Participation in Cardiac Rehabilitation and Survival Following ...

DOI: 10.1161/CIRCULATIONAHA.112.001365

1

Participation in Cardiac Rehabilitation and Survival Following Coronary

Artery Bypass Graft Surgery: A Community Based Study

Running title: Pack et al.; Cardiac rehabilitation after CABG

Quinn R. Pack, MD1; Kashish Goel, MD1,2; Brian D. Lahr, MS3; Kevin L. Greason, MD4;

Ray W. Squires, PhD1; Francisco Lopez-Jimenez, MD, MS1; Zixin Zhang, MD1,5;

Randal J. Thomas, MD, MS1

1Div of Cardiovascular Diseases, Dept of Internal Medicine; 3Div of Biomedical Statistics and

Informatics; 4Div of Cardiothoracic Surgery, Mayo Clinic, Rochester, MN; 2Div of Internal

Medicine, Detroit Medical Center/Wayne State University, Detroit, MI; 5Dept of Cardiology,

First Hospital of China Medical University, Shenyang, China

Address for Correspondence:

Randal Thomas, MD

Division of Cardiovascular Disease and Internal Medicine

Mayo Clinic

200 First Street SW

Rochester, MN 55905

Tel: 507-774-4375.

Fax: 507-266-7929.

E-mail: [email protected]

Journal Subject Codes: Treatment:[26] Exercise/exercise testing/rehabilitation, Cardiovascular (CV) surgery:[36] CV surgery: coronary artery disease, Treatment:[122] Secondary prevention, Ethics and policy:[100] Health policy and outcome research

Randal J. Thomas, MD, MS1

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Abstract:

Background—Cardiac rehabilitation (CR) is recommended for all patients following coronary

artery bypass surgery (CABG), yet little is known about the long term mortality effects of CR in

this population.

Methods and Results—We performed a community-based analysis on residents of Olmsted

County, Minnesota who underwent CABG between 1996 and 2007. We assessed the association

between subsequent outpatient CR attendance and long-term survival. Propensity analysis was

performed. Cox PH regression was then used to assess the association between CR attendance

and all-cause mortality adjusted for the propensity to attend CR. We identified 846 eligible

patients (age 66 ± 11 years, 76% men, and 96% non-Hispanic whites) who survived at least 6

months after surgery, of whom 582 (69%) attended CR. During a mean (± SD) follow-up of 9.0

± 3.7 years, the 10-year all-cause mortality rate was 28% (193 deaths). Adjusted for the

propensity to attend CR, participation in CR was associated with a 10-year relative risk reduction

in all-cause mortality of 46% (HR=0.54; 95% CI, 0.40-0.74; p<0.001), and a 10-year absolute

risk reduction of 12.7% (NNT=8). There was no evidence of a differential effect of CR on

mortality with respect to age ( 65 vs <65 yrs.), gender, diabetes, or prior myocardial infarction.

Conclusions— Cardiac rehabilitation attendance is associated with a significant reduction in 10

year all-cause mortality following CABG. Our results strongly support national standards that

recommend CR for this patient group.

Key words: cardiac rehabilitation, mortality, secondary prevention, bypass surgery, Propensity, Participation

and all-cause mortality adjusted for the propensity to attend CR. We identified 848446 6 eeligigigibibiblelele

patients (age 66 ± 11 years, 76% men, and 96% non-Hispanic whites) who survived at least 6

momontntnthshshs aaftftfterere ssurrgegegeryry, of whom 582 (69%) attendddedede CR. During aaa meaeaann n ((± SD) follow-up of 9.0

±± 3...7 7 years, thehe 11100-yeyeaar aaallllll-c-c-cauauusese mmmororo tttallity rrrattte wwwass 2888%%% (1(119933 ddeaeaathths)s)).. AAdAdjujuuststteded fffororr tthehh

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n all-cause mmmororortataalililitytyty ooof f f 4666% % % (HHHR=R=R 0.00 54544;; 959595%%% CCCI,I,I 000.4.440-0-0.0.0 747474;;; p<p<p<0.00 000001)1)1), , ananand d d a a 101010-y-yyeaeaearr r absolute



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Introduction

Each year, more than 300,000 patients undergo Coronary Artery Bypass Grafting (CABG)

surgery in the United States.1 Although the introduction of percutaneous coronary intervention

(PCI) has decreased the utilization of CABG in the past decade,1, 2 CABG remains the most

common cardiac surgery and is the standard of care for patients with either left main or severe 3-

vessel coronary artery disease. Following CABG, national guidelines strongly recommend

cardiac rehabilitation (CR) for all patients.3, 4

Although a survival advantage has been well demonstrated with CR in patients with

myocardial infarction (MI),5 and PCI,6, 7 surprisingly, only a small handful of studies have

previously examined the mortality impact of CR following CABG. These studies were either

small and not statistically significant,8, 9 involved only older patients,10 utilized billing data,10 or

did not account for participation bias.11 In addition, to our knowledge, no randomized controlled

trials have ever specifically tested CR following CABG. Lastly, based upon the results of one

recent controversial trial in patients with a recent MI,12 new doubts have arisen regarding the

effectiveness of CR in the era of modern medical therapy for coronary artery disease.

Consequently, the aim of this study was to determine the influence of CR participation on

all-cause mortality following CABG in a contemporary, community-based, mixed-age cohort

using detailed patient level data.

Methods

We utilized the database of the Division of Cardiovascular Surgery, Mayo Clinic, Rochester, MN

to identify consecutive residents of Olmsted County who underwent CABG from January 1996

to December 2007 and were discharged alive. We excluded patients who were non-Olmsted

previously examined the mortality impact of CR following CABG. These studiesess wwwere ee e eieieithththerere

mall and not statistically significant,8, 9 involved only older patients,10 utilized billing data,10 or

diid d nononottt acacccococouuunt fofoforrr pparticipation bias.11 In additiiionono ,, to our knowledede gee,, nonono randomized controlled

rriaallsls have everer ssspeeciciififif caaallllllyy ttetesststededd CCCR R fooollowwiwinng CCCAAABG.G.G LLLasststlyly,, bbabasesedd d uupupononn ttthehe rrresesesulululttsts ooofff oononeee

eecececentntnt cconontrtrtrovoovererssiaalal ttrririalall iinn papaatitiienenentststs wwiitith hh aa a rerrececeentntn MMMI,I,1112 nnnewewew dddououo btbtb sss hahah vveve aaririiseses n nn rereegagagardrdiiingg g ththeee

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county residents, underwent a combined procedure, lacked a valid research consent (per

Minnesota law), or were discharged to a long-term care facility. As Mayo Clinic is the only

center in Olmsted County performing CABG and also has the only CR program in the county,

this study closely approximates a community-based study.13 This study was approved by the

Mayo Clinic Institutional Review Board.

Standard definitions for risk factors and comorbidities were used according to the Society

for Thoracic Surgery database.14 The Charlson index was calculated from 16 clinical variables

known to be predictive of mortality.15 Renal failure was defined as a baseline creatinine 2.0

mg/dL, and renal complication as a creatinine 2.0 mg/dL with a doubling from baseline or need

for temporary or permanent dialysis. Arrhythmia was defined as the presence of, or prior

treatment for, atrial fibrillation, atrial flutter, ventricular fibrillation, ventricular tachycardia, or

3rd degree heart block. Neurologic complication was defined by a new stroke, transient ischemic

attack, or post-operative delirium with hallucinations. Functional status was a combination of

New York Heart Association class and Canadian Cardiovascular Society class, graded on a I to

IV scale. This database did not have CR referral information for the majority of patients, nor did

it have sufficiently available and reliable morbidity events (subsequent MI, PCI, or stroke) to

allow a proper analysis of these outcomes.

In addition, we obtained socioeconomic factors known to affect CR attendance from the

general medical record. Distance from home to CR was determined using an online web-based

mileage calculator. Insurance status was classified in four groups: Medicare, Medicaid,

commercial, or self-pay/uninsured. Medical “connectedness” was estimated by tabulating all

outpatient physician visits in the year prior to CABG. These factors were used as important

baseline socioeconomic variables in all analyses.

for temporary or permanent dialysis. Arrhythmia was defined as the presence of,f, or rr prprioioor rr

reatment for, atrial fibrillation, atrial flutter, ventricular fibrillation, ventricular tachycardia, or

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Patients were considered to have participated in CR if they attended at least 1 outpatient

session within 6 months of the index CABG surgery, as previously done.10 Attendance was

ascertained by use of the Mayo Clinic CR database. All non-participants’ medical records were

checked to assure they had not attended CR within 6 months following CABG surgery.

All patients attending CR underwent conventional exercise training and lifestyle

counseling according to American Association Cardiovascular and Pulmonary Rehabilitation

guidelines. Most patients underwent a baseline 6 minute walk as part of an exercise prescription.

Patients typically exercised for 30-45 minutes 3 times per week but were also encouraged to

exercise for 30 minutes per day on days when not attending CR. This program also included

evaluating and managing any active symptoms, arranging follow-up appointments and laboratory

testing, and managing risk factors such as hypertension, hyperlipidemia, and tobacco dependance

in coordination with the patient’s primary care physician

Following CABG surgery, all patients were encouraged to participate in a long-term,

nurse administered, disease-management program.16 Participating patients were more likely to be

CR participants (due to encouragement from CR staff), but this was not uniformly the case and

was not recorded. In this program, follow-up typically occurred at 6, 9, 12, 18 and 24 months

after surgery, and annually thereafter. Consequently, to evaluate the adherence patterns of our

patients regarding healthcare follow-up after CABG, we tabulated all outpatient physician visits

occurring between 6 and 24 months of follow-up. Similarly, we obtained low-density lipoprotein

(LDL) cholesterol levels taken between 6 and 18 months of follow-up, and considered any LDL

level <100 mg/dL controlled.

The primary outcome was the 10-year incidence of all-cause mortality, which was

ascertained using a two-stage approach. First, vital status was extracted from the Mayo

evaluating and managing any active symptoms, arranging follow-up appointmennttts aaandndd lllabababorororatatory

esting, and managing risk factors such as hypertension, hyperlipidemia, and tobacco dependance

nn cccoooooordrdrdinininatatatioioion wiwiwiththt the patient’s primary care ppphhyhyssician

Followwininngg CACAABGBGG sssurururgeggeryry, , aalall l papapattiennntss werrree enncococoururagagageded ttoo papartrttici ipipatatte e inin aaa lloonong-g-teeermrmm,,

nunursrsrse ee adada mimiinininiststererrededd, , didiiseseeasase-e-mmamanananagegegememeentntnt ppprorrogrgrgramamam.166 PPParrrtititiccicipapaatitit nngng pppatata iieenntntss wwewererer mmmoorore lllikkekelylyy too o beb

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registration database, in partnership with the Minnesota State Death Tapes. For anyone not

indicated as deceased according to Mayo records, death information was pulled from the

Accurint® system.17 Patients with no record of death from either source were ultimately

censored (indicated as alive) on October 25th, 2011, one month prior to the Accurint pull.

Statistical Methods

Cox proportional hazards (PH) regression analysis was used to test the association between CR

attendance and long-term mortality. An individual was considered a CR participant if they

attended at least one session within 6 months of surgery. We used a landmark approach such that

subjects who died or were lost to follow-up within 6 months were excluded. Conditioning on 6-

month survival allowed all patients in the analysis to have the same opportunity to attend CR,

and allowed testing of CR participation as a “baseline” factor in the Cox PH modeling.

To control for CR participation bias, propensity score methods18 were employed. Using

logistic regression, we fit a non-parsimonious multivariable model (including any significant 2-

way interactions) to assess the influence of all available baseline factors on the likelihood of

being a CR participant. The propensity score is a function of the predicted probability of CR

participation from this model. We controlled for the propensity score using three different

approaches: 1) regression adjustment treating the propensity score as a covariate, 2) stratification

by propensity score levels, and 3) caliper matching on propensity scores. All available variables

were included in the propensity model with the exceptions of postoperative MI, resuscitation,

shock, and postoperative angiogram. These factors were excluded due to low event rates,

concerns about model convergence, and missing data.

For the stratification approach, we examined the distribution of propensity scores from

both groups and “trimmed” the non-overlapping tail ends, reducing the sample to those within a

month survival allowed all patients in the analysis to have the same opportunity ttoto aaatttenenend d d CRCRCR,,

and allowed testing of CR participation as a “baseline” factor in the Cox PH modeling.

ToToTo cccoonntrrololol ffoor CR participation bias, propoppenennsity score metethohh dsds11818 wwere employed. Using

oogiiists ic regressssioioionn,, wweee fififitt aaa nonononn-n-papaarsrssimimmooniouusus muullttiivarririaabablelee mmmododdeell ((ininclcc uududininng gg anany yy sisisigngnifficicicanannt 222-

wawaayy y ininintetet raractctctioioionsns)) ttoto aassseesesss thhhe e inininflflflueuuencncce e ofofof aaallll aaavavaailllababblele bbbaasaselellininineee ffacacactotorrrs oon n ththt e ee lilikekekelllihohooododd oofff

being a CR pppararartitit ciciipapapantntt. ThThhe e e prprp opopopenene sisis tyyy ssscococorerere iiisss aaa fffunununctc ioioon n n ofofof ttthehehe pprereredddicicicteteted d d prprp obobobabababilillititity yy of CR



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common range of scores. The retained subjects were then divided into 5 equally-sized strata

using propensity score quintile values. The influence of CR participation on mortality was

assessed within each stratum using Kaplan-Meier methods and Cox PH regression modeling, as

well as in the combined group via stratified Cox PH regression. To assess the effectiveness of

the stratified propensity approach, CR participants were compared to non-participants within the

five strata for each significant factor in the overall propensity model. To test the effect of the

trimming, we also performed a sensitivity analysis including all patients.

For the propensity matching approach, CR participants were individually matched to non-

participants within the same caliper (width based on 0.10 of the standard deviation of propensity

score) and closest in terms of propensity score. This analysis included only individuals with a

suitable match and due to a relative shortage of non-participants in the overall cohort, the

majority of those unmatched (362 of 406, or 89%) were CR participants.

For secondary analyses, logistic regression was used to test for a linear trend in CR

participation rates over the study time period. The year of surgery was the independent variable

and a patient was considered to have attended CR if they attended for a single session anytime in

the subsequent 6 months. Poisson regression was used to test for a difference in the annualized

rate of outpatient physician follow-up visits between participants and non-participants. We also

tested for group difference in the proportions with an LDL level drawn and controlled at 1-year

follow-up using a Chi square test. A p value < 0.05 was considered statistically significant. All

analyses were carried out using the SAS statistical software package (Version 9.2, SAS Institute

Inc., Cary, NC).

Results

We identified 869 consecutive Olmsted county residents consent who underwent isolated CABG

core) and closest in terms of propensity score. This analysis included only indiviviiduduualallss wiwiwiththth aa

uitable match and due to a relative shortage of non-participants in f the overall cohort, the

mamajojojoririritytyty ooof f f thththossee e uununmatched (362 of 406, or 89%%)%) wwere CR partiicicic pantntntss.s.

For secocondndndarryy annnalalalysysysesess, , loloogigigists iic rregrrressssionnn wwasss uususeedd ttto o tteesstt fforor a linineaeaearr trtrenenend d d ininin CCCRRR

papartrtrticiccipipipatatioioon n n raratetees ovoveeer ttthehe stututudydydy tttimimime e pepeperiririododod. ThThhee yeyeeararr oooff f suuurgrgr eerery yy wawawas tththe e ininindeded pepepenndndenennt vavarririababblel

and a patient t wawawas s cococonsnssididderrededed ttoo hahahaveveve aattttttenenndededed d d CRCRCR iiiff ttheheey y y atatattetetendndndedede fffororor aaa sssinininglglg ee seseessssssioioion nn anytime innnfff



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during the study period. A total of 23 (2.6%) patients were excluded; 13 of whom died in the

first 6 months (only 3 attended CR,) 7 in which the vital status could not be verified, and 3 due to

unknown CR status. Consequently, a total of 846 subjects were used in all CR-related analyses.

Baseline characteristics, socioeconomic factors, operative, postoperative, and surgical

complications are reported in Table 1. During a mean follow-up of 9.0 ± 3.7 years, the 10-year

all-cause mortality rate was 28% (193 deaths). The unadjusted 10-year cumulative incidence of

all-cause mortality for the non-CR and CR groups were 45% (100 deaths) and 20% (93 deaths)

respectively, p < 0.001.

The majority of patients began CR within 1 month after hospital discharge (median [Q1,

Q3] time to start CR was 10 [5-17] days) and all patients started CR within 6 months. Median

time (Q1, Q3) from first to last CR session was 55 (42 to 69) days. Overall attendance during the

time frame was 69% (annual rates ranged from 55% to 76%) and the median number of CR

sessions (Q1, Q3) per patient was 14 (9 to 19.) There was no significant linear trend for change

in CR attendance over the study time frame by univariate analysis (p = 0.79). See Figure S1

(online supplement.)

Table 2 lists the baseline variables and their effects on CR participation from a

multivariable logistic regression model, from which the predicted probabilities were used to

derive propensity scores. Specifically, smoking, renal failure, lack of insurance, and having a

peri-operative neurologic complication were significantly associated with not attending CR

(p<0.05 for each).

Table 3 summarizes the differences across propensity quintiles for the prediction of

attendance at CR. As seen, none of these factors differed significantly between the two groups in

any of the five quintiles, suggesting adequate group balance to perform within-strata

Q3] time to start CR was 10 [5-17] days) and all patients started CR within 6 moonntnthshsh . MMMededediaiaian n

ime (Q1, Q3) from first to last CR session was 55 (42 to 69) days. Overall attendance during the

imememe fffrararamememe wwaas 66699%9% (annual rates ranged from 555555%%% to 76%) and d thtt e mememeddian number of CR

eessssioi ns (Q1, Q3Q3Q3) peper r papaatititienenenttt wwawass 14144 ((99 tto 119..)) TThheeere wawwass nonono ssigiggnniifificacaantnt llininneaeaar r trtrenene d d d fofofor r chcchaananggeg

nn CCCR R R atata tetendndndanancecee oooveverrr ththhe e sttududu y yy tititimemem fffraraamememe byyy uunnnivvavaririiatatteee aananalalalysysysisis (((p p p === 00.0.79799).).) SSSeeeee FiFFiguguureee SS111

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comparisons of survival or to estimate an overall stratified effect of CR on survival.

The associations between CR attendance and mortality are summarized in Table 4 based

on unadjusted, propensity-adjusted, propensity-stratified, and propensity-matched analyses.

Using the propensity score method of covariate adjustment, CR was associated with a 46%

reduction in hazard of 10-year mortality (HR=0.54; 95% CI, 0.40-0.74; p<0.001), conditional on

surviving the first 6 months. Both the stratified and matched propensity score methods produced

a nearly identical effect for CR attendance as reflected by a 45% reduction in hazard of mortality

(stratified: HR=0.55; 95% CI, 0.40-0.75; p<0.001; matched: HR=0.55; 95% CI, 0.36-0.84; p =

0.007.) Strata-specific effects of CR on long-term mortality are also reported in Table 4, and

illustrated in Figure 1, for each of the five propensity score quintiles. Based on a 10-year

adjusted mortality rate of 35.7% in non-participants and 23.0% in participants, the absolute risk

reduction was 12.7% and the number needed to treat to prevent one death over 10 years was 8.

Among those who attended CR, the number of sessions attended was not associated with long-

term mortality, after adjustment for age, gender and Charlson Index (p=0.41). When trimmed

patients (34 total, 4%) were included as part of the sensitivity analysis, results were nearly

identical (HR, 0.54; 95% CI, 0.40 – 0.74; p<.001).”

There was no significant differential effect of CR on mortality when tested by age ( or

<65), p = 0. 87; gender, p = 0.86; prior MI, p = 0.74; or diabetes, p = 0.61.

Compared to non-attendees, CR attendees were significantly more likely to have had an

LDL level drawn at around 1-year following CABG, (83% vs. 52%, p <0.001) and to have that

LDL <100 mg/dL (72% vs. 60%, p = 0.006). Furthermore, the annualized rate of total outpatient

clinic visits in the two years after CABG was higher on average among CR attendees, (rate = 7.8

visits per person per year; 95% CI, 7.6 to 7.9) than non-attendees (rate = 6.2 visits per person per

llustrated in Figure 1, for each of the five propensity score quintiles. Based on aa a 10100-yyyeaeaearr r

adjusted mortality rate of 35.7% in non-participants and 23.0% in participants, the absolute risk

eeduduuctctctioioionn wawaw sss 1222 7.7.7% % and the number needed to tttrerr aaat to prevent ononne dedeatatathh h over 10 years was 8.

AmAmAmono g those whwhwhoo atatteteendnddededed CCCR,RR, tthehehe nnumumumberr r oof seessssiionnsns aattttenenendededdd wwawas nonnott asasssosoociciatattededed wwiti h h h llolongngng-

eermrmm mmmorortataalililitytyty, , aafafteteer r aadadjujuuststmemeentntnt fffororor aagegee, gegegenndndererer aandndnd CCChahaarlrlrlssoson nn InInI dededexx x (p(pp=0=00.441)1)1). WhWhWhenenen trririmmmmmeeed

patients (34 ttotototalala , , 4%4%4%) ) ) weww rerere iiincncn lululudededed dd asasas pppararartt t ofofo tthehehe sssenene sisiititit viviv tytyty aaananan lyyysisisis,s,s rrresesesululu tstss wwwerereree e nenen arly fff



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year; 95% CI, 5.9 to 6.4; p<0.001).

Discussion

We found in our large contemporary, community-based, mixed age, post-CABG cohort that CR

participation was significantly associated with an approximate 45% reduction in all-cause

mortality. This finding was demonstrated using three different techniques to adjust for the

propensity to attend cardiac rehabilitation, and was not significantly different by sex, age /< 65

years, presence/absence of diabetes or prior MI. The number needed to treat with CR to prevent

one death following CABG at ten years was 8. These findings support national guidelines and

coverage policies that recommend CR participation after CABG.3, 4

Our study adds to the small number of published studies that have assessed the

relationship between CR participation and mortality following CABG. Suaya et al.10

demonstrated a 5-year, 28% relative risk reduction using a large Medicare claims database, but

this study was limited by lack of detailed patient information and an elderly cohort. Hansen et

al.11 demonstrated a 2-year, 87% relative reduction in mortality risk using patient level data, but

participation bias was not accounted for. Hedback et al.8 found a 54% reduction in 10-year all-

cause mortality following CABG but this did not meet statistical significance likely due to small

sample size, (n = 147, p = 0.06.)

To our knowledge, there are no randomized controlled trials that have specifically tested

CR in CABG, although these patients have generally been included in general post-MI trials.

Among these trials, meta-analyses have demonstrated a 20-25% reduction in all-cause mortality

seen in patients with either MI or PCI.19-21 Unfortunately, most randomized trials of CR are now

more than 20 years old.21 In addition, one recent controversial trial12 suggests that CR following

coverage policies that recommend CR participation after CABG.3, 4

Our study adds to the small number of published studies that have assessed the

eelalaatititionononshshshipipip bbbetweweweenen CR participation and mortalalaliityyy following CAAABGG. SSSuau ya et al.10

ddedemmomonstrated aa 555-yyyeaearrr, 2228%8%8% rreleelatatiiiveveve riiskkk redduducctioonn uusininngg g a a lalargrgee MMeMedididiccacarrere ccclalalaimims s dadadatatabababassese,, bububut

hhisisis sstututudydydy wwwaasas llimimmiititeded bby y y lalackckk ooofff dededettatailillededd pppaaatieeentntn iininffof rmrmrmatatatioioion n anana ddd ananan eellldeererlylyy ccohoho ororrt.t.. HHaananseses n n ett

al.111111 demonststrararatetet d d d a a a 2-2-yeyey arrr,,, 87878 %%% rerer lalalatiivevev rrredededucucuctitit ononon iiinnn mmmororortatatalilil tytyty rrrisi k k k usususinining g g papap tiiienenent t t leleevevev l data, but nn



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an MI, may not be effective in the era of modern medical therapy for coronary artery disease.

Furthermore, it appears unlikely that additional randomized trials of CR will be completed given

the problematic ethical considerations of withholding this guideline-endorsed therapy.

Consequently, carefully controlled cohort studies (such as this one) have an important role in

evaluating the modern effects of comprehensive cardiac rehabilitation.

When compared to the above studies, our results showed a smaller impact of CR on all-

cause mortality risk than was noted by Hansen et al.,11 similar to the results of Hedback et al.,8

larger than the results of the Suaya et al.,10 and larger than the meta-analyses of randomized

controlled trials performed in mixed coronary artery disease populations.19-21 Furthermore, our

findings are consistent with previously published cohort studies from Olmsted County,

Minnesota and Calgary, Alberta, Canada that found that CR participation was significantly

associated with a 40-50% reduction in mortality risk following MI,13 PCI,6 or a new diagnosis of

coronary artery disease.22

What, then, might explain our findings? Two possible explanations are worth

consideration. First, we contend that our findings reflect a true association between CR and

substantial reduced mortality risk, related to the direct effects of CR on the short- and long-term

delivery of effective secondary prevention therapies in CABG patients. Previously published

studies support this concept, showing that CR participation is associated with improvements in

coronary heart disease risk factor control20 as well as long-term follow-up and adherence to

secondary prevention medications.16, 23 We confirmed these concepts in our study by

demonstrating improved rates of LDL measurement, LDL control, and outpatient follow-up in

the first two years after CABG. We maintain that these results are a direct consequence of

participation in a comprehensive CR program and one of several possible explanations for why

findings are consistent with previously published cohort studies from Olmsted CCoouountntn yy,y,

Minnesota and Calgary, Alberta, Canada that found that CR participation was significantly

asssosoociciciatatatededed wwwiitith aa a 44040-50% reduction in mortality y y ririr sskk following MMMI,II 13 PPPCCICI,6 or a new diagnosis of

coorooonan ry arterry y didd ssseasasse.e 222222

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CR participants have improved outcomes. In addition, given that patients undergoing CABG

typically have more severe coronary artery disease and risk factors, they likely derive a greater

benefit from CR than patients with more limited coronary artery disease.

A second possible explanation for our findings is the presence of a “healthy cohort” bias,

such that CR participants are healthier and more motivated to maintain optimal health than are

those who do not participate in CR. Certainly, our data show that CR participants were generally

younger and healthier than those who did not participate in CR. To help address this concern, we

utilized multiple propensity score techniques. Though the final result remained statistically

significant, this adjustment substantially attenuated the effect of CR, likely reflecting the removal

of such bias. Furthermore, we also assessed the potential role for instrumental variable analysis

(i.e., adjusting for factors that are associated with “accessibility” of CR but that are not

necessarily related to mortality risk), which in similar studies has further reduced the point

estimate.10 We found, however, that the instrumental variables we could identify (driving

distance to CR and medical “connectedness”) did not differ significantly between those who

participated in CR and those who did not, likely due to the short distance (<10 miles) that most

patients needed to travel to attend CR. Consequently we were unable to perform the planned

instrumental analysis. Lastly, and most importantly, we found no differences in the key predictor

variables for CR attendance when comparing our propensity quintiles across study groups as

demonstrated in Table 3. In summary, even after adjusting for identifiable factors that were

associated with a possible “healthy cohort” bias and “accessibility” of CR, we found a persistent

significant association between CR participation and reduced all-cause mortality risk.

We did not find an association between the numbers of CR sessions attended and reduced

mortality in our cohort, which differs from recent findings suggesting an approximate 1%

of such bias. Furthermore, we also assessed the potential role for instrumental vaarirriababableee aanananalylylysisis

i.e., adjusting for factors that are associated with “accessibility” of CR but that are not

neecececesssssaararilililyy y rereelateteeddd tot mortality risk), which in simimimiillar studies hass ffurththhererer rreduced the point

estiimmam te.10 We e fofofouuund,d,d hhowowoweveveveerer, , ththhatatt tthhehe instttruuumennnttaal vvvararriaiabblb eeses wwwee cocoululu dd iddenenenttitifyfy (((drdrdrivivinini gg g

didistststananancecec ttoo CRCRCR aandndd mmeededicici ala “““coconnnnnneeecctctededdnenenessssss”)”) dddididd nnoot ddififffefeferr sisiigngngniififiicacacantnttlyyy bbetetetweweweenenn ttthhhossese wwwhohoo

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reduction in mortality for each session of CR attended.22, 24 However, we believe this is primarily

due to the fact that during the study period, Mayo Clinic CR individualized the recommended

number of CR sessions per patient depending on progress towards goals. Healthier patients were

allowed to graduate earlier, while more frail and sick patients were encouraged to complete 36

sessions. Therefore, a higher number of CR sessions attended may in part reflect poorer

underlying health.

Our CR participation rates were high (68%) and compare favorably to national

participation rates of 20-30%.10 This implies that, nationally, higher participation rates are

clearly achievable and that many more patients would attend CR if given the opportunity. In

addition, our participation rates compared favorably to previously reported rates from Olmsted

County, Minnesota during a similar time period in persons recuperating from MI or PCI (55%

and 40% respectively).6,13 This higher relative participation for patients undergoing CABG when

compared to MI or PCI is likely due to increased disease severity and the need for surgical

revascularization, and has previously been noted. 10 However, it remains unclear why 32% of

patients did not participate, and more importantly, if this participation rate could be improved

through additional quality improvement projects.

Limitations

Our study included data from only one county in Minnesota, and, therefore, may have limited

generalizability. Subgroup analyses (such as those for individual propensity strata) may have

been underpowered due to smaller sample sizes. Referral to CR was unknown and thus our

results may reflect some element of referral bias. Our database did not include a number of

behavioral factors and attitudes that might affect attendance at CR or adherence to other

recommended therapies. Our follow-up system with nurse case management may have

addition, our participation rates compared favorably to previously reported rates s frffromomo OOOlmlmlmstststeded

County, Minnesota during a similar time period in persons recuperating from MI or PCI (55%

annd d d 404040%%% rererespspspectitiivvevelyl ).6,13 This higher relative papaarrtiiccipation for papaatit enntststs uuundergoing CABG when

coommpmpared to MIMI orrr PCPCPCI isisis lllikikikelelely y dududueee totoo iinncreeeassed ddiiseaaasesee sseeevereritityy anand dd thtt eee neneeededed ffororr ssururu ggig cacacall

eevavavascsccululu ararizizizataatioionnn, aaandndd hhasasa prereeviviviouououslslsly y bbebeenenen nnnotttedede .. 100 HoHoowewewevvever,r, iiit t reremamamaininns ununclclc eaeaear r whwhwhy y 33232%% % ooof

patients did nnototot pppararartititiciciipapap teee, ,, ananand dd momom rerere iimpmpmpororortatatantntntlylyly,, ififf tthiiisss papapartrtrticiccipipipatatioioion n n rararatetete cccououuldldd bbbee e imimi proved



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favorably biased our results, but we note that the GOSPEL study tested a 3 year program of

intensive followup after CR and found no difference in either cardiovascular or all-cause

mortality.25 Our use of landmark analysis limits the generalizability of our results to patients that

survive the first 6-months following CABG. Lastly, because our data were observational in

nature, it is possible that our results may have been affected by bias in our population sample

(e.g., “healthy cohort” bias). Despite our best efforts to adjust for bias in our population, it is

possible that unidentified sources of potential bias still exist in our data. Our results, therefore,

may overestimate the true association between CR participation and mortality risk following

CABG. However, even if as much as half of our effect size was due to undetected residual bias,

there would still be a substantial and important protective association between CR attendance

and subsequent mortality following CABG.

Conclusions

We found in a community-based, mixed age cohort that CR participation after CABG was

associated with a significant reduction in long-term mortality. Our results support the recently

released clinical practice guidelines that strongly recommend CR for all patients following

CABG surgery.

Acknowledgments: We would like to thank Judy Lenoch and Laurie Barr, BS for assisting with

data collection and management.

Funding Sources: Funding for statistical analysis was provided by the Mayo Clinic’s

Department of Cardiovascular Disease. No other funding supported this work, including from

design and conduct of the study; collection, management, analysis, and interpretation of the data;

and preparation, review, or approval of the manuscript.

here would still be a substantial and important protective association between CCRRR atata teeendndndananancecec

and subsequent mortality following CABG.

CCConncnclusions

WeWeWe fffouououndnd iiin n n aa cocoommmmmuununiitity-y-babaaseseddd, mmmixixededed aaagegege cccohoho ooortt thhahat t CRCRCR ppparara ttiticiciipapapatitiiononn aaftftftererr CCABABABG G wawaass

associated wwititth h h a a sisis gngngnififificii ananntt rerr duduductctc ioioion ininin lllononong-g-g tetet rmrmrm mmmororrtatatalililitytyty.. OuOuOur rereresususultltltss s sususupppppororort t t thththee e recently



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Conflict of Interest Disclosures: None.

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24. Hammill BG, Curtis LH, Schulman KA, Whellan DJ. Relationship between cardiac rehabilitation and long-term risks of death and myocardial infarction among elderly medicare beneficiaries. Circulation. 2010;121:63-70. 25. Giannuzzi P, Temporelli PL, Marchioli R, Maggioni AP, Balestroni G, Ceci V, Chieffo C, Gattone M, Griffo R, Schweiger C, Tavazzi L, Urbinati S, Valagussa F, Vanuzzo D. Global secondary prevention strategies to limit event recurrence after myocardial infarction: Results of the gospel study, a multicenter, randomized controlled trial from the italian cardiac rehabilitation network. Arch Intern Med. 2008;168:2194-2204.



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Table 1. Baseline Characteristics

Patient and Clinical Characteristics No CR (n=264) CR (n=582) p-valueAge (yrs.) 68.3±11.0 64.4±10.3 <0.001 Male Gender 192 (73%) 456 (78%) 0.07 Caucasian Race 245 / 254 (96%) 550 (95%) 0.46 Surgery Year^ 2001 (1997, 2004) 2001 (1998, 2004) 0.71 Any Prior Cardiac Operations 9 / 180 (5%) 5 / 415 (1%) 0.005 Total # of Diseased Coronary Arteries 0.08

0 0 (0%) 1 (<1%) 1 13 (5%) 24 (4%) 2 37 (14%) 119 (20%) 3 214 (81%) 438 (75%)

Left Main Disease >50% 82 (31%) 179 (31%) 0.94 Charlson Index (ordinal categories) <0.001

0 42 (16%) 132 (23%) 1-2 93 (35%) 235 (40%) 3-4 64 (24%) 124 (21%)

5 65 (25%) 91 (16%) Ejection Fraction (%) 53.3±13.5 56.0±13.3 0.010 Functional Status Classification 0.11

1 11 (4%) 25 (4%) 2 25 (9%) 95 (16%) 3 116 (44%) 233 (40%) 4 112 (42%) 229 (39%)

Preoperative Risk Factors Body Mass Index (BMI) kg/m2 29.4±5.6 29.5±5.2 0.74 BMI categories 0.67

<25 51 (19%) 108 (19%) 25 - <30 109 (41%) 229 (39%) 30 - <35 62 (23%) 160 (27%)

35 42 (16%) 85 (15%) Family History of Coronary Artery Disease 110 / 258 (43%) 264 / 564 (47%) 0.26 Diabetes 95 (36%) 157 (27%) 0.008 Hypercholesterolemia 223 (85%) 516 (89%) 0.10 Smoking 0.13

Never 78 (30%) 200 (34%) Current 50 (19%) 82 (14%) Past 136 (52%) 300 (52%)

Renal Failure 19 (7%) 16 (3%) 0.003 Hypertension 203 (77%) 417 (72%) 0.11 Peripheral Arterial Disease 62 (23%) 71 (12%) <0.001 Cerebrovascular Disease 47 (18%) 81 (14%) 0.14 Prior Cardiovascular Intervention 100 (38%) 194 (33%) 0.20 Prior Myocardial Infarction 137 (52%) 257 (44%) 0.037 Prior Congestive Heart Failure 33 (13%) 29 (5%) <0.001 Angina 232 (88%) 528 (91%) 0.20

3-4 64 (24%) 124 (21%)5 65 (25%) 91 (16%)

Ejection Fraction (%) 53.3±13.5 56.0±13.3 000.01001000 Functional Status Classification 0.11

1 11 (4%) 25 ((4%)222 2225 (9%) 95955 (((116%) 3 11116 (44%%%)) ) 232333 (4(4( 0%%)))4 1112 (42%2%2%) ) 22222999 (((39%9%%)))

PPrPreooopep rativee RRiskkk FFFaccttoorrsBoBoodydydy MMMasassss InInIndedexxx (B(BBMMIMI) ) kgkg/mmm2 2299.4.44±5±55.666 29299.555±5±5.2.2.2 0.0.74744 BMMI I cacatetegogorriess 0.0.6767

<25 51515 ((19191 %)%)%) 10100888 (1(1(19%9%9%)))2525 - <<3030 101099 (4(41%1%)) 222299 (3(39%9%))



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Cardiogenic Shock 6 (2%) 12 (2%) 0.84 Resuscitation 0 (0%) 2 (<1%) 0.34 Arrhythmia 49 (19%) 71 (12%) 0.014 Preoperative Beta Blocker Use 209 (79%) 491 (84%) 0.06 Social Factors Type of insurance: <0.001 . Medicare 160 (61%) 275 (47%) . Medicaid 13 (5%) 24 (4%) . Commercial/Mayo 76 (29%) 279 (48%) . Self-Pay/Uninsured 15 (6%) 4 (1%) Distance to CR facility (miles) ^ 3.3 (1.8, 9.9) 3.6 (2.3, 7.1) 0.60 Distance to CR facility >10 miles 65 (25%) 118 (20%) 0.15 # Visits in 1-year prior to CABG ^ 4 (1, 8) 5 (2, 8) 0.035 Operative Characteristics Intraaortic Balloon Pump Used 26 (10%) 26 (4%) 0.003 Cross Clamp Time (minutes) 45.6±21.3 48.7±20.5 0.048 Elective Status 179 (68%) 416 (71%) 0.28 Internal Mammary Artery Used as Graft 245 (93%) 561 (96%) 0.023 Post-Operative Complications Length of hospitalization stay 1 week 165 (63%) 270 (46%) <0.001 Post-operative Angiogram 1 / 211 (0%) 11 / 487 (2%) 0.10 Reoperation for Bleeding 10 (4%) 17 (3%) 0.51 Myocardial Infarction 0 (0%) 2 (<1%) 0.34 Neurologic Complication 32 (12%) 28 (5%) <0.001 Renal Complication 10 (4%) 11 (2%) 0.10 ^ median (Q1, Q3); p-value from Wilcoxon Rank Sum Test N (%) reported for all categorical variables; for those with any missing data, the denominator of subjects with observed data is reported and used to compute the percentage CR = Cardiac Rehabilitation, CABG = Coronary Artery Bypass Grafting Surgery, BMI = Body Mass Index

Post-Operative ComplicationsLength of hospitalization stay 1 week 165 (63%) 270 (46%) <0<0<0.0.0001010 Post-operative Angiogram 1 / 211 (0%) 11 / 487 (2%) 00.1010 Reoperation for Bleeding 10 (4%) 17 (3%) 0.51 Myyoccardial IInfn arrctctioion 0 (0( %) 2 (<(<( 1%) 0.34 NeNeurururolololoogogicicic CCCoomomplplpliicicata ion 33232 ((12%) 28288 (((5%5 ) <0.001 ReReenanaal l CoC mpplililicacatitiononon 110 (4%%))) 1111 (((2%2%)) 0.0.101010 ^̂ meeedid an (Q1, Q3Q3);)); p--valalluueue fffrororom mm WiWiWilclcoxoxxonnn RRanankk Suuum m Testtt N N N (%%%)) reported fof r aaall cateegogorricaal l vavaariabblel s;s; fooor tthoseee wwwith aananyy mimissssssininingg g daaata, ttheee denooommminaaatoorr ofo suububjeectctss wwwith obobbsess rvrvvedd data a a isisis rrepepororteted d aaanddd usu ededd tooo cocompmpmpututeee thhhe e pepeerccenentatagege CRCR === CCCarara dididiacacac RRehehhabababilililitititatattioioionn,n, CCCABABGGG = CoCoCororonanaaryryry AAArtrtrterereryy y ByByBypapapasssss GGGrararaftftftininingg g SuSSurgrggerereryy,y, BBBMIMIMI === BBBodododyy y MaMaMasss IIIndndndexexex



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Table 2. Propensity Factors for Attendance at Cardiac Rehabilitation Patient and Clinical Characteristics Multivariable Result Age (per 10 years)† Hospitalization 1 week 0.96 (0.69, 1.33) [0.786]

>1 week 0.58 (0.43, 0.77) [<.001] Male Gender 1.20 (0.79, 1.81) [0.396] Surgery Year 0.94 (0.88, 1.01) [0.094] Caucasian Race 1.02 (0.43, 2.42) [0.966] Any Prior Cardiac Operations 0.31 (0.09, 1.11) [0.072] Total # of Diseased Coronary Arteries 0.90 (0.65, 1.27) [0.559] Left main disease >50% 1.14 (0.79, 1.66) [0.485] Charlson Index (categorized) 0.85 (0.69, 1.05) [0.123] Ejection Fraction 1.00 (0.99, 1.02) [0.531] Functional Status Classification 0.95 (0.72, 1.24) [0.683] Preoperative Risk Factors BMI categories F test p=0.473

<25 1.0 (reference) 25 - <30 0.86 (0.54, 1.38) [0.541] 30 - <35 1.12 (0.67, 1.89) [0.660]

35 0.77 (0.43, 1.37) [0.371] Family History of Coronary Artery Disease 1.14 (0.77, 1.69) [0.500] Hypercholesterolemia 1.19 (0.72, 1.97) [0.499] Smoking F test p=0.021

Never 1.0 (reference) Current 0.46 (0.27, 0.80) [0.006] Past 0.82 (0.56, 1.22) [0.328]

Renal Failure 0.43 (0.18, 0.99) [0.046] Hypertension 0.96 (0.64, 1.44) [0.844] Peripheral Arterial Disease 0.64 (0.41, 1.01) [0.054] Cerebrovascular Disease 1.20 (0.74, 1.93) [0.460] Prior Cardiovascular Intervention 0.92 (0.63, 1.35) [0.678] Prior Myocardial Infarction 1.24 (0.84, 1.82) [0.284] Congestive Heart Failure 0.75 (0.40, 1.41) [0.370] Angina 1.13 (0.61, 2.12) [0.692] Arrhythmia 0.73 (0.46, 1.17) [0.196] Preoperative Beta Blocker Used 1.39 (0.90, 2.14) [0.137] Operative Characteristics Intraaortic Balloon Pump Used 0.64 (0.32, 1.28) [0.205] Cross Clamp Time (min) 1.01 (1.00, 1.01) [0.223] Elective Status 0.83 (0.52, 1.32) [0.428] Internal Mammary artery used as graft 1.64 (0.78, 3.47) [0.193] Post-Operative Complications Reoperation for Bleeding 0.84 (0.33, 2.08) [0.700] Neurologic Complication 0.52 (0.27, 0.98) [0.042] Renal Complication 1.06 (0.38, 2.97) [0.916] Social Factors Insurance: F test p=0.017

Medicare 1.0 (ref) Medicaid 0.97 (0.40, 2.34) [0.942] Commercial/Mayo 1.14 (0.68, 1.91) [0.611] Self-pay/Uninsured 0.15 (0.04, 0.53) [0.003]

Distance of CR center >10 miles 0.92 (0.61, 1.38) [0.677] #Visits in prior 1-year‡ No diabetes 1.28 (0.98, 1.68) [0.071]

Diabetes 2.14 (1.47, 3.12) [<.001] Results reported from logistic regression include: OR (95% CI) [p-value] † A significant interaction was detected between age and length of hospital stay; younger age was predictive of CR attendance among those hospitalized 1 week, but not in subjects whose hospital stay was >1 week. ‡ To satisfy regression assumptions, a log-transformation was applied to the total number of visits in the 1 year prior to CABG; a significant interaction was detected between # visits and diabetes, such that a higher [log-transformed] # visits was associated with non-attendance, though more so in diabetic subjects. CR = Cardiac Rehabilitation, CABG = Coronary Artery Bypass Grafting Surgery, BMI = Body Mass Index

moking F teststt ppp=0=0= .0.00212121Never 1.0 (reference) Current 0.46 (0.27, 0.80) [0.006] Past 0.82 (0.56, 1.22) [0.328]

nal Failure 0.43 (0.18, 0.99) [0.046] ypertrtenenensisisiononon 0.96 (0.64, 1.44444))) [0[0[ .844] ririphphpherereralal Artrtererriaiaial DiDiseseasase 0.64 (0.44141, 1.0101) ) [0[0.054]rrerebrrroovascular r DDDisisseaeaeasses 1.1.1.202020 ((0.0.0.74744,,, 1.1.1 939393))) [0[0.4460600]]]oor CCaCardiovascullarar IIInttterrveventntiioion n 0.0.9222 ((0.0.633, 1.1 35355) [[0.666787878]]ooor MMMyocardialal IInfaararccttion 1.1.1.2444 (0..844, 1.8222) [0[0.2228444] ngnggesestititiveve HHeaeaartrtrt FFaiaillulurrere 0.0.0.7555 (((0.0.4040,, 1.1.1 41411) [0[0.3.33707070]]]

ngiinana 11.1.131313 ((0.616161,, 22.2.121212))) [0[0[0.6692922]]]rhrhrhytytythmhmhmiaiaia 000.737373 (((000.464646, 111.171717))) [0[0[0 11.1969696]]]eoperative Betetta a a BlBlBlococockekeker rr UsUsU edede 1.1.1 393939 (((0.0.0 9099 ,, 2.2.2 141414) ) ) [0[0[0.1.113737]]]per tatiive ChCharactte iri tstiics



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Table 3. Comparison of Patient and Clinical Predictors of Attendance at Cardiac Rehabilitation by Propensity Matched Quintiles Patient and Clinical Characteristics

Propensity Quintile

Variable Subgroup No CR CR P-value

Age (years) 1 - 71.7±10.2 70.7±10.9 0.55 2 - 68.7±9.4 69.3±8.4 0.68

3 - 66.4±11.1 66.5±9.6 0.96 4 - 61.1±11.3 64.1±8.7 0.14 5 - 61.0±12.0 59.5±9.4 0.53 Smoking Status 1 Never 28 (27%) 15 (25%) 0.82 Current 21 (21%) 15 (25%) Past 53 (52%) 31 (51%) 2 Never 22 (31%) 21 (23%) 0.19 Current 17 (24%) 17 (18%) Past 31 (44%) 54 (59%)

3 Never 14 (31%) 35 (30%) 0.79 Current 6 (13%) 21 (18%) Past 25 (56%) 62 (53%)

4 Never 5 (21%) 44 (32%) 0.24 Current 5 (21%) 14 (10%) Past 14 (58%) 80 (58%)

5 Never 8 (40%) 67 (47%) 0.24* Current 0 (0%) 14 (10%) Past 12 (60%) 61 (43%) Diabetes 1 - 42 (41%) 27 (44%) 0.70 2 - 28 (40%) 32 (35%) 0.50 3 - 16 (36%) 35 (30%) 0.47 4 - 3 (13%) 29 (21%) 0.33 5 - 4 (20%) 32 (23%) 0.80 PVD 1 - 35 (34%) 25 (41%) 0.39 2 - 17 (24%) 18 (20%) 0.47 3 - 9 (20%) 16 (14%) 0.31 4 - 1 (4%) 7 (5%) 1.00* 5 - 0 (0%) 4 (3%) 1.00* Hospital stay >1 week 1 - 82 (80%) 49 (80%) 0.99 2 - 46 (66%) 62 (67%) 0.82 3 - 20 (44%) 50 (42%) 0.81 4 - 7 (29%) 39 (28%) 0.93 5 - 7 (35%) 48 (34%) 0.92 Renal Failure 1 - 13 (13%) 8 (13%) 0.95 2 - 4 (6%) 4 (4%) 0.69 3 - 2 (4%) 0 (0%) 0.07* 4 - 0 (0%) 3 (2%) 1.00* 5 - 0 (0%) 1 (1%) 1.00* #Visits in 1-year prior^ 1 - 3.0 (1.0, 7.0) 4.0 (1.0, 7.0) 0.31 2 - 5.0 (2.0, 9.0) 4.0 (1.0, 8.0) 0.63 3 - 6.0 (2.0, 9.0) 5.0 (2.0, 9.0) 0.72 4 - 2.0 (1.0, 5.5) 4.0 (2.0, 7.0) 0.08 5 - 6.5 (2.5, 15.5) 5.0 (3.0, 9.0) 0.44 Neurologic complication 1 - 21 (21%) 15 (25%) 0.55 2 - 8 (11%) 6 (7%) 0.27 3 - 1 (2%) 4 (3%) 1.00* 4 - 1 (4%) 1 (1%) 0.28* 5 - 0 (0%) 1 (1%) 1.00*

Current 5 (21%) 14 (10%) Past 14 (58%) 80 (58%)%)

5 Never 8 (40%) 67 (47%%)) 0.0.0 242424**Current 0 (0%) 14 (10%)

Past 12 (60%) 61 (43%) Diabbeteteses 1 - 42 (41%) 27 (44%) 0.70

2 - 28 (40%) 332 (35%) 0.50 3 3 - 16166 (((363 %)%)%) 35 (3(30%0%%))) 0.0.47477 444 -- 33 ((1( 33%3%) ) 29 (((212121%)%) 000 33.33335 -- 444 (((2000%) 322 (223%) 0.8000

PVPVVDD 11 -- 3535 ((344%)%) 225 5 (4(41%1%)) 0.0 39399 2 2 - 171717 (((24244%)%%) 1118 8 (2(2(20%0%0%))) 0.0.0 474747 3 3 - 99 (2(20%0%) ) 1616 ((144%)%) 00.33114 4 4 -- 111 (4(4(4%)%)%) 777 ((5%5%%))) 1.00*55 - 0 0 (0(0%)%) 44 ((3%3%)) 11.0000*



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Type of insurance 1 Medicare 74 (73%) 44 (72%) 0.48 Medicaid 6 (6%) 3 (5%) Commercial 10 (10%) 10 (16%)

Self-Pay 12 (12%) 4 (7%) 2 Medicare 46 (66%) 63 (68%) 0.83 Medicaid 3 (4%) 5 (5%) Commercial 21 (30%) 24 (26%) 3 Medicare 25 (56%) 71 (60%) 0.82 Medicaid 2 (4%) 6 (5%) Commercial 18 (40%) 41 (35%) 4 Medicare 9 (38%) 64 (46%) 0.70* Medicaid 0 (0%) 3 (2%) Commercial 15 (63%) 71 (51%) 5 Medicare 6 (30%) 31 (22%) 0.22* Medicaid 2 (10%) 6 (4%) Commercial 12 (60%) 105 (74%) ^ median (Q1, Q3); Wilcoxon Rank Sum Test * p-value obtained from Fisher’s Exact Test due to low cell counts CR = Cardiac Rehabilitation



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Table 4. Effect of Cardiac Rehabilitation on All-Cause Mortality, by Propensity Approach

Propensity Method (NCR+ / NCR-) N (#Deaths) 10-year Cumulative Incidence of Death (%)^ CR Participation Effect* CR participants Non-participants HR (95% CI) [p-value]

Unadjusted Overall (582 / 264) 846 (193) 20.3% 44.6% 0.36 (0.27-0.47) [<.001] Adjustment Overall (582 / 264) 846 (193) 23.0% 35.7% 0.54 (0.40-0.74) [<.001] Stratification Overall (551 / 261) 812 (192) 23.9% 36.5% 0.55 (0.40-0.75) [<.001] Quintile 1 (61/102) 163 (70) 40.9% 54.6% 0.66 (0.40-1.10) [0.113] Quintile 2 (92/70) 162 (47) 31.3% 38.9% 0.76 (0.43-1.35) [0.348] Quintile 3 (118/45) 163 (36) 17.4% 51.1% 0.27 (0.14-0.52) [<.001] Quintile 4 (138/24) 162 (25) 18.2% 30.9% 0.54 (0.22-1.36) [0.191] Quintile 5 (142/20) 162 (14) 10.5% 19.9% 0.50 (0.14-1.79) [0.288] Matching Overall (220 / 220) 440 (130) 26.9% 42.7% 0.55 (0.36-0.84) [0.007] ^Cumulative incidence rates obtained from Kaplan-Meier method; rates in the overall group for all three propensity methods reflect adjustment for the propensity score *Effect of CR participation on 10-year mortality was assessed via Cox PH regression conditional on 6-month surviva CR = Cardiac Rehabilitation. + = attended CR. - = did not attend CR.

ification erall (551 / 261) 812 (192) 23.9% 36.5% 0.55555 (((0.0 04040 0-0-0.7.7.75)5) [<.uintile 1 (61/102) 163 (70) 40.9% 54.6% 00.666666 ((00.404040 1-11 1.110)0) [[[00.uintile 2 (92/70) 162 (47) 31.3% 38.9% 0.76 (0.43-1.35) [0.uintile 3 (118/45) 163 (36) 17.4% 51.1% 0.27 (0.14-0.52) [<.uiintntilililee e 4 44 (1(1(1383 /24) 162 (25) 18181 22.2% 300 9.9.9% % % 0.54 (0.22-1.36) [0.uiuintnn ilillee 5 5 (1(14242/2/ 0)0) 16162 2 (1(14)4) 0010 55.5% 919.9.9% % 0.0.505 ((0.0.1414-11.779)9) [0.2hihh gngn

eerar llll (2(( 2022 / 22 0020) 444 0 (1(13030) ) 6626 99.9% 42 77.7% % 0.00 555 ((0.00 6363 -0 88.8 )4) [0.ululataa vive e e incidence raaratetetes bobta nii ed ffror m mm Kaplplanaa MM-Meie er mmmetete hohod;d rrrata es iin n hhthe overee ala l l grrouoo pp fofor r alaa l thtt ree propoo ensi ytyt mmmett ohohods rrefefllect adada ujujustmemm tntn for ttheh prop

t off CCR R papa trtrtiicicipipata ion n onn 110-0-yeyearar mortatalility wwasas aassssese ssed via CCCoxox PPHHH reregrgresessision cconondiditititiononalal oon n 6-6 montnth h h usurvrviviva CCCararardididiacacac RRRehehehabababilililitititatatatioioionn.n. ++ = atatattetetendndndededed CCCRR.R. -- = didididdd nononottt atatattetetendndnd CCCRR.R.



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Figure Legend:

Figure 1. Association between Cardiac Rehabilitation and Survival in CABG Patients.



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Kaplan Meier survival plots by propensity score quintile and for strata-combined group, comparing rates over time between patients attending and not attending cardiac rehabilitation



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Lopez-Jimenez, Zixin Zhang and Randal J. ThomasQuinn R. Pack, Kashish Goel, Brian D. Lahr, Kevin L. Greason, Ray W. Squires, Francisco

Surgery: A Community Based StudyParticipation in Cardiac Rehabilitation and Survival Following Coronary Artery Bypass Graft

Print ISSN: 0009-7322. Online ISSN: 1524-4539 Copyright © 2013 American Heart Association, Inc. All rights reserved.

is published by the American Heart Association, 7272 Greenville Avenue, Dallas, TX 75231Circulation published online July 8, 2013;Circulation.

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Supplemental Material

Participation in Cardiac Rehabilitation and Survival Following Coronary Artery Bypass

Graft Surgery: A Community Based Study

[Intended for online publication]

Authors:

Quinn R. Pack, MD; Kashish Goel, MD; Brian D. Lahr, MS; Kevin L. Greason, MD; Ray

W. Squires, PhD; Francisco Lopez-Jimenez, MD, MS; Zixin Zhang, MD; Randal

J.Thomas, MD, MS

Figure S1. Time Trends in Cardiac Rehabilitation Participation among patients with Coronary

Artery Bypass Graft Surgery in Olmsted County, MN.

As seen, participation in CR remained consistently high for the duration of the study with only

minimal year to year variability.

Participation in Cardiac Rehabilitation and Survival Following ...

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