Systolic Blood Pressure at Admission, Clinical Characteristics, and Outcomes in Patients Hospitalized With Acute Heart Failure

Abstract

The association between systolic blood pressure (SBP) at admission, clinical characteristics, and outcomes in patients hospitalized for heart failure who have reduced or relatively preserved systolic function has not been well studied.
To evaluate the relationship between SBP at admission, clinical profile, and outcomes in patients hospitalized for acute heart failure.
Cohort study using data from the Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients with Heart Failure (OPTIMIZE-HF) registry and performance-improvement program for patients hospitalized with heart failure at 259 US hospitals between March 2003 and December 2004. Patients were divided into quartiles by SBP at hospital admission (<120, 120-139, 140-161, and >161 mm Hg). In-hospital outcomes were based on 48,612 patients aged 18 years or older with heart failure. Of the 41,267 patients with left ventricular function assessed, 21,149 (51%) had preserved left ventricular function. Postdischarge outcomes were based on a prespecified subgroup (n = 5791, 10% of patients) with follow-up data assessed between 60 and 90 days.
In-hospital and postdischarge mortality.
Patients with higher SBP were more likely to be female and black and to have preserved systolic function. Fifty percent of the patients had SBP higher than 140 mm Hg at admission. Patients with lower SBP at admission had higher in-hospital and postdischarge mortality rates. Higher SBP at admission was associated with lower in-hospital mortality rates: 7.2% (<120 mm Hg), 3.6% (120-139 mm Hg), 2.5% (140-161 mm Hg), and 1.7% (>161 mm Hg) (P<.001 for overall difference). Postdischarge mortality rates in the follow-up cohort by SBP at admission were 14.0%, 8.4%, 6.0%, and 5.4%, respectively (P<.001 for overall difference).
Systolic hypertension is common in patients hospitalized for heart failure. Systolic blood pressure is an independent predictor of morbidity and mortality in patients with heart failure with either reduced or relatively preserved systolic function. Low SBP (<120 mm Hg) at hospital admission identifies patients who have a poor prognosis despite medical therapy. These findings may have important therapeutic implications because characteristics and outcomes differ greatly among patients with heart failure with varying SBP.

Full text

ORIGINAL CONTRIBUTION
Systolic Blood Pressure at Admission,
Clinical Characteristics, and Outcomes in
Patients Hospitalized With Acute Heart Fail ure
Mihai Gheorghiade, MD
William T. Abraham, MD
Nancy M. Albert, RN, PhD
Barry H. Greenberg, MD
Christopher M. O’Connor, MD
Lilin She, PhD
Wendy Gattis Stough, PharmD
Clyde W. Yancy, MD
James B. Young, MD
Gregg C. Fonarow, MD
for the OPTIMIZE-HF Investigators
and Coordinators
A
CUTE HEART FAILURE IS A MA-
jor public health concern be-
cause of its prevalence and as-
sociated morbidity and
mortality. In 2003, 1.1 million pa-
tients were discharged from the hospi-
tal for heart failure, making this the
most common primary discharge diag-
nosis among patients older than 65
years.
1,2
Until recently, the scientific
community’s understanding of acute
heart failure syndromes (AHFS) had
been based on demographic and out-
come data obtained from randomized
controlled trials.
3
While these results
drive therapeutic decision making, re-
lying on clinical trial data to character-
ize the general acute heart failure popu-
lation is limited by the fact that
randomized controlled trials have
tended to focus on a small proportion
of AHFS patients. Because of selective
enrollment criteria, clinical trials may
See also p p 2209 and 2259.
Author Affiliations: Division of Cardiology, Feinberg
School of Medicine, Northwestern University, Chi-
cago, Ill (Dr Gheorghiade); Division of Cardiology, Ohio
State University, Columbus (Dr Abraham); George M.
and Linda H. Kaufman Center for Heart Failure, Cleve-
land Clinic Foundation, Cleveland, Ohio (Drs Albert
and Young); Department of Medicine, University
of California San Diego Medical Center, San Diego
(Dr Greenberg); Duke Clinical Research Institute,
Durham, NC (Drs O’Connor and She); Department
of Medicine, Duke University Medical Center, Durham,
NC (Dr Stough); Campbell University School of
Pharmacy, Research Triangle Park, NC (Dr Stough);
Department of Medicine, University of Texas South-
western Medical Center, Dallas (Dr Yancy); and De-
partment of Medicine, University of California Los An-
geles Medical Center, Los Angeles (Dr Fonarow). Dr
Yancy is now with the Baylor Heart and Vascular In-
stitute, Baylor University Medical Center, Dallas, Tex.
Corresponding Author: Gregg C. Fonarow, MD, Ah-
manson-UCLA Cardiomyopathy Center, UCLA Medi-
cal Center, 10833 LeConte Ave, Room 47-123 CHS,
Los Angeles, CA 90095 (gfonarow@mednet.ucla
.edu).
Context The association between systolic blood pressure (SBP) at admission, clinical
characteristics, and outcomes in patients hospitalized for heart failure who have re-
duced or relatively preserved systolic function has not been well studied.
Objective To evaluate the relationship between SBP at admission, clinical profile,
and outcomes in patients hospitalized for acute heart failure.
Design, Setting, and Patients Cohort study using data from the Organized Pro-
gram to Initiate Lifesaving Treatment in Hospitalized Patients with Heart Failure
(OPTIMIZE-HF) registry and performance-improvement program for patients hospi-
talized with heart failure at 259 US hospitals between March 2003 and December 2004.
Patients were divided into quartiles by SBP at hospital admission (⬍120, 120-139, 140-
161, and ⬎161 mm Hg). In-hospital outcomes were based on 48 612 patients aged
18 years or older with heart failure. Of the 41 267 patients with left ventricular func-
tion assessed, 21 149 (51%) had preserved left ventricular function. Postdischarge out-
comes were based on a prespecified subgroup (n=5791, 10% of patients) with fol-
low-up data assessed between 60 and 90 days.
Main Outcome Measures In-hospital and postdischarge mortality.
Results Patients with higher SBP were more likely to be female and black and to
have preserved systolic function. Fifty percent of the patients had SBP higher than 140
mm Hg at admission. Patients with lower SBP at admission had higher in-hospital and
postdischarge mortality rates. Higher SBP at admission was associated with lower in-
hospital mortality rates: 7.2% (⬍120 mm Hg), 3.6% (120-139 mm Hg), 2.5% (140-
161 mm Hg), and 1.7% (⬎161 mm Hg) (P⬍.001 for overall difference). Postdis-
charge mortality rates in the follow-up cohort by SBP at admission were 14.0%, 8.4%,
6.0%, and 5.4%, respectively (P⬍.001 for overall difference).
Conclusions Systolic hypertension is common in patients hospitalized for heart fail-
ure. Systolic blood pressure is an independent predictor of morbidity and mortality in
patients with heart failure with either reduced or relatively preserved systolic func-
tion. Low SBP (⬍120 mm Hg) at hospital admission identifies patients who have a
poor prognosis despite medical therapy. These findings may have important thera-
peutic implications because characteristics and outcomes differ greatly among pa-
tients with heart failure with varying SBP.
JAMA. 2006;296:2217-2226 www.jama.com
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not be representative of broad popula-
tions with AHFS.
4
Registries can pro-
vide complementary data to clinical
trials and may include patients that are
a more representative sampling of the
patient population of interest.
Based on the demographics of popu-
lations included in 6 recent acute heart
failure clinical trials, the conclusion
could be drawn that the majority of pa-
tients hospitalized for AHFS present
with low or normal systolic blood pres-
sure (SBP).
5-11
The mean SBP across
these studies ranged from 106 to 132
mm Hg. However, data from the Acute
Decompensated Heart Failure Na-
tional Registry (ADHERE) revealed that
the mean SBP at admission was higher
(144 mm Hg) among an unselected pa-
tient population than that observed in
randomized controlled trials.
2
El-
evated SBP was common in ADHERE,
with 50% of registry patients having ad-
mission values higher than 140
mm Hg.
2
Elevated SBP may identify patients
with certain clinical characteristics that
are unique from those in patients with
low SBP. Pathophysiological pro-
cesses may also differ between these
groups. Furthermore, patients with el-
evated SBP have been underrepre-
sented in acute heart failure clinical
trials. As a result, the relationship be-
tween SBP and clinical characteristics
is not known.
In this study, the first report of out-
comes from the Organized Program to
Initiate Lifesaving Treatment in Hos-
pitalized Patients with Heart Failure
(OPTIMIZE-HF) registry database, we
evaluated the relationship between SBP
at admission, clinical profile, and out-
comes in patients hospitalized for acute
heart failure.
METHODS
Data Collection and Hospitals
OPTIMIZE-HF was designed to evalu-
ate the use of evidence-based, guideline-
recommended therapy in patients hos-
pitalized for heart failure and to improve
the quality of care provided to these pa-
tients.
12
There were 2 components of
the study: a Web-based data collec-
tion and reporting system and a process-
of-care improvement program.
Data were collected by each site and
entered into the electronic data cap-
ture system. Data were collected on pa-
tient demographics, medical history,
signs, symptoms, medications, proce-
dures, and outcomes, as previously de-
scribed.
12
Systolic blood pressure at ad-
mission was defined as the supine
measurement first obtained after pre-
sentation to the emergency depart-
ment or, for patients directly admit-
ted, what was first recorded on the
medical ward. Admission staff, medi-
cal staff, or both recorded race/
ethnicity, usually as the patient was reg-
istered. Prior studies in patients
hospitalized with heart failure have sug-
gested differences in characteristics and
outcomes based on race/ethnicity.
Hospitals enrolled all consecutive pa-
tients meeting inclusion criteria or, if
there were more than 75 hospitaliza-
tions per month, were given the op-
tion of using an electronic sampling tool
that used a standard algorithm to gen-
erate a sample from an administrative
file upload. Automated electronic data
checks were used to prevent an “out-
of-range entry” (eg, SBP value ⬎300
mm Hg at admission), illogical data, or
duplicate patients. A database audit was
performed, based on predetermined cri-
teria, of a random sample of 5% of the
first 10 000 patients verified against
source documents. The process-of-
care improvement techniques con-
sisted of real-time data reports on per-
formance indicators and periodic
educational programs. The registry data
coordinating center was Outcome Sci-
ences Inc (Cambridge, Mass). All sta-
tistical analyses were performed inde-
pendently by Duke Clinical Research
Institute, Durham, NC.
Patients and Outcomes
Patients aged 18 years or older with a
discharge diagnosis of heart failure were
eligible for enrollment. Patients with left
ventricular systolic dysfunction (LVSD)
and preserved systolic function were in-
cluded. Patients were considered to
have preserved systolic function if left
ventricular ejection fraction was docu-
mented as 40% or higher or if they were
described as having left ventricular sys-
tolic function that was qualitatively nor-
mal or mildly impaired. Patients were
considered to have LVSD if they had left
ventricular ejection fraction of less than
40% or moderate to severe left ven-
tricular dysfunction by qualitative
assessment.
The incidence of death or rehospi-
talization within 60 to 90 days was pro-
spectively collected on a prespecified
10% subset of the total OPTIMIZE-HF
population. Sites had the option of par-
ticipating in the collection of fol-
low-up data. The protocol was ap-
proved by each participating center’s
institutional review board or through
use of a central institutional review
board. Written informed consent was
obtained prior to enrollment from pa-
tients who participated during the fol-
low-up period.
Statistical Analyses
Data are reported as mean (SD) for con-
tinuous variables or number (percent-
ages) of patients for categorical vari-
ables. Admission SBP values were
prospectively categorized into quar-
tiles. Overall tests of any differences in
patient characteristics and evidence-
based treatments were compared us-
ing the Pearson ␹
2
test for categorical
variables and analysis of variance for
continuous variables.
In-hospital mortality and the com-
posite of postdischarge mortality or re-
hospitalization were analyzed using lo-
gistic regression modeling techniques.
Analysis of variance was used for the
length of stay analyses. To account for
differential follow-up, Cox propor-
tional hazards modeling was used for
postdischarge mortality. The propor-
tional hazards assumption was evalu-
ated, and if a factor was found to be
nonproportional it was included as a
stratum.
Models had been previously devel-
oped to predict the risk of 4 outcomes
of interest. These were used when per-
forming adjusted models of these risks.
Only baseline factors were used for the
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2 in-hospital events (in-hospital mor-
tality and length of stay). In addition,
in-hospital treatments and events were
included when modeling the 2 post-
discharge outcomes. The variables for
the 4 multivariable models include the
following.
For the in-hospital mortality model,
we included the following variables: age
per 10-year increase, black race, heart
rate per 10/min increase (range, 65-
110/min), SBP per 10-mm Hg in-
crease (ⱕ160 mm Hg), diastolic blood
pressure per 10-mm Hg increase (ⱕ100
mm Hg), sodium level per 3-mEq/L de-
crease (ⱕ140 mEq/L and ⬎140 mEq/
L), serum creatinine level per 1-mg/dL
increase (⬎3.5 mg/dL [⬎309.4 µmol/
L]), hemoglobin level per 1-g/dL de-
crease (⬍13 g/dL and ⱖ13 g/dL), pri-
mary cause of hospital admission, prior
cerebrovascular accident or transient is-
chemic attack, hyperlipidemia, hyper-
tension, liver disease, smoker within
past year, chronic obstructive pulmo-
nary disease, peripheral vascular dis-
ease, no known heart failure prior to
this admission, rales, and LVSD.
For the length of stay model, we in-
cluded the following variables: age per
10-year increase (⬍80 years and ⱖ80
years), sex, weight per 10-kg increase,
heart rate per 10/min increase (ⱖ70/
min), SBP per 10-mm Hg increase
(⬍160 mm Hg), serum creatinine level
per 1-mg/dL increase (⬍3.5 mg/dL
[⬍309.4 µmol/L] and ⱖ3.5 mg/dL
[ⱖ309.4 µmol/L]), implantable car-
diac defibrillator, sodium level per
3-mEq/L decrease (⬍140 mEq/L and
ⱖ140 mEq/L), hemoglobin level per
1-g/dL decrease (⬍13 g/dL), primary
cause of hospital admission, coronary
artery disease or ischemic heart dis-
ease, renal disorder, atrial arrhythmia,
prior cerebrovascular accident or tran-
sient ischemic attack, depression, dia-
betes (insulin dependent), hyperlipi-
demia, chronic obstructive pulmonary
disease, pulmonary hypertension, pe-
ripheral vascular disease, ventricular ar-
rhythmia, lower extremity edema, and
LVSD.
For the postdischarge mortality
model, we included the following vari-
Table 1. Patient Characteristics*
Overall Registry
(n = 48 612)
Follow-up Cohort
(n = 5791)
Age, mean (SD), y 73.1 (14.2) 72.0 (14.1)
Male sex 23 537 (48) 2965 (51)
Black race 8608 (18) 1044 (18)
Ischemic etiology 22 219 (46) 2435 (42)
Hypertensive etiology 11 181 (23) 1827 (32)
LVSD† 20 118 (48.8) 2720 (53.2)
Left ventricular ejection fraction, mean (SD), % 39.0 (17.6) 36.9 (17.0)
No known prior heart failure 5675 (12) 697 (12)
Implantable cardioverter-defibrillator during hospitalization 975 (2) 187 (3)
Atrial fibrillation 14 970 (31) 1948 (34)
Medications prior to admission
ACE inhibitor 19 273 (40) 2409 (42)
Aldosterone antagonist 3449 (7) 455 (8)
Amlodipine 3850 (8) 379 (7)
Angiotensin receptor blocker 5704 (12) 719 (12)
Antiarrhythmic 5035 (10) 720 (12)
Aspirin 19 217 (40) 2352 (41)
␤-Blocker 25 800 (53) 3161 (55)
Digoxin 11 369 (23) 1417 (24)
Loop diuretic 29 683 (61) 3544 (61)
Hydralazine 1504 (3) 143 (2)
Statin‡ 14 672 (39) 1872 (40)
Nitrate 10 499 (22) 1276 (22)
Intravenous medications during hospitalization
Any inotrope 3564 (7) 414 (7)
Nesiritide 5225 (11) 597 (10)
Other intravenous vasodilator 1650 (3) 170 (3)
Weight change from admission to discharge, mean (SD), kg −2.6 (9.1) −2.6 (8.6)
B-type natriuretic peptide, mean (SD), pg/mL 1272.91 (1330.07) 1290.65 (1295.32)
Creatinine level, mean (SD), mg/dL
At admission 1.8 (1.8) 1.7 (1.4)
At discharge 1.8 (1.4) 1.7 (1.2)
Systolic blood pressure, mean (SD), mm Hg
Overall at admission 142.6 (33.2) 140.3 (32.8)
At admission in patients with LVSD 135.2 (30.9) 133.2 (30.1)
At discharge 124.3 (24.0) 122.5 (25.2)
Change from admission to discharge −18.4 (30.6) −17.1 (29.7)
Edema
At admission 30 710 (65) 3686 (65)
At discharge 10 395 (27) 1209 (24)
Rales
At admission 30 546 (64) 3522 (62)
At discharge 6292 (15) 658 (13)
Dyspnea at admission
On exertion 29 856 (61) 3670 (63)
At rest 21 279 (44) 2559 (44)
Heart rate, mean (SD), beats/min
At admission 87 (21.5) 86 (21.3)
At discharge 75.9 (15.0) 75.8 (14.5)
Sodium, mean (SD), mEq/L 136.7 (11.0) 136.8 (9.2)
Hemoglobin, mean (SD), g/dL 12.1 (3.4) 12.2 (2.3)
Orthopnea at admission 13 298 (27) 2051 (35)
Paroxysmal nocturnal dyspnea at admission 7338 (15) 1277 (22)
Abbreviations: ACE, angiotensin-converting enzyme; LVSD, left ventricular systolic dysfunction.
SI conversion factor: To convert creatinine to µmol/L, multiply by 88.4.
*Values are expressed as number (percentage) unless otherwise indicated.
†The number (percentage) of those with LVSD assessed. Defined as left ventricular ejection fraction of less than 40% or
moderate to severe LVSD.
‡Statin use in patients with medical history of coronary artery disease, cerebrovascular accident or transient ischemic at-
tack, diabetes, hyperlipidemia, or peripheral vascular disease.
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ables: SBP per 10-mm Hg increase
(⬍140 mm Hg and ⱖ140 mm Hg) at
admission, serum creatinine level lower
than 4 mg/dL per unit increase (⬍4
mg/dL [⬍353.6 µmol/L]) at admis-
sion, age per 10-year increase, reactive
airway disease, weight per 10-kg in-
crease, lower extremity edema, lipid-
lowering agent at discharge, sodium
level per 1-mEg/L increase (⬍140 mEq/
L), depression, any ␤-blocker use at dis-
charge, SBP per 10-mm Hg increase
(⬍130 mm Hg) at discharge, serum
creatinine level per 1-mg/dL increase
(⬍3 mg/dL [⬍265.2 µmol/L]) at dis-
charge, and liver disease.
For the postdischarge mortality and
rehospitalization model, we included
the following variables: hemoglobin
level at admission (all levels ⬍11 have
equal risk), serum creatinine level at ad-
mission (ⱕ3.8 mg/dL [ⱕ335.9 µmol/
L]), diuretic use at admission, chronic
obstructive pulmonary disease, heart
failure hospitalization in past 6 mo (yes/
no), nitrate use at admission, digoxin
use at admission, prior cerebrovascu-
lar accident or transient ischemic at-
tack, SBP per increments of 10 mm Hg,
coronary angiography performed dur-
ing hospitalization, angiotensin recep-
tor blocker use at discharge, mechani-
cal ventilation performed during
hospitalization, angiotensin-convert-
ing enzyme inhibitor use at discharge,
implantable cardiac defibrillator placed
during hospitalization, and lipid-
lowering agent use at discharge.
For each of the 4 outcomes, a simi-
lar modeling process was used. The as-
sumption of linearity was evaluated for
the continuous measures using re-
stricted cubic splines and when vio-
lated appropriate transformations were
applied. Both forward stepwise and
backward variable selection tech-
niques were applied to the data with a
value of .05 for both inclusion and re-
maining in the model. The forward
stepwise selection process was also
bootstrapped using 200 samples. The
final factors for a model must have been
selected by at least 1 of the 2 selection
methods and at least 50% of the boot-
strapped samples.
If SBP was not selected as 1 of the co-
variates in the model, it was included
to evaluate the association of this fac-
tor with outcome after adjusting for po-
tential confounders. The c statistic was
0.77 for the in-hospital model and 0.74
for the postdischarge model. For all sta-
tistical analyses, SAS software version
8.2 (SAS Institute Inc, Cary, NC) was
used. With the large sample size of the
hospital cohort, one would expect sta-
tistical significances with small differ-
ences. No adjustment has been made
for multiple comparisons, which should
be considered in the interpretation of
the P values.
RESULTS
OPTIMIZE-HF enrolled 48 612 pa-
tients (T
ABLE 1) between March 2003
and December 2004 from 259 hospi-
tals across the United States. Aca-
demic and community-based centers of
all sizes and from all regions of the
country were represented (T
ABLE 2).
The mean age of the overall cohort
was 73 years; 52% were women and
74% were white. Of the 48 612 pa-
tients, 41 267 (84.9%) had data for left
ventricular ejection fraction or a quali-
tative assessment of left ventricular
function. Of the patients with left ven-
tricular function assessed, 20 118 (49%)
had LVSD and 21 149 (51.2%) had
heart failure with preserved systolic
function. Systolic blood pressure at ad-
mission was missing in 45 (0.1%) of
48 612 patients.
At the 91 hospitals in the follow-up
cohort, there were 19 082 potential pa-
tients for follow-up, of whom 6121 pro-
vided informed consent and were en-
rolled. Of these patients, follow-up data
was unavailable for 330, resulting in
5791 patients in the follow-up popu-
lation. The characteristics of the fol-
low-up cohort were similar to the over-
all hospital cohort (Table 1).
The mean (SD) SBP at admission in
the total cohort was 143 (33) mm Hg.
Fifty percent of the patients had SBP at
admission that was higher than 140
mm Hg. Systolic blood pressure at ad-
mission was higher than 140 mm Hg
in 38% of the patients with LVSD and
in 56% of patients without LVSD. Pa-
tients were categorized into quartiles
based on their admission SBP values
(T
ABLE 3). Quartile 1 included 12 252
patients with SBP below 120 mm Hg;
quartile 2, 12 096 patients with SBP in
the range of 120 to 139 mm Hg; quar-
tile 3, 12 099 patients with SBP in the
range of 140 to 161 mm Hg; and quar-
tile 4, 12 120 patients with SBP higher
than 161 mm Hg.
Patient characteristics differed across
admission SBP quartiles (Table 3). Spe-
cifically, more patients in the higher SBP
quartiles (140-161 mm Hg and ⬎161
mm Hg) had preserved systolic func-
tion. A higher proportion of patients in
the higher admission SBP quartiles were
black. Other statistically significant dif-
ferences were observed that may or may
not be of clinical relevance because of
the large numbers of patients (Table 3).
For instance, a larger proportion of pa-
tients were classified as having new-
onset heart failure in the higher SBP
quartiles. The mean change in SBP from
admission to discharge was different in
each quartile, although all changes were
statistically significant. In the quartile
with the lowest SBP values at admis-
sion (⬍120 mm Hg), there was a mean
increase of approximately 6.5 mm Hg
from admission to discharge. In the next
3 quartiles, mean SBP was reduced from
admission to discharge: quartile 2, −8.7;
quartile 3, −21.3; quartile 4, −49.2.
Table 2. Hospital Characteristics
No. (%) of Hospitals
Total
(n = 259)
Follow-up
(n = 91)
Bed size
0-99 31 (12) 9 (10)
100-249 58 (22) 21 (23)
250-499 103 (40) 40 (44)
500-749 38 (15) 13 (14)
ⱖ750 13 (5) 4 (4)
Unknown 16 (6) 4 (4)
Academic 118 (48) 48 (55)
Transplant program 34 (14) 9 (10)
Interventional
(CABG surgery/PCI)
163 (67) 62 (70)
Region
Midwest 68 (27) 27 (30)
Northeast 44 (17) 14 (16)
South 87 (34) 34 (38)
West 56 (22) 15 (17)
Abbreviations: CABG, coronary artery bypass graft; PCI, per-
cutaneous coronary intervention.
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Table 3. Demographics by Systolic Blood Pressure at Admission*
Systolic Blood Pressure Quartile, mm Hg
⬍120
(n = 12 252)
120-139
(n = 12 096)
140-161
(n = 12 099)
⬎161
(n = 12 120)
Age, mean (SD), y 72.9 (14) 74 (13.5) 73.8 (13.6) 72.1 (14.6)
Female sex 5314 (43.4) 5941 (49.1) 6683 (55.2) 7112 (58.7)
Black race 1525 (12.4) 1688 (14.0) 2279 (18.8) 3111 (25.7)
Left ventricular systolic dysfunction† 6612 (62.8) 5367 (52.2) 4530 (44.1) 3585 (35.3)
Left ventricular ejection fraction, mean (SD), % 33.3 (17.4) 37.8 (17.6) 40.9 (17.1) 44.4 (16.5)
Ischemic etiology 6210 (50.7) 5903 (48.8) 5332 (44.1) 4753 (39.2)
Hypertensive etiology 1645 (13.4) 2190 (18.1) 3071 (25.4) 4216 (34.8)
No known prior heart failure 1034 (8.4) 1334 (11) 1565 (12.9) 1742 (14.4)
Atrial arrhythmia 4365 (35.6) 4099 (33.9) 3692 (30.5) 2798 (23.1)
Implantable cardioverter-defibrillator during hospitalization 1140 (9.3) 630 (5.2) 436 (3.6) 276 (2.3)
Medications prior to admission
ACE inhibitor 5021 (41.0) 4677 (38.7) 4668 (38.6) 4897 (40.4)
Aldosterone antagonist 1448 (11.8) 955 (7.9) 630 (5.2) 413 (3.4)
Amlodipine 503 (4.1) 862 (7.1) 1110 (9.2) 1374 (11.3)
Angiotensin receptor blocker 1275 (10.4) 1309 (10.8) 1403 (11.6) 1713 (14.1)
Antiarrhythmic 1714 (14.0) 1312 (10.8) 1106 (9.1) 899 (7.4)
Aspirin 4909 (40.1) 4801 (39.7) 4841 (40.0) 4649 (38.4)
␤-Blocker 6624 (54.1) 6197 (51.2) 6318 (52.2) 6634 (54.7)
Digoxin 3710 (30.3) 3019 (25.0) 2585 (21.4) 2041 (16.8)
Loop diuretic 8536 (69.7) 7639 (63.2) 7184 (59.4) 6294 (51.9)
Hydralazine 274 (2.2) 311 (2.6) 376 (3.1) 541 (4.5)
Statin 3871 (31.6) 3876 (32.0) 3868 (32.0) 3806 (31.4)
Nitrate 2527 (20.6) 2635 (21.8) 2662 (22.0) 2668 (22.0)
Intravenous medications during hospitalization
Any inotrope 1838 (15.0) 786 (6.5) 549 (4.5) 384 (3.2)
Nesiritide 1571 (12.8) 1315 (10.9) 1197 (9.9) 1137 (9.4)
Other intravenous vasodilator 263 (2.1) 301 (2.5) 375 (3.1) 709 (5.8)
Creatinine, mean (SD), mg/dL
At admission 1.8 (1.2) 1.6 (1.2) 1.7 (1.5) 2.0 (2.1)
At discharge 1.6 (1.1) 1.6 (1.1) 1.7 (1.5) 2.0 (2.1)
B-type natriuretic peptide, mean (SD), pg/mL 1416 (1429) 1229 (1289) 1197 (1268) 1271 (1316)
Weight change from admission to discharge, mean (SD), kg –2.5 (5) –2.7 (4.8) –2.6 (4.6) –2.4 (4.6)
Systolic blood pressure, mean (SD), mm Hg
At admission 105 (11) 129 (6) 150 (6) 187 (22)
Left ventricular systolic dysfunction (n = 6612)
104 (11)
(n = 5367)
129 (6)
(n = 4530)
149 (6)
(n = 3585)
185 (20)
At discharge 112 (19) 121 (19) 128 (20) 138 (23)
Change from admission to discharge 6.5 (19.9) –8.7 (19.3) –21.3 (20.6) –49.2 (28.5)
Diastolic blood pressure, mean (SD), mm Hg
At admission 62 (12) 72 (13) 79 (15) 92 (20)
At discharge 63 (11) 66 (12) 68 (13) 71 (14)
Change from admission to discharge 0.45 (14.7) −6.1 (15.3) −11.4 (16.8) −22.4 (20.8)
Heart rate, mean (SD), beats/min
At admission 85 (21) 86 (21) 86 (21) 90 (22)
At discharge 78 (15) 77 (14) 75 (14) 74 (13)
Edema
At admission 7630 (63.9) 7708 (65.1) 7769 (65.6) 7588 (63.9)
At discharge 2817 (30.1) 2610 (27.1) 2637 (27.0) 2329 (23.8)
Rales
At admission 7207 (60.3) 7450 (62.8) 7755 (65.2) 8116 (67.9)
At discharge 1794 (18.2) 1552 (15.3) 1554 (15.1) 1389 (13.4)
Dyspnea at admission
At rest 5259 (42.9) 5261 (43.5) 5238 (43.3) 5485 (45.3)
On exertion 7294 (59.5) 7377 (61.0) 7508 (62.1) 7642 (63.1)
Orthopnea at admission 3089 (25.2) 3293 (27.2) 3376 (27.9) 3538 (29.2)
Paroxysmal nocturnal dyspnea at admission 1726 (14.1) 1782 (14.7) 1882 (15.6) 1945 (16.0)
Abbreviation: ACE, angiotensin-converting enzyme.
SI conversion factor: To convert creatinine to µmol/L, multiply by 88.4.
*Values are expressed as number (percentage) unless otherwise indicated.
†Defined as left ventricular ejection fraction of less than 40% or moderate to severe left ventricular dysfunction.
BLOOD PRESSURE AND OUTCOMES IN HEART FAILURE
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Parenteral inotropes or vasodilators
were used more often for patients in the
lower SBP quartiles. The use of any ino-
trope decreased from 15% in the low-
est SBP quartile to 3% in the highest SBP
quartile (P⬍.001). Nesiritide use also
decreased with increasing SBP but to a
lesser extent. Nesiritide was pre-
scribed in 12.8% of patients in the low-
Table 4. Clinical Event Rates by Systolic Blood Pressure at Admission and Left Ventricular Systolic Dysfunction*
Systolic Blood Pressure Quartile, mm Hg P Value
Across
Quartiles⬍120 120-139 140-161 ⬎161
Overall cohort (n = 48 612)† (n = 12 252) (n = 12 096) (n = 12 099) (n = 12 120)
In-hospital mortality 7.2 (6.7-7.6) 3.6 (3.3-4.0) 2.5 (2.2-2.7) 1.7 (1.5-2.0) ⬍.001
Length of stay, mean (95% CI), d 6.5 (6.4-6.6) 5.7 (5.6-5.8) 5.4 (5.3-5.5) 5.1 (5.0-5.2) ⬍.001
Follow-up cohort (n = 5791)‡ (n = 1557) (n = 1469) (n = 1429) (n = 1325)
Postdischarge mortality 14.0 (12.2-15.7) 8.4 (7.0-9.8) 6.0 (4.7-7.2) 5.4 (4.2-6.7) ⬍.001
Rehospitalization for 60-90 d 30.6 (28.3-32.9) 29.9 (27.5-32.2) 30.3 (27.9-32.7) 27.6 (25.2-30.0) .31
Subgroup with left ventricular function measured (n = 41 267)§ (n = 10 525) (n = 10 276) (n = 10 263) (n = 10 161)
In-hospital mortality 6.5 (6.0-6.9) 3.2 (2.8-3.5) 2.2 (2.0-2.5) 1.5 (1.2-1.7) ⬍.001
Length of stay, mean (95% CI), d 6.7 (6.6-6.8) 5.9 (5.8-6.0) 5.6 (5.5-5.7) 5.2 (5.1-5.3) ⬍.001
Follow-up cohort with left ventricular function measured (n = 4959)‡ (n = 1336) (n = 1259) (n = 1240) (n = 1113)
Postdischarge mortality 13.6 (11.8-15.5) 8.2 (6.7-9.7) 5.5 (4.2-6.8) 4.5 (3.3-5.7) ⬍.001
Rehospitalization for 60-90 d 30.6 (28.2-33.1) 29.9 (27.4-32.4) 30.3 (27.8-32.9) 27.2 (24.6-29.8) .23
Patients with left ventricular systolic dysfunction (n = 20 118)㛳 (n = 6612) (n = 5367) (n = 4530) (n = 3585)
In-hospital mortality 6.6 (6.0-7.2) 3.1 (2.6-3.6) 2.5 (2.1-3.0) 1.6 (1.2-2.0) ⬍.001
Length of stay, mean (95% CI), d 6.8 (6.6-6.9) 5.8 (5.8-5.9) 5.6 (5.4-5.7) 5.1 (4.9-5.1) ⬍.001
Postdischarge mortality 13.0 (10.8-15.2) 6.8 (5.0-8.7) 6.3 (4.4-8.2) 4.1 (2.2-6.0) ⬍.001
Rehospitalization for 60-90 d 31.5 (28.5-34.5) 28.6 (25.4-31.9) 32.4 (28.7-36.1) 25.5 (21.3-29.6) .15
No left ventricular systolic dysfunction (n = 21 149)¶ (n = 3913) (n = 4909) (n = 5733) (n = 6576)
In-hospital mortality 6.2 (5.4-6.9) 3.2 (2.7-3.7) 2.0 (1.6-2.4) 1.4 (1.1-1.7) ⬍.001
Length of stay, mean (95% CI), d 6.5 (6.3-6.6) 5.9 (5.7-6.0) 5.5 (5.4-5.7) 5.3 (5.2-5.4) ⬍.001
Postdischarge mortality 14.9 (11.6-18.2) 10.0 (7.4-12.5) 4.7 (3.1-6.4) 4.7 (3.2-6.3) ⬍.001
Rehospitalization for 60-90 d 29 (24.9-33.1) 31.6 (27.8-35.5) 28.4 (25.0-31.9) 28.2 (24.9-31.5) .44
Abbreviation: CI, confidence interval.
*Values are expressed as percentage (95% CI) unless otherwise indicated.
†Systolic blood pressure at admission was missing in 45 patients.
‡Systolic blood pressure at admission was missing in 11 patients.
§Systolic blood pressure at admission was missing in 42 patients.
㛳Systolic blood pressure at admission was missing in 24 patients.
¶Systolic blood pressure at admission was missing in 18 patients.
Table 5. In-Hospital Mortality Risk by Systolic Blood Pressure Quartiles in Patients Receiving Parenteral Inotropic Agents, Vasodilators, or Neither*
Systolic Blood Pressure Quartile, mm Hg
P Value
Across
Quartiles
⬍120
(n = 12 252)
120-139
(n = 12 096)
140-161
(n = 12 099)
⬎161
(n = 12 120)
Overall cohort, No. of hospital deaths/
No. of patients in SBP quartile (N=48 612)
881/12 252 441/12 096 297/12 099 209/12 120
In-hospital death 7.2 (6.7-7.6) 3.6 (3.3-4.0) 2.5 (2.2-2.7) 1.7 (1.5-2.0) ⬍.001
Patients with no parenteral therapies, No. of
hospital deaths/No. of patients in SBP
quartile (n = 39 401)
490/9058 306/9959 186/10 226 138/10 126
In-hospital death 5.4 (4.9-5.9) 3.1 (2.7-3.4) 1.8 (1.6-2.1) 1.4 (1.1-1.6) ⬍.001
Patients with inotropes, No. of hospital deaths/
No. of patients in SBP quartile (n = 2620)†‡
252/1404 64/569 45/375 26/265
In-hospital death 17.9 (15.9-20.0) 11.2 (8.7-13.8) 12.0 (8.7-15.3) 9.8 (6.2-13.4) ⬍.001
Patients with vasodilators, No. of hospital deaths/
No. of patients in SBP quartile (n = 5647)‡§
60/1356 36/1351 40/1324 33/1610
In-hospital death 4.4 (3.3-5.5) 2.7 (1.8-3.5) 3.0 (2.1-3.9) 2.0 (1.4-2.7) .002
Abbreviation: SBP, systolic blood pressure.
*Values are expressed as percentage (95% confidence interval) unless otherwise indicated. Systolic blood pressure at admission was missing in 45 (0.1%) of 48 612 patients.
†Inotropes indicate dobutamine, milrinone, and dopamine.
‡Patients with both inotropes and vasodilators are excluded.
§Vasodilators indicate nesiritide or other intravenous vasodilator.
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est SBP quartile and 9.4% in the high-
est SBP quartile (P⬍.001). Other
intravenous vasodilators were used
more often in the higher SBP quartiles
(2.1% in the lowest vs 5.8% in the high-
est quartile; P⬍.001). Overall, di-
uretic use at admission was highest
(73.3%) in patients in the lowest SBP
quartile and much lower (57.4%) in pa-
tients in the highest SBP quartile
(P⬍.001).
The in-hospital mortality rate was
3.8% in the entire cohort and the mean
length of stay was 6.4 days. Higher SBP
at admission was associated with sub-
stantially lower in-hospital mortality:
7.2% (⬍120 mm Hg), 3.6% (120-139
mm Hg), 2.5% (140-161 mm Hg), and
1.7% (⬎161 mm Hg) (P⬍.001 for over-
all difference; c statistic=0.65; T
ABLE 4).
Lower SBP (⬍120 mm Hg) at admis-
sion was associated with higher in-
hospital mortality risk in patients re-
ceiving parenteral inotropic agents,
vasodilators, or neither (T
ABLE 5).
In the follow-up cohort, higher SBP at
admission was also associated with lower
60- to 90-day mortality (c statis-
tic=0.61) (Table 4). While higher ad-
mission SBP was associated with shorter
length of stay (r=0.01), rehospitaliza-
tion rates during follow-up were simi-
lar regardless of SBP at admission: 30.6%
(⬍120 mm Hg), 29.9% (120-139
mm Hg), 30.3% (140-161 mm Hg), and
27.6% (⬎161 mm Hg) (P =.31). The as-
sociation between SBP and clinical events
was not statistically significantly differ-
ent among patients with and without sys-
tolic dysfunction (Table 4).
A monotonic relationship was ob-
served when the association between
SBP at admission and in-hospital mor-
tality was examined further by SBP
deciles and restricted cubic splines, with
no suggestion of increased mortality
even with extremely high SBP at ad-
mission (F
IGURE).
Admission SBP was a significant pre-
dictor of in-hospital and postdis-
charge mortality after adjusting for
other factors. The odds of in-hospital
death increased 21% for each 10-
mm Hg decrease in SBP below 160
mm Hg (odds ratio, 1.21; 95% confi-
dence interval [CI], 1.17-1.25). The in-
hospital mortality risk did not change
for SBP above 160 mm Hg. Admission
SBP also independently predicted post-
discharge mortality, with an 18% in-
crease in hazard ratio for each 10-
mm Hg decrease in SBP (hazard ratio,
1.18; 95% CI, 1.10-1.26). For SBP above
140 mm Hg, the increase in risk with
each 10-mm Hg decrease in SBP was
8%, which was statistically significant
(hazard ratio, 1.08; 95% CI, 1.01-
1.15). Across all values of SBP, the odds
for the composite of mortality and re-
hospitalization increased 5% with each
10-mm Hg decrease in SBP (odds ra-
tio, 1.05; 95% CI, 1.03-1.07). Inclu-
Figure. In-Hospital Mortality Rates by Admission Systolic Blood Pressure Deciles (n = 48 567)
10
11
3
6
5
4
7
8
9
2
1
0
Admission Systolic Blood Pressure Deciles, mm Hg (N
=
48
567)
In-Hospital Mortality, %
50-104 105-114 115-123 124-131 132-139 140-147 148-156 157-168 169-188 189-300
P⬍.001 for trend across deciles. Error bars indicate 95% confidence intervals.
Table 6. Performance Measures at Discharge by Systolic Blood Pressure at Admission
Systolic Blood Pressure Quartile, mm Hg
% (95% Confidence Interval)
P Value
Across
Quartiles
⬍120
(n = 10 525)
120-139
(n = 10 276)
140-161
(n = 10 263)
⬎161
(n = 10 161)
At discharge
Instructions 57.0 (55.9-58.2) 54.9 (53.8-56.0) 53.6 (52.5-54.6) 50.2 (49.2-51.2) ⬍.001
Left ventricular function assessment 87.7 (87.0-88.3) 86.7 (86.1-87.4) 86.2 (85.5-86.8) 85.5 (84.9-86.2) ⬍.001
ACE inhibitor 73.0 (71.7-74.4) 75.3 (74.0-76.7) 76.1 (74.7-77.5) 77.8 (76.3-79.4) ⬍.001
ACE inhibitor or ARB 79.9 (78.7-81.1) 82.2 (81.0-83.4) 84.0 (82.8-85.2) 85.8 (84.5-87.1) ⬍.001
Smoking cessation counseling 63.4 (61.0-65.8) 63.5 (61.1-65.8) 62.3 (59.9-64.7) 61.2 (59.0-63.4) .46
␤-Blocker 81.6 (80.5-82.7) 82.7 (81.6-83.9) 84.0 (82.9-85.2) 85.0 (83.7-86.2) ⬍.001
Warfarin in atrial fibrillation 55.0 (53.4-56.7) 53.1 (51.5-54.8) 53.1 (51.4-54.9) 46.3 (44.4-48.3) ⬍.001
Statin* 36.5 (35.5-37.5) 39.0 (38.1-40.0) 39.9 (38.9-40.9) 41.2 (40.2-42.1) ⬍.001
Aldosterone antagonist† 20.6 (19.6-21.5) 18.1 (17.1-19.1) 17.1 (16.0-18.2) 14.4 (13.2-15.5) ⬍.001
Abbreviations: ACE, angiotensin-converting enzyme; ARB, angiotensin receptor blocker.
*Use among patients with coronary artery disease, cerebrovascular disease or transient ischemic attack, diabetes, hyperlipidemia, or peripheral vascular disease.
†Use among patients with left ventricular systolic dysfunction.
BLOOD PRESSURE AND OUTCOMES IN HEART FAILURE
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sion of intravenous medications dur-
ing hospitalizations and discharge oral
medications in the multivariable mod-
els for postdischarge mortality showed
that admission SBP was still a signifi-
cant predictor of mortality at 60 to 90
days, independent of medications and
other variables.
The association between SBP at
admission and performance indica-
tors and the use of evidence-based
therapies are shown in T
ABLE 6.
Associations were observed between
admission SBP and several perfor-
mance indicators as well as the use of
evidence-based therapies.
COMMENT
The OPTIMIZE-HF data provide insight
into the characteristics of a broad popu-
lation of patients with acute heart fail-
ure. These results provide evidence that
elevated SBP is common in patients hos-
pitalized for ADHS, including patients
with reduced systolic function. These
data are consistent with the findings from
other registries such as ADHERE and
Enhanced Feedback for Effective Car-
diac Treatment (EFFECT).
2,13
How-
ever, these observations are in contrast
with data from clinical trials that sug-
gest patients hospitalized with AHFS are
most commonly admitted with low or
normal SBP.
Furthermore, this analysis demon-
strates that SBP at hospital admission,
a readily accessible vital sign, is an im-
portant and independent predictor of
morbidity and mortality in patients with
heart failure, including patients with re-
duced or relatively preserved systolic
function. Systolic blood pressure at hos-
pital admission can effectively iden-
tify groups of patients that differ with
respect to clinical characteristics, prog-
nosis, and perhaps underlying patho-
physiology. Accordingly, the therapeu-
tic approach may vary among patients
with high, normal, or low SBP.
Several notable differences were ob-
served in patient characteristics across
SBP quartiles. For example, the pro-
portion of women within each quar-
tile increased as SBP increased. The pro-
portion of black patients was also
greater in the higher SBP quartiles. A
lower proportion of patients had an is-
chemic etiology in the higher SBP quar-
tiles. Left ventricular systolic dysfunc-
tion was more prevalent in the lower
SBP quartiles. These observations are
consistent with the existing data that
hypertension is most prevalent in
women and blacks, and is more often
associated with preserved systolic func-
tion.
14-16
Patients with elevated SBP at hos-
pital admission may have a better
response to in-hospital treatments for
acute heart failure. At admission,
congestive symptoms were more
common in the higher SBP quartiles.
However, by the time of discharge,
these symptoms were less common
in the higher SBP quartiles and more
common in the lower SBP quartiles.
In addition, elevated SBP did not
appear to persist for the duration of
the hospitalization. By the time of
discharge, the overall mean SBP
decreased from baseline. Systolic
blood pressure also decreased from
baseline within quartiles 2, 3, and 4,
and increased from baseline within
quartile 1. These observations sug-
gest that patients with elevated SBP
tended to respond to treatments
administered during hospitalization
from the standpoint of symptom
resolution and reduction in SBP.
Elevated SBP also signaled a group
of patients who were prognostically dif-
ferent from those with lower SBP.
Higher SBP was associated with better
in-hospital and short-term (60-90 days)
survival. Even patients with ex-
tremely high (188-300 mm Hg) SBP at
admission had a low risk for in-
hospital mortality. Patients with SBP be-
low 120 mm Hg at admission were at
particularly high risk with a com-
bined in-hospital and early postdis-
charge mortality risk of 21.2%. How-
ever, even among normotensive patients
(SBP of 120-139 mm Hg), the com-
bined in-hospital and postdischarge
mortality was substantial at 12%. These
patients were treated with angiotensin-
converting enzyme inhibitors and
␤-blockers, but this mortality rate per-
sisted. This observation emphasizes the
need to implement other evidence-
based strategies in an effort to reduce
mortality.
The finding that SBP was a signifi-
cant predictor of outcome is consistent
with other studies that have demon-
strated the prognostic importance of
SBP.
17-20
These studies have reported ad-
justed relative risks for mortality rang-
ing from 0.78 to 0.90 for each 10-
mm Hg increase in SBP.
17,18,20
The
association between SBP and mortality
in OPTIMIZE-HF was similar, with an
adjusted relative in-hospital mortality
risk of 0.83 for each 10-mm Hg in-
crease in SBP up to 160 mm Hg and an
adjusted follow-up mortality risk of 0.85
for each 10-mm Hg increase in SBP up
to 140 mm Hg. Short-term readmis-
sion rates were high regardless of SBP.
Thus, patients with an elevated SBP at
admission are at high risk of subse-
quent morbid events even though they
appear to have a much lower short-
term mortality risk. Physicians may per-
ceive that a patient with normal or bor-
derline-high SBP and heart failure is less
severely ill than a hypotensive patient
with heart failure. While this supposi-
tion may be accurate with regard to mor-
tality, it does not appear to be true for
morbid events. Physicians should rec-
ognize that these patients are at high risk
of rehospitalization and should aggres-
sively manage their disease in an effort
to reduce recurrent hospitalizations.
This analysis focused on SBP be-
cause previous studies found less of a
relationship between diastolic blood
pressure and outcomes in patients with
acute heart failure.
19
Diastolic blood
pressure at admission was included in
the in-hospital mortality model but it
was less predictive of mortality than
SBP. More importantly, SBP at admis-
sion was predictive of outcome inde-
pendently of diastolic blood pressure.
The findings from this analysis may
provide insight into the pathophysi-
ological processes that occur in AHFS.
It has been hypothesized that the el-
evated SBP at admission observed in the
majority of AHFS patients may be re-
lated to neurohormonal and cytokine
BLOOD PRESSURE AND OUTCOMES IN HEART FAILURE
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activation resulting in increased after-
load.
3
Patients with this clinical pre-
sentation may be those with early or
mid-stage disease. The pathophysiol-
ogy may differ in patients presenting
with low SBP, who may be more likely
to have advanced or end-stage disease
with low cardiac output and signs of or-
gan hypoperfusion.
3
Systolic blood pres-
sure may be a marker for a different
stage of the disease or for a different
pathophysiology altogether.
Recognizing SBP as a signal of the un-
derlying pathophysiological process has
important implications for future stud-
ies investigating treatment approaches.
These data from OPTIMIZE-HF dem-
onstrate that clinical characteristics and
outcomes differ substantially between
patients with higher and lower SBP.
These groups could potentially be
viewed as 2 unique populations. Thus,
clinical trials should be designed to limit
enrollment to only 1 patient type based
on SBP or should stratify enrollment by
SBP at admission.
It is reasonable to hypothesize that
patients with elevated SBP may re-
spond favorably to vasodilators and
neurohormonal antagonists. How-
ever, these patients have typically been
underrepresented in clinical trials, and
as a result it is not possible to deter-
mine whether they benefit from these
agents. None of the agents (vasodila-
tors, inodilators, and calcium sensitiz-
ers) studied in recent trials
5-11
has im-
proved clinical outcomes. The
hypotensive effects of these drugs may
potentially explain the lack of benefit
or potential harm observed in these
studies. Additional lowering of SBP in
a patient with baseline hypotension may
result in organ hypoperfusion, wors-
ening renal function, cardiac ische-
mia, and reductions in cardiac output.
Our findings revealed that ino-
tropes and nesiritide were used more
commonly in patients with lower SBP,
however these agents should be used
with caution in patients with lower SBP.
Patients with elevated SBP may re-
spond to acute heart failure treat-
ments differently, and they may be more
likely to benefit from vasodilators or
acute neurohormonal antagonists than
patients with low SBP. This hypoth-
esis needs further investigation in ran-
domized controlled trials.
The observed differences in perfor-
mance measures and evidence-based
medicine prescribing were interest-
ing. Higher angiotensin receptor
blocker, angiotensin-converting en-
zyme inhibitor, and ␤-blocker use in the
higher SBP quartiles may be related to
their antihypertensive effects. It is pos-
sible that poor outcomes associated
with lower SBP may be due to reluc-
tance on the part of the physician to use
1 or more of these therapies in pa-
tients with low SBP. The finding that
therapies proven to reduce morbidity
and mortality, such as angiotensin-
converting enzyme inhibitors and
␤-blockers, were used more fre-
quently in patients with higher SBP may
indicate that physicians are more will-
ing to treat patients with higher SBP—
those who they may consider to be less
sick—more aggressively. It is also pos-
sible that the use of higher doses of
heart failure medications may have in-
fluenced the better outcomes ob-
served in patients with higher SBP.
Lower rates of aldosterone antago-
nist use and lower rates of adherence to
the discharge instructions and left ven-
tricular ejection fraction assessment per-
formance measures may be related to a
perception that patients with normal or
elevated SBP are less ill or at lower risk
than those with hypotension and do not
need to be treated aggressively. Al-
though patients with higher SBP did
have lower rates of in-hospital and fol-
low-up mortality, the rate of rehospital-
ization was similar, regardless of SBP.
Thus, these patients are still at high risk
of morbid events, and they should re-
ceive the highest quality care and edu-
cation in an effort to reduce the risk of
rehospitalization. The majority of pa-
tients with heart failure have elevated
SBP and appear to respond favorably to
in-hospital acute heart failure treat-
ments but have typically been under-
represented in clinical trials.
These results should be evaluated in
the context of several limitations. First,
OPTIMIZE-HF was not a prospective
randomized trial. Unmeasured vari-
ables may have been present that could
have influenced the findings. Al-
though heart failure was determined
from chart review by clinical person-
nel, the potential for incomplete or in-
accurate classification of heart failure
remains. Systolic blood pressure was
not collected prior to hospital admis-
sion or after discharge; consequently,
we were unable to characterize chronic
changes in SBP over time. We cannot
determine from these data whether SBP
at admission directly influences in-
hospital and short-term postdischarge
outcomes or if it is simply a marker of
other processes that influence out-
come. In addition, as in other large heart
failure cohort studies, we did not col-
lect measures of diastolic function be-
cause reporting of these variables is not
well standardized.
13
It is possible that
some patients classified as having heart
failure with relatively preserved sys-
tolic function based on a heart failure
symptoms, discharge diagnosis, and left
ventricular ejection fraction of 40% and
higher, consistent with the current heart
failure guideline definition, may not
have had echocardiographic evidence
of diastolic dysfunction.
CONCLUSIONS
The findings from this OPTIMIZE-HF
analysis indicate that SBP assessment
at admission provides important, inde-
pendent prognostic information in
patients with heart failure with both
reduced and preserved systolic func-
tion. Patients with heart failure with
low SBP are at the highest risk for
mortality despite the use of current
pharmacological therapies. These data
support previous findings from
ADHERE.
Further study of the relationship be-
tween SBP in heart failure and out-
comes is important and warranted; pro-
spective studies should be designed to
test the hypothesis that SBP at admis-
sion is useful for risk stratification of
patients with heart failure. Elevated SBP
appears to signal specific pathophysi-
ological processes that differ from the
BLOOD PRESSURE AND OUTCOMES IN HEART FAILURE
©2006 American Medical Association. All rights reserved. (Reprinted) JAMA, November 8, 2006—Vol 296, No. 18 2225
Downloaded From: http://jama.jamanetwork.com/ on 02/25/2013

underlying processes in patients with
low SBP. Because the characteristics and
outcomes are different among pa-
tients with heart failure with varying
SBP levels, management may need to
vary according to SBP at admission.
Author Contributions: Drs Gheorghiade and Fon-
arow had full access to all of the data in the study and
take responsibility for the integrity of the data and the
accuracy of the data analysis.
Study concept and design: Gheorghiade, Abraham,
Albert, Greenberg, O’Connor, Stough, Young,
Fonarow.
Acquisition of data: Abraham, Albert, Greenberg,
O’Connor, Young, Fonarow.
Analysis and interpretation of data: Gheorghiade,
Abraham, Greenberg, O’Connor, She, Yancy, Young,
Fonarow.
Drafting of the manuscript: Gheorghiade, Albert,
Greenberg, O’Connor, She, Fonarow.
Critical revision of the manuscript for important in-
tellectual content: Abraham, Greenberg, O’Connor,
She, Yancy, Young, Fonarow.
Statistical analysis: She, Fonarow.
Obtained funding: Fonarow.
Administrative, technical, or material support:
Greenberg, O’Connor, She.
Study supervision: Gheorghiade, Abraham, Greenberg,
O’Connor, Fonarow.
Financial Disclosures: Dr Gheorghiade reported re-
ceiving research grants from the National Institutes of
Health, Otsuka, Sigma Tau, Merck, and Scios Inc; being
a consultant for Debbio Pharm, Errekappa Terapeu-
tici, GlaxoSmithKline, Protein Design Labs, and
Medtronic; and receiving honoraria from Abbott, As-
traZeneca, GlaxoSmithKline, Medtronic, Otsuka, Pro-
tein Design Lab, Scios Inc, and Sigma Tau. Dr Abra-
ham reported receiving research grants from Amgen,
Biotronik, CHF Solutions, GlaxoSmithKline, Heart Fail-
ure Society of America, Medtronic, Myogen, the Na-
tional Institutes of Health, Orqis Medical, Otsuka Mary-
land Research Institute, Paracor, and Scios Inc; being
a consultant or serving on the speaker’s bureau for
Amgen, AstraZeneca, Boehringer-Ingelheim, CHF So-
lutions, GlaxoSmithKline, Guidant, Medtronic, Merck,
Pfizer, ResMed, Respironics, Scios Inc, and St Jude
Medical; being on the advisory board of CardioKine,
CardioKinetix Inc, CHF Solutions, the Department of
Veterans Affairs Cooperative Studies Program, Ino-
vise, the National Institutes of Health, and Savacor Inc;
and receiving honoraria from AstraZeneca, Boehringer-
Ingelheim, GlaxoSmithKline, Guidant, Medtronic,
Merck, Pfizer, ResMed, Respironics, Scios Inc, and St
Jude Medical. Dr Albert reported being a consultant
for GlaxoSmithKline and Medtronic; and serving on
the speaker’s bureau for GlaxoSmithKline, Medtronic,
NitroMed, and Scios Inc. Dr Stough reported receiv-
ing research grants from Actelion, GlaxoSmithKline,
Medtronic, Otsuka, and Pfizer; being a consultant or
serving on the speaker’s bureau for Abbott, Astra-
Zeneca, GlaxoSmithKline, Medtronic, Novacardia, Ot-
suka, Protein Design Labs, RenaMed, Sigma Tau, and
Scios Inc; and receiving honoraria from Abbott, As-
traZeneca, GlaxoSmithKline, Medtronic, and Pfizer. Dr
Greenberg reported receiving research grant support
from Abbott Laboratories, Amgen, Cardiodynamics,
GlaxoSmithKline, Medicines Company, Millennium,
Novacardia, Otsuka, Pfizer, Sanofi-Aventis, and Ti-
tan; serving on the speaker’s bureau or being a con-
sultant for Amgen, AstraZeneca, GlaxoSmithKline,
Guidant Corp, Medtronic, Merck & Co, NitroMed,
Pfizer, Remon Medical Technologies, and Scios Inc;
serving on the advisory board for CHF Solutions,
GlaxoSmithKline, and NitroMed; and receiving hono-
raria from AstraZeneca, GlaxoSmithKline, Medtronic,
Merck, NitroMed, Novartis, Pfizer, and Scios Inc.
Dr O’Connor reported receiving research grant
support from the National Institutes of Health; serv-
ing on the speaker’s bureau and/or being a consul-
tant for Amgen, AstraZeneca, Bristol-Myers Squibb,
GlaxoSmithKline, Guidant, Medtronic, Merck, Ni-
troMed, Novartis, Otsuka, Pfizer, and Scios Inc; and
receiving honoraria from GlaxoSmithKline, Pfizer, and
Otsuka. Dr Yancy reported receiving research grants
from Cardiodynamics, GlaxoSmithKline, Scios Inc,
Medtronic, and NitroMed; being a consultant or serv-
ing on the speaker’s bureau for AstraZeneca, Cardio-
dynamics, GlaxoSmithKline, Medtronic, NitroMed,
Novartis, and Scios Inc; being on the advisory board
for CHF Solutions, the Food and Drug Administra-
tion cardiovascular device panel, and the National In-
stitutes of Health; and receiving honoraria from As-
traZeneca, Cardiodynamics, GlaxoSmithKline,
Medtronic, Novartis, and Scios Inc. Dr Young re-
ported receiving research grants from Abbott, Acorn,
Amgen, Artesion Therapeutics, AstraZeneca, Biosite,
GlaxoSmithKline, Guidant, Medtronic, MicroMed, the
National Institutes of Health, Scios Inc, Vasogen, and
World Heart; and being a consultant for Abbott, Acorn,
Amgen, Biomax Canada, Biosite, Boehringer-
Ingelheim, Bristol-Myers Squibb, Cotherix, Edwards
Lifescience, GlaxoSmithKline, Guidant, Medtronic, Mi-
croMed, Novartis, Paracor, Proctor & Gamble, Pro-
temix, Scios Inc, Sunshine, Thoratec, Transworld Medi-
cal Corp, Vasogen, Viacor, and World Heart. Dr
Fonarow reported receiving research grants from Am-
gen, Biosite, Bristol-Myers Squibb, Boston Scientific/
Guidant, GlaxoSmithKline, Medtronic, Merck, Pfizer,
Sanofi-Aventis, Scios Inc, and the National Institutes
of Health; serving on the speaker’s bureau or receiv-
ing honoraria from Amgen, AstraZeneca, Biosite, Bris-
tol-Myers Squibb, Boston Scientific/Guidant,
GlaxoSmithKline, Kos, Medtronic, Merck, NitroMed,
Pfizer, Sanofi-Aventis, Schering-Plough, Scios Inc, St
Jude Medical, Takeda, and Wyeth; and being a con-
sultant for Biosite, Bristol-Myers Squibb, Boston Sci-
entific/Guidant, GlaxoSmithKline, Medtronic, Merck,
NitroMed, Orqis Medical, Pfizer, Sanofi-Aventis, Scher-
ing-Plough, Scios Inc, and Wyeth.
Funding/Support: GlaxoSmithKline funded the
OPTIMIZE-HF registry under the guidance of the
OPTIMIZE-HF Steering Committee, the data collec-
tion and management by Outcome Inc, analysis of reg-
istry data at the Duke Clinical Research Institute, and
administrative and material support by Accel Health.
Role of the Sponsor: GlaxoSmithKline was involved
in the design and conduct of the OPTIMIZE-HF reg-
istry and funded data collection and management
through Outcome Inc, and data management and sta-
tistical analyses through the Duke Clinical Research
Institute. The sponsor was not involved in the man-
agement, analysis, or interpretation of data or the
preparation of the manuscript. GlaxoSmithKline re-
viewed the manuscript prior to submission for publi-
cation.
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2226 JAMA, November 8, 2006—Vol 296, No. 18 (Reprinted) ©2006 American Medical Association. All rights reserved.
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