Impact of abnormal glucose metabolism on the early neurological outcome in acute ischemic stroke patients treated with intravenous thrombolysis

DOI: https://doi.org/10.21203/rs.3.rs-2258874/v1

Abstract

Background and purpose:

Abnormal glucose metabolism status (AGM), including prediabetes and diabetes mellitus (DM) have been reported to be an important predictor of poor functional outcome in patients experiencing acute ischemic stroke (AIS). However, conclusions of recent studies are inconsistent about which AGM status increases the risk of post-thrombolysis early neurological deterioration (END). The purpose of this study was to evaluate the impact of AGM status on the risk of post-thrombolysis early neurological outcomes. We further investigated the influence of previous glucose control of diabetic patients on the post-thrombolysis early neurological outcomes evaluation.

Methods:

Prediabetes was identified as glycosylated hemoglobin (HbAlc) (%) level within the range of 5.7%-6.4%, and diabetes mellitus (DM) was diagnosed based on prior history of diabetes or an HbAlc≥6.5% and patients with HbAlc less than 5.7% were classified as normal glucose metabolism (NGM). Diabetic patients with good PGC had HbAlc <7%, diabetic patients with poor PGC had HbAlc≥7%. END was defined as a National Institutes of Health Stroke Scale Score (NIHSS) ≥ 4, ENI was defined as a ≥4-point decrease in NIHSS score or a complete resolution of neurological deficits, between the time of admission and 24 hours after IV-rtPA.

Results

In total, 261 (32.7%) patients were diagnosed with prediabetes, 91 (11.4%) patients were DM had good PGC and 186 (23.3%) patients were DM had poor PGC. After adjusted for confounders, in model 1, DM with poor PGC associated with the increased risk of post-thrombolysis END and poor functional outcome at discharge (OR, 2.09; 95% CI, 1.220-3.579; P=0.007) (OR, 1.91; 95% CI, 1.165-3.133; P=0.010), both prediabetes and DM with poor PGC were less likely to experience post-thrombolysis ENI (OR, 0.58; 95% CI, 0.377-0.907; P=0.016) (OR, 0.43; 95% CI, 0.255-0.71; P=0.001); in model 2, further adjusted for admission hyperglycemia, the presence of diabetes and DM with poor PGC was still independently related to post-thrombolysis ENI (OR, 0.62; 95% CI, 0.400-0.969; P=0.036) (OR, 0.51; 95% CI, 0.282-0.923; P=0.026).

Conclusion

Prediabetes and DM with poor PGC might be two abnormal blood glucose metabolism states that affects post-thrombolysis early neurological outcome in AIS patients.

Introduction

Abnormal glucose metabolism (AGM) is a common phenomenon in patients with acute ischemic stroke (AIS), a previous study showed that the prevalence of AGM was 68.7% among Chinese stroke patients. The proportion of diabetes mellites (DM) and pre-diabetes in all stroke patients were range from 21%-44.4% and 29%-53%, respectively[14]. Patients with AGM do not only have an increased risk of cerebrovascular disease, but also clearly associated with poor prognosis and mortality after acute ischemic stroke (AIS)[5, 6]. The deleterious role of DM in cerebrovascular diseases is well established, however, an undiagnosed AGM status, pre-diabetes, is gradually recognized as important modifiable risk factor of cerebrovascular diseases. Prediabetes is an intermediate metabolic state between normal glucose metabolism and DM, including impaired fasting glucose, impaired glucose tolerance and/or impaired glycosylated hemoglobin (HbAlc), which is highly prevalent in non-diabetic patients[6]. Compared with normal glucose metabolism (NGM), prediabetes was considered to be an important predictor of recurrent stroke and unfavorable functional outcome after stroke[7, 8].

Early neurological deterioration (END) after AIS is a prominent clinical issue that is strongly correlated with poor functional outcome and mortality after AIS[9, 10]. Metabolic factors such as hyperglycemia and DM have been identified as contributing factors for END[9, 11]. Several studies have reported a significant correlation between disturbed glucose metabolism and early END[5, 12], however, inconsistent conclusions exist regarding which AGM status increases the risk of END. The discrepancy among studies may be due to different diagnostic criteria for identifying pre-diabetes. In addition, previous glucose control (PGC) of diabetic patients could be relevant in outcome evaluation. However, limited data are available on the value of different PGC on the END after AIS. Therefore, the purpose of this study was to investigate the risk of END after intravenous thrombolysis in AIS patients with different AGM status, and we further analyzed the influence of PGC of diabetes on END.

Methods

Study population

This study retrospectively included consecutive patients with AIS treated with intravenous recombinant tissue-type plasminogen activator (IV-rtPA) Department of Neurology, ChangHai Hospital and The Second Affiliated Hospital of Xu Zhou Medical School from January 2017, to December 2020. Patients enrolled in this study if they: (1) aged 18 years or older; (2) were admission within 4.5 h after onset; and (3) were treatment with IV-rtPA. Patients were excluded from this study if they: (1) were diagnoses of malignant tumors, autoimmune diseases, major organ failure or presence of an active infection; and (2) had incomplete clinical data. We further excluded patients treated with IV-rtPA and endovascular thrombectomy to maintain the homogeneity of the enrolled patients. Written informed consent was obtained from participants or legal representatives. The study protocol was approved by Ethics Committee of ChangHai Hospital and The Second Affiliated Hospital of Xu Zhou Medical School.

Baseline assessments

Stroke severity was assessed via National Institutes of Health Stroke Scale (NIHSS). The Trial of Org 10172 in Acute Stroke Treatment (TOAST) criteria was used to classified stroke subtype[13]. The diagnosis of symptomatic intracranial hemorrhage (sICH) was based on the results of CT scans, combined with a NIHSS score of ≥ 4. Early malignant edema was considered if the brain was swollen, a midline shift was present, and consciousness worsened. A poor functional outcome at discharge was defined as a modified Rankin Scale (mRS) score of 3–6 at discharge. The mRS score were collected the day before discharge by two trained physicians independent of the study. The proximal artery occlusion confirmed by the Computed tomography angiography (CTA), Magnetic resonance angiography (MRA) and Digital subtraction angiography (DSA). Image data were reviewed in blind manner by two physicians, with advice of the third experienced physicians in case of disagreement.

Definition of post-thrombolysis early neurological outcome

The post-thrombolysis END was defined as a ≥ 4-point increase in NIHSS score between the time of admission and 24 hours after IV-rtPA. Meanwhile post-thrombolysis ENI was defined as a ≥ 4-point decrease in NIHSS score or a complete resolution of neurological deficits between the time of admission and 24 hours after IV-rtPA. Neurological deficit was evaluated on admission and at 24 hours after IV-rtPA by two certified neurologists blinded to the clinical data.

Assessment of abnormal glucose metabolism status

According to the recommended of American Diabetes Association (ADA), HbAlc level within the range of 5.7%-6.4% as identifying patients with prediabetes, DM was diagnosed based on prior history of diabetes or an HbAlc ≥ 6.5% and patients with HbAlc less than 5.7% were classified as NGM[14]. Diabetic patients were classified into 2 groups according to PGC, diabetic patients with good PGC had HbAlc < 7%, diabetic patients with poor PGC had HbAlc ≥ 7%[14]. Patients HbAlc was measured within 24 hours after hospitalization. Admission blood glucose was measured shortly after arrived the emergency room, hyperglycemia was defined as blood glucose levels higher than 7.8mmol/L[15].

Statistical analysis

The Kolmogorov–Smirnov test was performed to test the normality of variables, and continuous variables were described as the mean (standard deviation) and median (quartile) based on the normality of the data. Categorical variables are expressed as percentages. Differences in the baseline characteristics were assessed by χ2 test for categorical variables and ANOVA or Kruskal–Wallis test for continuous variables.

Multivariate logistical regression was performed to analysis the association of AGM and early neurological outcome, patients with NGM as the reference category. Two models were generated in this study: in mode l, the covariates entered in the multivariable logistical regression were age, admission NIHSS, time of onset to treatment (OTT), proximal artery occlusion, stroke subtype, sICH, malignant edema; model 2 was further adjusted for admission hyperglycemia (> 7.8mmol/L). Two-tailed P values of < 0.05 were considered statistically significant. Data analyses were performed using the statistical software package SPSS 22.0 for Windows (IBM, Armonk, NY).

Results

Baseline characteristics 

A total of 798 AIS patients treated with IV-rtPA were included in this study, 260 (32.6%) patients were NGM, 261 (32.7%) patients were prediabetes, 91 (11.4%) patients with DM had good PGC and 186 (23.3%) diabetic patients had poor PGC.

Table 1. compares the baseline characteristics in patients with different ENO group. Patients in the END group were more likely to be older (66 vs. 69 vs. 67, P=0.023), to have proximal artery occlusion (4.7% vs. 13.7% vs. 4.2%, P<0.001), to have a higher incidence of large artery atherosclerosis (25.4% vs. 41.7% vs. 30.9%, P<0.001), to have a higher proportion DM with poor PGC and lower proportion of NGM (23.7% vs. 31.7 vs. 16.2%; 32.3% vs. 24.5% vs. 39.3%, P=0.010). The admission NIHSS score were higher in END and ENI group (4 vs. 8 vs. 9, P<0.001). 

The baseline characteristics of patients grouped according to the glucose metabolism are provided in Table 2. Patients in prediabetic and DM with good PGC group were more older (66 vs. 68 vs. 69 vs. 66, P=0.035), the prevalence of  hypertension and coronary heart disease was higher in diabetic patients (64.2% vs. 66.7% vs. 82.4% vs. 68.3%, P=0.014) (9.2% vs. 10.4% vs. 25.6% vs. 14.5%, P<0.001). Diabetic patients with poor PGC have a significantly higher admission blood glucose than other groups (6.4 vs. 7.2 vs. 7.9 vs. 13.3, P<0.001) The proportion of current smoking and drinking is higher in NGM and prediabetic group (44.2% vs. 42.9% vs. 28.6% vs. 35.5%, P=0.024) (32.7% vs. 22.6% vs. 14.3% vs. 16.1%, P<0.001). The level of diastolic blood pressure and high-density lipoprotein is much higher in NGM and prediabetic group (89 vs. 89 vs. 83 vs. 85, P<0.001) (1.3 vs. 1.2 vs. 1.2 vs. 1.2, P<0.001). However, diabetic patients have a higher level of triglyceride (1.4 vs. 1.5 vs. 1.6 vs. 2.0, P=0.002), prediabetic and DM with poor PGC group have a higher level of fibrinogen (3.4 vs. 3.6 vs. 3.4 vs. 3.7, P=0.026). The incidence of poor functional outcome at discharge is higher in prediabetic and DM with poor PGC group (23.1% vs. 26.8% vs. 24.2% vs. 33.9%, P=0.076). 

Association of ABM and early neurological outcome 

In the multivariate logistical regression, according to model 1, which was adjusted for confounders, the risks of post-thrombolysis END and poor functional outcome at discharge in DM with poor PGC group was significantly higher than those patients in the NGM group (as the reference value) (OR, 2.09; 95% CI, 1.220-3.579; P=0.007) (OR, 1.91; 95% CI, 1.165-3.133; P=0.010), prediabetes and DM with poor PGC were less likely to experience post-thrombolysis ENI (OR, 0.58; 95% CI, 0.377-0.907; P=0.016) (OR, 0.43; 95% CI, 0.255-0.71; P=0.001). Model 2 was further adjusted for the admission hyperglycemia (>7.8mmol/L), the presence of diabetes and DM with poor PGC was still independently related to post-thrombolysis ENI (OR, 0.62; 95% CI, 0.400-0.969; P=0.036) (OR, 0.51; 95% CI, 0.282-0.923; P=0.026)(Table 3).

Discussion

In accordance with previous studies, this study confirmed the deleterious effect of abnormal glucose metabolism on poor prognosis and early neurological outcomes[5, 12]. Compared with normal glycemic, prediabetes and diabetic with poor PGC appears to be two high risk states of abnormal glucose metabolism. The prediabetes is defined as an intermediate state between normal glucose metabolism and DM, represent growing risks of developing diabetes[6]. Therefore, it is reasonable to suggest that prediabetes and diabetes affect post-thrombolysis early neurological outcomes in same directions. Moreover, the results of this study further confirmed the effect of pre-stroke PGC on the outcome evaluation.

According to the results of this study, diabetic patients with poor PGC had significantly higher admission blood glucose level than other groups, therefore, we considered that the underlying mechanisms may involve the deleterious effects of hyperglycemia. Firstly, hyperglycemia has direct toxic to the ischemic tissue by promoting development of cortical acidosis and associates with worsening mitochondrial function in ischemic penumbra, and further leads to recruitment of ischemic penumbra into infarction[16]. Second, patients with DM and hyperglycemia exhibit procoagulant and prothrombotic properties after AIS[17], in our research, the level of fibrinogen is higher in prediabetes and DM with poor PGC groups. The plasma factor VIIa (FVIIa) which were reported to contributed to enhanced blood coagulation after ischemic stroke by stimulating thrombin generation inducing fibrin deposition, platelet aggregation and thrombus formation[18]. The FVIIa levels were higher in diabetic patients than non-diabetic ischemic stroke patients, and the evaluations were persisted over time[17]. In addition, hyperglycemia and hyperinsulinemia can decrease the fibrinolytic activity by increasing the production of plasminogen activator inhibitor, further affects the activity of rt-PA and impaired recanalization after AIS[19]. Hyperglycemia also affects endothelium-dependent vasodilatation, reduce reperfusion in ischemic brain tissue and increase infarct volumes[20, 21]. Third, hyperglycemia is associated with increased reperfusion injury. Glucose was identified as requisite electron donor for reperfusion-induced neuronal superoxide production [22]. The formation of superoxide further leads to oxidative stress, increased oxidative stress can ultimately lead to neuron death and exacerbate ischemic brain injury[22]. Finally, the insulin resistance could also be involved in the mechanisms. Previous studies have confirmed that insulin resistance is independently associated with poor functional outcome after AIS[23]. The plausible explanations are insulin resistance may lead to proinflammatory and prothrombotic state[24, 25], these effects may further contribute to exacerbate ischemic damage in the brain and affect the response to intravenous thrombolysis[26]. High rates of insulin resistance were found in NIDDM and hypertriglyceridemia and in the low-HDL cholesterol states[27]. In our study, AIS patients with DM have a significantly higher hypertriglyceridemia, especially those with poor PGC. Low-HDL cholesterol states was common in patients with prediabetes and DM.

However, after adjusted for admission hyperglycemia, DM with poor PGC and prediabetes were remains to be an independent significant predictor of no post-thrombolysis ENI. Other factor could also be involved in this mechanism. Previous study have showed that glycemic fluctuation may occurred frequently in prediabetic patients, and the rapid glycemic fluctuation increase the production of oxidative stress and reactive oxygen species, indicating a high risk of END after AIS[28]. Pre-stroke medications may also contribute to the post-thrombolysis early neurological outcomes, in this study we found the prior use of antiplatelet is higher in diabetic patients with good PGC, in another study statin use was also reported to be significantly lower in prediabetic patients than in diabetic patients[6]. Absence of medication and lifestyle management may be a common problem in prediabetic patients and diabetic patients with poor PGC. The acute blood pressure level was associated with END after ischemic stroke[29], our results showed that diastolic blood pressure is significantly higher in prediabetic patients. Although, various factors may be involved, prediabetes and DM with poor PGC still had a significant impact on post-thrombolysis ENI even after adjustment for possible confounders.

The present study has several potential limitations that should be addressed when interpreting the results. First, this is a retrospective study; approximately one-fifth of the patients were excluded because they lacked HbAlc values, and we excluded patients treated with endovascular therapy after IV-rtPA, which inevitably produced biases. Second this study did not complete pre-stroke medication information, especially the use of hypoglycemic drug. Third, this study was performed in a single country, which might limit the generalizability of the results to other patient cohorts. However, the strengths of this study include the large sample size and the fact that patients were selected from multiple centers via strict inclusion and exclusion criteria. This study used HbAlc levels to identified patients with prediabetes, which can be unaffected by the acute-phase reaction[14].

Conclusion

In conclusion, prediabetes and DM with poor PGC might be two abnormal blood glucose metabolism states that affects post-thrombolysis early neurological outcome in AIS patients. This conclusion suggests that pre-stroke glucose metabolism states might become an important modifiable therapeutic targets in prevention of post-thrombolysis END and poor functional outcome.

Declarations

Ethics approval and consent to participate:

This study was conducted according to the protocol approved by the Human Subjects Research Ethics Committee of ChangHai Hospital (CHEC2019-143) and The Second Affiliated Hospital of Xu Zhou Medical School ([2021]0111301). Written informed consent was obtained from participants or legal representatives. In this study, all methods were performed in accordance with the relevant guidelines and regulations.

Consent for publication:

Not applicable 

Funding:

This study was supported by Scientific Research Fund of Anhui Medical University, the grant number: 2019xkj149.

Author contribution:

WL and HT designed the study and write the manuscript, WN , LHY and WL collected the data and performed the analysis, LHY WT, BXY and CQT were resiponsible for the data interpretation and manuscript revision. all authors reviewered the manuscript.

Competing interests:

The authors declare that they have no competing interest

Availability of data and materials:

The datasets are available from the corresponding author on reasonable request.

Acknowledgements

We thank all patients for their participant in this study. 

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Tables

Table 1

Baseline Characteristics of subgroups based on the presence of post-thrombolysis early neurological outcomes 

 

Neither END nor ENI group

(n = 470)

END group (n = 139)

ENI group (n = 189)

P

Demographics

       

Age, mean (SD), y

66 (10.9)

69 (12.5)

67 (11.6)

0.023

Male, n (%)

295 (63.0)

93 (66.9)

124 (64.9)

0.683

Vascular risk factors

       

Hypertension, n (%)

317 (67.7)

99 (71.2)

127 (66.5)

0.645

Atrial fibrillation, n (%)

57 (12.2)

22 (15.8)

31 (16.2)

0.292

Coronary heart disease, n (%)

52 (11.1)

16 (11.5)

33 (17.5)

0.079

Previous stroke, n (%)

93 (19.9)

27 (19.4)

35 (18.3)

0.901

Current smoking, n (%)

179 (38.2)

57 (41.0)

83 (43.5)

0.448

Current drinking, n (%)

107 (22.9)

35 (25.2)

45 (23.6)

0.851

Glucose metabolism status

     

0.010

NGM

151 (32.3)

34 (24.5)

75 (39.3)

 

Pre-diabetes

157 (33.5)

47 (33.8)

57 (29.8)

 

Good PGC-DM

49 (10.5)

14 (10.1)

28 (14.7)

 

Poor PGC-DM

111 (23.7)

44 (31.7)

31 (16.2)

 

Clinical data

SBP, mean (SD), mmHg

154 (20.7)

155 (21.1)

150 (23.6)

0.058

DBP, mean (SD), mmHg

87 (13.2)

89 (13.0)

87 (15.5)

0.365

Admission NIHSS, median (IQR)

4 (2–5)

8 (4–12)

9 (6–13)

< 0.001

Previous antiplatelet, n (%)

88 (18.8)

25 (18.0)

36 (18.8)

0.974

Proximal artery occlusion, n (%)

22 (4.7)

19 (13.7)

8 (4.2)

< 0.001

OTT, mean (SD), min

150 (58.4)

145 (59.0)

142 (62.2)

0.303

Stroke subtype, n (%)

     

< 0.001

LAA

119 (25.4)

58 (41.7)

59 (30.9)

 

CE

50 (10.7)

22 (15.8)

35 (18.3)

 

SAO

240 (51.3)

45 (32.4)

64 (33.5)

 

Others and Undetermined

59 (12.6)

14 (10.1)

33 (17.3)

 

Laboratory data

       

PLT, mean (SD)

217.4 (65.3)

204.0 (57.7)

213.5 (60.9)

0.089

TG, median (IQR), mmol/L

1.3 (0.9–1.8)

1.2 (0.9–1.8)

1.3 (1.0–2.0)

0.391

LDL, mean (SD), mmol/L

3.0 (1.0)

3.1 (0.9)

3.0 (0.9)

0.261

HDL, median (IQR), mmol/L

1.2 (1.0-1.4)

1.2 (1.1–1.5)

1.2 (1.1–1.4)

0.331

WBC, median (IQR)

7.5 (6.1–8.9)

7.9 (6.1–9.9)

7.5 (6.1–9.1)

0.055

FIB, median (IQR)

3.6 (3.1-4.0)

3.6 (3.1–4.1)

3.5 (3.1–4.1)

0.723

SD, standard deviation;IQR, interquartile range; NCM, Normal Glucose Metabolism; DM, Diabetes Mellitus; PGC, Previous Glucose Control;  ,  SBP, Systolic Blood Pressure; DBP, Diastolic Blood Pressure;  NIHSS, National Institutes of Health Stroke Scale; OTT, Onset-to-treatment; LAA, Large Artery Atherosclerosis; CE, Cardioe mbolism  SAO, Small Artery Occlusion; PLT, Platelet; TG, Triglyceride; LDL, Low-density Lipoprotein; FIB,  Fibrinogen; PLT, Platelet; WBC, White blood cell counts; NLR, Neutrophil-to-lymphocyte ratio; SHR, stress hyperglycemia ratio

 

T1 

T2

T3

P

Demographics

 

 

 

 

Age, mean (SD), y

66 (10.9)

69 (12.5)

67 (11.6)

0.023

Male, n (%)

295 (63.0)

93 (66.9)

124 (64.9)

0.683

Vascular risk factors  

 

 

 

 

Hypertension, n (%)

317 (67.7)

99 (71.2)

127 (66.5)

0.645

Atrial fibrillation, n (%)

57 (12.2)

22 (15.8)

31 (16.2)

0.292

Coronary heart disease, n (%)

52 (11.1)

16 (11.5)

33 (17.5)

0.079

Previous stroke, n (%)

93 (19.9)

27 (19.4)

35 (18.3)

0.901

Current smoking, n (%)

179 (38.2)

57 (41.0)

83 (43.5)

0.448

Current drinking, n (%)

107 (22.9)

35 (25.2)

45 (23.6)

0.851

Glucose metabolism status

 

 

 

0.010

      NGM

151 (32.3)

34 (24.5)

75 (39.3)

 

      Pre-diabetes

157 (33.5)

47 (33.8)

57 (29.8)

 

   Good PGC-DM

49 (10.5)

14 (10.1)

28 (14.7)

 

   Poor PGC-DM

111 (23.7)

44 (31.7)

31 (16.2)

 

Clinical data 

SBP, mean (SD), mmHg

154 (20.7)

155 (21.1)

150 (23.6)

0.058

DBP, mean (SD), mmHg

87 (13.2)

89 (13.0)

87 (15.5)

0.365

Admission NIHSS, median (IQR)

4 (2-5)

8 (4-12)

9 (6-13)

<0.001

Previous antiplatelet, n (%)

88 (18.8)

25 (18.0)

36 (18.8)

0.974

Proximal artery occlusion, n (%) 

22 (4.7)

19 (13.7)

8 (4.2)

<0.001

OTT, mean (SD), min

150 (58.4)

145 (59.0)

142 (62.2)

0.303

Stroke subtype, n (%)

 

 

 

<0.001

LAA

119 (25.4)

58 (41.7)

59 (30.9)

 

CE

50 (10.7)

22 (15.8)

35 (18.3)

 

SAO

240 (51.3)

45 (32.4)

64 (33.5)

 

Others and Undetermined 

59 (12.6)

14 (10.1)

33 (17.3)

 

Laboratory data

 

 

 

 

PLT, mean (SD)

217.4 (65.3)

204.0 (57.7)

213.5 (60.9)

0.089

TG, median (IQR), mmol/L

1.3 (0.9-1.8)

1.2 (0.9-1.8)

1.3 (1.0-2.0)

0.391

LDL, mean (SD), mmol/L

3.0 (1.0)

3.1 (0.9)

3.0 (0.9)

0.261

HDL, median (IQR), mmol/L

1.2 (1.0-1.4)

1.2 (1.1-1.5)

1.2 (1.1-1.4)

0.331

WBC, median (IQR)

7.5 (6.1-8.9)

7.9 (6.1-9.9)

7.5 (6.1-9.1)

0.055

FIB, median (IQR)

3.6 (3.1-4.0)

3.6 (3.1-4.1)

3.5 (3.1-4.1)

0.723


Table 2. Baseline characteristics of subgroups based on the glucose metabolism status.

 

NGM

(n = 260)

Pre-diabetes (n = 261)

Good PGC-DM (n = 91)

Poor PGC-DM

(n = 186)

P

Demographics

         

Age, mean (SD), y

66 (12.6)

68 (11.3)

69 (9.5)

66 (10.4)

0.035

Male, n (%)

174 (66.9)

166 (63.6)

57 (62.6)

115 (61.8)

0.698

Vascular risk factors

         

Hypertension, n (%)

167 (64.2)

174 (66.7)

75 (82.4)

127 (68.3)

0.014

Atrial fibrillation, n (%)

38 (14.6)

40 (15.3)

13 (14.3)

19 (10.2)

0.443

Coronary heart disease, n (%)

24 (9.2)

27 (10.4)

23 (25.6)

27 (14.5)

< 0.001

Previous stroke, n (%)

56 (21.5)

43 (16.5)

23 (25.3)

33 (17.7)

0.211

Current smoking, n (%)

115 (44.2)

112 (42.9)

26 (28.6)

66 (35.5)

0.024

Current drinking, n (%)

85 (32.7)

59 (22.6)

13 (14.3)

30 (16.1)

< 0.001

Clinical data

 

SBP, mean (SD), mmHg

154 (22.9)

154 (21.1)

150 (18.4)

152 (20.2)

0.485

DBP, mean (SD), mmHg

89 (13.5)

89 (14.8)

83 (12.5)

85 (12.2)

< 0.001

Admission NIHSS, median (IQR)

4 (3–9)

5 (3–10)

4 (3–9)

5 (3–10)

0.428

Previous antiplatelet, n (%)

48 (18.5)

46 (17.6)

21 (23.1)

34 (18.3)

0.711

Proximal artery occlusion, n (%)

15 (5.8)

19 (13.7)

4 (4.4)

11 (5.9)

0.766

OTT, mean (SD), min

155 (60.4)

143 (59.1)

140 (61.5)

146 (57.0)

0.059

Stroke subtype, n (%)

       

0.103

LAA

77 (29.6)

63 (24.1)

24 (26.4)

72 (38.7)

 

CE

39 (15.0)

39 (14.9)

10 (11.1)

19 (10.2)

 

SAO

108 (41.5)

120 (46.0)

46 (50.5)

75 (40.3)

 

Others and Undetermined

36 (13.8)

39 (14.9)

11 (12.1)

20 (10.8)

 

Poor outcome at discharge, n (%)

60 (23.1)

70 (26.8)

22 (24.2)

63 (33.9)

0.076

Laboratory data

         

PLT, mean (SD)

215.9 (66.6)

212.6 (57.8)

214.6 (69.3)

213.7 (62.6)

0.947

TG, mean (SD), mmol/L

1.4 (0.8)

1.5 (1.0)

1.6 (0.8)

2.0 (1.8)

0.002

LDL, mean (SD), mmol/L

3.0 (1.0)

3.0 (0.9)

2.9 (0.9)

3.1 (1.0)

0.078

HDL, mean (SD), mmol/L

1.3 (0.3)

1.2 (0.3)

1.2 (0.3)

1.2 (0.3)

< 0.001

WBC, median (IQR)

7.4 (6.0-8.9)

7.5 (6.0-8.9)

7.7 (6.1–9.3)

7.8 (6.4–9.2)

0.493

FIB, median (IQR)

3.4 (3.0-3.9)

3.6 (3.1-4.0)

3.4 (2.9-4.0)

3.7 (3.2–4.1)

0.026

Admission glucose, mean (SD),mmol/L

6.4 (1.4)

7.2 (1.7)

7.9 (2.6)

13.3 (4.9)

< 0.001

SD, standard deviation;IQR, interquartile range; NCM, Normal Glucose Metabolism; DM, Diabetes Mellitus; PGC, Previous Glucose Control; SBP, Systolic Blood Pressure; DBP, Diastolic Blood Pressure; NIHSS, National Institutes of Health Stroke Scale; OTT, Onset-to-treatment; LAA, Large Artery Atherosclerosis; CE, Cardioe mbolism SAO, Small Artery Occlusion; PLT, Platelet; TG, Triglyceride; LDL, Low-density Lipoprotein; HDL, High-density Lipoprotein; FIB, Fibrinogen; PLT, Platelet; WBC, White blood cell counts; NLR, Neutrophil-to-lymphocyte ratio;

 

Table 3

Multivariate logistical regression analyses depicting the association of GMS and respective outcomes

   

Model 1

Model 2

Outcome

GMS

OR

95%CI

P

OR

95% CI

P

Post-thrombolysis END

NGM

Ref

Ref

 

Ref

Ref

 

Pre-diabetes

1.34

0.789–2.277

0.278

1.17

0.680–2.008

0.574

Good PGC-DM

1.17

0.547–2.490

0.690

0.82

0.369–1.798

0.612

Poor PGC-DM

2.09

1.220–3.579

0.007

1.11

0.589–2.093

0.747

 

NGM

Ref

Ref

 

Ref

Ref

 

Post-thrombolysis

Pre-diabetes

0.58

0.377–0.907

0.016

0.62

0.400-0.969

0.036

Good PGC-DM

1.21

0.688–2.110

0.515

1.35

0.749–2.416

0.321

ENI

Poor PGC-DM

0.43

0.255–0.711

0.001

0.51

0.282–0.923

0.026

 

NGM

Ref

Ref

 

Ref

Ref

 

Poor outcome at discharge

Pre-diabetes

1.05

0.649–1.714

0.829

0.89

0.542–1.475

0.661

Good PGC-DM

1.18

0.603–2.299

0.632

0.86

0.428–1.717

0.664

Poor PGC-DM

1.91

1.165–3.133

0.010

1.05

0.582–1.901

0.866

END, Early Neurological Deterioration; ENI, Early Neurological Improvement; GMS, Glucose Metabolism Status; NGM, Normal Glucose Metabolism; DM, Diabetes Mellitus; PGC, Previous Glucose Control; CI, Confident Interval; OR, Odds Ratio; SHR, stress hyperglycemia ratio; P for trend.