Publications

The MitraClip device for percutaneous mitral valve repair was approved by the Food and Drug Administration in the United States in October 2013. Few studies have evaluated national outcomes after this procedure in routine clinical practice. We identified adults aged ≥18 years who received percutaneous mitral valve repair from November 2013 to December 2014 in the Nationwide Readmissions Database, a publicly available administrative claims database. Procedural volumes, number of performing hospitals, individual hospital volumes, in-hospital mortality rate, and 30-day hospital readmission rate were determined. Patient demographics, clinical comorbidities, and hospital characteristics were analyzed using logistic regression to determine risk factors for in-hospital death and 30-day readmission. We identified 879 cases performed in the first 14 months after device approval (mean age ± SD, 75.0 ± 13.1 years; 45% women). The number of performing hospitals increased by 5.7-fold (23 to 132), although mean individual hospital volumes remained small (6.2 ± 10.4 cases per hospital). In-hospital all-cause mortality was 3.3% and was associated with higher number of clinical comorbidities. The rate of 30-day readmission was 14.6%, and 6.6% of patients died during rehospitalization. Increased procedural experience was associated with a nonsignificant trend toward reduced hospital readmission after multivariable adjustment (p = 0.08). In conclusion, use of percutaneous mitral valve repair in the United States early after approval increased steadily over time, although individual hospital volumes remained low. More than 1 in 7 patients who underwent this procedure are readmitted within 30 days of discharge.

Background Prospectively collected frailty markers are associated with an incremental 1-year mortality risk after transcatheter aortic valve replacement (TAVR) compared with comorbidities alone. Whether information on frailty markers captured retrospectively in administrative billing data is similarly predictive of long-term mortality after TAVR is unknown. We sought to characterize the prognostic importance of frailty factors as identified in healthcare billing records in comparison to validated measures of frailty for the prediction of long-term mortality after TAVR. Methods and Results Adult patients undergoing TAVR between August 25, 2011, and September 29, 2015, were identified among Medicare fee-for-service beneficiaries. The Johns Hopkins Claims-based Frailty Indicator was used to identify frail patients. We used nested Cox regression models to identify claims-based predictors of mortality up to 4 years post-procedure. Four groups of variables, including cardiac risk factors, noncardiac risk factors, patient procedural risk factors, and nontraditional markers of frailty, were introduced sequentially, and their integrated discrimination improvement was assessed. A total of 52 338 TAVR patients from 558 clinical sites were identified, with a mean follow-up time period of 16 months. In total, 14 174 (27.1%) patients died within the study period. The mortality rate was 53.9% at 4 years post-TAVR. A total of 34 863 (66.6%) patients were defined as frail. The discrimination of each of the 4 models was 0.60 (95% CI, 0.59-60), 0.65 (95% CI, 0.64-0.65), 0.68 (95% CI, 0.67-0.68), and 0.70 (95% CI, 0.69-0.70), respectively. The addition of nontraditional frailty markers as identified in claims improved mortality prediction above and beyond traditional risk factors (integrated discrimination improvement: 0.019; P<0.001). Conclusions Risk prediction models that include frailty as identified in claims data can be used to predict long-term mortality risk after TAVR. Linkage to claims data may allow enhanced mortality risk prediction for studies that do not collect information on frailty.

OBJECTIVES: This study sought to evaluate the trends in isolated surgical aortic valve replacement (SAVR) procedures across hospitals with different transcatheter aortic valve replacement (TAVR) volumes among Medicare beneficiaries.

BACKGROUND: The volume of TAVR has increased in the United States since its approval, now exceeding that of isolated SAVR.

METHODS: Hospitalizations of adults (≥18 years of age) with International Classification of Diseases-9th Revision-Clinical Modification procedure codes for SAVR (35.21 or 35.22) or TAVR (35.05 or 35.06) who were included in the Medicare Provider Analysis and Review database between January 1, 2011, and December 31, 2014, were included. Trends in isolated SAVR patient characteristics, procedural volumes, and outcomes by quartile (Q) of hospital-level TAVR use were assessed over the study period.

RESULTS: A total of 37,705 isolated SAVR procedures were analyzed for the study. The annual volume of isolated SAVR procedures decreased in hospitals performing the largest number of TAVR procedures (Q3: 1,557 in 2011 to 1,391 in 2014; and Q4: 2,607 in 2011 to 1,791 in 2014). Thirty-day and 1-year mortality after SAVR also declined over the study period in hospitals with the largest TAVR volume (annual change rate in mortality for Q3: -16.4%; p < 0.001; Q4: -20.8%; p < 0.001).

CONCLUSIONS: The advent of TAVR was associated with a reduction in isolated SAVR volumes, a decrease in comorbidities among patients undergoing SAVR, and corresponding reductions in observed short- and long-term SAVR mortality among hospitals performing the greatest number of TAVRs.

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.

OBJECTIVE: To determine if using a parachute prevents death or major traumatic injury when jumping from an aircraft.

DESIGN: Randomized controlled trial.

SETTING: Private or commercial aircraft between September 2017 and August 2018.

PARTICIPANTS: 92 aircraft passengers aged 18 and over were screened for participation. 23 agreed to be enrolled and were randomized.

INTERVENTION: Jumping from an aircraft (airplane or helicopter) with a parachute versus an empty backpack (unblinded).

MAIN OUTCOME MEASURES: Composite of death or major traumatic injury (defined by an Injury Severity Score over 15) upon impact with the ground measured immediately after landing.

RESULTS: Parachute use did not significantly reduce death or major injury (0% for parachute v 0% for control; P>0.9). This finding was consistent across multiple subgroups. Compared with individuals screened but not enrolled, participants included in the study were on aircraft at significantly lower altitude (mean of 0.6 m for participants v mean of 9146 m for non-participants; P<0.001) and lower velocity (mean of 0 km/h v mean of 800 km/h; P<0.001).

CONCLUSIONS: Parachute use did not reduce death or major traumatic injury when jumping from aircraft in the first randomized evaluation of this intervention. However, the trial was only able to enroll participants on small stationary aircraft on the ground, suggesting cautious extrapolation to high altitude jumps. When beliefs regarding the effectiveness of an intervention exist in the community, randomized trials might selectively enroll individuals with a lower perceived likelihood of benefit, thus diminishing the applicability of the results to clinical practice.

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.

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: 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.

Readmission after hospitalization for acute myocardial infarction (AMI) significantly contributes to preventable morbidity and health-care costs. Outcomes after AMI vary by sex but the relationship of sex to readmissions warrants further exploration. Using the 2013 Nationwide Readmissions Database, we identified patients with a principal discharge diagnosis of AMI and stratified all-cause 30-day readmissions by sex and age. Of 214,824 patients, 44% were 18 to 64 years of age, 56% were ≥65 years, and 28% and 45%, respectively, were female. For patients 18 to 64 years, the readmission rate was 14% for women and 10% for men (p <0.001). For patients ≥65 years, the readmission rate was 18% for women and 16% for men (p <0.001). After adjusting for co-morbidities, women had a significantly higher risk of 30-day readmission compared with men, an effect that was strongest in younger women (odds ratio [OR] 1.21, 95% confidence interval [CI] 1.06 to 1.39, for ages 18 to 44; OR 1.13, 95% CI 1.07 to 1.18, for ages 45 to 64; OR 1.13, 95% CI 1.07 to 1.19, for ages 65 to 74, interaction p <0.001). The procedure rates during the index hospitalization were significantly lower for women. The most common readmission diagnoses were recurrent AMI, ischemic heart disease, and heart failure. Costs associated with readmissions after AMI totaled $447,506,740, of which $176,743,622 were attributed to readmissions of women. In conclusion, women are at higher risk of short-term readmission after an AMI hospitalization than men, particularly younger women. Sex-specific strategies to reduce these readmissions may be warranted.