Objective To explore clinical application and significance of coronary angiography （CAG） prior to heart valve replacement for patients with rheumatic valvular heart disease （RVHD）. Methods We retrospectively analyzed clinical data of 313 RVHD patients who underwent heart valve replacement in the First Affiliated Hospital of Chongqing Medical University from January 2002 to June 2012. All the patients received screening CAG before surgery. According to CAG results，313 patients were divided into two groups. In the coronary artery lesion （CAL） group，there were 29 patients including 17 male and 12 female patients with their age of 60.0±5.2 years. In the non-coronary artery lesion （non-CAL）group，there were 284 patients including 98 male and 186 female patients with their age of 57.0±5.4 years. Surgicaloutcomes were compared between the two groups. Univariate analysis and multivariate logistic regression were performed to analyze risk factors of CAL for RVHD patients. Results CAG showed 29 patients with CAL，and the overall prevalence of CAL was 9.27%. In CAL group，11 patients underwent concomitant coronary artery bypass grafting with 2.2 grafts for each patient on the average. Postoperatively 1 patient （3.45%） died of low cardiac output syndrome （LCOS）. In non-CAL group，5 patients （1.76%） postoperatively died mainly because of LCOS，ventricular fibrillation，sudden cardiac arrest or respiratory failure. Cardiopulmonary bypass time and aortic cross-clamp time of CAL group were significantly longer than those of non-CAL group （P＜0.05）. There was no statistical difference in postoperative mortality，incidence of LCOS，acute renal failure，respiratory failure，reexploration for bleeding，intraoperative blood loss，mechanical ventilation time or hospital stay between the two groups（P＞0.05）. There was no significant correlation between the types of valvular lesions and CAL. Age≥ 55 years （OR=5.534，P=0.005），male gender （OR=2.335，P=0.038） and diabetes mellitus （OR=4.265，P=0.006） were independent risk factors of CAL for RVHD patients undergoing heart valve replacement. Conclusion For RVHD patients with independent risk factors of CAL （age≥55 years，male gender and diabetes mellitus），CAG must beseriously considered before heart valve replacement. RVHD patients with CAL can obtain similarly satisfactory surgicaloutcomes of heart valve replacement as RVHD patients without CAL by appropriate surgical strategy and strengthened perio-perative management.
ObjectiveTo observes the postoperative transformation of subjective and objective sleep quality and related influencing factors in patients with rheumatic valvular heart disease (RVHD) who were found with central sleep apnea (CSA) after cardiac valve replacement.MethodsA total of 262 patients undergoing cardiac valve replacement were screened for CSA by overnight polysomnography and 21 patients with CSA were enrolled and followed up successfully in the 3th, 6th and 12th month of postoperation from April 2010 to January 2013. The Pittsburgh Sleep Quality Index, Epworth Sleepiness, polysomnography and cardiac function were evaluated in preoperation and postoperation (in the 3th, 6th and 12th month).ResultsNew York Heart Association class ［preoperation and postoperation: (3.7±0.5), (2.3±0.6), (1.7±0.6), (1.6±0.7), F=81.124, P<0.05］ continuously decreased, left ventricular ejection fraction ［preoperation and postoperation: (58.5±6.8)%, (60.0±7.4)%, (60.9±5.6)%, (64.4±4.0)%, F=7.182, P<0.05］ steadily increased, six-minute walk distance ［preoperation and postoperation: (271.5±76.6), (422.1±71.9), (445.1±56.2), (454.5± 63.5) m, F=67.134, P<0.05］ constantly increased. During postoperative follow-up, sleep apnea-hypopnea index ［preoperation and postoperation: (26.2±13.4), (12.0±11.5), (8.6±7.5), (7.4±5.5)/h, F=20.548, P<0.05, central sleep apnea index ［preoperation and postoperation: (19.6±10.3), (0.5±1.5), (0.3±1.3), (0.2±0.7)/h, F=72.926, P<0.05］ and oxygen desaturation index ［preoperation and postoperation: (20.1±16.6), (10.8±9.5), (8.5±7.2), (6.1±5.1)/h, F=9.646, P<0.05］ sustained improved. Aroual index ［preoperation and postoperation: (23.1±12.1), (2.7±3.8), (3.5±4.8), (2.2±2.1)/h, F=58.370, P<0.05］ presented overall downward trend. Pittsburgh Sleep Quality Index scale ［preoperation and postoperation: (11.1±3.2), (8.2±3.3), (6.0±3.8), (4.4±2.5), F=27.670, P<0.05］ were constantly improved. Epworth Sleepiness scale ［preoperation and postoperation: (13.3±5.7), (6.9±4.5), (8.2±4.8), (6.1±3.7), F=15.994, P<0.05］ showed overall reduction.ConclusionThe sleep quality of patients with RVHD and CSA is improved after cardiac valve replacement, of which the trend is in keep with postoperative recovery of cardiac function.
ObjectiveTo investigate the influence of mechanical and biological valves on clinical benefits of elderly patients with valvular heart disease.MethodsWe retrospectively analyzed the clinical data of 280 elderly patients with valvular heart disease treated by valve replacement between 2008 and 2014 year. The patients were divided into two groups by tendency score matching including a group A with biological valves and a group B with mechanical valves. Finally, there were 96 patients in each group. There were 43 males and 53 females at age of 64.41±6.52 years in the group A, 44 males and 52 females at age of 64.07±6.20 years in the group B.ResultsThe bleeding rate of skin and mucosa of the group B was significantly higher than that of the group A (P<0.05). There was no statistical difference in mortality within 30 days after operation, all-cause mortality, re-hospitalization rate, re-valve replacement rate, combined atrial flutter/atrial fibrillation ratio, drug use, incidence of cerebral infarction, cerebral hemorrhage, new peripheral vascular embolism and visceral hemorrhage, heart function (NYHA) classification, the cumulative survival rate of all the patients during follow-up (P=0.63), or the cumulative survival rate of the patients with no thrombus/hemorrhage (P=0.75) between the two groups (P>0.05).ConclusionMechanical valve replacement and bioprosthetic valve replacement in the treatment of valvular heart disease in the elderly can achieve similar clinical benefits and both have clinical application value.
ObjectiveTo analyze the recovery rule of atrial contractility (AC) function after Maze Ⅳ procedure of valvular atrial fibrillation (AF).MethodsIn our hospital from March 2016 to April 2018, 103 patients who underwent cryoablation Maze Ⅳ procedure due to mitral valve lesions associated with persistent or long-term persistent AF were enrolled. There were 42 males and 61 females, with an average age of 58.5±9.1 years. Electrocardiogram and echocardiography were followed up at discharge and 1, 3, 6, 12 months after procedure. A multivariate Cox analysis of predictive factors for AC recovery was applied.ResultsAll the 103 patients were followed up for 1 year. The recovery rate of AC increased gradually after operation. It was not until 3 months after procedure that most of the right atrial contractility (RAC) was accompanied by synchronous recovery of the corresponding left atrial contractility (LAC, Kappa coefficient≥0.40, P<0.05). However, the coexistence of sinus rhythm (SR) and bilateral AC was not consistent well until 1 year after operation (Kappa coefficient≥0.40, P<0.05). One year after procedure, the recovery rates of SR and bilateral AC were 86.4% (89/103) and 66.0% (68/103) respectively. By Cox multivariate regression analysis, longer preoperative AF duration (P=0.040), larger preoperative left atrial diameter (LAD, P=0.003), and AC deletion 3 months after surgery (P=0.037) were predictive factors for AF recurrence in the middle and advanced stages (>3 months) after Maze surgery. At the same time, longer preoperative AF duration and larger preoperative LAD were also negative predictors of middle and late recovery of LAC and bilateral AC (All P<0.05). Receiver operating characteristic curve analysis showed that the best critical value of preoperative AF time and preoperative LAD for prediction of AC recovery was 37 months (sensitivity 99.6%, specificity 76.3%) and 60.5 mm (sensitivity 98.5%, specificity 78.9%), respectively.ConclusionThe recovery of AC after Maze procedure is a dynamic improvement process. Early recovery of AC is beneficial to the stable maintenance of SR in the future. Prolonged duration of AF and enlarged LAD have adverse effects on the outcome of Maze Ⅳ procedure.
ObjectiveTo investigate the clinical effect of Maze Ⅳ in the treatment of elderly patients with valvular heart disease and persistent atrial fibrillation (AF).MethodsWe retrospectively analyzed the clinical data of 78 elderly patients with cardiac valve disease combined with persistent AF in our hospital from 2017 to 2018. The patients were allocated to two groups including a trial group (n=37) and a control group (n=41). There were 21 males and 16 females aged 61 to 74 (65.2±2.5) years in the trial group. There were 23 males and 18 females aged 62 to 76 (64.8±3.3) years in the control group. The clinical effects of the two groups were compared.ResultsThere was no statistical difference in baseline data between the two groups (P>0.05). The aortic occlusion time, extracorporeal circulation time, and operation time of the trial group were longer than those of the control group with statistical differences (P<0.05). There was no statistical difference in postoperative ventilator assistance time, complication rate, mortality, ICU retention time, perioperative drainage, red blood cell transfusion volume, or length of hospital stay between the two groups (P>0.05). At the time of discharge, postoperaive 1-month, 3-month, 6-month, and 12-month, the maintenance rates of sinus rhythm in the control group were statistically different from those of the trial group (P<0.05). Compared with the control group, left atrial diameter, left ventricular end diastolic diameter and the decrease of pulmonary artery systolic blood pressure were statistically different (P<0.05).ConclusionMaze Ⅳ is safe and effective in the treatment of elderly patients with valvular heart disease and persistent AF, which is conducive to the recovery and maintenance of sinus rhythm, and is beneficial to the remodeling of the left atrium and left ventricle and the reduction of pulmonary systolic blood pressure with improvement of life quality of the patients.
The incidence of valvular heart disease (VHD) increases with age, and its principal therapy is valve replacement. However, in recent years, the emergence of transcatheter interventions has changed the traditional therapy, making high-risk patients of surgery see dawn of hope. 3D printing technology has developed rapidly since it was applied to the medical field in 1990. Moreover, it has been widely applied in many surgical majors via refined reduction technology. However, the application of 3D printing technology in cardiovascular surgery is still in the preliminary stage, especially in the field of VHD. This article aims to review basic principles of 3D printing technology, its advantages in the therapy of VHD, and its current status of clinical application. Furthermore, this article elaborates current problems and looks forward to the future development direction.
Objective To establish a machine learning based framework to rapidly screen out high-risk patients who may develop atrial fibrillation (AF) from patients with valvular heart disease and provide the information related to risk prediction to clinicians as clinical guidance for timely treatment decisions. Methods Clinical data were retrospectively collected from 1 740 patients with valvular heart disease at West China Hospital of Sichuan University and its branches, including 831 (47.76%) males and 909 (52.24%) females at an average age of 54 years. Based on these data, we built classical logistic regression, three standard machine learning models, and three integrated machine learning models for risk prediction and characterization analysis of AF. We compared the performance of machine learning models with classical logistic regression and selected the best two models, and applied the SHAP algorithm to provide interpretability at the population and single-unit levels. In addition, we provided visualization of feature analysis results. ResultsThe Stack model performed best among all models (AF detection rate 85.6%, F1 score 0.753), while XGBoost outperformed the standard machine learning models (AF detection rate 71.9%, F1 score 0.732), and both models performed significantly better than the logistic regression model (AF detection rate 65.2%, F1 score 0.689). SHAP algorithm showed that left atrial internal diameter, mitral E peak flow velocity (Emv), right atrial internal diameter output per beat, and cardiac function class were the most important features affecting AF prediction. Both the Stack model and XGBoost had excellent predictive ability and interpretability. ConclusionThe Stack model has the highest AF detection performance and comprehensive performance. The Stack model loaded with the SHAP algorithm can be used to screen high-risk patients for AF and reveal the corresponding risk characteristics. Our framework can be used to guide clinical intervention and monitoring of AF.
ObjectiveTo evaluate the use of machine learning algorithms for the prediction and characterization of cardiac thrombosis in patients with valvular heart disease and atrial fibrillation. MethodsThis article collected data of patients with valvular disease and atrial fibrillation from West China Hospital of Sichuan University and its branches from 2016 to 2021. From a total of 2 515 patients who underwent valve surgery, 886 patients with valvular disease and atrial fibrillation were included in the study, including 545 (61.5%) males and 341 (38.5%) females, with a mean age of 55.62±9.26 years, and 192 patients had intraoperatively confirmed cardiac thrombosis. We used five supervised machine learning algorithms to predict thrombosis in patients. Based on the clinical data of the patients (33 features after feature screening), the 10-fold nested cross-validation method was used to evaluate the predictive effect of the model through evaluation indicators such as area under the curve, F1 score and Matthews correlation coefficient. Finally, the SHAP interpretation method was used to interpret the model, and the characteristics of the model were analyzed using a patient as an example. ResultsThe final experiment showed that the random forest classifier had the best comprehensive evaluation indicators, the area under the receiver operating characteristic curve was 0.748±0.043, and the accuracy rate reached 79.2%. Interpretation and analysis of the model showed that factors such as stroke volume, peak mitral E-wave velocity and tricuspid pressure gradient were important factors influencing the prediction. ConclusionThe random forest model achieves the best predictive performance and is expected to be used by clinicians as an aided decision-making tool for screening high-embolic risk patients with valvular atrial fibrillation.