Horm Metab Res 2023; 55(03): 176-183
DOI: 10.1055/a-2010-2345
Original Article: Endocrine Care
1
Emergency Department, Hospital of Chengdu University of Traditional
Chinese Medicine, Chengdu, China
2
Clinical Medical School, Chengdu University of Traditional Chinese
Medicine, Chengdu, China
,
1
Emergency Department, Hospital of Chengdu University of Traditional
Chinese Medicine, Chengdu, China
2
Clinical Medical School, Chengdu University of Traditional Chinese
Medicine, Chengdu, China
,
Mingfei Li
1
Emergency Department, Hospital of Chengdu University of Traditional
Chinese Medicine, Chengdu, China
2
Clinical Medical School, Chengdu University of Traditional Chinese
Medicine, Chengdu, China
,
Yun Lu
1
Emergency Department, Hospital of Chengdu University of Traditional
Chinese Medicine, Chengdu, China
2
Clinical Medical School, Chengdu University of Traditional Chinese
Medicine, Chengdu, China
› Author Affiliations
Funding Information
Science & Technology Department of Guangdong Province —
2020B1111100009
Science & Technology Department of Sichuan Province —
2019YFS0040
› Further Information
Also available at
Buy Article Permissions and Reprints
Abstract
Glycemic disorder may affect the outcomes of patients with intracerebral
hemorrhage (ICH). However, the association between glycemic variability (GV) and
prognosis in these patients remains to be determined. We performed a
meta-analysis to compressive the influence of GV on functional outcome and
mortality in patients with ICH. Observational studies comparing the risks of
poor functional outcome (defined as modified Rankin Scale>2) and
all-cause mortality between ICH patients with higher versus lower acute GV were
retrieved by systematic search of Medline, Web of Science, Embase, CNKI, and
Wanfang databases. A random-effect model was used to pool the data after
incorporating the between-study heterogeneity. Sensitivity analyses were
performed to evaluate the stability of the findings. Eight cohort studies
involving 3400 patients with ICH were included in the meta-analysis. The
follow-up duration was within 3 months after admission. All of the included
studies used standard deviation of blood glucose (SDBG) as the indicator of
acute GV. Pooled results showed that ICH patients with higher SDBG were
associated with a higher risk of poor functional outcome as compared to those
with lower SDBG [risk ratio (RR): 1.84, 95% confidence interval (CI):
1.41 to 2.42, p<0.001, I2=0%]. In addition, patients
with higher category of SDBG were also associated with a higher mortality risk
(RR: 2.39, 95% CI: 1.79 to 3.19, p<0.001,
I2=0%). In conclusion, high acute GV may be a predictor of poor
functional outcome and mortality of patients with ICH.
Key words
intracerebral hemorrhage -
glycemic variability -
mortality -
functional outcome -
meta-analysis
* These authors contributed equally to this work.
Publication History
Received: 31 October 2022
Accepted after revision: 02 January 2023
Article published online:
27 February 2023
© 2023. Thieme. All rights reserved.
Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany
References
1
Cordonnier C,
Demchuk A,
Ziai W.
et al.
Intracerebral haemorrhage: current approaches to acute management. Lancet 2018; 392: 1257-1268
2
Greenberg SM,
Ziai WC,
Cordonnier C.
et al.
2022 Guideline for the management of patients with spontaneous intracerebral
hemorrhage: a guideline from the American heart association/American
stroke association. Stroke 2022; 53: e282-e361
3
van Asch CJ,
Luitse MJ,
Rinkel GJ.
et al.
Incidence, case fatality, and functional outcome of intracerebral haemorrhage
over time, according to age, sex, and ethnic origin: a systematic review and
meta-analysis. Lancet Neurol 2010; 9: 167-176
4
Poon MT,
Fonville AF,
Al-Shahi Salman R..
Long-term prognosis after intracerebral haemorrhage: systematic review and
meta-analysis. J Neurol Neurosurg Psychiatry 2014; 85: 660-667
5
Pinho J,
Costa AS,
Araujo JM.
et al.
Intracerebral hemorrhage outcome: A comprehensive update. J Neurol Sci 2019; 398: 54-66
6
Dorn AY,
Sun PY,
Sanossian N.
et al.
Admission glycemic gap in the assessment of patients with intracerebral
hemorrhage. Clin Neurol Neurosurg 2021; 208: 106871
7
Tan X,
He J,
Li L.
et al.
Early hyperglycaemia and the early-term death in patients with spontaneous
intracerebral haemorrhage: a meta-analysis. Intern Med J 2014; 44: 254-260
8
Zheng J,
Yu Z,
Ma L.
et al.
Association between blood glucose and functional outcome in intracerebral
hemorrhage: a systematic review and meta-analysis. World Neurosurg 2018; 114: e756-e765
9
Naidech AM,
Levasseur K,
Liebling S.
et al.
Moderate hypoglycemia is associated with vasospasm, cerebral infarction, and
3-month disability after subarachnoid hemorrhage. Neurocrit Care 2010; 12: 181-187
10
Sadan O,
Feng C,
Vidakovic B.
et al.
Glucose variability as measured by inter-measurement percentage change is
predictive of in-patient mortality in aneurysmal subarachnoid hemorrhage. Neurocrit Care 2020; 33: 458-467
11
Ceriello A,
Monnier L,
Owens D..
Glycaemic variability in diabetes: clinical and therapeutic implications. Lancet Diabetes Endocrinol 2019; 7: 221-230
12
Rodbard D..
Glucose variability: a review of clinical applications and research
developments. Diabetes Technol Ther 2018; 20: S25-S215
13
Lin J,
Cai C,
Xie Y..
Acute glycemic variability and functional outcome in patients with acute
ischemic stroke: a meta-analysis. Horm Metab Res 2022; 54: 371-379
14
Lin J,
Cai C,
Xie Y.
et al.
Acute glycemic variability and mortality of patients with acute stroke: a
meta-analysis. Diabetol Metab Syndr 2022; 14: 69
15
Pu Z,
Lai L,
Yang X.
et al.
Acute glycemic variability on admission predicts the prognosis in hospitalized
patients with coronary artery disease: a meta-analysis. Endocrine 2020; 67: 526-534
16
Li X,
Zhang D,
Chen Y.
et al.
Acute glycemic variability and risk of mortality in patients with sepsis: a
meta-analysis. Diabetol Metab Syndr 2022; 14: 59
17
Kurtz P,
Claassen J,
Helbok R.
et al.
Systemic glucose variability predicts cerebral metabolic distress and mortality
after subarachnoid hemorrhage: a retrospective observational study. Crit Care 2014; 18: R89
18
Guo MF,
Sun BL..
Relationship between blood glucose and its variability with prognosis in
patients with severe intracerebral hemorrhage. Zhejiang Clin Med 2015; 17: 1953-1954
19
Okazaki T,
Hifumi T,
Kawakita K.
et al.
Blood glucose variability: a strong independent predictor of neurological
outcomes in aneurysmal subarachnoid hemorrhage. J Intensive Care Med 2018; 33: 189-195
20
Wada S,
Yoshimura S,
Inoue M.
et al.
Outcome prediction in acute stroke patients by continuous glucose
monitoring. J Am Heart Assoc 2018; 7
21
Wu YC,
Ding Z,
Wu J.
et al.
Increased glycemic variability associated with a poor 30-day functional outcome
in acute intracerebral hemorrhage. J Neurosurg 2018; 129: 861-869
22
Chen SP,
Lei KL,
Sun HL..
The correlation analysis between blood glucose variability and prognosis in
patients withs evere acute cerebral hemorrhage. Chin J Pract Nerv Dis 2020; 23: 1973-1978
23
Gao PT,
Fu ZQ..
The correlation between blood glucose variability and neurological function
recovery in patients with severe cerebral hemorrhage. Stroke Nerv Dis 2020; 27: 604-613
24
Santana D,
Mosteiro A,
Pedrosa L.
et al.
Clinical relevance of glucose metrics during the early brain injury period after
aneurysmal subarachnoid hemorrhage: an opportunity for continuous glucose
monitoring. Front Neurol 2022; 13: 977307
25
Page MJ,
McKenzie JE,
Bossuyt PM.
et al.
The PRISMA 2020 statement: an updated guideline for reporting systematic
reviews. BMJ 2021; 372: n71
26
Page MJ,
Moher D,
Bossuyt PM.
et al.
PRISMA 2020 explanation and elaboration: updated guidance and exemplars for
reporting systematic reviews. BMJ 2021; 372: n160
27
Higgins J,
Thomas J,
Chandler J.
et al.
Cochrane handbook for systematic reviews of interventions version 6.2. The Cochrane Collaboration. 2021
www.training.cochrane.org/handbook
28
Breyton AE,
Lambert-Porcheron S,
Laville M.
et al.
CGMS and glycemic variability, relevance in clinical research to evaluate
interventions in T2D, a literature review. Front Endocrinol (Lausanne) 2021; 12: 666008
29
Acosta JN,
Leasure AC,
Kuohn LR.
et al.
Admission hemoglobin levels are associated with functional outcome in
spontaneous intracerebral hemorrhage. Crit Care Med 2021; 49: 828-837
30
Wells GA,
Shea B,
O'Connell D.
et al.
The Newcastle-Ottawa scale (NOS) for assessing the quality of
nonrandomised studies in meta-analyses. 2010
http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp
31
Ziff OJ,
Lane DA,
Samra M.
et al.
Safety and efficacy of digoxin: systematic review and meta-analysis of
observational and controlled trial data. BMJ 2015; 351: h4451
32
Higgins JP,
Thompson SG..
Quantifying heterogeneity in a meta-analysis. Stat Med 2002; 21: 1539-1558
33
Patsopoulos NA,
Evangelou E,
Ioannidis JP..
Sensitivity of between-study heterogeneity in meta-analysis: proposed metrics
and empirical evaluation. Int J Epidemiol 2008; 37: 1148-1157
34
Egger M,
Davey Smith G,
Schneider M.
et al.
Bias in meta-analysis detected by a simple, graphical test. BMJ 1997; 315: 629-634
35
Valente T,
Arbex AK..
Glycemic variability, oxidative stress, and impact on complications related to
type 2 diabetes mellitus. Curr Diabetes Rev 2021; 17: e071620183816
36
Papachristoforou E,
Lambadiari V,
Maratou E.
et al.
Association of glycemic indices (hyperglycemia, glucose variability, and
hypoglycemia) with oxidative stress and diabetic complications. J Diabetes Res 2020; 7489795
37
Zheng Y,
Li R,
Fan X..
Targeting oxidative stress in intracerebral hemorrhage: prospects of the natural
products approach. Antioxidants (Basel) 2022; 11
38
Zhang Y,
Khan S,
Liu Y.
et al.
Oxidative stress following intracerebral hemorrhage: from molecular mechanisms
to therapeutic targets. Front Immunol 2022; 13: 847246
39
Yao Z,
Bai Q,
Wang G..
Mechanisms of oxidative stress and therapeutic targets following intracerebral
hemorrhage. Oxid Med Cell Longev 2021; 8815441
留言 (0)