Epidemiology of cardiac implantable electronic device infections in the United States: a population-based cohort study

Journal Pre-proof Epidemiology of cardiac implantable electronic device infections in the United States: a population-based cohort study Elissa Rennert-May, MD MSc, Derek Chew, MD, Shengjie Lu, MSc, Angel Chu, MD, Vikas Kuriachan, MD, Ranjani Somayaji, MD MPH PII:

S1547-5271(20)30114-4

DOI:

https://doi.org/10.1016/j.hrthm.2020.02.012

Reference:

HRTHM 8283

To appear in:

Heart Rhythm

Received Date: 11 December 2019 Accepted Date: 10 February 2020

Please cite this article as: Rennert-May E, Chew D, Lu S, Chu A, Kuriachan V, Somayaji R, Epidemiology of cardiac implantable electronic device infections in the United States: a populationbased cohort study, Heart Rhythm (2020), doi: https://doi.org/10.1016/j.hrthm.2020.02.012. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier Inc. on behalf of Heart Rhythm Society.

SHORT TITLE: CARDIAC IMPLANTABLE ELECTRONIC DEVICE INFECTIONS 1

Epidemiology of cardiac implantable electronic device infections in the United States: a

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population-based cohort study

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Elissa Rennert-May MD MSc1-5, Derek Chew MD6, Shengjie Lu MSc1, Angel Chu MD1, Vikas

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Kuriachan MD7,8, Ranjani Somayaji MD MPH1-5

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1. Department of Medicine, University of Calgary, Canada

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2. Department of Microbiology, Immunology and Infectious Diseases, University of Calgary,

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Canada

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3. Department of Community Health Sciences, University of Calgary, Calgary, AB, Canada

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4. O’Brien Institute of Public Health, University of Calgary, Calgary, AB, Canada

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5. Snyder Institute for Chronic Diseases, University of Calgary, Calgary, AB, Canada

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6. Duke Clinical Research Institute, Duke University, Durham, NC, USA

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7. Department of Cardiology, University of Calgary, Calgary, AB, Canada

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8. Libin Cardiovascular Institute, University of Calgary, Calgary, AB, Canada

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The authors have no conflicts of interest to declare.

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Corresponding Author:

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Ranjani Somayaji

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3330 Hospital Drive NW

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Calgary, AB T2J 4N1, Canada

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[email protected]

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Word Count: 4114

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SHORT TITLE: CARDIAC IMPLANTABLE ELECTRONIC DEVICE INFECTIONS 22

Abstract

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Background: Trends in cardiac implantable electronic device (CIED) infections have been

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studied previously. However, coding for administrative data is more granular in contemporary

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datasets and indications for CIED implantations have expanded.

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Objective: To provide an update on the rates of CIED infections and the influence of different

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variables including sex, on length of stay (LOS), and costs in the United States.

30 31

Methods: Data from the 2016 healthcare utilization project (HCUP) national inpatient sample

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(NIS) database were utilized. International classification of diseases codes – tenth revision (ICD-

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10) were used to track CIED infections. Demographic and clinical characteristics were collected

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including Elixhauser comorbidities. Univariate and multivariable logistic and linear regression

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models were used to assess mortality, costs, and LOS.

36 37

Results: Of 191,610 CIED implantations identified in the HCUP NIS database in 2016, we

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identified 8060 infections (4.2%). In-hospital mortality in these patients was 4.7%. The majority

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of patients (68.9%) with CIED infections had three or more Elixhauser comorbidities. Females

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had decreased LOS and costs compared to males, and patients with three or more

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comorbidities had increased costs and LOS.

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SHORT TITLE: CARDIAC IMPLANTABLE ELECTRONIC DEVICE INFECTIONS 43

Conclusions: We identified that the majority of patients with CIED infection had three or more

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comorbidities which was associated with increased costs and LOS. The observed sex differences

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in health resource utilization and in-hospital costs among patients admitted with CIED infection

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requires further exploration. Patients with increased numbers of comorbidities should be

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recognized and managed carefully peri- CIED implantation given their increased risk of infection

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and use of healthcare resources.

49 50 51

Keywords: Cardiac implantable electronic device infections, Healthcare utilization project,

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infection epidemiology

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SHORT TITLE: CARDIAC IMPLANTABLE ELECTRONIC DEVICE INFECTIONS 53 54

Introduction The rate of implantation for cardiac implantable electronic devices (CIEDs) has increased

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over time, due to the expanding indications for implantation over the last decade.1 These

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devices include permanent pacemakers (PM), implantable cardioverter-defibrillators (ICD) and

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cardiac resynchronization therapy (CRT). Furthermore, CIED implantation is occurring in older

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patients with increased comorbidity, and increased rates of CIED infection have been

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observed.1

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CIED infection is associated with increased morbidity and mortality, and can be

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challenging to manage and treat. CIED infections usually require surgical removal of the

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infected device and leads, a prolonged course of antibiotics and increased hospital length of

63

stay.2 This can lead to morbidity for patients as well as significant economic costs.3

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There have been previous studies utilizing administrative data to explore the trends in

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CIED infections that have demonstrated increasing rates over time.1,3 In the past five years,

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International Classification of Diseases (ICD) codes moved from ninth revision (ICD-9) to tenth

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revision (ICD-10) codes in many administrative datasets. The revised codes were intended to

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increase specificity and accuracy.4 Our primary objective for the current study was to utilize a

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large administrative dataset after ICD-10 codes were implemented and provide an update on

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current rates of CIED infections and CIED infection epidemiology in the United States (US).

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Methods

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Study Population and Outcomes

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We utilized data from the 2016 Healthcare cost and Utilization Project (HCUP) Nationalwide Inpatient Sample (NIS) database. The NIS database contains information regarding

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SHORT TITLE: CARDIAC IMPLANTABLE ELECTRONIC DEVICE INFECTIONS 75

hospitalizations from approximately 1000 US hospitals from which a 20% stratified sample are

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created.1 To identify admissions with CIED infections, ICD-10 Codes were used. The CIED

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devices included PMs, ICDs and CRT.

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CIED-related infections were identified using previously described methods.1 We used

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the ICD-10 codes for device-related infection (T82.7XXA, T82.6XXA) in addition to any codes

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along with CIED implant (described below) or removal (0JPT0PZ, 0JPT3PZ). Additionally, CIED-

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related infections were identified as CIED removal along with evidence of systemic infection,

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including sepsis (R65.20, R65.21, A40.9, A41.89, A41.9, A41.01, A41.2, A41.1), bacteremia

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(R78.81), or fever (R50.9).

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CIED implants were identified with the ICD-10 codes of 0JH604Z, 0JH634Z, 0JH804Z,

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0JH834Z, 0JH605Z, 0JH805Z, 0JH835Z, 0JH606Z, 0JH636Z, 0JH806Z, 0JH836Z for PM; 0JH607Z,

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0JH637Z, 0JH807Z, 0JH837Z, 0JH609Z, 0JH639Z, 0JH809Z, 0JH839Z for CRT; and 0JH608Z,

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0JH638Z, 0JH808Z, 0JH838Z for ICD.

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We recorded socio-demographic characteristics as covariates including age (in years),

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sex (male/female), race (Caucasian/Black/Hispanic/Asian or Pacific Islander/First

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Nations/other), household income national quartile for patient ZIP code (first quartile being the

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lowest income), admission on the weekend (non-weekend/weekend), primary expected payer

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(Medicare/Medicaid/private insurance/self-pay/no charge/other), hospital region

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(Northeast/Midwest/South/West) and hospital location/teaching status (rural/urban

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nonteaching/urban teaching). Additionally, we included cardiovascular related comorbidities

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such as diabetes with and without chronic complications, renal failure, heart failure, and

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hypertension. Furthermore, a comorbidity count classifier (0/1-2/3+) of all Elixhauser

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SHORT TITLE: CARDIAC IMPLANTABLE ELECTRONIC DEVICE INFECTIONS 97

comorbidities5 was computed. All comorbidity variables were computed with the HCUP Beta

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Elixhauser Comorbidity Software for ICD-10-CM.6

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Statistical Analyses

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Baseline characteristics of the cohort with CIED infection were summarized. Weighted

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frequencies (based on weights per admission) were calculated for CIED infection. These

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estimates were divided by the total number of CIED implantations in the same time period and

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provide number of CIED infections that occurred over that period of time. These are generally

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reported by HCUP as rates given that these are the closest rate estimates possible with this

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type of dataset, and will be referred to as such. Our outcomes included in-hospital death, LOS

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and costs in 2016 US dollars. We constructed univariate and multivariable logistic and linear

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regression models for the outcomes of death, and LOS and costs respectively. Covariates were

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selected a priori including age, sex, race, income quartile, payer, hospital status, cardiovascular

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comorbidities and comorbidity burden. Model fit was assessed using the Akaike information

110

criterion (AIC) and the Bayesian information criterion (BIC) and were constructed with robust

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standard errors. All analyses were conducted with R 3.6.1 (2019).

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All data was de-identified and therefore institutional ethics was not required. HCUP data

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use agreement training certification was obtained by all authors who worked directly with the

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data.

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Results

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Baseline Demographics

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Of 191,610 CIED implantations (82990 (43%) female), there were 8,060 (4.2%)

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admissions for CIED infections. Baseline characteristics of the cohort with CIED infection are

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SHORT TITLE: CARDIAC IMPLANTABLE ELECTRONIC DEVICE INFECTIONS 119

depicted in Table 1. The mean age was 66.6 years and 30.8% of the cohort were female. The

120

majority of patients were admitted on a weekday to an urban teaching hospital. Most patients

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(68.9%) had greater than or equal to three Elixhauser comorbidities. Most patients with CIED

122

infection also had a diagnosis of hypertension (63.3%).

123

Clinical outcomes

124

Among the 8,060 patients admitted with a CIED infection, 379 (4.7%) patients died

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during the hospitalization. In the univariate models, there were higher odds of in-hospital

126

mortality among CIED patients with renal failure (odds ratio (OR) 2.74, 95% CI 1.71 to 4.4),

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heart failure (OR 2.11, 95% CI 1.11 to 4.02), and persons of black race (OR 1.83, 95% CI 1.01 to

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3.29). In the multivariable models, only renal failure was associated with a significantly greater

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odds of in-hospital death (OR 2.26, 95% CI 1.24 to 4.15).

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The average LOS following admission for CIED infection was 13.7 +/- 12.6 days. LOS was

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increased among patients with a higher burden of baseline comorbidities (i.e. ≥3 Elixhauser

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comorbidities). For those with greater or equal to three comorbidities, LOS was increased by

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5.91 days (95% CI 2.97 to 8.85) and 7.61 days (95% CI 4.02 to 11.2), in the univariate and

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multivariate models, respectively (Table 2 displays all results for the LOS models).

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Finally, when examining costs, the mean in-hospital cost for those with CIED infection

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was $51,258. Females with CIED infections were more likely to have reduced healthcare costs in

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both the univariate and multivariate models (-$6,081 (95% CI -$11,100 to -$1,062) and -$7,102

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(-$12,044, -$2,159), respectively). There were several other variables associated with significant

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differences in costs and the full outputs from the models are represented in Table 3.

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Discussion

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SHORT TITLE: CARDIAC IMPLANTABLE ELECTRONIC DEVICE INFECTIONS 141

Our study explored the rate of CIED infections in 2016 using a large, nationally

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representative, administrative database and identified a CIED infection rate of 4.2%. The

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majority of the cohort was male and had hypertension. Having increased comorbidities was

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associated with longer LOS and increased costs. There was also a trend towards increased odds

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of mortality with greater numbers of comorbidities but this did not reach statistical significance.

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Female sex was associated with decreased costs and shorter LOS (though the latter was not

147

significant) even after adjusting for confounding variables.

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When comparing our findings to previous studies, the rate of CIED infection was higher

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in our population-based study. A recent randomized controlled trial exploring the use of a novel

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antibiotic envelope for infection prevention prior to CIED implantation found an infection rate

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of only 1.2% in the standard care group and 0.7% in the intervention group.7 A second recent

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randomized trial assessing change in perioperative antibiotics also found an infection rate of

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around 1% (1.03%) in their standard therapy arm. However, given differences in protocols and

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select patient populations for randomized controlled trials, we would expect studies with

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similar methodology to the current study to be more comparable.8 For example, in a study

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exploring 16 year trends of CIED infections, also using the NIS database found that from 1993-

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2008 CIED infection incidence was 1.61%.1 However the annual rate by 2008 was 2.41%,

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indicating an increase in CIED infections.1 An update of the study, also using NIS data, assessed

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trends in CIED infection from 2000 to 2012.3 They noted that by the end of the study period

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infection rates increased from 1.45% to 3.41%.3 Our findings are more consistent with this

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previously observed increased trend in CIED infection rate. The increasing rates of CIED

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infection have been previously attributed to the higher frequency of CIED implantation among

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SHORT TITLE: CARDIAC IMPLANTABLE ELECTRONIC DEVICE INFECTIONS 163

patients with greater burden of comorbidities such as kidney disease, heart failure and

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diabetes.2 From 1993 to 2008, CIED implantation increased by 96%, primarily driven by a

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greater volume of PM implants.1 Our findings support this notion through demonstrating that

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amongst those with CIED infection the majority have three or more Elixhauser comorbidities.

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Another potential reason for the change in rates of CIED infection is the difference in

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coding used by the NIS database. The prior studies utilized ICD-9 codes and we used the current

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ICD-10 codes. As the ICD-10 codes are intended to be more specific it is possible that the use of

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ICD-9 codes over captured device implantation beyond just CIED. Alternatively, the use of ICD-

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10 codes in the HCUP database for CIED infection are not necessarily validated for accuracy,

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and there may be some degree of misclassification of the coding that influenced our results.

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Our mortality rate of 4.7% for those with CIED infections was consistent with a previous

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study on mortality in CIED infections which noted an average mortality rate of 4.39% but it

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increased from 2.91% in 1993 to 4.69% in 2008 (likely due to expanding indications for

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implantation of CIED).1 The average age in our CIED infection population was 66.6 years, and

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our mortality rate related to CIED infection was substantially higher than the average mortality

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in the United States for those between ages 65-74 years of 1.79%.9 While not directly

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comparable, this does indicate that there is a higher mortality rate in the CIED infection

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population.

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The LOS was longer and direct health costs were greater among patients with CIED

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infections and a greater burden of comorbidities. Our mean in-hospital cost for CIED infection

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was similar to previous findings in the literature. A study published in 2011 that assessed

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admission costs in US dollars for CIED infections found a mean range of $28 676 to $53 349 per

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SHORT TITLE: CARDIAC IMPLANTABLE ELECTRONIC DEVICE INFECTIONS 185

admission depending on specific CIED.10 Interestingly, females had lower costs compared to

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males, and while it did not reach significance when comorbidities were adjusted for, females

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tended to have shorter length of stay in hospital. The shorter LOS in hospital and lower health-

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care costs demonstrate less resource utilization by females who develop a CIED infection

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compared to males. Previous work has demonstrated that for a variety of medical conditions

190

females are more likely to have shorter LOS compare to males.11 Our findings suggest the

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possibility of sex and gender based biases in access to healthcare.

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We determined that a greater number of males than females develop CIED infections

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(30.8% of the infected cohort were female). This was consistent with a previous study also using

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the NIS database from 2003-2011 that demonstrated that men had a higher number of CIED

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infections compared to women every year.12 This may be in part due to the fact that generally

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females are less likely to receive a CIED despite having similar indications to males (in our

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cohort of CIED implantation, 43% were female).13 This is potentially due to the results of clinical

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trials of CIED which have frequently demonstrated results more generalizable to males and on

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some occasions increased adverse events (non-infectious) in females, however it is difficult to

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draw conclusions on the benefits to females given that they are generally underrepresented in

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these trials.13

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A recent population level study published in 2019 from New Zealand and Australia did

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demonstrate that women were at higher risk of acute CIED complications and that this may

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influence CIED use in women.14 However, disparities in cardiac care have previously been noted

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between males and females.15 For example, in a recent study it was noted that women receive

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around 50% the number of treatments that men do for coronary artery disease. Even when sex

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SHORT TITLE: CARDIAC IMPLANTABLE ELECTRONIC DEVICE INFECTIONS 207

specific testing was done to identify myocardial injury, the rates of myocardial injury or

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cardiovascular death were not significantly reduced, potentially due to women ultimately being

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less likely to receive treatment.15 As our findings do suggest that a smaller percentage of

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females (30.8%) are diagnosed with a CIED infection relative to the female percentage of those

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that receive a CIED implantation (43%), this could be due to females being less likely to develop

212

a CIED infection or being underdiagnosed.

213

Our study adds to the literature as it explores the recent rates of CIED infection and its

214

epidemiology as well as variables that contribute to differences in cost and LOS amongst those

215

with infection. This study also utilizes the ICD-10 codes which are more recently being used

216

with increased frequency in administrative databases given their improved specificity compared

217

to ICD-9 codes. However, the change in codes from ICD-10 to ICD-9 make direct comparisons

218

with previous literature in this area challenging.

219

Limitations include the study’s observational design in that causal inferences are

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challenging to make so no definitive conclusions can be made about the relationship between

221

different variables and their influence on resource utilization including costs and LOS, and

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mortality in those with CIED infections. As HCUP provides discharge-level data rather than

223

patient-level claims data, we were not able to directly associate patient-level comorbidities

224

with subsequent CIED infection risk. As our study utilized ICD-10 coding, it is possible that

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events were misclassified. However, as we used more than one strategy of coding to identify

226

infection and utilized similar methods to a prior study, this is less likely to have occurred.

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Additionally, the ICD-10 codes did not allow us to distinguish details including leadless PMs and

228

subcutaneous ICDs. These sub-groups may have had different infection risks compared to the

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SHORT TITLE: CARDIAC IMPLANTABLE ELECTRONIC DEVICE INFECTIONS 229

entire infection cohort and could not be assessed. The HCUP database captures in-hospital

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mortality and thus it is possible that this and other outcomes as cost were actually

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underestimated as they did not account for community-based events.

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Another limitation is that this work only explored the 2016 HCUP NIS database in a

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cross-sectional analysis (the most recent dataset using ICD-10 codes available at the time of this

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work). Therefore, we were unable to assess CIED trends over time. The higher than expected

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CIED infection rate in our study may be due in part to the fact that a proportion of late

236

infections would have occurred from implantations prior to 2016. Similarly, however, there may

237

be some degree of underestimation as late infections from 2016 implantations would not occur

238

until 2017 or even later. Our results are a period prevalence rather than a true incidence rate as

239

the precise denominator is not known. Given that the HCUP NIS dataset is at a discharge-level

240

rather than patient-level we were unable to perform a longitudinal data analysis appropriately

241

accounting for time-varying covariates. Nevertheless, our CIED infection estimates are

242

consistent with methodology previously reported1, and allow for comparisons to previously

243

published infection rates.1,3

244 245

Conclusions

246

Our work provided one of the first assessments of CIED infections using ICD-10 codes

247

from a large administrative database of which we are aware. Future work should continue to

248

assess the trends of CIED infections once more data from HCUP NIS is available using ICD-10

249

codes. Our work also suggests that exploration of gender in CIED infections is necessary.

250

Differences in LOS and costs suggest that either females are not receiving the same care or that

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SHORT TITLE: CARDIAC IMPLANTABLE ELECTRONIC DEVICE INFECTIONS 251

they have fewer adverse events compared to males with CIED infections. Additionally, those

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with greater numbers of comorbidities also had significantly higher resource utilization. While

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this is not surprising this suggests that these patients require pre-operative optimization along

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with close monitoring following CIED implantation to minimize infection risk and identify it early

255

to avoid adverse patient outcomes and decrease healthcare use. A formal Infectious Diseases

256

consult early in the course of infection may provide beneficial in improving outcomes in those

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with CIED infection, and this warrants further investigation as well.

258 259

Funding

260

This research did not receive any specific grant from funding agencies in the public, commercial,

261

or not-for-profit sectors.

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SHORT TITLE: CARDIAC IMPLANTABLE ELECTRONIC DEVICE INFECTIONS 263

References

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Tables

SHORT TITLE: CARDIAC IMPLANTABLE ELECTRONIC DEVICE INFECTIONS Table 1. Baseline characteristics of cohort with CIED infection Parameter/Type of Infection Number of Admissions

CIED Infection 8060

Age

Mean Years (SD) Median Years

Sex

Male Female White

5565 (69.0%) 2485 (30.8%) 5615 (69.7%)

Black

1080 (13.4%)

Race

Hispanic Asian/Pacific Islander

Median Income

66.6 (15.0) 69

570 (7.1%) 145 (1.8%)

Native American

50 (0.6%)

Other

235 (2.9%)

First Quartile

2595 (32.2%)

Second Quartile

2125 (26.4%)

Third Quartile Fourth Quartile

1650 (20.5%) 1505 (18.7%)

Admission on the Weekend

Non Weekend Weekend

6630 (82.3%) 1430 (17.7%)

Primary Expected Payer

Medicare

5410 (67.1%)

Medicaid Private Insurance

925 (11.5%) 1375 (17.1%)

Hospital Location/Teaching Status

Hospital Region

Elixhauser Comorbidities (Counts)

Elixhauser Cardiovascular Comorbidities

Self-pay

95 (1.2%)

No Charge Other

35 (0.4%) 210 (2.6%)

Rural

145 (1.8%)

Urban Non-teaching Urban Teaching

1130 (14.0%) 6785 (84.2%)

Northeast Midwest

1490 (18.5%) 1720 (21.3%)

South

3490 (43.3%)

West

1360 (16.9%)

0

350 (4.3%)

1-2

2160 (26.8%)

≥3

5550 (68.9%)

Diabetes without Chronic Complications

1555 (19.3%)

Diabetes with Chronic Complications

1725 (21.4%)

Renal Failure Congestive Heart Failure

2840 (35.2%) 695 (8.6%)

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SHORT TITLE: CARDIAC IMPLANTABLE ELECTRONIC DEVICE INFECTIONS Hypertension

5105 (63.3%)

306 307 308

17

SHORT TITLE: CARDIAC IMPLANTABLE ELECTRONIC DEVICE INFECTIONS 309 310 311

Table 2. Length of stay models. Model 1 is univariate and model 2 is multivariate with coefficients representing days and a negative sign indicating a reduction in length of stay compared to the reference baseline.

Age Sex Race

Median Income

Primary Expected Payer

Hospital Location/Teaching Status

Hospital Region

Elixhauser Comorbidities (Counts)

Diabetes without Chronic Complications Diabetes with Chronic Complications Renal Failure

Age Male

Model 1: Coefficient (95% CI)

Model 2: Coefficient (95% CI)

-0.12 (-0.17, -0.08)

-0.11 (-0.16, -0.05)

Ref

✝

Ref

Female

-0.18 (-1.45, 1.08)

-0.82 (-2, 0.36)

White Black

Ref 2.23 (0.13, 4.33)

Ref 0.68 (-1.38, 2.74)

Hispanic Asian/Pacific Islander Native American

-0.19 (-2.1, 1.73)

-0.81 (-2.61, 0.99)

0.01 (-2.98, 2.99) -2.11 (-6.96, 2.74)

-0.23 (-2.82, 2.37) -0.56 (-4.99, 3.87)

Other

-1.66 (-3.81, 0.49)

-1.52 (-3.61, 0.58)

Ref

Ref

Second Quartile

-1.79 (-3.31, -0.26)

-1.09 (-2.46, 0.28)

Third Quartile Fourth Quartile

-0.4 (-2.43, 1.62) -2.16 (-3.81, -0.5)

0.68 (-1.26, 2.62) -1.29 (-2.9, 0.32)

Ref

Ref

Medicaid Private Insurance

3.31 (1.02, 5.6) -0.45 (-2.02, 1.11)

-0.74 (-3.09, 1.61) -1.34 (-3.14, 0.46)

Self-pay

3.08 (-4.15, 10.32)

-2.29 (-7.54, 2.96)

No Charge Other

1.47 (-6.39, 9.32) -1.87 (-3.98, 0.25)

-0.41 (-7.9, 7.08) -2.35 (-4.81, 0.11)

First Quartile

Medicare

Rural Urban Nonteaching Urban Teacing

Ref

Ref

2.08 (-1.15, 5.3) 3.94 (0.93, 6.95)

-0.73 (-4.22, 2.76) 2.03 (-1.33, 5.39)

Northeast Midwest

Ref -2.17 (-4.1, -0.24)

-

South

-1 (-2.82, 0.81)

-

West

-2.42 (-4.7, -0.14)

-

Ref

Ref

0 1-2

1.05 (-2, 4.09)

2.6 (-0.89, 6.08)

≥3

5.91 (2.97, 8.85)

7.61 (4.02, 11.2)

No

Ref

Ref

Yes

-2.17 (-3.67, -0.67)

-2.87 (-4.48, -1.26)

No

Ref

Ref

Yes

1.51 (0.1, 2.91)

-1.77 (-3.34, -0.19)

No

Ref

Ref

Yes

2.76 (1.42, 4.1)

1.82 (0.37, 3.28)

18

SHORT TITLE: CARDIAC IMPLANTABLE ELECTRONIC DEVICE INFECTIONS Congestive Heart Failure Hypertension

312 313

No

Ref

Ref

Yes

9.5 (6.34, 12.66)

8.61 (5.44, 11.79)

No Yes

Ref -2.39 (-3.73, -1.05)

Ref -3.35 (-4.64, -2.05)

✝ Reference

19

SHORT TITLE: CARDIAC IMPLANTABLE ELECTRONIC DEVICE INFECTIONS 314 315 316

Table 3. Cost models. Model 1 is univariate and model 2 is multivariate, coefficients represent United States dollars, with a negative sign indicating a reduction in cost compared to the reference baseline.

Age Sex Race

Median Income

Age Male

Elixhauser Comorbidities (Counts)

Diabetes without Chronic Complications Diabetes with Chronic Complications

-511 (-721, -301)

Ref

✝

Ref

-6081 (-11100, -1062)

-7102 (-12044, -2159)

Ref 1954 (-5421, 9329)

Ref 983 (-6464, 8430)

Hispanic Asian/Pacific Islander Native American

3139 (-6198, 12475)

4372 (-4428, 13171)

11135 (-6504, 28775) -8320 (-28588, 11949)

11123 (-55967, 27843) -6038 (-26409, 14332)

Other

-4393 (-14162, 5377)

-4353 (-14365, 5659)

First Quartile

Ref

Ref

810 (-4963, 6582) 8819.74 (237.21, 17402.26) 6487 (-660, 13634)

2350 (-3380, 8079) 12265 (3644, 20886) 8886 (1448, 16324)

Medicare

Ref

Ref

Medicaid

8674 (380, 16967)

-6548 (-15881, 2785)

Private Insurance

Hospital Region

-487 (-647, -327)

White Black

Third Quartile Fourth Quartile

Hospital Location/Teaching Status

Model 2: Coefficient (95% CI)

Female

Second Quartile

Primary Expected Payer

Model 1: Coefficient (95% CI)

4573 (-3542, 12687)

-1939 (-10655, 6776)

Self-pay No Charge

-4801 (-17782, 8181) -9006 (-32569, 14557)

-20842 (-33888, -7795) -17901 (-39181, 3380)

Other

-4726 (-15866, 6414)

-9040 (-20355, 2276)

Rural Urban Nonteaching

Ref

Ref

11149 (1109, 21189)

-3320 (-15224, 8583)

Urban Teacing

23609 (14523, 32695)

11087 (-71, 22245)

Northeast

Ref

-

Midwest

-12092 (-20693, -3492)

-

South West

-17351 (-25253, -9448) -776 (-11458, 9906)

-

0 1-2

Ref -1457 (-13243, 10329)

Ref 9481 (-4160, 23122)

≥3

13609 (2036, 25183)

28221 (13640, 42801)

No Yes

Ref -6230 (-13300, 840)

Ref -9194 (-16925, -1463)

No Yes

Ref 1272 (-4161, 6704)

Ref -9885 (-16525, -3246)

20

SHORT TITLE: CARDIAC IMPLANTABLE ELECTRONIC DEVICE INFECTIONS Renal Failure

317

No

Ref

Ref

Yes

6274 (710, 11839)

4434 (-2292, 11160)

Congestive Heart Failure

No Yes

Ref 27041 (13877, 40206)

Ref 24407 (11298, 37515)

Hypertension

No Yes

Ref -14427 (-20141, -8712)

Ref -17359 (-23549, -11168)

✝ Reference

21