Publications

The duration and type of dual antiplatelet therapy (DAPT) prescribed to patients after percutaneous coronary intervention (PCI) involves carefully balancing reduced ischemia and increased bleeding risk for individual patients. Whereas multiple bleeding risk scores exist, the performance of these models to predict long-term bleeding in the setting of DAPT across different settings and populations is unclear. Therefore, we performed a systematic review and meta-analysis to compare the performance of current bleeding risk prediction scores for predicting major long-term bleeding events in patients on DAPT post-PCI. Based on a search of MEDLINE (January 1, 1946 to March 3, 2017) and EMBASE (January 1, 1974 to March 3, 2017) for studies published in the English language, we identified 10 published studies of 11 risk unique risk prediction models across a wide variety of settings. Area under the receiver operating characteristic curve (AUC) was used to measure discrimination, when available. Our findings reveal that the prediction models created to date demonstrate only modest accuracy, with the reported AUCs ranging from 0.54 to 0.89; aggregated AUC 0.68 (95% confidence intervals 0.65 to 0.72). Although only 5 studies (50%) reported measures of calibration, the reported models were reasonably well calibrated. Only 3 models (33%) were externally validated. Meta-regression demonstrated lack of influence by age (p = 0.99) or length of follow up (p = 0.42). Sensitivity analysis did not significantly change the results. Novel prediction models are warranted to aid in maximizing the benefit of DAPT after PCI while minimizing harm.

Few studies have examined rates and causes of short-term readmissions among adults across age and insurance types. We compared rates, characteristics, and costs of 30-day readmission after all-cause hospitalizations across insurance types in the US. We retrospectively evaluated alive patients ≥18 years old, discharged for any cause, 1/1/13-11/31/13, 2006 non-federal hospitals in 21 states in the Nationwide Readmissions Database. The primary stratification variable of interest was primary insurance. Comorbid conditions were assessed based on Elixhauser comorbidities, as defined by administrative billing codes. Additional measures included diagnoses for index hospitalizations leading to rehospitalization. Hierarchical multivariable logistic regression models, with hospital site as a random effect, were used to calculate the adjusted odds of 30-day readmissions by age group and insurance categories. Cost and discharge estimates were weighted per NRD procedures to reflect a nationally representative sample. Diagnoses for index hospitalizations leading to rehospitalization were determined. Among 12,533,551 discharges, 1,818,093 (14.5%) resulted in readmission within 30 days. Medicaid insurance was associated with the highest adjusted odds ratio (AOR) for readmission both in those ≥65 years old (AOR 1.12, 95%CI 1.10-1.14; p <0.001), and 45-64 (AOR 1.67, 95% CI 1.66-1.69; p < 0.001), and Medicare in the 18-44 group (Medicare vs. private insurance: AOR 1.99, 95% CI 1.96-2.01; p <0.001). Discharges for psychiatric or substance abuse disorders, septicemia, and heart failure accounted for the largest numbers of readmissions, with readmission rates of 24.0%, 17.9%, 22.9% respectively. Total costs for readmissions were 50.7 billion USD, highest for Medicare (29.6 billion USD), with non-Medicare costs exceeding 21 billion USD. While Medicare readmissions account for more than half of the total burden of readmissions, costs of non-Medicare readmissions are nonetheless substantial. Medicaid patients have the highest odds of readmission in individuals older than age 44, commonly due to hospitalizations for psychiatric illness and substance abuse disorders. Medicaid patients represent a population at uniquely high risk for readmission.

BACKGROUND: In 2010, New York State began excluding selected patients with cardiac arrest and coma from publicly reported mortality statistics after percutaneous coronary intervention. We evaluated the effects of this exclusion on rates of coronary angiography, revascularization, and mortality among patients with acute myocardial infarction and cardiac arrest.

METHODS AND RESULTS: Using statewide hospitalization files, we identified discharges for acute myocardial infarction and cardiac arrest January 2003 to December 2013 in New York and several comparator states. A difference-in-differences approach was used to evaluate the likelihood of coronary angiography, revascularization, and in-hospital mortality before and after 2010. A total of 26 379 patients with acute myocardial infarction and cardiac arrest (5619 in New York) were included. Of these, 17 141 (65%) underwent coronary angiography, 12 183 (46.2%) underwent percutaneous coronary intervention, and 2832 (10.7%) underwent coronary artery bypass grafting. Before 2010, patients with cardiac arrest in New York were less likely to undergo percutaneous coronary intervention compared with referent states (adjusted relative risk, 0.79; 95% confidence interval, 0.73-0.85; P<0.001). This relationship was unchanged after the policy change (adjusted relative risk, 0.82; 95% confidence interval, 0.76-0.89; interaction P=0.359). Adjusted risks of in-hospital mortality between New York and comparator states after 2010 were also similar (adjusted relative risk, 0.94; 95% confidence interval, 0.87-1.02; P=0.152 for post- versus pre-2010 in New York; adjusted relative risk, 0.88; 95% confidence interval, 0.84-0.92; P<0.001 for comparator states; interaction P=0.103).

CONCLUSIONS: Exclusion of selected cardiac arrest cases from public reporting was not associated with changes in rates of percutaneous coronary intervention or in-hospital mortality in New York. Rates of revascularization in New York for cardiac arrest patients were lower throughout.

BACKGROUND: Off-label magnetic resonance imaging (MRI) for patients with cardiac implantable electrical devices has been limited owing to concerns about safety and unclear diagnostic and prognostic utility.

OBJECTIVE: The purpose of this study was to define major and minor adverse events with off-label MRI scans.

METHODS: We prospectively evaluated patients with non-MRI-conditional cardiac implantable electrical devices referred for MRI scans under a strict clinical protocol. The primary safety outcome was incidence of major adverse events (loss of pacing, inappropriate shock or antitachycardia pacing, need for system revision, or death) or minor adverse events (inappropriate pacing, arrhythmias, power-on-reset events, heating at the generator site, or changes in device parameters at baseline or at 6 months).

RESULTS: A total of 189 MRI scans were performed in 123 patients (63.1% [78] men; median age 70 ± 18.5 years; 56.9% [70] patients with implantable cardioverter-defibrillators; 33.3% [41] pacemaker-dependent patients) predominantly for brain or spinal conditions. A minority of scans (22.7% [43]) were performed for urgent or emergent indications. Major adverse events were rare: 1 patient with loss of pacing, no deaths, or system revisions (overall rate 0.5%; 95% confidence interval 0.01-2.91). Minor adverse events were similarly rare (overall rate 1.6%; 95% confidence interval 0.3-4.6). Nearly all studies (98.4% [186]) were interpretable, while 75.1% [142] were determined to change management according to the prespecified criteria. No clinically significant changes were observed in device parameters acutely after MRI or at 6 months as compared with baseline across all patient and device categories.

CONCLUSION: Off-label MRI scans performed under a strict protocol demonstrated excellent short- and medium-term safety while providing interpretable imaging that frequently influenced clinical care.

BACKGROUND: Early readmission after percutaneous coronary intervention is an important quality metric, but prediction models from registry data have only moderate discrimination. We aimed to improve ability to predict 30-day readmission after percutaneous coronary intervention from a previously validated registry-based model.

METHODS AND RESULTS: We matched readmitted to non-readmitted patients in a 1:2 ratio by risk of readmission, and extracted unstructured and unconventional structured data from the electronic medical record, including need for medical interpretation, albumin level, medical nonadherence, previous number of emergency department visits, atrial fibrillation/flutter, syncope/presyncope, end-stage liver disease, malignancy, and anxiety. We assessed differences in rates of these conditions between cases/controls, and estimated their independent association with 30-day readmission using logistic regression conditional on matched groups. Among 9288 percutaneous coronary interventions, we matched 888 readmitted with 1776 non-readmitted patients. In univariate analysis, cases and controls were significantly different with respect to interpreter (7.9% for cases and 5.3% for controls; P=0.009), emergency department visits (1.12 for cases and 0.77 for controls; P<0.001), homelessness (3.2% for cases and 1.6% for controls; P=0.007), anticoagulation (33.9% for cases and 22.1% for controls; P<0.001), atrial fibrillation/flutter (32.7% for cases and 28.9% for controls; P=0.045), presyncope/syncope (27.8% for cases and 21.3% for controls; P<0.001), and anxiety (69.4% for cases and 62.4% for controls; P<0.001). Anticoagulation, emergency department visits, and anxiety were independently associated with readmission.

CONCLUSIONS: Patient characteristics derived from review of the electronic health record can be used to refine risk prediction for hospital readmission after percutaneous coronary intervention.

BACKGROUND: A mechanism to stratify patients resuscitated from a cardiac arrest according to the likelihood of an acute coronary lesion would have significant utility. We thus sought to develop and validate a risk prediction model for the presence of an acute coronary lesion among patients resuscitated from an arrest.

METHODS AND RESULTS: All subjects undergoing coronary angiography after resuscitation from a cardiac arrest were identified in an ongoing institutional registry from 2009 to 2014. Backwards stepwise selection of candidate covariates was used to create a logistic regression model for the presence of an angiographic culprit lesion and internally validated with bootstrapping. A clinical point score was generated and its prognostic abilities compared with contemporary measures. Among 247 subjects undergoing coronary angiography after resuscitation from a cardiac arrest, 130 (52%) had an acute lesion in a coronary artery. A multivariable model-including angina, congestive heart failure symptoms, shockable arrest rhythm (ventricular fibrillation/ventricular tachycardia), and ST-elevations-had excellent discrimination (optimism corrected C-Statistic, 0.88) and calibration (Hosmer-Lemeshow P=0.540) for an acute coronary lesion. Compared with electrocardiographic findings alone, a point score based on this model more accurately predicted the presence of an acute lesion among patients resuscitated from a cardiac arrest (integrated discrimination improvement, 0.10; 95% confidence interval, 0.04-0.19; P<0.001).

CONCLUSIONS: Patients with a cardiac arrest can be risk stratified for the presence of an acute coronary lesion using 4 easily measured variables. This simple risk score may be used to improve patient selection for emergent coronary angiography among resuscitated patients.

BACKGROUND: Rehospitalization within 30 days after an admission for percutaneous coronary intervention (PCI) is common, costly, and a future target for Medicare penalties. Causes of readmission after PCI are largely unknown.

METHODS AND RESULTS: To illuminate the causes of PCI readmissions, patients with PCI readmitted within 30 days of discharge between 2007 and 2011 at 2 hospitals were identified, and their medical records were reviewed. Of 9288 PCIs, 9081 (97.8%) were alive at the end of the index hospitalization. Of these, 893 patients (9.8%) were readmitted within 30 days of discharge and included in the analysis. Among readmitted patients, 341 patients (38.1%) were readmitted for evaluation of recurrent chest pain or other symptoms concerning for angina, whereas 59 patients (6.6%) were readmitted for staged PCI without new symptoms. Complications of PCI accounted for 60 readmissions (6.7%). For cases in which chest pain or other symptoms concerning for angina prompted the readmission, 21 patients (6.2%) met criteria for myocardial infarction, and repeat PCI was performed in 54 patients (15.8%). The majority of chest pain patients (288; 84.4%) underwent ≥1 diagnostic imaging test, most commonly coronary angiography, and only 9 (2.6%) underwent target lesion revascularization.

CONCLUSIONS: After PCI, readmissions within 30 days were seldom related to PCI complications but often for recurrent chest pain. Readmissions with recurrent chest pain infrequently met criteria for myocardial infarction but were associated with high rates of diagnostic testing.

BACKGROUND: The growth of centers capable of performing percutaneous coronary intervention (PCI) has outpaced population growth despite declining incidence of myocardial infarction and prevalence of coronary artery disease, potentially increasing the proportion of operators falling below minimal yearly volume standards set by professional societies.

METHODS AND RESULTS: Electronic literature search of MEDLINE and the Cochrane Library for English-language articles published between 1977 and November 2012 was performed. Title and abstract review followed by full-text and references review were performed by 2 authors independently to identify studies examining the association between operator volume and outcomes in PCI. Using a standardized form, 2 authors abstracted information on study design, methods, outcomes, statistical methods, and conclusions. Studies were categorized according to methodological quality and outcomes. Meta-analyses were performed by outcome using a random-effects model. Of the 23 studies included in the analysis, 14 (61%) evaluated mortality, 7 (30%) evaluated major adverse cardiac events, and 2 (9%) evaluated angiographic success. In total, the studies evaluated 15 907 operators performing 205 214 PCIs on 1 109 103 patients at 2456 centers with a mean follow-up of 2.8 years. Eleven (48%) were considered higher quality. Studies with higher methodological quality and large sample sizes more often showed a relationship between operator volume and outcomes in PCI. Higher volume was associated with improved major adverse cardiac events at every threshold, regardless of the threshold evaluated.

CONCLUSIONS: Mortality and major adverse cardiac events increase as operator volumes decrease in PCI. Among studies showing a relationship, high-volume operators were defined variably, with annual PCIs ranging from >11 to >270, with no clear evidence of a threshold effect within the ranges studied.