Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation.

BACKGROUND: Optical sensors on wearable devices can detect irregular pulses. The ability of a smartwatch application (app) to identify atrial fibrillation during typical use is unknown. METHODS: Participants without atrial fibrillation (as reported by the participants themselves) used a smartphone (Apple iPhone) app to consent to monitoring. If a smartwatch-based irregular pulse notification algorithm identified possible atrial fibrillation, a telemedicine visit was initiated and an electrocardiography (ECG) patch was mailed to the participant, to be worn for up to 7 days. Surveys were administered 90 days after notification of the irregular pulse and at the end of the study. The main objectives were to estimate the proportion of notified participants with atrial fibrillation shown on an ECG patch and the positive predictive value of irregular pulse intervals with a targeted confidence interval width of 0.10. RESULTS: We recruited 419,297 participants over 8 months. Over a median of 117 days of monitoring, 2161 participants (0.52%) received notifications of irregular pulse. Among the 450 participants who returned ECG patches containing data that could be analyzed - which had been applied, on average, 13 days after notification - atrial fibrillation was present in 34% (97.5% confidence interval [CI], 29 to 39) overall and in 35% (97.5% CI, 27 to 43) of participants 65 years of age or older. Among participants who were notified of an irregular pulse, the positive predictive value was 0.84 (95% CI, 0.76 to 0.92) for observing atrial fibrillation on the ECG simultaneously with a subsequent irregular pulse notification and 0.71 (97.5% CI, 0.69 to 0.74) for observing atrial fibrillation on the ECG simultaneously with a subsequent irregular tachogram. Of 1376 notified participants who returned a 90-day survey, 57% contacted health care providers outside the study. There were no reports of serious app-related adverse events. CONCLUSIONS: The probability of receiving an irregular pulse notification was low. Among participants who received notification of an irregular pulse, 34% had atrial fibrillation on subsequent ECG patch readings and 84% of notifications were concordant with atrial fibrillation. This siteless (no on-site visits were required for the participants), pragmatic study design provides a foundation for large-scale pragmatic studies in which outcomes or adherence can be reliably assessed with user-owned devices. (Funded by Apple; Apple Heart Study ClinicalTrials.gov number, NCT03335800.).

Lessons learned in the Apple Heart Study and implications for the data management of future digital clinical trials.

The digital clinical trial is fast emerging as a pragmatic trial that can improve a trial's design including recruitment and retention, data collection and analytics. To that end, digital platforms such as electronic health records or wearable technologies that enable passive data collection can be leveraged, alleviating burden from the participant and study coordinator. However, there are challenges. For example, many of these data sources not originally intended for research may be noisier than traditionally obtained measures. Further, the secure flow of passively collected data and their integration for analysis is non-trivial. The Apple Heart Study was a prospective, single-arm, site-less digital trial designed to evaluate the ability of an app to detect atrial fibrillation. The study was designed with pragmatic features, such as an app for enrollment, a wearable device (the Apple Watch) for data collection, and electronic surveys for participant-reported outcomes that enabled a high volume of patient enrollment and accompanying data. These elements led to challenges including identifying the number of unique participants, maintaining participant-level linkage of multiple complex data streams, and participant adherence and engagement. Novel solutions were derived that inform future designs with an emphasis on data management. We build upon the excellent framework of the Clinical Trials Transformation Initiative to provide a comprehensive set of guidelines for data management of the digital clinical trial that include an increased role of collaborative data scientists in the design and conduct of the modern digital trial.

Bleeding avoidance strategies and percutaneous coronary intervention outcomes: A 10-year observation from a Japanese Multicenter Registry.

BACKGROUND: Bleeding avoidance strategies (BASs) are increasingly adopted for patients undergoing percutaneous coronary intervention (PCI) due to bleeding complications. However, their association with bleeding events outside of Western countries remains unclear. In collaboration with the National Cardiovascular Data Registry (NCDR) CathPCI registry, we aimed to assess the time trend and impact of BAS utilization among Japanese patients. METHODS: Our study included 19,656 consecutive PCI patients registered over 10 years. These patients were divided into 4-time frame groups (T1: 2008-2011, T2: 2012-2013, T3: 2014-2015, and T4: 2016-2018). BAS was defined as the use of transradial approach or vascular closure device (VCD) use after transfemoral approach (TFA). Model performance of the NCDR CathPCI bleeding model was evaluated. The degree of bleeding reduction associated with BAS adoption was estimated via multilevel mixed-effects multivariable logistic regression analysis. RESULTS: The NCDR CathPCI bleeding risk score demonstrated good discrimination in the Japanese population (C-statistics 0.79-0.81). The BAS adoption rate increased from 43% (T1) to 91% (T4), whereas the crude CathPCI-defined bleeding rate decreased from 10% (T1) to 7% (T4). Adjusted odds ratios for bleeding events were 0.25 (95% confidence interval, 0.14-0.45, P< .001) for those undergoing TFA with VCD in T4 and 0.26 (95% confidence interval 0.20-0.35, P< .001) for transradial approach in T4 compared to patients that received TFA without VCD in T1. CONCLUSIONS: BAS use over the studied time frames was associated with lower risk of bleeding complications among Japanese. Nonetheless, observed bleeding rates remained higher compared to the US population.

Myocardial infarction with non-obstructive coronary arteries as compared with myocardial infarction and obstructive coronary disease: outcomes in a Medicare population.

AIMS: The prognosis of patients with MINOCA (myocardial infarction with non-obstructive coronary arteries) is poorly understood. We examined major adverse cardiac events (MACE) defined as all-cause mortality, re-hospitalization for acute myocardial infarction (AMI), heart failure (HF), or stroke 12-months post-AMI in patients with MINOCA versus AMI patients with obstructive coronary artery disease (MICAD). METHODS AND RESULTS: Multicentre, observational cohort study of patients with AMI (≥65 years) from the National Cardiovascular Data Registry CathPCI Registry (July 2009-December 2013) who underwent coronary angiography with linkage to the Centers for Medicare and Medicaid (CMS) claims data. Patients were classified as MICAD or MINOCA by the presence or absence of an epicardial vessel with ≥50% stenosis. The primary endpoint was MACE at 12 months, and secondary endpoints included the components of MACE over 12 months. Among 286 780 AMI admissions (276 522 unique patients), 16 849 (5.9%) had MINOCA. The 12-month rates of MACE (18.7% vs. 27.6%), mortality (12.3% vs. 16.7%), and re-hospitalization for AMI (1.3% vs. 6.1%) and HF (5.9% vs. 9.3%) were significantly lower for MINOCA vs. MICAD patients (P < 0.001), but was similar between MINOCA and MICAD patients for re-hospitalization for stroke (1.6% vs. 1.4%, P = 0.128). Following risk-adjustment, MINOCA patients had a 43% lower risk of MACE over 12 months (hazard ratio = 0.57, 95% confidence interval 0.55-0.59), in comparison to MICAD patients. This pattern was similar for adjusted risks of the MACE components. CONCLUSION: This study confirms an unfavourable prognosis in elderly patients with MINOCA undergoing coronary angiography, with one in five patients with MINOCA suffering a major adverse event over 12 months.

Management of acute myocardial infarction during the COVID-19 pandemic: A Consensus Statement from the Society for Cardiovascular Angiography and Interventions (SCAI), the American College of Cardiology (ACC), and the American College of Emergency Physicians (ACEP).

The worldwide pandemic caused by the novel acute respiratory syndrome coronavirus 2 has resulted in a new and lethal disease termed coronavirus disease 2019 (COVID-19). Although there is an association between cardiovascular disease and COVID-19, the majority of patients who need cardiovascular care for the management of ischemic heart disease may not be infected with this novel coronavirus. The objective of this document is to provide recommendations for a systematic approach for the care of patients with an acute myocardial infarction (AMI) during the COVID-19 pandemic. There is a recognition of two major challenges in providing recommendations for AMI care in the COVID-19 era. Cardiovascular manifestations of COVID-19 are complex with patients presenting with AMI, myocarditis simulating an ST-elevation myocardial infarction (STEMI) presentation, stress cardiomyopathy, non-ischemic cardiomyopathy, coronary spasm, or nonspecific myocardial injury, and the prevalence of COVID-19 disease in the US population remains unknown with risk of asymptomatic spread. This document addresses the care of these patients focusing on (a) varied clinical presentations; (b) appropriate personal protection equipment (PPE) for health care workers; (c) the roles of the emergency department, emergency medical system, and the cardiac catheterization laboratory (CCL); and (4) regional STEMI systems of care. During the COVID-19 pandemic, primary percutaneous coronary intervention (PCI) remains the standard of care for STEMI patients at PCI-capable hospitals when it can be provided in a timely manner, with an expert team outfitted with PPE in a dedicated CCL room. A fibrinolysis-based strategy may be entertained at non-PCI-capable referral hospitals or in specific situations where primary PCI cannot be executed or is not deemed the best option.

'Real-world' observational studies in arrhythmia research: data sources, methodology, and interpretation. A position document from European Heart Rhythm Association (EHRA), endorsed by Heart Rhythm Society (HRS), Asia-Pacific HRS (APHRS), and Latin America HRS (LAHRS).

The field of observational studies or "real world studies" is in rapid development with many new techniques introduced and increased understanding of traditional methods. For this reason the current paper provides an overview of current methods with focus on new techniques. Some highlights can be emphasized: We provide an overview of sources of data for observational studies. There is an overview of sources of bias and confounding. Next There is an overview of causal inference techniques that are increasingly used. The most commonly used techniques for statistical modelling are reviewed with focus on the important distinction of risk versus prediction. The final section provides examples of common problems with reporting observational data.

Rationale and design of a large-scale, app-based study to identify cardiac arrhythmias using a smartwatch: The Apple Heart Study.

BACKGROUND: Smartwatch and fitness band wearable consumer electronics can passively measure pulse rate from the wrist using photoplethysmography (PPG). Identification of pulse irregularity or variability from these data has the potential to identify atrial fibrillation or atrial flutter (AF, collectively). The rapidly expanding consumer base of these devices allows for detection of undiagnosed AF at scale. METHODS: The Apple Heart Study is a prospective, single arm pragmatic study that has enrolled 419,093 participants (NCT03335800). The primary objective is to measure the proportion of participants with an irregular pulse detected by the Apple Watch (Apple Inc, Cupertino, CA) with AF on subsequent ambulatory ECG patch monitoring. The secondary objectives are to: 1) characterize the concordance of pulse irregularity notification episodes from the Apple Watch with simultaneously recorded ambulatory ECGs; 2) estimate the rate of initial contact with a health care provider within 3 months after notification of pulse irregularity. The study is conducted virtually, with screening, consent and data collection performed electronically from within an accompanying smartphone app. Study visits are performed by telehealth study physicians via video chat through the app, and ambulatory ECG patches are mailed to the participants. CONCLUSIONS: The results of this trial will provide initial evidence for the ability of a smartwatch algorithm to identify pulse irregularity and variability which may reflect previously unknown AF. The Apple Heart Study will help provide a foundation for how wearable technology can inform the clinical approach to AF identification and screening.

The Learning Healthcare System and Cardiovascular Care: A Scientific Statement From the American Heart Association.

The learning healthcare system uses health information technology and the health data infrastructure to apply scientific evidence at the point of clinical care while simultaneously collecting insights from that care to promote innovation in optimal healthcare delivery and to fuel new scientific discovery. To achieve these goals, the learning healthcare system requires systematic redesign of the current healthcare system, focusing on 4 major domains: science and informatics, patient-clinician partnerships, incentives, and development of a continuous learning culture. This scientific statement provides an overview of how these learning healthcare system domains can be realized in cardiovascular disease care. Current cardiovascular disease care innovations in informatics, data uses, patient engagement, continuous learning culture, and incentives are profiled. In addition, recommendations for next steps for the development of a learning healthcare system in cardiovascular care are presented.

Enhancing the prediction of acute kidney injury risk after percutaneous coronary intervention using machine learning techniques: A retrospective cohort study.

BACKGROUND: The current acute kidney injury (AKI) risk prediction model for patients undergoing percutaneous coronary intervention (PCI) from the American College of Cardiology (ACC) National Cardiovascular Data Registry (NCDR) employed regression techniques. This study aimed to evaluate whether models using machine learning techniques could significantly improve AKI risk prediction after PCI. METHODS AND FINDINGS: We used the same cohort and candidate variables used to develop the current NCDR CathPCI Registry AKI model, including 947,091 patients who underwent PCI procedures between June 1, 2009, and June 30, 2011. The mean age of these patients was 64.8 years, and 32.8% were women, with a total of 69,826 (7.4%) AKI events. We replicated the current AKI model as the baseline model and compared it with a series of new models. Temporal validation was performed using data from 970,869 patients undergoing PCIs between July 1, 2016, and March 31, 2017, with a mean age of 65.7 years; 31.9% were women, and 72,954 (7.5%) had AKI events. Each model was derived by implementing one of two strategies for preprocessing candidate variables (preselecting and transforming candidate variables or using all candidate variables in their original forms), one of three variable-selection methods (stepwise backward selection, lasso regularization, or permutation-based selection), and one of two methods to model the relationship between variables and outcome (logistic regression or gradient descent boosting). The cohort was divided into different training (70%) and test (30%) sets using 100 different random splits, and the performance of the models was evaluated internally in the test sets. The best model, according to the internal evaluation, was derived by using all available candidate variables in their original form, permutation-based variable selection, and gradient descent boosting. Compared with the baseline model that uses 11 variables, the best model used 13 variables and achieved a significantly better area under the receiver operating characteristic curve (AUC) of 0.752 (95% confidence interval [CI] 0.749-0.754) versus 0.711 (95% CI 0.708-0.714), a significantly better Brier score of 0.0617 (95% CI 0.0615-0.0618) versus 0.0636 (95% CI 0.0634-0.0638), and a better calibration slope of observed versus predicted rate of 1.008 (95% CI 0.988-1.028) versus 1.036 (95% CI 1.015-1.056). The best model also had a significantly wider predictive range (25.3% versus 21.6%, p < 0.001) and was more accurate in stratifying AKI risk for patients. Evaluated on a more contemporary CathPCI cohort (July 1, 2015-March 31, 2017), the best model consistently achieved significantly better performance than the baseline model in AUC (0.785 versus 0.753), Brier score (0.0610 versus 0.0627), calibration slope (1.003 versus 1.062), and predictive range (29.4% versus 26.2%). The current study does not address implementation for risk calculation at the point of care, and potential challenges include the availability and accessibility of the predictors. CONCLUSIONS: Machine learning techniques and data-driven approaches resulted in improved prediction of AKI risk after PCI. The results support the potential of these techniques for improving risk prediction models and identification of patients who may benefit from risk-mitigation strategies.

Variation in post-TAVR antiplatelet therapy utilization and associated outcomes: Insights from the STS/ACC TVT Registry.

BACKGROUND: Dual antiplatelet therapy (DAPT) is recommended following transcatheter aortic valve replacement (TAVR); however, the optimal antiplatelet strategy is undefined, and little is known about practice patterns. We aimed to describe contemporary practice patterns of antiplatelet therapy and their relationship to outcomes post-TAVR. METHODS: The population was derived from the National Cardiovascular Data Registry, Society of Thoracic Surgeons/American College of Cardiology Transcatheter Valve Therapies Registry with Center for Medical Services linkage for 1-year outcomes from October 1, 2011 to June 30,2016. The primary outcome measured was DAPT use in patients without anticoagulation. Secondary outcomes included death, major bleeding, myocardial infarction (MI), and stroke at 1 year. RESULTS: Overall, 16,694 patients underwent transfemoral TAVR at 444 hospitals and were discharged without anticoagulation. Among these, 13,546 (81.1%) patients were discharged on DAPT, whereas 3,148 patients (18.9%) were discharged on monotherapy. Patients discharged on DAPT versus monotherapy were similar in age, sex, and most comorbid illnesses but had higher rates of coronary artery disease (64.6% vs 52.3%; P < .01) and peripheral artery disease (25.2% vs 22.3%; P < .01). Hospital prescribing patterns varied significantly (median frequency of DAPT 85.7%, interquartile range 94.1%-74.2%). DAPT (vs monotherapy) patients had a similar mortality risk at 1 year (adjusted hazard ratio 0.92, 95% CI 0.81-1.05), significantly higher risk for major bleeding (1.48, 1.10-1.99), and similar hazard for stroke (1.04, 0.83-1.31) and MI (1.00, 0.72-1.39). CONCLUSIONS: In the United States, most patients were discharged on DAPT following TAVR. Practice patterns varied significantly among hospitals. Patients discharged with DAPT had a similar adjusted risk of mortality, stroke, and MI compared to antiplatelet monotherapy, although risk for bleeding was significantly higher. Future investigation is needed to define the optimal antiplatelet therapy for patients undergoing TAVR.

Gait Speed Predicts 30-Day Mortality After Transcatheter Aortic Valve Replacement: Results From the Society of Thoracic Surgeons/American College of Cardiology Transcatheter Valve Therapy Registry.

BACKGROUND: Surgical risk scores do not include frailty assessments (eg, gait speed), which are of particular importance for patients with severe aortic stenosis considering transcatheter aortic valve replacement. METHODS AND RESULTS: We assessed the association of 5-m gait speed with outcomes in a cohort of 8039 patients who underwent transcatheter aortic valve replacement (November 2011-June 2014) and were included in the Society of Thoracic Surgeons/American College of Cardiology Transcatheter Valve Therapy Registry. We evaluated the association between continuous and categorical gait speed and 30-day all-cause mortality before and after adjustment for Society of Thoracic Surgeons-predicted risk of mortality score and key variables. Secondary outcomes included in-hospital mortality, bleeding, acute kidney injury, and stroke. The overall median gait speed was 0.63 m/s (25th-75th percentile, 0.47-0.79 m/s), with the slowest walkers (<0.5 m/s) constituting 28%, slow walkers (0.5-0.83 m/s) making up 48%, and normal walkers (>0.83 m/s) constituting 24% of the population. Thirty-day all-cause mortality rates were 8.4%, 6.6%, and 5.4% for the slowest, slow, and normal walkers, respectively (P<0.001). Each 0.2-m/s decrease in gait speed corresponded to an 11% increase in 30-day mortality (adjusted odds ratio, 1.11; 95% confidence interval, 1.01-1.22). The slowest walkers had 35% higher 30-day mortality than normal walkers (adjusted odds ratio, 1.35; 95% confidence interval, 1.01-1.80), significantly longer hospital stays, and a lower probability of being discharged to home. CONCLUSIONS: Gait speed is independently associated with 30-day mortality after transcatheter aortic valve replacement. Identification of frail patients with the slowest gait speeds facilitates preprocedural evaluation and anticipation of a higher level of postprocedural care. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT01737528.

Association of Borderline Pulmonary Hypertension With Mortality and Hospitalization in a Large Patient Cohort: Insights From the Veterans Affairs Clinical Assessment, Reporting, and Tracking Program.

BACKGROUND: Pulmonary hypertension (PH) is associated with increased morbidity across the cardiopulmonary disease spectrum. Based primarily on expert consensus opinion, PH is defined by a mean pulmonary artery pressure (mPAP) ≥25 mm Hg. Although mPAP levels below this threshold are common among populations at risk for PH, the relevance of mPAP <25 mm Hg to clinical outcome is unknown. METHODS AND RESULTS: We analyzed retrospectively all US veterans undergoing right heart catheterization (2007-2012) in the Veterans Affairs healthcare system (n=21,727; 908-day median follow-up). Cox proportional hazards models were used to evaluate the association between mPAP and outcomes of all-cause mortality and hospitalization, adjusted for clinical covariates. When treating mPAP as a continuous variable, the mortality hazard increased beginning at 19 mm Hg (hazard ratio [HR]=1.183; 95% confidence interval [CI], 1.004-1.393) relative to 10 mm Hg. Therefore, patients were stratified into 3 groups: (1) referent (≤18 mm Hg; n=4,207); (2) borderline PH (19-24 mm Hg; n=5,030); and (3) PH (≥25 mm Hg; n=12,490). The adjusted mortality hazard was increased for borderline PH (HR=1.23; 95% CI, 1.12-1.36; P<0.0001) and PH (HR=2.16; 95% CI, 1.96-2.38; P<0.0001) compared with the referent group. The adjusted hazard for hospitalization was also increased in borderline PH (HR=1.07; 95% CI, 1.01-1.12; P=0.0149) and PH (HR=1.15; 95% CI, 1.09-1.22; P<0.0001). The borderline PH cohort remained at increased risk for mortality after excluding the following high-risk subgroups: (1) patients with pulmonary artery wedge pressure >15 mm Hg; (2) pulmonary vascular resistance ≥3.0 Wood units; or (3) inpatient status at the time of right heart catheterization. CONCLUSIONS: These data illustrate a continuum of risk according to mPAP level and that borderline PH is associated with increased mortality and hospitalization. Future investigations are needed to test the generalizability of our findings to other populations and study the effect of treatment on outcome in borderline PH.

Medication Initiation Burden Required to Comply With Heart Failure Guideline Recommendations and Hospital Quality Measures.

BACKGROUND: Guidelines for heart failure (HF) recommend prescription of guideline-directed medical therapy before hospital discharge; some of these therapies are included in publicly reported performance measures. The burden of new medications for individual patients has not been described. METHODS AND RESULTS: We used Get With The Guidelines-HF registry data from 2008 to 2013 to characterize prescribing, indications, and contraindications for angiotensin-converting enzyme inhibitors or angiotensin receptor blockers, ß-blockers, aldosterone antagonists, hydralazine/isosorbide dinitrate, and anticoagulants. The difference between a patient's medication regimen at hospital admission and that recommended by HF quality measures at discharge was calculated. Among 158 922 patients from 271 hospitals with a primary discharge diagnosis of HF, initiation of angiotensin-converting enzyme inhibitors or angiotensin receptor blockers was indicated in 18.1% of all patients (55.5% of those eligible at discharge were not receiving angiotensin-converting enzyme inhibitors or angiotensin receptor blockers at admission), ß-blockers in 20.3% (50.5% of eligible), aldosterone antagonists in 24.1% (87.4% of eligible), hydralazine/isosorbide dinitrate in 8.6% (93.1% of eligible), and anticoagulants in 18.0% (58.0% of eligible). Cumulatively, 0.4% of patients were eligible for 5 new medication groups, 4.1% for 4 new medication groups, 9.4% for 3 new medication groups, 10.1% for 2 new medication groups, and 22.7% for 1 new medication group; 15.0% were not eligible for new medications because of adequate prescribing at admission; and 38.4% were not eligible for any medications recommended by HF quality measures. Compared with newly indicated medications (mean, 1.45 ± 1.23), actual new prescriptions were lower (mean, 1.16 ± 1.00). CONCLUSIONS: A quarter of patients hospitalized with HF need to start >1 medication to meet HF quality measures. Systems for addressing medication initiation and managing polypharmacy are central to HF transitional care.

Facility-Level Variation in Hospitalization, Mortality, and Costs in the 30 Days After Percutaneous Coronary Intervention: Insights on Short-Term Healthcare Value From the Veterans Affairs Clinical Assessment, Reporting, and Tracking System (VA CART) Program.

BACKGROUND: Policies to reduce unnecessary hospitalizations after percutaneous coronary intervention (PCI) are intended to improve healthcare value by reducing costs while maintaining patient outcomes. Whether facility-level hospitalization rates after PCI are associated with cost of care is unknown. METHODS AND RESULTS: We studied 32,080 patients who received PCI at any 1 of 62 Veterans Affairs hospitals from 2008 to 2011. We identified facility outliers for 30-day risk-standardized hospitalization, mortality, and cost. Compared with the risk-standardized average, 2 hospitals (3.2%) had a lower-than-expected hospitalization rate, and 2 hospitals (3.2%) had a higher-than-expected hospitalization rate. We observed no statistically significant variation in facility-level risk-standardized mortality. The facility-level unadjusted median per patient 30-day total cost was $23,820 (interquartile range, $19,604-$29,958). Compared with the risk-standardized average, 17 hospitals (27.4%) had lower-than-expected costs, and 14 hospitals (22.6%) had higher-than-expected costs. At the facility level, the index PCI accounted for 83.1% of the total cost (range, 60.3%-92.2%), whereas hospitalization after PCI accounted for only 5.8% (range, 2.0%-12.7%) of the 30-day total cost. Facilities with higher hospitalization rates were not more expensive (Spearman ρ=0.16; 95% confidence interval, -0.09 to 0.39; P=0.21). CONCLUSIONS: In this national study, hospitalizations in the 30 day after PCI accounted for only 5.8% of 30-day cost, and facility-level cost was not correlated with hospitalization rates. This challenges the focus on reducing hospitalizations after PCI as an effective means of improving healthcare value. Opportunities remain to improve PCI value by reducing the variation in total cost of PCI without compromising patient outcomes.

Relation between door-to-balloon times and mortality after primary percutaneous coronary intervention over time: a retrospective study.

BACKGROUND: Recent reductions in average door-to-balloon (D2B) times have not been associated with decreases in mortality at the population level. We investigated this seemingly paradoxical finding by assessing components of this association at the individual and population levels simultaneously. We postulated that the changing population of patients undergoing primary percutaneous coronary intervention (pPCI) contributed to secular trends toward an increasing mortality risk, despite consistently decreased mortality in individual patients with shorter D2B times. METHODS: This was a retrospective study of ST-elevation myocardial infarction (STEMI) patients who underwent pPCI between Jan 1, 2005, and Dec 31, 2011, in the National Cardiovascular Data Registry (NCDR) CathPCI Registry. We looked for catheterisation laboratory visits associated with STEMI. We excluded patients not undergoing pPCI, transfer patients for pPCI, patients with D2B times less than 15 min or more than 3 h, and patients at hospitals that did not consistently report data across the study period. We assessed in-hospital mortality in the entire cohort and 6-month mortality in elderly patients aged 65 years or older matched to data from the Centers for Medicare and Medicaid Services. We built multilevel models to assess the relation between D2B time and in-hospital and 6-month mortality, including both individual and population-level components of this association after adjusting for patient and procedural factors. FINDINGS: 423 hospitals reported data on 150,116 procedures with a 55% increase in the number of patients undergoing pPCI at these facilities over time, as well as many changes in patient and procedural factors. Annual D2B times decreased significantly from a median of 86 min (IQR 65-109) in 2005 to 63 min (IQR 47-80) in 2011 (p<0·0001) with a concurrent rise in risk-adjusted in-hospital mortality (from 4·7% to 5·3%; p=0·06) and risk-adjusted 6-month mortality (from 12·9% to 14·4%; p=0·001). In multilevel models, shorter patient-specific D2B times were consistently associated at the individual level with lower in-hospital mortality (adjusted OR for each 10 min decrease 0·92; 95% CI 0·91-0·93; p<0·0001) and 6-month mortality (adjusted OR for each 10 min decrease, 0·94; 95% CI 0·93-0·95; p<0·0001). By contrast, risk-adjusted in-hospital and 6-month mortality at the population level, independent of patient-specific D2B times, rose in the growing and changing population of patients undergoing pPCI during the study period. INTERPRETATION: Shorter patient-specific D2B times were consistently associated with lower mortality over time, whereas secular trends suggest increased mortality risk in the growing and changing pPCI population. The absence of association of annual D2B time and changes in mortality at the population level should not be interpreted as an indication of its individual-level relation in patients with STEMI undergoing primary PCI. FUNDING: National Heart, Lung, and Blood Institute.

Door-to-balloon time and mortality among patients undergoing primary PCI.

BACKGROUND: Current guidelines for the treatment of ST-segment elevation myocardial infarction recommend a door-to-balloon time of 90 minutes or less for patients undergoing primary percutaneous coronary intervention (PCI). Door-to-balloon time has become a performance measure and is the focus of regional and national quality-improvement initiatives. However, it is not known whether national improvements in door-to-balloon times have been accompanied by a decline in mortality. METHODS: We analyzed annual trends in door-to-balloon times and in-hospital mortality using data from 96,738 admissions for patients undergoing primary PCI for ST-segment elevation myocardial infarction from July 2005 through June 2009 at 515 hospitals participating in the CathPCI Registry. In a subgroup analysis using a linked Medicare data set, we assessed 30-day mortality. RESULTS: Median door-to-balloon times declined significantly, from 83 minutes in the 12 months from July 2005 through June 2006 to 67 minutes in the 12 months from July 2008 through June 2009 (P<0.001). Similarly, the percentage of patients for whom the door-to-balloon time was 90 minutes or less increased from 59.7% in the first year to 83.1% in the last year (P<0.001). Despite improvements in door-to-balloon times, there was no significant overall change in unadjusted in-hospital mortality (4.8% in 2005-2006 and 4.7% in 2008-2009, P=0.43 for trend) or in risk-adjusted in-hospital mortality (5.0% in 2005-2006 and 4.7% in 2008-2009, P=0.34), nor was a significant difference observed in unadjusted 30-day mortality (P=0.64). CONCLUSIONS: Although national door-to-balloon times have improved significantly for patients undergoing primary PCI for ST-segment elevation myocardial infarction, in-hospital mortality has remained virtually unchanged. These data suggest that additional strategies are needed to reduce in-hospital mortality in this population. (Funded by the National Cardiovascular Data Registry of the American College of Cardiology Foundation.).

Comparison of performance on Hospital Compare process measures and patient outcomes between hospitals that do and do not participate in Acute Coronary Treatment and Intervention Outcomes Network Registry-Get With The Guidelines.

BACKGROUND: Acute Coronary Treatment and Intervention Outcomes Network Registry-Get With The Guidelines (ACTION Registry-GWTG) was designed to measure and improve the treatment and outcomes of patients with acute myocardial infarction (AMI), yet it is unknown whether performance of Medicare Hospital Compare metrics and outcomes differ between hospitals participating versus those not participating in the registry. METHODS: Using 2007 to 2010 Hospital Compare data, we matched participating to nonparticipating hospitals based on teaching status, size, percutaneous coronary intervention capability, and baseline (2007) Hospital Compare AMI process measure performance. We used linear mixed modeling to compare 2010 Hospital Compare process measure adherence, 30-day risk-adjusted mortality, and readmission rates. We repeated these analyses after stratification according to baseline performance level. RESULTS: Compared with nonparticipating hospitals, those participating were larger (median 288 vs 139 beds, P < .0001), more often teaching hospitals (18.8% vs 6.3%, P < .0001), and more likely had interventional catheterization lab capabilities (85.7% vs 34.0%, P < .0001). Among 502 matched pairs of participating and nonparticipating hospitals, we found high levels of process measure adherence in both 2007 and 2010, with minimal differences between them. Rates of 30-day mortality and readmission in 2010 were also similar between both groups. Results were consistent across strata of baseline performance level. CONCLUSIONS: In this observational analysis, there were no significant differences in the performance of Hospital Compare process measures or outcomes between hospitals in Acute Coronary Treatment and Intervention Outcomes Network Registry-Get With The Guidelines and other hospitals not in the registry. However, baseline performance on the Hospital Compare process measures was very high in both groups, suggesting the need for new quality improvement foci to further improve patient outcomes.

Association of Admission to Veterans Affairs Hospitals vs Non-Veterans Affairs Hospitals With Mortality and Readmission Rates Among Older Men Hospitalized With Acute Myocardial Infarction, Heart Failure, or Pneumonia.

IMPORTANCE: Little contemporary information is available about comparative performance between Veterans Affairs (VA) and non-VA hospitals, particularly related to mortality and readmission rates, 2 important outcomes of care. OBJECTIVE: To assess and compare mortality and readmission rates among men in VA and non-VA hospitals. DESIGN, SETTING, AND PARTICIPANTS: Cross-sectional analysis involving male Medicare fee-for-service beneficiaries aged 65 years or older hospitalized between 2010 and 2013 in VA and non-VA acute care hospitals for acute myocardial infarction (AMI), heart failure (HF), or pneumonia using the Medicare Standard Analytic Files and Enrollment Database together with VA administrative claims data. To avoid confounding geographic effects with health care system effects, we studied VA and non-VA hospitals within the same metropolitan statistical area (MSA). EXPOSURES: Hospitalization in a VA or non-VA hospital in MSAs that contained at least 1 VA and non-VA hospital. MAIN OUTCOMES AND MEASURES: For each condition, 30-day risk-standardized mortality rates and risk-standardized readmission rates for VA and non-VA hospitals. Mean aggregated within-MSA differences in mortality and readmission rates were also assessed. RESULTS: We studied 104 VA and 1513 non-VA hospitals, with each condition-outcome analysis cohort for VA and non-VA hospitals containing at least 7900 patients (men; ≥65 years), in 92 MSAs. Mortality rates were lower in VA hospitals than non-VA hospitals for AMI (13.5% vs 13.7%, P = .02; -0.2 percentage-point difference) and HF (11.4% vs 11.9%, P = .008; -0.5 percentage-point difference), but higher for pneumonia (12.6% vs 12.2%, P = .045; 0.4 percentage-point difference). In contrast, readmission rates were higher in VA hospitals for all 3 conditions (AMI, 17.8% vs 17.2%, 0.6 percentage-point difference; HF, 24.7% vs 23.5%, 1.2 percentage-point difference; pneumonia, 19.4% vs 18.7%, 0.7 percentage-point difference, all P < .001). In within-MSA comparisons, VA hospitals had lower mortality rates for AMI (percentage-point difference, -0.22; 95% CI, -0.40 to -0.04) and HF (-0.63; 95% CI, -0.95 to -0.31), and mortality rates for pneumonia were not significantly different (-0.03; 95% CI, -0.46 to 0.40); however, VA hospitals had higher readmission rates for AMI (0.62; 95% CI, 0.48 to 0.75), HF (0.97; 95% CI, 0.59 to 1.34), or pneumonia (0.66; 95% CI, 0.41 to 0.91). CONCLUSIONS AND RELEVANCE: Among older men with AMI, HF, or pneumonia, hospitalization at VA hospitals, compared with hospitalization at non-VA hospitals, was associated with lower 30-day risk-standardized all-cause mortality rates for AMI and HF, and higher 30-day risk-standardized all-cause readmission rates for all 3 conditions, both nationally and within similar geographic areas, although absolute differences between these outcomes at VA and non-VA hospitals were small.

Derivation and validation of a risk standardization model for benchmarking hospital performance for health-related quality of life outcomes after acute myocardial infarction.

BACKGROUND: Before outcomes-based measures of quality can be used to compare and improve care, they must be risk-standardized to account for variations in patient characteristics. Despite the importance of health-related quality of life (HRQL) outcomes among patients with acute myocardial infarction (AMI), no risk-standardized models have been developed. METHODS AND RESULTS: We assessed disease-specific HRQL using the Seattle Angina Questionnaire at baseline and 1 year later in 2693 unselected AMI patients from 24 hospitals enrolled in the Translational Research Investigating Underlying disparities in acute Myocardial infarction Patients' Health status (TRIUMPH) registry. Using 57 candidate sociodemographic, economic, and clinical variables present on admission, we developed a parsimonious, hierarchical linear regression model to predict HRQL. Eleven variables were independently associated with poor HRQL after AMI, including younger age, previous coronary artery bypass graft surgery, depressive symptoms, and financial difficulties (R(2)=20%). The model demonstrated excellent internal calibration and reasonable calibration in an independent sample of 1890 AMI patients in a separate registry, although the model slightly overpredicted HRQL scores in the higher deciles. Among the 24 TRIUMPH hospitals, 1-year unadjusted HRQL scores ranged from 67-89. After risk-standardization, HRQL score variability narrowed substantially (range=79-83), and the group of hospital performance (bottom 20%/middle 60%/top 20%) changed in 14 of the 24 hospitals (58% reclassification with risk-standardization). CONCLUSIONS: In this predictive model for HRQL after AMI, we identified risk factors, including economic and psychological characteristics, associated with HRQL outcomes. Adjusting for these factors substantially altered the rankings of hospitals as compared with unadjusted comparisons. Using this model to compare risk-standardized HRQL outcomes across hospitals may identify processes of care that maximize this important patient-centered outcome.