Factors related to in-hospital heart failure are very ... - Springer

Heart Vessels (2009) 24:399–405 © Springer 2009
DOI 10.1007/s00380-008-1141-y
ORIGINAL ARTICLE
Boonjong Saejueng · Tada Yipintsoi
Rattana Chaisuksuwan · Wirash Kehasukcharoen
Watana Boonsom · Rungsrit Kanjanavanit
Factors related to in-hospital heart failure are very different for unstable
angina and non-ST elevation myocardial infarction
Received: May 15, 2008 / Accepted: December 19, 2008
Representing the Thai ACS-Registry group
B. Saejueng (*) · R. Chaisuksuwan · W. Kehasukcharoen
Cardiac Unit of Chest Disease Institute, Tiwanon Street, Nonthaburi
11000, Thailand
Tel. +66-2-580-3423, +66-2-591-9999; Fax +66-2-589-9028; +66-2-591-
9512
e-mail: bunjong70@yahoo.com
T. Yipintsoi
Faculty of Medicine, Prince of Songkla University, HatYai, Songkla
90110, Thailand
W. Boonsom
Department of Medicine, BMA Medical College and Vajira
Hospital, Bangkok, Thailand
R. Kanjanavanit
Division of Cardiology, Department of Medicine, Maharaj Nakorn
Chiang Mai Hospital, Chiang Mai, Thailand
Abstract Non-ST-elevation myocardial infarction
(NSTEMI) and unstable angina (UA) resulted in different
degrees of damage to the heart muscle, and yet, when
factors related to in-hospital outcomes were examined,
these two subsets were often lumped together as non-STelevation
acute coronary syndrome. Therefore, we investigated
predictors of in-hospital heart failure (HF) in UA and
NSTEMI separately. Factors related to HF (Killip ≥ 2) were
analyzed for NSTEMI and UA in a Thai Acute Coronary
Syndrome (ACS) registry conducted in 17 institutions
between 2002 and 2005. The registry comprised of 9373
single admissions age 65.1 ± 12.3 years, 40.2% women, and
45.1% with HF. There were 3548 NSTEMI and 1989 UA
with HF prevalence of 56.2% and 27.4%, respectively.
Heart failure patients were older, more were women, sicker
(as shown by more of those with shock, postcardiac arrest,
and breathless on admission), more with diabetes mellitus
(DM), received less intervention and medication, and
showed higher total death (19.3% vs 5.3% for NSTEMI
with and without HF; and correspondingly, 5.9% and 1.9%
for UA). Independent predictors (at presentation) for the
development of HF following NSTEMI or UA were age
(not sex), breathlessness, and less prevalence of chest pain.
However, shock and DM were risks only for NSTEMI but
not UA. Heart failure was found to be a factor for inhospital
death for NSTEMI only, with odds ratio of 2.84
(confidence interval 2.11–3.82) and 3.23 (2.25–4.64) for total
and cardiac deaths, respectively. Non-ST-elevation myocardial
infarction and UA showed substantial differences in
factors related to predictors for in-hospital outcome such
that these should be examined separately.
Key words Heart failure · Non-ST segment elevation acute
coronary syndrome · Diabetes mellitus · Thai Acute Coronary
Syndrome Registry
Introduction
Heart failure (HF) associated with acute coronary syndrome
(ACS) is of interest because of its varied frequency,
outcomes, and determinants. The frequency of HF in ACS
ranged very widely from 16% to 40% possibly related to
the population being studied. 1–3,5 The mortality differs by
3–4 fold or much more between those ACS with or without
HF 2,4–8 and this persisted even after discharge. 9,10 The evaluation
by Steg et al. 5 from the Global Registry of Acute
Coronary Events (GRACE) reported an in-hospital mortality
for patients who never had heart failure, whether on
admission or during the in-hospital stay, of 1.1% for all
ACS, non-ST elevation myocardial infarction (NSTEMI),
or unstable angina. These mortalities increased by more
than 10 times in those who presented with heart failure or
those who developed HF during the hospital stay. The difference
in mortalities may be related to the types of ACS,
existing diseases such as previous myocardial damage, 7 previous
HF, 7,8,10 the timing of HF in the course of the ACS, 5
the type of left ventricular dysfunction associated with the
heart failure, 11 and risk factors, particularly diabetes mellitus
(DM). 12 The difference in prevalence of HF between
those with acute myocardial infarction (MI) and unstable
angina (UA) 4,5,9 suggests that the degree of muscle damage
may be important in the development of HF. However, this
is not supported by the similar prevalence of HF between
ST-elevation MI (STEMI) and NSTEMI in some reports, 5

400
unless the mechanisms of HF between the two MIs are different,
for, e.g., more of a systolic dysfunction in one and
more of a nonsystolic in the other. 13,14
Factors related to the development of HF during an
ACS 5–8 include age, DM, previous MI, and compromised
renal function. Diabetes mellitus seemed to be very prevalent
across all types of ACS, ranging from 17%–27% 5,8,15–17
and some reports showed differences between the frequency
of DM among the non-HF patients versus those with heart
failure. 5,7,10,11,18,19
Until recently, there have been few reports on HF
related to non-ST-elevation ACS (NSTEACS). Current
reports 5–8,11,20 show that HF associated with NSTEACS has
a poor prognosis, but as stated, the prevalence of HF
between NSTEMI and UA is different, 4,5,9 aside from differences
in subsequent mortalities. 4,5,9 Factors related to HF
and its complications for NSTEMI and UA have not always
been detailed in previous reports.
The recently completed Thai Acute Coronary Syndrome
Registry (TACSR) 21 showed a high proportion of patients
with HF (45%) and a high prevalence of DM (44%). There
were 5537 patients with the discharged diagnosis of
NSTEACS thus allowing the evaluation of factors related
to HF in NSTEMI and UA separately in this very high-risk
group.
Materials and methods
This report obtained the data from the Thai Acute Coronary
Syndrome Registry (TACSR), which included consecutive
ACS subjects (enrolled from August 2002 to
October 2005). There were 17 medical centers (10 government
and 3 private hospitals from Bangkok; 1 private hospital
and 3 government hospitals in other provincial regions
in Thailand). Cardiac catheterization and open-heart
surgery were available in 16 hospitals and 11 hospitals had
facilities for primary percutaneous coronary intervention
(PCI). The median number of beds per hospital and beds
per cardiac care unit was 755 and 6, respectively. Not every
site contributed to the registry for the total duration of
enrollment. The details related to the registry had been
reported. 21
Patients identified by the TACSR had a history predominantly
of chest pain (but in certain cases, the presenting
symptoms such as HF or cardiac arrest dominated such that
preceding chest pain could not be elicited) and presentation
suggestive of myocardial ischemia, and were older than 18
years. The study was approved by the ethics committee at
each participating center. Quality control was accomplished
by a series of workshop and site visits periodically throughout
the duration of the registry.
The present analyses evaluated subjects with a discharge
diagnosis of NSTEACS and excluded those with repeated
admission. Non-ST-elevation myocardial infarction was
defined as an acute MI with ECG changes other than ST
segment elevation and at least one value of elevated cardiac
enzymes for myocardial necrosis defined as total creatinine
phosphokinase or creatine kinase MB fraction greater than
2 times the upper limit of the hospital normal range and/or
positive troponin I or T. Unstable angina in this registry
had to show ST- and or T-wave abnormalities. These ECG
changes had to be present independent of whether the
patient was having chest pain at the time of the recording
of the ECG (despite the patient being admitted because of
chest pain). However, with the ECG changes, there must
be no laboratory evidence of myocardial necrosis. Some
centers may have performed enzyme estimation only
once.
Demographic data and coronary artery disease (CAD)
risks were recorded. Coronary artery disease risks were:
diabetes mellitus (DM) which included patients with known
diabetes or those with fasting plasma glucose of ≥126 mg/dl
on at least two occasions during the hospital stay; systemic
hypertension (HT), including patients with known/treated
HT or those with blood pressure ≥140 mmHg systolic and/
or ≥90 mmHg diastolic on at least 2 occasions; dyslipidemia,
including patients being treated and those found during
hospital stay with total cholesterol ≥200 mg/dl or LDL
≥130 mg/dl or HDL 24 h and
presumed to be caused by brain ischemia. The cause of
death was differentiated as either cardiac or noncardiac.
Total death was a combination of cardiac and noncardiac
deaths.
Statistical analysis
For the present analysis, the hospitals were arranged into
three groups: the private hospitals, government hospitals in
Bangkok, and the three peripheral medical-school hospitals.
The five age groups were: 74 years. Continuous variables are presented as median
and interquartile range (IQR) or mean and standard deviation,
and categorical variables are reported as frequencies.
Differences in variables in patients with and without HF
were examined separately for NSTEMI and UA with Student’s
t-tests or Chi-square tests. Multiple logistic regres-

401
sion was used to examine the independent predictors for
development of in-hospital HF and whether HF was a predictor
in total and cardiac death. Factors selected to independently
predict development of in-hospital heart failure
included only those at presentation. We did not include
medications, interventions, or other in-hospital outcomes
since our intention was to find factors that will predict the
in-hospital development of heart failure when the patient
was first seen. A nominal significance level of 0.05 (twosided)
was used. For ease of scrutiny, odds ratios (OR) and
confidence intervals (CI) are provided only when P <
0.05.
Results
The TACSR consists of 9373 subjects, of which 5537 had a
discharge diagnosis of NSTEACS (3548 NSTEMI and 1989
UA). The prevalence of HF (Killip class ≥2) for NSTEMI
and UA was 56.2% and 27.4%, respectively, compared to
44.1% for STEMI. The prevalence of Killip class 4 within
the first 48 h of admission was 7.8% for NSTEMI and 1.2%
for UA.
Table 1 shows the baseline characteristic of subjects
with and without HF for patients with NSTEMI and with
UA. The proportion of HF and non-HF in each subset differed
among the groups of hospitals. A higher proportion
of patients with HF were admitted to the government hospitals
as compared to those admitted to private hospitals.
The private hospitals (355 patients with NSTEMI and 249
with UA) admitted less HF, 8.0% versus 12.5% of those
without HF. The reverse was observed in the regional hospitals
(694 patients with NSTEMI and 309 with UA). For
the government hospitals in Bangkok (2499 patients with
NSTEMI and 1431 with UA), equal proportions of patients
with and without HF were admitted. Patients who subsequently
developed HF were older, with a higher proportion
of females, and tended to present with atypical symptoms
(i.e., less with chest pain and more with shock, and postcardiac
resuscitation). Heart failure patients commonly presented
with symptoms of cardiac dyspnea. The prevalence
of DM was significantly higher among those with heart
failure. However, even without heart failure, DM was
present in 39% and 43% of NSTEMI and UA
respectively.
Table 2 shows differences in management and outcomes
during the hospital stay between those with and without
HF. Fewer HF patients received beta-blockers, and fewer
NSTEMI patients with HF were prescribed aspirin, nitrate,
and statin. Fewer HF patients underwent coronary arteriogram
or early PCI (i.e., within 7 days), and for NSTEMI,
fewer HF received elective PCI (i.e., after 7 days for persisting
symptoms). Similar results were observed if we combined
subjects who had either PCI or coronary artery bypass
graft (CABG). For NSTEMI, all in-hospital outcomes (significant
arrhythmia, stroke, major bleeding, and death)
were significantly more frequent among patients with HF.
For UA, total and cardiac deaths (but not other outcomes)
were higher among patients with HF. The ORs were 3–4
for deaths among those with HF when compared to non-
HF. Hence, for both NSTEMI and UA, those with HF were
less aggressively managed and showed poorer in-hospital
outcomes especially those with NSTEMI.
Table 3 presents the independent factors (i.e. factors
when the patient was first seen on admission and did not
include management or in-hospital outcomes) associated
with the development of in-hospital HF. These factors
explained about 30% (pseudo R-square) of HF in this
registry. Age, as a whole, contributed to in-hospital heart
failure (OR 1.30). However, when the youngest was used
as a reference, only the group with age 65 years or older
was an independent predictor. Hospital group, as a whole,
predicts the probability of developing HF with an OR of
1.54. If the reference was the private hospitals, i.e., both
types of government hospitals, received larger proportions
of HF patients. Cardiac dyspnea was, as expected, a dominant
factor. An additional predictor for both subsets
was the absence of chest pain. Shock, DM, and dyslipidemia
were significant factors only for NSTEMI, not for
UA. Sex and referral status did not contribute to the prediction.
If the hospital group was not offered as a factor
for the multivariate, the factors involved in the prediction
remained.
In the analyses of independent factors for hospital outcomes,
which were total and cardiac deaths and major
arrhythmia (detailed data not presented as a table), we
found that HF affected these outcomes differently for
NSTEMI vs UA. Heart failure in NSTEMI had an OR (CI)
of 2.84 (2.11–3.82) for total death, 3.23 (2.25–4.64) for
cardiac death, and 1.68 (1.29–2.19) for in-hospital arrhythmia.
None of these factors was applicable for UA unless we
substituted a more severe HF (i.e., Killip class ≥3 instead of
≥2), which resulted in ORs (CI) of 4.63 (2.11–10.17) for
total death and 4.94 (1.98–12.32) for cardiac death.
Discussion
The objectives of the present study were to evaluate factors
related to in-hospital development of heart failure following
NSTEMI and UA in the TACS registry and to evaluate
the two subsets of NSTEACS separately. This registry
showed a very high prevalence of in-hospital Killip ≥2
(56.2% of NSTEMI and 27.4% of UA), and as well, significantly
higher prevalence of DM among those with HF
as compared to those without HF. The univariate factors
which distinguished the group with HF are not unlike previous
reports on NSTEACS 5–8,20 which included age, being
female, and sicker on admission (with more shock, postcardiac
resuscitation, and dyspnea which may result in less
percentage of patients presented with chest pain). The
consequence with regard to management is a lower proportion
of patients with HF receiving medication (i.e., fewer
beta-blockers for both NSTEMI and UA, and less aspirin,
nitrate, and statin for NSTEMI) and interventions, again
not dissimilar to previous reports. 4–8,11 However, registries

402
Table 1. Baseline characteristics, symptoms, and coronary risk factors
Non ST-elevation MI Unstable angina
N0 HF HF OR 95% CI P N0 HF HF OR 95% CI P
N 1554 1994 1445 544
T-admit, median (IQR), h 7.3 (2.8, 35.9) 9.8 (2.9, 48.0) – – 0.013 6.0 (2.0, 29.5) 6.4 (2.7, 33.5) – – 0.661
T-admit

403
Table 2. Treatment, intervention, and in-hospital outcome
Non ST-elevation MI
Unstable angina
N0 HF HF OR 95% CI P N0 HF HF OR 95% CI P
ASA 95.7 93.8 0.69 0.51–0.93 0.015 93.4 95.4 0.062
Nitrate 88.5 85.1 0.74 0.61–0.90 0.003 92.3 91.7 0.732
Beta-blocker 77.1 49.5 0.29 0.25–0.34

404
are not. 12,22,24,25 In our NSTEMI, there were 60% with DM
among those that developed HF as contrasted to 39% with
DM in those without HF. For UA, this corresponding prevalence
was 53% and 43%, respectively. Our prevalence of
DM was higher than most previous reports. 5–8,11 Independent
of ACS, the close inter-relationship between DM and
HF is being recognized. A recently completed, large and
prospective, 2.4-year follow-up of subjects at high risk of
cardiovascular disease showed that grades of fasting plasma
glucose may be risks for hospitalization for HF, and both
newly detected or known DM is an independent risk for
hospitalization for HF as well as hospitalization for HF
combined with cardiovascular death. 26 A long-term retrospective
study reported that DM and increased hemoglobin
A1c could be associated with both total and cardiovascular
mortality among a Japanese population who underwent
PCI. 27
Univariate comparison between HF and non-HF for
NSTEMI or for UA did not show marked differences
among major variables, but the contribution of DM to HF
and of HF to death were limited to NSTEMI. Hence, if one
has to look for independent relationships to specific outcomes
in NSTEACS, these two entities should be analyzed
separately, more so since the proportion of UA in different
population of NSTEACS can vary.
There are several weaknesses in our analyses aside from
the fact that a registry should not be used to answer basic
questions. Heart failure in this study pertains to Killip ≥2
that developed after admission, and the result cannot always
be compared to reports of HF previous to ACS, 10 or the
more commonly reported HF at presentation 5,8,11,18,19 or HF
that only developed after admission. 5,19,23 Several reports
have shown that the HF at various stages of ACS exhibited
different mortality rates. 2,5,10,18–20 Other factors which are
determinants of HF as reported by others but which were
absent in our registry included renal function, previous MI,
and previous HF. 5–8,10,11,19,20 All of these factors were used in
the risk score from the GRACE to predict long-term (i.e.
6 months to 4 years) mortality. 28
In the present report, in-hospital HF was defined by
using clinical criteria, i.e., Killip’s classification, which others
also used. It may be useful, when differentiating events,
either in-hospital or later, to be able to complement these
Killips by measuring the level of the natriuretic peptide
and/or left ventricular ejection fraction. Another potential
mislabeling of diagnosis is in the criteria used for defining
NSTEMI or UA among patients presented with dominant
HF (in contrast to those presenting with chest pain), which
persisted during the hospital stay. Heart failure per se,
without coronary artery disease, with or without preceding
chest pain can and does show changes in ECG associated
with elevated enzyme of myocardial necrosis. 29 These may
be mislabeled as NSTEMI. Coronary arteriography was not
performed in all our NSTEMI patients and hence we will
not recognize the magnitude of this mislabeling. In the same
vein, since some UA had only one estimation of enzyme of
myocardial necrosis, we may have missed the late rising
enzyme, which would change the diagnosis from UA to
NSTEMI.
Conclusions
In this registry, where HF is a frequent complication of
NSTEACS and where DM is prevalent, independent factors,
at presentation on admission, predicting in-hospital HF
were different between NSTEMI and UA. This difference
between the two types of NSTEACS also pertains to contribution
of in-hospital HF to death. These two entities of
NSTEACS should be analyzed separately. Our data suggest
that medication and intervention may affect the prevalence
of in-hospital HF. We have no explanation for the high
prevalence of HF and the poor outcomes in TACS registry.
One possibility is that our NSTEACS patients sought
medical assistance only when the symptoms or manifestations
of ACS became very severe.
Acknowledgments The Thai Acute Coronary Syndrome Registry
(TACSR) was supported by The Heart Association of Thailand under
the Royal Patronage of H.M. the King, Thai Health Promotion Foundation,
Clinical Research Collaboration Network, and the Health
Systems Research Institute. The following individuals were involved
in the Registry.
Steering Committee: Suphachai Chaithiraphan (Chair), Tada
Yipintsoi, Chadsri Prachuabmoh, Pyatat Tatsanavivat, Supachai
Tanomsup, Piyamitr Sritara, Taworn Suithichaiyakul, Sawaet Nontakanun,
Damras Tresukosol, Chumpol Piamsomboon, Sudaratana
Tansuphaswadikul, Gampanat Veerakul, Saowaluk Prompongsa,
Rungsrit Kanjanavanit, Songkwan Silaruks, Worachat Moleerergpoom,
Woravut Jintapakorn, Pisit Hutayanon, Rangson Ratanaprakarn,
Permyos Ruengsakulrach, Osthon Sriyadthasak, Sopon
Krisanarungson, Charuwan Kangkagate.
Executive committee: Chadsri Prachuabmoh (Chair), Pyatat Tatsanavivat,
Piyamitr Sritara, Suphot Srimahachota, Damras Tresukosol,
Sopon Sanguanwong, Gampanat Veerakul, Kitiporn Angkasuwapala,
Rungsrit Kanjanavanit, Worachart Moleerergpoom, Pisit Hutayanon.
Data coordinating center: Ladathip Suwan, Charuwan Kangkagate,
Kongkait Kespechara.
Institution and investigators involved in data collection: Bangkok
General Hospital: Nithi Mahanonda, Permyos Ruengsakulrach, Pakorn
Lolekha, Boonchu Srichaiveth; Bhumibol Adulayadej Hospital:
Gampanat Veerakul, Lertlak Chaothawee; Chest Disease Institute:
Sudaratana Tansuphaswadikul, Wirash Kehasukcharoen, Boonjong
Saejueng; King Chulalongkorn Memorial Hospital:Taworn Suithichaiyakul,
Suphot Srimahachota; Maharaj Nakorn Chiang Mai Hospital:
Thanawat Benjanuwattra, Rungsrit Kanjanavanit; Phya Thai 2 Hospital:
Osthon Sriyadthasak; Police General Hospital: Worachart
Moleerergpoom, Kasem Ratanasumawong; Pramongkutklao Hospital:
Chumpol Piamsomboon, Sopon Sanguanwong; Rajavithi Hospital:
Saowaluk Prompongsa, Kitiporn Angkasuwapala, Napa Siriviwattanakul;
Ramathibodi Hospital: Supachai Tanomsup, Piyamitr Sritara;
Samitivej Hospital: Rangson Ratanaprakarn, Chartchai Suntiparpluacha;
Siriraj Hospital: Damras Tresukosol, Wiwun Tungsubutra; Songklanagarind
Hospital: Woravut Jintapakorn; Srinagarind Khon Kaen
Hospital: Songkwan Silaruks, Songsak Kiatchoosakul,Chaiyasit Wongvipaporn;
Thammasat Chalermphakiat Hospital: Pisit Hutayanon,
Adisai Buakhamsri; Vajira College Hospital: Sawaet Nontakanun,
Kajorn Khaopaisarn, Navin Suraphakde, Watana Boonsom; Bangkok
Hospital Phuket: Sopon Krisanarungson.
We express our sincere thanks to the personnel of the intensive care
units, the patients and their relatives, and most of all, the research
nurses who patiently assisted in all aspects of patient care, data collection
and entry.

405
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