Impact of High Lipoprotein(a) on Long-Term Survival Following Coronary Artery Bypass Grafting.

BACKGROUND:Lipoprotein(a) is a possible causal risk factor for atherosclerosis and related complications. The distribution and prognostic implication of lipoprotein(a) in patients undergoing coronary artery bypass grafting remain unknown. This study aimed to assess the impact of high lipoprotein(a) on the long-term prognosis of patients undergoing coronary artery bypass grafting.METHODS AND RESULTS:Consecutive patients with stable coronary artery disease who underwent isolated coronary artery bypass grafting from January 2013 to December 2018 from a single-center cohort were included. The primary outcome was all-cause death. The secondary outcome was a composite of major adverse cardiovascular and cerebrovascular events. Of the 18 544 patients, 4072 (22.0%) were identified as the high-lipoprotein(a) group (≥50 mg/dL). During a median follow-up of 3.2 years, primary outcomes occurred in 587 patients. High lipoprotein(a) was associated with increased risk of all-cause death (high lipoprotein(a) versus low lipoprotein(a): adjusted hazard ratio [aHR], 1.31 [95% CI, 1.09-1.59]; P=0.005; lipoprotein(a) per 1-mg/dL increase: aHR, 1.003 [95% CI, 1.001-1.006]; P=0.011) and major adverse cardiovascular and cerebrovascular events (high lipoprotein(a) versus low lipoprotein(a): aHR, 1.18 [95% CI, 1.06-1.33]; P=0.004; lipoprotein(a) per 1-mg/dL increase: aHR, 1.002 [95% CI, 1.001-1.004]; P=0.002). The lipoprotein(a)-related risk was greater in patients with European System for Cardiac Operative Risk Evaluation <3, and tended to attenuate in patients receiving arterial grafts.CONCLUSIONS:More than 1 in 5 patients with stable coronary artery disease who underwent coronary artery bypass grafting were exposed to high lipoprotein(a), which is associated with higher risks of death and major adverse cardiovascular and cerebrovascular events. The adverse effects of lipoprotein(a) were more pronounced in patients with clinically low-risk profiles or not receiving arterial grafts.

Comparative analysis of machine learning vs. traditional modeling approaches for predicting in-hospital mortality after cardiac surgery: temporal and spatial external validation based on a nationwide cardiac surgery registry.

AIMS:Preoperative risk assessment is crucial for cardiac surgery. Although previous studies suggested machine learning (ML) may improve in-hospital mortality predictions after cardiac surgery compared to traditional modeling approaches, the validity is doubted due to lacking external validation, limited sample sizes, and inadequate modeling considerations. We aimed to assess predictive performance between ML and traditional modelling approaches, while addressing these major limitations.METHODS AND RESULTS:Adult cardiac surgery cases (n = 168 565) between 2013 and 2018 in the Chinese Cardiac Surgery Registry were used to develop, validate, and compare various ML vs. logistic regression (LR) models. The dataset was split for temporal (2013-2017 for training, 2018 for testing) and spatial (geographically-stratified random selection of 83 centers for training, 22 for testing) experiments, respectively. Model performances were evaluated in testing sets for discrimination and calibration. The overall in-hospital mortality was 1.9%. In the temporal testing set (n = 32 184), the best-performing ML model demonstrated a similar area under the receiver operating characteristic curve (AUC) of 0.797 (95% CI 0.779-0.815) to the LR model (AUC 0.791 [95% CI 0.775-0.808]; P = 0.12). In the spatial experiment (n = 28 323), the best ML model showed a statistically better but modest performance improvement (AUC 0.732 [95% CI 0.710-0.754]) than LR (AUC 0.713 [95% CI 0.691-0.737]; P = 0.002). Varying feature selection methods had relatively smaller effects on ML models. Most ML and LR models were significantly miscalibrated.CONCLUSION:ML provided only marginal improvements over traditional modelling approaches in predicting cardiac surgery mortality with routine preoperative variables, which calls for more judicious use of ML in practice.

Safety and feasibility of a real-time electronic heart team decision-making approach in patients with complex coronary artery disease: a protocol for a randomised controlled trial (EHEART trial).

INTRODUCTION:The implementation of a heart team still faces many challenges which may be facilitated with advanced communication technology. There is a knowledge gap to support the use of an electronic real-time heart team decision-making approach based on communication technology in the real clinical practice and evaluate its safety and feasibility in patients with complex coronary artery disease (CAD).METHODS AND ANALYSIS:The EHEART (Electronic HEArt team with Real-Time decision-making) trial is a prospective, multicentre, two-arm, randomised controlled trial that will randomise 490 patients with complex CAD to either an electronic real-time heart team group or conventional heart team group. For patients allocated to the real-time electronic group, heart team meetings will be initiated during the coronary angiography and guided by a supporting system based on communication technology to help with information synchronisation, real-time communication between specialists, meeting process recording and assistance and joint decision-making with patients' families. The primary and safety endpoint is a composite of all-cause death, myocardial infarction, stroke, revascularisation or re-angina hospital admission at 1 year. The primary secondary outcome is the time interval from the coronary angiography to the final treatment, which is the major indicator of feasibility. We will also compare the practical feasibility from the specialist's and patient's perspectives (for example, specialist's workload and patient's decision results) between the two groups.ETHICS AND DISSEMINATION:The study was approved by the Institutional Review Board (IRB) of Fuwai Hospital (no. 2022-1749). Informed consent will be obtained from all participants. The results of this trial will be disseminated through manuscript publication and national/international conferences, and reported in the trial registry entry.TRIAL REGISTRATION NUMBER:ClinicalTrials.gov Registry (NCT05514210).

Optimal Heart Team Protocol to Improve Revascularization Decisions in Patients with Complex Coronary Artery Disease: A Sequential Mixed Method Study.

AIMS:Current guidelines recommend a heart team in the decision-making for patients with complex coronary artery disease (CAD). However, the decision-making stability of these teams has not been evaluated and the optimum protocol is unknown. We assessed inter-team agreement for revascularization decision-making and influencing factors to inform the development of a heart team protocol.METHODS AND RESULTS:This sequential, explanatory mixed methods study included (i) a cross-sectional quantitative study to assess inter-team agreement on treatment strategy for retrospectively enrolled complex CAD patients and (ii) a qualitative study that used semi-structured interviews with heart team members to identify factors influencing decision-making discrepancy. We randomly selected 101 complex CAD patients. Sixteen specialists were randomly assigned to four heart teams to make decisions for these patients. The primary outcome kappa of inter-team decision-making agreement was moderate (kappa 0.58). Factors influencing decision-making were generated through inductive thematic analysis and were summarized by 3 themes (specialist quality, team composition, and meeting process) and 10 subthemes. Recommendations of heart team implementation were generated based on qualitative and quantitative data at five levels: specialist selection, specialist training, team composition, team training, and meeting process. A detailed protocol on the integration of guidelines, previous experience, and recommendations was generated to establish and deploy a qualified heart team.CONCLUSION:Agreement between heart teams for revascularization decision-making in complex CAD patients was moderate. Potential factors associated with decision discrepancies were summarized and recommendations were generated. A detailed heart team protocol was designed and should be validated in future.

Impact of coronary total occlusion on graft failure and outcomes of coronary artery bypass grafting.

OBJECTIVE:The study objective was to assess the impact of chronic total occlusion on long-term graft failure and outcomes in patients who underwent coronary artery bypass grafting.METHODS:We conducted an observational study involving a single-center subgroup of the CORONARY trial. At 6 to 9 years after coronary artery bypass grafting, all alive patients were invited for coronary computed tomography angiography and clinical follow-up. We assessed the association between chronic total occlusion graft and failing graft showing Fitzgibbon type B or O. Risk factors associated with chronic total occlusion graft failure were assessed. The impact of chronic total occlusion on clinical outcomes was analyzed, including death, myocardial infarction, and repeated revascularization.RESULTS:A total of 349 patients undergoing coronary artery bypass grafting were enrolled between May 2007 and October 2011. Of 301 alive patients at follow-up time (median, 6.8 years; interquartile range, 6.0-8.0 years), repeat coronary computed tomography angiography was performed in 206 patients (68.4%) with 723 grafts (154 chronic total occlusion grafts and 569 nonchronic total occlusion grafts). Chronic total occlusion graft was significantly associated with an increased risk of long-term graft failure after adjustment for patient- and graft-level characteristics (adjusted odds ratio, 2.27; 95% confidence interval, 1.42-3.62; P < .001). Arterial graft, side-to-side anastomosis, higher graft flow, and antiplatelet therapy at discharge were associated with chronic total occlusion graft patency. The presence of 1 or more chronic total occlusions was not significantly associated with long-term composite of death, myocardial infarction, or repeat revascularization (adjusted hazard ratio, 0.91; 95% confidence interval, 0.54-1.51; P = .707).CONCLUSIONS:Chronic total occlusion graft was associated with an increased risk of graft failure. Surgical technique and guideline-directed medical therapy should be noted to improve chronic total occlusion graft patency.

Optimizing the dynamic treatment regime of in-hospital warfarin anticoagulation in patients after surgical valve replacement using reinforcement learning.

OBJECTIVE:Warfarin anticoagulation management requires sequential decision-making to adjust dosages based on patients' evolving states continuously. We aimed to leverage reinforcement learning (RL) to optimize the dynamic in-hospital warfarin dosing in patients after surgical valve replacement (SVR).MATERIALS AND METHODS:10 408 SVR cases with warfarin dosage-response data were retrospectively collected to develop and test an RL algorithm that can continuously recommend daily warfarin doses based on patients' evolving multidimensional states. The RL algorithm was compared with clinicians' actual practice and other machine learning and clinical decision rule-based algorithms. The primary outcome was the ratio of patients without in-hospital INRs >3.0 and the INR at discharge within the target range (1.8-2.5) (excellent responders). The secondary outcomes were the safety responder ratio (no INRs >3.0) and the target responder ratio (the discharge INR within 1.8-2.5).RESULTS:In the test set (n = 1260), the excellent responder ratio under clinicians' guidance was significantly lower than the RL algorithm: 41.6% versus 80.8% (relative risk [RR], 0.51; 95% confidence interval [CI], 0.48-0.55), also the safety responder ratio: 83.1% versus 99.5% (RR, 0.83; 95% CI, 0.81-0.86), and the target responder ratio: 49.7% versus 81.1% (RR, 0.61; 95% CI, 0.58-0.65). The RL algorithms performed significantly better than all the other algorithms. Compared with clinicians' actual practice, the RL-optimized INR trajectory reached and maintained within the target range significantly faster and longer.DISCUSSION:RL could offer interactive, practical clinical decision support for sequential decision-making tasks and is potentially adaptable for varied clinical scenarios. Prospective validation is needed.CONCLUSION:An RL algorithm significantly optimized the post-operation warfarin anticoagulation quality compared with clinicians' actual practice, suggesting its potential for challenging sequential decision-making tasks.

Response by Lin et al to Letter Regarding Article, "Coronary Artery Bypass Grafting and Percutaneous Coronary Intervention in Patients With Chronic Total Occlusion and Multivessel Disease".

Effect of a standardised heart team protocol versus a guideline-based protocol on revascularisation decision stability in stable complex coronary artery disease: rationale and design of a randomised trial of cardiology specialists using historic cases.

INTRODUCTION:A multidisciplinary heart team approach has been recommended by revascularisation guidelines, but how to organise and implement the heart team in a standardised way has not been validated. Inter-team and intra-team decision instability existed in the guideline-based heart team protocol, and our standardised heart team protocol based on a mixed method study may improve decision stability. The objective of this study is to evaluate the effect of the standardised heart team protocol versus the guideline-based protocol on decision-making stability in stable complex coronary artery disease (CAD).METHODS AND ANALYSIS:Eighty-four eligible interventional cardiologists, cardiac surgeons or non-interventional cardiologists from 26 hospitals in China have been enrolled. They will be randomised to a standardised heart team protocol group or a guideline-based protocol group to make revascularisation decisions for 480 historic cases (from a prospective registry) with stable complex CAD. In the standardised group, we will establish 12 heart teams based on an evidence-based protocol, including specialist selection, specialist training, team composition, team training and a standardised meeting process. In the guideline-based group, we will organise 12 heart teams according to the guideline principles, including team composition and standardised meeting process. The primary outcome is the overall percent agreement in revascularisation decisions between heart teams within a group. To demonstrate the clinical implication of decision-making stability, we will further explore the association between decision stability and 1-year clinical outcomes.ETHICS AND DISSEMINATION:The study was approved by the Institutional Review Board (IRB) of Fuwai Hospital (No. 2019-1303). All participants have provided informed consent and all patients included as historic cases provided written informed consent at the time of entry to the prospective registry. The results of this trial will be disseminated through manuscript publication and national/international conferences, and reported in the trial registry entry.TRIAL REGISTRATION NUMBER:NCT05039567.

Clinical Outcomes in Chronic Total Occlusion Revascularization Versus No Chronic Total Occlusion Revascularization: Variability by Target Vessel.

We aimed to investigate the impact of target vessel on clinical outcomes in chronic total occlusion (CTO) revascularization versus no CTO revascularization. This multicenter, retrospective, cohort study involves patients with ≥1 CTO. After classification based on different CTO target vessels or multiple CTOs, patients were further categorized as the CTO revascularization group and the no CTO revascularization group based on treatment received. The primary outcome was a composite of death, myocardial infarction, stroke, repeated revascularization, and hospital admission due to ischemic symptoms. From August 2016 to August 2017, 1712 eligible patients were consecutively enrolled. Chronic total occlusion revascularization was associated with lower risk of 1-year major adverse cardiovascular and cerebrovascular events (MACCEs; adjusted hazard ratio [HR]: 0.36; 95% CI: 0.20-0.67; P = .001) compared with no CTO revascularization in left anterior descending (LAD) CTO patients. The benefit of CTO revascularization was not evident among those with left circumflex (LCX; adjusted HR: 0.51; 95% CI: 0.23-1.10; P = .087), right coronary artery (RCA; adjusted HR: 1.17; 95% CI: 0.59-2.33; P = .648), and multiple CTOs (adjusted HR: 1.00; 95% CI: 0.41-2.44; P = .994). Revascularization for LAD CTO, but not LCX, RCA, or multiple CTOs, was associated with lower risk of 1-year MACCEs compared with no CTO revascularization.

Model assessment: new measures should be known and traditional measures should be accurately interpreted.

Impact of High Lipoprotein(a) on Long-Term Survival Following Coronary Artery Bypass Grafting.

BACKGROUND:Lipoprotein(a) is a possible causal risk factor for atherosclerosis and related complications. The distribution and prognostic implication of lipoprotein(a) in patients undergoing coronary artery bypass grafting remain unknown. This study aimed to assess the impact of high lipoprotein(a) on the long-term prognosis of patients undergoing coronary artery bypass grafting.METHODS AND RESULTS:Consecutive patients with stable coronary artery disease who underwent isolated coronary artery bypass grafting from January 2013 to December 2018 from a single-center cohort were included. The primary outcome was all-cause death. The secondary outcome was a composite of major adverse cardiovascular and cerebrovascular events. Of the 18 544 patients, 4072 (22.0%) were identified as the high-lipoprotein(a) group (≥50 mg/dL). During a median follow-up of 3.2 years, primary outcomes occurred in 587 patients. High lipoprotein(a) was associated with increased risk of all-cause death (high lipoprotein(a) versus low lipoprotein(a): adjusted hazard ratio [aHR], 1.31 [95% CI, 1.09-1.59]; P=0.005; lipoprotein(a) per 1-mg/dL increase: aHR, 1.003 [95% CI, 1.001-1.006]; P=0.011) and major adverse cardiovascular and cerebrovascular events (high lipoprotein(a) versus low lipoprotein(a): aHR, 1.18 [95% CI, 1.06-1.33]; P=0.004; lipoprotein(a) per 1-mg/dL increase: aHR, 1.002 [95% CI, 1.001-1.004]; P=0.002). The lipoprotein(a)-related risk was greater in patients with European System for Cardiac Operative Risk Evaluation <3, and tended to attenuate in patients receiving arterial grafts.CONCLUSIONS:More than 1 in 5 patients with stable coronary artery disease who underwent coronary artery bypass grafting were exposed to high lipoprotein(a), which is associated with higher risks of death and major adverse cardiovascular and cerebrovascular events. The adverse effects of lipoprotein(a) were more pronounced in patients with clinically low-risk profiles or not receiving arterial grafts.

Comparative analysis of machine learning vs. traditional modeling approaches for predicting in-hospital mortality after cardiac surgery: temporal and spatial external validation based on a nationwide cardiac surgery registry.

AIMS:Preoperative risk assessment is crucial for cardiac surgery. Although previous studies suggested machine learning (ML) may improve in-hospital mortality predictions after cardiac surgery compared to traditional modeling approaches, the validity is doubted due to lacking external validation, limited sample sizes, and inadequate modeling considerations. We aimed to assess predictive performance between ML and traditional modelling approaches, while addressing these major limitations.METHODS AND RESULTS:Adult cardiac surgery cases (n = 168 565) between 2013 and 2018 in the Chinese Cardiac Surgery Registry were used to develop, validate, and compare various ML vs. logistic regression (LR) models. The dataset was split for temporal (2013-2017 for training, 2018 for testing) and spatial (geographically-stratified random selection of 83 centers for training, 22 for testing) experiments, respectively. Model performances were evaluated in testing sets for discrimination and calibration. The overall in-hospital mortality was 1.9%. In the temporal testing set (n = 32 184), the best-performing ML model demonstrated a similar area under the receiver operating characteristic curve (AUC) of 0.797 (95% CI 0.779-0.815) to the LR model (AUC 0.791 [95% CI 0.775-0.808]; P = 0.12). In the spatial experiment (n = 28 323), the best ML model showed a statistically better but modest performance improvement (AUC 0.732 [95% CI 0.710-0.754]) than LR (AUC 0.713 [95% CI 0.691-0.737]; P = 0.002). Varying feature selection methods had relatively smaller effects on ML models. Most ML and LR models were significantly miscalibrated.CONCLUSION:ML provided only marginal improvements over traditional modelling approaches in predicting cardiac surgery mortality with routine preoperative variables, which calls for more judicious use of ML in practice.

Safety and feasibility of a real-time electronic heart team decision-making approach in patients with complex coronary artery disease: a protocol for a randomised controlled trial (EHEART trial).

INTRODUCTION:The implementation of a heart team still faces many challenges which may be facilitated with advanced communication technology. There is a knowledge gap to support the use of an electronic real-time heart team decision-making approach based on communication technology in the real clinical practice and evaluate its safety and feasibility in patients with complex coronary artery disease (CAD).METHODS AND ANALYSIS:The EHEART (Electronic HEArt team with Real-Time decision-making) trial is a prospective, multicentre, two-arm, randomised controlled trial that will randomise 490 patients with complex CAD to either an electronic real-time heart team group or conventional heart team group. For patients allocated to the real-time electronic group, heart team meetings will be initiated during the coronary angiography and guided by a supporting system based on communication technology to help with information synchronisation, real-time communication between specialists, meeting process recording and assistance and joint decision-making with patients' families. The primary and safety endpoint is a composite of all-cause death, myocardial infarction, stroke, revascularisation or re-angina hospital admission at 1 year. The primary secondary outcome is the time interval from the coronary angiography to the final treatment, which is the major indicator of feasibility. We will also compare the practical feasibility from the specialist's and patient's perspectives (for example, specialist's workload and patient's decision results) between the two groups.ETHICS AND DISSEMINATION:The study was approved by the Institutional Review Board (IRB) of Fuwai Hospital (no. 2022-1749). Informed consent will be obtained from all participants. The results of this trial will be disseminated through manuscript publication and national/international conferences, and reported in the trial registry entry.TRIAL REGISTRATION NUMBER:ClinicalTrials.gov Registry (NCT05514210).

Optimal Heart Team Protocol to Improve Revascularization Decisions in Patients with Complex Coronary Artery Disease: A Sequential Mixed Method Study.

AIMS:Current guidelines recommend a heart team in the decision-making for patients with complex coronary artery disease (CAD). However, the decision-making stability of these teams has not been evaluated and the optimum protocol is unknown. We assessed inter-team agreement for revascularization decision-making and influencing factors to inform the development of a heart team protocol.METHODS AND RESULTS:This sequential, explanatory mixed methods study included (i) a cross-sectional quantitative study to assess inter-team agreement on treatment strategy for retrospectively enrolled complex CAD patients and (ii) a qualitative study that used semi-structured interviews with heart team members to identify factors influencing decision-making discrepancy. We randomly selected 101 complex CAD patients. Sixteen specialists were randomly assigned to four heart teams to make decisions for these patients. The primary outcome kappa of inter-team decision-making agreement was moderate (kappa 0.58). Factors influencing decision-making were generated through inductive thematic analysis and were summarized by 3 themes (specialist quality, team composition, and meeting process) and 10 subthemes. Recommendations of heart team implementation were generated based on qualitative and quantitative data at five levels: specialist selection, specialist training, team composition, team training, and meeting process. A detailed protocol on the integration of guidelines, previous experience, and recommendations was generated to establish and deploy a qualified heart team.CONCLUSION:Agreement between heart teams for revascularization decision-making in complex CAD patients was moderate. Potential factors associated with decision discrepancies were summarized and recommendations were generated. A detailed heart team protocol was designed and should be validated in future.

Impact of coronary total occlusion on graft failure and outcomes of coronary artery bypass grafting.

OBJECTIVE:The study objective was to assess the impact of chronic total occlusion on long-term graft failure and outcomes in patients who underwent coronary artery bypass grafting.METHODS:We conducted an observational study involving a single-center subgroup of the CORONARY trial. At 6 to 9 years after coronary artery bypass grafting, all alive patients were invited for coronary computed tomography angiography and clinical follow-up. We assessed the association between chronic total occlusion graft and failing graft showing Fitzgibbon type B or O. Risk factors associated with chronic total occlusion graft failure were assessed. The impact of chronic total occlusion on clinical outcomes was analyzed, including death, myocardial infarction, and repeated revascularization.RESULTS:A total of 349 patients undergoing coronary artery bypass grafting were enrolled between May 2007 and October 2011. Of 301 alive patients at follow-up time (median, 6.8 years; interquartile range, 6.0-8.0 years), repeat coronary computed tomography angiography was performed in 206 patients (68.4%) with 723 grafts (154 chronic total occlusion grafts and 569 nonchronic total occlusion grafts). Chronic total occlusion graft was significantly associated with an increased risk of long-term graft failure after adjustment for patient- and graft-level characteristics (adjusted odds ratio, 2.27; 95% confidence interval, 1.42-3.62; P < .001). Arterial graft, side-to-side anastomosis, higher graft flow, and antiplatelet therapy at discharge were associated with chronic total occlusion graft patency. The presence of 1 or more chronic total occlusions was not significantly associated with long-term composite of death, myocardial infarction, or repeat revascularization (adjusted hazard ratio, 0.91; 95% confidence interval, 0.54-1.51; P = .707).CONCLUSIONS:Chronic total occlusion graft was associated with an increased risk of graft failure. Surgical technique and guideline-directed medical therapy should be noted to improve chronic total occlusion graft patency.

Optimizing the dynamic treatment regime of in-hospital warfarin anticoagulation in patients after surgical valve replacement using reinforcement learning.

OBJECTIVE:Warfarin anticoagulation management requires sequential decision-making to adjust dosages based on patients' evolving states continuously. We aimed to leverage reinforcement learning (RL) to optimize the dynamic in-hospital warfarin dosing in patients after surgical valve replacement (SVR).MATERIALS AND METHODS:10 408 SVR cases with warfarin dosage-response data were retrospectively collected to develop and test an RL algorithm that can continuously recommend daily warfarin doses based on patients' evolving multidimensional states. The RL algorithm was compared with clinicians' actual practice and other machine learning and clinical decision rule-based algorithms. The primary outcome was the ratio of patients without in-hospital INRs >3.0 and the INR at discharge within the target range (1.8-2.5) (excellent responders). The secondary outcomes were the safety responder ratio (no INRs >3.0) and the target responder ratio (the discharge INR within 1.8-2.5).RESULTS:In the test set (n = 1260), the excellent responder ratio under clinicians' guidance was significantly lower than the RL algorithm: 41.6% versus 80.8% (relative risk [RR], 0.51; 95% confidence interval [CI], 0.48-0.55), also the safety responder ratio: 83.1% versus 99.5% (RR, 0.83; 95% CI, 0.81-0.86), and the target responder ratio: 49.7% versus 81.1% (RR, 0.61; 95% CI, 0.58-0.65). The RL algorithms performed significantly better than all the other algorithms. Compared with clinicians' actual practice, the RL-optimized INR trajectory reached and maintained within the target range significantly faster and longer.DISCUSSION:RL could offer interactive, practical clinical decision support for sequential decision-making tasks and is potentially adaptable for varied clinical scenarios. Prospective validation is needed.CONCLUSION:An RL algorithm significantly optimized the post-operation warfarin anticoagulation quality compared with clinicians' actual practice, suggesting its potential for challenging sequential decision-making tasks.

Response by Lin et al to Letter Regarding Article, "Coronary Artery Bypass Grafting and Percutaneous Coronary Intervention in Patients With Chronic Total Occlusion and Multivessel Disease".

Effect of a standardised heart team protocol versus a guideline-based protocol on revascularisation decision stability in stable complex coronary artery disease: rationale and design of a randomised trial of cardiology specialists using historic cases.

INTRODUCTION:A multidisciplinary heart team approach has been recommended by revascularisation guidelines, but how to organise and implement the heart team in a standardised way has not been validated. Inter-team and intra-team decision instability existed in the guideline-based heart team protocol, and our standardised heart team protocol based on a mixed method study may improve decision stability. The objective of this study is to evaluate the effect of the standardised heart team protocol versus the guideline-based protocol on decision-making stability in stable complex coronary artery disease (CAD).METHODS AND ANALYSIS:Eighty-four eligible interventional cardiologists, cardiac surgeons or non-interventional cardiologists from 26 hospitals in China have been enrolled. They will be randomised to a standardised heart team protocol group or a guideline-based protocol group to make revascularisation decisions for 480 historic cases (from a prospective registry) with stable complex CAD. In the standardised group, we will establish 12 heart teams based on an evidence-based protocol, including specialist selection, specialist training, team composition, team training and a standardised meeting process. In the guideline-based group, we will organise 12 heart teams according to the guideline principles, including team composition and standardised meeting process. The primary outcome is the overall percent agreement in revascularisation decisions between heart teams within a group. To demonstrate the clinical implication of decision-making stability, we will further explore the association between decision stability and 1-year clinical outcomes.ETHICS AND DISSEMINATION:The study was approved by the Institutional Review Board (IRB) of Fuwai Hospital (No. 2019-1303). All participants have provided informed consent and all patients included as historic cases provided written informed consent at the time of entry to the prospective registry. The results of this trial will be disseminated through manuscript publication and national/international conferences, and reported in the trial registry entry.TRIAL REGISTRATION NUMBER:NCT05039567.

Clinical Outcomes in Chronic Total Occlusion Revascularization Versus No Chronic Total Occlusion Revascularization: Variability by Target Vessel.

We aimed to investigate the impact of target vessel on clinical outcomes in chronic total occlusion (CTO) revascularization versus no CTO revascularization. This multicenter, retrospective, cohort study involves patients with ≥1 CTO. After classification based on different CTO target vessels or multiple CTOs, patients were further categorized as the CTO revascularization group and the no CTO revascularization group based on treatment received. The primary outcome was a composite of death, myocardial infarction, stroke, repeated revascularization, and hospital admission due to ischemic symptoms. From August 2016 to August 2017, 1712 eligible patients were consecutively enrolled. Chronic total occlusion revascularization was associated with lower risk of 1-year major adverse cardiovascular and cerebrovascular events (MACCEs; adjusted hazard ratio [HR]: 0.36; 95% CI: 0.20-0.67; P = .001) compared with no CTO revascularization in left anterior descending (LAD) CTO patients. The benefit of CTO revascularization was not evident among those with left circumflex (LCX; adjusted HR: 0.51; 95% CI: 0.23-1.10; P = .087), right coronary artery (RCA; adjusted HR: 1.17; 95% CI: 0.59-2.33; P = .648), and multiple CTOs (adjusted HR: 1.00; 95% CI: 0.41-2.44; P = .994). Revascularization for LAD CTO, but not LCX, RCA, or multiple CTOs, was associated with lower risk of 1-year MACCEs compared with no CTO revascularization.

Model assessment: new measures should be known and traditional measures should be accurately interpreted.