Michael T. Koller, Manfred D. Seeberger and Miodrag Filipovic

Transcrição

Troponin T and Brain Natriuretic Peptide after On-Pump Cardiac Surgery: Prognostic Impact
on 12-Month Mortality and Major Cardiac Events After Adjustment for Postoperative
Complications
Giovanna A. L. Lurati Buse, Daniel Bolliger, Esther Seeberger, Jorge Kasper, Martin Grapow,
Michael T. Koller, Manfred D. Seeberger and Miodrag Filipovic
Circulation. published online August 6, 2014;
Circulation is published by the American Heart Association, 7272 Greenville Avenue, Dallas, TX 75231
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DOI: 10.1161/CIRCULATIONAHA.113.007253
Troponin T and Brain Natriuretic Peptide after On-Pump Cardiac Surgery:
Prognostic Impact on 12-Month Mortality and Major Cardiac Events After
Adjustment for Postoperative Complications
Running title: Lurati Buse et al.; Biomarkers and Outcome after Cardiac Surgery
Giovanna A.L. Lurati Buse, MD, MSc1; Daniel Bolliger, MD1; Esther Seeberger, RN1;
Jorge Kasper, MD1; Martin Grapow, MD2; Michael T. Koller, MD3;
Manfred D. Seeberger, MD1; Miodrag Filipovic, MD1,4
1
Dept for Anesthesia, Surgical Intensive Care, Prehospital Emergency Medicine and Pain
Therapy,
Th
her
erap
apy,
ap
y, U
University
n veersit
ni
i y Hospital of Basel, Basel, Sw
Swi
Switzerland;
itzerland; 2Ca
Cardiac
ard
rdiacc Su
Surgery
urgery Dept, University
Hospital
Hosspital
sp
off Ba
B
Basel,
sell,
se
l, Basel,
Bas
asel
el,, Switzerland;
el
Swit
Sw
ittze
zerl
rlan
rl
a d; 3Ba
an
Basel
Base
sell In
se
Inst
Institute
tittutee fo
forr Cl
Clin
Clinical
nic
icall E
Epidemiology
pide
pi
demi
de
miol
olog
ol
ogyy & Bi
og
Bios
Biostatistics,
osta
os
tati
ta
tist
ti
stic
st
i s
U
Un
University
iversiity of
of Basel,
Bassel,, Basel,
Baasel, Switzerland;
Swit
Sw
itze
zeerllandd; 4Ane
Anesthesiology
esthessio
est
iolo
logy
lo
gy
y Dep
Dept,
ept, Kan
Kantonsspital
anttonnssspital
an
sp l S
St.
t. G
Gallen,
allenn,
St.
Stt. Ga
Gall
Gallen,
l en
ll
en, Sw
Swit
Switzerland
itze
it
zerl
ze
rllan
andd
Address for Correspondence:
Giovanna A.L. Lurati Buse, MD, MSc
Anesthesiology
University Hospital Basel
CH-4031 Basel
Switzerland
Tel: +41-61-328-6427
Fax: +41-61-265-7320
E-mail: [email protected]
Journal Subject Codes: Cardiovascular (CV) surgery:[36] CV surgery: coronary artery disease,
Cardiovascular (CV) surgery:[35] CV surgery: aortic and vascular disease
1
Abstract
Background—The independent predictive value of troponin T (TNT) after on-pump cardiac
surgery was established in several studies. However, adjustment was limited to preoperative risk
factors without considering perioperative complications. Data on the prognostic value of
postoperative B-type natriuretic peptide (BNP) are scarce. Our aim was to assess independent
value of TNT and BNP to predict 12-month outcome after cardiac surgery after adjustment
considering preoperative risk estimates and postoperative complications and to report risk
stratification gains when considering the EuroSCORE combined with postoperative biomarkers.
Methods and Results—This prospective cohort study includedd consecutive patients
patie
iennts
nts undergoing
unnde
derg
rgoi
rg
oing
ng
on-pump cardiac surgery between 2007 and 2010. We evaluated postoperative TNT and BNP,
the
he EuroSCORE,
EurroSC
Eu
roSC
SCOR
O E, and
and
n postoperative complications
complicatio
ons
n as
as predictors off adverse
adv
dvver
ersse events using Cox
regression.
egrres
e sion. The
Th
he primary
prim
prim
imaary endpoint
en
ndp
dpoi
oint
nt was
wa death
deeathh or
or major
maajoor adverse
adver
dverrsee cardiac
cardiac
diac events
eveent
ntss (MACE)
(MAC
(MAC
ACE)
E) within
wit
ithi
hinn 1
hi
year
ye
ar after
aft
f er surgery.
sur
urge
gerry.
ry Wee calculated
cal
alcu
cula
late
la
teed the
the net
net reclassification
recclas
re
assi
as
s fic
si
ficatiion index
ind
ndex
ex (NRI)
(NR
NRI)
I ooff TN
I)
TNT
T an
aand
d BNP
BNP in
n
event.
addition to the
th
he EuroSCORE.
Euro
Eu
roSC
ro
SCOR
SC
ORE.
OR
E We
E.
We enrolled
enro
en
r llled 1559
ro
155
5599 patients;
p ti
pa
t ent
n s; of
of whom
whom 176
176 (11.3%)
(11
11.3
.3%)
.3
%) ssuffered
uffe
uf
fere
fe
r d an even
nt
The adjusted hazard ratio (HR) of TNT >0.8 ȝg/L was 2.13 (95% CI, 1.47-3.15), of BNP >790
ng/L 2.44 (95% CI, 1.65-3.62). The NRI of the addition of TNT and BNP to the EuroSCORE
was 0.276 (95% CI, 0.195-0.348).
Conclusions—Postoperative TNT and BNP are strong predictors of 1-year events after on-pump
cardiac surgery independent of preoperative risk factors and postoperative complications.
Updating the preoperative EuroSCORE risk with postoperative TNT and BNP after surgery
allows for improved prediction of 1-year death or MACE.
Key words: prognosis, mortality, troponin, brain natriuretic peptide, surgery
2
Introduction
Surgical risk stratification models,1 including the EuroSCORE,2, 3 exclusively consider pre- and
intraoperative risk factors. Although useful for healthcare planning and for preoperative riskbenefit assessments, this view may prove fragmentary postoperatively, as it disregards
perioperative myocardial ischemic events4, 5 or postoperative complications6-8 despite their
association with mortality. Therefore, there is a need for tools that allow for early postoperative
risk re-assessment to guide management decisions (eg, transfer to step-down units and postdischarge follow-up schedules).
Troponin T (TNT) has an established prognostic value for short-term9-11 and mid-term
outcome12-14 after cardiac surgery. However, previous studies on the predictive vvalue
alu
ue of
troponin
roponin9-11 have focused on preoperative risk factors and have not accounted for postoperative
co
omp
mpli
liccati
li
cati
tion
o s (e
on
eg,
g, iinfections,
nfections, acute kidney failu
ure
r ). Inhospital co
omp
m liica
cattions,
ti
however, may
complications
(eg,
failure).
complications,
exert
ex
xert
errt a relevant
nt prognostic
proogn
gnos
osti
ticc change
ti
ch
hange
angee by
by being
beeing associated
asssocciaated
d with
wit
ithh both
both
h eelevated
leva
le
vaate
tedd ca
cardiac
ard
rdia
iacc bi
biom
biomarkers
om
marrker
kers
postoperatively
post
po
stop
st
oper
op
e at
er
ativ
ivel
iv
elyy an
andd m
mid-term
idd-te
d-term
m ooutcome.
utco
ut
come
co
mee.
Several
Severa
raal studies
s ud
st
udie
i s have
ie
h ve described
ha
desscr
criibe
bed the
the as
asso
association
soci
so
c at
ci
atio
ionn be
io
between
etw
twee
eenn pr
ee
preoperative
preop
oper
op
erat
er
ativ
at
ivee na
iv
natriuretic
atr
triu
iure
iu
reti
re
t c peptides
ti
and outcomes after cardiac surgery.15, 16 Evidence supporting the prognostic value of
postoperative concentrations, in contrast, is scarce17-22 and has been generated mostly in small
studies17, 21, 22 underpowered for multiple adjustment.
Moreover, the prognostic gain of a risk stratification based on the EuroSCORE alone vs. a
risk re-stratification based the EuroSCORE with the addition of early postoperative cardiac
biomarker concentrations (reclassification) is insufficiently known.
The aim of this cohort study was first, to test the hypothesis that postoperative TNT and
BNP concentrations are predictive of 1-year outcome in adults undergoing on-pump cardiac
3
surgery independent of preoperative risk factors and postoperative complications, and second, to
estimate reclassification of extended models that include postoperative TNT and BNP
information in addition to the EuroSCORE,2, 3, 23 an established and clinically widely used
preoperative risk stratification tool.
Patients and Methods
Study Design and Participants
We conducted a single-center prospective cohort of consecutive adult patients who underwent
on-pump cardiac surgery (ie, including isolated CABG, single and multiple valvular procedures,
and combined CABG and valvularr surgery) at the University Hospital of Basel, Switzerland
Swi
witz
tzer
erla
land
la
nd
between January 2007 and January 2010. Patients were included independent of preoperative
TN
NT.
T. We
We excluded
e clud
ex
ded patients from the current analysis
anaalyssis if they under
e weent off-pump
er
off-pump surgery or
TNT.
underwent
proc
ced
e ures requiring
req
qui
uiriing deep
deeep hypothermic
hyppoth
hy
poth
her
ermi
m c circulatory
mi
circul
ulaatorry arre
reest.
st Th
Thee st
tud
udyy w
ass ap
pprrov
oved
ed bby
y th
thee loca
lo
ocaal
procedures
arrest.
study
was
approved
local
ethics
et
thi
hics
css bboard,
oard
oa
rd,, an
rd
andd all
all pa
pparticipants
art
rttic
icip
pan
a ts pprovided
rovi
ovided w
written
riitt
tten
en
n iinformed
nfoorme
medd co
me
cons
consent.
nssen
nt.
peri
riop
ri
oper
op
erat
er
a iv
at
ivee an
nd in
iintensive
tens
te
n iv
ns
ive ca
care
re m
anag
an
agem
ag
emeent
em
nt,, in
incl
c ud
udin
i g su
in
surg
rgic
rg
ical
ic
al ttechniques,
echn
ec
hniq
hn
iq
que
u s, choice
All pe
perioperative
and
management,
including
surgical
and dosage of catecholamines for cardiopulmonary bypass weaning and in the intensive care unit
(ICU) coagulation management, blood transfusion triggers, duration of ICU stay, and
investigations for and treatment of postoperative complications were at the discretion of the
attending clinicians. Trained research personnel prospectively collected detailed data on
perioperative patient treatment, surgical techniques, and inhospital course and conducted followup. Inhospital complications were not adjudicated but were extracted from the hospital charts as
diagnosed by the attending physicians with the exception of acute kidney injury (AKI)
classification.24 Its detection is based on highest postoperative creatinine concentration measured
4
during hospitalization independent of its mention in the hospital charts. For the categories risk,
injury, and failure,24 the AKI classification did not require any minimal duration for creatinine
value elevations above the various cut-offs.
Cardiac Marker Analyses
TNT (Elecsys, Roche Diagnostics, F. Hoffmann-La Roche Ltd., Basel, Switzerland) and brain
natriuretic peptide (BNP) concentrations (ECLIA, Roche Diagnostics, F. Hoffmann-La Roche
Ltd., Basel, Switzerland) were measured routinely at 6 am on the first and second postoperative
day in all patients. Analyses were performed by the central hospital laboratory, which is
subjected to practice-certified regulatory quality controls. The 99th percentile and 10%
coefficient of variation of TNT lies at <0.01 ȝg/L and at 0.035 ȝg/L, respectivel
respectively.
ly.
y. T
The
hee 995th
5thh
5t
percentile and 6.7% coefficient of variation of BNP were at 135 ng/L and at 180 ng/L,
respectively.
esppec
ecti
tive
ti
veely
ly.
Clinical
C
lin
nic
i al Endpo
Endpoint
poin
i t Definitions
Defiini
De
niti
tion
ti
onss and
on
an
nd Endpoint
Endpoi
oiint Ascertainment
Assce
scerta
ta
ainm
inment
nt
The
primary
endpoint
was
predefined
Th
he pr
prim
i arry en
im
end
dpoint
dpo
oint w
as pr
rede
rede
defi
fine
fi
nedd as tthe
ne
he ccomposite
ompo
om
posi
po
s te
te ooff ddeath
eat
athh fr
at
from
om aany
nyy ccause
ause
ause
s or tthe
he ooccurrence
ccurrre
ccur
renc
n e
nc
of non-fatal major
maj
ajor
orr adverse
adv
dver
errsee cardiac
car
ardi
diiac events
eve
v nt
ntss (MACE)
(MAC
(M
ACE)
AC
E) within
wit
i hi
hinn one
one year
ye r after
afte
af
terr surgery.
te
surg
su
r er
rg
e y.
y MACE
MAC
A E
included myocardial infarction, cardiac arrest, need for subsequent surgical or percutaneous
coronary intervention, and congestive heart failure requiring hospitalization.
Follow-up data were obtained by a questionnaire mailed to all patients one year after
surgery. Patients or next of kin were asked to report the occurrence and date of any
hospitalization within the first year after surgery and/or the patient’s vital status. If the
questionnaire was not returned, research personnel contacted the patient by telephone. If unable
to contact a patient, we asked his general practitioner to provide the health or vital status
information. A trained research nurse blinded to the patients’ data conducted the interviews. If
5
the questionnaire or the interview indicated any hospitalization, the research team contacted the
hospital or the patient’s general practitioner to obtain appropriate documentation. Based on this
information, the occurrence of an endpoint was determined by two independent adjudicators
blinded to inhospital TNT and BNP data.
Statistical Analysis
Continuous data are presented as mean with standard deviation (SD) or as median with the 1st
and 3rd quartiles (Q1-Q3) as appropriate. Categorical data are presented as absolute numbers and
percentages. Baseline differences between patients with events compared to event-free patients
were calculated with the Student’s t, Mann-Whitney U Test, or Pearson’s Ȥ2 tests as appropriate.
All analyses were based on the higher TNT and BNP value measured at 6 am
m oon
n
postoperative day 1 and 2. We explored the association between increasing concentrations of
TNT
TN
NT and
and BNP
BNP for
fo
or the
th composite outcome by calculating
cal
allcu
c lating the interval
interrva
v l likelihood
liike
keli
l hood ratio over 10percentile
perc
cen
e tile groups
gro
oup
upss and
andd pplotted
lo
ott
tted
ed it.
it.
year
Wee calculated
cal
alcu
cu
ulaate
tedd the
th
he association
asso
soci
so
ciat
ci
atio
at
ionn between
io
betw
betw
tweeen
een cardiac
c rdi
ca
rdiac
iac biomarkers
biiom
omar
arrke
k rs and
and
n outcome
ouutco
utco
ome at
at 1 ye
earr iin
n a Cox
Co
regression
egression model
mod
odel
e with
el
wit
i h forced
f rcced entry.
fo
enntr
try.
y. The
The dependent
dep
pen
ende
dent
de
nt variable
var
aria
iabl
ia
blee was
bl
was the
the time
time to
to the
th
he composite
comp
co
mposite
mp
endpoint. We modelled cardiac biomarkers linearly, nonlinearly and dichotomized. For
dichotomization, we defined the optimal cut-off using receiver operating characteristic (ROC)
curves of each biomarker for the composite outcome at 1 year under assuming equal weight for
sensitivity and specificity. We predefined the logistic EuroSCORE23(continuous per % increase),
sepsis, sternal infection (without sepsis), respiratory infections (pneumonia, ventilator associated
pneumonia, or purulent tracheobronchitis without sepsis), AKI classification,24 as additional
independent variables. The explanatory variables either were acute events (e.g. postoperative
sepsis), or apply to a single point in time (logistic EuroSCORE). Therefore, we opted to model
6
them as static variables rather than time-dependent. To avoid model overfitting, we decided to
limit the number of independent variables. The selection of postoperative variables to include
into the model was guided by the following principles: 1) the concept that early complications
affecting the cardiovascular system (eg, postoperative cardiogenic or hemorrhagic shock) are
reflected by TNT and BNP concentrations); 2) the prevalence of the risk factor; and 3) the
prognostic challenge. The decision not to include postoperative ECMO-dependency exemplifies
this approach: first, hemodynamic instability requiring ECMO results in elevated TNT and BNP
concentrations (ie, ECMO is not as much a confounder, but rather a link of the
pathophysiological chain leading to elevated cardiac biomarkers). Second, the requirement for
ECMO was exceedingly rare in our cohort. Third, ECMO-dependency is such a sstrong
trron
o g in
indi
dica
di
c to
ca
tor
indicator
of poor outcome that clinicians hardly need to rely on cardiac biomarkers to restratify such
pa
atiien
ents
ts.
ts
patients.
We assessed
assses
esseed th
the mo
mode
dells
de
ls uusing
s ng
si
ng tthe
he A
kaike in
ka
nform
rmat
rm
atio
i n cr
io
cri
iteerio
ionn (A
AIC
C),, tthe
hee H
arrrel’
ar
l’ss C
l’
models
Akaike
information
criterion
(AIC),
Harrel’s
C-nde
dex,
x total
x,
tot
otal
all model
mod
odeel chi-square
chi
hi-s
-sqquar
qua e (Wald
(W
Wal
aldd test)
teest
st)) , and
and adjusted
adju
ad
just
ju
s ed
ed R squared.
squuar
a ed.
ed. We assessed
ass
sses
essseed ca
cal
li rat
libr
atiion
ion off
index,
calibration
he final model
mode
deel by plotting
plo
ott
t in
i g the
the observed
obse
ob
serv
se
r ed and
rv
and the
the predicted
pred
pr
ed
dic
i te
tedd co
comp
mpos
mp
o it
itee ev
even
ents
en
ts.. We eevaluated
ts
valu
va
luated
the
composite
events.
collinearity using the variance inflation factor (VIF). We internally validated the model by
bootstrapping with 1000 samples. We generated 4 risk stratification strata (5%, >5% to 10%,
>10% to 15%, and >15%) according to the EuroSCORE, the full model, and a model including
the EuroSCORE and early cardiac biomakers information. We then assessed the net
reclassification index (NRI) for EuroSCORE vs. the full model and for EuroSCORE vs.
EuroSCORE and TNT plus BNP. We calculated the NRI in patients with events, in those without
events, and the overall NRI.25A secondary Cox regression model with the same independent
variables was fitted for 30-day mortality and MACE. We generated a third model by including
7
the variables recently added to the EuroSCORE II26 (ie, CCS4, NYHA class, urgency of the
procedure in 3 categories [urgent, emergent, and salvage], insulin-dependent diabetes, creatinine
clearance, and the new procedure scores) as independent variables in our model.
The focus of this analysis were any on-pump cardiac surgery procedures, however we
also analyzed the distribution of troponin and BNP concentrations following specific procedures.
Further, we explored the potential interaction in the association between cardiac biomarkers and
outcome by the type of procedure. We opted to test for interaction within the subgroups “isolated
CABG” vs. “other procedures” to maintain power for the interaction analysis, rather than define
subgroups by specific types of non-CABG procedures.
Statics were calculated by SPSS 20, R 3.1.0., and by Microsoft Excel 201
010.
0. W
2010.
Wee
considered the null-hypothesis refuted if the two-sided P value was < 0.05.
Sa
amp
mple
le S
izee
iz
Sample
Size
F
orr th
tthee 36-mon
onth
th eenrollment
nroollm
nr
men
entt peri
pperiod,
eriod
od, we
od
we ant
tic
iciipatted
d a ssample
amplee si
amp
siz
ze off 15
11500
00 ppatients.
00
attie
ient
ntts.
s A
ssum
umin
um
ing
ng a
For
36-month
anticipated
size
Assuming
1
1-ye
year
ar event
eve
vent
nt rate
rat
atee of
of 12%,
12%
2%,,14
we
we expected
expe
ex
pect
pe
cteed
ed up
up to 180
180
0 events,
eveentts,
s, aallowing
llo
lo
owi
wing
ng
g ffor
orr a sstatistically
taati
t st
stic
icaally
ally rrobust
obustt
obus
1-year
o el bbased
od
ased
as
e oon
n up
u tto
o 18 vvariables.
aria
ar
iabl
ia
b es
bl
e .27
multivariate m
model
Results
Descriptive Analysis
Of the 1713 consecutive patients who underwent cardiac surgery in our institution between 2007
and 2010, 1569 fulfilled the eligibility criteria. In 10 patients (0.6%), no TNT values were
available, of whom 8 (0.5%) had died prior to the first sampling time (6 am on postoperative day
1) (Figure 1). Follow-up was completed in 1545 patients (99.1%); the remaining 14 patients
were censored at last contact date. One hundred-fifteen patients (7.3%) underwent cardiac
8
surgery within 7 days of an acute coronary syndrome with detectable preoperative TNT
concentrations. Their median preoperative TNT was 0.28 ug/L (Q1-Q3, 0.12-0.68 ug/L). BNP
concentrations were available in 1364 patients (86.9%). In patients missing POD 1 or POD2
samples, we assumed the available concentration to represent the higher concentration.
Within the 12-month postoperative follow-up, 176 patients (11.3%) suffered the
composite endpoint event, including 103 deaths (6.6%). We recorded 86 MACE (5.5%): 17
acute coronary syndromes (1.1%), 14 cardiac arrests (0.9%), 20 percutaneous coronary
interventions (1.3%), 6 subsequent CABG (0.4%), and 29 acute congestive heart failures (1.9%)
requiring hospitalization. Eighty-three events (5.3%) occurred within 30 days of surgery, of
which there were 58 deaths (3.7%). Compared to patients with uneventful follow-up,
follow
w-u
-up,
p those
tho
hose
se who
who
suffered
uffered an event had a higher EuroSCORE, higher TNT, higher BNP, and had presented more
postoperative
complications
BNP
were
po
ost
stop
opeerat
op
erat
ativ
ivee co
iv
omp
mpli
l cations (Table 1; Figure 22a-c).
a c). Troponin and
aan
nd BN
NP we
w
re higher after
procedures
proc
ced
e ures other
oth
herr than
thhan
han isolated
issol
olat
ated
at
ed CABG
CAB
ABG
G (Table
(Tablle 2).
Association
As
Asso
soci
so
ciat
ci
atio
io
on between
betw
betw
ween
een Postoperative
Po
ost
stop
perrat
atiive
ve TNT
TNT and
and
d BNP
BNP
P with
wit
ith
h 1-Year
1-Ye
1Y ar
Ye
ar Events
E ent
Ev
ents
ts and
and Reclassification
Rec
ecllasssiffic
icaatio
at o n
ratio
event
Figure 3 plots
plo
otss tthe
he llikelihood
i el
ik
e ih
i oood ra
rati
tioo of TN
ti
TNT
T an
andd BN
BNP
P fo
forr th
thee 111-year
year
ye
a ccomposite
omp
mpos
osit
os
i e ev
it
even
entt by increasingg
en
concentrations (groups defined by 10-percentiles). The AUC of the ROC curve of TNT was
0.688 (95% CI, 0.640-0.735) with an optimal cut-off at 0.8 μg/L. The corresponding values for
BNP were 0.714 (95% CI, 0.670-0.759) and 790 ng/L. The median duration from surgery to
event was 34 days (Q1-Q3, 8.25-114.75) in the whole population. In patients with elevated
cardiac biomarkers, the composite event occurred after a median of 22 days (Q1-Q3, 6-90).
Patients without elevated cardiac markers suffered their event after a median of 87 days (Q1-Q3,
22.75-157) (P<0.001).
Table 3 reports models’ informations. Concentrations of both TNT and BNP that above
9
the cut-off within the first two postoperative days were independently associated with the
composite endpoint at 1 year after on-pump cardiac surgery after adjustment by the EuroSCORE,
postoperative infectious complications, and AKI (Table 4). VIF were not suggestive of
collinearity (VIF <2 for all variables). Figure 4 shows the calibration results at various risk
levels.
The overall NRI for 1-year events with the addition of TNT and BNP information to the
EuroSCORE vs. the EuroSCORE alone was 0.276 (95% CI, 0.195-0.348). The addition of
biomarkers performed well for detecting increased risk (NRI, 0.696 [95% CI, 0.620-0.762]) but
poorly for decreased risk (NRI, -0.420 [95% CI, -0.448 to -0.0393]). The same pattern was
present for the final model. The overall NRI of the final model was 0.426 (95% CI,
CI, 00.347-0.493)
.34
34734
7 0.
70.49
493))
with a NRI for higher risk amounting to 0.734 (95% CI, 0.660-0.797) and -0.308 (95% CI, 0.335
0..3335 to -0.283)
-0.
0.28
0.
283)) ffor
28
or decreased risk (Supplemental
or
(Supplement
nttal Tables
Tables 1-4).
The models
mode
mo
d lss fitted
de
fit
itttedd to predict
predi
redict
c 30-day
ct
30-day events
eventss and
eve
and with
with
h the
thhe
he addition
add
ddit
itio
ionn of EuroSCORE
EuroS
uroS
SCO
CORE
R II,
RE
II, tthe
hee
variables
Wee di
vari
va
riab
ri
able
ab
l s showed
le
shhow
owed
ed
d similar
sim
imiilaar results
res
esuults (Supplemental
(Su
Supp
pp
pleeme
menttal
a Tables
Tabl
ables
les 5-6).
5-66).. W
5didd not
not fi
find
nd aany
ny eevidence
vidden
dence
nce off
significant
ignificant interaction
in
nte
tera
r ct
ra
ctio
io
on inn the
thhe association
a so
as
soci
c at
ci
atio
ionn between
betw
be
twee
tw
eenn TNT
ee
TNT (p=0.153)
(p=0
(p
=0
0.1
. 53
53)) and
an
nd BNP
BNP (p=0.785)
( =0
(p
0.7
.785
85)) and
85
outcome by the type of procedure (isolated CABG vs other procedures).
Discussion
Main Results
This cohort study showed that the association between an increase in TNT concentration within
the first 2 postoperative days and 1-year all-cause mortality and MACE after cardiac surgery
persisted after adjustment considering preoperative as well as postoperative confounders.
Further, we detected a significant independent association between postoperative BNP
10
concentrations and 1-year mortality and MACE. Extending the EuroSCORE to include
postoperative TNT and BNP information allowed for improved the risk stratification in every
fourth patient. The time-window of approximately 1 month between events and elevated
biomarkers suggests that measurement of cardiac biomarkers flags high-risk patients early (i.e.,
at a time point when management optimization holds promise for outcome improvement).
Preoperative cardiac surgery risk stratification models,1 including the EuroSCORE,2, 3
that exclusively consider pre- and intraoperative risk factors are the most useful for healthcare
planning and for preoperative risk-benefit assessments. However, there is a need for reevaluation
and risk reassessment after the surgical procedure itself. The data generated in this cohort study
uggest that postoperative TNT and BNP concentrations within the first 2 postop
perat
a iv
at
ve da
days
ys aare
re
suggest
postoperative
helpful tools for risk reassessment after cardiac surgery. They are non-invasive, easily obtained,
an
nd allow
allo
al
low
lo
w for
for early
eaarl
rlyy flagging
f agging of patients at riskk for
fl
or death
death and MACE
MAC
CE within
wiith
thiin the next (few)
and
m
onnth(s).
nt
This
is oobservational
bsserrva
vati
tiion
nal sstudy
tudy
tu
dy
y ddid
id
d nnot
ot aaddress
dd
dresss tthe
hee qquestion
uesstion ho
ue
ow to
o ooptimize
ptim
pt
imiize
im
ize th
thee m
annage
nageemen
month(s).
how
management
off ppatients
atie
at
ient
ie
ntss wi
with
th iincreased
nccre
reaaseed
ed rrisk
issk aafter
fter
ft
er ccardiac
arrdiiac ssurgery.
urge
ur
gerry.
ge
ry. P
oteent
ntiiall ap
appr
proa
pr
oach
oa
ch
hess m
ight
ig
h iinclude
ht
nclludde m
nc
orre
Potential
approaches
might
more
tringent inhospital
inho
hoosp
spit
ital
al m
onitor
on
orin
or
in
ng in step-down
ste
tep--do
down
wn uunits
n ts
ni
t oorr sy
yst
stem
emaati
em
ticc te
ttelemetry
leme
le
metr
me
tryy mo
tr
moni
nito
ni
tori
to
ring
ri
ng on the
stringent
monitoring
systematic
monitoring
regular ward, dedicated post-cardiac surgery outpatients clinics, or virtual wards.
Comparison with Previous Studies
Several studies evaluated the association between troponin elevations after cardiac surgery and
short-9, 10 and long-term adverse events.12-14 Adabag and colleagues9 reported on a concentrationresponse relationship between troponin I release and short-term mortality (OR, 1.3 [95% CI 1.11.5] per 0.05 μg/L increase in troponin I levels in valvular patients and 1.4 [95% CI 1.2-1.6] in
CABG patients). Similarly, Nesher and colleagues10 described a concentration-dependent
association of TNT and short-term MACE. Further, their analysis revealed an association
11
between a TNT cut-off concentration of 0.8 μg/L and short-term mortality. In our data, the
optimal cut-off for the prediction of 1-year mortality or MACE was also 0.8 μg/L.
Croal and colleagues12 showed an OR of 1.10 (95% CI, 1.03-1.18) per 10 μg/L troponin I
increase for one-year mortality. Our group previously described in next to 750 patients (enrolled
in 2005-2006) an AUC 0.78 (95% CI, 0.7-0.86) using TNT for 12-month mortality and an
independent association between elevated TNT and 12-month mortality (OR, 3.83 [95% CI,
2.10-7.12]) after adjustment using the EuroSCORE.14 Previous studies (including our own data),
however, disregarded potential confounding by postoperative complications and did not assess
BNP concentrations. Further, they did not quantify the prognostic gain compared to preoperative
isk stratification tools in terms off reclassification (eg, the EuroSCORE).
risk
Fox and colleagues19 assessed the association between postoperative BNP and 5-year
mo
mort
rtal
rt
alit
al
ityy in 11183
it
1883 patients
pa
undergoing elective C
ABG. In contras
AB
st to our
our data,
data, they did not detect
mortality
CABG.
contrast
an
any
ny si
ssignificant
gnifican
nt independent
inddepe
in
peend
den
nt association
asso
as
soci
ciiat
atio
ionn bbetween
etw
ween po
postop
postoperative
opperat
erattiv
ve BN
BNP
P an
and
nd lo
long-term
ong
ng-t
-ter
erm
m mo
m
mortality
rtal
rt
alit
al
ityy (HR
(H
off 1.62,
1.662, 95%
95% CI,
CI,, 0.71–3.68).
0.7
.71–
1–
–3.68
68).
) This
Thi
hiss fact
fact might
mig
ighht be
be related
reelaateed to their
theeir choice
cho
oic
icee off a longer
lon
onge
gerr follow-up
ge
follow
fo
ow-u
ow
-upp
duration. It iiss pl
plau
plausible
au
usi
sibl
blee th
bl
tthat
at over
ove
verr a 5-year
5 yeear period,
5per
erio
iod,
io
d, in
in an
a elderly
elde
derl
rlyy population
rl
popuula
po
lati
t on with
ti
wit
ithh a high
high burden of
risk factors, subsequent cardiac and noncardiac events might have diluted the strength of the
association between early postoperative BNP concentrations and all-cause death. This hypothesis
is supported first, by the report of the association between congestive heart failure episodes and
heart failure mortality in the same population,20 and second, by the significant independent
association between postoperative BNP and poor physical function within a shorter follow-up
duration in a subgroup of the same patients.18 Three smaller cohort studies (<400 patients in
total)17, 21, 22 described higher postoperative BNP concentrations in patients who died after
cardiac surgery. However, they were underpowered to conduct multivariable adjustment.
12
Strength and Limitations
The strength of our study stems from first, the inclusion of a broad, unselected population of
consecutive patients undergoing on-pump cardiac surgery; second, the minimal number of
missing TNT data (0.6%); third, achieving >99% follow-up completeness; fourth, the blinded
event adjudication by two independent readers with extensive knowledge and experience of the
perioperative cardiac surgery setting (cardiac anesthesiologists and intensive care physicians);
fifth, the high data quality with extensive data consistency checks and quality controls; and
finally, our analysis plan that considers not only preoperative risk factors but also postoperative
complications in the prediction model given their role as confounders and with the quantification
of reclassification by cardiac biomarkers.
We are aware of some limitations of our study. First, we assessed the concentration of
biomarkers
all
independent
bi
iom
mar
arkkers
kers iin
n al
ll patients
pa
at 6 am on postoperative
postoperatiive
v dday
ay 1, independ
n en
nd
nt of the time of surgery.
Therefore,
thee samples
hours
after
T
heerefore,
er
sam
amplles of
of postoperative
post
po
stop
st
oper
eraativ
er
ativ
ve dayy 1 were
re collected
col
ollleect
cted
ed between
betweeen 122 and
and 220
0 ho
hour
u s af
ur
fter
t er
surgery
after
surgery.
Blood
urg
rger
eryy and
er
and the
the samples
sampl
sam
mples
les of postoperative
posto
tope
perrati
pe
ratiivee day
day
ay 2 between
beetw
weeen 36 and
and 44
44 ho
hhours
urss af
fte
terr su
surg
rgeery.
rg
y. B
loo
lo
od
sample
collection
conforms
clinical
ample colle
ecttio
ionn at a ffixed
i ed
ix
d ppoint
oint
oi
n ooff th
nt
thee da
day,
y hhowever,
y,
owev
ow
ever
ev
e , co
er
conf
nfor
nf
o ms too cl
or
clin
inic
in
ical
ic
al rroutine
ou
uti
tine
ne rrather
a her than too
at
sample collection at a defined time after surgery. A further disadvantage of our set time for blood
sample collection is the fact that cardiac biomarkers were not measured in the few patients who
died before 6 am on the first postoperative morning.
Second, in contrast to the standardized approach to cardiac biomarkers sampling, the
study protocol did not mandate any screening standard for infectious or renal complications;
rather, their detection relied on diagnostic work-up ordered by the attending physicians.
Therefore, we cannot exclude that some patients might have been misclassified. However, this
approach mimicked clinical routine, and as such it better complied with the pragmatic approach
13
of our study question. Further, the large sample size can be expected to have mitigated this issue.
Third, follow-up assessment based on mailed questionnaires may be subjected to
non-response bias. However, telephone interviews with patients and/or their general practitioners
allowed us to achieve almost complete follow-up (>99%). Our follow-up assessment may also
have been biased by misclassification of outcomes, but the probability of forgetting a
hospitalization seemed remote. Moreover, misclassification bias could be expected to be nondifferential as the patients were not aware of their exposure status (ie, TNT and BNP readings).
Fourth, the choice of equal weight for sensitivity and specificity to define the optimal cutoff point resulted in the fact that at the proposed cut-off value sensitivity was higher than
specificity.
pecificity. This in turn led to a good reclassification in patients with increased risk,
riisk
sk,, whereas
wher
wh
erea
er
eass risk
ea
ri
down-rating was poor.
Fifth,
focused
only.
Thielmann
Fift
Fi
fth
ft
h, wee fo
h,
foc
cused on postoperative TNT cconcentrations
onncentrations on
nly
l . Th
Thi
ie
ielmann
and colleagues28
showed
howed
ow
w a prognostic
progn
gnoostticc vvalue
alu
luee of eelevated
lu
levvat
le
vated
ted ppreoperative
reopper
perative
ve tro
troponin
oponi
poniin I co
concentrations
oncen
enttra
tratio
ons
ns ffor
or sshort-term
hort
ho
rtt-t
- erm
e rm
mortality.
However,
the
presenting
acute
coronary
mo
ort
r al
alit
i y.
it
y H
owever,
owe
er, th
he hi
highh bbaseline
asel
as
elin
el
inee ri
in
risk
sk ooff ppatients
a ients
at
nt pr
pres
eseenti
es
enti
ting
ng a rrecent
e entt ac
ec
acut
u e co
ut
oro
onaary
ry
syndrome
yndrome and/or
and
ndd/o
/orr emergent
emer
em
errge
g ntt surgery
sur
u ge
gery
r is
ry
is already
alre
al
read
re
adyy considered
ad
co
ons
nsid
ider
id
ered
ed
d by
by preoperative
preo
pr
eope
eo
peera
rati
tivve risk
ti
risk
s stratification
str
trat
a if
at
ific
ication
ic
(EuroSCORE).2 Further, fewer than 8% of the included patients demonstrated detectable TNT
concentrations before surgery. We also did not measure preoperative of BNP. Multiple studies15,
16, 19
established the significant independent association between preoperative BNP
concentrations and outcome after cardiac surgery.
Sixth, for adjustment by preoperative risk estimation we used the EuroSCORE that was
initially generated to predict short-term outcome. However, its prognostic value was validated
for long-term events.23 Further, the independent prognostic impact of cardiac biomarkers was
maintained when restricting the analysis to short-term mortality and MACE. An additional
14
limitation of the EuroSCORE is its overestimation of mortality, particularly with higher
scores.1,29
Seventh, a new version of the EuroSCORE (II) was proposed after completing
enrollment.26 We had information on the variables newly included in the model with the
exception of pulmonary arterial pressure, which was collected as pulmonary hypertension (>60
mm Hg) instead of the categories (31-55 mm Hg and >55 mm Hg) as per the EuroSCORE II.
Therefore, we were not able to calculate the EuroSCORE II in our patients. However, the
addition of the new variables included in the EuroSCORE II (eg, CCS 4, NYHA, creatinine
clearance) into our model did not affect the association between TNT and BNP with the 30-day
or 1-year endpoint. Further, the improvement in predictive performance of the E
uroS
o CO
oS
CORE
RE IIII is
EuroSCORE
till not fully established.1, 29-31
still
Eigh
Ei
ghth
gh
th, the
th
th
he sample
s mple size in the subgroups was
sa
was nott sufficient
sufficien
nt to test
tes
estt for interaction in the
Eighth,
association
asso
oci
c ation be
between
etw
weeen ca
card
cardiac
rd
dia
iacc ma
m
markers
rk
ker
erss aand
nd outcome
ouutccomee within
with
hin
n specific
spe
peci
cifi
fiic surgical
surggic
su
ical
al procedures.
prooce
cedu
dure
du
rees. H
However,
owev
ow
ever,
ev
wee did
did not
not find
fin
indd any
any evidence
ev
vid
den
encee for
for interaction
int
nter
eraacti
acti
tion
on inn th
tthee subg
ssubgroup
ubg
bgro
roup
ro
up iisolated
s late
so
lateed CA
CABG
BG
G vvss ot
other
the
her pro
pprocedures.
roced
oced
dur
ures
e.
Finally,
Finall
lly,
y, 12%
12% of
of postoperative
p st
po
stop
oper
op
errat
ativ
iv
ve BNP
BNP concentrations
conc
co
ncen
nc
entr
en
t at
tr
a ion
onss we
on
were
re m
missing.
isssi
sing
ng.. Ho
ng
Howe
However,
weve
we
ver,
ve
r, w
with
i h a total ooff
it
over 1300 patients, this cohort still represents one of the largest to address this topic.
Conclusion
Postoperative TNT and BNP elevations are independently and strongly associated with 1-year
mortality and MACE after on-pump cardiac surgery. The extension of the EuroSCORE, a
preoperative risk stratification tool, with postoperative TNT and BNP concentrations allowed for
a better prediction of 1-year all-cause mortality and the occurrence of MACE after on-pump
cardiac surgery.
15
Acknowledgments: The authors thank Salome Dell-Kuster, MD, MSc for statistical advice,
Tanja Schmidt, MD, Claudia Werner, RN, and Anne-Michelle Droux, RN, for data collection,
Domenik Zwahlen for data management, and Allison Dwileski, BS, for her expert editorial
assistance.
Funding Sources: This study was supported by a research Grant of the Swiss National Science
Foundation (SNF Number 3200B0_121943/1), the European Association of Cardiothoracic
Anaesthesiologists, and by the Foundation for Research and Education, Department for
Anesthesia, Surgical Intensive Care, Prehospital Emergency Medicine and Pain Therapy,
Prehospital Emergency Medicine and Pain Therapy, University Hospital Basel, Switzerland.
Conflict of Interest Disclosures: None.
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Preo
Pr
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eo
pera
pe
rati
tive
ve bb-type
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ypee na
yp
atrriu
iure
r ti
ticc pe
pept
ptiide
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nde
d penndeent
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pred
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dic
icto
to
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en
ntr
tric
iccullar
a ddysfunction
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n aand
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bypass
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ti
bili
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mark
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From aarea
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mith
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19
Table 1. Patient Characteristics, Surgical and Postoperative Data
All Patients
n=1559
Preoperative data
Age (years), mean (SD)
67 (10)
Male
1151 (73.8)
Recent ACS (30 days)
234 (15.0)
Left main stem stenosis >50%
345 (22.2)
Acute endocarditis
32 (2.1)
Pulmonary hypertension 60 mm Hg
86 (5.5)
Preoperative EF
60 (49-65)
Arterial hypertension
1092 (70.1)
Diabetes (insulin or OAD)
359 (23.1)
BMI (kg/m2), mean (SD)
27.8 (10.8)
History of TIA/CVI
137 (8.8)
History of PVD
195 (12.5)
Preoperative GRF (ml/min)
82 (61-106)
COPD under treatment
87 (5.6)
Logistic EuroSCORE
2.25 (1.42-3.80)
Additive EuroSCORE
5 (3-7)
Procedural data
Isolated
778 (50.0)
solated CABG
Isolated
196 (12.6))
sollat
ated
ed aortic
aor
orti
ticc valve
v lv
va
ve replacement
replacement
CA
ABG and
and
d aortic
aor
orticc va
valv
lve surg
gery
3)
CABG
valve
surgery
176 (11.3)
CABG
CAB
BG and 2-valve
2-v
-val
allve
ve procedures
pro
oce
cedu
durees
du
3 ((2.2)
2.2)
2.
2
2)
CABG
34
Emergent
er
46 (3.0)
(3
3.0
0)
Emergent
surgeryy
46
Po
osttop
o erativ
ve data
ta
Postoperative
Trop
Tr
op
pon
o in T P
OD 1 ((μg/L)
μg/L
μg
/L))
00.45
0.
45
5 ((0.25-0.90)
0.25
0.
2 -0
25
-0.9
.90)
.9
0)
Troponin
POD
Trop
Tr
opon
op
onin
on
in T P
OD 2 ((μg/L)
μg/L
μg
/L))
/L
0.40 ((0.19-0.96)
0.40
0.19
0.19
19-0
0.9
.96)
96)
Troponin
POD
(ng/
(n
g/L)
g/
L
L)
43
33 (277-794)
(277
(2
77-7
77
-794
-7
94))
94
BNP POD 1 (ng/L)
433
O 2 (ng/L)
( / )
(326 812)
BNP POD
498 (326-812)
ECMO
6 (0.4)
IABP
55 (3.5)
Postoperative acute kidney
141 (9.0)
injury/failure
Inhospital sepsis
33 (2.1)
Inhospital respiratory infection*
73 (4.7)
Sternal infection
49 (3.1)
ICU LOS (days)
2 (2-3)
Hospital LOS (days)
11 (9-16)
No Events
n=1383
Events
n=176
P Value
67 (11)
1031 (74.5)
199 (14.4)
291 (21.1)
28 (2.0)
67 (4.9)
60 (50-65)
965 (69.9)
306 (22.2)
27.6 (9.1)
122 (8.8)
157 (11.4)
83 (63-107)
72 (5.2)
2.14 (1.41-3.44)
5 (3-7)
71 (10)
120 (68.2)
35 (19.9)
54 (30.7)
4 (2.3)
19 (10.8)
54 (40-60)
127 (72.2)
53 (30.1)
32.7 (27.1)
15 (8.5)
38 (21.6)
71 (58-93)
15 (8.6)
6)
(1.87-6.96)
3.68 (1.8
877-6.
6.96
6.
96))
96
(4-9)
7 (4
4-9
9)
0.64
0.07
0.054
0.04
0.827
0.001
0.012
0.533
0.019
0.103
0.985
<0.001
0.012
0.068
0.0
.06
68
<0.001
<0.0
<0
.0
001
0
<0.001
<0.0
<0
001
0
695 (50.3)
187 (13.5)
153 (11.1
1)
(11.1)
331
1 (2
((2.3)
.3
3)
37 (2.7)
(2.7)
(2.7
37
83 (47.2)
9 (5.1)
23 (13.1)
(13.1)
3 (1
(1.8
.8))
.8
(1.8)
(5.11)
(5
9 (5.1)
0.429
0.002
0.434
00.668
0.66
.66
668
0.07
0.
72
0.072
00.42
0.
42 ((0.25-0.82)
0 25
0.
25-0
-0
0.882)
0.37 ((0.18-0.82)
0.37
0.18
0.18
18-0
-0
0.8
.82)
82)
417 (259-722)
(259
(2
59-7
59
-7
7222)
417
4 0 (313-724)
(313 24)
470
1 (0.07)
28 (2.0)
00.87
. 7 (0
.8
.40400-1
1.92
92
2)
(0.40-1.92)
00.83
.83
.8
83 (0
.31.3
31 1.93
1.93
93))
(0.31-1.93)
870
87
0 (4
483
83-1
- 36
-1
367)
7
(483-1367)
892 (440
1 06)
(440-1506)
5 (2.8)
27 (15.3)
<0.0
<0
.001
0
01
<0.001
<0
0.0
.001
001
<0.001
<0.001
0 001
<0.001
<0.001
<0.001
89 (6.5)
52 (29.5)
<0.001
15 (1.1)
43 (3.1)
34 (2.5)
2 (2-2)
11 (9-15)
18 (10.2)
30 (17.0)
15 (8.5)
4 (2-7)
15.5 (10-31)
<0.001
<0.001
<0.001
<0.001
<0.001
Number (%) unless stated otherwise, continuous variables are reported as median (Q1-Q3) unless stated otherwise.
*Respiratory infections included pneumonia, ventilator associated pneumonia, or purulent tracheobronchitis.
ACS, acute coronary syndrome; BMI, body mass index; BNP, B-type natriuretic peptide; CABG, coronary artery
bypass graft; COPD, chronic obstructive pulmonary disease; CVI, cerebrovascular insult; ECMO, extra-corporal
membrane oxygenation; EF, ejection fraction; GFR, glomerular filtration rate (Cockcroft-Gault estimate); IABP,
intra-aortic balloon pump; ICU, intensive care unit; LOS, length of stay; OAD, oral antidiabetics; POD,
postoperative day; PVD, peripheral vascular disease; Q1-Q3, first to third quartile; SD, standard deviation; TIA,
transient ischemic attack.
20
Table 2. Troponin T and BNP concentrations by type of procedure.
Higher TNT POD 1 and 2
at 6 am (μg/L)
TNT POD 1 (μg/L)
TNT POD 2 (μg/L)
Higher BNP POD 1 and 2
at 6 am (ng/L)
BNP POD 1 (ng/L)
BNP POD 2 (ng/L)
Isolated CABG
Other procedures
0.38
(0.20-0.71)
0.37
(0.15-0.90)
0.31
(0.2-0.78)
400
(259-705)
369
(233-661)
434
(285-766)
0.55
(0.31-1.07)
0.54
(0.25-1.04)
0.46
(0.32-1.05)
532
(353-926)
493
(328-900)
541
(377-835)
Difference of the
median (95%CI)
0.17
(0.12-0.21)
0.17
(0.12-0.22)
0.16
(0.11-0.20)
132
(75-189)
124
(79-169)
107
(38-176)
p-value
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
Median (Q1
(Q1-Q3);
Q3); BNP: brain natriuretic peptide; POD: postoperative day; TNT: troponin T; pp-values
vallue
uess ca
cal
calculatated
lcul
ulattat
ateed
using Mann-Whitney-U test
21
Table 3. Cox-regression Model Information
Model
Univariate Models
Peak TNT, linear
Peak TNT, non-linear
Peak TNT, binary (0.8)
BNP, linear
BNP, non-linear
BNP, binary (790)
Models with BNP and TNT
BNP binary, TNT binary
BNP non-linear, TNT
non-linear
Multivariable Models
Euroscore
Eu
uro
rosc
scor
sc
oree linear,
or
line
li
n arr, postop
po
complications,
co
omp
mpli
licatiionns, T
TNT
NT bbinary,
inar
in
ary,
y
y,
BNP binary (fi
BNP
(final
fina
nal mo
na
model)
mode
del)
l)
Euroscore
Eu
uro
osc
scor
o e linear,
liine
near
ar,, postop
postop
post
opp
complications,
comp
co
mp
pli
lica
cati
ca
tioons,
ti
ons, T
TNT
NT
nonlinear,
nonl
no
nlin
nl
inea
in
earr, B
ea
BNP
NP nnonlinear
onli
on
line
li
near
ne
ar
AIC
C-index
Total model
Chi-Square
(Wald-test)
2516.6
2480.1
2486
2211.51
2173.88
2178.91
0.689
0.689
0.666
0.707
0.707
0.674
96.19
99.24
80.11
104.95
97.1
83.97
0.04
0.07
0.063
0.046
0.081
0.074
2145.979
0.721
0.729 (original)
0.7258 (corrected,
150 bootstrap
samples)
117.91
0.103
123.22
00.103
.1103
217.377
217.37
21
3777
0.155
0.
210.6961
210.
21
0 69961
00.147
.1147
2150.397
2098.685
2098
20
98.6
.685
85
2105.984
21005.9
21
05 984
0.761
0.7661 ((original)
original) 0.757
57
(corrected,
(cor
(c
rrect
cted
ed,, 15
1150
0
bootstrap
boootstrapp samples)
samp
samp
mple
les)
s))
0.7594
0.75
0.
7594
75
94
(original)0.7531
(orrigi
(o
gina
gi
naal))0.7
0.7531
7531
3
(corrected,
(corre
(c
ect
cted
ed, 15
1500
bootstrap
boot
bo
o st
ot
s ra
rapp samples)
samp
sa
mple
mp
lees)
22
Adjusted R
squared
Table 4. Cox-regression Model for Composite Endpoint within 1 Year after Surgery.
HR
Logistic
EuroSCORE
TNT 0.8 ȝg/L
BNP 790 ng/L
Inhospital sepsis
Inhospital
respiratory infection
Sternal infection
Acute kidney injury
Model Derivation
95% CI
P Value
Model Validation
(1000 Bootstrap Samples)
HR
95% CI
P Value
1.029
2.128
2.445
2.064
0.999
1.483
1.705
1.159
1.061
3.053
3.508
3.676
0.062
0.000
0.000
0.014
1.029
2.128
2.445
2.064
0.996
1.472
1.647
1.151
1.060
3.154
3.616
4.118
0.059
0.001
0.001
0.021
2.270
1.260
1.310
1.433
0.702
1.120
3.595
2.262
1.534
0.000
0.440
0.001
2.270
1.260
1.310
1.340
0.610
1.089
3.613
2.437
1.559
0.003
0.515
0.005
Logistic EuroSCORE entered continuously per % increase. Respiratory infections included pneumonia, ventilator
associated pneumonia, or purulent tracheobronchitis. Acute kidney injury included the following categories: a) Risk:
serum
erum creatinine (SCr) increased by 1.5 or glomerular filtration rate (GFR) decreased >25%;
25%; b) Injury:
Inj
njury:
y: SCr
SCr
increased
SCr
ncreased by 2 or GFR decreased >50%; c) Failure: SCr increased by 3 or GFR decreased 75% orr S
Cr 4
4 mg/dL
mg/d
mg
/dL
/d
L or
acute
cute rise 0.5 mg/dL; d) Loss: persistent acute renal failure: complete loss of kidney function >4
>4 weeks
week
we
ek
ks24
TNT,
troponin
BNP, brain natriuretic peptide; CI, confidence interval; HR, hazard ratio; LR, likelihood ratio; T
NT
T, tr
tropon
oniin T
Figure
F
igu
gure
u Legends:
Legen
nds
ds:
CABG,
coronary
bypass
Figure 1. Flow
Flo
ow chart
ch
har
artt of patient
pat
atie
ient
ie
n inclusion.
nt
inc
n lu
usion
on.. CA
on
CABG
BG,, co
BG
coro
r na
nary
ry aartery
rter
rt
eryy by
er
bypa
pass
pa
ss ggraft;
r ft
ra
ft; CP
CPB,
B,
cardiopulmonary bypass; DHCA, deep hypothermic circulatory arrest; MACE, major adverse
cardiac events.
Figure 2a-c. KaplanMeier curves and survival table stratified by TNT (a), BNP (b), and
postoperative complications (c).
Figure 3. Likelihood ratio of the 1-year composite by increasing TNT and BNP concentrations.
Figure 4. Calibration of the final model by risk groups.
23
Figure 1
Figure 2A
Figure 2B
Figure 2C
Figure 3
Figure 4
SUPPLEMENTAL MATERIAL
Reclassification Tables
Supplemental Table 1. Reclassification by Using Biomarker Information in Patients with 1-year Events
EuroSCORE and Cardiac Biomarker
Predicted
Predicted Predicted
Predicted
≤0.05
>0.05-0.1
>0.1-0.15
>0.15
Predicted ≤0.05
27
4
34
42
Predicted >0.05-0.1
0
5
1
23
Predicted >0.1-0.15
0
3
0
10
Predicted >0.15
0
0
1
8
EuroSCORE
Supplemental Table 2. Reclassification by Using Biomarker Information in Patients without 1-year Events
EuroSCORE and Cardiac Biomarker
Predicted Predicted Predicted
<=0.05
Predicted
>0.05-0.1
>0.1-0.15
>0.15
601
75
265
87
Predicted >0.05-0.1
0
59
10
61
Predicted >0.1-0.15
0
8
0
22
Predicted >0.15
0
2
3
13
Predicted ≤0.05
EuroSCORE
Supplemental Table 3. Reclassification by Using Biomarker and Postoperative Complication Information (Full Model) in Patients with 1-year Events
Full Model
Predicted
Predicted Predicted
Predicted
≤0.05
>0.05-0.1
>0.1-0.15
>0.15
Predicted ≤0.05
21
17
18
51
Predicted >0.05-0.1
0
3
7
19
Predicted >0.1-0.15
0
3
2
8
Predicted >0.15
0
0
1
8
EuroSCORE
Supplemental Table 4. Reclassification by Using Biomarker and Postoperative Complication Information (Full Model) in Patients without 1-year Events
Full Model
Predicted
Predicted Predicted
Predicted
≤0.05
>0.05-0.1
>0.1-0.15
>0.15
Predicted ≤0.05
587
208
111
122
Predicted >0.05-0.1
26
27
37
40
Predicted >0.1-0.15
0
8
5
17
Predicted >0.15
0
5
2
11
EuroSCORE
Supplemental Table 5. Cox-Regression Model for Composite Endpoint within 30 Days after Surgery
Hazard
Ratio
95% Confidence Interval
P Value
Logistic EuroSCORE
1.039
0.998
1.082
0.062
TNT ≥0.8 μg/L
2.964
1.695
5.185
<0.001
BNP ≥790 ng/L
2.664
1.540
4.609
<0.001
Inhospital sepsis
2.079
0.974
4.440
0.059
infection
1.382
0.704
2.715
0.347
Sternal infection
1.159
0.493
2.726
0.735
Acute kidney injury
1.301
1.048
1.614
0.017
Inhospital respiratory
BNP, brain natriuretic protein; TNT, troponin T
Supplemental Table 6. Independent Association between Cardiac Biomarkers and 1-year and 30-day Events in the full Model and in the Model including
EuroSCORE II Variables
TNT ≥0.8 μg/L
1-year Composite
30-day Composite
Event
Event
HR (95% CI)
HR (95% CI)
2.13
2.96
(1.48-3.05)
(1.69-5.18)
2.45
2.66
(1.70-3.51)
(1.54-4.61)
2.18
2.70
(1.49-3.19)
(1.48-4.92)
2.28
2.12
(1.55-3.37)
(1.17-3.82)
Full model
BNP≥790 ng/L
Full model
+
TNT ≥0.8 μg/L
EuroSCORE
II variables BNP ≥790 ng/L
*EuroSCORE II variables: CCS4, NYHA class, urgency of the procedure in 3 categories (urgent, emergent, and salvage), insulin-dependent diabetes, creatinine
clearance, and the procedure weights according to the EuroSCORE II ; Full model variables: Logistic EuroSCORE, TNT, BNP, and postoperative sepsis,
pneumonia, sternal infection, acute kidney injury

Michael T. Koller, Manfred D. Seeberger and Miodrag Filipovic

Transcrição

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