Experimental and Clinical Endocrinology & Diabetes,
Год журнала:
2023,
Номер
131(01/02), С. 51 - 60
Опубликована: Янв. 13, 2023
Notice
of
Update
The
DDG
practice
recommendations
are
updated
regularly
during
the
second
half
calendar
year.
Please
ensure
that
you
read
and
cite
respective
current
version.
Diabetes Care,
Год журнала:
2023,
Номер
46(4), С. 704 - 713
Опубликована: Фев. 7, 2023
Maintenance
of
glycemic
control
during
and
after
exercise
remains
a
major
challenge
for
individuals
with
type
1
diabetes.
Glycemic
responses
to
may
differ
by
(aerobic,
interval,
or
resistance),
the
effect
activity
on
unclear.The
Type
Diabetes
Exercise
Initiative
(T1DEXI)
was
real-world
study
at-home
exercise.
Adult
participants
were
randomly
assigned
complete
six
structured
aerobic,
resistance
sessions
over
4
weeks.
Participants
self-reported
nonstudy
exercise,
food
intake,
insulin
dosing
(multiple
daily
injection
[MDI]
users)
using
custom
smart
phone
application
provided
pump
(pump
users),
heart
rate,
continuous
glucose
monitoring
data.A
total
497
adults
diabetes
(mean
age
±
SD
37
14
years;
mean
HbA1c
6.6
0.8%
[49
8.7
mmol/mol])
aerobic
(n
=
162),
interval
165),
170)
analyzed.
The
(±
SD)
change
in
-18
39,
-14
32,
-9
36
mg/dL
resistance,
respectively
(P
<
0.001),
similar
results
closed-loop,
standard
pump,
MDI
users.
Time
range
70-180
(3.9-10.0
mmol/L)
higher
24
h
when
compared
days
without
76
20%
vs.
70
23%;
P
0.001).Adults
experienced
largest
drop
level
followed
regardless
delivery
modality.
Even
well-controlled
diabetes,
contributed
clinically
meaningful
improvement
time
but
have
slightly
increased
below
range.
IEEE Transactions on Biomedical Engineering,
Год журнала:
2021,
Номер
68(7), С. 2251 - 2260
Опубликована: Янв. 5, 2021
Continuous
glucose
monitoring
(CGM)
enables
prediction
of
the
future
concentration
(GC)
trajectory
for
making
informed
diabetes
management
decisions.
The
values
are
affected
by
various
physiological
and
metabolic
variations,
such
as
physical
activity
(PA)
acute
psychological
stress
(APS),
in
addition
to
meals
insulin.
In
this
work,
we
extend
our
adaptive
modeling
framework
incorporate
effects
PA
APS
on
GC
predictions.A
wristband
conducive
use
free-living
ambulatory
people
is
used.
measured
variables
analyzed
generate
new
quantifiable
input
features
APS.
Machine
learning
techniques
estimate
type
intensity
when
they
occur
individually
concurrently.
Variables
quantifying
characteristics
both
integrated
exogenous
inputs
an
system
identification
technique
enhancing
accuracy
predictions.
Data
from
clinical
experiments
illustrate
improvement
accuracy.The
average
mean
absolute
error
(MAE)
one-hour-ahead
predictions
with
testing
data
decreases
35.1
31.9
mg/dL
(p-value
=
0.01)
inclusion
information,
it
16.9
14.2
0.006)
information.The
first-ever
model
developed
that
incorporates
measures
improve
accuracy.Modeling
will
enable
meal,
insulin
dosing
Current Topics in Diabetes,
Год журнала:
2022,
Номер
2(1), С. 1 - 130
Опубликована: Янв. 30, 2022
2022
Guidelines
on
the
management
of
patients
with
diabetes
A
position
Diabetes
Poland
Rules
for
diagnosing
carbohydrate
metabolism
disordersKey
recommendations•
Blood
sugar
tests
early
detection
prediabetes/type
2
should
be
performed
people
over
45,
as
well
younger
overweight
or
obese
if
there
is
at
least
one
additional
risk
factor
diabetes.[B]•
Women
not
previously
diagnosed
undergo
an
oral
glucose
tolerance
test
between
24
th
and
28
week
pregnancy
to
diagnose
gestational
diabetes.[A]•
Diagnosing
in
children
during
first
9
weeks
after
birth
requires
genetic
neonatal
diabetes.[a]•
Patients
cystic
fibrosis
aged
10
above
each
year
diabetes.[a]Diabetes
a
group
metabolic
diseases
characterised
by
hyperglycaemia
resulting
from
defect
insulin
secretion
and/or
activity.Chronic
associated
damage,
dysfunction
failure
various
organs,
especially
eyes,
kidneys,
nerves,
heart
blood
vessels.
I.
Symptoms
indicative
potentialdiabetes
significant
hyperglycaemia:•
increased
diuresis
(polyuria);•
thirst;•
loss
weight
explained
intentional
dieting;•
other,
less
typical
symptoms:
weakness
sleepiness,
purulent
skin
lesions
inflammation
genitourinary
organs.
II.
disorders:•
symptoms
occur,
random
performed,
result
≥
200
mg/dl
(≥
11.1
mmol/l)
constituting
grounds
diabetes;2022
Prevention
delay
Key
pre-diabetes
given
recommendations
healthy
lifestyle
(physical
activity
150
min/week;
case
patients,
reduction
7%
maintenance)
information
effectiveness
such
measures
preventing
development
Apart
modification
lifestyle,
pharmacological
prevention
form
metformin
considered
pre-diabetic
concomitant
IFG
IGT
body
mass
index
(BMI)
35
kg/m
under
60
years
age,
women
history
mellitus.[a]•
Screening
using
fasting
glucose,
glucose.[c]
Type
1
diabetesCurrently,
no
effective
method
type
either
general
population
at-risk
people.Type
1.
test.2.
Risk
factors
(see
chapter
1).
Review
delaying
diabetes:2022
Monitoring
Most
therapy
multiple
daily
injections
self-monitor
(SMBG)
both
before
meals,
bedtime,
planned
physical
activity,
when
low
suspected,
activities
where
hypoglycaemia
particularly
dangerous
(e.g.driving).[B]
Setting
objectives
managementKey
In
individuals
diabetes,
overall
target
glycaemic
control
expressed
HbA
1c
level
more
than
7.0%
(53
mmol/mol).[a]•
LDL
fraction
cholesterol
55
(less
1.4mmol/l)
50%
baseline
very
high
cardiovascular
LDL-C
concentration
70
(1.8
levels
100
(2.6
moderate
(young
yrs.with
without
chronic
complications
other
below
50
duration
years,
factors).[a]•
Recommended
arterial
pressure:
130/80
mm
Hg.
[a]
Diabetes Care,
Год журнала:
2023,
Номер
47(1), С. 132 - 139
Опубликована: Ноя. 3, 2023
Data
from
the
Type
1
Diabetes
Exercise
Initiative
Pediatric
(T1DEXIP)
study
were
evaluated
to
understand
glucose
changes
during
activity
and
identify
factors
that
may
influence
changes.In
this
real-world
observational
study,
adolescents
with
type
diabetes
self-reported
physical
activity,
food
intake,
insulin
dosing
(multiple-daily
injection
users)
using
a
smartphone
application.
Heart
rate
continuous
monitoring
data
collected,
as
well
pump
downloads.Two
hundred
fifty-one
(age
14
±
2
years
[mean
SD];
HbA1c
7.1
1.3%
[54
14.2
mmol/mol];
42%
female)
logged
3,738
activities
over
∼10
days
of
observation.
Preactivity
was
163
66
mg/dL
(9.1
3.7
mmol/L),
dropping
148
(8.2
mmol/L)
by
end
activity;
median
duration
40
min
(20,
75
[interquartile
range])
mean
peak
heart
109
16
bpm
130
21
bpm.
Drops
in
greater
those
lower
baseline
levels
(P
=
0.002),
shorter
disease
0.02),
less
hypoglycemia
fear
0.04),
BMI
0.05).
Event-level
predictors
drops
included
self-classified
"noncompetitive"
activities,
on
board
>0.05
units/kg
body
mass,
already
prior
preactivity
>150
(>8.3
time
70-180
>70%
24
h
before
(all
P
<
0.001).Participant-level
event-level
can
help
predict
magnitude
drop
youth
diabetes.
A
better
appreciation
these
improve
decision
support
tools
self-management
strategies
reduce
activity-induced
dysglycemia
active
living
disease.
Diabetes Care,
Год журнала:
2021,
Номер
45(1), С. 194 - 203
Опубликована: Ноя. 17, 2021
OBJECTIVE
To
compare
glucose
control
with
hybrid
closed-loop
(HCL)
when
challenged
by
high
intensity
exercise
(HIE),
moderate
(MIE),
and
resistance
(RE)
while
profiling
counterregulatory
hormones,
lactate,
ketones,
kinetic
data
in
adults
type
1
diabetes.
RESEARCH
DESIGN
AND
METHODS
This
study
was
an
open-label
multisite
randomized
crossover
trial.
Adults
diabetes
undertook
40
min
of
HIE,
MIE,
RE
random
order
using
HCL
(Medtronic
MiniMed
670G)
a
temporary
target
set
2
h
prior
to
during
15
g
carbohydrates
if
pre-exercise
<126
mg/dL
prevent
hypoglycemia.
Primary
outcome
median
(interquartile
range)
continuous
monitoring
time-in-range
(TIR;
70–180
mg/dL)
for
14
post–exercise
commencement.
Accelerometer
venous
glucose,
hormones
were
measured
280
RESULTS
Median
TIR
81%
(67,
93%),
91%
(80,
94%),
80%
(73,
89%)
0–14
commencement
RE,
respectively
(n
=
30),
no
difference
between
types
(MIE
vs.
HIE;
P
0.11,
MIE
0.11;
HIE
0.90).
Time-below-range
0%
all
bouts.
For
compared
there
greater
increases,
respectively,
noradrenaline
(P
0.01
0.004),
cortisol
<
0.001
0.001),
lactate
≤
heart
rate
0.007
0.015).
During
increases
growth
hormone
0.024).
CONCLUSIONS
Under
controlled
conditions,
provided
satisfactory
type.
Lactate,
differentiate
exercise,
their
measurement
may
help
inform
insulin
needs
exercise.
However,
potential
utility
as
modulators
dosing
will
be
limited
the
pharmacokinetics
subcutaneous
delivery.
Applied System Innovation,
Год журнала:
2020,
Номер
3(3), С. 31 - 31
Опубликована: Июль 28, 2020
This
paper
presents
a
comprehensive
survey
about
the
fundamental
components
of
artificial
pancreas
(AP)
system
including
insulin
administration
and
delivery,
glucose
measurement
(GM),
control
strategies/algorithms
used
for
type
1
diabetes
mellitus
(T1DM)
treatment
control.
Our
main
focus
is
on
T1DM
that
emerges
due
to
pancreas’s
failure
produce
sufficient
loss
beta
cells
(β-cells).
We
discuss
various
delivery
methods
physiological
methods,
open-loop,
closed-loop
schemes.
Furthermore,
we
report
several
factors
such
as
hyperglycemia,
hypoglycemia,
many
other
physical
need
be
considered
while
infusing
in
human
body
via
AP
systems.
three
prominent
algorithms
proportional-integral-
derivative
(PID),
fuzzy
logic,
model
predictive,
which
have
been
clinically
evaluated
all
shown
promising
results.
In
addition,
linear
non-linear
infusion
schemes
formally
discussed.
To
best
our
knowledge,
this
first
work
systematically
covers
recent
developments
with
solid
foundation
future
studies
field.