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A random Abstract
Our Project
Our Team
Evaluation and construction of diagnostic criteria for inclusion body myositis.
[inclusion body myositis]
To
use
patient
data
to
evaluate
and
construct
diagnostic
criteria
for
inclusion
body
myositis
(
IBM
)
,
a
progressive
disease
of
skeletal
muscle
.
The
literature
was
reviewed
to
identify
all
previously
proposed
IBM
diagnostic
criteria
.
These
criteria
were
applied
through
medical
records
review
to
200
patients
diagnosed
as
having
IBM
and
171
patients
diagnosed
as
having
a
muscle
disease
other
than
IBM
by
neuromuscular
specialists
at
2
institutions
,
and
to
a
validating
set
of
66
additional
patients
with
IBM
from
2
other
institutions
.
Machine
learning
techniques
were
used
for
unbiased
construction
of
diagnostic
criteria
.
Twenty
-
four
previously
proposed
IBM
diagnostic
categories
were
identified
.
Twelve
categories
all
performed
with
high
(
≥
97
%
)
specificity
but
varied
substantially
in
their
sensitivities
(
11
%
-
84
%
)
.
The
best
performing
category
was
European
Neuromuscular
Centre
2013
probable
(
sensitivity
of
84
%
)
.
Specialized
pathologic
features
and
newly
introduced
strength
criteria
(
comparative
knee
extension
/
hip
flexion
strength
)
performed
poorly
.
Unbiased
data-directed
analysis
of
20
features
in
371
patients
resulted
in
construction
of
higher-performing
data-derived
diagnostic
criteria
(
90
%
sensitivity
and
96
%
specificity
)
.
Published
expert
consensus-derived
IBM
diagnostic
categories
have
uniformly
high
specificity
but
wide
-ranging
sensitivities
.
High
-performing
IBM
diagnostic
category
criteria
can
be
developed
directly
from
principled
unbiased
analysis
of
patient
data
.
This
study
provides
Class
II
evidence
that
published
expert
consensus-derived
IBM
diagnostic
categories
accurately
distinguish
IBM
from
other
muscle
disease
with
high
specificity
but
wide
-ranging
sensitivities
.