Publications

BACKGROUND: The role of basal septal hypertrophy (BSH) on preprocedural transthoracic echocardiography in transcatheter aortic valve replacement (TAVR) is unknown.

METHODS: Medical charts and preprocedural transthoracic echocardiograms of 378 patients who underwent TAVR were examined. The association between BSH and the primary composite outcome of valve pop-out, recapture, embolization, aborted procedure, conversion to open procedure, new conduction disturbance, or need for permanent pacemaker ≤30 days after TAVR was evaluated. Patients with preexisting pacemakers were excluded. Sensitivity analyses were performed varying the definition of BSH.

RESULTS: Of 296 TAVR patients (78.3%) with interpretable images, 55 (18.6%) had BSH at a median of 40 days (interquartile range, 19-62 days) before TAVR. Age and sex were similar among those with and without BSH. BSH patients received postdilation more frequently (BSH+ vs BSH-: 41.8% vs 29.9%, P = .04). A total of 50 individuals (16.9%) received pacemakers within 30 days, and 128 (43.2%) developed conduction disturbances (with left bundle branch block most common), without differences between groups. BSH was unrelated to the primary outcome on multivariate analysis (adjusted odds ratio BSH+ vs BSH-, 0.94; 95% CI, 0.42-2.11; P = .88).

CONCLUSIONS: In this convenience sample of TAVR recipients at a large academic medical center, patients with BSH were more likely to receive postdilation. BSH was not associated with procedural or conduction outcomes after TAVR in patients without preexisting pacemakers.

BACKGROUND: Cerebrovascular events (CVEs) are devastating complications after aortic valve replacement. We assessed whether billing claims accurately identify CVEs in place of clinical event adjudication in structural heart disease trials.

METHODS: Adult participants in the US CoreValve High Risk and SURTAVI trials (Surgical or Transcatheter Aortic-Valve Replacement in Intermediate-Risk Patients) were linked to Medicare inpatient claims from January 1, 2006 to December 31, 2016. Claims consistent with CVEs within 14 days of a similar trial-adjudicated CVE were considered a match. The sensitivity, specificity, and positive and negative predictive values of International Classification of Diseases,Ninth andTenthRevisions, Clinical Modification billing codes for cerebrovascular disease were determined against trial-defined CVEs as the criterion standard. Kaplan-Meier estimates of claims-defined versus trial-defined CVEs were compared.

RESULTS: Among 4230 linked trial participants (linkage rate 79.8%), 550 (13.0%) sustained 630 adjudicated CVEs over a 5-year follow-up period. Linked and nonlinked individuals were similar. An algorithm using 4 International Classification of Diseases, Ninth Revision, Clinical Modification codes (434.91, 434.11, 433.11, and 997.02) had a sensitivity of 60.9%, specificity of 99.0%, positive predictive value of 86.5%, and negative predictive value of 95.8% for identifying a trial-adjudicated ischemic stroke. An algorithm using 3 International Classification of Diseases, Tenth Revision, Clinical Modification codes (I63.9, I63.40, I63.49) had a sensitivity of 66.7%, specificity of 99.4%, positive predictive value of 88.9%, and negative predictive value of 97.6%.

CONCLUSIONS: In linked clinical trial and Medicare claims data, 4 International Classification of Diseases, Ninth Revision, Clinical Modification and 3 International Classification of Diseases, Tenth Revision, Clinical Modification billing codes identified half of trial-adjudicated CVEs during follow-up with high specificity and predictive value, but imperfect sensitivity. Although low sensitivity may limit the use of claims to substitute for traditional trial outcomes to identify CVEs, high specificity suggests claims could be used to trigger evaluation of neurological events, potentially improving the efficiency of the evaluation of techniques and devices designed to reduce such events.

AIMS: Despite rising rates of cardiogenic shock (CS), data on trends and in-hospital outcomes of short-term non-durable mechanical circulatory support (MCS) are limited. Thus, we aimed to identify recent national trends in MCS utilisation in the USA, patient-level predictors of MCS use, and in-hospital outcomes in CS inclusive of extracorporeal membrane oxygenation (ECMO).

METHODS AND RESULTS: Hospitalisations of US adults with a discharge diagnosis of CS, from January 2004 to December 2014, in the National Inpatient Sample were included. Rates of MCS were stratified by device type and clinical presentation. Outcomes included in-hospital mortality, hospitalisation costs, and number of procedures. A total of 183,516 hospitalisations with CS (47,636 [25.9%] involving MCS) were included. MCS recipients were younger, less frequently female, received more procedures, had higher costs, and more frequently presented with MI (MCS vs. non-MCS: 71.6% vs. 42.9%; p<0.0001). Growth in CS hospitalisations (214.4%) outpaced annual MCS use (160.0%), with relative declines in intra-aortic balloon pump use starting in 2008. Right heart catheterisation rates for both groups remained low (MCS vs. non-MCS: 5.9% vs. 3.3%; p<0.0001). In-hospital mortality declined but remained high in both groups (MCS vs. non-MCS [2014]: 32.7% vs. 41.5%; p<0.0001).

CONCLUSIONS: In-hospital mortality for CS has declined but remains high. Rates of CS have outpaced MCS utilisation which remains uncommon in non-MI hospitalisations with shock. MCS is associated with utilisation of other procedures during hospitalisation.

OBJECTIVES: Factors associated with performing urgent coronary angiography (UCA) in patients with out-of-hospital cardiac arrest (OHCA) were identified.

BACKGROUND: Current guidelines for resuscitated OHCA patients recommend UCA if there is ST-elevation on post-arrest electrocardiogram or high suspicion of acute myocardial infarction. Some have advocated for UCA in all OHCA regardless of suspected etiology. The reasons for variations in performing UCA are not well understood.

METHODS: A retrospective analysis of subjects presenting with resuscitated OHCA to a single academic medical center from 12/15/2007 to 8/31/2014 was conducted. Demographic and clinical characteristics of patients undergoing UCA, defined as angiography within 6 hr of presentation, were compared with those not undergoing UCA. Logistic regression was used to determine predictors of UCA.

RESULTS: A total of 323 resuscitated OHCA patients (mean age, 64 years; women, 35%) were included in the analysis; 107 (33.1%) underwent coronary angiography during their hospitalization and 66 (20.4%) underwent UCA. Multivariable adjusted factors associated with UCA were ST-elevation [odds ratio (OR) 14.66, 95% confidence interval (CI) 6.28-34.24, P < 0.001], initial shockable rhythm (OR 3.69, 95% CI 1.52-8.97, P = 0.004), and history of coronary artery disease (CAD) (OR 3.37, 95% CI 1.43-7.95, P = 0.005). Higher age (OR 0.71 per decade, 95% CI 0.55-0.92, P = 0.01) and obvious non-cardiac cause of arrest (OR 0.08, 95% CI 0.02-0.38, P = 0.001) were negatively associated with UCA.

CONCLUSIONS: In resuscitated out-of-hospital cardiac arrest patients, ST-elevation, shockable rhythm, and history of CAD were associated with performing urgent coronary angiography; older patients and those with obvious non-cardiac causes of arrest were negatively associated.

BACKGROUND: Readmission rates after hospitalizations for heart failure (HF), acute myocardial infarction (AMI), and pneumonia among Medicare beneficiaries are used to assess quality and determine reimbursement. Whether these measures reflect readmission rates for other conditions or insurance groups is unknown.

OBJECTIVE: To investigate whether hospital-level 30-day readmission measures for publicly reported conditions (HF, AMI, and pneumonia) among Medicare patients reflect those for Medicare patients hospitalized for unreported conditions or non-Medicare patients hospitalized with HF, AMI, or pneumonia.

DESIGN: Cross-sectional.

SETTING: Population-based.

PARTICIPANTS: Hospitals in the all-payer Nationwide Readmissions Database in 2013 and 2014.

MEASUREMENTS: Hospital-level 30-day all-cause risk-standardized excess readmission ratios (ERRs) were compared for 3 groups of patients: Medicare beneficiaries admitted for HF, AMI, or pneumonia (Medicare reported group); Medicare beneficiaries admitted for other conditions (Medicare unreported group); and non-Medicare beneficiaries admitted for HF, AMI, or pneumonia (non-Medicare group).

RESULTS: Within-hospital differences in ERRs varied widely among groups. Medicare reported ratios differed from Medicare unreported ratios by more than 0.1 for 29% of hospitals and from non-Medicare ratios by more than 0.1 for 46% of hospitals. Among hospitals with higher readmission ratios, ERRs for the Medicare reported group tended to overestimate ERRs for the non-Medicare group but underestimate those for the Medicare unreported group.

LIMITATION: Medicare groups and risk adjustment differed slightly from those used by the Centers for Medicare & Medicaid Services.

CONCLUSION: Hospital ERRs, as estimated by Medicare to determine financial penalties, have poor agreement with corresponding measures for populations and conditions not tied to financial penalties. Current publicly reported measures may not be good surrogates for overall hospital quality related to 30-day readmissions.

PRIMARY FUNDING SOURCE: Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology.

BACKGROUND: Apparent increase in mortality associated with being admitted to hospital on a weekend compared to weekdays has led to controversial policy changes to weekend staffing in the United Kingdom. Studies in the United States have been inconclusive and diagnosis specific, and whether to implement such changes is subject to ongoing debate.

OBJECTIVE: To compare mortality, length of stay, and cost between patients admitted on weekdays and weekends.

DESIGN: Retrospective cohort study.

SETTING: National Inpatient Sample, an administrative claims database of a 20% stratified sample of discharges from all hospitals participating in the Healthcare Cost and Utilization Project.

PATIENTS: Adult patients who were emergently admitted from 2012 to 2014.

INTERVENTION: The primary predictor was whether the admission was on a weekday or weekend.

MEASUREMENTS: The primary outcome was in-hospital mortality and secondary outcomes were length of stay and cost.

RESULTS: We included 13,505,396 patients in our study. After adjusting for demographics and disease severity, we found a small difference in inpatient mortality rates on weekends versus weekdays (odds ratio [OR] 1.029; 95% confidence interval [CI], 1.020-1.039; P < .001). There was a statistically significant but clinically small decrease in length of stay (2.24%; 95% CI, 2.16-2.33; P < .001) and cost (1.14%; 95% CI, 1.05-1.24; P < .001) of weekend admissions. A subgroup analysis of the most common weekend diagnoses showed substantial heterogeneity between diagnoses.

CONCLUSIONS: Differences in mortality of weekend admissions may be attributed to underlying differences in patient characteristics and severity of illness and is subject to large between-diagnoses heterogeneity. Increasing weekend services may not result in desired reduction in inpatient mortality rate.

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.