Contemporary mortality risk prediction for percutaneous coronary intervention: results from 588,398 procedures in the National Cardiovascular Data Registry

Critical appraisal and assessment of bias among studies evaluating risk prediction models for in-hospital and 30-day mortality after percutaneous coronary intervention: a systematic review

OBJECTIVE

We systematically assessed prediction models for the risk of in-hospital and 30-day mortality in post-percutaneous coronary intervention (PCI) patients.

DESIGN

Systematic review and narrative synthesis.

DATA SOURCES

Searched PubMed, Web of Science, Embase, Cochrane Library, CINAHL, CNKI, Wanfang Database, VIP Database and SinoMed for literature up to 31 August 2023.

ELIGIBILITY CRITERIA

The included literature consists of studies in Chinese or English involving PCI patients aged ≥18 years. These studies aim to develop risk prediction models and include designs such as cohort studies, case-control studies, cross-sectional studies or randomised controlled trials. Each prediction model must contain at least two predictors. Exclusion criteria encompass models that include outcomes other than death post-PCI, literature lacking essential details on study design, model construction and statistical analysis, models based on virtual datasets, and publications such as conference abstracts, grey literature, informal publications, duplicate publications, dissertations, reviews or case reports. We also exclude studies focusing on the localisation applicability of the model or comparative effectiveness.

DATA EXTRACTION AND SYNTHESIS

Two independent teams of researchers developed standardised data extraction forms based on CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies to extract and cross-verify data. They used Prediction model Risk Of Bias Assessment Tool (PROBAST) to assess the risk of bias and applicability of the model development or validation studies included in this review.

RESULTS

This review included 28 studies with 38 prediction models, showing area under the curve values ranging from 0.81 to 0.987. One study had an unclear risk of bias, while 27 studies had a high risk of bias, primarily in the area of statistical analysis. The models constructed in 25 studies lacked clinical applicability, with 21 of these studies including intraoperative or postoperative predictors.

CONCLUSION

The development of in-hospital and 30-day mortality prediction models for post-PCI patients is in its early stages. Emphasising clinical applicability and predictive stability is vital. Future research should follow PROBAST's low risk-of-bias guidelines, prioritising external validation for existing models to ensure reliable and widely applicable clinical predictions.

PROSPERO REGISTRATION NUMBER

CRD42023477272.

Real-World Experience and Outcomes With Percutaneous Coronary Intervention for Protected Versus Unprotected Left Main Coronary Artery Disease: Insights from the Veteran Affairs Clinical Assessment Reporting and Tracking Program

The practice patterns and outcomes of protected left main (PLM) and unprotected left main (ULM) percutaneous coronary intervention (PCI) are not well defined in contemporary US clinical practice. Data were collected from all Veteran Affairs catheterization laboratories participating in the Clinical Assessment Reporting and Tracking Program between 2009 and 2019. The analysis included 4,351 patients who underwent left main PCI, of whom 1,306 pairs of PLM and ULM PCI were included in a propensity-matched cohort. Selected temporal trends were also assessed. The primary outcome was major adverse cardiovascular event (MACE) outcomes at 1 year, which was defined as a composite of all-cause mortality, rehospitalization for myocardial infarction (MI), rehospitalization for stroke, or urgent revascularization. Patients who underwent ULM PCI compared with patients who underwent PLM PCI were older (age 71.5 vs 69.2 years, p <0.001), more clinically complex, and more likely to present with acute coronary syndrome. In the propensity-matched cohort, radial access was used more often for ULM PCI (21% [273] vs 14% [185], p <0.001) and ULM PCI was more likely to involve the left main bifurcation (22% vs 14%, p = 0.003) and require mechanical circulatory support (10% [134] vs 1% [17], p <0.001). The 1-year MACEs occurred more frequently with ULM PCI than PLM PCI (22% [289] vs 16% [215], p ≤0.001) and all-cause mortality was also higher (16% [213] vs 10% [125], p ≤0.001). In the matched cohort, there was a low incidence of rehospitalization for MI (4% [48] ULM vs 4% [48] PLM, p = 1.000) or revascularization (7% [94] ULM vs 6% [84] PLM, p = 0.485). In this real-world experience, patients who underwent PLM PCI had better 1-year outcomes than those who underwent ULM PCI; however, in both groups, there was a high rate of mortality and MACEs at 1 year despite a relatively low rate of MI or revascularization.

Periprocedural myocardial infarction after percutaneous coronary intervention and long-term mortality: a meta-analysis

BACKGROUND AND AIMS

Conflicting data are available regarding the association between periprocedural myocardial infarction (PMI) and mortality following percutaneous coronary intervention. The purpose of this study was to evaluate the incidence and prognostic implication of PMI according to the Universal Definition of Myocardial Infarction (UDMI), the Academic Research Consortium (ARC)-2 definition, and the Society for Cardiovascular Angiography and Interventions (SCAI) definition.

METHODS

Studies reporting adjusted effect estimates were systematically searched. The primary outcome was all-cause death, while cardiac death was included as a secondary outcome. Studies defining PMI according to biomarker elevation without further evidence of myocardial ischaemia ('ancillary criteria') were included and reported as 'definition-like'. Data were pooled in a random-effect model.

RESULTS

A total of 19 studies and 109 568 patients were included. The incidence of PMI was progressively lower across the UDMI, ARC-2, and SCAI definitions. All PMI definitions were independently associated with all-cause mortality [UDMI: hazard ratio (HR) 1.61, 95% confidence interval (CI) 1.32-1.97; I2 34%; ARC-2: HR 2.07, 95% CI 1.40-3.08, I2 0%; SCAI: HR 3.24, 95% CI 2.36-4.44, I2 78%]. Including ancillary criteria in the PMI definitions were associated with an increased prognostic performance in the UDMI but not in the SCAI definition. Data were consistent after evaluation of major sources of heterogeneity.

CONCLUSIONS

All currently available international definitions of PMI are associated with an increased risk of all-cause death after percutaneous coronary intervention. The magnitude of this latter association varies according to the sensitivity and prognostic relevance of each definition.

Contemporary Risk Models for In-Hospital and 30-Day Mortality After Percutaneous Coronary Intervention

PURPOSE OF REVIEW

Risk models for mortality after percutaneous coronary intervention (PCI) are underutilized in clinical practice though they may be useful during informed consent, risk mitigation planning, and risk adjustment of hospital and operator outcomes. This review analyzed contemporary risk models for in-hospital and 30-day mortality after PCI.

RECENT FINDINGS

We reviewed eight contemporary risk models. Age, sex, hemodynamic status, acute coronary syndrome type, heart failure, and kidney disease were consistently found to be independent risk factors for mortality. These models provided good discrimination (C-statistic 0.85-0.95) for both pre-catheterization and comprehensive risk models that included anatomic variables. There are several excellent models for PCI mortality risk prediction. Choice of the model will depend on the use case and population, though the CathPCI model should be the default for in-hospital mortality risk prediction in the United States. Future interventions should focus on the integration of risk prediction into clinical care.

Safety and Efficacy of Enoxaparin During Low-Risk Elective Percutaneous Coronary Intervention

Intravenous unfractionated heparin (UFH) is the most frequently used anticoagulant for percutaneous coronary intervention (PCI). Intravenous enoxaparin, a low-molecular-weight heparin, has superior pharmacokinetic and pharmacodynamic properties compared with UFH. Multiple trials have shown enoxaparin to be safe and effective in PCI. However, there has not been a contemporary study evaluating its safety and efficacy. To assess its efficacy and safety, intravenous enoxaparin during PCI through radial artery access was evaluated in PCI patients from January 2015 to December 2019. Outcomes included procedural success, all-cause mortality, ischemic complications, and bleeding complications from the time of the procedure until hospital discharge. A total of 1019 consecutive eligible patients were identified. Median age was 63 years, and 70% were men. The indication for PCI was stable and unstable angina in two-thirds of cases (77%). Few patients had myocardial infarction (MI) (2.2%) as the indication for intervention. The procedure was successful in 98.2% of cases. There were no deaths. Procedural MI occurred in 0.3% of patients. Acute stent thrombosis occurred in 0.4%. Urgent revascularization and stroke occurred in 0.1% each. Small wrist hematomas occurred in 0.3% and all were managed conservatively. There was one radial artery pseudoaneurysm. There were no cases of major bleeding. In conclusion, this single-center study showed that intravenous enoxaparin is a reasonable alternative anticoagulant for use in low-risk and elective non-MI PCI through radial artery access.

Impact of preprocedural left ventricular systolic function on the safety and durability of percutaneous coronary intervention

BACKGROUND

Percutaneous coronary intervention (PCI) is considered less safe in patients with reduced ejection fraction (EF), an impression based on older data. Whether the safety and durability of contemporary PCI are different in patients with reduced EF compared with normal EF patients is unknown.

METHODS

Patients from the BIOFLOW II, IV and V clinical trials were grouped as normal EF (≥50%) and reduced EF (30%-50%). Using multivariable logistic regression and cox proportional hazards regression, we determined relations of EF category with procedural safety (a composite of cardiac death, myocardial infarction, stroke and urgent coronary artery bypass grafting within 30 days of PCI) and target lesion failure (TLF; comprising cardiac death, target vessel myocardial infarction, target vessel revascularization within 1 year of PCI) respectively. In sensitivity analyses, we regrouped patients into EF < 45% and ≥55% and repeated the aforementioned analyses.

RESULTS

In 1685 patients with normal EF (mean age 65 years; 27% women; mean EF 61%) and 259 with low EF (mean age 64 years; 17% women; mean EF 41%), 101 safety and 148 TLF events occurred. Compared with patients in the normal EF group, those with reduced EF had neither a statistically significant higher proportion of safety events, nor a higher multivariable-adjusted risk for such events. Similarly, patients with reduced EF and normal EF did not differ in terms of TLF event proportions or multivariable-adjusted risk for TLF. The results were similar in sensitivity analyses with EF groups redefined to create a 10% between-group EF separation.

CONCLUSION

PCI safety and durability outcomes are similar in patients with mild-moderately reduced EF and normal EF.

Assessing Quality in Interventional Practice: Identifying Meaningful and Actionable Metrics

Interventional cardiologists should insist on quality assessment techniques that indisputably reflect the merit of care delivered. Only measurable outcomes and metrics that are modifiable should be identified and collected. An evaluation process should be adopted that genuinely appraises clinical practice, incorporating appropriate benchmarks for comparison.

Interpretable machine learning models for predicting in-hospital and 30 days adverse events in acute coronary syndrome patients in Kuwait

The relationships between acute coronary syndromes (ACS) adverse events and the associated risk factors are typically complicated and nonlinear, which poses significant challenges to clinicians' attempts at risk stratification. Here, we aim to explore the implementation of modern risk stratification tools to untangle how these complex factors shape the risk of adverse events in patients with ACS. We used an interpretable multi-algorithm machine learning (ML) approach and clinical features to fit predictive models to 1,976 patients with ACS in Kuwait. We demonstrated that random forest (RF) and extreme gradient boosting (XGB) algorithms, remarkably outperform traditional logistic regression model (AUCs = 0.84 & 0.79 for RF and XGB, respectively). Our in-hospital adverse events model identified left ventricular ejection fraction as the most important predictor with the highest interaction strength with other factors. However, using the 30-days adverse events model, we found that performing an urgent coronary artery bypass graft was the most important predictor, with creatinine levels having the strongest overall interaction with other related factors. Our ML models not only untangled the non-linear relationships that shape the clinical epidemiology of ACS adverse events but also elucidated their risk in individual patients based on their unique features.

The everolimus eluting Synergy MegatronTM drug-eluting stent platform: Early outcomes from the European Synergy MegatronTM Implanters' Registry

BACKGROUND

The Synergy MegatronTM is an everolimus-drug eluting stent that may offer advantages in the treatment of aorto-ostial disease and large proximal vessels.

AIMS

To report the short- to medium-term clinical outcomes from the European Synergy MegatronTM Implanters' Registry.

METHODS

This registry was an investigator-initiated study conducted at 14 European centers. The primary outcome was target lesion failure (TLF), defined as the composite of cardiovascular death, target vessel myocardial infarction (MI), and target lesion revascularisation.

RESULTS

Five hundred seventy-five patients underwent PCI with MegatronTM between 2019 and 2021. Patients were 69 ± 12 years old, 26% had diabetes mellitus, 24% had moderate-severe left ventricular impairment and 59% presented with an acute coronary syndrome. 15% were deemed prohibitively high risk for surgical revascularisation. The target vessel involved the left main stem in 55%, the ostium of the RCA in 13% and was a true bifurcation (Medina 1,1,1) in 50%.  At 1 year, TLF was observed in 40 patients, with 26 (65%) occurring within the first 30 days. The cumulative incidence of TLF was 4.5% at 30 days and 8.6% (95% CI 6.3-11.7) at 1 year. The incidence of stent thrombosis was 0.5% with no late stent thromboses. By multivariate analysis, the strongest independent predictors of TLF were severe left ventricular impairment (HR 3.43, 95% CI: 1.67-6.76, p < 0.001) and a target vessel involving the left main (HR 4.00 95% CI 1.81-10.15 p = 0.001).

CONCLUSIONS

Use of the Synergy MegatronTM everolimus eluting stent in a 'real-world' setting shows favorable outcomes at 30 days and 1 year.

Development of Comorbidity Index for in-hospital mortality for patients who underwent coronary artery revascularization

BACKGROUND

For myocardial revascularization, coronary artery bypass grafting (CAGB) and percutaneous coronary intervention (PCI) are two common modalities but with high in-hospital mortality. A Comorbidity Index is useful to predict mortality or can be used with other covariates to develop point-scoring systems. This study aimed to develop specific comorbidity indices for patients who underwent coronary artery revascularization.

METHODS

Patients who underwent CABG or PCI were identified in the National Inpatient Sample database between Q4 2015-2020. Patients of age <40 were excluded for congenital heart defects. Patients were randomly sampled into experimental (70%) and validation (30%) groups. Thirty-eight Elixhauser comorbidities were identified and included in multivariable regression to discriminate in-hospital mortality. Weight for each comorbidity was assigned and single indices, Li CABG Mortality Index (LCMI) and Li PCI Mortality Index (LPMI), were developed.

RESULTS

Mortality discrimination by LCMI approached adequacy (c-statistic=0.691, 95% CI=0.682-0.701) and was comparable to multivariable regression with comorbidities (c-statistic=0.685, 95% CI=0.675-0.694). LCMI discrimination performed significantly better than Elixhauser Comorbidity Index (ECI) (c-statistic=0.621, 95% CI=0.611-0.631) and can be further improved by adjusting age (c-statistic=0.721, 95% CI=0.712-0.730). All models were well-calibrated (Brier score=0.021-0.022). LPMI moderately discriminated in-hospital mortality (c-statistic=0.666, 95% CI=0.660-0.672) and performed significantly better than ECI (c-statistic=0.610, 95% CI=0.604-0.616). LPMI performed better than the all-comorbidity multivariable regression (c-statistic=0.658, 95% CI=0.652-0.663). After age adjustment, LPMI discrimination was significantly increased and was approaching adequacy (c-statistic=0.695, 95% CI=0.690-0.701). All models were well-calibrated (Brier score=0.025-0.026).

CONCLUSIONS

LCMI and LPMI effectively discriminated and predicted in-hospital mortality. These indices were validated and performed superior to ECI. These indices can standardize comorbidity measurement as alternatives to ECI to help replicate and compare results across studies.

Predicting target lesion failure following percutaneous coronary intervention through machine learning risk assessment models

Aims

Central to the practice of precision medicine in percutaneous coronary intervention (PCI) is a risk-stratification tool to predict outcomes following the procedure. This study is intended to assess machine learning (ML)-based risk models to predict clinically relevant outcomes in PCI and to support individualized clinical decision-making in this setting.

Methods and results

Five different ML models [gradient boosting classifier (GBC), linear discrimination analysis, Naïve Bayes, logistic regression, and K-nearest neighbours algorithm) for the prediction of 1-year target lesion failure (TLF) were trained on an extensive data set of 35 389 patients undergoing PCI and enrolled in the global, all-comers e-ULTIMASTER registry. The data set was split into a training (80%) and a test set (20%). Twenty-three patient and procedural characteristics were used as predictive variables. The models were compared for discrimination according to the area under the receiver operating characteristic curve (AUC) and for calibration. The GBC model showed the best discriminative ability with an AUC of 0.72 (95% confidence interval 0.69-0.75) for 1-year TLF on the test set. The discriminative ability of the GBC model for the components of TLF was highest for cardiac death with an AUC of 0.82, followed by target vessel myocardial infarction with an AUC of 0.75 and clinically driven target lesion revascularization with an AUC of 0.68. The calibration was fair until the highest risk deciles showed an underestimation of the risk.

Conclusion

Machine learning-derived predictive models provide a reasonably accurate prediction of 1-year TLF in patients undergoing PCI. A prospective evaluation of the predictive score is warranted.

Registration

Clinicaltrial.gov identifier is NCT02188355.

Development and validation of a predictive models for predicting the cardiac events within one year for patients underwent percutaneous coronary intervention procedure at IJN

PURPOSE

Percutaneous coronary intervention (PCI) is a common treatment modality for coronary artery disease. Accurate prediction of patients at risk for complications and hospital readmission after PCI could improve the overall clinical management. We aimed to develop and validate predictive models to predict any cardiac event within a year post PCI procedure.

METHODS

This is a retrospective cohort study utilizing data from the National Cardiovascular Disease (NCVD)-PCI registry. The data collected (N = 28,007) were split into training set (n = 24,409) and testing set (n = 3598). Four predictive models (logistic regression [LR], random forest method, support vector machine [SVM], and artificial neural network) were developed and validated. The outcome on risk prediction were compared.

RESULTS

The demographic and clinical features of patients in the training and testing cohorts were similar. Patients had mean age ± standard deviation of 58.15 ± 10.13 years at admission with a male majority (82.66%). In over half of the procedures (50.61%), patients had chronic stable angina. Within 1 year of follow up mortality, target vessel revascularization (TVR), and composite event of mortality and TVR were 3.92%, 9.48%, and 12.98% respectively. LR was the best model in predicting mortality event within 1-year post-PCI (AUC: 0.820). SVM had the highest discrimination power for both TVR event (AUC: 0.720) and composite event of mortality and TVR (AUC: 0.720).

CONCLUSIONS

This study successfully identified optimal prediction models with the good discriminatory ability for mortality outcome and good discrimination ability for TVR and composite event of mortality and TVR with a simple machine learning framework.

Transradial intervention in dialysis patients undergoing percutaneous coronary intervention: a Japanese nationwide registry study

Aims

Transradial intervention (TRI) for percutaneous coronary intervention (PCI) is used to reduce periprocedural complications. However, its effectiveness and safety for patients on dialysis are not well established. We aimed to investigate the association of TRI with in-hospital complications in dialysis patients undergoing PCI.

Methods and results

We included 44 462 patients on dialysis who underwent PCI using Japanese nationwide PCI registry data (2019-21) regardless of acute or chronic coronary syndrome. Patients were categorized based on access site: TRI, transfemoral intervention (TFI). Periprocedural access site bleeding complication requiring transfusion was the primary outcome and in-hospital death, and other periprocedural complications were the secondary outcomes. Matched weighted analysis was performed for TRI and TFI. Here, 8267 (18.6%) underwent TRI, and 36 195 (81.4%) underwent TFI. Patients who received TRI were older and had lower rates of comorbidities than those who received TFI. Access site bleeding rate and in-hospital death were significantly lower in the TRI group (0.1% vs. 0.7%, P < 0.001; 1.8% vs. 3.2%, P < 0.001, respectively). After adjustment, TRI was associated with a lower risk of access site bleeding (odds ratio [OR] [95% confidence interval (CI)]: 0.19 [0.099-0.38]; P < 0.001) and in-hospital death (OR [95% CI]: 0.79 [0.65-0.96]; P = 0.02). Other periprocedural complications between TRI and TFI were not significantly different.

Conclusion

In patients undergoing dialysis and PCI, TRI had a lower risk of access site bleeding and in-hospital death than TFI. This suggests that TRI may be safer for this patient population.

Outcomes of Percutaneous Coronary Intervention for Protected versus Unprotected Left Main Coronary Artery Disease: Insights from the VA CART Program

Background

Practice patterns and outcomes of protected left main (PLM) and unprotected left main (ULM) percutaneous coronary intervention (PCI), as well as the differences between these types of PCI, are not well defined in real-world clinical practice.

Methods

Data collected from all Veteran Affairs (VA) catheterization laboratories participating in the Clinical Assessment Reporting and Tracking Program between 2009 and 2019. The analysis included 4,351 patients undergoing left main PCI, of which 1,306 pairs of PLM and ULM PCI were included in a propensity matched cohort. Patients and procedural characteristics were compared between PLM and ULM PCI. Temporal trends were also assessed. Peri-procedural and one-year major adverse cardiovascular events (MACE) were compared using cumulative incidence plots. The primary outcome was MACE outcomes at 1-year, which was defined as a composite of all-cause mortality, rehospitalization for myocardial infarction (MI), rehospitalization for stroke or urgent revascularization.

Results

ULM PCI patients in comparison to PLM PCI were older (71.5 vs 69.2; P < 0.001), more clinically complex and more likely to present with ACS. In the propensity matched cohort, radial access was used more often for ULM PCI (21% [273] vs. 14% [185], P < 0.001), and ULM PCI was more likely to involve the LM bifurcation (22% vs 14%; P = 0.003) and require mechanical circulatory support (10% [134] vs 1% [17]; P <0.001). One-year MACE occurred more frequently with ULM PCI compared to PLM PCI (22% [289] vs. 16% [215]; P = < 0.001) and all-cause mortality was also higher (16% [213] vs. 10% [125]; P = < 0.001). In the matched cohort there was a low incidence of rehospitalization for MI (4% [48] ULM vs. 4% [48] PLM; P = 1.000) or revascularization (7% [94] ULM vs. 6% [84] PLM; P = 0.485).

Conclusions

Veterans undergoing PLM PCI had better one-year outcomes than those undergoing ULM PCI, but in both groups there was a high rate of mortality and MACE at one-year despite a relatively low rate of MI or revascularization.

One-Year Survival for Developing Acute Kidney Injury in Adult Patients with AMI Cardiogenic Shock Receiving Venoarterial Extracorporeal Membrane Oxygenation

Objective

The incidence of cardiogenic shock cases treated with veno-arterial extracorporeal membrane oxygenation (VA-ECMO) support has been on the rise. Acute kidney injury (AKI) is a significant complication of cardiogenic shock and a frequent serious complication in patients requiring ECMO-supported therapy. AKI is strongly associated with unfavorable patient prognosis. However, there is a paucity of data on the influence of AKI on the prognosis of patients with acute myocardial infarction complicated by cardiogenic shock (AMI-CS) who are receiving ECMO support, particularly with regard to long-term outcomes.

Methods

This retrospective observational study included 103 patients in the People's Hospital of Guangxi Zhuang Autonomous Region from January 2017 and June 2022. AKI was defined according to Kidney Disease Improving Global Outcome (KDIGO) criteria. Cox regression and logistic regression were used to identify risk factors.

Results

In this study, the incidence of AKI was 63.11%, with AKI stage 1, 2, and 3 accounting for 21.36%, 12.62%, and 29.13%, respectively. Patients with severe AKI had significantly higher in-hospital mortality (43.33% vs 27.40%, P < 0.001), 30-day mortality (60.00% vs 31.51%, P = 0.001), and 1-year mortality (63.67% vs 34.25%, P<0.001) than those without severe AKI. Furthermore, severe AKI significantly increased the risk of one-year mortality (HR 10.816, CI 3.118-37.512, P<0.001). Baseline serum creatinine, baseline platelet, and active cardiopulmonary resuscitation were independent predictors of one-year mortality. In addition, baseline white blood cell count, baseline aspartate aminotransferase, baseline alanine aminotransferase (ALT), baseline serum creatinine, preoperative lactate, and postoperative mean arterial pressure were independent risk factors of severe AKI during hospitalization.

Conclusion

In patients with AMI-CS receiving ECMO support, AKI is highly prevalent. Development of severe AKI significantly increased the risk of one-year mortality.

Risk-adjusted management in catheterization procedures for non-ST-segment elevation myocardial infarction: A standard operating procedure pilot study

BACKGROUND

The effects of standardized risk-adjusted periprocedural management of cardiac catheterization procedures in Non-ST segment elevation myocardial infarction (NSTEMI) remain unknown. We implemented a standard operating procedure (SOP) specifying risk assessment (RA, using National Cardiovascular Data Registry (NCDR) risk models) and risk-adjusted management (RM, e.g. intensified monitoring) in 2018 and aimed to investigate staff SOP adherence and associations with patient outcomes.

METHODS AND RESULTS

All 430 invasively managed NSTEMI patients (mean age 72y; 70.9% male) in 2018 were analyzed for staff SOP adherence and in-hospital clinical outcomes. 207 patients (48.1%; RM+) received both RA and RM; 92 patients (21.4%; RM-) received RA but no RM; 131 patients (30.5%; RA-) received neither RA nor RM. Lower staff adherence to RA was associated with emergency settings (51.9% (RA-) vs. 22.1% (RA+); p<0.01), presentation in cardiogenic shock (17.6% (RA-) vs. 6.4% (RA+); p<0.01) and invasive mechanical ventilation (12.2% (RA-) vs. 3.3% (RA+); p<0.01). Early sheath removal (87.9% (RM+) vs. 56.5% (RM-); p<0.01) and intensified monitoring (p<0.01) were more frequent in the RM+ group. All-cause mortality was not different (1.4% (RM+) vs. 4.3% (RM-); p=0.13), but there were fewer major bleeding events with associated with RM (2.4% (RM+) vs. 12% (RM-); p<0.01), which remained independently associated with RM in a multivariate logistic regression model correcting for confounders (p<0.01).

CONCLUSION

In an all-comer patient cohort with NSTEMI, staff adherence to risk-adjusted periprocedural management was independently associated with fewer major bleeding events. Staff adherence to SOP-specified risk assessment was frequently neglected in more critical clinical situations.

Comparison of Outcomes of Elective Percutaneous Coronary Intervention between Complex and High-Risk Intervention in Indicated Patients (CHIP) versus Non-CHIP

AIMS

Complex and high-risk intervention in indicated patients (CHIP) is an emerging concept in the contemporary percutaneous coronary intervention (PCI). CHIP is known to consist three factors, namely, (1) patient factors, (2) complicated heart disease, and (3) complex PCI. However, it remains unclear whether additional CHIP factors further increase the incidence of complications in complex PCI. Thus, in this study, we aim to compare the incidence of complications among definite CHIP, possible CHIP, and non-CHIP in terms of complex PCI and to further investigate the association between CHIP and complications.

METHODS

The primary aim of this study was to determine the major complications in PCI. We included 989 PCI lesions and divided those into definite CHIP (n=140), possible CHIP (n=397), and the non-CHIP groups (n=452).

RESULTS

The incidence of major complications was noted to be the highest in the definite CHIP, followed by the possible CHIP, and lowest in the non-CHIP (p=0.001). The multivariate logistic regression analysis using a generalized estimating equation revealed definite CHIP (versus non-CHIP: odds ratio (OR) 2.099, 95% confidence interval (CI) 1.062-4.150, p=0.033) was significantly associated with major complications after controlling for confounding factors. Another multivariate logistic regression analysis revealed immunosuppressive drugs (OR 3.040, 95% CI 1.251-7.386, p=0.014), unstable hemodynamics (OR 5.753, 95% CI 1.217-27.201, p=0.027), and frailty (OR 2.039, 95% CI 1.108-3.751, p=0.022) were significantly associated with major complications among CHIP factors.

CONCLUSIONS

The incidence of major complications in complex PCI was determined to be the highest in the definite CHIP, followed by the possible CHIP and lowest in the non-CHIP. Thus, more attention should be given to the three components of CHIP to prevent major complications in complex PCI.

Clinical Use of CathPCI Registry Risk Score and Its Validation to Predict Long-Term Mortality

Risk models to estimate percutaneous coronary intervention (PCI) mortality have limited value in complex high-risk patients. However, it was improved by a recently developed bedside model to predict in-hospital mortality using data from the American College of Cardiology CathPCI Registry that included 706,263 patients. The median risk-standardized in-hospital mortality rate was 1.9%. In an attempt to validate this model in patients admitted because of acute coronary ischemia to predict in-hospital, 30-day, and 1-year mortality, we applied the proposed risk score to the study population of the Acute Coronary Syndrome Israeli Survey (ACSIS). This study was conducted for 2 months in 2018 and included all patients admitted to 25 coronary care units and cardiology departments in Israel. The ACSIS included 1,155 patients admitted because of acute myocardial infarction and who underwent PCI. In-hospital, 30-day, and 1-year mortality were 2.3%, 3.1%, and 6.2%, respectively. The CathPCI risk score yielded an area under the receiver operating characteristic curve of 0.96 (95% confidence interval [CI] 0.94 to 0.99) for in-hospital mortality; 0.96 (95% CI 0.94 to 0.98) for the 30-day mortality, and 0.88 (95% CI 0.83 to 0.93) for the 1-year mortality. The current model also included frail patients, and those with aortic stenosis, refractory shock, and after cardiac arrest. In conclusion, the CathPCI Registry risk score was validated using data from the ACSIS. Because the ACSIS population comprised patients with acute ischemia including those with high-risk features this model demonstrates a wider scope of application compared with previous ones. In addition, the model seems to be suitable to predict also the 30-day and 1-year mortality.

Health Status and Clinical Outcomes in Older Adults With Chronic Coronary Disease: The ISCHEMIA Trial

BACKGROUND

Whether initial invasive management in older vs younger adults with chronic coronary disease and moderate or severe ischemia improves health status or clinical outcomes is unknown.

OBJECTIVES

The goal of this study was to examine the impact of age on health status and clinical outcomes with invasive vs conservative management in the ISCHEMIA (International Study of Comparative Health Effectiveness with Medical and Invasive Approaches) trial.

METHODS

One-year angina-specific health status was assessed with the 7-item Seattle Angina Questionnaire (SAQ) (score range 0-100; higher scores indicate better health status). Cox proportional hazards models estimated the treatment effect of invasive vs conservative management as a function of age on the composite clinical outcome of cardiovascular death, myocardial infarction, or hospitalization for resuscitated cardiac arrest, unstable angina, or heart failure.

RESULTS

Among 4,617 participants, 2,239 (48.5%) were aged <65 years, 1,713 (37.1%) were aged 65 to 74 years, and 665 (14.4%) were aged ≥75 years. Baseline SAQ summary scores were lower in participants aged <65 years. Fully adjusted differences in 1-year SAQ summary scores (invasive minus conservative) were 4.90 (95% CI: 3.56-6.24) at age 55 years, 3.48 (95% CI: 2.40-4.57) at age 65 years, and 2.13 (95% CI: 0.75-3.51) at age 75 years (Pinteraction = 0.008). Improvement in SAQ Angina Frequency was less dependent on age (Pinteraction = 0.08). There were no age differences between invasive vs conservative management on the composite clinical outcome (Pinteraction = 0.29).

CONCLUSIONS

Older patients with chronic coronary disease and moderate or severe ischemia had consistent improvement in angina frequency but less improvement in angina-related health status with invasive management compared with younger patients. Invasive management was not associated with improved clinical outcomes in older or younger patients. (International Study of Comparative Health Effectiveness with Medical and Invasive Approaches [ISCHEMIA]; NCT01471522).

Development of Comorbidity Index for In-hospital Mortality for Patients Underwent Coronary Artery Revascularization

Background

For myocardial revascularization, coronary artery bypass grafting (CAGB) and percutaneous coronary intervention (PCI) are two common modalities but with high in-hospital mortality. A comorbidity index is useful to predict mortality or can be used with other covariates to develop point-scoring systems. This study aimed to develop specific comorbidity indices for patients who underwent coronary artery revascularization.

Methods

Patients who underwent CABG or PCI were identified in the National Inpatient Sample database between Q4 2015-2020. Patients of age<40 were excluded for congenital heart defects. Patients were randomly sampled into experimental (70%) and validation (30%) groups. Thirty-eight Elixhauser comorbidities were identified and included in multivariable regression to predict in-hospital mortality. Weight for each comorbidity was assigned and single indices, Li CABG Mortality Index (LCMI) and Li PCI Mortality Index (LPMI), were developed.

Results

Mortality prediction by LCMI approached adequacy ( c -statistic=0.691, 95% CI=0.682-0.701) and was comparable to multivariable regression with comorbidities ( c -statistic=0.685, 95% CI=0.675-0.694). LCMI prediction performed significantly better than Elixhauser Comorbidity Index (ECI) ( c -statistic=0.621, 95% CI=0.611-0.631) and can be further improved by adjusting age ( c -statistic=0.721, 95% CI=0.712-0.730). LPMI moderately predicted in-hospital mortality ( c -statistic=0.666, 95% CI=0.660-0.672) and performed significantly better than ECI ( c -statistic=0.610, 95% CI=0.604-0.616). LPMI performed better than the all-comorbidity multivariable regression ( c -statistic=0.658, 95% CI=0.652-0.663). After age adjustment, LPMI prediction was significantly increased and was approaching adequacy ( c -statistic=0.695, 95% CI=0.690-0.701).

Conclusions

LCMI and LPMI effectively predicted in-hospital mortality. These indices were validated and performed superior to ECI. The adjustment of age increased their predictive power to adequacy, implicating potential clinical application.

New Criteria to Identify Patients at Higher Risk for Cardiovascular Complications After Percutaneous Coronary Intervention

A universal definition to identify patients at higher risk of complications after percutaneous coronary intervention (PCI) is lacking. We aimed to validate a recently developed score to identify patients at increased risk of all-cause death after PCI. All consecutive patients from a large PCI registry not presenting with ST-elevation myocardial infarction or cardiogenic shock were included. Each patient was assigned a score obtained by summing the points associated with the following variables: age >80 years (3 points), dialysis (6 points), left ventricular ejection fraction <30% (2 points), and multivessel PCI (2 points). Patients were stratified in 3 groups: low risk (score 0), intermediate risk (score 2 to 3), or high risk (score ≥4). The primary outcome was all-cause death, and the secondary outcomes were major adverse cardiovascular events and major bleeding. Events were assessed at 1 year after PCI. Between January 2014 and December 2019, 12,689 patients underwent PCI. Compared with the 9,884 patients at low risk, those at intermediate and high risk had a fourfold (hazard ratio 3.99, 95% confidence interval 2.95 to 5.38) and ninefold (hazard ratio 9.55, 95% confidence interval 6.89 to 13.2) higher hazard for all-cause death at 1 year, respectively. The score had a good predictive value for all-cause death at 1 year (area under the curve 0.70). The risk of major adverse cardiovascular events and major bleeding increased consistently from the low- to the high-risk group. In conclusion, in patients who underwent PCI for stable ischemic heart disease or non-ST-elevation acute coronary syndrome, a score based on 4 variables well predicted the risk of all-cause death at 1 year.

Health Status Outcomes in Older Adults Undergoing Chronic Total Occlusion Percutaneous Coronary Intervention

Background Although chronic total occlusions (CTOs) are common in older adults, they are less likely to be offered CTO percutaneous coronary intervention for angina relief than younger adults. The health status impact of CTO percutaneous coronary intervention in adults aged ≥75 years has not been studied. We sought to compare technical success rates and angina-related health status outcomes at 12 months between adults aged ≥75 and <75 years in the OPEN-CTO (Outcomes, Patient Health Status, and Efficiency in Chronic Total Occlusion) registry. Methods and Results Angina-related health status was assessed with the Seattle Angina Questionnaire (score range 0-100, higher scores denote less angina). Technical success rates were compared using hierarchical modified Poisson regression, and 12-month health status was compared using hierarchical multivariable linear regression between adults aged ≥75 and <75 years. Among 1000 participants, 19.8% were ≥75 years with a mean age of 79.5±4.1 years. Age ≥75 years was associated with a lower likelihood of technical success (adjusted risk ratio=0.92 [95% CI, 0.86-0.99; P=0.02]) and numerically higher rates of in-hospital major adverse cardiovascular events (9.1% versus 5.9%, P=0.10). There was no difference in Seattle Angina Questionnaire Summary Score at 12 months between adults aged ≥75 and <75 years (adjusted difference=0.9 [95% CI, -1.4 to 3.1; P=0.44]). Conclusions Despite modestly lower success rates and higher complication rates, adults aged ≥75 years experienced angina-related health status benefits after CTO-percutaneous coronary intervention that were similar in magnitude to adults aged <75 years. CTO percutaneous coronary intervention should not be withheld based on age alone in otherwise appropriate candidates.

Impact of complex percutaneous coronary intervention features on clinical outcomes in patients with or without chronic kidney disease

BACKGROUND

Patients with chronic kidney disease (CKD) are at higher risk of ischemic and bleeding events after percutaneous coronary intervention (PCI). Complex PCI (CPCI) is associated with higher rates of ischemic complications. Whether CPCI confers an additive risk of adverse events in CKD patients is unclear.

METHODS

Patients who underwent PCI at a single tertiary-care-center between 2012 and 2019 were stratified by CKD status and CPCI. The primary outcome was major adverse cardiac events (MACE), a composite of all-cause death, myocardial infarction (MI), and target-vessel revascularization (TVR) at 1-year follow-up. Secondary outcomes included the individual components of the primary outcome and major bleeding.

RESULTS

Out of 15,071 patients, 4537 (30.1%) had CKD and 10,534 (69.9%) had no CKD. Patients undergoing CPCI were 1151 (25.4%) and 2983 (28.3%) in the two cohorts, respectively. At one year, CPCI compared with no CPCI was associated with higher risk of MACE in both CKD (Adj. HR 1.72, 95% confidence interval [CI] 1.45-2.06, p < 0.001) and no-CKD patients (Adj. hazard ratios [HR] 2.19, 95% CI 1.91-2.51, p < 0.001; p of interaction 0.057), determined by an excess of death, MI and TVR in CKD patients and of TVR and MI only in no-CKD. CPCI was related with a consistent increase of major bleeding in the CKD (Adj. HR 1.49, 95% CI 1.18-1.87, p < 0.001) and no-CKD group (Adj. HR 1.23, 95% CI 0.98-1.54, p = 0.071, p of interaction 0.206).

CONCLUSION

At 1-year follow-up, CPCI was associated with higher risk of MACE and major bleeding irrespective of concomitant CKD. CPCI predicted mortality in CKD patients only.

Development and validation of a nomogram predicting one-year mortality in patients undergoing percutaneous coronary intervention

OBJECTIVE

To formulate a nomogram to predict the risk of one-year mortality after percutaneous coronary intervention (PCI) based on a large-scale real-world Asian cohort.

METHODS

This study cohort included consecutive patients undergoing PCI in the National Center for Cardiovascular Diseases of China. The endpoint was all-cause mortality. Least absolute shrinkage and selection operator Cox regression and backward stepwise regression were used to select potential risk factors. A nomogram based on the predictors was accordingly constructed to predict one-year mortality. The performance of the nomogram was evaluated. Patients were stratified into low-, intermediate- and high-risk groups according to the tertile points in the nomogram and compared by the Kaplan-Meier analysis.

RESULTS

A total of 9603 individuals were included in this study and randomly divided into the derivation cohort (60%) and the validation cohort (40%). Six variables were selected to formulate the nomogram, including age, renal insufficiency, cardiac dysfunction, previous cerebrovascular disease, previous PCI, and TIMI 0-1 before PCI. The area under the curve of this nomogram regarding one-year mortality risks were 0.792 and 0.754 in the derivation cohort and validation cohort, respectively. Kaplan-Meier curve successfully stratified the patients according to three risk groups. This nomogram calibrated well and exhibited satisfactory clinical utility in the decision curve analysis.

CONCLUSIONS

This study developed and validated a simple-to-use nomogram predicting one-year mortality risk in Asian patients undergoing PCI and could help clinicians make risk-dependent decisions.

Multi-modal fusion model for predicting adverse cardiovascular outcome post percutaneous coronary intervention

Background.Clinical medicine relies heavily on the synthesis of information and data from multiple sources. However, often simple feature concatenation is used as a strategy for developing a multimodal machine learning model in the cardiovascular domain, and thus the models are often limited by pre-selected features and moderate accuracy.Method.We proposed a two-branched joint fusion model for fusing the 12-lead electrocardiogram (ECG) signal data with clinical variables from the electronic medical record (EMR) in an end-to-end deep learning architecture. The model follows the joint fusion scheme and learns complementary information from ECG and EMR. Retrospective data from the Mayo Clinic Health Systems across four sites for patients that underwent percutaneous coronary intervention (PCI) were obtained. Model performance was assessed by area under the receiver-operating characteristics (AUROC) and Delong's test.Results.The final cohort included 17,356 unique patients with a mean age of 67.2 ± 12.6 year (mean ± std) and 9,163 (52.7%) were male. The joint fusion model outperformed the ECG time-domain model with statistical margin. The model with clinical data obtained the highest AUROC for all-cause mortality (0.91 at 6 months) but the joint fusion model outperformed for cardiovascular outcomes - heart failure hospitalization and ischemic stroke with a significant margin (Delong's p < 0.05).Conclusion.To the best of our knowledge, this is the first study that developed a deep learning model with joint fusion architecture for the prediction of post-PCI prognosis and outperformed machine learning models developed using traditional single-source features (clinical variables or ECG features). Adding ECG data with clinical variables did not improve prediction of all-cause mortality as may be expected, but the improved performance of related cardiac outcomes shows that the fusion of ECG generates additional value.

Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries

Catheter-induced dissections (CID) of coronary arteries and/or the aorta are among the most dangerous complications of percutaneous coronary procedures, yet the data on their risk factors are anecdotal. Logistic regression and five more advanced machine learning techniques were applied to determine the most significant predictors of dissection. Model performance comparison and feature importance ranking were evaluated. We identified 124 cases of CID in electronic databases containing 84,223 records of diagnostic and interventional coronary procedures from the years 2000-2022. Based on the f1-score, Extreme Gradient Boosting (XGBoost) was found to have the optimal balance between positive predictive value (precision) and sensitivity (recall). As by the XGBoost, the strongest predictors were the use of a guiding catheter (angioplasty), small/stenotic ostium, radial access, hypertension, acute myocardial infarction, prior angioplasty, female gender, chronic renal failure, atypical coronary origin, and chronic obstructive pulmonary disease. Risk prediction can be bolstered with machine learning algorithms and provide valuable clinical decision support. Based on the proposed model, a profile of 'a perfect dissection candidate' can be defined. In patients with 'a clustering' of dissection predictors, a less aggressive catheter and/or modification of the access site should be considered.

Incidence and prognosis of late readmission after percutaneous coronary intervention

BACKGROUND

Early readmission (< 30 days) after percutaneous coronary intervention (PCI) is associated with a worse prognosis, but little is known regarding the causes and consequences of late readmission. The aim of the present study was to determine the incidence, causes, and prognosis of patients readmitted > 1 < 12-months after PCI (late readmission).

METHODS

Single-center retrospective cohort study of 743 consecutive post-PCI patients. Patient characteristics and follow-up data were collected by reviewing their electronic medical records and from standardized telephone interviews performed at 1 year and at the end of follow-up.

RESULTS

Of the 743 patients, 224 (30.14%) were readmitted 1-12 months after PCI, 109 due to chest pain (48.66%), and 115 for other reasons (51.34%). Hospital readmission was associated with lower survival rates of 77.6% vs. 98.3% at 24 months and 73.5% vs. 97.6% at 36 months (p < 0.001). Univariate predictors for late readmission were hypertension, older age, chronic kidney disease, lower left ventricular ejection fraction, and lower baseline hemoglobin concentration. Only baseline hemoglobin concentration was an independent predictor of late readmission (odds ratio: 0.867, 95% confidence interval: 0.778-0.966, p = 0.01). Readmission for chest pain portrayed a lower mortality rate compared to other causes, with survival rates of 90.2% vs. 50% at 36 months (p < 0.001).

CONCLUSIONS

Late hospital readmission after PCI is associated with a worse prognosis and is related to patient comorbidities. Readmission for chest pain is common and portrayed a more favorable prognosis, similar to patients not readmitted. A readily available parameter, baseline anemia, was the main predictor of late readmission.

Use of machine learning models to predict in-hospital mortality in patients with acute coronary syndrome

BACKGROUND

Cardiovascular diseases are a significant health burden with the prevalence increasing worldwide. Thus, a highly accurate assessment and prediction of death risk are crucial to meet the clinical demand. This study sought to develop and validate a model to predict in-hospital mortality among patients with the acute coronary syndrome (ACS) using nonlinear algorithms.

METHODS

A total of 2414 ACS patients were enrolled in this study. All samples were divided into five groups for cross-validation. The logistic regression (LR) model and XGboost model were applied to predict in-hospital mortality. The results of two models were compared between the variable set by the global registry of acute coronary events (GRACE) score and the selected variable set.

RESULTS

The in-hospital mortality rate was 3.5% in the dataset. Model performance on the selected variable set was better than that on GRACE variables: a 3% increase in area under the receiver operating characteristic (ROC) curve (AUC) for LR and 1.3% for XGBoost. The AUC of XGBoost is 0.913 (95% confidence interval [CI]: 0.910-0.916), demonstrating a better discrimination ability than LR (AUC = 0.904, 95% CI: 0.902-0.905) on the selected variable set. Almost perfect calibration was found in XGBoost (slope of predicted to observed events, 1.08; intercept, -0.103; p < .001).

CONCLUSIONS

XGboost modeling, an advanced machine learning algorithm, identifies new variables and provides high accuracy for the prediction of in-hospital mortality in ACS patients.

Complex, high-risk percutaneous coronary intervention types, trends, and in-hospital outcomes among different age groups: An insight from a national registry

BACKGROUND

Complex, high-risk percutaneous coronary intervention (PCI) (CHiP) is increasingly being undertaken in octogenarians. However, limited data exist on CHiP types, trends, and outcomes in the octogenarian.

METHODS

This is a retrospective cohort study from a national registry dataset on CHiP undertaken in patients with stable angina in England and Wales (January 2006 and December 2017) according to three age groups (group 1 [G1]: &lt; 65 years; group 2 [G2]: 65-79 years; and group 3 [G3]: ≥80 years).

RESULTS

Of 424,290 elective PCI procedures, 138,831 (33.0%) were CHiP [G1: 46,832 (33.7%); G2: 59,544 (42.9%); G3: 32,455 (23.4%)]. Among CHiP types, chronic total occlusion (CTO) (49.2%), prior coronary artery bypass graft (CABG) (30.4%), and severe vascular calcification (21.8%) were common in G1; prior CABG (42.9%), CTO (32.9%), and severe vascular calcifications (27%) were common in G2; prior CABG (15.8%), severe vascular calcification (15.5%), and chronic renal failure (11.1%) were common CHiP among the octogenarians. The older age groups had higher adjusted odds (aOR) for adverse outcomes [G2: mortality, aOR 1.7, 95% confidence interval (CI): (1.3-2.3); major bleeding, aOR 1.3, 95% CI (1.1-1.5); MACCE, aOR 1.2, 95% CI (1.0-1.3); G3: mortality, aOR 2.6, 95%CI (1.9-3.6); major bleeding, aOR 1.4, 95% CI (1.1-1.7); MACCE, aOR 1.3, 95% CI (1.1-1.5)].

CONCLUSION

There were significant differences in the types of CHiP cases undertaken and clinical outcomes across age groups.

Management of Coronary Complications

Coronary complications are increasingly rare but remain fatal if not managed promptly and effectively. We review the incidence, management, and prevention of the most serious coronary complications including acute vessel closure from dissection, no-reflow, thrombosis, and air embolism as well as mechanical complications including perforation, stent dislodgment, and atherectomy burr entrapment.

Predictors of Hospital Mortality Based on Primary Angioplasty Treatment: A Multicenter Case-Control Study

Fundamento

A estratificação do risco de morte dos pacientes no contexto da angioplastia primária (ATC) é fundamental.

Objetivo

Identificar os fatores relacionados ao desfecho morte em pacientes submetidos a ATC.

Métodos

Estudo de caso-controle, utilizando como fonte de dados um registro brasileiro. A associação entre cada variável e o desfecho óbito foi avaliada via modelo de regressão logística binária. Consideramos significativo p<0,05.

Resultados

Foram analisados 26.990 registros, sendo 18.834 (69,8%) do sexo masculino, com idade mediana de 61 (17) anos. Na análise multivariada, as principais variáveis relacionadas ao desfecho óbito com seus respectivos odds ratio e intervalos de confiança (IC) com nível de significância de 95% foram a idade avançada 70 - 79 anos (2,46; 1,64 - 3,79) e ≥ 80 anos (3,68; 2,38 - 5,81), p<0,001, classificação de Killip II (2,71; 1,92 - 3,83), Killip III (8,14; 5,67 - 11,64), Killip IV (19,83; 14,85 - 26,69), p<0,001, disfunção global acentuada do ventrículo esquerdo (VE) (3,63; 2,39 - 5,68), p<0,001 e ocorrência de infarto após a intervenção (5,01; 2,57- 9,46), p<0,001. O principal fator protetor foi o fluxo TIMI III pós-intervenção (0,18; 0,13 - 0,24), p<0,001, seguido do TIMI II (0,59; 0,41 - 0,86), p=0,005, sexo masculino (0,79; 0,64 - 0,98), p= 0,032, dislipidemia (0,69; 0,59 - 0,85), p<0,001 e número de lesões tratadas (0,86; 0,9 - 0,94), p<0,001.

Conclusão

Os preditores de mortalidade nos pacientes submetidos a ATC foram: classificação de Killip, reinfarto, idade, disfunção global acentuada do VE, sexo feminino e fluxo TIMI 0/I pós-intervenção.

Post-Cardiac Arrest PCI is Underutilized Among Cancer Patients: Machine Learning Augmented Nationally Representative Case-Control Study of 30 Million Hospitalizations

BACKGROUND

Cancer patients are less likely to undergo percutaneous coronary intervention (PCI) after cardiac arrest, although they demonstrate improved mortality benefit from the procedure. We produced the largest nationally representative analysis of mortality of cardiac arrest and PCI for patients with cancer versus non-cancer.

METHODS

Propensity score adjusted multivariable regression for mortality was performed in this case-control study of the United States' largest all-payer hospitalized dataset, the 2016 National Inpatient Sample. Regression models of mortality and PCI weighted by the complex survey design were fully adjusted for age, race, income, cancer metastases, NIS-calculated mortality risk by Diagnosis Related Group (DRG), acute coronary syndrome, and likelihood of undergoing PCI RESULTS: Of the 30,195,722 hospitalized adult patients, 15.43% had cancer, and 0.79% of the whole sample presented with cardiac arrest (of whom 20.57% underwent PCI). In fully adjusted regression analysis among patients with cardiac arrest, PCI significantly reduced mortality (OR 0.15, 95%CI 0.13-0.19; p<0.001) among patients with cancer greater than those without it (OR 0.21, 95%CI 0.20-0.23; p<0.001).

CONCLUSIONS

This nationally representative study suggests that post-cardiac arrest PCI is underutilized among patients with cancer despite its significant mortality reduction for such patients (independent of clinical acuity).

Multimorbidity and Mortality Models to Predict Complications Following Percutaneous Coronary Interventions

BACKGROUND

Previous percutaneous coronary intervention risk models were focused on single outcome, such as mortality or bleeding, etc, limiting their applicability. Our objective was to develop contemporary percutaneous coronary intervention risk models that not only determine in-hospital mortality but also predict postprocedure bleeding, acute kidney injury, and stroke from a common set of variables.

METHODS

We built risk models using logistic regression from first percutaneous coronary intervention for any indication per patient (n=19 322, 70.6% with acute coronary syndrome) using the Mayo Clinic registry from January 1, 2000 to December 31, 2016. Approval for the current study was obtained from the Mayo Foundation Institutional Review Board. Patients with missing outcomes (n=4183) and those under 18 (n=10) were removed resulting in a sample of 15 129. We built both models that included procedural and angiographic variables (Models A) and precatheterization model (Models B).

RESULTS

Death, bleeding, acute kidney injury, and stroke occurred in 247 (1.6%), 650 (4.3%), 1184 (7.8%), and 67 (0.4%), respectively. The C statistics from the test dataset for models A were 0.92, 0.70, 0.77, and 0.71 and for models B were 0.90, 0.67, 0.76, and 0.71 for in-hospital death, bleeding, acute kidney injury, and stroke, respectively. Bootstrap analysis indicated that the models were not overfit to the available dataset. The probabilities estimated from the models matched the observed data well, as indicated by the calibration curves. The models were robust across many subgroups, including women, elderly, acute coronary syndrome, cardiogenic shock, and diabetes.

CONCLUSIONS

The new risk scoring models based on precatheterization variables and models including procedural and angiographic variables accurately predict in-hospital mortality, bleeding, acute kidney injury, and stroke. The ease of its application will provide useful prognostic and therapeutic information to both patients and physicians.

Improved outcomes in patients with severely depressed LVEF undergoing percutaneous coronary intervention with contemporary practices

BACKGROUND

Contemporary practices for hemodynamically supported high-risk percutaneous coronary intervention have evolved over the last decade. This study sought to compare outcomes of the prospective, multicenter, PROTECT III study to historic patients treated with Impella in the PROTECT II randomized controlled trial.

METHODS

Of 1,134 patients enrolled in PROTECT III from March 2017 to March 2020, 504 were "PROTECT II-like" (met eligibility for PROTECT II randomized controlled trial) and are referred to as PROTECT III for comparative analysis. Major adverse cardiac and cerebrovascular events (MACCE), comprising all-cause mortality, stroke/transient ischemic attack, myocardial infarction, and repeat revascularization, were compared at hospital discharge and 90 days.

RESULTS

Compared with PROTECT II (N = 216), PROTECT III patients were less often Caucasian (77.1% vs 83.8%, P = .045), with less prior CABG (13.7% vs 39.4%; P < .001) and prior myocardial infarction (40.7% vs 69.3%; P < .001). More PROTECT III patients underwent rotational atherectomy (37.1% vs 14.8%, P < .001) and duration of support was longer (median 1.6 vs 1.3 hours; p<0.001), with greater improvement achieved in myocardial ischemia jeopardy scores (7.0±2.4 vs 4.4±2.9; P < .001) and SYNTAX scores (21.4±10.8 vs 15.7±9.5; P < .001). In-hospital bleeding requiring transfusion was significantly lower in PROTECT III (1.8% vs 9.3%; P < .001), as was procedural hypotension (2.2% vs 10.1%; P < .001) and cardiopulmonary resuscitation or ventricular arrhythmia (1.6% vs 6.9%; P < .001). At 90 days, MACCE was 15.1% and 21.9% in PROTECT III and PROTECT II, respectively (p=0.037). Following propensity score matching, Kaplan-Meier analysis showed improved 90-day MACCE rates in PROTECT III (10.4% vs 16.9%, P = .048).

CONCLUSIONS

The PROTECT III study demonstrates improved completeness of revascularization, less bleeding, and improved 90-day clinical outcomes compared to PROTECT II for Impella-supported high-risk percutaneous coronary intervention among patients with severely depressed LVEF.

Machine learning models for prediction of adverse events after percutaneous coronary intervention

An accurate prediction of major adverse events after percutaneous coronary intervention (PCI) improves clinical decisions and specific interventions. To determine whether machine learning (ML) techniques predict peri-PCI adverse events [acute kidney injury (AKI), bleeding, and in-hospital mortality] with better discrimination or calibration than the National Cardiovascular Data Registry (NCDR-CathPCI) risk scores, we developed logistic regression and gradient descent boosting (XGBoost) models for each outcome using data from a prospective, all-comer, multicenter registry that enrolled consecutive coronary artery disease patients undergoing PCI in Japan between 2008 and 2020. The NCDR-CathPCI risk scores demonstrated good discrimination for each outcome (C-statistics of 0.82, 0.76, and 0.95 for AKI, bleeding, and in-hospital mortality) with considerable calibration. Compared with the NCDR-CathPCI risk scores, the XGBoost models modestly improved discrimination for AKI and bleeding (C-statistics of 0.84 in AKI, and 0.79 in bleeding) but not for in-hospital mortality (C-statistics of 0.96). The calibration plot demonstrated that the XGBoost model overestimated the risk for in-hospital mortality in low-risk patients. All of the original NCDR-CathPCI risk scores for adverse periprocedural events showed adequate discrimination and calibration within our cohort. When using the ML-based technique, however, the improvement in the overall risk prediction was minimal.

One-year outcome after percutaneous coronary intervention in nonagenarians: Insights from the J-PCI OUTCOME registry

BACKGROUND

Nonagenarian patients who undergo percutaneous coronary intervention (PCI) are increasing, and a few previous studies have reported their long-term outcomes. However, differences in their long-term outcomes between generations remain unclear. This study aimed to investigate 1-year all-cause and cardiovascular (CV) mortality, and major adverse cardiovascular events (MACE; cardiovascular death, myocardial infarction, and stroke) of nonagenarian patients who underwent PCI compared with the other elder patients, using a nationwide registration system.

METHODS

The patient-level data registered between January 2017 and December 2017 was extracted from the J-PCI OUTCOME Registry endorsed by the Japanese Association of Cardiovascular Intervention and Therapeutics (CVIT). The one-year all-cause and cardiovascular (CV) mortality, MACE, and major bleeding events were identified.

RESULTS

Out of 40,722 patients over 60 years of age, 880 (2.1%) were nonagenarians. For nonagenarians, the 1-year mortality rate was substantial (13.5%). The MACE and CV death rates were also high (8.1%, and 6.8%, respectively) for nonagenarians, and these event rates were approximately 1.5 times higher in nonagenarians than octogenarians. Multivariate regression analysis showed that presentation with cardiogenic shock [hazard ratio (HR) 2.32; 95 confidence intervals (CI): 1.22-4.41], or cardiac arrest (HR 2.91; 90% CI: 1.28-6.62), and use of oral anticoagulants (HR 2.10; 90% CI: 1.07-4.12) were the predictors of 1-year MACE.

CONCLUSIONS

Even in the contemporary era, nonagenarians who have undergone PCI still face a considerably increased risk for adverse cardiovascular events that reduces long-term survival. In addition to having poorer lesion characteristics, adverse events, including death, MACEs, and major bleeding, occurred 1.5 times more frequently in nonagenarians than in octogenarians.

Thrombosis and Major Bleeding Risk After Primary PCI Among Patients With Multivessel Coronary Artery Disease

Background and Aim

This study aimed to develop and validate separate risk prediction models for thrombosis events (TEs) and major bleeding (MB) in patients with multivessel coronary artery lesions who had undergone primary percutaneous coronary intervention (PCI).

Methods and Results

Thrombosis events (TEs) were defined as the composite of myocardial infarction recurrence or ischemic cerebrovascular events, whereas MB was defined as the occurrence of bleeding academic research consortium (BARC) three or five bleeding. The derivation and validation cohorts comprised 2,976 patients who underwent primary PCI between January 2010 and June 2017. At a median follow-up of 3.07 years (1,122 days), TEs and MB occurred in 167 and 98 patients, respectively. Independent predictors of TEs were older age, prior PCI, non-ST elevated MI (NSTEMI), and stent thrombosis (ST). Independent predictors of MB were triple therapy at discharge, coronary artery bifurcation lesions, lesion restenosis, target lesion of the left main coronary artery, stent thrombosis, non-use of IABP during primary PCI, type A/B according to the American College of Cardiology classification of the coronary lesion, and PTCA. In the derivation and validation cohorts, the areas under the curve were 0.817 and 0.82 for thrombosis and 0.886 and 0.976 for bleeding, respectively. In the derivation cohort, high thrombotic risk (n = 755) was associated with higher 3-year incidence of TEs, major adverse cardiovascular events (MACEs), and all-cause death compared to low risk (n = 1,275) (p = 0.0022, 0.019, and 0.012, respectively). High bleeding risk (n = 1,675) was associated with higher incidence of bleeding, MACEs, and cardiac death compared to low risk (n = 355) (p < 0.0001).

Conclusion

Simple risk scores can be useful in predicting risks of ischemic and bleeding events after primary PCI, thereby stratifying thrombotic or MB risks and facilitating clinical decisions.

Defining Percutaneous Coronary Intervention Complexity and Risk: An Analysis of the United Kingdom BCIS Database 2006-2016

OBJECTIVES

The authors used the BCIS (British Cardiovascular Intervention Society) database to define the factors associated with percutaneous coronary intervention (PCI) procedural complexity.

BACKGROUND

Complex high-risk indicated percutaneous coronary intervention (CHIP-PCI) is an emerging concept that is poorly defined.

METHODS

The BCIS (British Cardiovascular Intervention Society) database was used to study all PCI procedures in the United Kingdom 2006-2016. A multiple logistic regression model was developed to identify variables associated with in-hospital major adverse cardiac or cerebrovascular events (MACCE) and to construct a CHIP score. The cumulative effect of this score on patient outcomes was examined.

RESULTS

A total of 313,054 patients were included. Seven patient factors (age ≥80 years, female sex, previous stroke, previous myocardial infarction, peripheral vascular disease, ejection fraction <30%, and chronic renal disease) and 6 procedural factors (rotational atherectomy, left main PCI, 3-vessel PCI, dual arterial access, left ventricular mechanical support, and total lesion length >60 mm) were associated with increased in-hospital MACCE and defined as CHIP factors. The mean CHIP score/case for all PCIs increased significantly from 1.06 ± 1.32 in 2006 to 1.49 ± 1.58 in 2016 (P < 0.001 for trend). A CHIP score of 5 or more was present in 2.5% of procedures in 2006 increasing to 5.3% in 2016 (P < 0.001 for trend). Overall in-hospital MACCE was 0.6% when the CHIP score was 0 compared with 1.2% with any CHIP factor present (P < 0.001). As the CHIP score increased, an exponential increase in-hospital MACCE was observed. The cumulative MACCE for procedures associated with a CHIP score 4+ or above was 3.2%, and for a CHIP score 5+ was 4.4%. All other adverse clinical outcomes were more likely as the CHIP score increased.

CONCLUSIONS

Seven patient factors and 6 procedural factors were associated with adverse in-hospital MACCE and defined as CHIP factors. Use of a CHIP score might be a future target for risk modification.

Contemporary Clinical and Coronary Anatomic Risk Model for 30-Day Mortality After Percutaneous Coronary Intervention

BACKGROUND

Percutaneous coronary intervention (PCI) procedures are increasing in clinical and anatomic complexity, likely increasing the calculated risk of mortality. There is need for a real-time risk prediction tool that includes clinical and coronary anatomic information that is integrated into the electronic medical record system.

METHODS

We assessed 70 503 PCIs performed in 73 Veterans Affairs hospitals from 2008 to 2019. We used regression and machine-learning strategies to develop a prediction model for 30-day mortality following PCI. We assessed model performance with and without inclusion of the Veterans Affairs SYNTAX score (Synergy Between Percutaneous Coronary Intervention With Taxus and Cardiac Surgery), an assessment of anatomic complexity. Finally, the discriminatory ability of the Veterans Affairs model was compared with the CathPCI mortality model.

RESULTS

The overall 30-day morality rate was 1.7%. The final model included 14 variables. Presentation status (salvage, emergent, urgent), ST-segment-elevation myocardial infarction, cardiogenic shock, age, congestive heart failure, prior valve disease, chronic kidney disease, chronic lung disease, atrial fibrillation, elevated international normalized ratio, and the Veterans Affairs SYNTAX score were all associated with increased risk of death, while increasing body mass index, hemoglobin level, and prior coronary artery bypass graft surgery were associated with lower risk of death. C-index for the development cohort was 0.93 (95% CI, 0.92-0.94) and for the 2019 validation cohort and the site validation cohort was 0.87 (95% CI, 0.83-0.92) and 0.86 (95% CI, 0.83-0.89), respectively. The positive likelihood ratio of predicting a mortality event in the top decile was 2.87% more accurate than the CathPCI mortality model. Inclusion of anatomic information in the model resulted in significant improvement in model performance (likelihood ratio test P<0.01).

CONCLUSIONS

This contemporary risk model accurately predicts 30-day post-PCI mortality using a combination of clinical and anatomic variables. This can be immediately implemented into clinical practice to promote personalized informed consent discussions and appropriate preparation for high-risk PCI cases.

Clinical Characteristics and Outcomes Among Patients Undergoing High-Risk Percutaneous Coronary Interventions by Single or Multiple Operators: Insights From the Veterans Affairs Clinical Assessment, Reporting, and Tracking Program

Background High-risk percutaneous coronary intervention (HR-PCI) is increasingly common among contemporary patients with coronary artery disease. Experts have advocated for a collaborative 2-operator approach to support intraprocedural decision-making for these complex interventions. The impact of a second operator on patient and procedural outcomes is unknown. Methods and Results Patients who underwent HR-PCI from 2015 to 2018 within the Veterans Affairs Healthcare System were identified. Propensity-matched cohorts were generated to compare the outcomes following HR-PCI performed by a single or multiple (≥2) operators. The primary end point was the 12-month rate of major adverse cardiovascular events. We identified 6672 patients who underwent HR-PCI during the study period; 6211 (93%) were treated by a single operator, and 461 (7%) were treated by multiple operators, with a nonsignificant trend toward increased multioperator procedures over time. A higher proportion of patients treated by multiple operators underwent left main (10% versus 7%, P=0.045) or chronic total occlusion intervention (11% versus 5%, P<0.001). Lead interventionalists participating in multioperator procedures practiced at centers with higher annual HR-PCI volumes (124±71.3 versus 111±69.2; standardized mean difference, 0.197; P<0.001) but otherwise performed a similar number of HR-PCI procedures per year (34.4±35.3 versus 34.7±30.7; standardized mean difference, 0.388; P=0.841) compared with their peers performing single-operator interventions. In a propensity-matched cohort, there was no significant difference in major adverse cardiovascular events (32% versus 30%, P=0.444) between patients who underwent single-operator versus multioperator HR-PCI. Adjusted analyses accounting for site-level variance showed no significant differences in outcomes. Conclusions Patients who underwent multioperator HR-PCI had similar outcomes compared with single-operator procedures. Further studies are needed to determine if the addition of a second operator offers clinical benefits to a subset of HR-PCI patients undergoing left main or chronic total occlusion intervention.

Popular procedures without evidence of benefit: A case study of percutaneous coronary intervention for stable coronary artery disease

Despite limited benefit, percutaneous coronary intervention (PCI) remains a common procedure that is often performed for uncertain or inappropriate indications in patients with stable coronary artery disease (CAD). PCI cases per capita have increased year-over-year in most European countries, and many have higher rates than the U.S. Meanwhile, first-line therapy such as optimal medical therapy (OMT) and lifestyle changes, continue to be under-utilized. This article reviews the evidence on use of PCI in stable CAD. Specifically, we analyzed randomized control trials, systematic reviews, appropriate use criteria, and professional society guidelines that examine the risks and benefits of PCI compared to OMT. We then highlight utilization patterns as well as interventions that better align current practice with evidence-based care.

In-Hospital Mortality for Inpatient Percutaneous Coronary Interventions in the United States

Cardiovascular mortality is substantially higher in rural communities compared with urban communities. Understanding if disparities in inpatient percutaneous coronary intervention (PCI) persist in the United States will help inform initiatives to improve cardiovascular health. Of the more than 7 million hospitalizations in the National Inpatient Sample (2016), we identified 80,793 unweighted hospitalizations for PCI using ICD-10 procedure codes. Using survey weights, these hospitalizations projected 371,040 US admissions for inpatient PCI. For the primary analysis, we determined the association between hospital urban-rural designation and in-hospital mortality after inpatient PCI. In the secondary analysis, we evaluated the association between teaching status and this outcome. Multivariable logistic regression models, adjusted for multiple risk factors and patient characteristics, were used. Of the 371,430 hospitalizations for inpatient PCI, there were 108.9 (±2.2) admissions per 100,000 US population from urban hospitals and 152.9 (±6.3) from rural hospitals. Of the urban hospitals, there were 77.7 (±1.9) admissions per 100,000 US population at teaching hospitals (71.7%) and 30.7 (±1.0) at urban nonteaching hospitals (28.3%). In-hospital mortality did not differ between urban and rural hospitals (1.8% urban vs 1.9% rural, adjusted odds ratio for rural compared with urban: 1.15 [95% confidence interval 0.98, 1.34], p = 0.08). In urban hospitals, however, in-hospital mortality was higher in nonteaching hospitals than in teaching hospitals (2.0% nonteaching vs 1.7% teaching, adjusted odds ratio for teaching compared with nonteaching: 1.17 [95% confidence interval 1.01, 1.36], p = 0.04). In conclusion, in-hospital mortality rates after inpatient PCI were similar between urban and rural hospitals in the United States. However, among urban hospitals, nonteaching hospitals had higher rates of in-hospital mortality after PCI. In conclusion, solutions to address disparities for inpatient PCI outcomes between teaching and nonteaching hospitals are needed.

Procedural characteristics and outcomes following chronic total occlusion coronary intervention: pooled analysis from 5 registries

BACKGROUND

Recent improvements in clinical skills, technology, and hardware have resulted in improved success rates with chronic total occlusion (CTO) percutaneous coronary intervention (PCI). We performed a study level pooled analysis from the five largest registries of percutaneous coronary intervention (PCI) of CTO.

RESEARCH DESIGN AND METHODS

We conducted pooled analysis of 9500 patients in registries and data on procedural characteristics, technical success, and MACCE was collected.

RESULTS

A total of 9500 patients were included in the analysis. Mean age was 65.4 years with previous CABG in 24.8%, reattempt procedure in 24.8% and mean JCTO score was 2.2. Final wiring strategy in hybrid algorithm-based registries was AWE in 40.8-58%, Retrograde in 24-35%, ADR in 16-25% and in Expert JCTO and EURO CTO was AWE in 72-75% and retrograde in 25-28%. Technical success was achieved in 87.8%. In hospital MACCE was 2.5% (95% CI: 1.8- 3.4%), mortality 0.44% (95% CI: 0.23-0.84%), stroke 0.2% (95% CI: 0.1-0.3%); myocardial infraction 1.6% (95% CI: 1.1-2.2%); and cardiac tamponade 0.8% (95% CI: 0.5 to 1.3%).

CONCLUSION

CTO PCI is currently performed with high technical success rates and low complication rates in experienced hands utilizing various techniques.

Trends in Use and Outcomes of Same-Day Discharge Following Elective Percutaneous Coronary Intervention

OBJECTIVES

The aims of this study were to describe trends and hospital variation in same-day discharge following elective percutaneous coronary intervention (PCI) and to evaluate the association between trends in same-day discharge and patient outcomes.

BACKGROUND

Insights on contemporary use of same-day discharge following elective PCI are limited.

METHODS

In a sequential cross-sectional analysis of 819,091 patients undergoing elective PCI at 1,716 hospitals in the National Cardiovascular Data Registry CathPCI Registry from July 1, 2009, to December 31, 2017, overall and hospital-level trends in same-day discharge were assessed. Among the 212,369 patients who linked to Centers for Medicare and Medicaid Services data, the association between same-day discharge and 30-day mortality and rehospitalization was assessed.

RESULTS

A total of 114,461 patients (14.0%) were discharged the same day as PCI. The proportion of patients with same-day discharge increased from 4.5% in the third quarter of 2009 to 28.6% in the fourth quarter of 2017. From 2009 to 2017, the rate of same-day discharge increased from 4.3% to 19.5% for femoral-access PCI and from 9.9% to 39.7% for radial-access PCI. Hospital-level variation in the use of same-day discharge persisted throughout (median odds ratio adjusted for year and radial access: 4.15). Risk-adjusted 30-day mortality did not change over time, while risk-adjusted rehospitalization decreased over time and more quickly for same-day discharge (P for interaction <0.001).

CONCLUSIONS

In the past decade, a large increase in the use of same-day discharge following elective PCI was not associated with worse 30-day mortality or rehospitalization. Hospital-level variation in same-day discharge may represent an opportunity to reduce costs without compromising patient outcomes.

Hb Levels and Sex Differences in Relation to Short-Term Outcomes in Patients With Acute Myocardial Infarction

Background: Women had worse outcomes after acute myocardial infarction (AMI), and physiologically, women had lower hemoglobin values. We examined whether there were sex-related differences in the relationship between hemoglobin levels and adverse outcomes in patients with acute myocardial infarction. Method: We conducted a post-hoc analysis of data from the Acute Coronary Syndrome Quality Improvement in Kerala (ACS-QUIK) Study. We explored the relationship between baseline hemoglobin level and 30-days adverse outcomes by logistic regression model, generalized additive model (GAM) and two-piecewise linear regression model. We used multiple imputation, based on five replications and a chained equation approach method in the R multiple imputation procedure, to account for missing data. The primary outcome were 30-day major adverse cardiovascular events (MACEs) defined as death, reinfarction, stroke, and major bleeding. The secondary outcomes were 30-day major bleeding, 30-day stroke and 30-day cardiovascular death (CVD death). Results: Twenty thousand, five hundred fifty-nine patients with AMI were included in our analysis. Baseline hemoglobin level was associated with major bleeding [OR: 0.74, 95%CI (0.60, 0.92) P < 0.01], CVD death [OR: 0.94, 95%CI (0.90, 0.99) P < 0.01], and MACEs [OR: 0.95, 95%CI (0.92, 0.99) P < 0.01]. There was no significant relationship between baseline hemoglobin level and stroke incidence in both men [OR: 1.02, 95%CI (0.90, 1.14) P = 0.77] and women [OR: 1.15, 95%CI (0.96, 1.37) P = 0.18]. Baseline hemoglobin level was associated with major bleeding [OR: 0.71, 95%CI (0.58, 0.85) P < 0.01] in male patients, however we did not find the same relationship in female patients [OR: 0.89, 95%CI (0.56, 1.41) P = 0.61]. GAM and two-piecewise linear regression model showed the relationships of hemoglobin level with major bleeding, CVD death, and MACEs were non-linear (non-linear P < 0.05), and the threshold value were 13, 14.8, and 14.3 g/dL for MACEs and CVD death, respectively. Conclusion: Baseline hemoglobin level was one of the independent predictors of prognosis in South Asia patients with acute myocardial infarction. Moreover, its impact on prognosis was largely different depending on the patients' sex.

Transradial Access for High-Risk Percutaneous Coronary Intervention: Implications of the Risk-Treatment Paradox

[Figure: see text].