Effect of stress-induced hyperglycemia after non-traumatic non-aneurysmal subarachnoid hemorrhage on clinical complications and functional outcomes

DOI: https://doi.org/10.21203/rs.3.rs-944631/v1

Abstract

Background

Despite having an overall benign course, non-traumatic non-aneurysmal subarachnoid hemorrhage (naSAH) is still accompanied by a risk of clinical complications and poor outcomes. Risk factors and mechanisms of complications and poor outcomes after naSAH remain unknown. Our aim was to explore the effect of stress-induced hyperglycemia (SIH) on complication rates and functional outcomes in naSAH patients.

Methods

We retrospectively reviewed patients with naSAH admitted to our institution between 2013 and 2018. SIH was identified according to previous criterion. Symptomatic vasospasm, delayed cerebral infarction, and hydrocephalus were identified as main complications. Outcomes were reviewed using a modified Rankin Scale (mRS) at discharge, 3 months, and 12 months. A statistical analysis of clinical, radiological, and laboratory risk factors of complications and outcomes was conducted.

Results

244 naSAH patients were incorporated in the cohort with 74 (30.3%) SIH. After adjusting for age, gender, hypertension, Hunt and Hess (HH) grade, modified Fisher Scale (mFS), intraventricular hemorrhage (IVH), and subarachnoid blood distribution, SIH was significantly associated with symptomatic vasospasm (P < 0.001, 12.176 [4.904–30.231]), delayed cerebral infarction (P < 0.001, 12.434 [3.850-40.161]), hydrocephalus (P = 0.008, 5.771 [1.570-21.222]), and poor outcome at 12 months (P = 0.006, 5.506 [1.632–18.581]), whereas the correlation between SIH and poor outcome at discharge (P = 0.064, 2.409 [0.951-6.100]) or 3 months (P = 0.110, 2.029 [0.852–4.833]) was not significant. Incorporation of SIH increased the area under curve (AUC) of ROC in the combined model for predicting symptomatic vasospasm (P = 0.002), delayed cerebral infarction (P = 0.024), hydrocephalus (P = 0.037), and 12-month poor outcome (P = 0.087).

Conclusions

SIH is a significant and independent risk factor for symptomatic vasospasm, delayed cerebral infarction, hydrocephalus, and long-term poor outcome in naSAH patients. Identifying SIH early after naSAH is important for decision-making and treatment planning.

Background

In approximately 15% of spontaneous subarachnoid hemorrhage (SAH) patients, the source of intracranial hemorrhage could not be determined [13]. These are termed non-traumatic non-aneurysmal SAH (naSAH) [4]. Compared with aneurysmal SAH (aSAH), naSAH has an overall benign course of disease [5]. However, some patients with naSAH still develop clinical complications or achieve poor functional outcomes despite their mild condition at admission [57]. The risk factors and pathophysiological mechanisms of clinical complications and poor outcomes after naSAH remain unknown.

Stress-induced hyperglycemia (SIH) is a transient hyperglycemia caused by an acute illness [8]. It is an adaptive immune-neurohormonal response to stress, and is often associated with increased morbidity and mortality [8]. Post-SAH hyperglycemia may cause secondary brain damage and cerebral vasospasm [9, 10]. Previous studies have shown that post-aSAH hyperglycemia was associated with a higher incidence of clinical complications and adverse outcomes, as well as higher mortality [1114]. However, the prognostic value of SIH in patients with naSAH has not yet been established. Moreover, these studies did not differentiate between SIH and established diabetes mellitus (DM).

Therefore, the objective of this study was to examine the effect of SIH on naSAH patients' complication rates and functional outcomes, and to investigate the prognostic value of SIH for clinical complications and poor outcomes following naSAH.

Methods

Patients and management

We retrospectively reviewed patients suffering from naSAH that were admitted to our institution between January 1, 2013 and December 31, 2018. SAH was diagnosed by computed tomography (CT) or lumbar puncture. Non-traumatic SAH without confirmed bleeding source in cerebral digital subtraction angiography (DSA) examination within 72 hours of admission was identified as naSAH [15]. Additionally, patients that met the following criteria were excluded: (1) history of a head injury; (2) history of DM; (3) missing/lost radiological data; (4) missing/lost laboratory data. All aspects of this study were approved by the institutional board of the Second Affiliated Hospital of Zhejiang University School of Medicine. With their approval, patient consent was not required in this study.

All patients were treated according to SAH guidelines provided by the Neurocritical Care Society and the American Heart Association [16, 17]. Nimodipine was used to prevent cerebral vasospasm, and intravenous hydration was received to maintain euvolemia. Hemodynamic values were monitored via electrocardiogram at admission. All patients were not treated with insulin during hospitalization.

Data Collection

The baseline characteristics of the patients were reviewed, including age, gender, body mass index (BMI), as well as history of alcohol, smoking, and hypertension. The Hunt and Hess (HH) grade, modified Fisher Scale (mFS), and development of intraventricular hemorrhage (IVH) were used to assess SAH severity [18, 19]. Scores ranging from 3 to 5 for HH grade and 3 to 4 for mFS were considered high. According to the subarachnoid blood distribution, the patients were stratified into patients with perimesencephalic subarachnoid hemorrhage (PMH) and patients with non-PMH (NPMH) [4, 5, 15]. The laboratory data were investigated at admission, including serum glucose, total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), sodium, and potassium. SAH-related complications were reviewed during hospitalization, including symptomatic vasospasm, delayed cerebral infarction, rebleeding, hydrocephalus, and seizure [20]. We followed up with all patients in an outpatient clinic or by phone calls. The modified Rankin Scale (mRS) of patients at discharge, 3 months, and 12 months were investigated to assess the functional outcomes [21].

According to the latest consensus from the American Association of Clinical Endocrinologists and American Diabetes Association, SIH was defined as at least one of the following criteria: (1) an admission serum glucose level of 7.8 mmol/L (140 mg/dL) or more; (2) an in-hospital fasting serum glucose level of 7.0 mmol/L (126 mg/dL) or more on 2 or more determinations,; (3) a random serum glucose level of 11.1 mmol/L (200 mg/dL) or more without a prior history of DM [22].

Outcome Measurements

The primary outcomes included the development of clinical complications and poor outcomes. The main clinical complications included symptomatic vasospasm, delayed cerebral infarction, and hydrocephalus. Symptomatic vasospasm referred to either a focal neurological impairment or a decrease of at least 2 points on the Glasgow Coma Scale (GCS) lasting for at least 1 hour, which was not immediately apparent after SAH onset, and was not attributable to other causes [23]. Delayed cerebral infarction was diagnosed as a new infarction emerging on CT or magnetic resonance imaging (MRI), which had not originally been present within the first 24–48 hours after SAH onset, and was not attributable to other causes [23]. Hydrocephalus was defined as an expansion of the ventricular system on neuroimaging without obstructive cause or typical clinical presentation [24]. Functional outcomes were reviewed at discharge, 3 months, and 12 months using an mRS. Due to the overall favorable prognosis of naSAH patients, mRS scores ranging from 2 to 6 were considered poor outcome [15]. Two senior neurologists independently evaluated all clinical complications and functional outcomes of the patients. If there was a divergence, a third examiner would be used.

Statistical analysis

Statistical analysis was performed using IBM-SPSS V24.0 (SPSS Inc, Armonk, NY) with the statistical significance set at P < 0.05. Normally distributed variables were expressed as means ± standard deviations (SD), and non-normally distributed variables were expressed as median and interquartile range (IQR). Categorical variables were expressed as the number of patients (percentage). Student’s t-test and Mann-Whitney U-test were respectively used to compare the normally and non-normally distributed variables. Chi-square or Fisher’s exact test was used to compare the categorical variables. Variables with a P < 0.10 in univariate analysis were included in the multivariate logistic regression model to identify the independent risk factors of clinical complications and poor outcomes. Odds ratio (OR) and 95% confidence interval (Cl) were calculated. Receiver operating curve (ROC) was drawn using Prism 8 (GraphPad Software, Inc, LA Jolla, CA). The area under curve (AUC) was calculated to assess the ability of the models to predict clinical complications and poor outcomes.

Results

Patient characteristics

There were 296 patients diagnosed with naSAH in this study. Thirteen patients had a history of head injury. Twenty-two patients suffered from DM. Ten patients were missing radiological data and seven patients were missing laboratory data. Thus, 244 patients were included in the final cohort, with 74 (30.3%) suffering from SIH (Fig. 1). Among the patients, 108 (44.3%) were women, and the average age was 55.7 ± 11.2 years.

Table 1 shows the baseline characteristics, complications, and outcomes of the patients. Patients with SIH had a higher age (P = 0.004) and a higher proportion of hypertension (P = 0.002) and NPMH (P = 0.010). Regarding SAH severity, the HH grade 3–5 (P < 0.001), mFS 3–4 (P = 0.003), and IVH (P = 0.026) all correlated with SIH. In addition, SIH patients were more likely to develop SAH-related complications, including symptomatic vasospasm, delayed cerebral infarction, and hydrocephalus (all P < 0.001). They also had a higher proportion of mRS 2–6 at discharge (P = 0.013), 3 months (P < 0.001) and 12 months (P < 0.001). Figure 2 shows the subarachnoid blood distribution characteristic, HH grade, mFS, and IVH incidence of SIH and non-SIH patients. The main in-hospital complication rates and mRS distribution of the two groups of patients are shown in Fig. 3.

Table 1

Baseline characteristics, complications, and outcomes of SIH and non-SIH patients

     

Total (n = 244)

     

Variable

SIH (n = 74)

non-SIH (n = 170)

P value

Age, yr

58.8 ± 10.5

54.4 ± 11.2

0.004

Gender, female

39 (52.7)

69 (40.6)

0.080

Alcohol

27 (36.5)

67 (39.4)

0.666

Smoke

25 (33.8)

63 (37.1)

0.624

Hypertension

35 (47.3)

46 (27.1)

0.002

NPMH

33 (44.6)

47 (27.6)

0.010

HH grade 3–5

19 (25.7)

11 (6.5)

< 0.001

mFS 3–4

26 (35.1)

30 (17.6)

0.003

IVH

23 (31.1)

31 (18.2)

0.026

BMI, kg/m2

23.9 ± 3.1

23.6 ± 2.7

0.474

Glucose, mmol/L

9.24 ± 2.03

6.35 ± 0.78

< 0.001

TC, mmol/L

4.86 ± 1.05

4.80 ± 1.05

0.732

TG, mmol/L

1.51 ± 0.88

1.39 ± 0.72

0.383

HDL-C, mmol/L

1.34 ± 0.34

1.28 ± 0.29

0.221

LDL-C, mmol/L

2.59 ± 0.81

2.68 ± 0.81

0.454

Sodium, mmol/L

139.3 ± 4.0

139.0 ± 3.3

0.491

Potassium, mmol/L

3.73 ± 0.47

3.81 ± 0.36

0.206

Symptomatic vasospasm

41 (55.4)

19 (11.2)

< 0.001

Delayed cerebral infarction

27 (36.5)

5 (2.9)

< 0.001

Rebleeding

3 (4.1)

3 (1.8)

0.541

Hydrocephalus

14 (18.9)

4 (2.4)

< 0.001

Seizure

0 (0)

3 (1.8)

0.555

mRS 2–6 at discharge

67 (90.5)

131 (77.1)

0.013

mRS 2–6 at 3 months

19 (25.7)

15 (8.8)

< 0.001

mRS 2–6 at 12 months

14 (18.9)

5 (2.9)

< 0.001

SIH: stress-induced hyperglycemia; NPMH: non-perimesencephalic subarachnoid hemorrhage; HH: Hunt and Hess; mFS: modified Fisher scale; IVH: intraventricular hemorrhage; BMI: body mass index; TC: total cholesterol; TG: triglyceride; HDL-C: high-density lipoprotein cholesterol; LDL-C: low-density lipoprotein cholesterol; mRS: modified Rankin Scale

Association Of Variables With Clinical Complications And Functional Outcomes

The associations between variables and clinical complications are shown in Table 2. The development of symptomatic vasospasm was significantly associated with NPMH, HH grade 3–5, mFS 3–4, IVH, higher admission serum glucose levels, and SIH (all P < 0.001). Patients with delayed cerebral infarction had higher age (P = 0.028) and admission serum glucose levels (P < 0.001), lower serum potassium levels (P = 0.007), and a higher proportion of hypertension, NPMH, HH grade 3–5, mFS 3–4, IVH, and SIH (all P < 0.001). The hydrocephalus group was significantly related to higher serum glucose levels at admission (P = 0.001) and a higher proportion of hypertension (P = 0.002), NPMH (P < 0.001), HH grade 3–5 (P < 0.001), mFS 3–4 (P < 0.001), IVH (P = 0.003), and SIH (P < 0.001).

Table 2

Association of variables with symptomatic vasospasm, delayed cerebral infarction, and hydrocephalus

 

Symptomatic vasospasm

 

Delayed cerebral infarction

 

Hydrocephalus

 

Variable

Yes (n = 60)

No (n = 184)

P value

Yes (n = 32)

No (n = 212)

P value

Yes (n = 18)

No (n = 226)

P value

Age, yr

58.0 ± 10.6

55.0 ± 11.3

0.068

59.8 ± 10.9

55.1 ± 11.1

0.028

59.1 ± 8.9

55.5 ± 11.3

0.191

Gender, female

26 (43.3)

82 (44.6)

0.868

16 (50.0)

92 (43.4)

0.483

7 (38.9)

101 (44.7)

0.633

Alcohol

19 (31.7)

75 (40.8)

0.209

11 (34.4)

83 (39.2)

0.605

6 (33.3)

88 (38.9)

0.638

Smoke

18 (30.0)

70 (38.0)

0.260

12 (37.5)

76 (35.8)

0.856

5 (27.8)

83 (36.7)

0.447

Hypertension

26 (43.3)

55 (29.9)

0.055

20 (62.5)

61 (28.8)

< 0.001

12 (66.7)

69 (30.5)

0.002

NPMH

42 (70.0)

38 (20.7)

< 0.001

24 (75.0)

56 (26.4)

< 0.001

15 (83.3)

65 (28.8)

< 0.001

HH grade 3–5

22 (36.7)

8 (4.3)

< 0.001

17 (53.1)

13 (6.1)

< 0.001

9 (50.0)

21 (9.3)

< 0.001

mFS 3–4

36 (60.0)

20 (10.9)

< 0.001

19 (59.4)

37 (17.5)

< 0.001

13 (72.2)

43 (19)

< 0.001

IVH

27 (45.0)

27 (14.7)

< 0.001

17 (53.1)

37 (17.5)

< 0.001

9 (50.0)

45 (19.9)

0.003

BMI, kg/m2

23.9 ± 2.9

23.7 ± 2.8

0.613

23.4 ± 3.1

23.8 ± 2.8

0.415

23.0 ± 2.8

23.8 ± 2.8

0.232

Glucose, mmol/L

8.82 ± 2.42

6.70 ± 1.26

< 0.001

9.63 ± 2.72

6.86 ± 1.37

< 0.001

9.23 ± 2.35

7.06 ± 1.72

0.001

SIH

41 (68.3)

33 (17.9)

< 0.001

27 (84.4)

47 (22.2)

< 0.001

14 (77.8)

60 (26.5)

< 0.001

TC, mmol/L

4.76 ± 1.01

4.84 ± 1.06

0.667

4.87 ± 0.93

4.81 ± 1.06

0.793

5.02 ± 1.05

4.80 ± 1.05

0.434

TG, mmol/L

1.47 ± 0.73

1.41 ± 0.79

0.640

1.56 ± 0.74

1.41 ± 0.78

0.390

1.33 ± 0.49

1.44 ± 0.79

0.603

HDL-C, mmol/L

1.33 ± 0.35

1.28 ± 0.29

0.289

1.27 ± 0.39

1.30 ± 0.30

0.724

1.31 ± 0.29

1.29 ± 0.31

0.856

LDL-C, mmol/L

2.58 ± 0.82

2.68 ± 0.81

0.443

2.71 ± 0.82

2.65 ± 0.81

0.717

2.80 ± 0.79

2.64 ± 0.81

0.466

Sodium, mmol/L

139.4 ± 4.2

138.9 ± 3.3

0.358

139.1 ± 5.1

139.1 ± 3.3

0.995

138.5 ± 5.4

139.1 ± 3.4

0.479

Potassium, mmol/L

3.71 ± 0.44

3.81 ± 0.38

0.109

3.61 ± 0.50

3.81 ± 0.38

0.007

3.68 ± 0.48

3.79 ± 0.39

0.251

NPMH: non-perimesencephalic subarachnoid hemorrhage; HH: Hunt and Hess; mFS: modified Fisher scale; IVH: intraventricular hemorrhage; BMI: body mass index; SIH: stress-induced hyperglycemia; TC: total cholesterol; TG: triglyceride; HDL-C: high-density lipoprotein cholesterol; LDL-C: low-density lipoprotein cholesterol

Table 3 shows the associations between variables and functional outcomes. There were significant correlations between poor outcome at discharge and higher admission serum glucose levels (P = 0.048), SIH (P = 0.013), NPMH (P = 0.002), and higher SAH severity, including HH grade 3–5 (P = 0.038), mFS 3–4 (P = 0.002), and IVH (P = 0.002). Similar results were observed in 3-month and 12-month outcomes (all P < 0.05).

Table 3

Association of variables with functional outcomes at discharge, 3 months, and 12 months

 

Poor outcome at discharge

 

Poor outcome at 3 months

 

Poor outcome at 12 months

 

Variable

Yes (n = 198)

No (n = 46)

P value

Yes (n = 34)

No (n = 210)

P value

Yes (n = 19)

No (n = 225)

P value

Age, yr

56.2 ± 10.8

53.8 ± 12.5

0.188

57.6 ± 11.6

55.4 ± 11.1

0.283

59.1 ± 11.1

55.5 ± 11.1

0.171

Gender, female

85 (42.9)

23 (50.0)

0.384

14 (41.2)

94 (44.8)

0.696

4 (21.1)

104 (46.2)

0.060

Alcohol

77 (38.9)

17 (37.0)

0.808

10 (29.4)

84 (40.0)

0.239

7 (36.8)

87 (38.7)

0.875

Smoke

72 (36.4)

16 (34.8)

0.841

13 (38.2)

75 (35.7)

0.776

9 (47.4)

79 (35.1)

0.285

Hypertension

65 (32.8)

16 (34.8)

0.800

16 (47.1)

65 (31.0)

0.064

10 (52.6)

71 (31.6)

0.061

NPMH

74 (37.4)

6 (13.0)

0.002

22 (64.7)

58 (27.6)

< 0.001

15 (78.9)

65 (28.9)

< 0.001

HH grade 3–5

29 (14.6)

1 (2.2)

0.038

15 (44.1)

15 (7.1)

< 0.001

10 (52.6)

20 (8.9)

< 0.001

mFS 3–4

54 (27.3)

2 (4.3)

0.002

17 (50.0)

39 (18.6)

< 0.001

12 (63.2)

44 (19.6)

< 0.001

IVH

52 (26.3)

2 (4.3)

0.002

13 (38.2)

41 (19.5)

0.015

9 (47.4)

45 (20.0)

0.006

BMI, kg/m2

23.8 ± 2.8

23.4 ± 2.6

0.380

24.3 ± 3.2

23.6 ± 2.7

0.230

23.9 ± 3.6

23.7 ± 2.7

0.843

Glucose, mmol/L

7.34 ± 1.94

6.74 ± 1.38

0.048

8.78 ± 3.14

6.97 ± 1.41

0.002

9.56 ± 2.89

7.03 ± 1.60

0.001

SIH

67 (33.8)

7 (15.2)

0.013

19 (55.9)

55 (26.2)

< 0.001

14 (73.7)

60 (26.7)

< 0.001

TC, mmol/L

4.82 ± 1.07

4.81 ± 0.93

0.942

4.75 ± 0.83

4.83 ± 1.08

0.721

4.79 ± 0.91

4.82 ± 1.06

0.904

TG, mmol/L

1.42 ± 0.72

1.47 ± 0.96

0.684

1.44 ± 0.70

1.43 ± 0.78

0.926

1.41 ± 0.69

1.43 ± 0.78

0.919

HDL-C, mmol/L

1.31 ± 0.30

1.23 ± 0.32

0.159

1.36 ± 0.36

1.28 ± 0.30

0.242

1.38 ± 0.38

1.29 ± 0.30

0.212

LDL-C, mmol/L

2.65 ± 0.85

2.67 ± 0.63

0.865

2.60 ± 0.75

2.67 ± 0.82

0.691

2.60 ± 0.86

2.66 ± 0.81

0.753

Sodium, mmol/L

139.1 ± 3.7

138.9 ± 3.1

0.752

139.0 ± 4.8

139.1 ± 3.3

0.885

138.7 ± 5.3

139.1 ± 3.4

0.674

Potassium, mmol/L

3.79 ± 0.39

3.74 ± 0.46

0.419

3.68 ± 0.50

3.80 ± 0.38

0.195

3.71 ± 0.52

3.79 ± 0.39

0.410

NPMH: non-perimesencephalic subarachnoid hemorrhage; HH: Hunt and Hess; mFS: modified Fisher scale; IVH: intraventricular hemorrhage; BMI: body mass index; SIH: stress-induced hyperglycemia; TC: total cholesterol; TG: triglyceride; HDL-C: high-density lipoprotein cholesterol; LDL-C: low-density lipoprotein cholesterol

Effect of Sih On Clinical Complications And Functional Outcomes

SIH was found to be significantly associated with clinical complications and adverse outcomes in our cohort. Therefore, we evaluated the effect of SIH on clinical complications and functional outcomes in multivariate logistic regression analysis. As is depicted in Fig. 4, when accompanied by SIH, there was a 12.176 (P < 0.001, 95% CI 4.904–30.231) increase in the odds of developing symptomatic vasospasm, a 12.434 (P < 0.001, 95% CI 3.850-40.161) increase in the odds of developing delayed cerebral infarction, and a 5.771 (P = 0.008, 95% CI 1.570-21.222) increase in the odds of developing hydrocephalus after adjustment for covariates, including age, gender, hypertension, HH grade, mFS, IVH, and subarachnoid blood distribution characteristic. Regarding functional outcomes, there were no significant associations between SIH and poor outcome at discharge (P = 0.064, OR 2.409, 95% CI 0.951-6.100) or at 3 months (P = 0.110, OR 2.029, 95% CI 0.852–4.833) after adjusting for the above covariates. Interestingly, SIH was significantly and independently associated with poor outcome at 12 months (P = 0.006, OR 5.506, 95% CI 1.632–18.581).

Prognostic value of SIH for clinical complications and functional outcomes

The combined models were constructed to predict clinical complications and functional outcomes. The results are displayed in Table 4. Model 1 was obtained by incorporating variables with a P value < 0.10 in univariate analysis and using a forward stepwise method of multivariate logistic regression analysis. SIH was incorporated in the prediction of symptomatic vasospasm (P < 0.001, OR 11.507, 95% CI 4.807–27.544), delayed cerebral infarction (P < 0.001, OR 13.874, 95% CI 4.424–43.507), hydrocephalus (P = 0.003, OR 6.474, 95% CI 1.915–21.894), discharge poor outcome (P = 0.038, OR 2.512, 95% CI 1.051–6.001), 3-month poor outcome (P = 0.006, OR 2.980, 95% CI 1.376–6.452), and 12-month poor outcome (P = 0.010, OR 4.556, 95% CI 1.447–14.345). Model 2 was obtained in the same manner, but with exclusion of the variable SIH.

Table 4

Multivariate logistic regression models for predicting clinical complications and functional outcomes

 

Model 1 (SIH included)

 

Model 2 (SIH excluded)

Variable

OR (95% CI)

P value

 

OR (95% CI)

P value

Symptomatic vasospasm

         

SIH

11.507 (4.807–27.544)

< 0.001

 

N/A

N/A

NPMH

3.096 (1.079–8.884)

0.036

 

2.724 (1.086–6.830)

0.033

HH grade 3–5

3.417 (1.002–11.658)

0.050

 

4.908 (1.744–13.812)

0.003

mFS 3–4

5.007 (1.661–15.091)

0.004

 

4.047 (1.550-10.566)

0.004

IVH

2.636 (1.045–6.650)

0.040

 

2.510 (1.119–5.629)

0.026

Delayed cerebral infarction

         

SIH

13.874 (4.424–43.507)

< 0.001

 

N/A

N/A

Hypertension

3.200 (1.149–8.912)

0.026

 

4.109 (1.632–10.346)

0.003

NPMH

5.447 (1.878–15.796)

0.002

 

5.330 (2.035–13.963)

0.001

HH grade 3–5

7.457 (2.373–23.430)

0.001

 

9.760 (3.578–26.624)

N/A

Hydrocephalus

         

SIH

6.474 (1.915–21.894)

0.003

 

N/A

N/A

Hypertension

3.822 (1.221–11.970)

0.021

 

4.491 (1.522–13.252)

0.007

mFS 3–4

9.389 (2.944–29.940)

< 0.001

 

10.967 (3.612–33.292)

< 0.001

Poor outcome at discharge

         

SIH

2.512 (1.051–6.001)

0.038

 

N/A

N/A

mFS 3–4

N/A

N/A

 

6.436 (1.487–27.852)

0.013

IVH

7.092 (1.650-30.478)

0.008

 

6.024 (1.389–26.127)

0.016

Poor outcome at 3 months

         

SIH

2.980 (1.376–6.452)

0.006

 

N/A

N/A

NPMH

4.195 (1.918–9.173)

< 0.001

 

2.990 (1.296–6.899)

0.010

HH grade 3–5

N/A

N/A

 

6.806 (2.739–16.911)

< 0.001

Poor outcome at 12 months

         

SIH

4.556 (1.447–14.345)

0.010

 

N/A

N/A

NPMH

5.086 (1.483–17.445)

0.010

 

5.580 (1.665–18.706)

0.005

HH grade 3–5

4.144 (1.322–12.988)

0.015

 

6.234 (2.116–18.366)

0.001

Model 1 was obtained by incorporating variables with a P value < 0.10 in univariate analysis and using a forward stepwise method of multivariate logistic regression analysis. Model 2 was obtained in the same manner, but excluding the variable SIH.
SIH: stress-induced hyperglycemia; OR: odds ratio; Cl: confidence interval; NPMH: non-perimesencephalic subarachnoid hemorrhage; HH: Hunt and Hess; mFS: modified Fisher scale; IVH: intraventricular hemorrhage; N/A: not applicable

ROC analysis was performed to evaluate the predictive ability of the models (Fig. 5). In the ROC analysis, model 1 had a significantly higher AUC compared with model 2 for the prediction of symptomatic vasospasm (0.893 [0.848–0.929] vs. 0.828 [0.774–0.873]; P = 0.002). Similar results were observed when predicting delayed cerebral infarction (0.931 [0.892–0.959] vs. 0.871 [0.823–0.911]; P = 0.024) and hydrocephalus (0.890 [0.843–0.926] vs. 0.810 [0.755–0.857]; P = 0.037). However, in the prediction of poor outcomes at discharge (0.662 [0.599–0.721] vs. 0.671 [0.609–0.730]; P = 0.775) and 3 months (0.736 [0.676–0.790] vs. 0.747 [0.687-0.800]; P = 0.659), the AUC of model 1 was not higher than that of model 2. It is worth noting that, although not statistically significant, the AUC of model 1 was higher than that of model 2 in predicting 12-month poor outcome (0.854 [0.804–0.896] vs. 0.814 [0.759–0.861]; P = 0.087). Thus, incorporation of SIH increased the ability of the model for the prediction of symptomatic vasospasm, delayed cerebral infarction, hydrocephalus, and 12-month poor outcome.

Discussion

To our knowledge, this is the first study to explore the association of SIH with complication rates and functional outcomes in naSAH. This study found that SIH after naSAH was significantly and independently associated with the development of symptomatic vasospasm, delayed cerebral infarction, hydrocephalus, and a poor outcome at 12 months after adjusting for demographic data, hypertension history, subarachnoid blood distribution characteristic, and SAH severity. Taking SIH into consideration with risk factors improved the prediction of symptomatic vasospasm, delayed cerebral infarction, hydrocephalus, and 12-month poor outcome after naSAH, although it had limited benefits in the prediction of poor outcomes at discharge or at 3 months. These findings highlight the importance of considering SIH in the decision-making algorithm and treatment planning following naSAH.

SIH is a transient hyperglycemia after acute illness or injury caused by the activation of stress-neuroendocrine axis [8]. Previous research suggested that post-stroke SIH may be a biomarker of stroke severity [25, 26]. One meta-analysis involving 16 studies showed that 69% (range, 29 to 100%) of patients suffered a SIH after aSAH [13]. The proportion of SIH in our study cohort (30.3%) was much lower than this proportion, reflecting the low severity of naSAH. In one study, SIH occurred in 32.0% of naSAH patients, which was similar to the proportion in our cohort [27]. An early study confirmed a significant correlation between high serum glucose levels and high clinical severity assessed by HH grade in aSAH patients (P = 0.001) [26]. In addition, Santucci et al. reported that SIH after aSAH was significantly associated with radiologically estimated intracranial blood volume (P < 0.001) [28]. Our results in naSAH cohort were consistent with these findings. In our study, patients with SIH had higher HH grade (P = 0.001), mFS (P = 0.003) and a higher proportion of IVH (P = 0.026; Fig. 2). Additionally, in the characteristic of subarachnoid blood distribution, the proportion of NPMH in SIH patients was higher than that of non-SIH patients (P = 0.010), which may be due to the fact that NPMH was more similar to aSAH a higher severity [4, 5]. These results may indicate the systemic stress response caused by severe brain injury after SAH.

Several studies have explored the relationship between hyperglycemia and complication rates and adverse outcomes after aSAH. Badjatia et al. found that mean serum glucose levels during hospitalization correlated with the development of symptomatic vasospasm after aSAH (P < 0.001) [11]. Juvela and colleagues reported that hyperglycemia following aSAH were related to delayed cerebral infarction and hydrocephalus [12]. A meta-analysis incorporated 8 studies for the analysis of the association between hyperglycemia and clinical outcome after aSAH and found that post-aSAH hyperglycemia was associated with an increased risk of poor clinical outcome at 3 or 6 months [13]. These results supported our findings. However, these studies only identified patients with hyperglycemia, but did not differentiate between SIH patients and DM patients. Since pre-existing hyperglycemia before SAH onset could not reflect the activation of stress response caused by SAH, our study excluded patients with a history of DM. Moreover, these studies only described the association of hyperglycemia after SAH with functional outcomes within 6 months, but did not explore its relationship with long-term outcomes. Our study identified patients with SIH based on the latest consensus from the American Association of Clinical Endocrinologists and American Diabetes Association, and demonstrated the independent association of SIH with symptomatic vasospasm (P < 0.001), delayed cerebral infarction (P < 0.001) and hydrocephalus (P = 0.008) in the naSAH cohort. After adjusting for demographic data, hypertension history, subarachnoid blood distribution characteristic, and SAH severity, SIH was significantly associated with adverse outcomes at 12 months (P = 0.006), although no significant correlation was found between SIH and poor outcomes at discharge (P = 0.064) or at 3 months (P = 0.110; Fig. 4).

The deleterious effects of activation of stress-neuroendocrine axis after SAH may explain the correlation between SIH and adverse outcomes. The stress response can induce the activation of hypothalamus-pituitary-adrenal axis and sympathetic autonomic nervous system, as well as induce the secretion of glucagon, catecholamines, and corticosteroids [8]. The metabolic disorders caused by these factors may lead to inflammation, systemic damage, and various complications [8]. Sympathetic activation and serum catecholamine elevation after aSAH has been confirmed in previous studies, and were found to be related to symptomatic vasospasm and unfavorable outcomes [29, 30]. It was found that inhibition of sympathetic activity by beta-blockers could reduce cerebral vasospasm rates and improve functional outcomes after aSAH [31, 32]. In an animal study, inhibition of central sympathetic nerve activation through renal denervation significantly prevented cerebral vasospasm after SAH [33]. In addition, hyperglycemia may aggravate early brain injury (EBI) after SAH. Currently, new insight suggests that EBI within 72 hours after SAH onset may lay the foundation for subsequent pathophysiological changes and poor outcomes of patients. The pathological mechanisms of EBI include oxidative stress, platelet activation, inflammation, and neuronal apoptosis [3437]. One animal experiment found that hyperglycemia could increase reactive oxygen species (ROS) production through activating protein kinase C after stroke, thereby exacerbating oxidative stress [38]. In another study, hyperglycemia aggravated neuronal apoptosis through the activation of extrinsic caspase cascade via extracellular regulated kinase (ERK) signal pathway after experimental SAH [9]. In addition, hyperglycemia was also found to be related to the activation of platelets and the increase of pro-inflammatory cytokines [39].

In the present study, SIH was a significant and independent risk factor of symptomatic vasospasm, delayed cerebral infarction, hydrocephalus, and 12-month poor outcome in patients with naSAH. Taking SIH into consideration with risk factors improved the prediction of symptomatic vasospasm, delayed cerebral infarction, hydrocephalus, and 12-month poor outcome. Biomarkers for predicting complications and poor outcomes after naSAH have not yet been established. Currently, prediction of unfavorable outcomes after naSAH primarily still depends on the severity of SAH, which is assessed using HH grade, mFS, and occurrence of IVH. However, naSAH patients often have minor SAH severity at admission [57]. Thus, SAH severity has limited value in predicting poor outcomes in this population. Since the identification of SIH could easily be performed in any institution, it should be an important reference for predicting complications and poor outcomes of naSAH patients. In addition, this study suggested that the stress response and resulting hyperglycemia after naSAH may be harmful to patients. Therefore, we recommend proper glycemic management for naSAH patients with SIH.

This study had several limitations. First, we did not detect the patients' serum endocrine hormones, such as cortisol and catecholamines, to better explore the activation of the stress-neuroendocrine axis after naSAH. Second, we lost the data regarding glycated hemoglobin (HbA1c) of the patients to define SIH more precisely through relative hyperglycemia. To address this problem, we defined SIH through the serum glucose levels at admission and during hospitalization according to the latest consensus from the American Association of Clinical Endocrinologists and American Diabetes Association. The proportion of naSAH patients in our cohort who developed SIH (30.3%) was comparable to a previous study that defined SIH by relative hyperglycemia (32.0%) [27]. Third, our study did not reveal whether interventions on hyperglycemia after naSAH could assist in reducing risk of the development of complications and poor outcomes. Finally, our study was a single-center retrospective study. Further multi-center prospective studies are needed to verify our findings.

Conclusions

This study found that SIH was a significant and independent risk factor for symptomatic vasospasm, delayed cerebral infarction, hydrocephalus, and long-term poor outcomes in patients with naSAH. SIH was useful for predicting complications and long-term prognosis of naSAH, although its benefit in the prediction of short-term prognosis was limited. In addition, this study may allude to the underlying mechanism of stress-neuroendocrine axis in the pathogenesis of naSAH. Our findings highlight the importance of identifying SIH early after naSAH for decision-making and treatment planning.

Abbreviations

SAH

subarachnoid hemorrhage

naSAH

non-aneurysmal subarachnoid hemorrhage

aSAH

aneurysmal subarachnoid hemorrhage

SIH

stress-induced hyperglycemia

DM

diabetes mellitus

CT

computed tomography

DSA

digital subtraction angiography

BMI

body mass index

HH

Hunt and Hess

mFS

modified Fisher Scale

IVH

intraventricular hemorrhage

PMH

perimesencephalic subarachnoid hemorrhage

NPMH

non-perimesencephalic subarachnoid hemorrhage

TC

total cholesterol

TG

triglyceride

HDL-C

high-density lipoprotein cholesterol

LDL-C

low-density lipoprotein cholesterol

mRS

modified Rankin Scale

GCS

Glasgow Coma Scale

MRI

magnetic resonance imaging

SD

standard deviation

IQR

interquartile range

OR

odds ratio

Cl

confidence interval

ROC

receiver operating curve

AUC

area under curve

EBI

early brain injury

ROS

reactive oxygen species

ERK

extracellular regulated kinase

HbA1c

glycated hemoglobin.

Declarations

Ethics approval and consent to participate

This study was approved by Institutional board of the Second Hospital affiliated to Zhejiang University.

Consent for publication

Not applicable.

Availability of data and materials

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

This study was supported by the National Natural Science Foundation of China (No. 81971107, to SC).

Authors' contributions

ZYZ wrote the manuscript; YZ and SC designed the study; AKZ and XYW collected the study data; YJF, SC, and CL revised the manuscript; YBL, HSX, and YJL participated in the design and coordination of the study. All authors read and approved the final version of the manuscript.

Acknowledgements

We are grateful for the data support from the Second Affiliated Hospital of Zhejiang University School of Medicine.

Author details

1 Department of Neurosurgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China. 2 Department of Stomatology, The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Health, Hangzhou, China. 3 Department of Neurosurgery, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China. 4 Center for Neuroscience Research, Loma Linda University School of Medicine, Loma Linda, CA, USA.

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