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CARDIOVASCULAR JOURNAL OF AFRICA • Volume 28, No 5, September/October 2017
310
AFRICA
of Helsinki. Written informed consent was exempted by the
institutional review boards.
Patients’ demographic and clinical characteristics were
reviewed using electronic records. The following demographic
and clinical characteristics were extracted: age, gender, height,
weight, systolic blood pressure, diastolic blood pressure,
current smoking status, and history of hypertension, diabetes,
dyslipidaemia, coronary artery disease, and atrial fibrillation.
Each patient’s body mass index [BMI (kg/m
2
)] was calculated. In
addition, length of hospital stay was recorded.
The following laboratory data were extracted: haemoglobin,
pro-brain-type natriuretic peptide, blood urea nitrogen,
creatinine, estimated glomerular filtration rate, creatine kinase
MB, troponin I, C-reactive protein, and D-dimer values. In
addition, we recorded the dates of the diagnosis of pneumonia,
pulmonary thromboembolism and all-cause death from the
medical records.
Transthoracic echocardiographic images were reviewed for
all patients. Transthoracic echocardiography was performed
before the operation and images were obtained using the Vivid
7 or Vivid E9 echocardiography system (GE Vingmed, Horton,
Norway). Left ventricular (LV) systolic function was assessed
by calculation of LV ejection fraction (EF) using M-mode
echocardiography.
RV systolic function was assessed from the following
parameters: tricuspid annular plane systolic excursion (TAPSE),
tissue Doppler-derived tricuspid lateral annular systolic velocity
(RVs
′
), and RV fractional area change (FAC).
9
RV FAC was
calculated by tracing end-systolic and end-diastolic areas of the
RV in apical four chamber views.
9
Pulmonary artery systolic
pressure was calculated from the maximal velocity of the
tricuspid insufficiency jet and the estimated central venous
pressure. Two-dimensional images of the apical four-chamber
view were collected to analyse the longitudinal RV strain using
a mean frame rate of 68
±
10 frames per second. Analyses were
performed using an off-line software program (EchoPAC PC
version 113, GE Vingmed Ultrasound, Horton, Norway).
The endocardial border of the RVmyocardiumwas delineated
manually on an end-systolic frame, after which the software
automatically drew the epicardial border. Manual adjustment
was done for matching the actual borders of the regions
of interest. Then the RV myocardium was traced frame by
frame, and the longitudinal strain of the basal, middle and
apical segments of the RV free wall and septum were obtained
separately.
By averaging all segmental values, RV peak global longitudinal
strain (RV GLS) was calculated using this software with
two-dimensional speckle-tracking echocardiography.
10
Because
the longitudinal myocardial fibre length decreased during
systole, the myocardial shortening was interpreted in negative
values. Consequently, the more negative RV GLS values indicate
improved or better strain.
11
In patients with atrial fibrillation, all
RV GLS measurements were averaged over three cardiac cycles.
The primary outcome was the development of a clinically
apparent pulmonary complication during the one-month
postoperative period. We defined a pulmonary complication
as a composite outcome: development of either pneumonia
or pulmonary embolism during the first postoperative month.
Pulmonary embolism was confirmed by computed tomographic
pulmonary angiogram.
12
The diagnosis of pneumonia was based
on a combination of physical signs and chest X-rays obtained by
reviewing medical records.
13
To assess the inter-observer variability of RV GLS, a second
experienced independent investigator re-evaluated 20 randomly
selected images using the same software. Intra-observer
variability was evaluated: the first investigator who was blinded
to the former results analysed RV GLS for each randomly
selected image again at one month after the initial analysis.
Statistical analysis
Allcategoricaldataaresummarisedasfrequenciesandpercentages,
whereas statistics for continuous variables are presented as means
and standard deviations. The Pearson chi-squared test was used
to compare categorical variables. The Student’s
t
-test was used to
compare continuous variables and the Mann–Whitney
U
-test was
used when the sample size of at least one group was less than 30.
Univariate analysis was followed by multivariate logistic
regression analyses to evaluate potential risk factors for
pulmonary complications with adjustment for other risk factors.
Variables with a
p
-value less than 0.1 in univariate analysis were
selected for inclusion in the multivariate regression model.
RV GLS was analysed as a continuous variable in univariate
and multivariate models. We investigated the optimal cut-off
value of RV GLS to predict pulmonary complications in patients
with femur fracture using receiver operator characteristic (ROC)
curve analyses. In addition, Kaplan–Meier survival analyses and
log-rank tests were used to compare clinical event-free survival
rates between groups stratified by the RV GLS cut-off value.
Then, to evaluate the consistency of results according to the
identified cut-off value, RV GLS was analysed as a dichotomous
variable in univariate Cox analysis. The inter- and intra-
observer agreements were described by calculating the intra-class
correlation coefficient (ICC). A
p
-value of less than 0.05 was
considered statistically significant. All analyses were performed
using SPSS 18.0 (SPSS Inc, Chicago, IL).
Results
Seventy-eight patients with femur fracture were included; their
mean age was 80.1
±
9.1 years, and 59 (75.6 %) patients were
female. Patients’ baseline characteristics are presented in Table 1.
The mean hospital stay was 18.4
±
7.8 days (median 17 days). All
patients underwent successful surgery for femur fracture during
hospitalisation.
Eight patients (10.3%) developed pulmonary complications
during the first postoperative month. One patient (1.3%)
developed pulmonary embolism and the other seven developed
pneumonia. Among these, two patients (2.6%) died. The patients
who developed pulmonary complications had significantly longer
hospital stays than the patients who did not develop pulmonary
complications (29.8
±
17.0 vs 17.1
±
4.6 days,
p
=
0.003).
Table 2 compares laboratory results and echocardiographic
characteristics between the group with pulmonary complications
and that with no complications. The patients in the group with
pulmonary complications had significantly higher D-dimer
values than the group with no complications (19 191.5
±
16 257.0
vs 9 256.1
±
10 304.5 ng/ml,
p
=
0.023). The groups did not differ
significantly with regard to clinical characteristics, including
previous medical history (hypertension, diabetes, dyslipidaemia,