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Horm Metab Res 2021; 53(11): 746-751
DOI: 10.1055/a-1648-7767
Endocrine Care

Predictive Value of Insulin Resistance as Determined by Homeostasis Model Assessment in Acute Ischemic Stroke Patients: A Systematic Review and Meta-Analysis

An Wu‡
1   Department of Neurosurgery, Quzhou Hospital Affiliated to Wenzhou University, Quzhou, China
,
Yunping Li‡
1   Department of Neurosurgery, Quzhou Hospital Affiliated to Wenzhou University, Quzhou, China
,
Rongcai Liu
1   Department of Neurosurgery, Quzhou Hospital Affiliated to Wenzhou University, Quzhou, China
,
Dongjing Qi
1   Department of Neurosurgery, Quzhou Hospital Affiliated to Wenzhou University, Quzhou, China
,
Guofeng Yu
1   Department of Neurosurgery, Quzhou Hospital Affiliated to Wenzhou University, Quzhou, China
,
Xinjiang Yan
1   Department of Neurosurgery, Quzhou Hospital Affiliated to Wenzhou University, Quzhou, China
,
Dandan Mao
1   Department of Neurosurgery, Quzhou Hospital Affiliated to Wenzhou University, Quzhou, China
,
Xiang Li
1   Department of Neurosurgery, Quzhou Hospital Affiliated to Wenzhou University, Quzhou, China
,
Richeng Zhou
1   Department of Neurosurgery, Quzhou Hospital Affiliated to Wenzhou University, Quzhou, China
,
Weimin Dai 
1   Department of Neurosurgery, Quzhou Hospital Affiliated to Wenzhou University, Quzhou, China
› Author Affiliations Funding Information This work was supported by 2020 municipal science and technology plan competitive projects (2020K46).
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Abstract

Studies on association between homeostasis model assessment of insulin resistance (HOMA-IR) and adverse outcomes have yielded conflicting results in patients with acute ischemic stroke (AIS). This meta-analysis aimed to assess the predictive value of HOMA-IR in AIS patients. Two authors comprehensively searched PubMed and Embase databases until February 28, 2021. All observational studies investigating the association between HOMA-IR and adverse outcomes in AIS patients were included. Outcome measures were poor functional outcome (Modified Rankin Scale≥3), all-cause mortality, stroke recurrence, and neurologic worsening. Seven studies (eight articles) involving 8330 AIS patients were identified. For the highest versus lowest HOMA-IR, the pooled risk ratio (RR) of poor functional outcome was 2.55 (95% CI 1.76–3.70) after adjustment of conventional confounding factors. In addition, elevated HOMA-IR was associated with higher risk of neurologic worsening (RR 1.93; 95% CI 1.15–3.26). However, there were conflicting findings on the association of HOMA-IR with stroke recurrence and all-cause mortality. This meta-analysis confirms that HOMA-IR is significantly associated with an increased risk of poor functional outcome in patients with AIS. However, interpretation of the results of mortality, stroke recurrence, and neurologic worsening should be done with caution due to small number of studies available.

Key words

insulin resistance - HOMA-IR - acute ischemic stroke - poor functional outcome - meta-analysis

Supplementary Material



Publication History

Received: 16 March 2021

Accepted after revision: 15 September 2021

Article published online:
05 November 2021

© 2021. Thieme. All rights reserved.

Georg Thieme Verlag
Rüdigerstraße 14, 70469 Stuttgart, Germany

 

  • References

  • 1 Shiber JR, Fontane E, Adewale A. Stroke registry: Hemorrhagic vs. ischemic strokes. Am J Emerg Med 2010; 28: 331-333
    CrossrefPubMedGoogle Scholar
  • 2 Herpich F, Rincon F. Management of acute ischemic stroke. Crit Care Med 2020; 48: 1654-1663
    CrossrefPubMedGoogle Scholar
  • 3 Whiteley W, Chong WL, Sengupta A. et al Blood markers for the prognosis of ischemic stroke: A systematic review. Stroke 2009; 40: e380-e389
    CrossrefPubMedGoogle Scholar
  • 4 Adeva-Andany MM, Martinez-Rodriguez J, Gonzalez-Lucan M. et al Insulin resistance is a cardiovascular risk factor in humans. Diabetes Metab Syndr 2019; 13: 1449-1455
    CrossrefPubMedGoogle Scholar
  • 5 Matthews DR, Hosker JP, Rudenski AS. et al Homeostasis model assessment: Insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985; 28: 412-419
    CrossrefPubMedGoogle Scholar
  • 6 Aberg D, Aberg ND, Jood K. et al Homeostasis model assessment of insulin resistance and outcome of ischemic stroke in non-diabetic patients - a prospective observational study. BMC Neurol 2019; 19: 177
    CrossrefPubMedGoogle Scholar
  • 7 Calleja AI, Garcia-Bermejo P, Cortijo E. et al Insulin resistance is associated with a poor response to intravenous thrombolysis in acute ischemic stroke. Diabetes Care 2011; 34: 2413-2417
    CrossrefPubMedGoogle Scholar
  • 8 Ago T, Matsuo R, Hata J. et al Insulin resistance and clinical outcomes after acute ischemic stroke. Neurology 2018; 90: e1470-e1477
    CrossrefPubMedGoogle Scholar
  • 9 Jing J, Pan Y, Zhao X. et al Insulin resistance and prognosis of nondiabetic patients with ischemic stroke: The ACROSS-China study (Abnormal glucose regulation in patients with acutestroke across China). Stroke 2017; 48: 887-893
    CrossrefPubMedGoogle Scholar
  • 10 Li S, Yin C, Zhao W. et al Homeostasis model assessment of insulin resistance in relation to the poor functional outcomes in nondiabetic patients with ischemic stroke. Biosci Rep. 2018 38.
    PubMedGoogle Scholar
  • 11 Yang X, Li C, Li J. et al Insulin resistance is significantly related with worse clinical outcomes in non-diabetic acute ischemic stroke patients treated with intravenous thrombolysis. J Stroke Cerebrovasc Dis 2021; 30: 105526
    CrossrefPubMedGoogle Scholar
  • 12 Liberati A, Altman DG, Tetzlaff J. et al The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: Explanation and elaboration. J Clin Epidemiol 2009; 62: e1-e34
    CrossrefPubMedGoogle Scholar
  • 13 Wells G, Shea B, O’Connell D. et al The Newcastle–Ottawa Scale (NOS) for assessing the quality if nonrandomized studies in meta-analyses. http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp
    PubMedGoogle Scholar
  • 14 Mi D, Wang Y, Liu L. Insulin resistance is an independent risk factor for early neurological deterioration in non-diabetic patients with acute ischemic stroke. Neurol Sci 2020; 41: 1467-1473
    CrossrefPubMedGoogle Scholar
  • 15 Chang Y, Kim CK, Kim MK. et al Insulin resistance is associated with poor functional outcome after acute ischemic stroke in non-diabetic patients. Sci Rep 2021; 11: 1229
    CrossrefPubMedGoogle Scholar
  • 16 Qiu HC, Liu HZ, Li X. et al Insulin resistance as estimated by homeostasis model assessment predicts incident post-stroke depression in Chinese subjects from ischemic stroke. J Affect Disord 2018; 231: 1-7
    CrossrefPubMedGoogle Scholar
  • 17 Gu T, Yang Q, Ying G. et al Lack of association between insulin resistance as estimated by homeostasis model assessment and stroke risk: A systematic review and meta-analysis. Med Hypotheses 2020; 141: 109700
    CrossrefPubMedGoogle Scholar
  • 18 Pan Y, Chen W, Wang Y. Prediabetes and outcome of ischemic stroke or transient ischemic attack: A systematic review and meta-analysis. J Stroke Cerebrovasc Dis 2019; 28: 683-692
    CrossrefPubMedGoogle Scholar
  • 19 Lau LH, Lew J, Borschmann K. et al Prevalence of diabetes and its effects on stroke outcomes: a meta-analysis and literature review. J Diabetes Investig 2019; 10: 780-792
    CrossrefPubMedGoogle Scholar
  • 20 Liu C, Feng M, Fang XH. et al Metabolic syndrome is an independent risk factor for cardiovascular disease events in patients with ischemic stroke. Zhonghua Xin Xue Guan Bing Za Zhi 2011; 39: 358-362
    PubMedGoogle Scholar
  • 21 Lee M, Saver JL, Liao HW. et al Pioglitazone for secondary stroke prevention: A systematic review and meta-analysis. Stroke 2017; 48: 388-393
    CrossrefPubMedGoogle Scholar
  • 22 Wallace TM, Levy JC, Matthews DR. Use and abuse of HOMA modeling. Diabetes Care 2004; 27: 1487-1495
    CrossrefPubMedGoogle Scholar
  • 23 Lau J, Ioannidis JP, Terrin N. et al The case of the misleading funnel plot. BMJ 2006; 333: 597-600
    CrossrefPubMedGoogle Scholar