Insulin resistance may affect the functional recovery of acute ischemic stroke in non-diabetic patients



Background Insulin resistance is associated with the occurrence of stroke and atherosclerotic disease. However, the relationship between insulin resistance and the prognosis of acute ischemic stroke in nondiabetic patients is unclear. We hypothesized that insulin resistance may affect short-term functional recovery after acute ischemic stroke in nondiabetic patients.

Methods Between May 2014 and December 2016, 1377 consecutive patients with acute ischemic stroke were enrolled from a prospectively maintained stroke registry. After excluding patients with transient ischemic attacks (TIA), pre-stroke disabilities, diabetes mellitus, and patients with incomplete evaluations, 517 patients were included in the study. The homeostasis model assessment of insulin resistance (HOMA-IR) score was used to evaluate the degree of insulin resistance. The factors associated with poor functional outcomes were analyzed using multivariate logistic regression.

Results The patients with the highest quartile of log HOMA-IR index scores were younger and had higher fasting blood glucose, total cholesterol, triglycerides, low-density lipoprotein, and HbA1c levels. Multivariate logistic regression analysis revealed that log HOMA-IR scores were independently associated with poor prognosis after adjusting for age and sex and p < 0.1 in univariate analysis.

Conclusion Insulin resistance measured by the HOMA-IR index was associated with the poor functional outcome of non-diabetic stroke patients. This evidence supports treating insulin resistance in acute ischemic stroke patients with blood glucose levels within the normal range.


Insulin resistance is defined as the loss of insulin effectiveness on target tissues and is observed in patients with type 2 diabetes mellitus.[1, 2] Insulin resistance results in impaired glucose utilization and increases hepatic glucose production. Among biomarkers of insulin resistance, the homeostasis model assessment-insulin resistance (HOMA-IR) index is an easy way to assess insulin resistance and is frequently used in epidemiologic studies.[3] Unlike previously identified roles of insulin in nutrient metabolism and its target organs, liver, fat, and muscle, the role of insulin in the central nervous system is still unclear.

In the field of cerebrovascular diseases, recent studies have suggested that a strong relationship exists between insulin resistance and ischemic stroke. Insulin resistance has been reported to be associated with poor clinical outcomes after IV thrombolysis.[4, 5] Pioglitazone improved insulin sensitivity and recurrent cardiovascular disease in patients with ischemic strokes or transient ischemic attacks.[6, 7] A recent study in China reported that insulin resistance was associated with poor 1-year outcomes after acute ischemic strokes.[8] However, the reason for and mechanism of the association between insulin resistance and the prognosis of stroke patients has not been fully identified.

In this study, we hypothesized that insulin resistance may affect short-term functional recovery after acute ischemic strokes in nondiabetic patients. We aimed to determine whether this relationship was affected by stroke severity, stroke subtype, and clinical course.



Between May 2014 and December 2016, 1377 patients with acute ischemic strokes within seven days from symptom-onset were enrolled from a prospectively maintained stroke registry at our institution. In these 1377 patients, patients with transient ischemic attacks (TIA, n = 301) and pre-stroke disabilities (modified Rankin scale (mRS) score ≥ 2, n = 71) were excluded. After excluding the diabetic patients (n = 334) and those without three months of functional outcome data (n = 98) or insulin levels (n = 56), 517 patients were enrolled in the study (Fig. 1). This study was approved by the Institutional Review Board of our institution. Patient consent was waived due to the retrospective registry-based nature of the study.

Insulin Resistance

Fasting glucose and insulin levels were measured within 24 hours of admission. The HOMA-IR was used to assess patients with insulin resistance. HOMA-IR scores were calculated by the following equation: [fasting insulin level (uU/mL)] × [fasting glucose level (mmol/L)] / 22.5. HOMA-IR values were log-transformed due to their non-normal distribution. Subsequently, the log-transformed HOMA-IR values were categorized into quartiles (< 0.23, 0.23–0.36, 0.36–0.53, and > 0.53).

Clinical and Laboratory Variables

Baseline demographics and previous history of hypertension, diabetes mellitus, dyslipidemia, coronary artery disease, peripheral artery disease, or cardiac arrhythmia were collected in all patients. Routine blood tests; chest X-rays; 12-lead electrocardiograms; transthoracic echocardiographies; and brain imaging data, including computed tomography (CT), magnetic resonance imaging (MRI), and cerebral angiographic study using CT or/and MRI, were performed. Stroke severity was assessed by National Institutes of Health Stroke Scale (NIHSS) scores and the Trial of Org 10172 in Acute Stroke Treatment (TOAST) classification was used to determine the subtypes of stroke etiology.[9] To assess the clinical course, the presence of early neurological deterioration, defined as an increase in NIHSS score more than 2 points during admission, was collected. Functional outcome three months after the stroke onset was assessed through outpatient visits or centralized telephone follow-ups. Patient follow-ups were processed by a physician or a well-trained stroke nurse using a standardized interview protocol. Poor functional outcome was defined as a score of 3 or more on the mRS score.

Statistical Analysis

All statistical analyses were performed using SPSS (version 23.0, IBM Corp., Armonk NY, USA). The baseline characteristics were compared using Chi-squared (χ2) tests, independent t-tests, and analysis of variance (ANOVA) tests, as appropriate. The crude odds ratios (OR) with 95% confidence intervals (CIs) for poor functional outcomes at three months were estimated by using the logistic regression model. The multivariate logistic regression model was used to further evaluate the relationship between HOMA-IR values and poor functional outcome. A two-tailed p-value of less than 0.05 was considered significant.


Demographics and comparison of patients according to log HOMA-IR scores

The mean age of the patients was 65.3 ± 13.5 years and 65.2% were male. The median HOMA-IR value was 2.31 (interquartile range 1.68–3.42). When comparing patients according to the log HOMA-IR values divided into quartiles, age, fasting blood glucose levels, BMI, lipid levels, and HbA1c values were different among the quartiles. The patients in the highest quartile tended to be younger and had higher fasting blood glucose, total cholesterol, triglycerides, low-density lipoprotein, and HbA1c levels (Table 1). The presence of END was not different between the groups. There was no statistical difference in the rate of poor prognosis among the log HOMA-IR quartiles, but the mRS distribution showed a tendency of higher mRS score distributions in the highest quartile (Fig. 2).

Table 1
Baseline characteristics according to log homeostasis model assessment of insulin resistance scores quartiles
HOMA-IR, quartiles
Q1 (n = 129)
Q2 (n = 132)
Q3 (n = 128)
Q4 (n = 128)
Age (years)
67.7 ± 14.2
65.9 ± 11.0
64.8 ± 13.2
62.6 ± 13.1
Male sex
79 (61.2)
91 (68.9)
80 (62.5)
87 (68.0)
58 (45.0)
70 (53.0)
73 (57.0)
72 (56.2)
Previous coronary artery disease
6 (4.7)
13 (9.8)
9 (7.0)
9 (7.0)
Previous stroke
11 (8.5)
15 (11.4)
13 (10.2)
9 (7.0)
Body mass index (kg/m2)
22.6 ± 2.9
24.0 ± 2.7
24.2 ± 4.1
25.2 ± 3.5
< 0.001
Fasting blood glucose (mg/dL)
93.1 ± 10.5
100.0 ± 13.9
107.2 ± 23.0
120.7 ± 26.1
< 0.001
Total cholesterol level (mg/dL)
184.2 ± 37.5
188.9 ± 42.0
191.5 ± 37.6
196.0 ± 40.4
Triglycerides level (mg/dL)
101.8 ± 54.1
123.4 ± 72.6
136.2 ± 87.8
154.0 ± 116.6
< 0.001
High-density lipoprotein cholesterol (mg/dL)
47.8 ± 12.9
46.2 ± 12.4
42.5 ± 10.0
44.9 ± 10.6
Low-density lipoprotein cholesterol (mg/dL)
108.6 ± 32.3
114.8 ± 37.0
117.1 ± 32.9
117.6 ± 33.6
Hemoglobin A1c (%)
5.5 ± 0.4
5.6 ± 0.4
5.6 ± 0.4
5.7 ± 0.4
Systolic blood pressure (mmHg)
150.5 ± 28.2
150.3 ± 28.6
150.5 ± 29.6
149.1 ± 28.4
Diastolic blood pressure (mmHg)
89.3 ± 13.6
88.0 ± 15.5
87.5 ± 16.0
89.7 ± 16.5
Initial NIHSS score, median (IQR)
3 (1–6)
2 (1–5)
3 (1–5)
3 (1–6)
TOAST classification subtype
Large artery atherosclerosis
30 (23.3)
32 (24.2)
37 (28.9)
43 (33.6)
40 (31.0)
23 (17.4)
18 (14.1)
20 (15.6)
Small vessel occlusion
25 (19.4)
39 (29.5)
37 (28.9)
25 (19.5)
28 (21.7)
29 (22.0)
31 (24.2)
31 (24.2)
6 (4.7)
9 (6.8)
5 (3.9)
9 (7.0)
Early neurological deterioration
4 (3.1)
12 (9.1)
6 (4.7)
8 (6.2)
Poor neurological outcome at 3 months
30 (23.3)
29 (22)
34 (26.6)
41 (32.0)
Data are expressed as the mean ± SD, or n (%).
HOMA-IR, homeostasis model assessment of insulin resistance scores; NIHSS, National Institutes of Health Stroke Scale (NIHSS); IQR, interquartile range; TOAST, the Trial of Org 10172 in Acute Stroke Treatment;

Association between log HOMA-IR values and short-term prognosis after ischemic stroke

Of all the subjects, 25.9% had poor prognoses. Table 2 shows a comparison of patients according to their prognosis three months after an acute ischemic stroke. The log HOMA-IR values were higher in patients with poor prognoses (p = 0.06). After adjustment for age, sex, and variables with p-values < 0.1 in univariate analysis, the log HOMA-IR scores were independently associated with poor prognosis (OR = 3.877, 95% CI: 1.461–10.288, p = 0.006) (Table 2).

Table 2
Factors associated with poor functional outcome at 3 months after ischemic stroke.
Good prognosis (mRS < 3)
(n = 383)
Poor prognosis (mRS ≥ 3)
(n = 134)
Multivariable logistic regression
Model 1
Model 2
Age (years)
63.2 (12.9)
71.2 (11.5)
< 0.001
< 0.001
< 0.001
Male sex
251 (65.5)
86 (64.2)
192 (50.1)
81 (60.4)
Previous coronary artery disease
17 (4.4)
20 (14.9)
< 0.001
Previous stroke
28 (7.3)
20 (14.9)
HOMA-IR, median (IQR)
2.26 (1.66–3.23)
2.55 (1.75–3.99)
Log HOMA-IR, mean (SD)
0.38 ± 0.26
0.45 ± 0.26
Body mass index (kg/m2)
24.0 ± 3.7
23.8 ± 2.9
Fasting blood glucose (mg/dL)
104.4 ± 22.8
107.4 ± 19.0
Total cholesterol level (mg/dL)
189.7 ± 38.5
191.4 ± 42.2
Triglycerides level (mg/dL)
131.2 ± 89.6
121.8 ± 81.4
High-density lipoprotein cholesterol (mg/dL)
45.6 ± 11.7
44.7 ± 11.6
Low-density lipoprotein cholesterol (mg/dL)
113.0 ± 33.8
119.0 ± 34.6
< 0.001
Hemoglobin A1c (%)
5.6 ± 0.4
5.6 ± 0.4
Systolic blood pressure (mmHg)
149.7 ± 29.8
151.4 ± 25.2
Diastolic blood pressure (mmHg)
88.3 ± 15.9
89.4 ± 13.9
Initial NIHSS score, median (IQR)
4 (2–5)
6 (3–13)
< 0.001
< 0.001
< 0.001
TOAST classification subtype
< 0.001
Large artery atherosclerosis
96 (25.1)
46 (34.3)
71 (18.5)
30 (22.4)
Small vessel occlusion
113 (29.5)
13 (9.7)
81 (21.1)
38 (28.4)
22 (5.7)
7 (5.2)
Early neurological deterioration
11 (2.9)
19 (14.2)
< 0.001
< 0.001
< 0.001
Data are expressed as the mean ± SD, or n (%).
mRS, modified Rankin Scale; HOMA-IR, homeostasis model assessment of insulin resistance scores; IQR, interquartile range; NIHSS, National Institutes of Health Stroke Scale (NIHSS); TOAST, the Trial of Org 10172 in Acute Stroke Treatment;


Our study showed that log HOMA-IR scores were significantly associated with the poor functional outcome of non-diabetic ischemic stroke patients. This association remained statistically significant even the age of the highest quartiles of log HOMA-IR was youngest among quartiles and the relationship was sustained after adjusting for cardiovascular risk factors and lipid profile abnormalities.

In this study, the initial stroke severity and the presence of END did not differ between the log HOMA-IR quartiles. These results indicate that the harmful effect of insulin resistance impacts the recovery phase of acute ischemic stroke and is not associated with worsening of a preexisting impairment. A study based on the Fukuoka registry in Japan also reported that HOMA-IR scores were related to poor functional outcomes.[10] There were no associations with the recurrence of stroke or mortality, which supports our hypothesis. Another study reported that the HOMA-IR index scores were associated with increased mortality, recurrent stroke, and poor outcomes.[8] The differences between the study results may be due to different study populations.

Some hypotheses may explain the association between insulin resistance and poor patient outcome after an ischemic stroke. One of them involves the concept of synaptic plasticity. Synaptic plasticity is the ability of a neuron to change the synapse in response to external stimuli and activity. In the brain, the insulin/IGF receptor signaling pathway maintains the balance between neuroprotective and neurotoxic effects.[1113] Insulin resistance is defined as a loss of this function in insulin ligands. Subsequently, the balance is upset, causing changes in the survival of the neurons and synaptic plasticity. Likewise, the synaptic plasticity of the brain decreases in stroke patients with high insulin resistance, which interferes with its recovery from the primary insult. Second, insulin resistance in muscles may have contributed to the poor prognosis of these patients. Type 2 diabetes mellitus patients evolve whole-body insulin resistance and insulin resistance in skeletal muscles reduces glucose transport pathways, which results in excessive reactive oxygen species and mitochondrial dysfunction.[14, 15] This may interrupt recovery after an acute ischemic stroke. Third, endothelial damage might play a role. Endothelial function is related to vascular reactivity in the cerebral circulation.[16] Insulin and insulin resistance affect the vascular endothelium.[1618] Furthermore, insulin resistance is a risk factor for atherosclerosis.[19, 20] Endothelial dysfunction, decreased vascular reactivity, and enhanced atherosclerosis might cause recurrent stroke and delayed restoration.

Our study had some strengths. First, we demonstrated that the worsening effect of insulin resistance on ischemic stroke impacted the recovery phase. This finding indicates that we should treat insulin resistance itself, apart from diabetes mellitus, especially in the subacute stage of an acute ischemic stroke. Second, unlike previous studies, we thoroughly investigated the risk factors, including laboratory and clinical factors, associated with poor prognoses. Body mass index, individual lipid levels, and blood pressure levels were collected and adjusted for in the multivariate analysis and the association between insulin resistance and poor clinical outcome remained strong. There were several limitations to this study. First, the HOMA-IR scores were only determined once, within 24 hours of admission. This might not reflect the exact status of insulin resistance during the recovery period. Second, the HOMA-IR index scores for insulin resistance mainly reflect resistance in hepatic metabolism. Third, this was a single-center data review from a comprehensive stroke center in Korea. Consequently, the results cannot be generalized to other populations and races.


Insulin resistance measured by the HOMA-IR index was associated with the poor functional outcome of non-diabetic stroke patients. This finding may strengthen the need for treatment of insulin resistance itself in acute ischemic stroke patients with blood glucose levels within the normal range.


mRS, modified Rankin scale; HOMA-IR, homeostasis model assessment-insulin resistance; CT, computed tomography; MRI, magnetic resonance imaging; NIHSS, National Institutes of Health Stroke Scale, TOAST, Trial of Org 10172 in Acute Stroke Treatment; ANOVA, analysis of variance; OR, odds ratio; CI, confidence interval


Ethics approval and consent to participate

This study was approved by Korea University of College of Medicine Institutional Review Board. Informed consent of study participants was waived because of retrospective study design.


Availability of data and materials

Not applicable.


Competing interests

The authors declare that they have no competing interests





Authors' contributions

YC, CKK and KO contributed to conception and design of the study, YC and CKK analyzed and interpreted the patient data. YC and CKK drafted the manuscript. MK, WKS and KO critically revised the manuscript. All authors read and approved the final manuscript.


Consent for publication

Not applicable.


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