The Evolving Landscape of Impella® Use in the United ... · 08/01/2020 · adverse CV events in the primary intent to treat analysis, but did observe lower adverse events at 90

10.1161/CIRCULATIONAHA.119.044007

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The Evolving Landscape of Impella® Use in the United States Among Patients

Undergoing Percutaneous Coronary Intervention with Mechanical

Circulatory Support

Running Title: Amin et al.; Trends, Variation and Outcomes in Impella® Use

Amit P. Amin, MD, MSc1,2; John A. Spertus, MD, MPH3; Jeptha P. Curtis, MD4;

Nihar Desai, MD, MPH4; Frederick A. Masoudi, MD, MSc5; Richard G. Bach, MD1,2;

Christian McNeely, MD1,2; Firas Al-Badarin, MD, MSc3; John A. House, MS6;

Hemant Kulkarni, MD7; Sunil V. Rao, MD8

1Cardiovascular Division, Washington University School of Medicine, St. Louis, MO; 2Barnes-

Jewish Hospital, St. Louis, MO; 3Saint Luke’s Mid America Heart Institute, University of

Missouri-Kansas City, Kansas City, MO; 4Yale University, New Haven, CT; 5University of

Colorado Anschutz Medical Campus Aurora, CO; 6Premier, Inc, Premier Applied Sciences,

Charlotte, NC; 7M&H Research, LLC San Antonio, TX; 8The Duke Clinical Research Institute,

Durham, NC

Address for Correspondence:

Amit P. Amin, MD, MSc

Washington University School of Medicine

Cardiology Division, Campus Box 8086

660 S. Euclid Avenue, St. Louis, MO 63110

Tel: 314-286-2692

Fax: 314-747-1417

Email: [email protected].

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Abstract

Background: Impella® was approved for mechanical circulatory support (MCS) in 2008, but

large-scale, real-world data on its use are lacking. Our objective was to describe trends and

variations in Impella® use, clinical outcomes and costs across US hospitals in percutaneous

coronary intervention (PCI) patients treated with MCS (Impella® or intra-aortic balloon pump

(IABP)).

Methods: From the Premier Healthcare Database, we analyzed 48,306 patients undergoing PCI

with MCS at 432 hospitals between 1/2004-12/2016. Association analyses were performed at

three levels: time-period, hospitals and patients. Hierarchical models with propensity adjustment

were used for association analyses. We examined trends and variations in the proportion of

Impella® use, and associated clinical outcomes (in-hospital mortality, bleeding requiring

transfusion, acute kidney injury (AKI), stroke, length of stay (LOS) and hospital costs).

Results: Among PCI patients treated with MCS, 4,782 (9.9%) received Impella®; its use

increased over time, reaching 31.9% of MCS in 2016. There was wide variation in Impella® use

across hospitals (> 5-fold variation). Specifically, among Impella® patients, there was wide

variation in outcomes of bleeding (> 2.5-fold variation), and death, AKI and stroke (all ~1.5-fold

variation). Adverse outcomes and costs were higher in the Impella®-era (years 2008-2016) vs.

the pre-Impella® era (years 2004-2007). Hospitals with higher Impella® use had higher rates of

adverse outcomes and costs. After adjustment for the propensity score, and accounting for

clustering of patients by hospitals, Impella® use was associated with death: OR 1.24 (95%CI

1.13–1.36); bleeding: OR 1.10 (95%CI 1.00–1.21); and stroke: OR 1.34 (95%CI 1.18–1.53),

although a similar, non-significant result was observed for AKI: OR 1.08 (95%CI 1.00–1.17).

Conclusions: Impella® use is rapidly increasing among PCI patients treated with MCS, with

marked variability in its use and associated outcomes. Although unmeasured confounding cannot

be ruled out, when analyzed by time-periods, or at the hospital-level or the patient-level,

Impella® use was associated with higher rates of adverse events and costs. More data are needed

to define the appropriate role of MCS in patients undergoing PCI.

Key Words: Impella®; Intra-aortic balloon pump; mechanical circulatory support; percutaneous

coronary intervention; angioplasty procedure; cardiogenic shock.

Non-Standard Abbreviations and Acronyms

MCS, mechanical circulatory support

PCI, percutaneous coronary intervention

IABP, intra-aortic balloon pump

AKI, acute kidney injury

COPD, chronic obstructive pulmonary disease

CKD, chronic kidney disease

STEMI, ST segment elevation myocardial infarction

NSTEMI, non-ST segment elevation myocardial infarction

UA, unstable angina

GPIIb/IIIa inhibitors, glycoprotein IIb/IIIa inhibitors

ECMO, extra corporeal membrane oxygenation

PVAD, percutaneous ventricular assist device

LOS, length of stay

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OR, Odds ratio

MOR, median odds ratio

95% CI, 95% confidence interval

95% CrI, 95% credible interval

PHD, Premier healthcare database

USFDA, United States Food and Drug Administration

AHA, American Hospital Association

ICU, intensive care unit

ICD-9, international classification of diseases, 9th revision.

ICD-10, international classification of diseases, 10th revision.

CMS, centers for Medicare and Medicaid

MCCR, Medicare Cost to Charge Ratio

CPI, consumer pricing index

ICC, intra-class correlation coefficient

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Clinical Perspective

What is new?

• Among an unselected, real-world, clinical practice of PCI patients treated with MCS

devices, Impella® use was found to be rapidly increasing, with marked variability across

hospitals in not only its use, but also its associated adverse outcomes.

• When analyzed by time-periods, or at the level of hospitals, or at the level of patients,

Impella® use was associated with higher rates of adverse events and higher hospital

costs.

What are the clinical implications?

• The variability in Impella use, the variability in its associated outcomes and the

association of Impella use with higher adverse events and costs, underscores the need for

better defining the appropriate use of MCS devices with adequately powered randomized

clinical trials and prospective real-world evidence.

• Until then, perhaps a more measured approach is needed in clinical practice that balances

risks and benefits in complex patients undergoing PCI who require MCS devices.

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Introduction

Device options for mechanical circulatory support (MCS) to support high risk percutaneous

coronary intervention (PCI) include intra-aortic balloon pumps (IABP) and the intravascular

microaxial blood pump (Impella®). Impella® devices are catheter-based, miniaturized

ventricular assist pumps that can provide up to 5 liters of cardiac output and rapidly reduce left

ventricular preload.1 Whether support from Impella® devices translates into better outcomes in

PCI patients treated with MCS is unknown. The PROTECT-II Study randomized 452 patients

undergoing high risk PCI to IABP or Impella® 2.5 and found no difference in 30 or 90 day

adverse CV events in the primary intent to treat analysis, but did observe lower adverse events at

90 days in the Impella® 2.5 arm among per-protocol treated patients.2 Observational studies

have suggested higher survival rates with Impella® use in cardiogenic shock3-6 but large-scale

clinical trials have not been completed.7-11 The absence of data for cardiogenic shock has

resulted in limited guideline recommendations for Impella® use both in the United States and

Europe, raising the possibility of variability in its selection and use.12-14 Furthermore, there are

few data12-14 on trends in hospitals use of Impella® devices, or variations in use, and also

limited data on costs associated with Impella® use in patients undergoing PCI with MCS15, 16.

The Impella 2.5® device received United States Food and Drug Administration’s

(USFDA) 510(k) approval in June 2008 for high risk PCI and subsequently other devices

(Impella 5.0®, Impella CP®) have also received FDA approval with an expanded indication for

cardiogenic shock in April 2016. Thus, there is an opportunity to analyze a natural experiment

among PCI patients with MCS by comparing the scenarios before and after the Impella® devices

became available. Therefore, to better clarify the potential risks and benefits of Impella® use as a

means of MCS at the time-period level, the hospital-level and the patient-level, we examined

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patients undergoing PCI with MCS in a large dataset representative of contemporary PCI

practices in the United States to address the following objectives:

1) describe trends in Impella® use;

2) examine variation in Impella® use across hospitals; and separately examine, only in

the subset of patients who received Impella® devices, the hospital variation in clinical outcomes,

costs and length of stay;

3) compare clinical outcomes, hospitalization costs and length of stay a) in the pre-

Impella® vs. Impella® era and b) across low- vs. high-Impella® use hospitals (grouped by

quartiles of Impella® use);

4) examine the association between Impella® (versus IABP) use and clinical outcomes

(in-hospital mortality, bleeding, acute kidney injury (AKI) and stroke) .

Methods

The data, analytic methods, and study materials for this analysis will not be made

available to other researchers.

Study participants

To capture the practice patterns associated with Impella® use, we used the Premier® healthcare

database (PHD), an all payer database representing ~20% of all acute care hospitalizations in the

United States.17 It has similar distributions for hospital region and hospital characteristics as the

American Hospital Association (AHA) and has less than 1% records with incomplete

information. While the number of hospitals contributing to the PHD does change from year to

year typically more hospitals are added to the database and very few are removed with a current

median duration of 7 years.17 Data from the PHD has been used in numerous publications related

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to patient care patterns, outcomes, burden of illness over time, comparative effectiveness

analyses, cost analyses and cost-effectiveness studies.17

The dataset used in this study covered a 13-year period from 1/2004 to 12/2016. The

calendar years 2004-2007 were considered the Pre-Impella® era and the calendar years 2008-

2016 were considered the Impella® era. To keep the population more uniform, and limit

unmeasured confounding, we only included patients if the device was billed on the same day of

PCI at the PCI performing hospital, essentially excluding patients who either clinically

deteriorated, or had already developed complications with MCS placement, or received MCS and

were transferred.

The inclusion and exclusion flowchart for defining the study population is shown in

supplementary figure 1. Data from a total of 1,781,900 PCIs during the study period were

available from the Premier dataset. From this set, we selected the subset of patients undergoing

PCI with MCS, defined as use of either an Impella® device (n = 5,887) or an intra-aortic balloon

pump (IABP) (n = 46,690) on the day of PCI. We excluded patients who received both Impella®

and IABP devices (n = 828), as these patients may have required escalation of MCS, and our

intent was to examine Impella® use as a primary strategy. We also excluded patients in whom

covariate information on 37 potential confounders was missing (n = 2,615). The degree of

missing covariate information was equal in the Impella® (N=277/5,059, 5.48%) patients and

IABP (N=2,338/45,862, 5.10%) patients. Thus, a total of 48,306 patients were included in the

study; with Impella® being used in 4,782 patients and IABP being used in 43,524. Institutional

Review Board approval was granted by Washington University in St Louis, MO, which

considered this study to not be human subjects research and the requirement for informed

consent was waived.

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Outcomes, predictors and costs

The Premier® database contains information on the socio-demographic characteristics,

comorbidities, interventional procedures, medications, outcomes, the total length of hospital and

intensive care unit (ICU) length of stay and hospitalization costs form a ‘hospital’ perspective,

based on a micro-costing approach.

The database contains ICD-9 and ICD-10 codes with detailed billing information. ICD-10

codes were mapped back to ICD-9 using CMS General Equivalence Mappings, however the

ICD-10 codes were used when there were no direct mappings.17 To identify Impella® ICD-9

code 37.68 and ICD-10 codes 5A0221D, 5A0211D were first used to identify potential usage

and the billing information was used to determine named devices and matched to Impella®

devices. Impella® device usage was reported if both an ICD code and a billed Impella® device

was present. A similar approach to identify IABP was used where first ICD-9 code 37.61 and

ICD-10 codes 5A02210, 5A02110 were used to identify potential usage and then verified by the

billing information. If the Impella® or IABP devices were billed on the same day as the PCI,

only then were they included in the analysis. Use of these MCS devices before or after the day of

PCI were excluded. We examined the following four clinical outcomes during index

hospitalization: death, bleeding requiring transfusion, acute kidney injury (AKI) and stroke.

Death included all-cause mortality during the index hospitalization at the PCI performing

hospital. Clinically significant bleeding was defined as a bleeding event requiring transfusion

(supplementary material). Stroke comprised of either ischemic stroke, hemorrhagic stroke

intracerebral hemorrhage or transient ischemic attack (supplementary material). All the above

outcomes were required to be present at discharge but absent in ‘present on admission’ codes.

The validity of identifying comorbidities, complications, and procedures via ICD-9 and ICD-10

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codes in administrative datasets has been previously demonstrated and codes were selected based

on previously validated algorithms.18-21

Costs to the hospital and charges to the payer can be determined from the PHD from the

charge master, which is a comprehensive table of items billable to a patient or health insurance

provider.17 It includes hospital services, medical procedures, equipment fees, supplies, drugs and

diagnostic evaluations such as imaging and laboratory tests. Days of services/supplies/drugs

administered and billed are documented. Procedural costs are determined via hospitals’ cost

accounting systems using a ‘micro-costing’ approach.17 For a small proportion of patients when

micro costing was not available, Premier is provided the charges and Premier assigns Medicare

Cost to Charge Ratios (MCCR) to the data provided. Regardless of the source of the cost and

charge data, they are reviewed and validated against the data from the hospital and confirmed to

be within certain variances, before use within the database. We removed observations with

missing cost data or those below 1 percentile (N=482). All costs were inflation-adjusted to 2016

US dollars using the medical consumer pricing index (CPI) available from the Bureau of Labor

Statistics.

Statistical analyses

Our objectives were to describe the trends in Impella® use; variation in Impella® use and its

outcomes over 13 years from 1/2004 to 12/2016; and to compare the clinical outcomes (in-

hospital mortality, bleeding requiring transfusion, AKI and stroke) in patients who received

Impella® vs. IABP, among patients undergoing PCI with MCS.

Overall analytical approach

Recognizing the potential for confounding at the level of both patients and hospitals in all

association analyses, we first developed a propensity score, using a logistic regression model, to

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predict the likelihood of Impella® use based on patients’ clinical characteristics (supplementary

figure 2); Next, we used mixed effects logistic or linear regression models that used hospital

identifier as random effect to account for hospital-level random effects and the propensity score.

These steps are discussed in detail below.

1. Propensity Score Adjustment: The propensity score predicting Impella® use was

generated using multivariable logistic regression with Impella® use as the dependent variable

and a total of 37 potential confounders as the independent variables listed in Supplementary

Figure 2, Panel A. Information on all the covariates was available in 48,306 patients from 432

US hospitals. The balance of covariates before and after propensity adjustment for all the 37

confounders is shown in Supplementary Figure 2, Panel A.

2. Mixed effects modeling: We then developed a hierarchical model, with ‘hospital site’ as a

random effect, adjusted for patients’ propensity to receive an Impella® device. We examined

inter-hospital variation from these models as follows: from linear regression models (with

hospital cost or length of stay as the dependent variable) we estimated the intra-class correlation

coefficient (ICC) as the contribution of the hospital-level variance to the overall variance22; from

logistic regression models we estimated the median odds ratios (MOR) and their 95% credible

interval (CrI) as described by Larsen and Merlo23. The MOR represents the median of all odds

ratios (ORs) when comparing the odds of receiving Impella® for all possible pairs of patients

with identical characteristics presenting at 2 different randomly chosen hospitals. MOR larger

than unity indicates variation in the association across hospitals.23

Statistical analyses for time trends

We examined the temporal trends in: Impella® use by plotting the proportion of Impella® use

amongst patients undergoing PCI with MCS devices, by year. When examining these trends in

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Impella® use, we also plotted trends in Impella® use among critically-ill patients vs. those not

critically-ill to examine if Impella® was being used more in critically ill patients. A subset of

‘critically-ill’ patients were identified as those who received mechanical ventilation or cardiac

arrest or had a diagnosis of cardiogenic shock.

Statistical analyses to quantify variation across hospitals

We examined the variation in Impella® use across hospitals univariately and after adjusting for

patient characteristics; and expressed using the MOR. We separately examined the variation

across hospitals in outcomes, costs and length of stay in only the subset of patients who received

Impella® device (n=4,782).

Association analyses at the time-period level, hospital-level and patient-level

To examine the association of Impella® devices with clinical outcomes and costs, we compared

the pre-Impella® era (n=12,540) and Impella® era (n=35,766). We then grouped hospitals by

quartiles of Impella® use (with Quartile #1 being the lowest use, and Quartile #4 being the

highest use) to examine the associations of increasing Impella® use with outcomes. Next, we

performed patient level observational comparative effectiveness analyses comparing patients

receiving Impella® or IABP.

Sensitivity analyses

Finally, to examine the robustness of our results we also performed the following sensitivity

analyses. First, we repeated all analyses after excluding the small subset of patients escalated to

use of ECMO (n=163 [0.34%]). Second, we performed sensitivity analyses excluding hospitals

with <10 years of data . Third, to account for changing trends in MCS use, we included calendar

year as a covariate in the hierarchical regression models and repeated the analyses. Finally, we

performed a series of falsification endpoint analyses24, 25, in which endpoints not expected to be

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influenced by MCS choice, but would be influenced by confounding factors, were tested to

assess residual bias. Unrelated but acute falsification endpoints indicative of unmeasured frailty

or sickness (community-acquired pneumonia, diarrhea, cellulitis, deep vein thrombosis, intestinal

obstruction and osteomyelitis) were compared between Impella® vs. IABP groups using odds

ratios (ORs) and 95% confidence intervals (CI).24, 25 For all analyses, the statistical significance

was tested at a type I error rate of 0.05 and conducted using the Stata 12.0 (Stata Corp, College

Station, TX) software package.

Results

Study participants

A total of 48,306 patients undergoing PCI with MCS from 432 hospitals over 13 years from

2004 to 2016 were included in the study. Of these patients 4,782 (9.9%) received an Impella®

device, and the remaining 43,524 (90.1%) received an intra-aortic balloon pump (IABP). Clinical

characteristics of these patients are detailed in Table 1. Briefly, patients undergoing PCI with

MCS had a high prevalence of comorbidities: heart failure (50%), chronic renal failure (20%),

diabetes (40%), COPD (20%) and atrial fibrillation (23%). Cardiogenic shock was present in

50%, 38% required mechanical ventilation, 62% of patients presented with a STEMI and 26%

underwent multivessel PCI. Patients receiving Impella® were more likely than those receiving

IABP to be male with Medicare insurance, non-white, and had a higher prevalence of diabetes,

heart failure, CKD, COPD, multivessel disease, greater use of Ticagrelor and Bivalirudin, but

lesser use of warfarin and GPIIb/IIIa use (Table 1). However, Impella® was used less in patients

who required mechanical ventilation or who had cardiac arrest or cardiogenic shock (Table 1).

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Trends in Impella® use

When examined in the context of the entire Premier PCI population (N = 1,733,594), use of

MCS devices remained stable around 2.5% of all PCI procedures until 2008, thereafter

increasing to 3.5% in 2016 (Supplementary figure 3). The overall rise in MCS use after 2008

closely paralleled a concomitant rise in patients who received Impella® while the proportion of

patients who received IABP remained stable or declined slightly during the post-Impella® era.

Within the subset of the MCS-treated patients, the proportion of Impella® utilization increased

steadily, reaching 31.9% in 2016 (Figure 1). We did not observe increasing Impella® use in

more critically ill patients, defined by one or more of the following: presence of mechanical

ventilation, cardiac arrest or cardiogenic shock (Supplementary Figure 4). Also, we observed that

adjusted costs of hospitalization remained stable in the pre-Impella era from $46,989 in 2004 to

$47,282 in 2009, but increased to $51,202 in 2016, in the post-Impella® era. In contrast to the

increasing cost trend in patients undergoing PCI with MCS, when we examined the costs of PCI

when MCS devices were not used (N= 1,724,546), we observed a decline in costs

(Supplementary figure 5).

Variation in Impella® use across hospitals

We observed wide variation across hospitals in the proportional use of Impella® among patients

undergoing PCI with MCS, ranging from 0% to 100% (Figure 2). After adjustment for the

propensity score for Impella® use, and accounting for clustering of patients by hospitals in

mixed effects model, the MOR was estimated to be 5.77 (CrI 4.77 – 7.06), indicating that

statistically identical patients had an average 5.77-fold differing likelihood of receiving Impella®

at 1 randomly selected hospital as compared with another (Figure 2). Further, this variation

across hospitals was observed throughout the Impella® era (Figure 2, inset).

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Variation in outcomes, costs and length of stay in patients who received Impella®

Specifically, among patients who received Impella® (n=4,782), we determined if there was

variability in Impella®-associated outcomes via additional mixed effects modeling studies. As

shown in Table 2, we found that there was significant inter-hospital variation in clinical

outcomes when Impella® was used. The median odds ratio (MOR) estimates were highest for

bleeding (MOR 2.62, indicating an average 2.6-fold greater likelihood of a clinically similar

patient experiencing a bleeding complication, followed by death (MOR 1.71), AKI (MOR 1.53)

and stroke (MOR 1.47) even after accounting for clustering of patients across hospitals (full

results in Table 2). Thus, patients with a statistically similar clinical profile who received an

Impella® device tended to have variable outcomes across hospitals. On the other hand, the ICC

estimates capturing variation in LOS and cost association across hospitals indicated that hospital

factors only explained ~5-7% of variation in LOS and ~18% of variation in hospitalization costs,

indicating less variation across hospitals in these outcomes (Table 2).

Clinical outcomes and hospitalization costs in the Pre-Impella® and Impella® era

We conducted a comparison of the adjusted clinical outcomes, LOS and costs between the pre-

Impella® (n=12,540) and Impella® eras (n=35,766) (Table 3) and observed higher rates of in-

hospital death (OR 1.17), AKI (OR 1.91) and stroke (OR 3.34) in the Impella® era. While the

LOS, and ICU stay did not change significantly in the Impella® era, average per-patient

hospitalization costs increased by US$ 1,775.

High- vs. Low-Impella® use across hospitals and its association with outcomes

When we categorized hospitals by quartiles of Impella® use, we found the adjusted odds ratios

of clinical outcomes differed such that hospitals with higher use of Impella® had a higher risk of

death, bleeding, AKI and stroke as compared to hospitals with lower use of Impella®, after

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adjusting for the propensity score and accounting for clustering of patients across hospitals

(Table 4). We also observed a shorter length of stay in high-Impella® use hospitals both in and

out of the ICU. However, hospitalization costs in high-use hospitals exceeded costs in low-use

hospitals by at least $10,000 (Table 4).

Individual patient comparative effectiveness analyses

After adjustment for the propensity score for Impella® use, and accounting for clustering of

patients by hospitals in hierarchical models, Impella® use was associated with a higher risk of

the three outcomes [death: OR 1.24 (95% CI 1.13 - 1.36); bleeding: OR 1.10 (95% CI 1.00 –

1.21); and stroke: OR 1.34 (95% CI 1.18 – 1.53)] although a similar, but non-significant result

was observed for AKI: OR 1.08 (95% CI 1.00 – 1.17); (Figure 3).

Sensitivity analyses and falsification endpoint analysis

Numerous sensitivity analyses were performed to evaluate the robustness of the study results as

follows: First, hospital-level variation remained comparably high after a) excluding ECMO

patients; b) adding calendar year as covariate (adjusting for time trends); and c) excluding

hospitals contributing <10 years data. (Supplementary Table 1). Second, the outcome differences

across pre-Impella® era vs. Impella® era remained significant after a) excluding ECMO

patients; b) excluding hospitals with <10 years of data and; c) excluding hospitals with <10 years

of data and excluding ECMO patients. We observed similar variation in outcomes in each of

these sensitivity analyses as the primary analysis (Supplementary Table 2). Third, the differences

between high-Impella® use vs. low-Impella® use hospitals were demonstrable even after

excluding hospitals contributing <10 years data (Supplementary Table 3). Fourth, the strength

and direction of association of Impella® use with clinical outcomes was essentially unchanged

significant even after a) excluding ECMO patients; b) excluding hospitals with <10 years of data;

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and c) excluding hospitals with <10 years of data and excluding ECMO patients (Supplementary

Table 4). Lastly, In falsification endpoint analysis, we found no association of Impella® use with

a) community-acquired pneumonia and b) a combined endpoint of acute diarrhea, cellulitis, deep

vein thrombosis, intestinal obstruction or osteomyelitis (Supplementary Figure 6), indicating that

the adverse outcomes associated with Impella® use reported in the study, were unlikely to be

driven by unmeasured comorbid conditions or its use in sicker patients.

Discussion

Several important findings were observed in this large study of contemporary US practices of

Impella® use among 48,306 patients undergoing PCI with MCS from 432 hospitals over 13

years from 2004 to 2016. First, the use of Impella® steadily increased, especially in the recent

years, reaching 31.9% of cases of PCI with MCS in 2016. In contrast to the expectation that

Impella® was being used in the sicker patients, we observed a lower use of Impella® in critically

ill patients with cardiac arrest, mechanical ventilation or cardiogenic shock (Supplementary

Figure 4). Second, with increasing Impella® use, we observed a concurrent increase in the cost

of hospitalization among patients undergoing PCI with MCS after 2009, when Impella® devices

became available. This contrasts with a decreasing trend in PCI costs in the non MCS

population, suggesting that MCS devices may be a contributor to higher costs. Our findings of

increasing hospitalization costs over time in PCI patients with MCS is consistent with a prior

study from the Canadian health system perspective observing a higher cost associated with

Impella® use.26 Third, in this population of PCI patients requiring MCS, there was more than 5-

fold variation in the use of Impella® across hospitals for statistically comparable patients.

Fourth, when comparing differential time periods of pre-Impella® and Impella® eras, we

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observed that the outcomes among PCI patients receiving MCS were not any better in the

Impella® era. In the Impella® era, rates of death, AKI, stroke and costs were higher as compared

with the pre-Impella® era. Fifth, when comparing hospitals with high- vs. low-use of Impella®,

we observed that the outcomes were not better in the high use hospitals. In the highest use

quartile of hospitals, we observed a higher rate of death, bleeding, AKI, stroke and cost, but a

shorter length of stay when compared with hospitals having a lower use of Impella® devices.

Lastly, comparative effectiveness of Impella® vs IABP demonstrated that Impella® use was

associated with higher mortality, bleeding, and stroke. These results underscore the need for

higher quality evidence to inform clinical guidelines for the use of hemodynamic support

possibly contributing to variation in adverse outcomes associated with Impella® use. Trials such

as DanGerShock (ClinicalTrials.gov Identifier: NCT01633502), randomizing shock patients to

Impella® vs. no Impella® may shed light on some of these issues.

There was an association of higher risk of bleeding with Impella® use vs. IABP use in

the hospital-level and patient-level analyses of our study. While bleeding complications have

been associated with larger bore access site previously27, the association of Impella® use with

AKI is not well understood. In higher Impella® use hospitals (vs. lower Impella® use hospitals),

and Impella® era vs pre-Impella® era analyses we observed a greater risk of AKI and in patient-

level comparative effectiveness analysis, we observed a trend towards greater AKI. These

findings are at odds with a prior observation from a single center of 230 patients which found a

lower risk of AKI28, but are in agreement with a meta-analysis27 which showed a higher risk of

AKI associated with Impella® use. The PROTECT II randomized trial showed no change in

creatinine clearance between Impella® and IABP patients 24 hours after PCI in comparison with

baseline (4.65 vs 4.661, p=0.988), despite the higher volume of contrast media received by

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Impella® patients.2 In reality, AKI is a multifactorial adverse event, dependent on many factors

including the comorbidities, presence of cardiogenic shock, contrast volume use and indication

for the PCI procedure. It is possible that these differences in findings are due to differences in the

risk profile of patients across studies.

In this study we noted not only a wide variation in the use of Impella® across hospitals,

but also a wide variation in the outcomes when Impella® was used. Particularly noteworthy is

the >2.5-fold variation in bleeding events implying that operator- and hospital- practices

currently lack standardization and may be deficient in adherence to best practices for preventing

bleeding complications associated with large bore sheaths. Certainly, the high-Impella® use

hospitals appeared to have a reduction in the higher risk of bleeding from 33% (Quartile 1) to

17% (quartile 4) (Table 4), confirming the well-recognized ‘volume-outcome’ relationship in

prior studies or the ‘learning curve’ seen in in the PROTECT II trial29. In contrast to bleeding,

the variation in incremental costs associated with Impella® across hospitals was smaller (ICC

17.8%) likely because of the uniformly high cost of the device. Whether mitigating bleeding

complications, associated with increased costs and worse clinical outcomes, will result in

superior outcomes amongst this sick population remains to be seen.

The occurrence of stroke associated with Impella® use was higher in our study than

PROTECT II trial2. Consistent with our study, a European study showed a high risk of stroke

with Impella®.30 Early studies are emerging that suggest a biologic plausibility with a higher rate

of stroke with greater duration of Impella® support31 or lower levels of anticoagulation with

anti-Xa levels <0.1 u/ml32. These data suggest that in real world practice where trial conditions

cannot be met, lower levels of anticoagulation or longer duration of Impella® use may be

associated with higher stroke risk. Further supporting this premise is the fact that in PROTECT

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II, IABP patients had longer duration of support as compared to Impella® patients.2 However,

further studies are needed to better understand this association.

Our findings are consistent with prior studies. A study from the National Inpatient

Sample also found a substantial increase in the use of PVADs in recent years with a higher risk

of mortality, and higher associated cost33, indicating consistency across different populations.

Another study found that contrary to the belief that Impella® was being used in sicker patients,

Impella® was being used in a lower risk patients (more likely to be elective patients, less likely

to have shock and less likely to have STEMI than IABP patients)34, a finding also seen in our

study.

Limitations

The results of our study should be interpreted within the context of the following potential

limitations. First, despite adjustment with propensity scores and hierarchical models to account

for clustering of patients by hospitals, this is an observational study and cannot prove causation

and the comparative effectiveness results cannot rule out unmeasured confounding nor selection

bias. The association of Impella® use with a higher rate of adverse events or higher costs should

not be assumed to be causally linked with each other as these may be due to unmeasured

confounding amongst patients selected for PCI with Impella®. Nevertheless, these observations

are important as they describe the contemporary practice of MCS use and the costs and outcomes

trends in the United States and warrant further examination in prospective studies. Furthermore,

numerous sensitivity analyses and falsification endpoint analyses demonstrated the robustness of

these results. We found a higher risk of adverse clinical outcomes and costs at higher Impella®

use hospitals (vs. lower Impella® use hospitals) and Impella® era (vs. pre-Impella® era), a

comparison that is less likely to be influenced by confounding by indication. Second, Premier is

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an administrative database and the outcomes of death, bleeding, AKI and stroke are derived from

administrative codes with potential for misclassification. Nonetheless they were derived from

discharge codes and were absent in ‘present on arrival’ codes. Third, we did not have

information on the angiographic details and were therefore unable to adjust for anatomic

complexity or other clinical factors. Replicating this work in clinical registries with granular

angiographic data, such as the National Cardiovascular Data Registry could help validate these

observations. Fourth, since the definition of cardiogenic shock is not based on accurate

hemodynamic data, we chose to use a population where a decision to use MCS support had

already been made based on clinical circumstances; this may have resulted in the inclusion of

some patients with other forms of shock in our analysis and precluded our ability to compare the

outcomes of patients with shock who did not receive MCS. Nonetheless, MCS device use

represents the real-world clinicians’ choice of Impella® use amongst less selected patients

undergoing PCI with MCS than in randomized clinical trials. It is also important to note that by

including only those patients whose day of PCI matched the day of MCS device use, we

excluded patients whose shock preceded or developed after PCI. Fifth, our analyses did not

account for the type of Impella® device used such as Impella® 2.5®, Impella CP® or Impella

5.0® which may provide different degree of hemodynamic support. Sixth, the significant

variation in outcomes observed amongst the subset of Impella® patients could result from not

only physician technique or hospital practices but also the selection of patients. Nonetheless,

Impella® was used more common in lower risk patients and this variation persisted despite

adjusting for propensity score and clustering across hospitals and therefore this variation is

important to report. Seventh, costs are from the hospital perspective and short-term costs limited

to the index hospitalization. It is possible that longer-term costs from a societal perspective may

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be lower with Impella®. Finally, the clinical reasoning behind selection of Impella® use cannot

be ascertained from the data and could have resulted in known or unknown residual confounding

in the regression models, despite propensity score adjustment and accounting for clustering by

hospitals.

Conclusions

In conclusion, Impella® is increasingly being utilized instead of IABP to support PCI in the

United States, but the associated clinical outcomes did not show any substantial improvement,

while costs of hospitalization rose. Moreover, there exists a wide variation not only in the use of

Impella® across hospitals but also in its associated outcomes across hospitals. Although

unmeasured confounding cannot be ruled out, when analyzed by time periods, or at the level of

hospitals or at the level of patients, Impella® use was associated with higher rates of adverse

events and increased costs. These data underscore the need for defining the appropriate use of

MCS in patients undergoing PCI with appropriately powered prospective randomized controlled

trials.

Disclosures

Dr. Amit P. Amin – has received a comparative effectiveness research KM1 career development

award from the Clinical and Translational Science Award (CTSA) program of the National

Center for Advancing Translational Sciences of the National Institutes of Health, Grant Numbers

UL1TR000448, KL2TR000450, TL1TR000449 and the National Cancer Institute of the National

Institutes of Health, Grant Number 1KM1CA156708-01; an AHRQ R18 grant award (Grant

Number R18HS0224181-01A1), has received an unrestricted grant from MedAxiom Synergistic

Healthcare Solutions Austin, TX and is a consultant to Terumo and GE Healthcare. Dr. John A.

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Spertus discloses an equity interest in Health Outcomes Sciences and serves on the

Cardiovascular Scientific Advisory Board of United Healthcare and the board of Blue Cross

Blue Shield of Kansas City. Dr. Hemant Kulkarni provides research consultancy to MedAxiom –

Synergistic Healthcare Solutions Austin, TX. Dr. Masoudi has a contract with the American

College of Cardiology for his role as Chief Science Officer of the NCDR. Dr. Curtis reports

salary support under contracts with CMS and ACC, and equity in Medtronic. Dr. Sunil V. Rao

reports no disclosures. The other authors have nothing to disclose.

Sources of Funding

None.

Role of any Sponsor

No sponsor participated in the design and conduct of the study, collection, analysis, or

interpretation of the data, nor in the preparation, review, nor approval of the manuscript.

Data Access and Responsibility: Mr. House and Dr. Kulkarni had full access to the data in the

study and take responsibility for the integrity of the data and the accuracy of the data analysis.

References

1. Burzotta F, Russo G, Previ L, Bruno P, Aurigemma C and Trani C. Impella: pumps

overview and access site management. Minerva Cardioangiol. 2018;66:606-611.

2. O'Neill WW, Kleiman NS, Moses J, Henriques JP, Dixon S, Massaro J, Palacios I, Maini

B, Mulukutla S, Dzavik V, Popma J, Douglas PS and Ohman M. A prospective, randomized

clinical trial of hemodynamic support with Impella 2.5 versus intra-aortic balloon pump in

patients undergoing high-risk percutaneous coronary intervention: the PROTECT II study.

Circulation. 2012;126:1717-1727.

Dow


ovember 19, 2019


23

3. Basir MB, Kapur NK, Patel K, Salam MA, Schreiber T, Kaki A, Hanson I, Almany S,

Timmis S, Dixon S, Kolski B, Todd J, Senter S, Marso S, Lasorda D, Wilkins C, Lalonde T,

Attallah A, Larkin T, Dupont A, Marshall J, Patel N, Overly T, Green M, Tehrani B, Truesdell

AG, Sharma R, Akhtar Y, McRae T, 3rd, O'Neill B, Finley J, Rahman A, Foster M, Askari R,

Goldsweig A, Martin S, Bharadwaj A, Khuddus M, Caputo C, Korpas D, Cawich I, McAllister

D, Blank N, Alraies MC, Fisher R, Khandelwal A, Alaswad K, Lemor A, Johnson T, Hacala M,

O'Neill WW and National Cardiogenic Shock Initiative I. Improved Outcomes Associated with

the use of Shock Protocols: Updates from the National Cardiogenic Shock Initiative. Catheter

Cardiovasc Interv. 2019;93:1173-1183.

4. O'Neill WW, Grines C, Schreiber T, Moses J, Maini B, Dixon SR and Ohman EM.

Analysis of outcomes for 15,259 US patients with acute myocardial infarction cardiogenic shock

(AMICS) supported with the Impella device. Am Heart J. 2018;202:33-38.

5. Basir MB, Schreiber T, Dixon S, Alaswad K, Patel K, Almany S, Khandelwal A, Hanson

I, George A, Ashbrook M, Blank N, Abdelsalam M, Sareen N, Timmis SBH and O'Neill Md

WW. Feasibility of early mechanical circulatory support in acute myocardial infarction

complicated by cardiogenic shock: The Detroit cardiogenic shock initiative. Catheter Cardiovasc

Interv. 2018;91:454-461.

6. Basir MB, Schreiber TL, Grines CL, Dixon SR, Moses JW, Maini BS, Khandelwal AK,

Ohman EM and O'Neill WW. Effect of Early Initiation of Mechanical Circulatory Support on

Survival in Cardiogenic Shock. Am J Cardiol. 2017;119:845-851.

7. Ouweneel DM, Engstrom AE, Sjauw KD, Hirsch A, Hill JM, Gockel B, Tuseth V, van

der Schaaf RJ and Henriques JP. Experience from a randomized controlled trial with Impella 2.5

versus IABP in STEMI patients with cardiogenic pre-shock. Lessons learned from the IMPRESS

in STEMI trial. Int J Cardiol. 2016;202:894-896.

8. Ouweneel DM, Eriksen E, Seyfarth M and Henriques JP. Percutaneous Mechanical

Circulatory Support Versus Intra-Aortic Balloon Pump for Treating Cardiogenic Shock: Meta-

Analysis. J Am Coll Cardiol. 2017;69:358-360.

9. Ouweneel DM, Eriksen E, Sjauw KD, van Dongen IM, Hirsch A, Packer EJ, Vis MM,

Wykrzykowska JJ, Koch KT, Baan J, de Winter RJ, Piek JJ, Lagrand WK, de Mol BA, Tijssen

JG and Henriques JP. Percutaneous Mechanical Circulatory Support Versus Intra-Aortic Balloon

Pump in Cardiogenic Shock After Acute Myocardial Infarction. J Am Coll Cardiol.

2017;69:278-287.

10. Seyfarth M, Sibbing D, Bauer I, Frohlich G, Bott-Flugel L, Byrne R, Dirschinger J,

Kastrati A and Schomig A. A randomized clinical trial to evaluate the safety and efficacy of a

percutaneous left ventricular assist device versus intra-aortic balloon pumping for treatment of

cardiogenic shock caused by myocardial infarction. J Am Coll Cardiol. 2008;52:1584-1588.

11. Thiele H, Jobs A, Ouweneel DM, Henriques JPS, Seyfarth M, Desch S, Eitel I, Poss J,

Fuernau G and de Waha S. Percutaneous short-term active mechanical support devices in

cardiogenic shock: a systematic review and collaborative meta-analysis of randomized trials. Eur

Heart J. 2017;38:3523-3531.

12. Shah M, Patnaik S, Patel B, Ram P, Garg L, Agarwal M, Agrawal S, Arora S, Patel N,

Wald J and Jorde UP. Trends in mechanical circulatory support use and hospital mortality among

patients with acute myocardial infarction and non-infarction related cardiogenic shock in the

United States. Clin Res Cardiol. 2018;107:287-303.

13. Strom JB, Zhao Y, Shen C, Chung M, Pinto DS, Popma JJ, Cohen DJ and Yeh RW.

Hospital Variation in the Utilization of Short-Term Nondurable Mechanical Circulatory Support

Dow


ovember 19, 2019


24

in Myocardial Infarction Complicated by Cardiogenic Shock. Circ Cardiovasc Interv.

2019;12:e007270.

14. Strom JB, Zhao Y, Shen C, Chung M, Pinto DS, Popma JJ and Yeh RW. National trends,

predictors of use, and in-hospital outcomes in mechanical circulatory support for cardiogenic

shock. EuroIntervention. 2018;13:e2152-e2159.

15. Gregory D, Scotti DJ, de Lissovoy G, Palacios I, Dixon S, Maini B and O'Neill W. A

value-based analysis of hemodynamic support strategies for high-risk heart failure patients

undergoing a percutaneous coronary intervention. American health & drug benefits. 2013;6:88-

99.

16. Roos JB, Doshi SN, Konorza T, Palacios I, Schreiber T, Borisenko OV and Henriques JP.

The cost-effectiveness of a new percutaneous ventricular assist device for high-risk PCI patients:

mid-stage evaluation from the European perspective. J Med Econ. 2013;16:381-390.

17. Premier Applied Sciences® PI. Premier Healthcare Database White Paper: Data that

informs and performs. 2018, URL:

https://products.premierinc.com/downloads/PremierHealthcareDatabaseWhitepaper.pdf

18. McCormick N, Bhole V, Lacaille D and Avina-Zubieta JA. Validity of Diagnostic Codes

for Acute Stroke in Administrative Databases: A Systematic Review. PloS one.

2015;10:e0135834.

19. McCormick N, Lacaille D, Bhole V and Avina-Zubieta JA. Validity of myocardial

infarction diagnoses in administrative databases: a systematic review. PloS one. 2014;9:e92286.

20. Quan H, Li B, Saunders LD, Parsons GA, Nilsson CI, Alibhai A and Ghali WA.

Assessing validity of ICD-9-CM and ICD-10 administrative data in recording clinical conditions

in a unique dually coded database. Health services research. 2008;43:1424-1441.

21. Quan H, Parsons GA and Ghali WA. Assessing accuracy of diagnosis-type indicators for

flagging complications in administrative data. Journal of clinical epidemiology. 2004;57:366-

372.

22. Snijders TAB and Bosker RJ. Multilevel analysis: an introduction to basic and advanced

multilevel modeling. 1st ed ed. Thousand Oaks, CA: Sage Publications; 1999.

23. Larsen K and Merlo J. Appropriate assessment of neighborhood effects on individual

health: integrating random and fixed effects in multilevel logistic regression. American journal

of epidemiology. 2005;161:81-88.

24. Prasad V and Jena AB. Prespecified falsification end points: can they validate true

observational associations? JAMA. 2013;309:241-242.

25. Wimmer NJ, Resnic FS, Mauri L, Matheny ME and Yeh RW. Comparison of transradial

versus transfemoral percutaneous coronary intervention in routine practice: evidence for the

importance of "falsification hypotheses" in observational studies of comparative effectiveness. J

Am Coll Cardiol. 2013;62:2147-2148.

26. Group. TOHTAW. Percutaneous Ventricular Assist Devices: A Health Technology

Assessment. Ontario health technology assessment series. 2017;17:1-97.

27. Rios SA, Bravo CA, Weinreich M, Olmedo W, Villablanca P, Villela MA, Ramakrishna

H, Hirji S, Robles OA, Mahato P, Gluud C, Bhatt DL and Jorde UP. Meta-Analysis and Trial

Sequential Analysis Comparing Percutaneous Ventricular Assist Devices Versus Intra-Aortic

Balloon Pump During High-Risk Percutaneous Coronary Intervention or Cardiogenic Shock. Am

J Cardiol. 2018;122:1330-1338.

28. Flaherty MP, Pant S, Patel SV, Kilgore T, Dassanayaka S, Loughran JH, Rawasia W,

Dawn B, Cheng A and Bartoli CR. Hemodynamic Support With a Microaxial Percutaneous Left

Dow


ovember 19, 2019

https://products.premierinc.com/downloads/PremierHealthcareDatabaseWhitepaper.pdf


25

Ventricular Assist Device (Impella) Protects Against Acute Kidney Injury in Patients

Undergoing High-Risk Percutaneous Coronary Intervention. Circ Res. 2017;120:692-700.

29. Henriques JP, Ouweneel DM, Naidu SS, Palacios IF, Popma J, Ohman EM and O'Neill

WW. Evaluating the learning curve in the prospective Randomized Clinical Trial of

hemodynamic support with Impella 2.5 versus Intra-Aortic Balloon Pump in patients undergoing

high-risk percutaneous coronary intervention: a prespecified subanalysis of the PROTECT II

study. Am Heart J. 2014;167:472-479 e5.

30. Ouweneel DM, de Brabander J, Karami M, Sjauw KD, Engstrom AE, Vis MM,

Wykrzykowska JJ, Beijk MA, Koch KT, Baan J, de Winter RJ, Piek JJ, Lagrand WK,

Cherpanath TG, Driessen AH, Cocchieri R, de Mol BA, Tijssen JG and Henriques JP. Real-life

use of left ventricular circulatory support with Impella in cardiogenic shock after acute

myocardial infarction: 12 years AMC experience. Eur Heart J Acute Cardiovasc Care.

2019;8:338-349.

31. Novoa I, Hernandez G, Parmar R, Breton JN, Blumer V and Chaparro S. INCIDENCE

OF STROKE INCREASES WITH PROLONGED USE OF IMPELLA PERCUTANEOUS

LEFT VENTRICULAR ASSIST DEVICE. Journal of the American College of Cardiology.

2018;71:A808.

32. Batra S, Kamran H, Lech T, Montgomery J, Venesy D, Patten R and Shah S. High

Thromboembolic Event Rate in Patients Supported With an Impella CP Device With an Anti-Xa

Level of Less Than 0.1 u/mL. The Journal of Heart and Lung Transplantation. 2018;37:S59.

33. Khera R, Cram P, Lu X, Vyas A, Gerke A, Rosenthal GE, Horwitz PA and Girotra S.

Trends in the use of percutaneous ventricular assist devices: analysis of national inpatient sample

data, 2007 through 2012. JAMA internal medicine. 2015;175:941-950.

34. Khera R, Cram P, Vaughan-Sarrazin M, Horwitz PA and Girotra S. Use of Mechanical

Circulatory Support in Percutaneous Coronary Intervention in the United States. Am J Cardiol.

2016;117:10-16.

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Table 1. Characteristics of the study participants.

Characteristic Impella® (n=4,782) IABP Total (n=48,306)

(n=43,524)

N % N % N %

Hospital characteristics

Total number of beds at hospital

000-099 115 2.4 423 0.97 538 1.11

100-199 255 5.33 2,499 5.74 2,754 5.70

200-299 637 13.32 6,032 13.86 6,669 13.81

300-399 744 15.56 10,247 23.54 10,991 22.75

400-499 645 13.49 7,265 16.69 7,910 16.37

500+ 2,386 49.9 17,058 39.19 19,444 40.25

Teaching Hospital 2,617 54.73 21,486 49.37 24,103 49.90

Hospital - Urban/Rural

Rural 252 5.27 3,256 7.48 3,508 7.26

Urban 4,530 94.73 40,268 92.52 44,798 92.74

Patient demographics

Age* 67.85 12.14 64.62 12.63 64.95 12.62

Females 1,317 27.54 13,621 31.3 14,938 30.92

Marital Status

Married 2,103 43.98 21,796 50.08 23,899 49.47

Single 1,710 35.76 15,174 34.86 16,884 34.95

Other 969 20.26 6,554 15.06 7,523 15.57

Patient Race

Black 390 8.16 2,910 6.69 3,300 6.83

Hispanic 28 0.59 1,123 2.58 1,151 2.38

Other 1,129 23.61 8,748 20.1 9,877 20.45

Unknown 48 1 163 0.37 211 0.44

White 3,187 66.65 30,580 70.26 33,767 69.90

Insurance Payor

Medicare 3,059 63.96 21,864 50.23 24,923 51.59

Medicaid 382 7.99 3,282 7.54 3,664 7.58

Managed Care / Commercial 985 20.6 13,487 30.99 14,472 29.96

Self-Pay 171 3.58 2,825 6.49 2,996 6.20

Other 185 3.87 2,066 4.75 2,251 4.66

Prior history

Diabetes 2,564 53.62 16,659 38.28 19,223 39.79

Dyslipidemia 3,582 74.91 27,424 63.01 31,006 64.19

Hypertension 3,996 83.56 30,618 70.35 34,614 71.66

Smoking 2,267 47.41 19,339 44.43 21,606 44.73

Congestive heart failure 3,416 71.43 20,855 47.92 24,271 50.24

Atrial fibrillation 1,251 26.16 10,103 23.21 11,354 23.50

Chronic renal failure 1,673 34.99 7,860 18.06 9,533 19.73

COPD 1,266 26.47 8,793 20.2 10,059 20.82

Alcohol abuse 116 2.43 898 2.06 1,014 2.10

Drug abuse 55 1.15 362 0.83 417 0.86

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Medications given during index

hospitalization

GPIIbIIa inhibitors 1,170 24.47 24,754 56.87 25,924 53.67

Bivalirudin 1,654 34.59 12,297 28.25 13,951 28.88

Intravenous heparin 1,063 22.23 11,858 27.24 12,921 26.75

Prasugrel 739 15.45 4,310 9.9 5,049 10.45

Ticagrelor 1,158 24.22 3,682 8.46 4,840 10.02

Novel oral anticoagulants 148 3.09 401 0.92 549 1.14

Warfarin 394 8.24 5,462 12.55 5,856 12.12

PCI and lesion characteristics

Multi-vessel disease 2,554 53.41 10,044 23.08 12,598 26.08

Transradial access 529 11.06 3,358 7.72 3,887 8.05

Bifurcation lesion 382 7.99 1,230 2.83 1,612 3.34

Bare metal stents used 764 15.98 14,577 33.49 15,341 31.76

Chronic total occlusion 1,056 22.08 6,277 14.42 7,333 15.18

LASER atherectomy 666 13.93 1,498 3.44 2,164 4.48

Rotational/orbital atherectomy 340 7.11 585 1.34 925 1.91

Mechanical ventilation 1,407 29.42 16,813 38.63 18,220 37.72

Cardiac arrest 701 14.66 8,105 18.62 8,806 18.23

Cardiogenic shock 1,792 37.47 22,558 51.83 24,350 50.41

STEMI 1,267 26.5 28,509 65.5 29,776 61.64

NSTEMI/UA 2,114 44.21 10,246 23.54 12,360 25.59

Indication other than ACS 1,401 29.3 4,769 10.96 6,170 12.77

*, numbers indicate means and SD, respectively. COPD, chronic obstructive pulmonary disease;

GPIIbIIIa, glycoprotein IIbIIIa; STEMI, ST segment elevation myocardial infarction; NSTEMI, non-ST

segment elevation myocardial infarction; UA, unstable angina; ACS, acute coronary syndrome.

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Table 2. Hospital-level variation in the study outcomes in patients who received Impella®

device*.

Outcome Variation across all hospitals

(n = 4,782)

Dichotomous outcomes (MOR)

Death 1.71 (1.53 – 1.97)

Bleeding 2.62 (2.24 – 3.17)

AKI 1.53 (1.41 – 1.69)

Stroke 1.47 (1.27 – 1.86)

Continuous outcomes (ICC, %)

Total LOS 5.18 (3.40 – 7.80)

ICU LOS 6.98 (4.67 – 10.31)

Total cost 17.80 (13.93 – 22.46)

*Please note the sample size for this analysis is n=4,782. All results are from mixed effects

models that used hospitals as random effects. Variation in dichotomous outcomes is quantified

as median odds ratio (MOR) while that in continuous variables is shown as intraclass correlation

coefficient (ICC). Parentheses contain 95% credible interval (for MOR) or confidence interval

(for ICC). AKI, acute kidney injury; LOS, length of stay; ICU, intensive care unit.

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Table 3. Comparison of the pre-Impella® and Impella® era for study outcomes*.

Pre-Impella® vs. Impella® era study outcomes across all

hospitals (n = 48,306)

Dichotomous outcomes

Outcome OR (95% CI), p

Death 1.17 (1.10 – 1.24), <0.001

Bleeding 0.99 (0.94 – 1.05), 0.843

AKI 1.91 (1.81 – 2.01), <0.001

Stroke 3.34 (2.94 – 3.79), <0.001

Continuous outcomes

Outcome β coefficient (95% CI)

Total LOS 0.04 (-0.08 – 0.16), 0.524

ICU LOS -0.04 (-0.12 – 0.04), 0.319

Total cost 1,774.94 (1,687.99 – 1,861.89), <0.001

*Results are from mixed effects, hierarchical models which adjusted for the propensity scores and with

hospitals as random effects. Odds ratios (OR) higher than unity indicate increased risk during the

Impella® era as compared to the pre-Impella® era. Similarly, positive β coefficients indicate higher

values, while negative β coefficients indicate lower values associated with the Impella® era as compared

to the pre-Impella® era. AKI, acute kidney injury; LOS, length of stay; ICU, intensive care unit.

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Table 4. Comparison of the higher- vs. lower-Impella® use hospitals for study outcomes*.

1st Quartile Hospitals

(0% Impella® use)

2nd Quartile Hospitals

(>0% to ≤3.33% Impella® use)

3rd Quartile Hospitals

(>3.33% to ≤14.72% Impella® use)

4th Quartile Hospitals

(>14.72% Impella® use)

Dichotomous Outcomes

Death - 0.71 (0.43 – 1.18), 0.1863 1.11 (0.95 – 1.30), 0.1825 1.48 (1.32 – 1.67), <0.0001

Bleeding - 1.33 (0.87 – 2.02), 0.1897 1.10 (0.95 – 1.29), 0.1897 1.17 (1.03 – 1.33), 0.015

AKI - 0.64 (0.42 – 0.96), 0.0313 1.00 (0.88 – 1.15), 0.9551 1.29 (1.17 – 1.43), <0.0001

Stroke - 1.31 (0.68 – 2.53), 0.4218 1.42 (1.15 – 1.76), 0.0012 1.26 (1.06 – 1.50), 0.0094

Continuous Outcomes

Total LOS (days) - -0.99 (-1.95 – -0.02), 0.0449 -0.79 (-1.10 – -0.48), <0.0001 -0.75 (-1.00 – -0.49), <0.0001

ICU LOS (days) - -1.09 (-1.78 – -0.40), 0.0019 -0.73 (-0.95 – -0.51), <0.0001 -0.51 (-0.70 – -0.33), <0.0001

Total cost ($) - $11,002 ($6,987 – $15,018), <0.0001 $12,039 ($10,770 – $13,307), <0.0001 $12,071 ($11,067 – $13,075), <0.0001

*Results are from mixed effects, hierarchical models which adjusted for the propensity scores and accounting for clustering with hospitals as random effects. All results

are shown as odds ratio or the beta coefficient estimate (95% confidence interval), p-value. Odds ratios (OR) higher than unity indicate increased risk associated at higher-

Impella® use hospitals as compared to the lower-Impella® use hospitals. Similarly, positive β coefficients indicate higher values, while negative β coefficients indicate

lower values associated at higher-Impella® use hospitals as compared to the lower-Impella® use hospitals. AKI, acute kidney injury; LOS, length of stay; ICU, intensive

care unit.

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Figure Legends

Figure 1. Trends in the use of Impella® amongst PCI patients requiring MCS. X-axis

depicts the calendar year. The black bars represent proportion of Impella® use amongst PCI

patients requiring MCS. Grey box represents the pre-Impella® era in which the Impella®

devices had not become available. MCS, hemodynamic support.

Figure 2. Variation in the use of Impella® across hospitals amongst PCI patients requiring

MCS. X-axis represents hospitals arranged in the order of increasing use of Impella®. Inset

shows the estimated median odds ratio (MOR, diamonds) and the 95% credible interval (Crl,

error bars). The MOR and its 95% Crl is obtained from a hierarchical, mixed effects logistic

regression model with hospital as a random effect. MCS, mechanical circulatory support.

Figure 3. Association of Impella® versus IABP use with clinical outcomes. The X-axis

represents the odds ratio scale, the dotted vertical line indicates the line of unity, and for each

outcome, the black diamonds represent the odds ratio estimate, while the horizontal bars indicate

the 95% confidence intervals. The OR and its 95% CI for each outcome is obtained from a

hierarchical, mixed effects logistic regression model with hospital as a random effect. AKI, acute

kidney injury; OR, odds ratio; CI, confidence interval; PCI, percutaneous coronary intervention D

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Death

OR (95% CI) pOutcome

Bleeding

AKI

Stroke

0.5 1 1.5 2Odds Ra�o

Benefit Harm

1.34 (1.18 - 1.53) <0.0001

1.24 (1.13 - 1.36) <0.0001

1.10 (1.00 - 1.21) 0.0445

1.08 (1.00 - 1.17) 0.0521

Dow


ovember 19, 2019

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The Evolving Landscape of Impella® Use in the United ... · 08/01/2020 · adverse CV events in the primary intent to treat analysis, but did observe lower adverse events at 90