Association between triglyceride glucose-body mass index and the trajectory of cardio-renal-metabolic multimorbidity: insights from multi-state modelling
Cardiovascular Diabetology,
Journal Year:
2025,
Volume and Issue:
24(1)
Published: March 21, 2025
Although
some
studies
have
examined
the
association
between
triglyceride
glucose-body
mass
index
(TyG-BMI)
and
cardiovascular
outcomes
in
cardio-renal-metabolic
(CRM)
background,
none
explored
its
role
progression
of
CRM
multimorbidity.
In
addition,
prior
research
is
limited
by
small
sample
sizes
a
failure
to
account
for
competitive
effects
other
diseases.
this
study,
data
obtained
from
large-scale,
prospective
UK
Biobank
cohort
were
used.
multimorbidity
was
defined
as
new-onset
ischemic
heart
disease,
type
2
diabetes
mellitus,
or
chronic
kidney
disease
during
follow-up.
Multivariable
Cox
regression
used
analyse
independent
TyG-BMI
each
(first,
double,
triple
diseases).
The
C-statistic
calculated
model,
restricted
cubic
spline
applied
assess
dose–response
relationship.
A
multi-state
model
investigate
trajectory
(from
baseline
[without
disease]
first
double
disease),
with
disease-specific
analyses.
This
study
included
349,974
participants,
mean
age
56.05
(standard
deviation
[SD],
8.08),
55.93%
whom
female.
Over
median
follow-up
approximately
14
years,
56,659
(16.19%)
participants
without
developed
at
least
one
including
8451
(14.92%)
who
progressed
789
(9.34%)
further
disease.
crude
SD
increase
associated
47%
higher
risk
72%
95%
C-statistics
0.625,
0.694,
0.764,
respectively.
Multi-state
analysis
showed
32%
increased
new
24%
23%
those
significantly
onset
all
individual
diseases
(except
stroke)
transition
Significant
interactions
also
observed,
but
remained
across
subgroups.
Sensitivity
analyses,
varying
time
intervals
entering
states
an
expanded
definition
(including
atrial
fibrillation,
failure,
peripheral
vascular
obesity,
dyslipidaemia),
confirmed
these
findings.
remarkably
influences
Incorporating
it
into
prevention
management
could
important
public
health
implications.
Language: Английский
Cardiovascular–Kidney–Metabolic Syndrome: A New Paradigm in Clinical Medicine or Going Back to Basics?
Journal of Clinical Medicine,
Journal Year:
2025,
Volume and Issue:
14(8), P. 2833 - 2833
Published: April 19, 2025
Cardiovascular,
renal,
and
metabolic
diseases
are
pathophysiologically
interdependent,
posing
a
significant
global
health
challenge
being
associated
with
substantial
increase
in
morbidity
mortality.
In
2023,
the
American
Heart
Association
(AHA)
defined
this
complex
network
of
interconnected
conditions
as
cardiovascular–kidney–metabolic
(CKM)
syndrome.
This
syndrome
is
based
on
common
pathophysiological
mechanisms,
including
chronic
inflammation,
oxidative
stress,
hyperglycemia
insulin
resistance,
activation
renin–angiotensin–aldosterone
system
(RAAS),
neurohormonal
dysfunction,
which
trigger
vicious
cycle
where
impairment
one
organ
contributes
to
progressive
deterioration
others.
An
integrated
approach
these
conditions,
rather
than
treating
them
separate
entities,
supports
holistic
management
strategy
that
helps
reduce
burden
public
improve
patients’
quality
life.
Existing
focuses
lifestyle
modification,
glycemic
lipid
control,
use
nephroprotective
cardioprotective
therapies.
narrative
review
aims
synthesize
contextualize
existing
information
interactions
between
systems
diagnostic
approaches,
well
provide
an
overview
available
therapeutic
options.
Language: Английский
Association between cumulative changes of the triglyceride glucose index and incidence of stroke in a population with cardiovascular-kidney-metabolic syndrome stage 0–3: a nationwide prospective cohort study
Cardiovascular Diabetology,
Journal Year:
2025,
Volume and Issue:
24(1)
Published: May 12, 2025
The
triglyceride-glucose
(TyG)
index
was
associated
with
higher
risk
of
mortality
in
individuals
Cardiovascular-Kidney-Metabolic
(CKM)
syndrome
stages
0-3.
However,
the
relationship
between
cumulative
TyG
(cumTyG)
and
incidence
stroke
remains
unclear
CKM
Participants
stage
0-3
were
enrolled
from
China
Health
Retirement
Longitudinal
Study
(CHARLS)
2011
to
2015.
calculated
as
ln
[fasting
triglyceride
(mg/dL)×fasting
glucose
(mg/dL)/2],
cumTyG,
an
area-under-the-curve
estimate
(mean
×
time
span),
(TyG2012
+
2015)/2
*
(2015-2012).
control
levels
classified
using
k-mean
clustering
analysis.
Logistic
regression
used
analyze
effect
cumTyG
on
stroke.
Restricted
cubic
spline
models
(RCS)
performed
explore
potential
non-linear
at
different
A
total
4,700
participants
enrolled,
among
280
patients
had
developed
during
3-year
follow-up
period.
After
adjusting
for
confounders,
compared
class
1
group,
odds
ratio
(OR)
incidents
2
1.39
[95%
confidence
interval
(CI)
1.003,
1.92],
P
=
0.046;
OR
3
1.28
(95%
CI
0.92-1.77),
0.147,
4
0.84-1.94),
0.238.
Elevated
increase
(OR
1.13,
95%
1.05,
1.22,
0.002).
linear
restricted
regression.
increased
events
population
Long-term
dynamic
monitoring
changes
may
help
early
identification
high
developing
Language: Английский