Early Dynamics of P-selectin and Interleukin 6 Predicts Outcomes in Ischemic Stroke Gabriella Pusch, MD,* Birgit Debrabant, PhD,† Tihamer Molnar, MD, PhD,‡ Gergely Feher, MD, PhD,* Viktoria Papp, MD,* Miklos Banati, MD, PhD,* Norbert Kovacs, MD, PhD,* Laszlo Szapary, MD, PhD,* and Zsolt Illes, MD, PhD*xk

Background: Thromboinflammatory molecules connect the prothrombotic state, endothelial dysfunction, and systemic/local inflammation in the acute phase of ischemic stroke. Methods: We prospectively investigated (1) serial changes in the levels of thromboinflammatory biomarkers in 76 patients with acute ischemic stroke (6, 24, and 72 hours after onset); (2) compared with 44 patients with asymptomatic severe ($70%) carotid stenosis and 66 patients with Parkinson disease; and (3) we applied multiple regression methods, relating biological biomarkers combined with demographic data and comorbidities to poststroke infection, death, and functional outcome, and assessed the ability of the models to predict each outcome. Results: Interleukin 6 (IL-6) levels and change of IL-6 concentrations by 72 hours correlated with the size of tissue damage indicated by S100B titers. Levels of IL-6 and P-selectin at 72 hours were higher in patients with large-artery versus lacunar stroke. High concentration of IL-6, monocyte chemotactic protein 1, and S100B at 6 hours were associated with poststroke infections; high concentration of IL-6, S100B, and high-sensitivity C-reactive protein (hsCRP) correlated with death. Change of P-selectin from 6 to 72 hours by 1 unit increased the incidence of poststroke infections with an odds ratio of 22.7; each 100 units of IL-6 at baseline increased the odds of death by 9&, and at 72 hours, the odds of poststroke infections by 4&. Each unit of baseline hsCRP elevated the odds of death by 7%. Conclusions: In regression models, in which biological, demographic, and comorbid factors were combined, those biological biomarkers predicted poor outcome with high accuracy, which were characterized by an increasing concentration by 72 hours. Two particular biomarkers emerged to predict outcomes besides hsCRP: early dynamic changes in the systemic levels of P-selectin and IL-6. Key Words: Carotid stenosis—ischemic stroke—poststroke infection— P-selectin—MCP-1—IL-6. Ó 2015 Published by Elsevier Inc. on behalf of National Stroke Association

From the *Department of Neurology, University of Pecs, Pecs, Hungary; †Department of Epidemiology and Biostatistics and Biodemography, Institute of Public Health, University of Southern Denmark, Odense, Denmark; ‡Department of Anaesthesiology and Intensive Therapy, University of Pecs, Pecs, Hungary; xDepartment of Neurology, Odense University Hospital, Odense, Denmark; and kInstitute of Clinical Research, University of Southern Denmark, Odense, Denmark. Received February 12, 2015; revision received April 22, 2015; accepted May 6, 2015.

Z.I. received grant from Hungarian National Research Fund (OTKA K77892). Address correspondence to Zsolt Illes, MD, PhD, Department of Neurology, Odense University Hospital, Sdr Boulevard 29, Odense 5000, Denmark. E-mail: [email protected]. 1052-3057/$ - see front matter Ó 2015 Published by Elsevier Inc. on behalf of National Stroke Association http://dx.doi.org/10.1016/j.jstrokecerebrovasdis.2015.05.005

Journal of Stroke and Cerebrovascular Diseases, Vol. -, No. - (---), 2015: pp 1-10

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G. PUSCH ET AL.

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A number of experimental and clinical data demonstrated the role of innate and adaptive immune responses in both local inflammation1,2 and systemic immunodepression after cerebral ischemia.3-5 Recent studies have also indicated the importance of molecules, which connect coagulation and prothrombotic state with endothelial dysfunction and inflammation, resulting in a multifunctional network of ‘‘thromboinflammation.’’1,6,7 Although tissue plasminogen activator (tPA) is essential in thrombolysis, it also participates in blood–brain barrier permeability and extracellular matrix degradation.8 Beside the major role of recruiting leukocytes, P-selectin induces chemokine and proinflammatory gene expression in monocytes and granulocytes.9-11 CD40L triggers an inflammatory reaction in endothelial cells, platelet CD40L interacts with neutrophils, and soluble CD40L (sCD40 L) influences adaptive immune responses.12,13 Aggregation of platelets with monocytes mediated by P-selectin induces the expression of monocyte chemotactic protein 1 (MCP-1) and interleukin (IL)-8.10,11 MCP-1 plays an important role in cell migration and synthesis of matrix metalloproteinase 9; its endothelial expression is essential in atherosclerotic lesion formation and in changes of vascular permeability.14 IL-8 recruits neutrophils and increases the expression of matrix metalloproteinases.15 IL-6 is produced by many different cell types including central nervous system resident cells.15,16 IL-6 concentration is elevated in both serum and cerebrospinal fluid after ischemic stroke and correlates with brain infarct volume.15-18 C-reactive protein (CRP) may mediate vascular injury through the activation of the complement pathways,19 which is associated with unfavorable outcome.20 Besides these early thromboinflammatory events, infections in the immediate poststroke period also contribute to the poor outcome.21 Pneumonia and urinary tract infections are the most common causes of infection, accounting for up to 10% each.21 Pneumonia increases the risk of death 3-6–fold and is also associated with worse functional outcome.22 Here, we prospectively investigated the temporal profile of thromboinflammatory events reflected by combination of several biomarkers and their predictive potential. Concentrations in stroke patients were compared with those in patients with severe atherosclerosis and to Parkinson disease (PD), a neurodegenerative disorder of the brain accompanied by neuroinflammation.23 We examined the simultaneous relation of the measured biomarkers to the outcomes (death, infection, and function) using multiple regression and examined the regression models’ ability to predict the different outcomes.

Materials and Methods The study was approved by the Local Ethics Committee of the University of Pecs. The study was

conducted at the Department of Neurology, University of Pecs. All consecutively enrolled subjects or their authorized representative gave informed consent.

Subjects Seventy-six patients with acute ischemic stroke were enrolled within 6 hours after onset of symptoms: medical history was collected and standard laboratory tests, 12-lead electrocardiography, and cerebral computed tomography were performed (Table 1). Seventy-eight percentage of patients had hypertension, 16.7% had diabetes, 22.2% were smokers, and 27.5% had an increased body mass index. Hemorrhagic stroke, infection, and/or fever within less than 4 weeks and elevated white blood cell counts on admission were exclusion criteria. Severity of stroke was measured by the National Institutes of Health Stroke Scale (NIHSS). Tissue damage was assessed by the concentration of S100B.4,24,25 NIHSS was measured daily till day 7. BMI was determined. The outcome was assessed by the modified Barthel index on the 28th day either in the hospital or in an outpatient clinic. Thirteen patients received intravenous thrombolysis. The type of acute ischemic stroke was classified according to the Trial of Org 10172 in Acute Stroke Treatment (TOAST) classification: 22 patients had large-artery atherosclerosis (age, 68.7 6 10.03 years and NIHSS on admission, 12.65 6 5.88), 26 patients had lacunar infarct caused by small-vessel occlusion (age, 66.4 6 10.25 years and NIHSS on admission, 6.89 6 3.71), and 28 cases had cardioembolic stroke (age, 77.3 6 9.48 years and NIHSS on admission, 14.07 6 4.89). No patients had stroke of undetermined etiology. Sixty-six patients with PD were asked to participate as nonvascular, brain disease controls. Sera were also taken from 44 patients with 70%-100% stenosis of the carotid artery determined by Duplex scan sonography26; none of these patients had neurologic signs/symptoms (Table 1). Sera from controls were collected during the prospective phase of the study.

Infections An evidence-based guideline was followed to detect infectious complications; in short, physical and laboratory measures including fever, white blood cell count, erythrocyte sedimentation rate, procalcitonine, urine analysis, chest X-ray, or blood cultures, which were initiated on any suspicion of infections.27

Biomarkers Blood samples were taken on admission (within 6 hours after onset) and 24 and 72 hours later. Highsensitivity C-reactive protein (hsCRP) was measured by automated fluorescence immunoassay (BRAHMS

THROMBOINFLAMMATORY BIOMARKERS IN STROKE

Table 1. Baseline characteristics of the study populations n

Age, y

Acute ischemic stroke 76 69.79 6 12.01 Significant carotid 44 64.30 6 10.29 stenosis* Parkinson disease 66 62.33 6 9.54

Female:male 1.12 .5 .83

*Significant carotid stenosis was defined as $70% stenosis of the carotid artery determined by Duplex scan sonography.37

Kryptor), P-selectin, MCP-1, CD40L, IL-6, IL-8, and tPA by immunoassay (BMS711F, Bender Gmbh, Campus Vienna Biocenter 2, Vienna, Austria), S100B by automated electrochemiluminescence immunoassay (LIA-mat Sangtec 100).4,28

Statistical Analysis The primary statistical analysis was performed by SPSS 16.0 software. Between-group differences were evaluated by the Mann–Whitney test. The Spearman correlation coefficient was used to quantify the association between 2 continuous variables. All tests were 2-tailed. Regression analysis was performed with R version 3.0.1 to investigate 3 outcomes: death, the presence of poststroke infections, and the NIHSS score by day 7. For the binary outcomes (death and poststroke infections), Firth’s logistic regression was applied29 using the R package logistf version 1.21. This penalized version of an ordinary logistic regression removed the first-order bias from the effect estimates, especially in cases, when one or combinations of several explanatory variables perfectly predicted the outcome, leading to infinite parameter estimates if analyzed by ordinary logistic regression. For the NIHSS score by day 7, an ordinary linear regression model was used. To identify a reasonable statistical model describing each of the 3 outcomes based on some of the considered explanatory variables simultaneously correcting for possible confounders, we used a stepwise model selection approach forcing age and sex into the model. We examined the capability of the models to predict the outcomes (within the same data set) using Pearson’s correlation coefficient and the area under the curve (AUC, for the binary outcomes), respectively.

Results Biomarkers in the Hyperacute Phase of Stroke (within 6 Hours) Biomarkers (P-selectin, MCP-1, CD40L, IL-6, IL-8, tPA, S100B, and hsCRP) in the sera were examined within 6 hours after the onset of acute ischemic stroke. Systemic levels of all biomarkers but IL-8 were higher compared to both control groups: PD and significant carotid stenosis (Table 2). Concentrations were also higher in patients

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with carotid stenosis compared with PD, except P-selectin (Table 2). Although there was a significant difference in the female:male ratio between groups of patients with acute ischemic stroke and significant carotid stenosis, there was no difference in biomarker levels between males and females with significant carotid stenosis. Among patients with acute ischemic stroke, S100B was slightly higher among females at 72 hours (P 5 .042).

Temporal Profile of Biomarkers in the Acute Phase of Ischemic Stroke Changes in the biomarker levels during the acute phase of ischemic stroke were also examined (within 6, 24, and 72 hours). Three temporal profiles were observed (Figure 1 and Table 2): (1) elevation at 6 hours with additional increase by 72 hours (IL-6, P-selectin, hsCRP, and S100B); (2); elevation at 6 hours and decline thereafter (IL-8); and (3) constant elevation in the first 72 hours (tPA, CD40L, and MCP-1). Concentrations of all biomarkers at all 3 time points were higher compared with the PD controls (Table 2). Thrombolysis had no effect on the temporal profiles (data not shown).

Correlation with TOAST Categories We examined age, NIHSS on admission, 28-day Barthel index, and concentration of biomarkers at 6 and 72 hours after stroke onset in different subgroups of patients based on TOAST criteria. Patients with cardioembolic stroke were the oldest (aged 77.3 6 9.48 years) compared with large-artery (aged 68.7 6 10.03 years, P 5 .003) and lacunar stroke (aged 66.4 6 10.25 years, P 5 .001). Stroke was less severe in patients with small-vessel occlusion (NIHSS, 6.89 6 3.71) compared with large-artery (NIHSS, 12.65 6 5.887; P 5 .003) and cardioembolic stroke (14.07 6 4.89, P , .001). Both infection and death were the most common among patients with cardioembolic stroke (infection: 35% versus 10% and 14.3%; death: 32% versus 5% in lacunar stroke and 23.8% in large-artery occlusion). The concentration of P-selectin at 72 hours was significantly higher in patients with large-artery stroke (29999.7 6 53381.8) compared with patients with lacunar stroke (3312.56 6 1192.367, P 5 .03). The concentration of IL-6 at both 6 and 72 hours was higher in patients with large-artery atherosclerosis (5722.7 6 19823 and 28702 6 10809) compared with lacunar stroke (13.14 6 49.2 and 145.1 6 439.8, P 5 .04, respectively). The levels of hsCRP were not different on admission but became significantly higher at 72 hours in patients with large-artery atherosclerosis (P 5 .04) and cardioembolic stroke (P , .001) compared with patients with lacunar infarcts.

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Table 2. Biomarker concentrations in the peripheral blood of patients with acute ischemic stroke, asymptomatic significant carotid stenosis, and Parkinson disease P value Biomarkers

AIS (means 6 SD)

hsCRP (mg/L) 6h 10.8 6 1.2 72 h 42.6 6 70.1* S100B (ng/mL) 6h .175 6 .124 72 h .85 6 1.01* tPA (pg/mL) 6h 72835.5 6 22,278 72 h 77235.1 6 27638.1 P-selectin (pg/mL) 6h 1943.5 6 154.7 72 h 14727 6 5898.4* MCP-1 (pg/mL) 6h 35022.5 6 6714.3 72 h 27962.9 6 5803.8 IL-8 (pg/mL) 6h 7299 6 2632.3 72 h 3209.4 6 1425.7** IL-6 (pg/mL) 6h 1023.1 6 774.7 72 h 8053.2 6 5343.6* CD40L (pg/mL) 6h 485351 6 62867.3 72 h 460602.2 6 63520

CS (means 6 SD) PD (means 6 SD) AIS versus PD AIS versus CS CS versus PD 9.4 6 17.3

NM

NA

.09 #.001

NA

NM

NM

NA

NA

NA

7283.9 6 2160.7

1754.7 6 1021.5

#.001 #.001

#.001 #.001

#.001

478.3 6 581.1

352.3 6 271.2

#.001 #.001

#.001 #.001

.89

1745.2 6 716.4

436.7 6 177.3

#.01 #.001

#.001 #.001

#.001

575.3 6 860

27.3 6 71.4

.19 .08

#.001

.01 .005

81.9 6 88.6

.4 6 2.2

#.001 #.001

.001 .001

#.001

41339 6 26,508

6883.9 6 6135.5

#.001 #.001

#.001 #.001

#.001

Abbreviations: AIS, acute ischemic stroke; CS, significant ($70%) carotid stenosis; hsCRP, high-sensitivity C-reactive protein; IL, interleukin; MCP-1, monocyte chemotactic protein 1; NM, not measured; NA, not applicable; PD, Parkinson disease; SD, standard deviation; tPA, tissue plasminogen activator. Median and interquartile range are shown (Mann–Whitney U test). *P # .01, **P # .05 comparing concentration within 6 hours after stroke with concentration 72 hours later.

Correlation with the Extent of Tissue Damage (S100B) To evaluate the extent of tissue damage, we measured the concentration and temporal change of S100B.24,25 Increase in S100B concentrations by 72 hours positively correlated with hsCRP levels at 72 hours (P # .001). IL-6 both at baseline and at 72 hours correlated with S100B levels at 72 hours (P 5 .003 and P 5 .02, respectively) and also with change of S100B by 72 hours (P 5 .04). Concentration of IL-8 at 72 hours positively correlated with change of S100B titers by 72 hours (P 5 .02; Table 3).

Correlation with Poststroke Infection and Death Next, we examined, which factors were associated with infection (22%) and death (19% by day 28) (Table 4). High concentration of IL-6, MCP-1, and S100B at 6 hours correlated with the presence of poststroke infections (P 5 .001, P 5 .02, and P , .01, respectively); increased concentration of hsCRP and S100B at 72 hours also correlated with infections (P # .001, respectively).

Increased NIHSS and elevated concentration of S100B (P , .01), hsCRP (P , .01), IL-6 (P , .001), and IL-8 (P 5 .01) at 6 hours were all associated with death; S100B concentration at 72 hours also correlated with death (P , .01). Changes in P-selectin and IL-6 concentrations, which showed an increase by 72 hours, correlated with both poststroke infections and death (P , .01 and P , .05, respectively; Table 4 and Figure 1).

Correlation with Functional Outcome S100B levels measured within 6 hours correlated with NIHSS on admission (P 5 .001) and its change reflecting functional decline within the first week (P , .05; Table 5). IL-6 levels both within 6 hours and after 72 hours showed significant correlation with early stroke severity (NIHSS on day 1) and also with worsening of NIHSS within 48 hours (P , .05, respectively). Concentration of P-selectin in the hyperacute phase positively correlated with NIHSS on the first day (P , .05; Table 5). Elevated levels of hsCRP and S100B at 72 hours were the only

THROMBOINFLAMMATORY BIOMARKERS IN STROKE

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Figure 1. Temporal profile of thromboinflammatory biomarkers in the peripheral blood of patients during the acute phase of ischemic stroke. The figure indicates changes in the concentration of 6 biomarkers in the peripheral blood measured within 6 hours after the onset of ischemic stroke, and 24 as well as 72 hours later. Concentrations of biomarkers at 6 hours were significantly elevated compared with those in patients with Parkinson disease and asymptomatic significant carotid stenosis (but IL-8), respectively (see Table 2). P values indicate differences between concentration measured within 6 hours after onset and 72 hours later. (A) Temporal profile of IL-6 and P-selectin. (B) Temporal profile of tPA, IL-8, MCP-1, and sCD40L. Abbreviations: IL, interleukin; MCP-1, monocyte chemotactic protein 1; tPA, tissue plasminogen activator.

factors, which correlated with late outcome measured by Barthel index on day 28 (P ,.01 and P ,.05, respectively).

Regression Analysis For the 3 outcomes (death, poststroke infections, and function), we estimated a stepwise regression model to relate each outcome to the measured biomarkers and to control for confounders. As potential covariates, we simultaneously considered the 8 biomarkers (baseline, at 72 hours and the change from baseline to 72 hours), demographic/comorbidity variables (age, sex, smoking, BMI, and diabetes), and NIHSS at day 1 (Table 6). The given estimates quantify the net effect of the selected explanatory variables on the corresponding outcome. Outcome 1: Death Each additional year of age increased the odds of death by 31%; each unit of hsCRP at baseline by 7%; and each 100 units of IL-6 at baseline by 9&. The model fit was excellent: the AUC was .98. (Table 6). Outcome 2: Poststroke Infections Female sex increased the odds of infection on average by a factor of 15.3; elevation in P-selectin concentration between baseline and 72 hours by a factor of 22.7; each additional 100 units (pg/mL) elevation in the concentration of IL-6 at 72 hours by 4&. Again, the model fit within the discovery data set was very good: the AUC was .92 (Table 6). Outcome 3: NIHSS Score by Day 7 Each NIHSS point measured on day 2 increased NIHSS by day 7 with .9 points; NIHSS by day 7 was increased

with 2.5 points if IL-6 was measurable in the peripheral blood on admission; NIHSS by day 7 was increased with 2.1 points by the presence of increased BMI; and NIHSS by day 7 was increased with .2 points by each year of age and with 1.6 points by male sex. The correlation between the predicted outcomes for each person based on this model and the observed values in this cohort, that is, using the same data, which were used to select and fit the model, was very strong, .97 (Table 6).

Discussion Here, we prospectively investigated 8 biomarkers in acute ischemic stroke. Both absolute concentrations at different time points and change in the concentrations were determined, and their association with poststroke infections, death, and functional outcome were investigated. Two control populations were used: (1) patients with significant carotid stenosis but without symptoms, to determine if increased concentrations are related to the acute ischemic event or are inherent to the pre-existing atherosclerosis and (2) patients with PD, a chronic neurodegenerative disease of the central nervous system accompanied by neuroinflammation.23 Finally, we applied multiple regression methods, relating biological biomarkers combined with demographic data and comorbidities to the considered outcomes and assessed the ability of the models to predict each outcome. Compared with patients with PD, systemic concentration of tPA, P-selectin, MCP-1, IL-8, IL-6, and CD40L were elevated within 6 hours after stroke and 72 hours later, indicating persistent abnormalities. Previous data suggested similar elevation of some of these markers

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Table 3. Correlation of S100B reflecting the extent of tissue damage with concentration of biomarkers

Table 4. Correlation of the presence of poststroke infection and death with biomarker concentrations P value

S100B Biomarkers hsCRP 6h 72 h D tPA 6h 72 h D P-selectin 6h 72 h D MCP-1 6h 72 h D IL-8 6h 72 h D IL-6 6h 72 h D CD40L 6h 72 h D

6 h, P value

72 h, P value

D, P value*

.06 #.001 #.001

.06 #.001 .005

.40 .003 .11

.22 .36 .88

.06 .23 .80

.93 .93 .25

.15 .84 .34

.50 .25 .91

.04 .19 .15

.51 .31 .10

.17 .66 .10

.95 .45 .43

.86 .08 .21

.10 .36 .16

.48 .02 .68

.09 .42 .80

.003 .02 .35

.19 .04 .16

.65 .65 .05

.55 .32 .70

.30 .07 .19

Abbreviations: hsCRP, high-sensitivity C-reactive protein; IL, interleukin; MCP-1, monocyte chemotactic protein 1; tPA, tissue plasminogen activator. Significance levels (P values) determined by Spearman’s nonparametric correlations are shown. Significant changes are indicated in bold. *Change of concentration between poststroke 6 and 72 hours.

compared with healthy controls.30,31 A recent large meta-analysis found only 3 biomarkers, which differed between ischemic stroke and healthy control subjects, among them, hsCRP and P-selectin.32 Because the elevated levels within 6 hours may reflect such abnormalities related to atherosclerosis instead of stroke, we enrolled patients with severe asymptomatic carotid stenosis and examined also the temporal profiles. Concentration of all biomarkers but IL-8 was higher within 6 hours compared with patients with carotid stenosis, suggesting that increased levels were not related to the atherosclerosis per se. However, concentration of tPA, MCP-1, IL-8, IL-6, and CD40L were also higher in patients with carotid stenosis compared with PD, indicating that severe atherosclerosis was associated with increased systemic concentrations, and stroke

Biomarkers hsCRP 6h 72 h D* tPA 6h 72 h D P-selectin 6h 72 h D MCP-1 6h 72 h D IL-8 6h 72 h D IL-6 6h 72 h D CD40L 6h 72 h D S100B 6h 72 h D

Infection

Death

.09 #.001 #.001

.009 #.001 #.001

.13 .21 .57

.14 .43 .82

.13 .41 .007

.36 .91 .009

.02 .12 .72

.30 .15 .96

.12 .35 .80

.01 .11 .57

.001 .05 .04

#.001 .27 .39

.20 .22 .27

.88 .70 .02

.006 #.001 .02

.008 .004 .05

Abbreviations: hsCRP, high-sensitivity C-reactive protein; IL, interleukin; MCP-1, monocyte chemotactic protein 1; tPA, tissue plasminogen activator. Significance levels (P values) determined by Mann–Whitney U test are shown. Significant changes are indicated in bold. *Change of concentration between poststroke 6 and 72 hours.

resulted in an additional acute increase. Association of atherosclerosis and carotid stenosis with elevated concentrations of these biomarkers has indeed been shown.33,34 In the Framingham Heart Study, modest association with 25% or greater carotid stenosis was found, particularly with IL-6.33 We used multiple regression to examine, which combination of factors could best predict poststroke infection, death, and NIHSS score by day 7; as covariates, we considered biological biomarkers and their changes, demographic data, and comorbidities. For the regression analysis of the binary outcomes, we used Firth’s logistic

THROMBOINFLAMMATORY BIOMARKERS IN STROKE

Table 5. Correlation of functional outcomes with biomarker concentrations NIHSS Day 1

Days 1-2

Days 1-7

Day 28

P value

Biomarkers hsCRP 6h 72 h D* tPA 6h 72 h D P-selectin 6h 72 h D MCP-1 6h 72 h D IL-8 6h 72 h D IL-6 6h 72 h D CD40L 6h 72 h D S100B 6h 72 h D

Barthel

.09 #.001 #.001

.91 .08 .03

.17 .08 .21

.33 .009 .37

.21 .46 .24

.15 .14 .72

.15 .14 .83

.77 .80 .69

.04 .19 .73

.25 .85 .29

.15 .92 .15

.88 .79 .84

.36 .59 .44

.83 .50 .16

.46 .70 .96

.19 .08 .82

.22 .64 .81

.50 .41 .74

.97 .54 .85

.29 .95 .68

.03 .04 .98

.04 .54 .90

.98 .63 .95

.78 .12 .39

.83 .55 .24

.25 .70 .73

.27 .95 .48

.16 .15 .39

.001 #.001 .15

.03 .04 .49

.04 .20 .97

.27 .04 .001

Abbreviations: hsCRP, high-sensitivity C-reactive protein; IL, interleukin; MCP-1, monocyte chemotactic protein 1; NIHSS, National Institutes of Health Stroke Scale; tPA, tissue plasminogen activator. Significance levels (P values) determined by Spearman’s nonparametric correlations are shown. Significant changes are indicated in bold. *Change of concentration between poststroke 6 and 72 hours.

regression to circumvent the problem that a single covariate or a linear combination of covariates by merely random chance perfectly predicts the outcome. Logistic regression fails in such a case and leads to infinite odds ratio estimates; Firth’s logistic regression provides more realistic estimates by removing first-order bias from the calculated maximum likelihood estimates. At the same time, it has been indicated by simulations not to be overly conservative.29 When using the selected regression

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models, we achieved excellent predictions as indicated by high values of the AUC and correlation coefficient, respectively. By using these logistic regression models, the role of several factors emerged in predicting outcomes with high efficacy within our data set and confirmed correlation results: hsCRP, change of P-selectin in the acute phase, early and late elevation of IL-6, early NIHSS, and obesity (BMI). Particularly, change of P-selectin concentration from 6 to 72 hours by 1 unit (pg/mL) increased the incidence of poststroke infections with an odds ratio of 22.7; each 100 additional units (pg/mL) of IL-6 concentration at baseline increased the odds of death by 9&, and at 72 hours, the odds of poststroke infections by 4&; and each additional unit (mg/L) of baseline hsCRP concentration elevated the odds of death by 7%. Interestingly, P-selectin IL-6, and hsCRP contributing to outcomes in our models, all showed similar temporal profiles: an additional elevation by 72 hours besides an increased concentration on admission (within 6 hours) compared with both patients with carotid stenosis and PD. We also examined biomarker concentrations in different patient subgroups according to TOAST criteria: levels of both P-selectin and IL-6 measured 72 hours after stroke onset were higher in patients with large-artery occlusion and cardioembolic stroke compared with patients with lacunar stroke. Higher IL-6 plasma levels have been previously suggested in patients with cardioembolic stroke.35 Higher hsCRP levels in patients with large-artery stroke compared with lacunar stroke may reflect correlation with infarct size and tissue damage indicated by our data here and by previous studies.4,31 Interestingly, prevalence of death was also higher among patients with large-artery occlusion (23.8%) and cardioembolic stroke (32%) compared with patients with small-vessel occlusion (5%). P-selectin is produced by both platelets and endothelial cells and mediates early inflammatory cell adhesion.9,10 The ligand of P-selectin is expressed mainly by polymorphonuclear cells and monocytes. Such intercellular communication results in responses by all these cell populations: leukocyte invasion, enhanced platelet aggregation, and thromboxane release, and inflammatory gene expression in monocytes inducing synthesis of MCP-1 and IL-8.10,36 Thus, the early elevation of P-selectin may be associated with endothelial dysfunction and platelet activation, whereas the later increase may reflect leukocyte invasion peaking around 72 hours.37 Such increase in P-selectin concentration may also contribute to deleterious systemic complement activation in the early phase of stroke: platelet-specific complement activation requires the surface expression of P-selectin.6 Recent studies also found high P-selectin levels on admission that increased further during the first week, and were still

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Table 6. Prediction of death, poststroke infections, and NIHSS score by day 7 using logistic regression models Covariates Deathy Gender Age hsCRP IL-6 at 6 h Poststroke infectiony Gender Age IL-6 at 72 h P-selectin Dz IL-8 at 6 h NIHSS score by day 7x Gender Age NIHSS score by day 2 Obesity IL-6 at 6 hk

OR

P value

b (SE)*

2.53 1.31 1.07 1.000093

.511 .008 ,.001 .047

.93 (1.58) .27 (.13) .065 (.025) 9.3e-05 (5.1e-05)

15.26 .99 1.000043 22.69 .9999

.019 .902 .005 .002 .023

NA NA NA NA NA

AUC

Correlation (predicted, observed)

.98

NA

.92

NA

NA

.97; adjusted R2 5 .93

2.73 (1.29) 2.0062 (.048) 4.3e-5 (2.4e-5) 3.12 (1.19) 21.2e-4 (7.7e-5)

.064 .001 ,.001 .01 .02

21.64 (.85) .19 (.05) .89 (.06) 2.07 (.74) 2.50 (1.06)

Abbreviations: AUC, area under the curve; hsCRP, high-sensitivity C-reactive protein; IL, interleukin; MCP-1, monocyte chemotactic protein 1; NA, not applicable; NIHSS, National Institutes of Health Stroke Scale; OR, odds ratio; SE, standard error; tPA, tissue plasminogen activator. The table displays the explanatory variables, estimated coefficients, standard error (b and SE), nominal P value, and odds ratios. Considered explanatory variables were age; sex; smoking; obesity; diabetes; NIHSS score by day 1, day 2, and difference between day 1 and 2; and concentration of hsCRP, S100B, CD40L, tPA, MCP, IL-8, IL-6, P-selectin at baseline, and change between baseline and 72 hours later. The model underwent extension and reduction iterating between (1) screening explanatory variables not contained in the current model one at a time and adding the most significant one (if F-test P value , 5%) and (2) and removing explanatory variables one at a time, which no longer contributed significantly to the model (F-test P value . 5%). The final models were validated using standard residual diagnostics (linear regression) and Hosmer–Lemeshow’s goodness-of-fit test (logistic regression). *Estimated coefficients and standard error. yFirth’s logistic regression. zConcentration at 72 hours 2 6 hours. xMultiple logistic regression. kMeasurable concentration.

different from controls on day 10, indicating vascular instability and procoagulant activity.38,39 However, because change in P-selectin levels correlated with poststroke infections in our study, late elevation may also indicate leukocyte activation due to a subclinical phase of infection. The role of IL-6 in stroke is somewhat controversial.15,16,40 Upregulation of IL-6 on neurons, glial cells, and vascular endothelium is a consistent finding in animal models of cerebral ischemia.15,16 IL-6 is elevated in the cerebrospinal fluid of patients with stroke and can reflect systemic release and passive passage due to the blood–brain barrier disruption or release from dying neurons and production by microglia.15,17 Although animal models suggest a function in controlling oxidative stress and angiogenesis,15,40 such neuroprotective roles are difficult to reconcile with clinical findings: IL-6 on admission correlated with concentration of S100B at 72 hours in our cohort, indicating that early systemic production of IL-6 correlates with the extent of tissue damage on biomarker levels, similar to neuroimaging studies.17,41 Higher level of IL-6 after stroke also correlated with early neurologic

deficit, body temperature, and long-term poor outcome.17,41 It is also likely that alterations in systemic and intrathecal levels of IL-6 may reflect different cellular sources elicited by different interactions/ pathways, and eventually contribute to the differential effects. Early systemic elevation may be related to thrombotic events and platelet–endothelial–monocyte interactions,42 whereas late elevation can indicate leukocyte activation. Such dichotomization and multifunctionality is not exceptional in stroke: leukocyte infiltration and local activation within the ischemic tissue may be deleterious, but proper systemic activation of leukocytes is required to protect against infections in the poststroke period.4 Similarly, different causes may contribute to elevation of hsCRP at 6 and 72 hours, and late increase in concentration may be related to a subclinical infection. This may also explain why an increase of hsCRP by 72 hours correlates with poststroke infections.28 Correlation between S100B and hsCRP levels may also point to the fact that patients with more extensive tissue damage are more susceptible to poststroke infections because of more profound immune dysfunction.4,28,43

THROMBOINFLAMMATORY BIOMARKERS IN STROKE

The study is not without limitations. The infarct volume was not measured by neuroimaging approaches; rather, we correlated biomarker levels with concentration of S100B as a marker of tissue damage. However, this measurement cannot be regarded as a gold standard to establish the size of the infarct. Altogether, our data indicate that a number of biological biomarkers with a potential to influence thromboinflammation due to multiple effects on different cellular and humoral pathways, are elevated in the hyperacute phase of stroke compared with both vascular and neurodegenerative/neuroinflammatory controls. In regression models, in which biological, demographic, and comorbid factors were combined, those biological biomarkers predicted outcome with high accuracy, which were characterized by an increasing concentration by 72 hours. Two particular biomarkers emerged in this prospective study to predict outcomes: early dynamic changes in the levels of P-selectin and IL-6.

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