Accepted Manuscript

Impact of Symptoms, Gender, Co-morbidities and Operator Volume on Outcome ofCarotid Artery Stenting (From the Nationwide Inpatient Sample [2006 – 2010])

Apurva O. Badheka, M.D Ankit Chothani, M.D Sidakpal S. Panaich, M.D KathanMehta, M.D Nileshkumar J. Patel, M.D Abhishek Deshmukh, M.D Vikas Singh, M.DShilpkumar Arora, M.D Nilay Patel, M.D Peeyush Grover, M.D Neeraj Shah, M.DChirag N. Savani, M.D Achint Patel, M.D Vinaykumar Panchal, M.D Michael Brown,M.D Amir Kaki, M.D Ashok Kondur, M.D Tamam Mohamad, M.D Mahir Elder, M.DCindy Grines, M.D Theodore Schreiber, M.D

PII: S0002-9149(14)01377-0

DOI: 10.1016/j.amjcard.2014.06.030

Reference: AJC 20557

To appear in: The American Journal of Cardiology

Received Date: 25 March 2014

Revised Date: 6 June 2014

Accepted Date: 10 June 2014

Please cite this article as: Badheka AO, Chothani A, Panaich SS, Mehta K, Patel NJ, Deshmukh A,Singh V, Arora S, Patel N, Grover P, Shah N, Savani CN, Patel A, Panchal V, Brown M, Kaki A, KondurA, Mohamad T, Elder M, Grines C, Schreiber T, Impact of Symptoms, Gender, Co-morbidities andOperator Volume on Outcome of Carotid Artery Stenting (From the Nationwide Inpatient Sample [2006 –2010]), The American Journal of Cardiology (2014), doi: 10.1016/j.amjcard.2014.06.030.

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service toour customers we are providing this early version of the manuscript. The manuscript will undergocopyediting, typesetting, and review of the resulting proof before it is published in its final form. Pleasenote that during the production process errors may be discovered which could affect the content, and alllegal disclaimers that apply to the journal pertain.

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Impact of Symptoms, Gender, Co-morbidities and Operator

Volume on Outcome of Carotid Artery Stenting (From the

Nationwide Inpatient Sample [2006 – 2010])

Author: Apurva O. Badheka M.Da*, Ankit Chothani M.Db*, Sidakpal S Panaich M.Da*, Kathan Mehta

M.Dc*, Nileshkumar J. Patel M.Dd*, Abhishek Deshmukh M.De, Vikas Singh M.Df, Shilpkumar Arora

M.Da, Nilay Patel M.Da, Peeyush Grover M.Df, Neeraj Shah M.Dd, Chirag N. Savani M.Da, Achint Patel

M.Da, Vinaykumar Panchal M.Da, Michael Brown M.Da, Amir Kaki M.Da, Ashok Kondur M.Da, Tamam

Mohamad M.Da, Mahir Elder M.Da, Cindy Grines M.Da, Theodore Schreiber, M.Da.

a: Detroit Medical Center, MI; b: MedStar Washington Hospital Center, Washington, D.C; c: UPMC

Shadyside Hospital, Pittsburgh, PA; d: Staten Island University Hospital, Staten Island, NY; e: University

of Arkansas, Little Rock, AR; f: University of Miami Miller School of Medicine, Miami, FL.

*: Authors share equal contribution to this manuscript.

Address for correspondence:

Apurva O. Badheka M.D

Detroit Medical Center 15, East Kirby Street, Park Shelton Apt. 731 Detroit, MI 48202 Phone: 408-324-4516 e-mail: dr.apurva.badheka@gmail.com

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ABSTRACT

The increase in the number of carotid artery stenting (CAS) procedures over the last decade has

necessitated critical appraisal of procedural outcomes as well as patterns of utilization including cost

analysis. The main objectives of our study were to evaluate the post-procedural mortality and

complications following CAS and the patterns of resource utilization in terms of length of stay (LOS) and

cost of hospitalization. We queried the Healthcare Cost and Utilization Project’s Nationwide Inpatient

Sample (NIS) between 2006 and 2010 using the ICD9 procedure code of 00.63 for CAS. Hierarchical

mixed effects models were generated in order to identify the independent multivariate predictors of in-

hospital mortality, procedural complications, length of stay and cost of hospitalization. A total of 13,564

(weighted n=67,344) CAS procedures were analyzed. The overall post-procedural mortality was low at

0.5% while the complication rate was 8%, both of which remained relatively steady over the time frame

of the study. Higher post-operative mortality and complications were noted in symptomatic patients,

females and those with higher burden of baseline comorbidities. A higher operator volume was associated

with lower rate of post-operative mortality and complications as well shorter length of stay and lower

hospitalization costs. In conclusion, the post-procedural mortality following CAS has remained low over

the recent years. Operator volume is an important predictor of post-procedural outcomes and resource

utilization.

Key words: Carotid artery stent, complication, length of stay, cost of care.

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The geriatric population in the United States is expected to double between 2000 and 2030 with

the proportion of elderly individuals estimated to increase from 12.4 to 19.6%1. With a steady increase in

the older population, the burden of cardiovascular disease including carotid disease is bound to worsen.

With stroke being the third most common cause of death in the United States and carotid stenosis

accounting for 20-25% of the strokes2, a focus on appropriate management strategies for carotid artery

stenosis is becoming increasingly germane. Although, carotid end-arterectomy (CEA) has long been the

standard of care for carotid revascularization, carotid artery stenting (CAS) has been gaining popularity

especially after randomized control trials demonstrating non-inferiority within the last decade3, 4. The

consequential increase in the number of CAS procedures5 has necessitated critical appraisal of procedural

outcomes as well as patterns of utilization including cost analysis. The main objectives of our study were

twofold: 1) to evaluate the post-procedural mortality and complications following CAS and 2.) to study

the patterns of resource utilization in terms of length of stay (LOS) and cost of hospitalization using the

nation’s largest all payer insurance inpatient database from recent years (2006-2010).

METHODS

The study cohort was derived from the Nationwide Inpatient Sample (NIS) database between

2006 and 2010, a subset of the Healthcare Cost and Utilization Project (HCUP) sponsored by the Agency

for Healthcare Research and Quality (AHRQ). The NIS is the largest publicly available all-payer inpatient

care database in the United States, including data on approximately 7 to 8 million discharges per year, and

is a stratified sample designed to approximate a 20% sample of US community (nonfederal, short-term,

general, and specialty) hospitals. National estimates are produced using sampling weights provided by the

sponsor. Annual data quality assessments of the Nationwide Inpatient Sample are performed, which

guarantee the internal validity of the database. Furthermore, comparisons against the following data

sources strengthen the external validity of the Nationwide Inpatient Sample: the American Hospital

Association Annual Survey Database, the National Hospital Discharge Survey from the National Center

for Health Statistics, and the MedPAR inpatient data from the Centers for Medicare and Medicaid

Services.6, 7 We queried the NIS database between 2006 and 2010 using the International Classification of

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Diseases, 9th Revision, Clinical Modification (ICD-9-CM) procedure code designating CAS (ICD-9:

00.63). Only adult patients (age ≥ 18 years) were selected. Any patients with concomitant carotid end-

arterectomy (CES) (ICD-9-CM: 38.12) were excluded. Patients were considered symptomatic if they had

primary diagnosis of carotid artery stenosis with cerebral infarction (ICD-9-CM: 433.11) or stroke.

NIS variables were used to identify patients demographic characteristics including age, gender,

and race. Census data was used to calculate utilization rate of CAS for individual years using population

data for adult age ≥ 18 years old. We defined severity of comorbid conditions using deyo modification of

charlson comorbidity index (CCI), which contains 17 comorbid conditions with differential weights. The

score ranges from 0 to 33, with higher scores corresponding to greater burden of comorbid diseases

(Supplementary table 1). Preventable procedural complications were identified by Patient Safety

Indicators (PSIs), which were established by the AHRQ to monitor preventable adverse events during

hospitalization. These indicators are based on ICD-9-CM codes and Medicare severity Diagnosis-Related

Groups and each PSI has specific inclusion and exclusion criteria8 (Supplementary table 2). PSI

individual technical specifications, were used to identify and define preventable procedural complications

viz. post-procedure respiratory failure, post-procedure renal and metabolic derangement, post-procedure

pulmonary embolism or deep vein thrombosis, procedural infectious complications which included post-

procedure sepsis and central venous catheter related bloodstream infection, pressure ulcers. Other

procedure related complications, which included hemorrhage requiring blood transfusion, iatrogenic

cardiac complications, requirement of open-heart surgery, procedural stroke or transient ischemic attack

(TIA) and vascular complications were identified using ICD-9-CM codes in any secondary diagnosis

field. In order to prevent classification of a pre-existing condition (e.g. stroke or heart block) as a

complication, cases with the ICD-9-CM code for a complication listed as the principal diagnosis (DX1)

were excluded. Vascular complications were defined as PSI code for accidental puncture or ICD-9-CM

codes for injury to blood vessels, creation of arteriovenous fistula, injury to retroperitoneum, vascular

complications requiring surgery and other vascular complications not elsewhere classified. “Any

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complication” was defined as occurrence of one or more procedural complications listed in

Supplementary table 1.

The total duration of hospital stay in days was estimated for all patients, after excluding those

who died in the hospital, using the information on length of stay provided in the NIS dataset. Disposition

was classified into 3 categories: those who were discharged home or with home care services were

classified as home-based discharge, those who were discharged to short or long term nursing home or

transferred to another facility were classified as discharge to another facility and those who died in-

hospital were classified as in-hospital mortality. Annual hospital volume was determined on a year to year

basis using the unique hospital identification number to calculate the total number of procedures

performed by a particular institution in a given year. Similarly operator volume was computed using

operator identification number. Annual hospital volume and annual operator volume in tertiles were used

for further analysis and to create hierarchical multivariate models. Adjustment term was added to

multivariate models to adjust for interaction effect between hospital and operator volume. Hospital ID

was incorporated as a random effect in the model to account for the effect of hospital clustering (meaning

that patients treated at the same hospital may experience similar outcomes as a result of other processes of

care).

The HCUP NIS contains data on total charges for each hospital in the databases. This charge

information represents the amount that hospitals billed for services, but does not reflect how much

hospital services actually cost or the specific amounts that hospitals received in payment. In order to

calculate estimated cost of hospitalizations the NIS data were merged with cost-to charge ratios (CCR)

available from the Healthcare Cost and Utilization Project (HCUP). Using the merged data elements from

the CCR files and the total charges reported in the NIS database, we converted the hospital total charge

data to cost estimates by simply multiplying total charges with the appropriate cost-to-charge ratio. These

costs are in essence standardized and can be measured across hospitals and are used in remainder of

paper. Adjusted cost for each year was calculated in terms of the 2010 cost, after adjusting for inflation

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according to the latest consumer price index (CPI) data released by US government on January 16, 2013.

The similar methodology has been utilized for prior studies.9

Stata IC 11.0 (Stata-Corp, College Station, TX) and SAS 9.3 (SAS Institute Inc, Cary, North

Carolina) were utilized for analyses. Weighted values of patient level observations were generated to

produce a nationally representative estimate of the entire US population of hospitalized patients.

Differences between categorical variables were tested using the chi-square test and differences between

continuous variables were tested using student’s t test. P-value < 0.05 was considered significant. The

NIS dataset is inherently hierarchical viz. the data has group (i.e. hospital) specific attributes and within

each group (i.e. hospital) there are patients which contribute patient specific attributes to the data.

Hierarchical models take into consideration the effect of nesting (e.g. patient levels effects nested within

hospital level effects). Hence it is superior to simple regression modeling for the available dataset. Two

level hierarchical models (with patient level factors nested within hospital level factors) were created with

the unique hospital identification number incorporated as random effects within the model. Hierarchical

mixed effects logistic regression models were used for categorical dependent variables like in-hospital

mortality and procedural complications and hierarchical mixed effects linear regression models were used

for continuous dependent variables like cost of hospitalization and length of stay. In all multivariate

models, we included hospital level variables like hospital region, teaching vs. non-teaching hospital and

patient level variables like age, sex, Deyo modification of CCI, use of intra-cardiac echocardiography

(ICE), occurrence of procedural complications, admission over the weekend and primary payer (with

Medicare/Medicaid considered as referent) in addition to hospital/operator procedure volume tertile. All

interactions were thoroughly tested. Multicollinearity, defined as a perfect linear relationship or very high

correlation between two or more predictor (independent) variables was assessed using variance inflation

factor (VIF), with VIF greater than 20 suggestive of multicollinearity.

RESULTS

A total of 13,564 (weighted n=67,344) CAS procedures were analyzed. Table 1 shows baseline

characteristics of the study population. The mean age was 71 ± 10 years with majority of cohort being

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male (60.6%) and white (68.9%). The average CCI score for the cohort was 2.23 ± 0.01, with

hypertension being the most common comorbidity present in 75% of the patients undergoing CAS. A

significant proportion of these procedures were done in large (69.4%), teaching (60.3%) hospitals after an

elective admission (69.8%). Most common primary payer for these procedures was Medicare/Medicaid

(74.6%).

The overall post-procedural mortality was low at 0.5% and remained relatively steady over the

time frame of the study. Similarly, complication rate was also steady around an overall rate of 8% from

2006 to 2010 (Supplementary table 3). However, both the rate of post-procedural mortality and

complications were noticed to decrease amongst symptomatic patients (Figure 1) from 2006 to 2010. The

observed rate of iatrogenic stroke post-procedure was 1.6%. Only 2% of the patients had iatrogenic

cardiac complications after the procedure. The overall rate of vascular (3.7%) and renal (0.1%)

complications was low and only 0.8% of the patients had any significant post-operative hemorrhage

requiring transfusion.

Higher CCI was associated with a higher rate of death or complications {For CCI ≥ 2: OR 1.34,

95% CI (1.09-1.66), p-value<0.01} (Table 2). Female sex was predictive of higher rate of post-operative

mortality and complications {OR 1.47, 95% CI (1.23-1.76), p-value<0.001}. A higher annual operator

volume was associated with lower rate of mortality and complications {Tertile 2 (5 – 13 annual

procedures): OR 0.74, 95% CI (0.59 – 0.92), p-value=0.01; Tertile 3 (14 – 68 annual procedures): OR

0.70, 95% CI (0.54 – 0.91), p-value=0.01}. Besides, symptomatic patients suffered from a higher rate of

post-procedural complications and mortality {OR 2.17, 95% CI (1.78-2.65), p-value < 0.001}. In sub-

group analysis, higher annual operator volume continues to be significant independent predictor of lower

post-procedural mortality and complication in following subgroups: highest (third) annual hospital

volume tertile and asymptomatic patients (Table 3).

The average LOS was 2.52 ± 0.02 days and the mean cost of hospitalization was $ 14,366 ± 46.

As seen in Figures 2, although the average LOS has decreased since 2006, the cost of hospitalization has

increased from 2006 to 2010, mostly due to increase in the cost of hospitalization for symptomatic

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patients. A high burden of comorbidities represented by a high CCI score was predictive of lengthier

hospital stay {for CCI ≥ 2: OR 0.76, 95% CI (0.58-0.94); p-value<0.001} and increased the cost of

hospitalization by $1,603. Any post-procedural complications increased LOS by average 2.48 days (95%

CI: 2.2 to 2.76; P-value<0.001) and increase the cost of hospitalization by $7,466 (Table 2). Private

insurance holders had shorter LOS by 0.24 days (95% CI: -0.44 to -0.03; p-Value=0.02) with reduced

hospitalization costs by $1,644. Weekend admissions were associated with increased LOS by an average

of 2.29 days (95% CI: 1.88 to 2.70; p-value<0.001) and increased cost ($2,828), while elective admission

reduced the LOS by 2.34 days (95% CI: -2.54 to -2.14), p-value<0.001) and hospitalization costs by

$4,234. Likewise, symptomatic patients had a longer LOS by an average of 1.30 days (95% CI: 1.11 to

1.50; p-value<0.001) and higher hospitalization costs ($3,223). Importantly, a higher annual operator

volume predicted shorter LOS {Tertile 2 (5 – 13 annual procedures): estimate -1.11 days, 95% CI: -1.31

to -0.91; p-value<0.01; Tertile 3 (14 – 68 annual procedures): estimate -1.17 days, 95% CI: -1.40 to -0.94;

p-value<0.001} as well as reduced cost of hospitalization (Tertile 2: -$2,956; Tertile 3: -$2,778) (Table 4

& 5).

DISCUSSION

The mortality rate of 0.5% following CAS in our study is comparable to existing literature

including older NIS cohorts10 as well as the CREST trial.4 Analogous to a sub-analysis of the CREST

trial11 symptomatic patients had significantly higher post-operative mortality and rate of complications in

our study even in hospitals with highest annual volume. A subset analysis of our study cohort shows a

decreasing trend for in-hospital mortality as well as post-procedural complications in symptomatic

patients though it continues to be higher than that observed in asymptomatic patients undergoing CAS.

This improvement might be in part due to evolving technology and operator experience accompanying

increased utilization of CAS since its FDA approval. In recent times however, increasing volume of

complex interventional procedures including CAS has resulted in dissemination of limited operator

experience in real world practice.12 The lower mortality and complications seen with higher operator

volume in our study parallels previously reported literature.13 Our study extends the findings over a longer

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time frame with further stratification based on clinical status and comprehensive evaluation of resource

utilization detailed below. An absolute risk reduction of 4.3% between lowest and highest operator

volume tertiles (Figure 3) reiterates the importance of limiting CAS to physicians in the latter stages of a

relatively steep learning curve14, 15 associated with this procedure. Indeed, in keeping with current

literature/guidelines, CAS should be performed only when the anticipated peri-procedural mortality is

<6% for symptomatic and < 3% for asymptomatic patients.16, 17 Notably, the annual operator volume was

predictive of poor outcomes even in the highest annual hospital volume tertile further reiterating the

importance of individual operator experience in this intricate procedure.

A larger burden of comorbidities as defined by higher CCI score was predictive of higher post-

procedural mortality and complications. Additionally, older age was predictive of worse outcomes

amongst symptomatic patients, which is consistent with data from previous trials including SPACE

plausibly secondary to unfavorable anatomy in these patients.18 The main recipients of CAS are elderly

individuals with high surgical risk due to existing comorbidities.19, 20 further implying the importance of

operator volume and experience in reducing complications and eventually mortality in this technically

demanding procedure. Females were more likely to have post-procedural mortality and complications in

our study even in hospitals with highest annual volume. Published literature on CEA has consistently

shown gender differences in post-operative stroke and death rates.21, 22 Other reports have indicated the

peri-operative outcomes to be specifically worse in asymptomatic women23 than asymptomatic men, a fact

that was replicated in our study. Although, SPACE trial reported a non-significant increase in post-

procedural events in women24, most of the randomized CAS trials have under-representation of women to

derive any significant results.25 Smaller vessel size and unfavorable anatomy in females21 are

hypothesized for such gender differences although definitive evidence is lacking.

The rate of post-operative stroke reported in our study (1.6%) was lower than that reported in

multiple randomized trials. This could be largely due to the inherent limitation of NIS database26 to

adequately differentiate between post-operative complications and stroke thus underestimating the true

risk. However, the incidence of stroke was noticed to decrease over recent years especially amongst

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symptomatic patients (Figure 4) who had a higher incidence of peri-procedural stroke, a result that was

again similar to reports from previous studies like the EVA-3S trial.27, 28 A plausible explanation could be

increased use of embolic protection devices29 in recent years besides improving operator experience.

The average LOS in our study (2.52 ± 0.02 days) was similar to the relatively shorter LOS

following CAS reported in previous trials including the CREST (2.6 days) and SAPPHIRE trials.30 The

occurrence of any post-procedural complications as well as a higher baseline CCI score were significant

predictors of longer LOS following CAS independent of the symptom status. This is comprehensible

given a longer recovery time for patients with a higher burden of pre-existing comorbidities as well as

post-procedural complications. Most importantly, a higher operator volume was predictive of reduced

LOS and hospitalization costs even in the highest annual hospital volume tertile in both symptomatic and

asymptomatic patients. This is important in the current financial scenario of the United States healthcare

system, which necessitates effective resource utilization to reduce LOS and medical expenditures. The

mean cost of hospitalization in our study replicates the results from the CREST trial30 in a real world

clinical practice setting. We observed a trend towards increasing hospitalization costs in recent years

mainly due to worsening hospital expenses for symptomatic patients. This could plausibly be explained

by an increased rate of complications and mortality in symptomatic patients noted in our study thus

driving up their hospital expenditures.

The limitations of our study are primarily inherent to post-hoc analysis of an administrative

database like NIS2631. These include lack of long-term follow up data, clinical information (use of embolic

protection devices, anatomical lesion complexities and risk factors etc.) as well as a potential for

oversights in coding. Likewise, our determination of the operator volume could underestimate the overall

operator experience since they could be doing CAS in hospitals not part of the NIS database. Although

principal diagnosis is accurately coded in administrative data, secondary or comorbid diagnoses are often

under-reported. These limitations aside, the NIS provides the largest publicly available database that has

been previously utilized for clinically relevant information on various peri-procedural outcome.9 Our

study results though not conclusive should be considered as informative for further research in this field.

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ACKNOWLEDGEMENT: None declared.

FUNDING RESOURCES: No study specific funding was used to support this work. The authors are

solely responsible for the study design, conduct and analyses, drafting and editing of the manuscript and

its final contents. No statement should be construed as an official position of the AHRQ or the US

Department of Health and Human Services. All authors had access to the data and a role in writing the

manuscript.

DISCLOSURES: None of the authors have any disclosures relevant to the content of the manuscript.

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REFERENCES

1. Trends in aging--United States and worldwide. MMWR Morb Mortal Wkly Rep 2003;52:101-

104,106.

2. R Roger VL, Go AS, Lloyd-Jones DM, Adams RJ, Berry JD, Brown TM, Carnethon MR, Dai S,

de Simone G, Ford ES, Fox CS, Fullerton HJ, Gillespie C, Greenlund KJ, Hailpern SM, Heit JA,

Ho PM, Howard VJ, Kissela BM, Kittner SJ, Lackland DT, Lichtman JH, Lisabeth LD, Makuc

DM, Marcus GM, Marelli A, Matchar DB, McDermott MM, Meigs JB, Moy CS, Mozaffarian D,

Mussolino ME, Nichol G, Paynter NP, Rosamond WD, Sorlie PD, Stafford RS, Turan TN,

Turner MB, Wong ND, Wylie-Rosett J; American Heart Association Statistics Committee and

Stroke Statistics Subcommittee. Heart disease and stroke statistics--2011 update: a report from

the American Heart Association. Circulation 2011;123:e18-e209.

3. Yadav JS, Wholey MH, Kuntz RE, Fayad P, Katzen BT, Mishkel GJ, Bajwa TK, Whitlow P,

Strickman NE, Jaff MR, Popma JJ, Snead DB, Cutlip DE, Firth BG, Ouriel K; Stenting and

Angioplasty with Protection in Patients at High Risk for Endarterectomy Investigators. Protected

carotid-artery stenting versus endarterectomy in high-risk patients. N Engl J Med 2004;351:1493-

1501.

4. Brott TG, Hobson RW 2nd, Howard G, Roubin GS, Clark WM, Brooks W, Mackey A, Hill MD,

Leimgruber PP, Sheffet AJ, Howard VJ, Moore WS, Voeks JH, Hopkins LN, Cutlip DE, Cohen

DJ, Popma JJ, Ferguson RD, Cohen SN, Blackshear JL, Silver FL, Mohr JP, Lal BK, Meschia JF;

CREST Investigators. Stenting versus endarterectomy for treatment of carotid-artery stenosis. N

Engl J Med 2010;363:11-23.

5. Patel MR, Greiner MA, DiMartino LD, Schulman KA, Duncan PW, Matchar DB, Curtis LH.

Geographic variation in carotid revascularization among Medicare beneficiaries, 2003-2006. Arch

Intern Med 2010;170:1218-1225.

MANUSCRIP

T

ACCEPTED

ACCEPTED MANUSCRIPT

13

6. Healthcare cost and utilization project (hcup). Agency for healthcare research and quality,

rockville, md; 2008. Hcup databases. Available at: http://www.hcup-

us.ahrq.gov/db/nation/nis/nisrelatedreports.jsp. Accessed on 31 January 2013.

7. Epstein AJ, Polsky D, Yang F, Yang L, Groeneveld PW. Coronary revascularization trends in the

United States, 2001-2008. JAMA 2011;305:1769-1776.

8. Romano PS, Geppert JJ, Davies S, Miller MR, Elixhauser A, McDonald KM. A national profile

of patient safety in U.S. hospitals. Health Aff (Millwood) 2003;22:154-166.

9. Deshmukh A, Patel NJ, Pant S, Shah N, Chothani A, Mehta K, Grover P, Singh V, Vallurupalli S,

Savani GT, Badheka A, Tuliani T, Dabhadkar K, Dibu G, Reddy YM, Sewani A, Kowalski M,

Mitrani R, Paydak H, Viles-Gonzalez JF. Inhospital Complications Associated with Catheter

Ablation of Atrial Fibrillation in the United States between 2000-2010: Analysis of 93,801

Procedures. Circulation 2013;128:2104-2112.

10. Eslami MH, McPhee JT, Simons JP, Schanzer A, Messina LM. National trends in utilization and

postprocedure outcomes for carotid artery revascularization 2005 to 2007. J Vasc Surg

2011;53:307-315.

11. Silver FL, Mackey A, Clark WM, Brooks W, Timaran CH, Chiu D, Goldstein LB, Meschia JF,

Ferguson RD, Moore WS, Howard G, Brott TG; CREST Investigators. Safety of stenting and

endarterectomy by symptomatic status in the Carotid Revascularization Endarterectomy Versus

Stenting Trial (CREST). Stroke 2011;42:675-680.

12. Halm EA. The good, the bad, and the about-to-get ugly: national trends in carotid

revascularization: comment on "Geographic variation in carotid revascularization among

Medicare beneficiaries, 2003-2006". Arch Intern Med 2010;170:1225-1227.

13. Nallamothu BK, Gurm HS, Ting HH, Goodney PP, Rogers MA, Curtis JP, Dimick JB, Bates ER,

Krumholz HM, Birkmeyer JD. Operator experience and carotid stenting outcomes in Medicare

beneficiaries. JAMA 2011;306:1338-1343.

MANUSCRIP

T

ACCEPTED

ACCEPTED MANUSCRIPT

14

14. Lin PH, Bush RL, Peden EK, Zhou W, Guerrero M, Henao EA, Kougias P, Mohiuddin I,

Lumsden AB. Carotid artery stenting with neuroprotection: assessing the learning curve and

treatment outcome. Am J Surg 2005;190:850-857.

15. Verzini F, Cao P, De Rango P, Parlani G, Maselli A, Romano L, Norgiolini L, Giordano G.

Appropriateness of learning curve for carotid artery stenting: an analysis of periprocedural

complications. J Vasc Surg 2006;44:1205-1211; discussion 1211-1212.

16. Brott TG, Halperin JL, Abbara S, Bacharach JM, Barr JD, Bush RL, Cates CU, Creager MA,

Fowler SB, Friday G, Hertzberg VS, McIff EB, Moore WS, Panagos PD, Riles TS, Rosenwasser

RH, Taylor AJ; American College of Cardiology Foundation; American Stroke Association;

American Association of Neurological Surgeons; American College of Radiology; American

Society of Neuroradiology; Congress of Neurological Surgeons; Society of Atherosclerosis

Imaging and Prevention; Society for Cardiovascular Angiography and Interventions; Society of

Interventional Radiology; Society of NeuroInterventional Surgery; Society for Vascular

Medicine; Society for Vascular Surgery. 2011

ASA/ACCF/AHA/AANN/AANS/ACR/ASNR/CNS/SAIP/SCAI/SIR/SNIS/SVM/SVS guideline

on the management of patients with extracranial carotid and vertebral artery disease: executive

summary. A report of the American College of Cardiology Foundation/American Heart

Association Task Force on Practice Guidelines, and the American Stroke Association, American

Association of Neuroscience Nurses, American Association of Neurological Surgeons, American

College of Radiology, American Society of Neuroradiology, Congress of Neurological Surgeons,

Society of Atherosclerosis Imaging and Prevention, Society for Cardiovascular Angiography and

Interventions, Society of Interventional Radiology, Society of NeuroInterventional Surgery,

Society for Vascular Medicine, and Society for Vascular Surgery. Circulation 2011;124:489-532.

17. Buschur M, Gurm HS. Carotid Artery Stenting Versus Carotid Endarterectomy: Post CREST.

Curr Cardiol Rep 2012 Feb 5 [Epub ahead of print].

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18. SPACE Collaborative Group, Ringleb PA, Allenberg J, Brückmann H, Eckstein HH, Fraedrich G,

Hartmann M, Hennerici M, Jansen O, Klein G, Kunze A, Marx P, Niederkorn K, Schmiedt W,

Solymosi L, Stingele R, Zeumer H, Hacke W. 30 day results from the SPACE trial of stent-

protected angioplasty versus carotid endarterectomy in symptomatic patients: a randomised non-

inferiority trial. Lancet 2006;368:1239-1247.

19. Bangalore S, Bhatt DL, Röther J, Alberts MJ, Thornton J, Wolski K, Goto S, Hirsch AT, Smith

SC, Aichner FT, Topakian R, Cannon CP, Steg PG; REACH Registry Investigators. Late

outcomes after carotid artery stenting versus carotid endarterectomy: insights from a propensity-

matched analysis of the Reduction of Atherothrombosis for Continued Health (REACH) Registry.

Circulation 2010;122:1091-1100.

20. Wang FW, Esterbrooks D, Kuo YF, Mooss A, Mohiuddin SM, Uretsky BF. Outcomes after

carotid artery stenting and endarterectomy in the Medicare population. Stroke 2011;42:2019-

2025.

21. Alamowitch S, Eliasziw M, Barnett HJ. The risk and benefit of endarterectomy in women with

symptomatic internal carotid artery disease. Stroke 2005;36:27-31.

22. Halliday A, Mansfield A, Marro J, Peto C, Peto R, Potter J, Thomas D; MRC Asymptomatic

Carotid Surgery Trial (ACST) Collaborative Group. Prevention of disabling and fatal strokes by

successful carotid endarterectomy in patients without recent neurological symptoms: randomised

controlled trial. Lancet 2004;363:1491-1502.

23. Chambers BR, Donnan GA. Carotid endarterectomy for asymptomatic carotid stenosis. Cochrane

Database Syst Rev 2005:CD001923.

24. Stingele R, Berger J, Alfke K, Eckstein HH, Fraedrich G, Allenberg J, Hartmann M, Ringleb PA,

Fiehler J; SPACE investigators, Bruckmann H, Hennerici M, Jansen O, Klein G, Kunze A, Marx

P, Niederkorn K, Schmiedt W, Solymosi L, Zeumer H, Hacke W. Clinical and angiographic risk

factors for stroke and death within 30 days after carotid endarterectomy and stent-protected

angioplasty: a subanalysis of the SPACE study. Lancet Neurol 2008;7:216-222.

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25. De Rango P, Parlani G, Caso V, Verzini F, Giordano G, Cieri E, Cao P. A comparative analysis

of the outcomes of carotid stenting and carotid endarterectomy in women. J Vasc Surg

2010;51:337-344; discussion 344.

26. Hertzer NR. The Nationwide Inpatient Sample may contain inaccurate data for carotid

endarterectomy and carotid stenting. J Vasc Surg 2012;55:263-266.

27. Mas JL, Chatellier G, Beyssen B, Branchereau A, Moulin T, Becquemin JP, Larrue V, Lièvre M,

Leys D, Bonneville JF, Watelet J, Pruvo JP, Albucher JF, Viguier A, Piquet P, Garnier P, Viader

F, Touzé E, Giroud M, Hosseini H, Pillet JC, Favrole P, Neau JP, Ducrocq X; EVA-3S

Investigators. Endarterectomy versus stenting in patients with symptomatic severe carotid

stenosis. N Engl J Med 2006;355:1660-1671.

28. Brahmanandam S, Ding EL, Conte MS, Belkin M, Nguyen LL. Clinical results of carotid artery

stenting compared with carotid endarterectomy. J Vasc Surg 2008;47:343-349.

29. Iyer V, de Donato G, Deloose K, Peeters P, Castriota F, Cremonesi A, Setacci C, Bosiers M. The

type of embolic protection does not influence the outcome in carotid artery stenting. J Vasc Surg

2007;46:251-256.

30. Vilain KR, Magnuson EA, Li H, Clark WM, Begg RJ, Sam AD 2nd, Sternbergh WC 3rd, Weaver

FA, Gray WA, Voeks JH, Brott TG, Cohen DJ; CREST Investigators. Costs and cost-

effectiveness of carotid stenting versus endarterectomy for patients at standard surgical risk:

results from the Carotid Revascularization Endarterectomy Versus Stenting Trial (CREST).

Stroke 2012;43:2408-2416.

31. Iezzoni LI, Foley SM, Daley J, Hughes J, Fisher ES, Heeren T. Comorbidities, complications, and

coding bias. Does the number of diagnosis codes matter in predicting in-hospital mortality?

JAMA 1992;267:2197-2203.

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FIGURE LEGENDS

Figure 1: The rate of post-procedural mortality and complications amongst symptomatic patients

from 2006 to 2010.

Figure 2: The average Length of stay and the cost of hospitalization of symptomatic patients from

2006 to 2010.

Figure 3: Adjusted risk rate of death + any complication for tertiles of annual operator volume.

Figure 4: Incidence of stroke amongst the symptomatic patients from 2006 to 2010.

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Table 1: Baseline characteristics of the study population undergoing Percutaneous Carotid Artery

Stenting procedure in the United States from 2006-2010.

Actual (projected) number of Percutaneous Carotid Stent Placement procedure in the US 13564 (67344)

Age (Years) 71± 10

Men 60.6 %

White 68.9 %

Non-white 10.5 %

Charlson/deyo comorbidity index† 2.23±0.01

Obesity 5.4%

Hypertension 75%

Diabetes mellitus 31%

Congestive heart failure 10.5%

Chronic pulmonary disease 20.9%

Peripheral vascular disease 27.4%

Pulmonary circulatory disease 1.2%

Renal failure 13.4%

Neurological disorder/paralysis 0.4%

Anemia/coagulopathy 8.1%

Hematological/oncological malignancy 1.8%

Weight loss/cachexia 0.5%

Rheumatoid arthritis/collagen vascular disease 1.4%

Depression/substance Abuse 6.8%

Median household income category for patient's zip code‡ (Percentile)

0-25th 26.2%

26-50th 27.4%

51-75th 24.5%

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76-100th 19.7%

Primary Payer

Medicare / Medicaid 74.6%

Private including HMO 21.2%

Self-pay/no charge/other 3.9%

Hospital bed size

Small 10.5%

Medium 19.2%

Large 69.4%

Hospital Region

Northeast 19%

Mid West/North Central 24.09%

South 46.08%

West 10.80%

Teaching Hospital 60.3%

Admission types

Emergent/Urgent 29%

Elective 69.8%

Weekend Admission (%) 3.7%

Length of stay (Means ± SE) (days) 2.52 ± 0.02

Total charges§ ($)(Means ± SE) 14,366± 46

Peri-procedural complications|| 8.0%

Disposition

Home 92.4%

Facility 6.9%

Death 0.5%

* Race was missing in 20.6 % of the study population

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† Charlson/deyo comorbidity index was calculated using ICD-9 codes - Deyo RA, Cherkin DC, Coil MA.

Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin

Epidemiol.1992;45:613–619

‡ This represents a quartile classification of the estimated median household income of residents in the

patient's ZIP Code. These values are derived from ZIP Code-demographic data obtained from Claritas.

The quartiles are identified by values of 1 to 4, indicating the poorest to wealthiest populations. Because

these estimates are updated annually, the value ranges vary by year. Available at: http://www.hcup-

us.ahrq.gov/db/vars/zipinc_qrtl/nisnote.jsp

§ For each year, cost was adjusted for inflation according to reference 2010 cost. Cost was missing in 16.5

% cases.

|| Peri-procedural Complications were coded as using PSI indicator codes

http://www.qualityindicators.ahrq.gov/Modules/psi_overview.aspx and ICD 9 diagnosis codes, for

complications not coded by PSI indicator.

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Table 2: Predictors of death/complication, Length of Stay (LOS), and Cost of Hospitalization

related to percutaneous Carotid Artery Stenting in US from 2006-2010.

Variable Any complication/death Length of stay Cost of hospitalization

OR (95% CI) P value Days (95% CI) P value Dollar($) (95% CI) P value

Any complication +2.48(2.20-2.76) <0.001 +7466(5818 – 9115) <0.001

Age 1.01(0.997-

1.01) 0.16 +0.01(0.00-0.01) 0.22 -126(-185 - -67) <0.001

Female 1.47(1.23-1.76) <0.001 +0.08(-0.07 - 0.23) 0.30 +36(-1091 – 1163) 0.95

CCI * (Referent= 0)

1 0.94(0.74-1.18) 0.57 +0.09(-0.09 - 0.27) 0.32 +232(-1191 – 1656) 0.749

>2 1.34(1.09-1.66) 0.01 +0.76(0.58-0.94) <0.001 +1603(236 – 2970) 0.022

Primary payer (Referent=

Medicare/Medicaid)

Private 1.03(0.81-1.32) 0.80 -0.24(-0.44 - -0.03) 0.02 -1644(-3168 - -120) 0.034

Other 1.03(0.63-1.67) 0.92 +0.30(-0.13 - 0.72) 0.17 -3337(-6225 - -448) 0.024

Weekend Admission 1.27(0.86-1.88) 0.24 +2.29(1.88-2.70) <0.001 +2828(748 – 4908) 0.008

Hospital Region

(Referent=West)

North East 1.06(0.73-1.54) 0.74 +0.14(-0.36 - 0.63) 0.59 -2029 (-4735 - 678) 0.142

Mid West/North

Central 1.08(0.72-1.62) 0.72 -0.22(-0.75 - 0.32) 0.43 -2683(-4869 - -497) 0.016

South 1.05(0.76-1.46) 0.77 -0.10(-0.54 - 0.34) 0.65 -742(-3505 – 2020) 0.598

Hospital Volume Tertile

{Referent= 1(1 to 18)}

2(19 to 38) 0.98(0.77-1.26)

0.88

+0.29(0.02-0.57) 0.04 -54(-1828 -1720) 0.952

3(39 to 142) 1.01(0.77-1.33)

0.90

+0.26(-0.06 - 0.58) 0.12 -566(-2680 – 1549) 0.6

Operator Volume Tertile

{Referent=1(1 to 4)}

2(5 to 13) 0.74(0.59-0.92) 0.01 -1.11(-1.31 - -0.91) <0.001 -2956(-4479 - -1434) <0.001

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3(14 to 68) 0.70(0.54-0.91) 0.01 -1.17(-1.40 - -0.94) <0.001 -2778(-4508 - -1047) 0.002

Elective Admission 0.92(0.74-1.13) 0.42 -2.34(-2.54 - -2.14) <0.001 -4234(-5609 - -2858) <0.001

Symptomatic 2.17(1.78-2.65) <0.001 +1.30(1.11-1.50) <0.001 +3223(1918 - 4529) <0.001

* CCI: Charlson comorbidity index.

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Table 3: Predictors of death or complication related to percutaneous CAS in US from 2006-2010 for

following subgroups: a) highest (third) annual hospital volume tertile, b) symptomatic patients

(presenting with stroke), c) asymptomatic patients.

Highest (Third) Annual

Hospital Volume Tertile

Symptomatic Asymptomatic

OR(95% CI) P value OR(95% CI) P value OR(95% CI) P value

Age 1.02(1.00-1.03) 0.07 1.02(1.00-1.04) 0.02 1.00(0.99-1.01) 0.90

Female 1.65(1.21-2.25) <0.01 1.34(0.99-1.83) 0.06 1.53(1.23-1.91) <0.001

CCI (Referent= 0)

1 0.87(0.58-1.30) 0.49 0.86(0.57-1.31) 0.49 1.00(0.76-1.31) 0.98

>2 1.24(0.86-1.78) 0.25 1.25(0.88-1.79) 0.22 1.42(1.09-1.84) 0.01

Operator Volume Tertile {Referent=1(1 to 4)}

2(5 to 13) 0.59(0.37-0.94) 0.02 0.62(0.41-0.95) 0.03 0.79(0.60-1.04) 0.10

3(14 to 68) 0.63(0.42-0.92) 0.02 0.74(0.48-1.14) 0.17 0.71(0.52-0.97) 0.03

Symptomatic 2.41(1.70-3.42) <0.001

Note: Others variables included in hierarchical models but found not be significant: Primary Payer,

Weekend Admission, Hospital Region, Annual Hospital Volume Tertile (Symptomatic and

Asymptomatic patients), Elective admission.

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Table 4: Predictors of Length of Stay (LOS) related to percutaneous CAS in US from 2006-2010 for

following subgroups: a) highest (third) annual hospital volume tertile, b) symptomatic patients

(presenting with stroke), c) asymptomatic patients.

Highest (third) annual hospital volume tertile

Symptomatic Asymptomatic

Estimate (95% CI)

P value Estimate (95% CI)

P value Estimate (95% CI)

P value

Any Complication 1.77(1.39 - 2.14) <0.001 3.64(2.82 – 4.47) <0.001 1.92(1.68 -2.16) <0.001

Age 0.02(0.01 - 0.03) <0.001 -0.02(0.05 – 0.01) 0.11 0.01(0.01 – 0.02) <0.01

Female 0.25(0.06 - 0.44) 0.01 -0.44(-1 – 0.13) 0.13 0.17(0.05 – 0.29) <0.01

CCI (Referent= 0)

1 0.04(-0.19 - 0.27) 0.75 0.43(-0.29 – 1.14) 0.24 0.02(-0.12 – 0.16) 0.74

> 2 0.72(0.48 - 0.95) <0.001 1.42(0.76 – 2.08) <0.001 0.57(0.42 – 0.71) <0.001

Primary payer (Referent= Medicare/Medicaid)

Private 0.04(-0.21 - 0.29) 0.74 -0.84(-1.61 - -0.06) 0.03 -0.08(-0.24 – 0.08) 0.35

Other 1.17(0.60 - 1.74) <0.001 -0.18(-1.52 – 1.17) 0.80 0.54(0.18 – 0.9) <0.01

Weekend Admission 2.06(1.48 - 2.63) <0.001 1.04(0.05 – 2.03) 0.04 3.10(2.68 – 3.52) <0.001

Operator Volume Tertile {Referent=1(1 to 4)}

2(5 to 13) -1.40(-1.70 - -1.1) <0.001 -1.58(-2.32 - -0.85) <0.001 -0.88(-1.04- 0.72) <0.001

3(14 to 68) -1.33(-1.60 - -1.07) <0.001 -1.87(-2.68 - -1.06) <0.001 -0.97(-1.16- -0.78) <0.001

Elective Admission -1.59(-1.87 - -1.32) <0.001 -3.55(-4.18 - -2.92) <0.001 -1.75(-1.92- -1.58) <0.001

Symptomatic 1.04(0.78 – 1.31) <0.001

Note: Others variables included in hierarchical models but found not be significant: Hospital Region,

Annual Hospital Volume Tertile (Symptomatic and Asymptomatic patients).

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Table 5: Predictors of highest tertile of cost (in dollars) related to percutaneous CAS.

Variable Estimate (days) (95% CI) P value

Any Complication +7466(5818 – 9115) <0.001

Age -126(-185 - -67) <0.001

Female +36(-1091 – 1163) 0.95

CCI (Referent= 0)

1 +232(-1191 – 1656) 0.749

>2 +1603(236 – 2970) 0.022

Primary payer (Referent= Medicare/Medicaid)

Private -1644(-3168 - -120) 0.034

Other -3337(-6225 - -448) 0.024

Weekend Admission +2828(748 – 4908) 0.008

Hospital Region (Referent=West)

North East -2029 (-4735 - 678) 0.142

Mid West/ Mid West/North Central -2683(-4869 - -497) 0.016

South -742(-3505 – 2020) 0.598

Hospital Volume Tertile {Referent= 1(1 to 18)}

2(19 to 38) -54(-1828 -1720) 0.952

3(39 to 142) -566(-2680 – 1549) 0.6

Operator Volume Tertile {Referent=1(1 to 4)}

2(5 to 13) -2956(-4479 - -1434) <0.001

3(14 to 68) -2778(-4508 - -1047) 0.002

Elective Admission -4234(-5609 - -2858) <0.001

Symptomatic +3223(1918 - 4529) <0.001

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Figure 1: The rate of post-procedural mortality and complications amongst symptomatic patients

from 2006 to 2010.

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Figure 2: The average Length of stay and the cost of hospitalization of symptomatic patients from

2006 to 2010.

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Figure 3: Adjusted risk rate of death + any complication for tertiles of annual operator volume.

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Figure 4: Incidence of stroke amongst the symptomatic patients from 2006 to 2010.

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Supplementary table 2: Deyo modification of Charlson comorbidity index (CCI).

Reported ICD-9 CM Codes Condition Charlson Score

410 – 410.9 Myocardial infarction 1

428 – 428.9 Congestive heart failure 1

433.9, 441 – 441.9, 785.4, V43.4 Peripheral vascular disease 1

430 – 438 Cerebrovascular disease 1

290 – 290.9 Dementia 1

490 – 496, 500 – 505, 506.4 Chronic pulmonary disease 1

710.0, 710.1, 710.4, 714.0 – Rheumatologic disease 1

531 – 534.9 Peptic ulcer disease 1

571.2, 571.5, 571.6, 571.4 –

571.49

Mild liver disease 1

250 – 250.3, 250.7 Diabetes 1

250.4 – 250.6 Diabetes with chronic complications 2

344.1, 342 – 342.9 Hemiplegia/paraplegia 2

582 – 582.9, 583 – 583.7, 585,

586, 588 – 588.9

Renal disease 2

140-172.9, 174-195.8, 200-208.9 Any malignancy including leukemia and

lymphoma

2

572.2 – 572.8 Moderate or severe liver disease 3

196-199.1 Metastatic solid tumor 6

042 – 044.9 AIDS 6

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Supplementary table 1: Procedural complications of CAS procedure by ICD 9 code.

Any procedural complications ICD CODE

Vascular complications

1) Hemorrhage/Hematoma 998.11 or 998.12

2) Transfusion 99.0, V58.2

3) Postop-hemorrhage requiring transfusion

4) Vascular complications including -Injury to blood vessels-900-904

-Accidental puncture-998.2, e8700-8709

(PSI)

-AV fistula-447

-Injury to retro-peritoneum 8680.4

-Vascular complications requiring surgery-

39.31, 39.41, 39.49, 39.52, 39.53, 39.56,

39.57, 39.58, 39.59, 39.79

-Other vascular complications-999.2, 997.7

Cardiac complications

1) Iatrogenic cardiac complications* 997.1

2) Permanent pacemaker implantation 37.80-83

3) Pericardial complications 423.0-Hemopericardium

423.3-Cardiac temponade

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37.0-Pericardiocentesis

4) Implantable cardioverter-defibrillator

implantation

37.94, 0.51, 0.52

Requiring open heart surgery 35.10, 35.11, 35.12, 35.13, 35.14, 35.20,

35.21, 35.22, 35.23, 35.24, 35.25, 35.26,

35.27, 35.28, 35.31, 35.32, 35.33,35.34,

35.35,35.42, 35.50, 35.51, 35.52, 35.53,

35.54, 35.60, 35.61, 35.62, 35.63,35.70,

35.71, 35.72, 35.73, 35.81, 35.82, 35.83,

35.84,35.91, 35.92, 35.93, 35.94, 35.95,

35.97, 35.98, 35.99, 36.31, 36.32, 37.32,

37.33, 37.34, 37.35,36.10, 36.11, 36.12,

36.13, 36.14, 36.15, 36.16,36.31, 36.32,

37.32, 37.33, 37.35, 37.51, 37.52, 37.53,

37.54, 37.51, 37.52, 37.53, 37.54, 39.66,

Ecom-39.61

Respiratory complications (Postop respiratory

failure)

512.1

Neurological complications

Postop stroke/TIA 997.0, 997.00, 997.01, 997.02, 435.9,

438.0, 4381.0, 4381.1, 4381.2, 4381.9,

4382.0, 4382.1, 4382.2, 4383.0, 4383.1,

4383.2, 4384.0, 4384.1, 4384.2, 4385.0,

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4385.1, 4385.2, 4385.3,4388.1, 4388.2,

4388.9, 438.9

Renal and metabolic complications

Postoperative DVT/PE PSI†

Postop infectious complications PSI†

Pressure ulcer rate PSI†

*997.1 Iatrogenic cardiac complications

• Av block 3rd degree, complication of AV nodal ablation

• Av block, complete, post op complication of AV nodal ablation

• Bypass complications

• Cardiac arrest as a complication of care

• Cardiac arrest during and/or resulting from a procedure

• Cardiac complication

• Cardiac complication of procedure

• Cardiac insufficiency as a complication of care

• Cardiac insufficiency during and/or resulting from a procedure

• Cardiorespiratory failure as a complication of care

• Cardiorespiratory failure during and/or resulting from a procedure

• Chf after surgery, early postop complication

• Chf following cardiac surgery, postop

• Chf following non-cardiac surgery, postop

• Complete atrioventricular block due to atrioventricular nodal ablation

• Congestive heart failure after surgery

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• Congestive heart failure as early postoperative complication

• Congestive heart failure as postoperative complication of cardiac surgery

• Congestive heart failure as postoperative complication of non cardiac surgery

• Heart failure as a complication of care

• Junctional ectopic tachycardia, postoperative

• Post cardiac operation functional disturbance

• Postoperative cardiac complication

• Postoperative complete heart block

• Postoperative his bundle tachycardia

• Postoperative myocardial infarction

• Postoperative sinoatrial disease

• Postoperative subendocardial myocardial infarction

• Postoperative transmural myocardial infarction of anterior wall

• Postoperative transmural myocardial infarction of inferior wall

• Recurrent coronary arteriosclerosis after percutaneous transluminal coronary angioplasty

997.1 Excludes

• the listed conditions as long-term effects of cardiac surgery or due to the presence of cardiac

prosthetic device ( 429.4)

Applies To

• Cardiac:

o arrest during or resulting from a procedure

o insufficiency during or resulting from a procedure

• Cardiorespiratory failure during or resulting from a procedure

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†Post-procedural complications were identified by Patient Safety Indicators (PSIs) which have been

established by the Agency for Healthcare Research and Quality to monitor preventable adverse events

during hospitalization. These indicators are based on ICD-9-CM codes and Medicare severity diagnosis-

Related Groups and each PSI has specific inclusion and exclusion criteria. PSI individual measure

technical specifications, Version 4.4, March 2012 was used to identify & define preventable

complications.

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Supplementary table 3: Peri-procedural complication rate in patients undergoing Percutaneous

Carotid Artery Stenting in the United States from 2006-2010.

Variable 2006 2007 2008 2009 2010 Overall

Death (%) 0.5 0.3 0.6 0.7 0.6 0.5

Any complications (%) 7.0 7.3 9.2 7.8 8.5 8.0

Death + Any complications (%) 7.2 7.4 9.4 8.1 8.7 8.2

Vascular complications(%) 3.3 3.9 4.0 3.6 3.8 3.7

1. Postop-hemorrhage requiring transfusion (%) 0.5 0.7 1.0 0.8 1.1 0.8

2. Vascular injury (%) 2.7 3.2 3.1 2.8 2.7 2.9

Iatrogenic cardiac complications (%) 1.9 1.6 2.6 1.7 1.9 2.0

Respiratory complications (Post-op respiratory failure) (%) 0.4 0.6 0.5 0.7 1.1 0.7

Iatrogenic Stroke (%) 1.3 1.1 2.0 1.9 1.7 1.6

Renal and metabolic complications (%) 0.1 < 0.1 < 0.1 0.1 0.2 0.1

Postoperative DVT/PE* (%) 0.2 0.2 0.3 0.3 0.3 0.3

Postop infectious complications (%) 0.2 0.2 0.4 0.5 0.5 0.3

Pressure ulcer rate (%) 0.1 0.2 0.3 0.5 0.5 0.3

* DVT: Deep Vein Thrombosis PE: Pulmonary embolism