Background:
Early
identification
of
individuals
at
high
risk
for
type
1
diabetes
(T1D)
is
essential
timely
intervention.
Islet
autoantibodies
(AB)
and
continuous
glucose
monitoring
(CGM)
reveal
early
signs
glycemic
dysregulation,
while
T1D
genetic
scores
(GRS)
further
improve
disease
prediction.
We
use
CGM
data
GRS
to
develop
an
AB
classifier
(1
vs.
≥2
AB)
predict
risk.
Diabetology,
Journal Year:
2025,
Volume and Issue:
6(3), P. 17 - 17
Published: March 3, 2025
Continuous
glucose
monitoring
(CGM)
and
flash
(FGM)
systems
have
revolutionized
diabetes
management
by
delivering
real-time,
dynamic
insights
into
blood
levels.
This
article
provides
a
concise
overview
of
the
evolution
CGM
technology,
highlights
emerging
innovations
in
field
explores
current
potential
future
applications
(including
insulin
management,
early
diagnostics,
predictive
modeling,
education
integration
automated
delivery
(AID)
systems)
healthcare.
Journal of Diabetes Science and Technology,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Jan. 29, 2025
Background:
Glucose
is
an
essential
molecule
in
energy
metabolism.
Dysregulated
glucose
metabolism,
the
defining
feature
of
diabetes,
requires
active
monitoring
and
treatment
to
prevent
significant
morbidity
mortality.
Current
technologies
for
intermittent
continuous
measurement
are
invasive.
Noninvasive
would
eliminate
this
barrier
toward
making
more
accessible,
extending
benefits
from
people
living
with
diabetes
prediabetes
healthy.
Methods:
A
novel
spectroscopy-based
system
measuring
noninvasively
was
used
exploratory,
prospective,
single-center
clinical
study
(NCT06272136)
develop
test
a
machine
learning-based
computational
model
without
per-subject
calibration.
The
design
blinded
development
investigators
validation
analyses.
Results:
Twenty
subjects
were
enrolled.
Fifteen
set,
five
set.
All
participants
adults
insulin-treated
median
glycated
hemoglobin
(HbA
1c
)
7.3%
(interquartile
range
[IQR]
=
6.7-7.7).
resulted
mean
absolute
relative
difference
(MARD)
14.5%
96.5%
paired
data
points
plus
B
zones
Diabetes
Technology
Society
(DTS)
error
grid.
correlation
between
average
sensitivity
by
wavelength
spectrum
0.45
(
P
<
.001).
Conclusions:
Our
findings
suggest
that
Raman
spectroscopy
coupled
advanced
methods
can
enable
continuous,
noninvasive
invasive
Aim:
This
study
aims
to
evaluate
the
accuracy
of
continuous
glucose
monitoring
(CGM)-derived
metrics,
particularly
those
related
glycemic
variability,
in
presence
missing
data.
It
systematically
examines
effects
different
data
patterns
and
imputation
strategies
on
both
standard
metrics
complex
variability
metrics.
Methods:
The
analysis
modeled
compared
three
types
patterns-missing
completely
at
random,
segmental,
block-wise
gaps-with
proportions
ranging
from
5%
50%
CGM
derived
14-day
profiles
individuals
with
type
1
2
diabetes.
Six
were
assessed:
removal,
linear
interpolation,
mean
imputation,
piecewise
cubic
Hermite
temporal
alignment
random
forest-based
imputation.
Results:
A
total
933
468
diabetes
analyzed.
Across
all
coefficient
determination
(R2)
improved
as
proportion
decreased,
regardless
pattern.
impact
agreement
between
imputed
reference
varied
depending
To
achieve
high
(R2
>
0.95)
representing
true
least
70%
required.
While
no
strategy
fully
compensated
for
levels
data,
simple
removal
outperformed
others
most
scenarios.
Conclusion:
CGM-derived
findings
suggest
that
while
may
have
varying
metric
method,
removing
periods
without
is
a
general
acceptable
approach.
Diabetes Obesity and Metabolism,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Dec. 5, 2024
Abstract
With
the
widespread
use
of
continuous
glucose
monitoring
(CGM),
glycaemic
variability
(GV)
is
a
metric
that
has
been
gaining
increasing
attention.
However,
unlike
other
metrics
are
easily
defined
and
have
clear
targets,
GV
large
number
different
measures
given
complexity
involved
in
assessment.
While
variabilities
HbA1c,
fasting
postprandial
incorporated
under
banner,
short‐term
glucose,
within
day
between
days,
more
keeping
with
correct
definition
GV.
This
review
focused
on
GV,
as
assessed
by
CGM
data,
although
studies
calculating
from
capillary
testing
also
mentioned
appropriate.
The
addressed,
their
potential
role
microvascular
macrovascular
complications,
well
patient‐related
outcomes,
discussed.
It
should
be
noted
independent
vascular
pathology
not
always
clear,
inconsistent
findings
populations
close
association
hypoglycaemia,
itself
an
established
risk
factor
for
adverse
outcomes.
Therefore,
this
attempts,
where
possible,
to
disentangle
contribution
diabetes
complications
parameters,
particularly
hypoglycaemia.
Evidence
date
strongly
suggests
but
future
large‐scale
outcome
required
fully
understand
exact
complications.
can
followed
setting
appropriate
targets
subgroups,
order
optimise
management
limit
medRxiv (Cold Spring Harbor Laboratory),
Journal Year:
2024,
Volume and Issue:
unknown
Published: Aug. 19, 2024
Abstract
Glucose
is
an
essential
molecule
in
energy
metabolism.
Dysregulated
glucose
metabolism,
the
defining
feature
of
diabetes,
requires
active
monitoring
to
prevent
significant
morbidity
and
mortality.
Current
technologies
for
intermittent
continuous
measurement
are
invasive.
Non-invasive
would
eliminate
this
barrier
towards
making
more
accessible,
extending
benefits
from
people
living
with
diabetes
prediabetes
healthy.
We
developed
investigated
a
spectroscopy-based
system
measuring
non-invasively
without
per-person
calibration.
Using
data
study
including
adults
insulin-treated
we
constructed
computational
model
development
cohort
15
subjects
found
mean
absolute
relative
difference
14.5%
independent
validation
five
subjects.
The
correlation
between
average
sensitivity
by
wavelength
spectrum
was
0.45
(p<0.001).
Our
findings
suggest
that
non-invasive
invasive
calibration
possible.
