were different between the two groups. Multivariate logistic regression analysis showed that HbA1c > 7.2% (OR=2.869, P = 0.04) and postoperative insulin usage > 39.5 U (OR=7.548, P < 0.001) were independently associated with AKI. CONCLUSIONS: HbA1c levels and cumulative postoperative insulin usage could be used as independent predictors for AKI after OPCABG. Postoperative insulin usage is more predictive than preoperative HbA1c levels.

The estimation of bloodstain age utilizing circRNAs and mRNAs biomarkers.

Determining the time since deposition (TsD) of bloodstains can provide forensic investigators with additional clues, as it can corroborate eyewitness accounts, limit the number of suspects, and help confirm alibis. Bloodstains are the most common bodily fluid stains at crime scenes. In this study, we examined the relative expression levels (REs) of circRNAs and mRNAs data in bloodstains over ten time points by Real-time quantitative polymerase chain reaction (qPCR), to determine the utility of the relative expression levels of RNA markers for TsD estimation. Forensic samples more than just appear in indoor settings, we also evaluated the use of RNA degradation rate to indicate the age of bloodstains in different environments including indoor and outdoor conditions. The expression levels of six blood-specific mRNA markers (GYPA, CD93, ALAS2, SPTB, HBB, HBA), three highly expressed circRNAs in human peripheral blood (hsa_circ_0001445, hsa_circ_0000972, hsa_circ_0000095) and three reference genes (18 S, ACTB and U6) were analyzed across numerous ageing time points. Analysis of the degradation rates of individual RNAs under indoor and outdoor conditions showed that they exhibited a unique degradation profile during the four-month storage interval, with both circRNAs and mRNAs linearly showing continuous degradation, while U6 is more stable than other reference gene markers. In the current study, we firstly used circRNAs as additional novel biomarkers for bloodstain age estimation, and at the same time proved that different environments had a significant impact on the REs of certain blood biomarkers, and sex differences did not affect the age estimation of bloodstains. The REs of the selected RNA molecules in this study showed a non-linear relationship with bloodstain age and the mathematical formula for estimating the bloodstain age based on the relative expression levels of hsa_circ_0001445, ALAS2 and HBB can be used to estimate the TsD of bloodstains from the REs of bloodstains of unknown age, which represent a potentially effective approach to looking for time-dependent changes and TsD estimation.

The Impact of Serum Uric Acid on Postoperative Atrial Fibrillation in Coronary Artery Bypass Graft.

BACKGROUND: Postoperative atrial fibrillation (POAF) after cardiac surgery is a common complication. We aimed to investigate the impact of serum uric acid level (UA) on the POAF of patients undergoing coronary artery bypass grafting (CABG). METHODS: A retrospective cohort study of patients undergoing CABG at the Hospital between January 2019 and December 2019 was performed. Hyperuricemia (HUA) was defined as serum UA levels >420 µmol/l in men and>360 µmol/l in women. The included patients were divided into the HUA group (103) and the normal UA group (306) based on serum uric acid levels before surgery. POAF was defined as atrial fibrillation that occurred within 7 days of cardiac surgery. We use COX regression analysis and Kaplan-Meier curves (log-rank test) for statistical analysis. RESULTS: The incidence of HUA was 25.2% (103/409). The rate of POAF was 28.61%. Univariate COX regression analysis showed the risk of POAF occurrence. It was revealed that UA was an independent predictor of POAF (HR=1.493, 95% CI1.007-2.212, P = 0.046). Kaplan-Meier curves showed that high serum UA was associated with the occurrence of POAF (P = 0.034). Moreover, age (HR=1.05, 95%CI 1.024-1.076, P < 0.001), AD (HR=1.567, 95%CI .015-2.42, P = 0.043), and CCB (HR=0.647, 95%CI 0.424-0.988, P = 0.044) also were independent predictors of POAF. CONCLUSIONS: Preoperative UA level was significantly associated with POAF. Higher serum UA was an independent risk factor for POAF.

Circular RNA as a Potential Biomarker for Forensic Age Prediction.

In forensic science, accurate estimation of the age of a victim or suspect can facilitate the investigators to narrow a search and aid in solving a crime. Aging is a complex process associated with various molecular regulations on DNA or RNA levels. Recent studies have shown that circular RNAs (circRNAs) upregulate globally during aging in multiple organisms such as mice and C.elegans because of their ability to resist degradation by exoribonucleases. In the current study, we attempted to investigate circRNAs' potential capability of age prediction. Here, we identified more than 40,000 circRNAs in the blood of thirteen Chinese unrelated healthy individuals with ages of 20-62 years according to their circRNA-seq profiles. Three methods were applied to select age-related circRNA candidates including the false discovery rate, lasso regression, and support vector machine. The analysis uncovered a strong bias for circRNA upregulation during aging in human blood. A total of 28 circRNAs were chosen for further validation in 30 healthy unrelated subjects by RT-qPCR, and finally, 5 age-related circRNAs were chosen for final age prediction models using 100 samples of 19-73 years old. Several different algorithms including multivariate linear regression (MLR), regression tree, bagging regression, random forest regression (RFR), and support vector regression (SVR) were compared based on root mean square error (RMSE) and mean average error (MAE) values. Among five modeling methods, regression tree and RFR performed better than the others with MAE values of 8.767 years (S.rho = 0.6983) and 9.126 years (S.rho = 0.660), respectively. Sex effect analysis showed age prediction models significantly yielded smaller prediction MAE values for males than females (MAE = 6.133 years for males, while 10.923 years for females in the regression tree model). In the current study, we first used circRNAs as additional novel age-related biomarkers for developing forensic age estimation models. We propose that the use of circRNAs to obtain additional clues for forensic investigations and serve as aging indicators for age prediction would become a promising field of interest.