Abstract： Objective To evaluate prediction validation of Sino System for Coronary Operative Risk Evaluation （SinoSCORE） on in-hospital mortality in adult heart surgery patients in West China Hospital.?Methods?We included clinical records of 2 088 consecutive adult patients undergoing heart surgery in West China Hospital from January 2010 to May 2012, who were also included in Chinese Adult Cardiac Surgical Registry.We compared the difference of preoperative risk factors for the patients between Chinese Adult Cardiac Surgical Registry and West China Hospital. SinoSCORE was used to predict in-hospital mortality of each patient and to evaluate the discrimination and calibration of SinoSCORE for the patients.?Results?Among the 2 088 patients in West China Hospital, there were 168 patients （8.05%） undergoing coronary artery bypass grafting （CABG）, 1 884 patients （90.23%） undergoing heart valve surgery, and 36 patients （1.72%） undergoing other surgical procedures. There was statistical difference in the risk factors including hyperlipemia, stroke, cardiovascular surgery history, and kidney disease between the two units.The observed in-hospital mortality was 2.25% （47/2 088）. The predicted in-hospital mortality calculated by SinoSCORE was 2.35% （49/2 088） with 95% confidence interval 2.18 to 2.47. SinoSCORE was able to predict in-hospital mortality of the patients with good discrimination （Hosmer Lemeshow test: χ2=3.164, P=0.582） and calibration （area under the receiver operating characteristic curve of 0.751 with 95% confidence interval 0.719 to 0.924）. Conclusion SinoSCORE is an accurate predictor in predicting in-hospital mortality in adult heart surgery patients who are mainly from southwest China
Abstract： Objective To establish a risk prediction model and risk score for inhospital mortality in heart valve surgery patients, in order to promote its perioperative safety. Methods We collected records of 4 032 consecutive patients who underwent aortic valve replacement, mitral valve repair, mitral valve replacement, or aortic and mitral combination procedure in Changhai hospital from January 1,1998 to December 31,2008. Their average age was 45.90±13.60 years and included 1 876 (46.53%) males and 2 156 (53.57%) females. Based on the valve operated on, we divided the patients into three groups including mitral valve surgery group (n=1 910), aortic valve surgery group (n=724), and mitral plus aortic valve surgery group (n=1 398). The population was divided a 60% development sample (n=2 418) and a 40% validation sample (n=1 614). We identified potential risk factors, conducted univariate analysis and multifactor logistic regression to determine the independent risk factors and set up a risk model. The calibration and discrimination of the model were assessed by the HosmerLemeshow (H-L) test and [CM(159mm]the area under the receiver operating characteristic (ROC) curve,respectively. We finally produced a risk score according to the coefficient β and rank of variables in the logistic regression model. Results The general inhospital mortality of the whole group was 4.74% (191/4 032). The results of multifactor logistic regression analysis showed that eight variables including tricuspid valve incompetence with OR=1.33 and 95%CI 1.071 to 1.648, arotic valve stenosis with OR=1.34 and 95%CI 1.082 to 1.659, chronic lung disease with OR=2.11 and 95%CI 1.292 to 3.455, left ventricular ejection fraction with OR=1.55 and 95%CI 1.081 to 2.234, critical preoperative status with OR=2.69 and 95%CI 1.499 to 4.821, NYHA ⅢⅣ (New York Heart Association) with OR=2.75 and 95%CI 1.343 to 5641, concomitant coronary artery bypass graft surgery (CABG) with OR=3.02 and 95%CI 1.405 to 6.483, and serum creatinine just before surgery with OR=4.16 and 95%CI 1.979 to 8.766 were independently correlated with inhospital mortality. Our risk model showed good calibration and discriminative power for all the groups. P values of H-L test were all higher than 0.05 (development sample: χ2=1.615, P=0.830, validation sample: χ2=2.218, P=0.200, mitral valve surgery sample: χ2=5.175,P=0.470, aortic valve surgery sample: χ2=12.708, P=0.090, mitral plus aortic valve surgery sample: χ2=3.875, P=0.380), and the areas under the ROC curve were all larger than 0.70 (development sample: 0.757 with 95%CI 0.712 to 0.802, validation sample: 0.754 and 95%CI 0.701 to 0806; mitral valve surgery sample: 0.760 and 95%CI 0.706 to 0.813, aortic valve surgery sample: 0.803 and 95%CI 0.738 to 0.868, mitral plus aortic valve surgery sample: 0.727 and 95%CI 0.668 to 0.785). The risk score was successfully established: tricuspid valve regurgitation (mild:1 point, moderate: 2 points, severe:3 points), arotic valve stenosis (mild: 1 point, moderate: 2 points, severe: 3 points), chronic lung disease (3 points), left ventricular ejection fraction (40% to 50%: 2 points, 30% to 40%: 4 points, ＜30%: 6 points), critical preoperative status (3 points), NYHA IIIIV (4 points), concomitant CABG (4 points), and serum creatinine (＞110 μmol/L: 5 points).Conclusion Eight risk factors including tricuspid valve regurgitation are independent risk factors associated with inhospital mortality of heart valve surgery patients in China. The established risk model and risk score have good calibration and discrimination in predicting inhospital mortality of heart valve surgery patients.
Objective To investigate predictors for mortality among patients with Stanford type A acute aortic dissection (AAD) and to establish a predictive model to estimate risk of in-hospital mortality. Methods A total of 999 patients with Stanford type A AAD enrolled between 2010 and 2015 in our hospital were included for analysis. There were 745 males and 254 females with a mean age of 49.8±12.0 years. There were 837 patients with acute dissection and 182 patients (18.22%) were preoperatively treated or waiting for surgery in the emergency department and 817 (81.78%) were surgically treated. Multivariable logistic regression analysis was used to investigate predictors of in-hospital mortality. Significant risk factors for in-hospital death were used to develop a prediction model. Results The overall in-hospital mortality was 25.93%. In the multivariable analysis, the following variables were associated with increased in-hospital mortality: increased age (OR=1.04, 95% CI 1.02 to 1.05, P<0.000 1), acute aortic dissection (OR=2.49, 95% CI 1.30 to 4.77, P=0.006 1), syncope (OR=2.76, 95% CI 1.15 to 6.60, P=0.022 8), lower limbs numbness/pain (OR=7.99, 95% CI 2.71 to 23.52, P=0.000 2), type Ⅰ DeBakey dissection (OR=1.72, 95% CI 1.05 to 2.80, P=0.030 5), brachiocephalic vessels involvement (OR=2.25, 95% CI 1.20 to 4.24, P=0.011 7), acute liver insufficiency (OR=2.60, 95% CI 1.46 to 4.64, P=0.001 2), white blood cell count (WBC)>15×109 cells/L (OR=1.87, 95% CI 1.21 to 2.89, P=0.004 9) and massive pericardial effusion (OR=4.34, 95% CI 2.45 to 7.69, P<0.000 1). Based on these multivariable results, a reliable and simple bedside risk prediction tool was developed. Conclusion Different clinical manifestations and imaging features of patients with Stanford type A AAD predict the risk of in-hospital mortality. This model can be used to assist physicians to quickly identify high risk patients and to make reasonable treatment decisions.
Objective To evaluate the significance of lactate dehydrogenase (LDH) as a predictor of in-hospital mortality in patients with acute aortic dissection(AAD). Methods We conducted a retrospective analysis of the clinical data of 445 AAD patients who were admitted to the Second Xiangya Hospital of Central South University and the Changsha Central Hospital from January 2014 to December 2017 within a time interval of ≤14 days from the onset of symptoms to hospital admission, including 353 males and 92 females with the age of 45-61 years. LDH levels were measured on admission and the endpoint was the all-cause mortality during hospitalization. Results During hospitalization, 86 patients died and 359 patients survived. Increased level of LDH was found in non-survivors compared with that in the survived [269.50 (220.57, 362.58) U/L vs. 238.00 (191.25, 289.15) U/L, P<0.001]. A nonlinear relationship between LDH levels and in-hospital mortality was observed. Using multivariable logistic analysis, we found that LDH was an independent predictor of in-hospital mortality in the patients with AAD [OR=1.002, 95% CI (1.001 to 1.014), P=0.006]. Furthermore, using receiver operating characteristic (ROC) analysis, we observed that the best threshold of LDH level was 280.70 U/L, and the area under the curve was 0.624 (95% CI 0.556 to 0.689). Conclusion LDH level on admission is an independent predictor of in-hospital mortality in patients with AAD.
ObjectiveTo explore the clinical application value of antithrombin Ⅲ (ATⅢ) in pulmonary thromboembolism (PTE).MethodsA retrospective study included 204 patients with confirmed PTE who were admitted to Fujian Provincial Hospital from May 2012 to June 2019. The clinical data of the study included basic conditions, morbilities, laboratory examinations and scoring system within 24 hours after admission. The relationship between ATⅢ and PTE in-hospital death was analyzed, and the value of ATⅢ to optimize risk stratification was explored.ResultsFor ATⅢ, the area under receiver operating characteristic curve (AUC) of predicting in-hospital mortality was 0.719, with a cut-off value of 77.7% (sensitivity 64.71%, specificity 80.21%). The patients were divided into ATⅢ≤77.7% group (n=48) and ATⅢ>77.7% group (n=156) according to the cut-off value, and significant statistically differences were found in chronic heart failure, white blood cells count, platelets count, alanine aminotransferase (ALT), albumin and troponin I (P<0.05). According to the in-hospital mortality, patients were divided into a death group (n=17) and a survival group (n=187), and the differences in count of white blood cells, ATⅢ, D-dimer, ALT, albumin, estimated glomerular filtration rate and APACHEⅡ were statistically significant. Logistic regression analysis revealed that ATⅢ≤77.7% and white blood cells count were independent risk factors for in-hospital death. The risk stratification and the risk stratification combined ATⅢ to predict in-hospital death were evaluated by receiver operating characteristic curve, and the AUC was 0.705 and 0.813, respectively (P<0.05). A new scoring model of risk stratification combined with ATⅢ was showed by nomogram.ConclusionsATⅢ≤77.7% is an independent risk factor for in-hospital death, and is beneficial to optimize risk stratification. The mechanism may be related to thrombosis, right ventricular dysfunction and inflammatory response.
ObjectiveTo identify the risk factors for hospital mortality in patients with acute myocardial infarction (AMI) after emergency coronary artery bypass grafting (CABG).MethodsWe retrospectively analyzed the clinical data of 145 AMI patients undergoing emergency CABG surgery in Qingdao Municipal Hospital from 2009 to 2019. There were 108 (74.5%) males and 37 (25.5%) females with a mean age of 67.7±11.5 years. According to whether there was in-hospital death after surgery, the patients were divided into a survival group (132 patients) and a death group (13 patients). Preoperative and operative data were analyzed by univariate analysis, followed by multivariate logistic regression analysis, to identify the risk factors for hospital mortality.ResultsOver all, 13 patients died in the hospital after operation, with a mortality rate of 9.0%. In univariate analysis, significant risk factors for hospital mortality were age≥70 years, recent myocardial infarction, left ventricular ejection fraction (LVEF)<30%, left main stenosis/dissection, operation time and simultaneous surgeries (P<0.05). Multivariate logistic regression analysis showed that LVEF<30% (OR=2.235, 95%CI 1.024-9.411, P=0.014), recent myocardial infarction (OR=4.027, 95%CI 1.934-14.268, P=0.032), operation time (OR=1.039, 95%CI 1.014-1.064, P=0.002) were independent risk factors for hospital mortality after emergency CABG.ConclusionEmergency CABG in patients with AMI has good benefits, but patients with LVEF<30% and recent myocardial infarction have high in-hospital mortality, so the operation time should be shortened as much as possible.
ObjectiveTo explore the association between frailty and in-hospital mortality in older patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD). Methods Elderly patients who were hospitalized with AECOPD from June 2022 to December 2022 at a large tertiary hospital were selected. The independent prognostic factors including frailty status were determined by multivariate logistic regression analysis. Mediation effect analysis was used to evaluate the mediating relationships between C-reactive protein (CRP) and albumin and in-hospital death. ResultsThe training set included 1 356 patients (aged 86.7±6.6), 25.0% of whom were diagnosed with frailty. The multiple logistic regression analysis showed that frailty, mean arterial pressure, Charlson comorbidity index, neutrophil–lymphocyte ratio, interleukin-6, CRP, albumin, and troponin T were associated with in-hospital mortality. Furthermore, CRP and albumin mediated the associations between frailty and in-hospital mortality. ConclusionFrailty may be an adverse prognostic factor for older patients admitted with an AECOPD. CRP and albumin may be parts of mechanism between frailty and in-hospital death.