Objectives:Using data from the heart transplant patient dataset of our center,we aimed to develop a preoperative risk scoring model specifically suitable for the Chinese population undergoing heart transplantation.This model was established to predict the likelihood of graft failure within the first year post-surgery and classify recipients according to their risk level.Methods:A retrospective study was conducted at a single center on 1 210 consecutive heart transplant recipients between June 2004 and December 2022.Risk factor screening was performed using univariate and multivariate logistic regression analyses.Variable selection was carried out through a stepwise backward procedure based on the Akaike Information Criterion(AIC).The regression coefficients obtained from the final model were employed as weighting factors in the multifactor analysis.The study utilized the area under the receiver operating characteristic(ROC)area under curve(AUC)as a metric to evaluate the performance of the model.Patients were stratified into low,medium,and high-risk groups based on the distribution of the calculated scores.Survival analysis was conducted on the various risk groups using the Kaplan-Meier method,with statistical comparisons performed using the log-rank test.A significance level of P<0.05 was deemed statistically significant.Results:A risk scoring model,denoted as the heart transplant(HTx)score,was developed,comprising 11 variables and yielding a total score of 20.6 points.In comparison to the low-risk group,the OR for 1-year graft failure in the medium-risk group was 2.0(95%CI:1.1-3.6,P=0.02),while the high-risk group had an OR of 9.8(95%CI:5.4-17.7,P<0.01).The risk scoring model exhibited strong discriminative ability with an AUC of 0.712(95%CI:0.646-0.778)and an internally validated bias-corrected AUC of 0.713.The results of the Hosmer-Lemeshow goodness-of-fit test indicated that the predictive model demonstrated a strong calibration ability(Hosmer-Lemeshow χ2=2.92,P=0.71).Within the cohort,the AUC values for the IMPACT score,UNOS score,RSS score,Mayo score,BO score,and TRS score models were 0.645,0.651,0.632,0.589,0.610,and 0.604,respectively.These findings suggest that the HTx scoring model exhibited superior predictive performance compared to the aforementioned models in forecasting outcomes within our cohort.The Kaplan-Meier survival analysis revealed statistically significant differences in long-term survival rates between the three risk groups,a noticeable decrease in long-term survival rates were observed with increasing levels of HTx risk stratification(P<0.05).Conclusions:Present results indicate a significant association between the developed HTx risk scores and graft failure within the initial year post-surgery,present model effectively categorizes the heart transplant recipients into low,medium,and high-risk groups and is valuable for risk stratification.

Objectives:Using data from the heart transplant patient dataset of our center,we aimed to develop a preoperative risk scoring model specifically suitable for the Chinese population undergoing heart transplantation.This model was established to predict the likelihood of graft failure within the first year post-surgery and classify recipients according to their risk level.Methods:A retrospective study was conducted at a single center on 1 210 consecutive heart transplant recipients between June 2004 and December 2022.Risk factor screening was performed using univariate and multivariate logistic regression analyses.Variable selection was carried out through a stepwise backward procedure based on the Akaike Information Criterion(AIC).The regression coefficients obtained from the final model were employed as weighting factors in the multifactor analysis.The study utilized the area under the receiver operating characteristic(ROC)area under curve(AUC)as a metric to evaluate the performance of the model.Patients were stratified into low,medium,and high-risk groups based on the distribution of the calculated scores.Survival analysis was conducted on the various risk groups using the Kaplan-Meier method,with statistical comparisons performed using the log-rank test.A significance level of P<0.05 was deemed statistically significant.Results:A risk scoring model,denoted as the heart transplant(HTx)score,was developed,comprising 11 variables and yielding a total score of 20.6 points.In comparison to the low-risk group,the OR for 1-year graft failure in the medium-risk group was 2.0(95%CI:1.1-3.6,P=0.02),while the high-risk group had an OR of 9.8(95%CI:5.4-17.7,P<0.01).The risk scoring model exhibited strong discriminative ability with an AUC of 0.712(95%CI:0.646-0.778)and an internally validated bias-corrected AUC of 0.713.The results of the Hosmer-Lemeshow goodness-of-fit test indicated that the predictive model demonstrated a strong calibration ability(Hosmer-Lemeshow χ2=2.92,P=0.71).Within the cohort,the AUC values for the IMPACT score,UNOS score,RSS score,Mayo score,BO score,and TRS score models were 0.645,0.651,0.632,0.589,0.610,and 0.604,respectively.These findings suggest that the HTx scoring model exhibited superior predictive performance compared to the aforementioned models in forecasting outcomes within our cohort.The Kaplan-Meier survival analysis revealed statistically significant differences in long-term survival rates between the three risk groups,a noticeable decrease in long-term survival rates were observed with increasing levels of HTx risk stratification(P<0.05).Conclusions:Present results indicate a significant association between the developed HTx risk scores and graft failure within the initial year post-surgery,present model effectively categorizes the heart transplant recipients into low,medium,and high-risk groups and is valuable for risk stratification.

Objective To evaluate the effect of extracorporeal membrane oxygenation (ECMO) on early allograft dysfunction (EAD) after heart transplantation. Methods Clinical data of 614 heart transplant recipients were retrospectively analyzed. All recipients were divided into the ECMO group (n=43) and non-ECMO group (n=571) according to postoperative application of ECMO. In the ECMO group, the conditions of recipients undergoing ECMO after heart transplantation were summarized. Perioperative status and long-term prognosis of recipients were compared between two groups. Results Among 43 recipients undergoing ECMO, 17 cases underwent thoracotomy due to bleeding, 10 cases of infection, 4 cases of venous thrombosis of the lower limbs, and 1 case of stroke, respectively. Twenty-six recipients were recovered and discharged after successful weaning from ECMO, six died during ECMO support, six died after weaning from ECMO, five received retransplantation due to unsuccessful weaning from ECMO, and only one survived after retransplantation. Compared with the non-ECMO group, intraoperative cardiopulmonary bypass duration was significantly longer, the proportion of recipients requiring postoperative intra-aortic balloon pump (IABP), dialysis due to renal insufficiency, reoperation for hemostasis, infection, mechanical ventilation time≥96 h and tracheotomy was significantly higher, and the length of postoperative intensive care unit (ICU) stay was significantly longer in the ECMO group (all P < 0.05). The survival rate after discharge and 90-d survival rate in the ECMO group were 63% and 96%, significantly lower than 97% and 100% in the non-ECMO group (both P < 0.05). Survival analysis showed that the long-term survival rate in the ECMO group was significantly lower than that in the non-ECMO group (P < 0.05). After excluding the recipients who died within 90 d after heart transplantation, no significant difference was observed in the long-term survival rate (P > 0.05). Conclusions ECMO is an effective treatment of EAD after heart transplantation. The short-term survival rate of recipients using ECMO after heart transplantation is lower than that of those who do not use ECMO, and there is no significant difference in long-term survival of recipients surviving 90 d after heart transplantation.

Objective To analyze the early outcomes of heart transplantation in critical patients and its significance in donor allocation decision. Methods Clinical data of 449 recipients undergoing heart transplantation were retrospectively analyzed. According to preoperative status, all patients were divided into the critical status group (n=64) and general status group (n=385). The incidence of critical status was summarized. Clinical data of recipients were statistically compared between two groups. Postoperative survival and causes of death in recipients between two groups were analyzed. Perioperative results of critical recipients undergoing different mechanical circulation support as a bridge to heart transplantation were compared. Results Critical patients accounted for 14.3% of the total number of transplant recipients. The proportion of critical patients gradually increased in recent 5 years. Compared with the general status group, the recipients in critical status group had a lower proportion of smoking history, a higher proportion of cardiac surgery history, a higher serum level of creatinine, and a higher proportion of primary diseases of heart failure before heart transplantation(all P≤0.01). The proportion of undergoing mechanical circulation support was higher, the incidence of complications was higher, the stay time in intensive care unit (ICU) was longer and the in-hospital fatality was higher after heart transplantation in the critical status group (all P≤0.01). The 1-year survival rate of recipients in critical status group was significantly lower than that in general status group (83% vs. 95%, P < 0.01). The fatality of recipients due to infection and multiple organ failure in critical status group was higher than that in general status group. Among 64 critical recipients, 1 recipient received ventilator alone, and 63 recipients underwent mechanical circulation support devices as a bridge to heart transplantation. Among them, intra-aortic balloon pump (IABP) alone was applied in 49 cases (77%), 8 cases (13%) of extracorporeal membrane oxygenation (ECMO) combined with IABP, 4 cases (6%) of ECMO alone, and 2 cases (3%) of left ventricular assist device (LVAD) alone. Critical patients who received preoperative ECMO and ECMO combined with IABP bridging to heart transplantation have a higher proportion of postoperative complications, a longer ICU stay time, a longer mechanical ventilation time, and a higher proportion of hospital deaths. Conclusions The overall prognosis of critical patients undergoing heart transplantation is relatively poor. Effective preoperative management may reverse the high-risk status of critical patients in a certain extent. The limited quantity of donor heart should be allocated to the most urgent patients who can obtain the greatest benefit from heart transplantation.

In view of the evaluation of fundus image segmentation, a new evaluation method was proposed to make up insufficiency of the traditional evaluation method which only considers the overlap of pixels and neglects topology structure of the retinal vessel. Mathematical morphology and thinning algorithm were used to obtain the retinal vascular topology structure. Then three features of retinal vessel, including mutual information, correlation coefficient and ratio of nodes, were calculated. The features of the thinned images taken as topology structure of blood vessel were used to evaluate retinal image segmentation. The manually-labeled images and their eroded ones of STARE database were used in the experiment. The result showed that these features, including mutual information, correlation coefficient and ratio of nodes, could be used to evaluate the segmentation quality of retinal vessel on fundus image through topology structure, and the algorithm was simple. The method is of significance to the supplement of traditional segmentation evaluation of retinal vessel on fundus image.
Algorithms ; Databases, Factual ; Diagnostic Imaging ; methods ; Diagnostic Techniques, Ophthalmological ; Fundus Oculi ; Humans ; Image Processing, Computer-Assisted ; Retina ; Retinal Vessels ; anatomy & histology