Dysvascular amputation and comorbidity
Initial Review
Adult (18+) patients with a
history of a disvascular
amputation admitted to inpatient
rehabilitation unit between
January 2011 and April 2015
n=167
Inclusion/Exclusion
118 met criteria of being
admitted for inpatient
rehabilitation acutely
following transfemoral or
transtibilial amputation
49 patients were excluded
due to their not being new
amputations, or not having
had transfemoral or
transtibilial amputations
Fig. 1. Inclusion and exclusion criteria.
tional gains during the inpatient rehabilitation stay. Functional
outcomes were measured using the Functional Independence
Measure (FIM). Specifically, total gain in motor FIM (admission
– discharge motor FIM score) and motor FIM efficiency (total
motor FIM change divided by the number of days in inpatient
rehabilitation) were evaluated.
The primary predictors of interest were the presence of infec-
tion at admission assessed by elevated white blood cell count
and active treatment with intravenous (IV) antibiotics. Other
factors associated with poor wound healing, such as diabetes or
the need for negative pressure wound therapy (hereafter referred
to as “wound vac”), were also expected to indicate an increased
vulnerability to infections and possibly to be associated with
increased incidence of unplanned transfers from inpatient re-
habilitation. Markers of organ failure, represented by elevated
creatinine levels at admission, anaemia, and pre-admission need
for haemodialysis, were expected to correlate with increased
incidence of transfer. History of previous amputation was also
thought to be associated with higher rates of acute transfer, as
it could reflect more severe systemic disease. In our evaluation
of laboratory tests, the most recent results within 72 h prior to
admission to the inpatient rehabilitation unit were evaluated;
if there was no laboratory data available in that window of
time, the first available laboratory values in the 48 h following
admission were recorded. Finally, length of stay, gender, age
at inpatient rehabilitation admission, number of days since
amputation, and admission FIM scores (total and motor FIM)
were controlled for in the analysis.
Statistical analysis
Binary logistic regression was used to test the impact of fac-
tors on the likelihood that patients would have an unplanned
transfer from the inpatient rehabilitation unit. Hierarchical
multiple regression was used to assess the ability of infection,
poor wound healing, organ failure, and chronic vascular disease
to predict gains in function during inpatient rehabilitation.
Preliminary analyses were conducted to ensure no violation of
the assumptions of normality, linearity, multicollinearity, and
homoscedasticity. Linearity of the continuous variables with re-
spect to the logit of the dependent variable (unplanned transfer)
was assessed via the Box-Tidwell procedure (18). A Bonferroni
correction was applied using all terms in the model resulting in
statistical significance level of p < 0.00625. Based on this as-
sessment, all continuous independent variables were found to
be linearly related to the logit of the dependent variable. There
were 4 cases of studentized residuals with values greater than
371
3.00 standard deviations (SD), which were kept in the analysis.
Because of interest in the potential functional benefits of a
full course of inpatient rehabilitation, patients with unplanned
transfers were excluded from the analysis of functional gains.
In addition to examining the relationship of medical variables
and functional gains, 3 indices of change for total and motor
FIM scores (i.e. gain scores) were evaluated: minimal detect
able change (MDC); Cohen’s effect size; and the standardized
response mean (SRM). The MDC is a statistical measure of
change, defined as the minimum amount of change that exceeds
measurement error. In other words, the smallest change that is
due to “true” change and not variation in measurement (14).
The intraclass coefficients (ICC) for total and motor FIM gain
scores, within each group, were used to calculate the standard
error of measurement (SEM) and MDC at the 90% confidence
level (MDC90) using the following formula: 1.64*SEM*. The
percentage of patients whose total and motor FIM gain scores
exceeded the MDC90 using the χ 2 test of homogeneity were
also examined. Cohen’s effect size quantifies the size of the
difference between baseline and follow up (i.e. admission and
discharge) and estimates the magnitude of treatment effect; in
this case, inpatient rehabilitation. Within-group effect size as ad-
mission to discharge difference divided by the admission score
SD was also calculated. Similar to effect size, SRM attempts to
quantify the effect of the treatment, or inpatient rehabilitation. It
is preferred to paired t-test because it removes the dependence
on sample sizes (19). The model contained 12 independent
variables: white blood cell count (WBC, value), use of IV
antibiotics (no/yes), creatinine (value), haemodialysis status
at admission (no/yes), wound vac presence at admission (no/
yes), history of diabetes treated with insulin and/or medication
(no/yes), haemoglobin (value), history of a previous amputa-
tion (no/yes), length of stay on the rehabilitation unit (days),
gender (male/female), time between amputation and admission
to the acute inpatient rehabilitation unit (days), and motor FIM
at admission (value). These variables were selected due to their
correlation with chronic disease, risk of infection, and/or risk of
poor wound healing. The same predictive model was used for all
regression testing with the exception of length of stay for motor
FIM efficiency, as this is used in the calculation of the outcome.
Model variables were entered in a step-wise fashion, beginning
with factors expected to have the most explanatory power, to
observe the degree of change in the amount of variance in the
outcome each step contributed. All analyses were conducted in
IBM SPSS version 23, Armonk, NY, USA.
RESULTS
Patient characteristics
The sample was primarily male (82, 70.1%), Caucasian
(84, 75.7%), with a mean age of 60.8 years (standard
deviation (SD) 12.9). The patients had a mean of 10.9
days (SD 10.5) between amputation and admission to
acute rehabilitation with a mean length of stay of 14.1
days (SD 7.1). Descriptives of study variables are given
in Table I. In general, the sample reflected the medical
complexity of the dysvascular amputee population.
The mean creatinine value of the sample was above
the upper limit of normal (SD 1.3 mg/dl), and the mean
haemoglobin was below the lower limit of normal (SD
J Rehabil Med 51, 2019