Assessment of stress hyperglycemia ratio to predict all-cause mortality in patients with critical cerebrovascular disease: a retrospective cohort study from the MIMIC-IV database
Yuwen Chen,
No information about this author
Jian Xu,
No information about this author
Fan He
No information about this author
et al.
Cardiovascular Diabetology,
Journal Year:
2025,
Volume and Issue:
24(1)
Published: Feb. 7, 2025
The
association
between
the
stress
hyperglycemia
ratio
(SHR),
which
represents
degree
of
acute
hyperglycemic
status,
and
risk
mortality
in
cerebrovascular
disease
patients
intensive
care
unit
(ICU)
remains
unclear.
This
study
aims
to
investigate
predictive
ability
SHR
for
in-hospital
critically
ill
assess
its
potential
enhance
existing
models.
We
extracted
data
from
Medical
Information
Mart
Intensive
Care
(MIMIC-IV)
database
diagnosed
with
used
Cox
regression
mortality.
To
nature
this
association,
we
applied
restricted
cubic
spline
analysis
determine
if
it
is
linear.
was
evaluated
using
receiver
operating
characteristic
(ROC)
curves
C-index.
included
a
total
2,461
patients,
mean
age
70.55
±
14.59
years,
1,221
(49.61%)
being
female.
revealed
that
independently
associated
both
(per
standard
deviation
(SD)
increase:
hazard
(HR)
1.35,
95%
confidence
interval
(CI)
1.23-1.48)
ICU
SD
HR
1.37,
CI
1.21-1.54).
death
increased
an
approximately
linear
fashion
when
exceeded
0.77-0.79.
Subgroup
indicated
more
pronounced
non-diabetic
individuals.
Additionally,
incorporating
into
models
improved
discrimination
reclassification
performance.
serves
as
independent
factor
ICU.
Adding
enhances
their
performance,
offering
clinical
value
identification
high-risk
patients.
Language: Английский
Association between stress hyperglycemia ratio and contrast-induced nephropathy in ACS patients undergoing PCI: a retrospective cohort study from the MIMIC-IV database
BMC Cardiovascular Disorders,
Journal Year:
2025,
Volume and Issue:
25(1)
Published: Feb. 25, 2025
Contrast-induced
nephropathy
(CIN)
is
a
significant
complication
in
acute
coronary
syndrome
(ACS)
patients
undergoing
percutaneous
intervention
(PCI).
The
role
of
the
stress
hyperglycemia
ratio
(SHR)
as
predictor
CIN
and
mortality
these
remains
unclear
warrants
investigation.
To
assess
relationship
between
SHR
CIN,
well
its
impact
on
short-term
ACS
PCI.
We
conducted
retrospective
cohort
study
using
MIMIC-IV
database,
including
552
patients.
was
calculated
admission
glucose
to
estimated
average
from
hemoglobin
A1c.
defined
≥
0.5
mg/dL
or
25%
increase
serum
creatinine
within
48
h
Logistic
regression
spline
models
were
used
analyze
association
while
Kaplan–Meier
curves
assessed
30-day
mortality.
Higher
levels
independently
associated
with
increased
risk
(OR
2.36,
95%
CI:
1.56–3.57,
P
<
0.0001).
A
J-shaped
observed,
rising
sharply
when
exceeded
1.06.
also
higher
(P
Subgroup
analysis
revealed
stronger
SHR-CIN
non-diabetic
an
independent
It
offers
potential
for
stratification
clinical
decision-making,
especially
Language: Английский
Estimated glucose disposal rate outperforms other insulin resistance surrogates in predicting incident cardiovascular diseases in cardiovascular-kidney-metabolic syndrome stages 0–3 and the development of a machine learning prediction model: a nationwide prospective cohort study
Bingtian Dong,
No information about this author
Yuping Chen,
No information about this author
Xiaocen Yang
No information about this author
et al.
Cardiovascular Diabetology,
Journal Year:
2025,
Volume and Issue:
24(1)
Published: April 16, 2025
Background
The
American
Heart
Association
recently
introduced
the
concept
of
cardiovascular-kidney-metabolic
(CKM)
syndrome,
highlighting
increasing
importance
complex
interplay
between
metabolic,
renal,
and
cardiovascular
diseases
(CVD).
While
substantial
evidence
supports
a
correlation
estimated
glucose
disposal
rate
(eGDR)
CVD
events,
its
predictive
value
compared
with
other
insulin
resistance
(IR)
indices,
such
as
triglyceride–glucose
(TyG)
index,
TyG-waist
circumference,
TyG-body
mass
TyG-waist-to-height
ratio,
triglyceride-to-high
density
lipoprotein
cholesterol
metabolic
score
for
resistance,
remains
unclear.
Methods
This
prospective
cohort
study
utilized
data
from
China
Health
Retirement
Longitudinal
Study
(CHARLS).
individuals
were
categorized
into
four
subgroups
based
on
quartiles
eGDR.
associations
eGDR
incident
evaluated
using
multivariate
logistic
regression
analyses
restricted
cubic
spline.
Seven
machine
learning
models
to
assess
index
events.
To
model’s
performance,
we
applied
receiver
operating
characteristic
(ROC)
precision-recall
(PR)
curves,
calibration
decision
curve
analysis.
Results
A
total
4,950
participants
(mean
age:
73.46
±
9.93
years),
including
50.4%
females,
enrolled
in
study.
During
follow-up
2011
2018,
697
(14.1%)
developed
CVD,
486
(9.8%)
heart
disease
263
(5.3%)
stroke.
outperformed
six
IR
indices
predicting
demonstrating
significant
linear
relationship
all
outcomes.
Each
1-unit
increase
was
associated
14%,
19%
lower
risk
disease,
stroke,
respectively,
fully
adjusted
model.
incorporation
significantly
improved
prediction
performance
area
under
ROC
PR
curves
equal
or
exceeding
0.90
both
training
testing
sets.
Conclusions
outperforms
stroke
CKM
syndrome
stages
0–3.
Its
enhances
stratification
may
aid
early
identification
high-risk
this
population.
Further
studies
are
needed
validate
these
findings
external
cohorts.
Graphical
abstract
Language: Английский