11 / 76
CARDIOVASCULAR JOURNAL OF AFRICA • Volume 29, No 3, May/June 2018
AFRICA
141
For length of index hospitalisation, least-square means and
the difference between least-square means are presented. For
time-to-event outcomes, Cox regression models were used with
times for patients without the event of interest being censored
at the earlier of the last date the patient was known to be alive
or the period of interest for the specific outcome. Kaplan–Meier
estimates, hazard ratios and 95% confidence intervals are given,
with the log-rank test used for comparison between groups.
Two patients who were classified with AF but were missing
valvular disease status were excluded from tables comparing
valvular disease in only those patients with AF. Imputation
for missing values was done only when examining associations
after adjustment for potential confounders using multivariable
models. For multivariable modelling, these two patients were
counted as having neither valvular AF nor non-valvular AF.
Anticoagulation use over time is also presented as the frequency
of use by AF and by valvular/non-valvular disease in only those
patients with AF by time point.
The prognostic value of valvular and non-valvular AF was
examined in multivariable models for the outcomes all-cause
mortality within 180 days and the composite endpoint all-cause
mortality or rehospitalisation within 60 days. The multivariable
models were adjusted for significant clinical covariates from
multivariable prognostic models previously constructed for these
outcomes in the overall THESUS-HF registry.
13
To account for missing data, multiple imputations were
used with seven imputed datasets. Of the 11 baseline variables
included in the multivariable model for 180-day mortality, 278
(27.6%) patients were missing one variable, 57 (5.7%) were
missing two, nine (0.9%) were missing three, and four (0.4%)
were missing four or more. Of the seven baseline variables
included in the multivariable model for 60-day death or HF
rehospitalisation, 205 (20.4%) patients were missing one variable,
44 (4.4%) were missing two, five (0.5%) were missing three, and
none was missing four or more. Rubin’s algorithm was used for
averaging parameter estimates across the imputed data-sets.
14,15
Results
There was a total of 1 006 patients in the THESUS-HF registry.
The mean (SD) age of the patients was 52.3 (18.3) years, 511
(50.8%) were women, and the predominant race was black
African (98.5%). As reported previously,
16
the primary aetiology
of heart failure was most commonly hypertension (
n
=
363,
39.5%), followed by idiopathic dilated cardiomyopathy (
n
=
136,
14.8%) and rheumatic valvular heart disease (
n
=
137, 14.9%),
with ischaemic HF in only 72 (7.8%) patients.
AF was present in 209 (20.8%) of the 1 006 patients. In the
previous THESUS-HF publication,
2
prevalence was documented
to be 18.3%because only those who had AF on the admission ECG
were analysed. Table 1 shows the baseline patient characteristics
by AF status. In both the AF and non-AF groups, about 80%
of the patients were in NYHA class II or III one month prior to
admission. Compared to the patients without AF, the patients
with AF were older (mean age 57.1 vs 51.1 years) and more likely
to be female (57.4 vs 49.1%). They also had significantly lower
systolic (125 vs 132 mmHg) and diastolic (81 vs 85 mmHg) blood
pressures and higher mean heart rates (109 vs 102 bpm).
Ninety-two (44%) of the 207 AF patients had valvular heart
disease. Compared with those without valvular disease, these
patients were younger (mean age 52 vs 61 years), had lower
systolic blood pressure (120 vs 128 mmHg) and higher left
ventricular ejection fraction (LVEF) (47 vs 38%). Fifty-seven
per cent had LVEF
≥
45%. Among patients with non-valvular
AF, 61% had hypertensive heart disease. The other baseline
characteristics were similar in the two groups (Table 2).
Anticoagulation prescription rates were low in this cohort of
patients and decreased progressively over time. At six months,
only 22% of patients with AF were on oral anticoagulants. For
the AF patients, 33% of the patients with valvular AF and 12%
of those with non-valvular AF were on anticoagulants at six
months’ follow up (Table 3). For aspirin, a greater proportion of
patients with AF than without AF were on aspirin one month
prior to admission (29 vs 20%), but on and after admission the
proportions did not differ significantly.
As shown in Table 4, the mean length of the hospital stay
was 1.6 days longer in patients with valvular AF than for
patients with non-valvular AF, although this was not statistically
significant (
p
=
0.14). Patients were followed for a median of
180 days. Of 151 total deaths over 180 days, 20 occurred among
Table 1. Baseline patient clinical characteristics
by atrial fibrillation status
Variable
s
Atrial fibrillation
1
(
n
=
209)
No atrial fibrillation
1
(
n
=
797)
p
-value
2
Age (years)
57.1 (17.73),
60.0 (46.0–70.0)
51.1 (18.26),
52.0 (36.0–65.0)
< 0.0001
Gender: female,
n
(%)
120 (57.4)
391 (49.1)
0.0328
Black African,
n
(%)
203 (97.6)
781 (98.7)
0.2291
BMI (kg/m
2
)
24.94 (5.712),
24.73 (21.02–28.08)
24.85 (5.836),
23.88 (20.83–27.99)
0.4736
SBP (mmHg)
124.5 (29.86),
120.0 (102.0–145.0)
131.9 (34.27),
130.0 (108.0–150.0)
0.0128
DBP (mmHg)
80.6 (19.54),
80.0 (67.0–90.0)
85.3 (21.19),
82.0 (70.0–100.0)
0.0032
Heart rate (bpm)
109.3 (28.02),
108.0 (90.0–124.0)
102.2 (19.29),
103.0 (90.0–114.0)
0.0021
History of
hypertension,
n
(%)
110 (52.9)
446 (56.2)
0.3959
Hyperlipidaemia,
n
(%)
9 (4.5)
81 (10.4)
0.0109
Stroke,
n
(%)
7 (3.4)
18 (2.3)
0.3613
Ischaemic heart
disease,
n
(%)
11 (5.3)
71 (8.9)
0.0849
Valvular disease,
n
(%)
92 (44.4)
180 (22.7)
< 0.0001
Peripheral vascular
disease,
n
(%)
3 (1.4)
9 (1.1)
0.7072
Anaemia,
n
(%)
99 (49.0)
390 (51.0)
0.6183
Pericardial disease,
n
(%)
9 (4.3)
44 (5.6)
0.4815
Cardiomyopathy,
n
(%)
80 (38.8)
336 (42.6)
0.3243
LVEF (%)
42.31 (15.721),
41.90 (31.00–52.00)
38.74 (16.623),
37.00 (25.40–50.00)
0.0022
LVEF < 40%,
n
(%)
82 (41.6)
405 (55.3)
0.0155
eGFR
(ml/min/1.73 m
2
)
78.257 (40.114),
70.782 (49.422–98.271)
84.685 (49.838),
77.735 (55.929–104.20)
0.0522
Renal dysfunction,
n
(%)
10 (5.0)
63 (8.4)
0.1020
1
Mean (SD), median (first quartile – third quartile) for a continuous variable and
frequency (per cent) for a categorical variable.
2
Chi-squared
test
for a
categorical variable, CMH
for an ordinal variable and
Wilcoxon
test
for a
continuous variable.
BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pres-
sure; LVEF, left ventricular ejection fraction; eGFR, estimated glomerular filtra-
tion rate.