A contemporary risk model for predicting 30-day mortality following percutaneous coronary intervention in England and Wales

Temporal trends of in-hospital mortality and its determinants following percutaneous coronary intervention in patients with acute coronary syndrome in England and Wales: A population-based study between 2006 and 2021

BACKGROUND

There is limited data around drivers of changes in mortality over time. We aimed to examine the temporal changes in mortality and understand its determinants over time.

METHODS

743,149 PCI procedures for patients from the British Cardiovascular Intervention Society (BCIS) database who were aged between 18 and 100 years and underwent Percutaneous Coronary Intervention (PCI) for Acute Coronary Syndrome (ACS) in England and Wales between 2006 and 2021 were included. We decomposed the contributing factors to the difference in the observed mortality proportions between 2006 and 2021 using Fairlie decomposition method. Multiple imputation was used to address missing data.

RESULTS

Overall, there was an increase in the mortality proportion over time, from 1.7% (95% CI: 1.5% to 1.9%) in 2006 to 3.1% (95% CI: 3.0% to 3.2%) in 2021. 61.2% of this difference was explained by the variables included in the model. ACS subtypes (percentage contribution: 14.67%; 95% CI: 5.76% to 23.59%) and medical history (percentage contribution: 13.50%; 95% CI: 4.33% to 22.67%) were the strongest contributors to the difference in the observed mortality proportions between 2006 and 2021. Also, there were different drivers to mortality changes between different time periods. Specifically, ACS subtypes and severity of presentation were amongst the strongest contributors between 2006 and 2012 while access site and demographics were the strongest contributors between 2012 and 2021.

CONCLUSIONS

Patient factors and the move towards ST-elevated myocardial infarction (STEMI) PCI have driven the short-term mortality changes following PCI for ACS the most.

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.

Preoperative Variables of 30-Day Mortality in Adults Undergoing Percutaneous Coronary Intervention: A Systematic Review

BACKGROUND AND AIM

Risk adjustment following percutaneous coronary intervention (PCI) is vital for clinical quality registries, performance monitoring, and clinical decision-making. There remains significant variation in the accuracy and nature of risk adjustment models utilised in international PCI registries/databases. Therefore, the current systematic review aims to summarise preoperative variables associated with 30-day mortality among patients undergoing PCI, and the other methodologies used in risk adjustments.

METHOD

The MEDLINE, EMBASE, CINAHL, and Web of Science databases until October 2022 without any language restriction were systematically searched to identify preoperative independent variables related to 30-day mortality following PCI. Information was systematically summarised in a descriptive manner following the Checklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies checklist. The quality and risk of bias of all included articles were assessed using the Prediction Model Risk Of Bias Assessment Tool. Two independent investigators took part in screening and quality assessment.

RESULTS

The search yielded 2,941 studies, of which 42 articles were included in the final assessment. Logistic regression, Cox-proportional hazard model, and machine learning were utilised by 27 (64.3%), 14 (33.3%), and one (2.4%) article, respectively. A total of 74 independent preoperative variables were identified that were significantly associated with 30-day mortality following PCI. Variables that repeatedly used in various models were, but not limited to, age (n=36, 85.7%), renal disease (n=29, 69.0%), diabetes mellitus (n=17, 40.5%), cardiogenic shock (n=14, 33.3%), gender (n=14, 33.3%), ejection fraction (n=13, 30.9%), acute coronary syndrome (n=12, 28.6%), and heart failure (n=10, 23.8%). Nine (9; 21.4%) studies used missing values imputation, and 15 (35.7%) articles reported the model's performance (discrimination) with values ranging from 0.501 (95% confidence interval [CI] 0.472-0.530) to 0.928 (95% CI 0.900-0.956), and four studies (9.5%) validated the model on external/out-of-sample data.

CONCLUSIONS

Risk adjustment models need further improvement in their quality through the inclusion of a parsimonious set of clinically relevant variables, appropriately handling missing values and model validation, and utilising machine learning methods.

Calibration plots for multistate risk predictions models

INTRODUCTION

There is currently no guidance on how to assess the calibration of multistate models used for risk prediction. We introduce several techniques that can be used to produce calibration plots for the transition probabilities of a multistate model, before assessing their performance in the presence of random and independent censoring through a simulation.

METHODS

We studied pseudo-values based on the Aalen-Johansen estimator, binary logistic regression with inverse probability of censoring weights (BLR-IPCW), and multinomial logistic regression with inverse probability of censoring weights (MLR-IPCW). The MLR-IPCW approach results in a calibration scatter plot, providing extra insight about the calibration. We simulated data with varying levels of censoring and evaluated the ability of each method to estimate the calibration curve for a set of predicted transition probabilities. We also developed evaluated the calibration of a model predicting the incidence of cardiovascular disease, type 2 diabetes and chronic kidney disease among a cohort of patients derived from linked primary and secondary healthcare records.

RESULTS

The pseudo-value, BLR-IPCW, and MLR-IPCW approaches give unbiased estimates of the calibration curves under random censoring. These methods remained predominately unbiased in the presence of independent censoring, even if the censoring mechanism was strongly associated with the outcome, with bias concentrated in low-density regions of predicted transition probability.

CONCLUSIONS

We recommend implementing either the pseudo-value or BLR-IPCW approaches to produce a calibration curve, combined with the MLR-IPCW approach to produce a calibration scatter plot. The methods have been incorporated into the "calibmsm" R package available on CRAN.

Same-day discharge after percutaneous coronary procedures-Structured review and comprehensive meta-analysis

INTRODUCTION

Percutaneous coronary intervention is a well-established revascularization strategy for patients with coronary artery disease. The safety and feasibility of performing these procedures on a same-day discharge basis for selected patients has been studied in a large number of mostly nonrandomized trials. An up to date literature review should focus on trials with radial access, representing the current standard for coronary procedures in Austria and other European countries.

METHODS

The aim of this consensus statement is to review the most recent evidence for the safety and feasibility of performing same-day discharge procedures in selected patients. A structured literature search was performed using prespecified search criteria, focusing on trials with radial access procedures.

RESULTS

A total of 44 clinical trials and 4 large meta-analyses were retrieved, spanning 21 years of clinical evidence from 2001 to 2022. The outcome data from a wide range of clinical settings were unanimous in showing no negative effect on early (24 h) or late (30 day) major adverse events after same-day discharge coronary procedures. Based on nine prospective trials a comprehensive meta-analysis was compiled. Using 1‑month major adverse events data the pooled odds ratio of same-day discharge versus overnight stay procedures was 0.66 (95% confidence interval, CI 0.35-01.24; p = 0.19; I2 0%), indicating a noninferiority in carefully selected patients.

CONCLUSION

Outcome data from same-day discharge coronary intervention trials with radial access confirm the robust safety profile showing no increase in the risk of major adverse events compared to overnight stay.

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.

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.

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.

Individualization of Duration of Dual Antiplatelet Therapy after Coronary Stenting: A Comprehensive, Evidence-Based Review

Dual antiplatelet therapy (DAPT), comprising aspirin and a P2Y12 receptor inhibitor, is the cornerstone of post-percutaneous coronary intervention treatment to prevent stent thrombosis and reduce the risk of adverse cardiovascular events. The selection of an optimal DAPT regimen, considering the interplay of various antiplatelet agents, patient profiles, and procedural characteristics, remains an evolving challenge. Traditionally, a standard duration of 12 months has been recommended for DAPT in most patients. While contemporary guidelines provide general frameworks, DAPT modulation with longer or shorter treatment courses followed by aspirin or P2Y12 inhibitor monotherapy are evolving towards an individualized strategy to optimize the balance between efficacy and safety. This review comprehensively examines the current landscape of DAPT strategies after coronary stenting, with a focus on emerging evidence for treatment individualization.

New York Risk Model and Simplified Risk Score for In-Hospital/30-Day Mortality for Percutaneous Coronary Intervention

Risk models and risk scores derived from those models require periodic updating to account for changes in procedural performance, patient mix, and new risk factors added to existing systems. No risk model or risk score exists for predicting in-hospital/30-day mortality for percutaneous coronary interventions (PCIs) using contemporary data. This study develops an updated risk model and simplified risk score for in-hospital/30-day mortality following PCI. To accomplish this, New York's Percutaneous Coronary Intervention Reporting System was used to develop a logistic regression model and a simplified risk score model for predicting in-hospital/30-day mortality and to validate both models based on New York data from the previous year. A total of 54,770 PCI patients from 2019 were used to develop the models. Twelve different risk factors and 27 risk factor categories were used in the models. Both models displayed excellent discrimination for the development and validation samples (range from 0.894 to 0.896) and acceptable calibration, but the full logistic model had superior calibration, particularly among higher-risk patients. In conclusion, both the PCI risk model and its simplified risk score model provide excellent discrimination and although the full risk model requires the use of a hand-held device for estimating individual patient risk, it provides somewhat better calibration, especially among higher-risk patients.

Developing prediction models to estimate the risk of two survival outcomes both occurring: A comparison of techniques

INTRODUCTION

This study considers the prediction of the time until two survival outcomes have both occurred. We compared a variety of analytical methods motivated by a typical clinical problem of multimorbidity prognosis.

METHODS

We considered five methods: product (multiply marginal risks), dual-outcome (directly model the time until both events occur), multistate models (msm), and a range of copula and frailty models. We assessed calibration and discrimination under a variety of simulated data scenarios, varying outcome prevalence, and the amount of residual correlation. The simulation focused on model misspecification and statistical power. Using data from the Clinical Practice Research Datalink, we compared model performance when predicting the risk of cardiovascular disease and type 2 diabetes both occurring.

RESULTS

Discrimination was similar for all methods. The product method was poorly calibrated in the presence of residual correlation. The msm and dual-outcome models were the most robust to model misspecification but suffered a drop in performance at small sample sizes due to overfitting, which the copula and frailty model were less susceptible to. The copula and frailty model's performance were highly dependent on the underlying data structure. In the clinical example, the product method was poorly calibrated when adjusting for 8 major cardiovascular risk factors.

DISCUSSION

We recommend the dual-outcome method for predicting the risk of two survival outcomes both occurring. It was the most robust to model misspecification, although was also the most prone to overfitting. The clinical example motivates the use of the methods considered in this study.

Outlier identification and monitoring of institutional or clinician performance: an overview of statistical methods and application to national audit data

BACKGROUND

Institutions or clinicians (units) are often compared according to a performance indicator such as in-hospital mortality. Several approaches have been proposed for the detection of outlying units, whose performance deviates from the overall performance.

METHODS

We provide an overview of three approaches commonly used to monitor institutional performances for outlier detection. These are the common-mean model, the 'Normal-Poisson' random effects model and the 'Logistic' random effects model. For the latter we also propose a visualisation technique. The common-mean model assumes that the underlying true performance of all units is equal and that any observed variation between units is due to chance. Even after applying case-mix adjustment, this assumption is often violated due to overdispersion and a post-hoc correction may need to be applied. The random effects models relax this assumption and explicitly allow the true performance to differ between units, thus offering a more flexible approach. We discuss the strengths and weaknesses of each approach and illustrate their application using audit data from England and Wales on Adult Cardiac Surgery (ACS) and Percutaneous Coronary Intervention (PCI).

RESULTS

In general, the overdispersion-corrected common-mean model and the random effects approaches produced similar p-values for the detection of outliers. For the ACS dataset (41 hospitals) three outliers were identified in total but only one was identified by all methods above. For the PCI dataset (88 hospitals), seven outliers were identified in total but only two were identified by all methods. The common-mean model uncorrected for overdispersion produced several more outliers. The reason for observing similar p-values for all three approaches could be attributed to the fact that the between-hospital variance was relatively small in both datasets, resulting only in a mild violation of the common-mean assumption; in this situation, the overdispersion correction worked well.

CONCLUSION

If the common-mean assumption is likely to hold, all three methods are appropriate to use for outlier detection and their results should be similar. Random effect methods may be the preferred approach when the common-mean assumption is likely to be violated.

In-Hospital Mortality of Index Percutaneous Coronary Intervention in Patients With and Without Prior Percutaneous Revascularization: A Single-Institution Analysis

Percutaneous coronary intervention (PCI) is increasingly performed for symptom relief and survival benefit, particularly in patients presenting with acute coronary syndromes. It remains controversial whether prior PCI, and specifically when index PCI is performed on previously treated lesion(s), affects peri-procedural and in-hospital mortality. We queried an institutional PCI registry for all unique patients undergoing PCI during a 4-year period and classified them as having had or not prior PCI. If prior PCI had occurred, we further defined index PCI as a target lesion (TLR) PCI or non-TLR PCI, according to lesion(s) treated during the prior PCI. Multivariable analysis was performed to identify predictors of in-hospital mortality. Prior PCI was an independent predictor of in-hospital survival or lower mortality (HR 0.41 [0.22-0.76], P = 0.004), together with lower age (per 5 years, HR 0.73 [0.66-0.82], P < 0.001) and elective PCI (HR 0.63 [0.58-0.70], P < 0.0001). Among prior PCI patients, TLR PCI was associated with higher mortality (HR 3.03 [1.05-8.33]. P = 0.045), while elective PCI status was associated with lower mortality (HR 0.10 [0.01-0.80], P = 0.03). This excess mortality was only present in non-elective PCI cases (P_INT = 0.02). We conclude that PCI mortality risk is decreased in patients with prior PCI, particularly when index PCI is performed electively on a lesion not previously treated.

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.

Outcomes of Percutaneous Coronary Intervention in Patients With Acquired Immunosuppression

There are limited data on the clinical outcomes of percutaneous coronary intervention (PCI) in patients with acquired immunosuppression who are frequently underrepresented in clinical trials. All PCI procedures between October 2015 and December 2018 in the Nationwide Inpatient Sample were retrospectively analyzed, stratified by immunosuppression status. Multivariable logistic regression models were performed to examine (1) the association between immunosuppression status and in-hospital outcomes, expressed as adjusted odds ratio (aOR) with 95% confidence intervals (CIs) and (2) predictors of mortality among patients with severe acquired immunosuppression. In this contemporary analysis of nearly 1.5 million PCI procedures, approximately 4% of patients who underwent PCI had acquired immunosuppression. Of these, chronic steroid use accounted for approximately half of the cohort who underwent PCI who had acquired immunosuppression, with the remainder divided between hematologic cancer, solid organ active malignancy, and metastatic cancer, with the latter group having the highest rates of composite of in-hospital mortality or stroke (9.3%) (mortality 7.5% and acute ischemic stroke 2.4%). In conclusion, immunosuppression was independently associated with increased adjusted odds of adverse clinical outcomes, specifically mortality or stroke (aOR 1.11, 95% CI 1.06 to 1.15, p <0.001) and in-hospital mortality (aOR 1.21, 95% CI 1.13 to 1.29, p <0.001), with outcomes dependent on the cause of immunosuppression.

Management of Acute Coronary Syndrome in Cancer Patients: It's High Time We Dealt with It

Cancer patients have an increased risk of cardiovascular disease and, notably, a significant prevalence of acute coronary syndrome (ACS). It has been shown that an elevated presence of cardiovascular risk factors in this setting leads to an interaction between these two conditions, influencing their therapeutic strategies and contributing to higher mortality. Nonetheless, cancer patients have generally not been evaluated in ACS trials, so that the treatment in these cases is still not fully known. We reviewed the current literature and discussed the best management for these very high-risk patients. The treatment strategy must be tailored based on the cancer type and stage, balancing thrombotic and bleeding risks. When the prognosis is longer than six months, especially if a clinical instability coexists, patients with ACS and cancer should be referred for percutaneous coronary intervention (PCI) as soon as possible. Moreover, an invasive strategy should be preferred in STEMI patients as well as in NSTEMI patients who are considered as high risk. On the contrary, in clinically stable NSTEMI patients, a conservative non-invasive strategy could be adopted, especially in cases of a poor life expectancy and/or of high risk of bleeding. Drug-Eluting-Stents (DES) should be the first choice if an invasive strategy is adopted. Conservative therapy could instead be considered in cancer patients with more stable CAD at an increased risk of major bleeding complications. However, the duration of dual antiplatelet therapy (DAPT) with aspirin and clopidogrel is recommended, but it should be as short as possible, whereas triple antithrombotic therapy is non-advised because it significantly increases the risk of bleeding. ACS management among cancer patients should be based on an accurate evaluation of the risk of thrombosis and bleeding. Future studies focused on choosing optimal strategies in tumor patients with ACS should be performed to treat this subset of patients better.

Cardiac audit, data and registries: evolution of a national programme

The UK is one of the few countries in the world with national registries that record key statistics across a broad range of cardiovascular disorders. The British Cardiovascular Society and its affiliated groups have played a central role in the development of these registries and continue to provide clinical oversight to the present day. Seven of the UK's national registries are now integrated under the management of the National Institute for Cardiovascular Outcomes Research (NICOR) that currently holds records on nearly 6.5 million episodes of care since 1990. This represents a substantial data resource for national audit that has driven up standards of cardiovascular care in the UK with a palpable impact on patient outcomes. The registries have also spawned an impressive programme of research providing novel insights into the epidemiology of cardiovascular disease. Linkage with other datasets and international collaborations create the environment for new outputs, new opportunities for 'big data' research and new ways of performing clinical trials. As the centenary of the British Cardiac Society (now British Cardiovascular Society) approaches, its role in the development of the UK's cardiovascular audits can be counted as one of its outstanding achievements.

Revascularisation strategies in patients with significant left main coronary disease during the COVID-19 pandemic

Background

There are limited data on the impact of the COVID‐19 pandemic on left main (LM) coronary revascularisation activity, choice of revascularisation strategy, and post‐procedural outcomes.

Methods

All patients with LM disease (≥50% stenosis) undergoing coronary revascularisation in England between January 1, 2017 and August 19, 2020 were included (n = 22,235), stratified by time‐period (pre‐COVID: 01/01/2017–29/2/2020; COVID: 1/3/2020–19/8/2020) and revascularisation strategy (percutaneous coronary intervention (PCI) vs. coronary artery bypass grafting (CABG). Logistic regression models were performed to examine odds ratio (OR) of 1) receipt of CABG (vs. PCI) and 2) in‐hospital and 30‐day postprocedural mortality, in the COVID‐19 period (vs. pre‐COVID).

Results

There was a decline of 1,354 LM revascularisation procedures between March 1, 2020 and July 31, 2020 compared with previous years' (2017–2019) averages (−48.8%). An increased utilization of PCI over CABG was observed in the COVID period (receipt of CABG vs. PCI: OR 0.46 [0.39, 0.53] compared with 2017), consistent across all age groups. No difference in adjusted in‐hospital or 30‐day mortality was observed between pre‐COVID and COVID periods for both PCI (odds ratio (OR): 0.72 [0.51. 1.02] and 0.83 [0.62, 1.11], respectively) and CABG (OR 0.98 [0.45, 2.14] and 1.51 [0.77, 2.98], respectively) groups.

Conclusion

LM revascularisation activity has significantly declined during the COVID period, with a shift towards PCI as the preferred strategy. Postprocedural mortality within each revascularisation group was similar in the pre‐COVID and COVID periods, reflecting maintenance in quality of outcomes during the pandemic. Future measures are required to safely restore LM revascularisation activity to pre‐COVID levels.

Differential impact of type 1 and type 2 diabetes mellitus on outcomes among 1.4 million US patients undergoing percutaneous coronary intervention

BACKGROUND

The aim was to determine the impact of diabetes mellitus (DM) on outcomes after percutaneous coronary intervention (PCI). There is limited data on the impact of DM and its subtypes among patients who underwent PCI during hospitalization.

METHODS

All PCI hospitalizations from the National Inpatient Sample (October 2015-December 2018) were stratified by the presence and subtype of DM. Multivariable logistic regression was performed to determine the adjusted odds ratios (aOR) of in-hospital adverse outcomes in type 1 DM (T1DM) and type 2 DM (T2DM) compared to no-DM.

RESULTS

Out of 1,363,800 individuals undergoing PCI, 12,640 (0.9%) had T1DM and 539,690 (39.6%) had T2DM. T1DM patients had increased aOR of major adverse cardiovascular and cerebrovascular events (MACCE) (1.26, 95%CI 1.17-1.35), mortality (1.56, 95%CI 1.41-1.72), major bleeding (1.63, 95%CI 1.45-1.84), and stroke (1.75, 95%CI 1.51-2.02), while T2DM patients had only increased aOR of MACCE (1.02, 95%CI 1.01-1.04), mortality (1.10, 95%CI 1.08-1.13) and stroke (1.22, 95%CI 1.18-1.27), compared to no-DM patients. However, both T1DM and T2DM had lower aOR of cardiac complications (0.87, 95%CI 0.77-0.97 and 0.87, 95%CI 0.85-0.89, respectively), in comparison to no-DM patients. When accounting for the indication, both DM subgroups had higher aOR of MACCE, mortality, and stroke compared to no-DM patients in the acute coronary syndrome setting (p < 0.001, for all), while only increased aOR of stroke (1.59, 95%CI 1.17-2.15 for T1DM and 1.12, 95%CI 1.05-1.20 for T2DM) persisted in the elective setting.

CONCLUSIONS

Patients with DM who have undergone PCI during hospitalization are more likely to experience adverse in-hospital outcomes, and T1DM patients are a particularly high-risk cohort.

The ACIRA Registry: A Regional Tool to Improve the Healthcare Pathway for Patients Undergoing Percutaneous Coronary Interventions and Coronary Angiographies in the French Aquitaine Region: Study Design and First Results

BACKGROUND

In France, there is a lack of information about practices and pathways of coronary angiographies and percutaneous coronary interventions (PCI). We present the design and the first results of the ACIRA registry, the goal of which is to answer questions about quality, security, appropriateness, efficiency of, and access to interventional cardiology (IC) healthcare pathway in the French Aquitaine region.

METHODS

The ACIRA registry is an on-going, multicenter, prospective, exhaustive, scalable, and nominative cohort study of patients who undergo coronary angiographies or percutaneous coronary intervention in any of the catheterization laboratories. The data related to hospitalizations and procedures are directly extracted from hospital information systems. In-hospital mortality, readmissions, and cardiovascular morbidity are collected from the French hospital medical information system database. An identity management system has been implemented to create the patient health care pathway.

RESULTS

From January 1, 2012, to June 30, 2018, 147,136 procedures performed on 106,005 patients have been included in the ACIRA registry.

CONCLUSIONS

ACIRA has shown its ability to study the patient IC healthcare pathway, up to 1 year after the procedure. Nominative data enable the linkage between clinical and medico-administrative databases and possible supplementary data collection. The use of existing databases allowed us to limit patients lost to follow-up, prevent the double entry of data, improve data quality, and reduce the operating costs. The prospect of linkage with the French National Health Data System may offer promising opportunities for future medical research projects and for developing collaboration and benchmarking with other IC registries abroad.

Estimation of required sample size for external validation of risk models for binary outcomes

Risk-prediction models for health outcomes are used in practice as part of clinical decision-making, and it is essential that their performance be externally validated. An important aspect in the design of a validation study is choosing an adequate sample size. In this paper, we investigate the sample size requirements for validation studies with binary outcomes to estimate measures of predictive performance (C-statistic for discrimination and calibration slope and calibration in the large). We aim for sufficient precision in the estimated measures. In addition, we investigate the sample size to achieve sufficient power to detect a difference from a target value. Under normality assumptions on the distribution of the linear predictor, we obtain simple estimators for sample size calculations based on the measures above. Simulation studies show that the estimators perform well for common values of the C-statistic and outcome prevalence when the linear predictor is marginally Normal. Their performance deteriorates only slightly when the normality assumptions are violated. We also propose estimators which do not require normality assumptions but require specification of the marginal distribution of the linear predictor and require the use of numerical integration. These estimators were also seen to perform very well under marginal normality. Our sample size equations require a specified standard error (SE) and the anticipated C-statistic and outcome prevalence. The sample size requirement varies according to the prognostic strength of the model, outcome prevalence, choice of the performance measure and study objective. For example, to achieve an SE < 0.025 for the C-statistic, 60–170 events are required if the true C-statistic and outcome prevalence are between 0.64–0.85 and 0.05–0.3, respectively. For the calibration slope and calibration in the large, achieving SE < 0.15 would require 40–280 and 50–100 events, respectively. Our estimators may also be used for survival outcomes when the proportion of censored observations is high.

Primary percutaneous coronary intervention in nonagenarians: is it worthwhile?

Background

Previous studies have demonstrated the feasibility of primary percutaneous coronary intervention (PPCI) in carefully selected nonagenarians. Although current guidelines recommend immediate revascularization in patients with ST elevation myocardial infarction (STEMI) it remains unclear whether PPCI reduces mortality in nonagenarians. The objective of this study is to compare mortality in nonagenarians presenting via the PPCI pathway who undergo coronary intervention, versus those who are managed medically.

Methods and results

A total of 111 consecutive nonagenarians who presented to our tertiary center via the PPCI pathway between July 2013 and December 2018 with myocardial infarction were included. Clinical and angiographic details were collected alongside data on all-cause mortality. The final diagnosis was STEMI in 98 (88.3%) and NSTEMI in 13 (11.7%). PPCI was performed in 42 (37.8%), while 69 (62.2%) were medically managed. A significant number of the medically managed cohort had atrial fibrillation (23.2% vs 2.4% p = 0.003) and presented with a completed infarct (43.5% vs 4.8% p = 0.001). Other baseline and clinical variables were well matched in both groups. There was a trend towards increased 30-day mortality in the medically managed group (40.6% vs 23.8% p = 0.07). Kaplan Meier survival analysis demonstrated a significant difference in survival by 3 years (48.1% vs 21.7% p = 0.01). This was the case even when those with completed infarcts were excluded (44.3% vs 14.6%, p = 0.01).

Conclusion

In this series of selected nonagenarians presenting with acute myocardial infarction, those undergoing PPCI appeared to have a lower mortality compared to those managed medically.

Adoption of same day discharge following elective left main stem percutaneous coronary intervention

BACKGROUND

This study sought to investigate the safety and feasibility of same day discharge (SDD) practice and compare clinical outcomes to patients admitted for overnight stay (ON) undergoing elective left main stem (LMS) percutaneous coronary intervention (PCI). ON observation is still widely practiced in highly complex PCI as the standard of care, with no previous data comparing clinical outcomes in patients undergoing LMS PCI.

METHODS

We analysed 6452 patients undergoing elective LMS PCI between 2007 and 2014 in England and Wales. Multiple logistic regressions and the BCIS risk model were used to study association between SDD and 30 day mortality.

RESULTS

SDD rates almost doubled from 19.9% in 2007 to 39.8% in 2014 for all LMS procedures and increased from 20.7% to 41.4% for unprotected LMS cases during the same study period. There was a significant increase in procedural complexity with higher use of rotational atherectomy, longer stents and multivessel PCI. SDD was not associated with increased 30 day mortality (OR 0.70 95%CI 0.30-1.65) in the overall LMS PCI cohort and the results were similar in unprotected LMS (OR 0.48 95%CI 0.17-1.41) and those requiring ON stay (OR 0.58 95%CI 0.25-1.34).

CONCLUSIONS

We did not find evidence that SDD is not safe or feasible in highly complex LMS PCI procedures despite increasing procedural complexity with no significant increase in 30 day mortality rates.

Percutaneous coronary intervention in octogenarians: A risk scoring system to predict 30-day outcomes in the elderly

OBJECTIVE

Octogenarians are a high-risk group presenting for percutaneous coronary intervention (PCI). We aimed to create a 30-day mortality risk model for octogenarians presenting with both acute coronary syndrome (ACS) and chronic stable angina (CSA), using comprehensive mandatory UK data submissions to the UK National database.

BACKGROUND

Octogenarians are a high-risk group presenting for percutaneous coronary intervention, and decisions on whether or not to undertake intervention in this cohort can be challenging. The increasing number of octogenarians in the general population means they represent an important high-risk subgroup of patients.

METHODS

The data group consisted of 425,897 PCI procedures undertaken in the UK between 2008 and 2012 during which time there was comprehensive data linkage to mortality via the Office of National Statistics. Of these procedures, 44,221 (10.4%) were in patients aged ≥80. These comprised the model group. Logistic regression was used to create a predictive score which ultimately consisted of the following weightings: age 80-89 (n = 1); age > 90 (n = 2); unstable angina/non-ST-elevation myocardial infraction (NSTEMI) (n = 1); STEMI (n = 2); creatinine >200 mmol/L (n = 1); preprocedural ventilation (n = 1); left ventricular ejection fraction <30% (n = 1); cardiogenic shock (n = 2). Multiple imputation was used to account for missing data.

RESULTS

The patient cohort was divided into a derivation (n = 22,072) and a validation dataset (n = 22,071). Receiver operating characteristic analyses were used to derive the area-under-the-curve to assess properties of the score. The scoring system generated an AUC 0.83, (95% CI 0.80-0.85) suggesting high sensitivity and specificity. Scores of 1-4 were associated with good survival but scores ≥5 were associated with an estimated likelihood of death within 30 days of ≥40%.

CONCLUSIONS

This octogenarian risk score maybe a useful tool to determine the chance of a successful outcome in elderly patients presenting for PCI.

Current Understanding of the Role of Frailty in Cardiovascular Disease

The elderly population is increasing because of increasing life expectancy, and the prevalence of frailty increases with age. Frailty commonly coexists with cardiovascular diseases (CVDs), such as coronary artery disease (CAD), heart failure (HF), aortic stenosis (AS), and atrial fibrillation (AF). Frail patients who undergo revascularization for CAD have higher complication rates; those with HF have a high prevalence of poor outcomes, and those with AF are vulnerable to increased stroke incidence. Moreover, frailty and asymptomatic severe AS were independent factors for mortality. The presence of frailty can lead to poor clinical outcomes, and frailty has been identified as a risk factor for mortality. Thus, the identification of frail patients who are at higher risks of disability and adverse clinical outcomes is important. In this review, the relationship between frailty and CVD is appraised and optimal treatments for frail patients are discussed.

Rotational atherectomy and same day discharge: Safety and growth from a national perspective

OBJECTIVES

We explore whether same day discharge (SDD) is a feasible and safe practice following rotational atherectomy (ROTA) treatment during elective percutaneous coronary intervention (PCI), and examine which baseline characteristics are independently associated with SDD.

BACKGROUND

SDD following elective ROTA PCI is not recommended as per the recent SCAI consensus. However, reports show it is practiced and no previous study has evaluated its safety and feasibility.

METHODS

Our dataset included 4,591 patients undergoing elective ROTA PCI in England & Wales within an 8-years period. Independent associations with SDD were quantified via a multiple logistic regression model and the BCIS 30-day mortality risk model was used to evaluate the safety of SDD.

RESULTS

The majority of elective ROTA PCI cases remain at the hospital for overnight (ON) observation, although SDD rates increased substantially from 6.7% in 2007 to 35.5% in 2014. The use of glycoprotein IIb/IIIa antagonists, Q wave AMI, left main PCI and valvular heart disease were independently associated with ON, while patients operated underwent transradial PCI were more likely to be SDD (OR = 1.77, 95% CI [1.45-2.15]). Over the study period, observed mortality rates were not significantly higher than those expected from the BCIS risk model.

CONCLUSIONS

Our findings did not show superiority of the ON strategy over SDD for higher risk cases undergoing elective ROTA PCI, in terms of 30-day mortality. This is the first study to examine the safety of SDD after elective ROTA PCI and more should follow.

British Cardiovascular Intervention Society registry framework: a quality improvement initiative on behalf of the National Institute of Cardiovascular Outcomes Research (NICOR)

The British Cardiovascular Intervention Society (BCIS) percutaneous coronary intervention (PCI) registry is hosted by the National Institute of Cardiovascular Outcomes Research (NICOR) at Bart's Heart Centre and collects clinical characteristics, indications, procedural details, and outcomes of all patients undergoing PCI in the UK. The data are used for audit and research to monitor and improve PCI practices and patient outcomes. Bespoke live data analysis and structured monthly reports are used to provide real-time feedback to all participating hospitals about the provision of care. Risk-adjusted analyses are used as a quality metric and benchmarking PCI practices. The consecutive patients undergoing PCI in all PCI performing hospitals in the UK from 1994 to present. One hundred and thirteen variables encompassing patient demographics, indication, procedural details, complications, and in-hospital outcomes are recorded. Prospective data are collected electronically and encrypted before transfer to central database servers. Data are validated locally and further range checks, sense checks, and assessments of internal consistency are applied during data uploads. Analyses of uploaded data including an assessment of data completeness are provided to all hospitals for validation, with repeat validation rounds prior to public reporting. Endpoints are in-hospital PCI complications, bleeding and mortality. All-cause mortality is obtained via linkage to the Office of National Statistics. No other linkages are available at present. Available for research by application to NICOR at http://www.nicor.org.uk/ using a data sharing agreement.

Evaluation of the DAPT Score in Patients Who Undergo Percutaneous Coronary Intervention in England and Wales

This study aims to evaluate the temporal changes in DAPT score and determine whether there is an association between DAPT score and mortality. We analyzed all patients who underwent PCI in England and Wales 2007-2014. Statistical analyses were performed evaluating the DAPT score according to ≥2 and <2 cutoffs. Trends in DAPT score and logistic regressions were used to determine the association between DAPT score and 30 day, 1 year and 3 year mortality. A total of 243,440 patients were included in the analysis and the proportion of patients with DAPT score ≥ 2 was 35.6% (n = 86,550). The trend in DAPT score ≥ 2 showed an overall decline over time from 38.5% in 2007 to 34.5% in 2014. In more recent years, patients were older and a greater proportion were diabetic and had myocardial infarction on presentation and there was a significant decline in patients receiving paclitaxel stent (23.7% in 2007 to 0.2% in 2014). Patients with DAPT score ≥ 2 were more likely to be male, have previous CABG and have glycoprotein IIB/IIIa inhibitors. At 3 year follow up there was a significant difference in death compared DAPT ≥ 2 vs <2 (5.2% vs 5.5%, p < 0.001). DAPT score ≥ 2 was associated with reduced mortality at 1 year (OR 0.87 95%CI 0.82-0.92, p < 0.001) and 3 years (OR 0.82 95%CI 0.79-0.86, p < 0.001) after adjustments. These findings suggest that the DAPT score classifies 1 in 3 patients as having scores ≥2 and these patients have reduced odds of long-term mortality.

Acute myocardial infarction treatments and outcomes in 6.5 million patients with a current or historical diagnosis of cancer in the USA

Aims

The aim of this study is to evaluate temporal trends, treatment, and clinical outcomes of patients who present with an acute myocardial infarction (AMI) and have a current or historical diagnosis of cancer, according to cancer type and presence of metastases.

Methods and results

Data from 6 563 255 patients presenting with an AMI between 2004 and 2014 from the US National Inpatient Sample (NIS) database were analysed. A total of 5 966 955 had no cancer, 186 604 had current cancer, and 409 697 had a historical diagnosis of cancer. Prostate, breast, colon, and lung cancer were the four most common types of cancer. Patients with cancer were older with more comorbidities. Differences in invasive treatment were noted, 43.9% received percutaneous coronary intervention (PCI) in patients without cancer, whilst only 21.0% of patients with lung cancer received PCI. Lung cancer was associated with the highest in-hospital mortality [odds ratio (OR) 2.71, 95% confidence interval (CI) 2.62–2.80], major adverse cardiovascular and cerebrovascular complications (OR 2.38, 95% CI 2.31–2.45), and stroke (OR 1.91, 95% CI 1.80–2.02), while colon cancer was associated with highest risk of bleeding (OR 2.82, 95% CI 2.68–2.98). Irrespective of the type of cancer, presence of metastasis was associated with worse in-hospital outcomes, and historical cancer did not adversely impact on survival (OR 0.90, 95% CI 0.89–0.91).

Conclusion

A concomitant cancer diagnosis is associated with a conservative medical management strategy for AMI, and worse clinical outcomes, compared to patients without cancer. Survival and clinical outcomes in the context of AMI vary significantly according to the type of cancer and metastasis status. The management of this high-risk group is challenging and requires a multidisciplinary and patient-centred approach to improve their outcomes.

Contributors to the Growth of Same Day Discharge After Elective Percutaneous Coronary Intervention

Background:

Financial pressures for reducing hospitalization costs have driven to a move toward same day discharge (SDD) following uncomplicated percutaneous coronary intervention. The UK healthcare system has transitioned to predominantly SDD for elective percutaneous coronary intervention. This study aimed to examine patient’s clinical, procedural, and institutional characteristics that are associated with the increased adoption of SDD adoption over time in the United Kingdom and determine whether these vary by region.

Methods:

The data were derived from the British Cardiovascular Intervention Society including all the elective percutaneous coronary intervention from 2007 to 2014 in the United Kingdom. We structured 8 meaningful groups of variables, and their relative importance was obtained by decomposing the R 2 in each study year.

Results:

The relative importance of Strategic Health Authorities was substantially higher than all other factors every year, with some reduction over time, from 49.2% (95% CI, 45.4%–52.4%) in 2007 to 43.4% (95% CI, 39.9%–46.6%) in 2014. Center volume followed with 8.95% (95% CI, 7.0%–10.9%) to 19.8% (95% CI, 16.7%–22.4%). Between patients’ clinical and procedural characteristics, pharmacology and access site had the highest relative importance values, from 14.3% (95% CI, 12.1%–16.4%) to 7.1% (95% CI, 5.5%–8.8%) and from 3.6% (95% CI, 2.3%–5.1%) to 11.8% (95% CI, 9.4%–14.3%), respectively. Relative importance of different groups varied differently across Strategic Health Authorities.

Conclusions:

Growth of SDD was mainly associated with regional characteristics, while subcontributors varied substantially between different regions. Standardized guidelines would provide more homogenous adoption of SDD nationally. This analysis might be of wider interest in healthcare systems slower in SDD adoption.

Antithrombotic Therapy for Percutaneous Cardiovascular Interventions: From Coronary Artery Disease to Structural Heart Interventions

Percutaneous cardiovascular interventions have changed dramatically in recent years, and the impetus given by the rapid implementation of novel techniques and devices have been mirrored by a refinement of antithrombotic strategies for secondary prevention, which have been supported by a significant burden of evidence from clinical studies. In the current manuscript, we aim to provide a comprehensive, yet pragmatic, revision of the current available evidence regarding antithrombotic strategies in the domain of percutaneous cardiovascular interventions. We revise the evidence regarding antithrombotic therapy for secondary prevention in coronary artery disease and stent implantation, the complex interrelation between antiplatelet and anticoagulant therapy in patients undergoing percutaneous coronary intervention with concomitant atrial fibrillation, and finally focus on the novel developments in the secondary prevention after structural heart disease intervention. A special focus on treatment individualization is included to emphasize risk and benefits of each therapeutic strategy.

The association between the public reporting of individual operator outcomes with patient profiles, procedural management, and mortality after percutaneous coronary intervention: an observational study from the Pan-London PCI (BCIS) Registry using an interrupted time series analysis

AIMS

The public reporting of healthcare outcomes has a number of potential benefits; however, unintended consequences may limit its effectiveness as a quality improvement process. We aimed to assess whether the introduction of individual operator specific outcome reporting after percutaneous coronary intervention (PCI) in the UK was associated with a change in patient risk factor profiles, procedural management, or 30-day mortality outcomes in a large cohort of consecutive patients.

METHODS AND RESULTS

This was an observational cohort study of 123 780 consecutive PCI procedures from the Pan-London (UK) PCI registry, from January 2005 to December 2015. Outcomes were compared pre- (2005-11) and post- (2011-15) public reporting including the use of an interrupted time series analysis. Patients treated after public reporting was introduced were older and had more complex medical problems. Despite this, reported in-hospital major adverse cardiovascular and cerebrovascular events rates were significantly lower after the introduction of public reporting (2.3 vs. 2.7%, P < 0.0001). Interrupted time series analysis demonstrated evidence of a reduction in 30-day mortality rates after the introduction of public reporting, which was over and above the existing trend in mortality before the introduction of public outcome reporting (35% decrease relative risk 0.64, 95% confidence interval 0.55-0.77; P < 0.0001).

CONCLUSION

The introduction of public reporting has been associated with an improvement in outcomes after PCI in this data set, without evidence of risk-averse behaviour. However, the lower reported complication rates might suggest a change in operator behaviour and decision-making confirming the need for continued surveillance of the impact of public reporting on outcomes and operator behaviour.

Risk stratification model for in-hospital death in patients undergoing percutaneous coronary intervention: a nationwide retrospective cohort study in Japan

OBJECTIVES

To provide an accurate adjustment for mortality in a benchmark, developing a risk prediction model from its own dataset is mandatory. We aimed to develop and validate a risk model predicting in-hospital mortality in a broad spectrum of Japanese patients after percutaneous coronary intervention (PCI).

DESIGN

A retrospective cohort study was conducted.

SETTING

The Japanese-PCI (J-PCI) registry includes a nationally representative retrospective sample of patients who underwent PCI and covers approximately 88% of all PCIs in Japan.

PARTICIPANTS

Overall, 669 181 patients who underwent PCI between January 2014 and December 2016 in 1018 institutes.

MAIN OUTCOME MEASURES

In-hospital death.

RESULTS

The study population (n=669 181; mean (SD) age, 70.1(11.0) years; women, 24.0%) was divided into two groups: 50% of the sample was used for model derivation (n=334 591), while the remaining 50% was used for model validation (n=334 590). Using the derivation cohort, both 'full' and 'preprocedure' risk models were developed using logistic regression analysis. Using the validation cohort, the developed risk models were internally validated. The in-hospital mortality rate was 0.7%. The preprocedure model included age, sex, clinical presentation, previous PCI, previous coronary artery bypass grafting, hypertension, dyslipidaemia, smoking, renal dysfunction, dialysis, peripheral vascular disease, previous heart failure and cardiogenic shock. Angiographic information, such as the number of diseased vessel and location of the target lesion, was also included in the full model. Both models performed well in the entire validation cohort (C-indexes: 0.929 and 0.926 for full and preprocedure models, respectively) and among prespecified subgroups with good calibration, although both models underestimated the risk of mortality in high-risk patients with the elective procedure.

CONCLUSIONS

These simple models from a nationwide J-PCI registry, which is easily applicable in clinical practice and readily available directly at the patients' presentation, are valid tools for preprocedural risk stratification of patients undergoing PCI in contemporary Japanese practice.

Temporal validation of the CT-PIRP prognostic model for mortality and renal replacement therapy initiation in chronic kidney disease patients

Background

A classification tree model (CT-PIRP) was developed in 2013 to predict the annual renal function decline of patients with chronic kidney disease (CKD) participating in the PIRP (Progetto Insufficienza Renale Progressiva) project, which involves thirteen Nephrology Hospital Units in Emilia-Romagna (Italy). This model identified seven subgroups with specific combinations of baseline characteristics that were associated with a differential estimated glomerular filtration rate (eGFR) annual decline, but the model’s ability to predict mortality and renal replacement therapy (RRT) has not been established yet.

Methods

Survival analysis was used to determine whether CT-PIRP subgroups identified in the derivation cohort (n = 2265) had different mortality and RRT risks. Temporal validation was performed in a matched cohort (n = 2051) of subsequently enrolled PIRP patients, in which discrimination and calibration were assessed using Kaplan-Meier survival curves, Cox regression and Fine & Gray competing risk modeling.

Results

In both cohorts mortality risk was higher for subgroups 3 (proteinuric, low eGFR, high serum phosphate) and lower for subgroups 1 (proteinuric, high eGFR), 4 (non-proteinuric, younger, non-diabetic) and 5 (non-proteinuric, younger, diabetic). Risk of RRT was higher for subgroups 3 and 2 (proteinuric, low eGFR, low serum phosphate), while subgroups 1, 6 (non-proteinuric, old females) and 7 (non-proteinuric, old males) showed lower risk. Calibration was excellent for mortality in all subgroups while for RRT it was overall good except in subgroups 4 and 5.

Conclusions

The CT-PIRP model is a temporally validated prediction tool for mortality and RRT, based on variables routinely collected, that could assist decision-making regarding the treatment of incident CKD patients. External validation in other CKD populations is needed to determine its generalizability.

The influence of Elixhauser comorbidity index on percutaneous coronary intervention outcomes

BACKGROUND

Clinical outcomes with respect to the evolution of comorbidity burden in national cohorts of patients undergoing PCI have not been reported.

OBJECTIVES

We sought to explore the association between comorbidity burden and periprocedural outcomes in patients treated with PCI in the National Inpatient Sample.

METHODS

6,601,526 PCI procedures were identified between 2004 and 2014 and comorbidities were defined by the Elixhauser classification system (ECS) consisting of 30 comorbidity measures. Endpoints included in-hospital mortality, periprocedural complications, length of stay and cost. Patients were classified based on their ECS in five categories (ECS I < 0, ECS II = 0, ECS III = 1-5, ECS IV = 6-13, and ECS V ≥ 14).

RESULTS

Patients with a score over 13 had a fivefold increase in the odds of mortality (OR: 5.13, 95% CI: 4.76-5.54), major bleeding (OR: 11.46, 95% CI: 10.66-12.33) and doubled the hospitalization costs ($31,452 vs $17.566).

CONCLUSIONS

Our study of over six million PCI procedures demonstrates that patients with the greatest comorbid burden (as defined by an ECS of >13) have a fivefold increase risk of in-hospital mortality, a fourfold increase in in-hospital periprocedural complications and an 11-fold increase in major bleeding events once differences in baseline patient characteristics are adjusted for. In addition, ECS significantly impacts the length of stay and doubles the healthcare costs. Comorbid burden is an important predictor of poor outcomes after PCI and should be considered as part of the decision-making processes in patients undergoing PCI.

Dual Antiplatelet Therapy Duration: Reconciling the Inconsistencies

Dual antiplatelet therapy (DAPT) prevents recurrent ischemic events after an acute coronary syndrome (ACS) as well as stent thrombosis (ST) in patients with prior stent implantation. Nevertheless, these benefits are counterbalanced by a significant bleeding hazard, which is directly related to the treatment duration. Although DAPT has been extensively studied in numerous clinical trials, optimal treatment duration is still debated, mostly because of apparent inconsistencies among studies. Shortened treatment duration of 6 or 3 months was shown to mitigate bleeding risk compared with consensus-grounded 12-month standard duration, without any apparent excess of ischemic events. However, recent trials showed that a >12-month course of treatment reduces ischemic events but increases bleeding compared with 12 months. The inconsistent benefit of a longer DAPT course compared with shorter treatment durations is puzzling, and requires a careful appraisal of between-studies differences. We sought to summarize the existing evidence aiming at reconciling apparent inconsistencies among these studies, as well as thoroughly discuss the possible increased risk of fatal events associated with long-term DAPT. Benefits and risks of prolonging or shortening DAPT duration will be discussed, with a focus on treatment individualization. Finally, we will provide an outlook for possible future directions in the field.

Temporal Changes in Co-Morbidity Burden in Patients Having Percutaneous Coronary Intervention and Impact on Prognosis

This study aims to evaluate the impact of co-morbidity burden on outcomes in patients who undergo percutaneous coronary intervention (PCI). We used the Nationwide Inpatient Sample to identify all PCI procedures undertaken in the United States from 2004 to 2014. We then determined co-morbidity burden for each patient record based on the Charlson Co-morbidity Score. Multivariable logistic regression models were used to examine the association between co-morbidity burden and in-hospital mortality other in-hospital complications. A total of 6,601,526 PCI procedures were included in the analysis. Overall co-morbidity burden increased over time, with severe co-morbidity burden (defined as a CCI score ≥3) increasing from 5.3% in 2004 to 14.2% in 2014 (p <0.0001). After adjustment for confounding factors increasing co-morbidity burden was independently associated with increased odds of in-hospital mortality, complications, length of hospital stay, and total cost of hospitalization post PCI. A CCI score of 1 was independently associated with an increase in the odds of in hospital mortality (odds ratio [OR] 1.19 [95% confidence interval [CI] 1.15 to 1.25]), a score of 2 associated with an almost 1.5-fold increase (OR 1.41 [95% CI 1.34 to 1.48]) and a score of ≥3 a 2-fold increase (OR 1.96 [95% CI 1.86 to 2.07]) compared with no co-morbid burden (CCI score of 0). In conclusion, our results show that co-morbid burden is independently associated with increased risk of in-hospital mortality, in-hospital complications, length of stay, and healthcare costs.

Total Center Percutaneous Coronary Intervention Volume and 30-Day Mortality: A Contemporary National Cohort Study of 427 467 Elective, Urgent, and Emergency Cases

BACKGROUND

The relationship between procedural volume and prognosis after percutaneous coronary intervention (PCI) remains uncertain, with some studies finding in favor of an inverse association and some against. This UK study provides a contemporary reassessment in one of the few countries in the world with a nationally representative PCI registry.

METHODS AND RESULTS

A nationwide cohort study was performed using the national British Cardiovascular Intervention Society registry. All adult patients undergoing PCI in 93 English and Welsh NHS hospitals between 2007 and 2013 were analyzed using hierarchical modeling with adjustment for patient risk. Of 427 467 procedures (22.0% primary PCI) in 93 hospitals, 30-day mortality was 1.9% (4.8% primary PCI). 87.1% of centers undertook between 200 and 2000 procedures annually. Case mix varied with center volume. In centers with 200 to 399 PCI cases per year, a smaller proportion were PCI for ST-segment-elevation myocardial infarction (8.4%) than in centers with 1500 to 1999 PCI cases per year (24.2%), but proportionally more were for ST-segment-elevation myocardial infarction with cardiogenic shock (8.4% versus 4.3%). For the overall PCI cohort, after risk adjustment, there was no significant evidence of worse, or better, outcomes in lower volume centers from our own study, or in combination with results from other studies. For primary PCI, there was also no evidence for increased or decreased mortality in lower volume centers.

CONCLUSIONS

After adjustment for differences in case mix and clinical presentation, this study supports the conclusion of no trend for increased mortality in lower volume centers for PCI in the UK healthcare system.

CLINICAL TRIAL REGISTRATION

https://www.clinicaltrials.gov. Unique identifier: NCT02184949.

Development and validation of a clinical risk score to predict mortality after percutaneous coronary intervention

OBJECTIVE

To develop and validate a contemporary clinical risk score to predict mortality after percutaneous coronary intervention (PCI).

METHODS

Using data collected from patients undergoing PCI at the South Yorkshire Cardiothoracic Centre, Sheffield, UK, between January 2007 and September 2013, a risk score was developed to predict mortality. Logistic regression was used to evaluate the effect of each variable upon 30-day mortality. A backwards stepwise logistic regression model was then used to build a predictive model. The results were validated both internally and externally with data from Manchester Royal Infirmary, UK. 30-Day mortality status was determined from the UK Office of National Statistics.

RESULTS

The development data set comprised 6522 patients from Sheffield. Five risk factors, including cardiogenic shock, procedural urgency, history of renal disease, diabetes mellitus and age, were statistically significant to predict 30-day mortality. The risk score was validated internally on a further 3290 patients from Sheffield and externally on 3230 patients from Manchester. The discrimination of the model was high in the development (C-statistic=0.82, 95% CI 0.79 to 0.85), internal (C-statistic=0.81, 95% CI 0.76 to 0.86) and external (C statistics=0.90, 95% CI 0.87 to 0.93) cohorts. There was no significant difference between observed and predicted mortality in any group.

CONCLUSION

This contemporary risk score reliably predicts 30-day mortality after PCI using a small number of clinical variables obtainable prior to the procedure, without knowledge of the coronary anatomy.