Cell Mol Neurobiol (2015) 35:355–361 DOI 10.1007/s10571-014-0131-0
ORIGINAL RESEARCH
Relationship Between Procalcitonin Serum Levels and Functional Outcome in Stroke Patients Wen-Jing Deng • Rui-Le Shen • Meng Li Jun-Fang Teng
•
Received: 10 September 2014 / Accepted: 24 October 2014 / Published online: 5 November 2014 Ó Springer Science+Business Media New York 2014
Abstract To determine whether serum procalcitonin (PCT) levels at admission were associated with short-term functional outcome after acute ischemic stroke (AIS) in a cohort Chinese sample. We prospectively studied 378 patients with AIS who were admitted within 24 h after the onset of symptoms. PCT and NIH stroke scale (NIHSS) were measured at the time of admission. Short-term functional outcome was measured by modified Rankin scale (mRS) 90 days after admission. The results indicated that the serum PCT levels were significantly higher in AIS patients as compared to normal controls (P \ 0.0001). In the 114 patients with an unfavorable functional outcome, serum PCT levels were higher compared with those in patients with a favorable outcome (2.40 (IQR, 1.10–3.69) ng/mL and 0.42 (IQR, 0.10–1.05) ng/mL, respectively, P \ 0.001). PCT was an independent prognostic marker of functional outcome [odds ratio (OR) 3.45 (2.29–4.77), adjusted for the NIHSS and other possible confounders] in patients with ischemic stroke, added significant additional predictive value to the clinical NIHSS score. In receiver operating characteristic curve analysis, the prognostic accuracy of PCT was higher compared to Hs-CRP and NIHSS score. PCT is an independent predictor of short-term functional outcome after ischemic stroke in Chinese sample even after correcting for possible confounding factors.
W.-J. Deng M. Li J.-F. Teng (&) Department of Neurology, The First Affiliated Hospital of Zhengzhou University, No. 1, Jianshe East Road, Zhengzhou 450052, Henan, People’s Republic of China e-mail: [email protected] R.-L. Shen Department of Neurology, The First Affiliated Hospital of Henan University of Science and Technology, Luoyang 471000, Henan, People’s Republic of China
Keywords Procalcitonin Acute ischemic stroke Functional outcome Short-term
Introduction Stroke is the second commonest cause of death and leading cause of adult disability in China (Bonita et al. 2004). An early risk assessment with estimate of the severity of disease and prognosis is pivotal for optimized care and allocation of healthcare resources to improve outcome (Slot et al. 2008). The ability of biomarkers to improve the prognostic accuracy after acute ischemic stroke (AIS) is attractive. Inflammatory processes have fundamental roles in stroke in both the etiology of ischemic cerebrovascular disease and the pathophysiology of cerebral ischemia. Inflammatory markers predicted the stroke risk, severity, and outcome (Rost et al. 2001; Vibo et al. 2007; Emerging Risk Factors Collaboration 2010; Whiteley et al. 2012; Markaki et al. 2013). Procalcitonin (PCT), a protein of 116 amino acids with molecular weight of 13 kDa, was discovered 25 years ago as a prohormone of calcitonin produced by C-cells of the thyroid gland and intracellularly cleaved by proteolytic enzymes into the active hormone. PCT detectable in the plasma during inflammation is not produced in C-cells of the thyroid. The probable site of PCT production during inflammation is the neuroendocrine cells in the lungs or intestine (Maruna et al. 2000). Mimoz et al. (1998) found that an early and transient release of PCT into the circulation was observed after severe trauma and the amount of circulating PCT seemed proportional to the severity of tissue injury and hypovolemia, yet unrelated to infection, indicating an inflammation-related induction of PCT (Castelli et al. 2004).
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Schiopu et al. (2012) found a positive association between plasma PCT levels and cardiovascular risk in subjects with no previous history of acute cardiovascular events in a largest population-based prospective study, while Katan et al. (2014) reported that higher levels of PCT were independently associated with ischemic stroke risk in a multiethnic, urban cohort. However, the prognostic value of PCT in AIS is uncertain. We sought to determine whether serum PCT levels at admission were associated with short-term functional outcome after AIS in a cohort Chinese sample.
Materials and Methods Patients and Study Design From December 2011 to November 2013, all patients with an AIS event in our hospital were included. Patients were eligible for inclusion if they were admitted to the emergency department with an AIS defined according to the World Health Organization criteria (rapidly developing clinical signs of focal disturbance of cerebral function, lasting more than 24 h or leading to death with no apparent cause other than that of vascular origin) and with symptom onset within 24 h. Exclusion criteria were malignant tumor, intracerebral hemorrhage, and systemic infections. Other types of stroke (transient ischemic attack, subarachnoid hemorrhage, embolicbrain infarction, brain tumors, and cerebrovascular malformation) and severe systemic diseases (collagenosis, endocrine, and metabolic disease [except for diabetes mellitus, DM], inflammation, neoplastic, liver, or renal diseases) were also in the range of exclusion. The control cases (N = 200) were of similar age and gender distribution to the AIS patients. The nearby residents who came to the health care department of our hospital for Health Examination were included. They had no known diseases and were not using any medication. A detailed medical history was taken and clinical and laboratory examinations were performed on all participants in both groups. The present study has been approved by the ethics committee of the First Affiliated Hospital of Zhengzhou University. All participants or their relatives were informed of the study protocol and their written informed consent was obtained, according to the Declaration of Helsinki. Clinical Variables and Follow-Up The following clinical and demographical data were taken: age, gender, stroke etiology, blood pressure, leukocyte count, and presence of risk factors such as hypertension,
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smoking status, hyperlipoproteinemia, and diabetes mellitus. Routine laboratory testing was always done. Stroke cause was determined according to the criteria of the TOAST (Trial of Org 10172 in Acute Stroke Treatment) classification (Adams et al. 1993), which distinguishes large-artery arteriosclerosis cardioembolism, small-artery occlusion, other causative factor, and undetermined causative factor. Severity of stroke was assessed at admission by the National Institutes of Health Stroke Scale (NIHSS) score (scores range from 0 to 42, with greater scores indicating increasing severity) (Brott et al. 1989). Functional outcome was obtained at 90-day after admission according to the modified Rankin Scale (mRS) (Bonita 1988) blinded to PCT levels. The primary end point of this study was favorable functional outcome of stroke patients after 90 days from baseline, defined as a mRS score of 0 to 2 points. Secondary end point in stroke patients was death from any cause within a 90-day followup. Outcome assessment was performed by two trained medical students blinded to PCT levels with a structured follow-up telephone interview with the patient or, if not possible, with the closest relative, or family physician. Neuroimaging Diagnosis of stroke was based on the results of strict neurological examination according to the International Classification of Diseases, ninth revision, Clinical Modification (ICD-9-CM, 1980). MRI was performed using a stroke protocol, including T1-, T2-, and diffusion-weighted imaging (DWI) sequences, and a magnetic resonance angiography. MRI with DWI was available in some stroke patients. In those patients, DWI lesion volumes were determined by consensus of two experienced raters unaware of the clinical and laboratory results. The lesion size was calculated by the commonly used semiquantitative method (Broderick et al. 1993). Lesions were ranked into three sizes to represent typical stroke patterns: (1) small lesion with a volume of less than 10 mL, (2) medium lesion of 10–100 mL, and (3) large lesion with a volume of more than 100 mL (Szabo et al. 2001). PCT Measurement Fasting blood was collected from all participants via venipuncture in BD Vacutainer Ò (New Jersey, USA) tubes at 7:30 am ± 30 min on the morning after the clinical assessments were conducted. Blood samples were centrifuged at 1,0009g for 10 min at 4 °C, and serum was separated and stored at -80 °C until the time of assay. PCT was measured by Time-Resolved Amplified Cryptate Emission (TRACE) Assay analysis on the B.R.A.H.M.S. KryptorÒ Compact instrument, and Hs-CRP was analyzed
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by the Roche Cobas Integra 800 analyzer (Roche Diagnostic, Indianapolis, IN, USA). The inter-assay and intraassay coefficients of variation for PCT were shown to be 1.9–4.8 and 2.5–5.6 %. Median serum PCT level in 200 healthy individuals was 0.04 ng/mL. Statistical Analysis Discrete variables are summarized as counts (percentage), and continuous variables as medians and interquartile
Table 1 Baseline characteristics of stroke patients (n = 378)
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ranges (IQRs). Two-group comparison of not normally distributed data was performed using Mann–Whitney U test, and a Kruskal–Wallis one-way analysis of variance was used for multi-group comparisons. The relation of PCT with the end points was investigated with the use of logistic regression models. We used crude models and multivariate models adjusted for all significant outcome predictors and report odds ratios (ORs). Note that the OR corresponds to a one-unit increase in the explanatory variable. Second, we compared different prognostic risk scores from different
Demographic characteristics
Patients (n = 378)
Normal cases (n = 200)
Male sex (%)
60.8
61
Age (years) median (IQR)
70 (62–79)
70 (62–78)
NIHSS at admission, median (IQR)
7 (3–11)
–
0–2
264 (69.8)
–
3–6
114 (30.2)
–
Temperature (°C)
36.8 (36.5–37.2)
36.7 (36.4–37.0)
Body mass index (BMI) (kg m-2)
25.5 (24.3–27.4)
25.4 (23.9–26.9)
Systolic blood pressure (mmHg)
156 (140–175)
122 (110–132)
mRS at 3 month no. (%)
Clinical findings median (IQR)
Diastolic blood pressure (mmHg)
94 (74–100)
74 (70–84)
Heart rate (beats min-1)
80 (72–91)
77 (70–85)
Hypertension
79.4
–
Diabetes mellitus Smoking history
40.2 20.6
– –
Hypercholesterolaemia
43.9
–
Coronary heart disease
27.0
–
Family history of cardiovascular event
32.3
–
Atrial fibrillation
28.0
–
Vascular risk factors (%)
Laboratory findings (median–IQR)
mRS modified Rankin Scale, IQR interquartile range, PCT procalcitonin, Hs-CRP, highsensitivity C-reactive protein, NIHSS National Institutes of Health Stroke Scale, WBC white blood cells count, HCY homocysteine a
Cut-off points for serum HsCRP and PCT in our laboratory were defined as 0.42 mg dL-1 and 0.52 ng mL-1
Total cholesterol (mmol L-1)
4.15 (3.35–4.96)
4.01 (3.12–4.82)
Triglycerides (mmol L-1)
1.44 (1.10–1.87)
1.22 (1.01–1.57)
High-density lipoproteins (mmol L-1)
1.36 (1.08–1.62)
1.45 (1.17–1.72)
Low-density lipoproteins (mmol L-1)
2.07 (1.33–2.73)
1.84 (1.25–2.54)
Glucose (mmol L-1)
5.65 (4.99–6.49)
5.20 (4.65–5.82)
WBC (9109 L-1)
8.6 (7.4–9.7)
8.3 (7.2–9.2)
HCY (lmol L-1)
19.8 (15.8–25.4)
15.2 (12.8–18.1)
Hs-CRP (mg dL-1)a
0.66 (0.28–1.52)
0.25 (0.17–0.37)
PCT (ng mL-1)a
0.88 (0.20–1.68)
0.04 (0.03–0.06)
Stroke etiology (%) Small-vessel occlusive
18.0
–
Large-vessel occlusive
19.0
–
Cardioembolic
31.2
–
Other
11.1
–
Unknown
20.7
–
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predictive models by calculating receiver operating characteristic analysis. Thereby, the area under the receiver operating characteristic curve (AUC) is a summary measure over criteria and cut-point choices. All testing was two tailed, and p values less than 0.05 were considered to indicate statistical significance. All calculations were performed using SPSS for Windows, version 17.0 (SPSS Inc., Chicago, IL, USA) and STATA 9.2 (Stata Corp, College Station, TX), R version 2.8.1.
Results
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levels paralleled lesion size (analysis of variance [ANOVA]: P \ 0.0001). Median levels in patients with small lesions, medium lesions, and large lesions were 0.40 (IQR, 0.06–0.75) ng/mL, 0.90(IQR, 0.22–1.69) ng/mL, and 1.02(IQR, 0.42–2.24) ng/mL, respectively. PCT levels increased with increasing severity of stroke as defined by the NIHSS score. Figure 1a. There was a positive correlation between levels of PCT and NIHSS score (r = 0.265, P \ 0.0001). Figure 1b. There was a correlation between levels of PCT and Hs-CRP (r = 0.226, P \ 0.001). Interestingly, there was also a correlation between levels of PCT and age (r = 0.193, P = 0.002). There was no correlation between levels of serum PCT levels and sex, stroke
Baseline Characteristics of the Study Population From 558 screened patients, AIS was diagnosed in 446 patients, and 378 (230 men, 148 women) aged 70 (IQR, 62–79) completed 90 days follow-up and were included in the analysis. At admission, the median NIHSS score was 7 (IQR, 3–11). Overall, an unfavorable outcome after 90 days was observed in 114 patients (30.2 %), defined as Rankin scale 3–6. After 90 days, 40 patients had died, thus the mortality rate was 10.6 %. The principal baseline characteristics of all patients are provided in Table 1. PCT and Stroke Characteristics The results indicated that the serum PCT levels were significantly higher in stroke patients as compared to normal controls [0.88 (IQR, 0.20–1.68) ng/mL vs 0.04 (IQR, 0.03–0.06) ng/mL; P \ 0.0001)]. In the subgroup of patients (n = 287) in whom MRI was available, PCT
Fig. 2 Serum PCT levels in AIS patients with favorable and unfavorable outcome. Mann–Whitney U test. All data are medians and interquartile ranges (IQR)
Fig. 1 Correlation between the serum PCT levels and other factors. a Correlation between the serum PCT levels and NIHSS score; b Correlation between the serum PCT levels and Hs-CRP
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Cell Mol Neurobiol (2015) 35:355–361 Table 2 Multivariate analysis for functional outcome
Predictors
359
Univariate analysis OR
a
95 % CI
Multivariate analysis P
OR
95 % CI
P
Functional outcome
OR odds ratio, CI confidence interval, NIHSS National Institutes of Health Stroke Scale, Hs-CRP high-sensitivity C-reactive protein, PCT Procalcitonin a
Note that the odds ratio corresponds to a unit increase in the explanatory variable
Hs-CRP
3.32
0.001
2.52
1.24–4.13
0.002
PCT
4.02
1.99-5.12
1.50–6.31
\0.0001
3.45
2.29-4.77
\0.0001
NIHSS score
1.22
1.06–1.44
\0.0001
1.09
1.04–1.15
\0.0001
Age
1.12
1.04–1.25
0.002
1.08
1.03–1.18
0.001
Female sex
1.71
1.15–2.46
0.02
1.23
0.94–2.31
0.332
1.01–1.45
0.044
1.02–2.98
0.144
Glucose
1.08
1.02–1.33
0.037
1.06
Temperature
0.86
0.50–1.48
0.592
–
Hypertension
1.91
1.14–3.19
0.011
1.55
Atrial fibrillation
1.62
1.00–2.70
0.064
–
Hypercholesterolemia Coronary heart disease
0.78 1.20
0.48–1.27 0.75–1.95
0.323 0.464
– –
Small-vessel occlusive
0.61
0.21–1.80
0.376
–
Large-vessel occlusive Cardioembolic
1.05
0.68–1.62
0.845
–
1.12
0.74–1.69
0.742
–
etiology, serum levels of glucose, white blood cells count, and homocysteine (P [ 0.05, respectively). PCT and 90-day Functional Outcome In the 114 patients with an unfavorable functional outcome, serum PCT levels were higher compared with those in patients with a favorable outcome (2.40 (IQR, 1.10–3.69) ng/mL and 0.42 (IQR, 0.10–1.05) ng/mL, respectively, P \ 0.001). Figure 2. In univariate logistic regression analysis, PCT levels as compared with Hs-CRP, the NIHSS score and other risk factors are presented in Table 2. After adjusting for all other significant outcome predictors, PCT remained independent unfavorable outcome predictors with an adjusted OR of 3.45 (95 % CI 2.29–4.77). In the subgroup of patients (n = 287) in whom MRI evaluations were performed, PCT was an independent unfavorable outcome predictor with an OR of 3.67 (95 % CI 2.17–4.89; P \ 0.001) after adjustment for both lesion size (OR, 1.08; 95 % C 1.03–1.13; P \ 0.001) and the NIHSS score (OR, 1.12; 95 % CI 1.07–1.18; P \ 0.001). Based on the ROC curve, the optimal cut-off value of serum PCT levels as an mortality indicator was estimated to be 1.15 ng/mL, which yielded a sensitivity of 75.4 % and a specificity of 80.7 %, with the area under the curve at 0.845 (95 % CI 0.799–0.890). Figure 3. With an AUC of 0.845, PCT showed a significantly greater discriminatory ability as compared with age, Hs-CRP, and the NIHSS score. In addition, a combined model (PCT/NIHSS score/ Hs-CRP/age/glucose) showed a greater discriminatory ability than those factors alone Table 3.
Fig. 3 Receiver operating characteristic (ROC) curves are utilized to evaluate the accuracy of serum PCT levels to predict functional outcome
Discussion To our knowledge, our study was the first time to determine the prognostic value of serum PCT levels to predict shortterm functional outcome in patients with AIS. Our main finding was that PCT was an independent prognostic marker of functional outcome in Chinese patients with
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Table 3 Receiver operating characteristics curve analysis Parameter
Functional outcome AUC
95 % CI
P
PCT
0.845
0.799–0.890
NHISS
0.730
0.668–0.786
\0.001
Hs-CRP
0.695
0.634–0.735
\0.0001
Age
0.616
0.567–0.679
\0.0001
Glucose
0.635
0.581–0.704
\0.0001
Combined scorea
0.887
0.813–0.932
\0.001
Combined scoreb Combined scorec
0.902 0.927
0.827–0.944 0.839–0.965
\0.001 \0.0001
AUC area under the curve, CI confidence interval, Hs-CRP highsensitivity C-reactive protein, PCT procalcitonin, NIHSS National Institutes of Health Stroke Scale a b c
Including PCT/NIHSS Including PCT/NIHSS/Hs-CRP Including PCT/NIHSS/Hs-CRP/age/glucose
ischemic stroke, and adds significant additional predictive information to the clinical score of the NIHSS and HsCRP. We demonstrated that PCT levels increased with lesion size and neurological deficit (assessed by the NIHSS), reflecting the severity of the stroke. Several biomarkers were evaluated previously: brain natriuretic peptide, copeptin, CRP, glutamate, glucose, and vitamin D have a significant association with outcome in stroke patients (Whiteley et al. 2009; Fuentes et al. 2009; Wang et al. 2014; Chang et al. 2014; Meng et al. 2014; Tu et al. 2013). All these biomarkers are available immediately due to rapid analytic procedure. In our study, we found that serum PCT levels at admission were associated with poor outcome in stroke patients. Luyt et al. (2005) suggested that PCT could be a prognostic marker of outcome during ventilator-associated pneumonia, while Wanner et al. (2000) indicated that PCT represents a sensitive and predictive indicator of sepsis and severe multiple organ dysfunction syndrome in injured patients. In the literature, PCT was a superior diagnostic marker in pneumonia and other bacterial infections when compared to WBC and CRP (Tamaki et al. 2008). Consistent with this, we also found that PCT was a superior outcome predictor than Hs-CRP. Similarly, Simon et al. (2004) found that the diagnostic accuracy of PCT markers was higher than that of CRP markers among patients hospitalized for suspected bacterial infections. In previous studies, PCT was selected to better discriminate infections from general inflammation (Fluri et al. 2012), and as an early marker for sepsis (McGrane et al. 2011). Elevated PCT concentrations appear to be a promising indicator of sepsis in newly admitted, critically ill patients capable of complementing clinical signs and routine laboratory parameters suggestive of severe infection (Harbarth et al. 2001).
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Levels of PCT were strongly associated with stroke severity in this sample. A severe stroke per se implicates a poor outcome; it is not surprising that PCT is also associated with poor outcome. Because PCT remained independently associated with outcome even after adjusting for stroke severity, however, it seems that this marker may provide additional general prognostic information. PCT and CRP levels are related to the severity of organ dysfunction (Fuentes et al. 2009). Inflammatory mediators produced during critical illness (for example, tumor necrosis factor-a, PCT) initiate a systemic cascade of endothelial damage, thrombin formation, and microvascular compromise (Wheeler and Bernard 1999). However, the interpretation of the data must be done cautiously. Firstly, concentrations of inflammatory markers at the site of infarction may only partially be reflected by the inflammatory response in the peripheral blood. This study yielded no data regarding when and how long PCT is elevated in these patients. Secondly, the effects of circulating PCT on long-term clinical outcome were not included in the study protocol, so these relationships were not examined beyond the 90-day clinical outcome. Thirdly, PCT was measured only at one time point (at admission). Serial measurements of PCT were not available because this was not considered during the planning of the epidemiological cohort that this study arises from. Therefore, our measurement was not able to reflect potentially dynamic changes of PCT level. Further studies are needed to assess how PCT levels change across time after stroke and whether levels drawn at later points provide improved prognostic information. These studies need to be large, involve multiple centers, and provide statistical confirmation of incremental value of these markers beyond that provided by potential confounding risk factors before inflammatory biomarkers could be considered as part of the routine clinical evaluation of patients with stroke.
Conclusions Despite its inherent limitations, we confirmed that PCT was an independent prognostic marker of functional outcome in Chinese patients with AIS. We recommend that further studies should be carried out with respect to the mechanism between increased PCT levels and poor outcome. If it is possible to elucidate this, the prognosis of Chinese patients with stroke might be improved. Acknowledgments We also express our gratitude to all the patients who participated in this study, and thereby made this work possible. Conflict of interest The authors have no relevant potential conflicts of interest to declare. Funding
The author(s) received no specific funding for this work.
Cell Mol Neurobiol (2015) 35:355–361
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ORIGINAL RESEARCH
Relationship Between Procalcitonin Serum Levels and Functional Outcome in Stroke Patients Wen-Jing Deng • Rui-Le Shen • Meng Li Jun-Fang Teng
•
Received: 10 September 2014 / Accepted: 24 October 2014 / Published online: 5 November 2014 Ó Springer Science+Business Media New York 2014
Abstract To determine whether serum procalcitonin (PCT) levels at admission were associated with short-term functional outcome after acute ischemic stroke (AIS) in a cohort Chinese sample. We prospectively studied 378 patients with AIS who were admitted within 24 h after the onset of symptoms. PCT and NIH stroke scale (NIHSS) were measured at the time of admission. Short-term functional outcome was measured by modified Rankin scale (mRS) 90 days after admission. The results indicated that the serum PCT levels were significantly higher in AIS patients as compared to normal controls (P \ 0.0001). In the 114 patients with an unfavorable functional outcome, serum PCT levels were higher compared with those in patients with a favorable outcome (2.40 (IQR, 1.10–3.69) ng/mL and 0.42 (IQR, 0.10–1.05) ng/mL, respectively, P \ 0.001). PCT was an independent prognostic marker of functional outcome [odds ratio (OR) 3.45 (2.29–4.77), adjusted for the NIHSS and other possible confounders] in patients with ischemic stroke, added significant additional predictive value to the clinical NIHSS score. In receiver operating characteristic curve analysis, the prognostic accuracy of PCT was higher compared to Hs-CRP and NIHSS score. PCT is an independent predictor of short-term functional outcome after ischemic stroke in Chinese sample even after correcting for possible confounding factors.
W.-J. Deng M. Li J.-F. Teng (&) Department of Neurology, The First Affiliated Hospital of Zhengzhou University, No. 1, Jianshe East Road, Zhengzhou 450052, Henan, People’s Republic of China e-mail: [email protected] R.-L. Shen Department of Neurology, The First Affiliated Hospital of Henan University of Science and Technology, Luoyang 471000, Henan, People’s Republic of China
Keywords Procalcitonin Acute ischemic stroke Functional outcome Short-term
Introduction Stroke is the second commonest cause of death and leading cause of adult disability in China (Bonita et al. 2004). An early risk assessment with estimate of the severity of disease and prognosis is pivotal for optimized care and allocation of healthcare resources to improve outcome (Slot et al. 2008). The ability of biomarkers to improve the prognostic accuracy after acute ischemic stroke (AIS) is attractive. Inflammatory processes have fundamental roles in stroke in both the etiology of ischemic cerebrovascular disease and the pathophysiology of cerebral ischemia. Inflammatory markers predicted the stroke risk, severity, and outcome (Rost et al. 2001; Vibo et al. 2007; Emerging Risk Factors Collaboration 2010; Whiteley et al. 2012; Markaki et al. 2013). Procalcitonin (PCT), a protein of 116 amino acids with molecular weight of 13 kDa, was discovered 25 years ago as a prohormone of calcitonin produced by C-cells of the thyroid gland and intracellularly cleaved by proteolytic enzymes into the active hormone. PCT detectable in the plasma during inflammation is not produced in C-cells of the thyroid. The probable site of PCT production during inflammation is the neuroendocrine cells in the lungs or intestine (Maruna et al. 2000). Mimoz et al. (1998) found that an early and transient release of PCT into the circulation was observed after severe trauma and the amount of circulating PCT seemed proportional to the severity of tissue injury and hypovolemia, yet unrelated to infection, indicating an inflammation-related induction of PCT (Castelli et al. 2004).
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Schiopu et al. (2012) found a positive association between plasma PCT levels and cardiovascular risk in subjects with no previous history of acute cardiovascular events in a largest population-based prospective study, while Katan et al. (2014) reported that higher levels of PCT were independently associated with ischemic stroke risk in a multiethnic, urban cohort. However, the prognostic value of PCT in AIS is uncertain. We sought to determine whether serum PCT levels at admission were associated with short-term functional outcome after AIS in a cohort Chinese sample.
Materials and Methods Patients and Study Design From December 2011 to November 2013, all patients with an AIS event in our hospital were included. Patients were eligible for inclusion if they were admitted to the emergency department with an AIS defined according to the World Health Organization criteria (rapidly developing clinical signs of focal disturbance of cerebral function, lasting more than 24 h or leading to death with no apparent cause other than that of vascular origin) and with symptom onset within 24 h. Exclusion criteria were malignant tumor, intracerebral hemorrhage, and systemic infections. Other types of stroke (transient ischemic attack, subarachnoid hemorrhage, embolicbrain infarction, brain tumors, and cerebrovascular malformation) and severe systemic diseases (collagenosis, endocrine, and metabolic disease [except for diabetes mellitus, DM], inflammation, neoplastic, liver, or renal diseases) were also in the range of exclusion. The control cases (N = 200) were of similar age and gender distribution to the AIS patients. The nearby residents who came to the health care department of our hospital for Health Examination were included. They had no known diseases and were not using any medication. A detailed medical history was taken and clinical and laboratory examinations were performed on all participants in both groups. The present study has been approved by the ethics committee of the First Affiliated Hospital of Zhengzhou University. All participants or their relatives were informed of the study protocol and their written informed consent was obtained, according to the Declaration of Helsinki. Clinical Variables and Follow-Up The following clinical and demographical data were taken: age, gender, stroke etiology, blood pressure, leukocyte count, and presence of risk factors such as hypertension,
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smoking status, hyperlipoproteinemia, and diabetes mellitus. Routine laboratory testing was always done. Stroke cause was determined according to the criteria of the TOAST (Trial of Org 10172 in Acute Stroke Treatment) classification (Adams et al. 1993), which distinguishes large-artery arteriosclerosis cardioembolism, small-artery occlusion, other causative factor, and undetermined causative factor. Severity of stroke was assessed at admission by the National Institutes of Health Stroke Scale (NIHSS) score (scores range from 0 to 42, with greater scores indicating increasing severity) (Brott et al. 1989). Functional outcome was obtained at 90-day after admission according to the modified Rankin Scale (mRS) (Bonita 1988) blinded to PCT levels. The primary end point of this study was favorable functional outcome of stroke patients after 90 days from baseline, defined as a mRS score of 0 to 2 points. Secondary end point in stroke patients was death from any cause within a 90-day followup. Outcome assessment was performed by two trained medical students blinded to PCT levels with a structured follow-up telephone interview with the patient or, if not possible, with the closest relative, or family physician. Neuroimaging Diagnosis of stroke was based on the results of strict neurological examination according to the International Classification of Diseases, ninth revision, Clinical Modification (ICD-9-CM, 1980). MRI was performed using a stroke protocol, including T1-, T2-, and diffusion-weighted imaging (DWI) sequences, and a magnetic resonance angiography. MRI with DWI was available in some stroke patients. In those patients, DWI lesion volumes were determined by consensus of two experienced raters unaware of the clinical and laboratory results. The lesion size was calculated by the commonly used semiquantitative method (Broderick et al. 1993). Lesions were ranked into three sizes to represent typical stroke patterns: (1) small lesion with a volume of less than 10 mL, (2) medium lesion of 10–100 mL, and (3) large lesion with a volume of more than 100 mL (Szabo et al. 2001). PCT Measurement Fasting blood was collected from all participants via venipuncture in BD Vacutainer Ò (New Jersey, USA) tubes at 7:30 am ± 30 min on the morning after the clinical assessments were conducted. Blood samples were centrifuged at 1,0009g for 10 min at 4 °C, and serum was separated and stored at -80 °C until the time of assay. PCT was measured by Time-Resolved Amplified Cryptate Emission (TRACE) Assay analysis on the B.R.A.H.M.S. KryptorÒ Compact instrument, and Hs-CRP was analyzed
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by the Roche Cobas Integra 800 analyzer (Roche Diagnostic, Indianapolis, IN, USA). The inter-assay and intraassay coefficients of variation for PCT were shown to be 1.9–4.8 and 2.5–5.6 %. Median serum PCT level in 200 healthy individuals was 0.04 ng/mL. Statistical Analysis Discrete variables are summarized as counts (percentage), and continuous variables as medians and interquartile
Table 1 Baseline characteristics of stroke patients (n = 378)
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ranges (IQRs). Two-group comparison of not normally distributed data was performed using Mann–Whitney U test, and a Kruskal–Wallis one-way analysis of variance was used for multi-group comparisons. The relation of PCT with the end points was investigated with the use of logistic regression models. We used crude models and multivariate models adjusted for all significant outcome predictors and report odds ratios (ORs). Note that the OR corresponds to a one-unit increase in the explanatory variable. Second, we compared different prognostic risk scores from different
Demographic characteristics
Patients (n = 378)
Normal cases (n = 200)
Male sex (%)
60.8
61
Age (years) median (IQR)
70 (62–79)
70 (62–78)
NIHSS at admission, median (IQR)
7 (3–11)
–
0–2
264 (69.8)
–
3–6
114 (30.2)
–
Temperature (°C)
36.8 (36.5–37.2)
36.7 (36.4–37.0)
Body mass index (BMI) (kg m-2)
25.5 (24.3–27.4)
25.4 (23.9–26.9)
Systolic blood pressure (mmHg)
156 (140–175)
122 (110–132)
mRS at 3 month no. (%)
Clinical findings median (IQR)
Diastolic blood pressure (mmHg)
94 (74–100)
74 (70–84)
Heart rate (beats min-1)
80 (72–91)
77 (70–85)
Hypertension
79.4
–
Diabetes mellitus Smoking history
40.2 20.6
– –
Hypercholesterolaemia
43.9
–
Coronary heart disease
27.0
–
Family history of cardiovascular event
32.3
–
Atrial fibrillation
28.0
–
Vascular risk factors (%)
Laboratory findings (median–IQR)
mRS modified Rankin Scale, IQR interquartile range, PCT procalcitonin, Hs-CRP, highsensitivity C-reactive protein, NIHSS National Institutes of Health Stroke Scale, WBC white blood cells count, HCY homocysteine a
Cut-off points for serum HsCRP and PCT in our laboratory were defined as 0.42 mg dL-1 and 0.52 ng mL-1
Total cholesterol (mmol L-1)
4.15 (3.35–4.96)
4.01 (3.12–4.82)
Triglycerides (mmol L-1)
1.44 (1.10–1.87)
1.22 (1.01–1.57)
High-density lipoproteins (mmol L-1)
1.36 (1.08–1.62)
1.45 (1.17–1.72)
Low-density lipoproteins (mmol L-1)
2.07 (1.33–2.73)
1.84 (1.25–2.54)
Glucose (mmol L-1)
5.65 (4.99–6.49)
5.20 (4.65–5.82)
WBC (9109 L-1)
8.6 (7.4–9.7)
8.3 (7.2–9.2)
HCY (lmol L-1)
19.8 (15.8–25.4)
15.2 (12.8–18.1)
Hs-CRP (mg dL-1)a
0.66 (0.28–1.52)
0.25 (0.17–0.37)
PCT (ng mL-1)a
0.88 (0.20–1.68)
0.04 (0.03–0.06)
Stroke etiology (%) Small-vessel occlusive
18.0
–
Large-vessel occlusive
19.0
–
Cardioembolic
31.2
–
Other
11.1
–
Unknown
20.7
–
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predictive models by calculating receiver operating characteristic analysis. Thereby, the area under the receiver operating characteristic curve (AUC) is a summary measure over criteria and cut-point choices. All testing was two tailed, and p values less than 0.05 were considered to indicate statistical significance. All calculations were performed using SPSS for Windows, version 17.0 (SPSS Inc., Chicago, IL, USA) and STATA 9.2 (Stata Corp, College Station, TX), R version 2.8.1.
Results
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levels paralleled lesion size (analysis of variance [ANOVA]: P \ 0.0001). Median levels in patients with small lesions, medium lesions, and large lesions were 0.40 (IQR, 0.06–0.75) ng/mL, 0.90(IQR, 0.22–1.69) ng/mL, and 1.02(IQR, 0.42–2.24) ng/mL, respectively. PCT levels increased with increasing severity of stroke as defined by the NIHSS score. Figure 1a. There was a positive correlation between levels of PCT and NIHSS score (r = 0.265, P \ 0.0001). Figure 1b. There was a correlation between levels of PCT and Hs-CRP (r = 0.226, P \ 0.001). Interestingly, there was also a correlation between levels of PCT and age (r = 0.193, P = 0.002). There was no correlation between levels of serum PCT levels and sex, stroke
Baseline Characteristics of the Study Population From 558 screened patients, AIS was diagnosed in 446 patients, and 378 (230 men, 148 women) aged 70 (IQR, 62–79) completed 90 days follow-up and were included in the analysis. At admission, the median NIHSS score was 7 (IQR, 3–11). Overall, an unfavorable outcome after 90 days was observed in 114 patients (30.2 %), defined as Rankin scale 3–6. After 90 days, 40 patients had died, thus the mortality rate was 10.6 %. The principal baseline characteristics of all patients are provided in Table 1. PCT and Stroke Characteristics The results indicated that the serum PCT levels were significantly higher in stroke patients as compared to normal controls [0.88 (IQR, 0.20–1.68) ng/mL vs 0.04 (IQR, 0.03–0.06) ng/mL; P \ 0.0001)]. In the subgroup of patients (n = 287) in whom MRI was available, PCT
Fig. 2 Serum PCT levels in AIS patients with favorable and unfavorable outcome. Mann–Whitney U test. All data are medians and interquartile ranges (IQR)
Fig. 1 Correlation between the serum PCT levels and other factors. a Correlation between the serum PCT levels and NIHSS score; b Correlation between the serum PCT levels and Hs-CRP
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Cell Mol Neurobiol (2015) 35:355–361 Table 2 Multivariate analysis for functional outcome
Predictors
359
Univariate analysis OR
a
95 % CI
Multivariate analysis P
OR
95 % CI
P
Functional outcome
OR odds ratio, CI confidence interval, NIHSS National Institutes of Health Stroke Scale, Hs-CRP high-sensitivity C-reactive protein, PCT Procalcitonin a
Note that the odds ratio corresponds to a unit increase in the explanatory variable
Hs-CRP
3.32
0.001
2.52
1.24–4.13
0.002
PCT
4.02
1.99-5.12
1.50–6.31
\0.0001
3.45
2.29-4.77
\0.0001
NIHSS score
1.22
1.06–1.44
\0.0001
1.09
1.04–1.15
\0.0001
Age
1.12
1.04–1.25
0.002
1.08
1.03–1.18
0.001
Female sex
1.71
1.15–2.46
0.02
1.23
0.94–2.31
0.332
1.01–1.45
0.044
1.02–2.98
0.144
Glucose
1.08
1.02–1.33
0.037
1.06
Temperature
0.86
0.50–1.48
0.592
–
Hypertension
1.91
1.14–3.19
0.011
1.55
Atrial fibrillation
1.62
1.00–2.70
0.064
–
Hypercholesterolemia Coronary heart disease
0.78 1.20
0.48–1.27 0.75–1.95
0.323 0.464
– –
Small-vessel occlusive
0.61
0.21–1.80
0.376
–
Large-vessel occlusive Cardioembolic
1.05
0.68–1.62
0.845
–
1.12
0.74–1.69
0.742
–
etiology, serum levels of glucose, white blood cells count, and homocysteine (P [ 0.05, respectively). PCT and 90-day Functional Outcome In the 114 patients with an unfavorable functional outcome, serum PCT levels were higher compared with those in patients with a favorable outcome (2.40 (IQR, 1.10–3.69) ng/mL and 0.42 (IQR, 0.10–1.05) ng/mL, respectively, P \ 0.001). Figure 2. In univariate logistic regression analysis, PCT levels as compared with Hs-CRP, the NIHSS score and other risk factors are presented in Table 2. After adjusting for all other significant outcome predictors, PCT remained independent unfavorable outcome predictors with an adjusted OR of 3.45 (95 % CI 2.29–4.77). In the subgroup of patients (n = 287) in whom MRI evaluations were performed, PCT was an independent unfavorable outcome predictor with an OR of 3.67 (95 % CI 2.17–4.89; P \ 0.001) after adjustment for both lesion size (OR, 1.08; 95 % C 1.03–1.13; P \ 0.001) and the NIHSS score (OR, 1.12; 95 % CI 1.07–1.18; P \ 0.001). Based on the ROC curve, the optimal cut-off value of serum PCT levels as an mortality indicator was estimated to be 1.15 ng/mL, which yielded a sensitivity of 75.4 % and a specificity of 80.7 %, with the area under the curve at 0.845 (95 % CI 0.799–0.890). Figure 3. With an AUC of 0.845, PCT showed a significantly greater discriminatory ability as compared with age, Hs-CRP, and the NIHSS score. In addition, a combined model (PCT/NIHSS score/ Hs-CRP/age/glucose) showed a greater discriminatory ability than those factors alone Table 3.
Fig. 3 Receiver operating characteristic (ROC) curves are utilized to evaluate the accuracy of serum PCT levels to predict functional outcome
Discussion To our knowledge, our study was the first time to determine the prognostic value of serum PCT levels to predict shortterm functional outcome in patients with AIS. Our main finding was that PCT was an independent prognostic marker of functional outcome in Chinese patients with
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Table 3 Receiver operating characteristics curve analysis Parameter
Functional outcome AUC
95 % CI
P
PCT
0.845
0.799–0.890
NHISS
0.730
0.668–0.786
\0.001
Hs-CRP
0.695
0.634–0.735
\0.0001
Age
0.616
0.567–0.679
\0.0001
Glucose
0.635
0.581–0.704
\0.0001
Combined scorea
0.887
0.813–0.932
\0.001
Combined scoreb Combined scorec
0.902 0.927
0.827–0.944 0.839–0.965
\0.001 \0.0001
AUC area under the curve, CI confidence interval, Hs-CRP highsensitivity C-reactive protein, PCT procalcitonin, NIHSS National Institutes of Health Stroke Scale a b c
Including PCT/NIHSS Including PCT/NIHSS/Hs-CRP Including PCT/NIHSS/Hs-CRP/age/glucose
ischemic stroke, and adds significant additional predictive information to the clinical score of the NIHSS and HsCRP. We demonstrated that PCT levels increased with lesion size and neurological deficit (assessed by the NIHSS), reflecting the severity of the stroke. Several biomarkers were evaluated previously: brain natriuretic peptide, copeptin, CRP, glutamate, glucose, and vitamin D have a significant association with outcome in stroke patients (Whiteley et al. 2009; Fuentes et al. 2009; Wang et al. 2014; Chang et al. 2014; Meng et al. 2014; Tu et al. 2013). All these biomarkers are available immediately due to rapid analytic procedure. In our study, we found that serum PCT levels at admission were associated with poor outcome in stroke patients. Luyt et al. (2005) suggested that PCT could be a prognostic marker of outcome during ventilator-associated pneumonia, while Wanner et al. (2000) indicated that PCT represents a sensitive and predictive indicator of sepsis and severe multiple organ dysfunction syndrome in injured patients. In the literature, PCT was a superior diagnostic marker in pneumonia and other bacterial infections when compared to WBC and CRP (Tamaki et al. 2008). Consistent with this, we also found that PCT was a superior outcome predictor than Hs-CRP. Similarly, Simon et al. (2004) found that the diagnostic accuracy of PCT markers was higher than that of CRP markers among patients hospitalized for suspected bacterial infections. In previous studies, PCT was selected to better discriminate infections from general inflammation (Fluri et al. 2012), and as an early marker for sepsis (McGrane et al. 2011). Elevated PCT concentrations appear to be a promising indicator of sepsis in newly admitted, critically ill patients capable of complementing clinical signs and routine laboratory parameters suggestive of severe infection (Harbarth et al. 2001).
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Levels of PCT were strongly associated with stroke severity in this sample. A severe stroke per se implicates a poor outcome; it is not surprising that PCT is also associated with poor outcome. Because PCT remained independently associated with outcome even after adjusting for stroke severity, however, it seems that this marker may provide additional general prognostic information. PCT and CRP levels are related to the severity of organ dysfunction (Fuentes et al. 2009). Inflammatory mediators produced during critical illness (for example, tumor necrosis factor-a, PCT) initiate a systemic cascade of endothelial damage, thrombin formation, and microvascular compromise (Wheeler and Bernard 1999). However, the interpretation of the data must be done cautiously. Firstly, concentrations of inflammatory markers at the site of infarction may only partially be reflected by the inflammatory response in the peripheral blood. This study yielded no data regarding when and how long PCT is elevated in these patients. Secondly, the effects of circulating PCT on long-term clinical outcome were not included in the study protocol, so these relationships were not examined beyond the 90-day clinical outcome. Thirdly, PCT was measured only at one time point (at admission). Serial measurements of PCT were not available because this was not considered during the planning of the epidemiological cohort that this study arises from. Therefore, our measurement was not able to reflect potentially dynamic changes of PCT level. Further studies are needed to assess how PCT levels change across time after stroke and whether levels drawn at later points provide improved prognostic information. These studies need to be large, involve multiple centers, and provide statistical confirmation of incremental value of these markers beyond that provided by potential confounding risk factors before inflammatory biomarkers could be considered as part of the routine clinical evaluation of patients with stroke.
Conclusions Despite its inherent limitations, we confirmed that PCT was an independent prognostic marker of functional outcome in Chinese patients with AIS. We recommend that further studies should be carried out with respect to the mechanism between increased PCT levels and poor outcome. If it is possible to elucidate this, the prognosis of Chinese patients with stroke might be improved. Acknowledgments We also express our gratitude to all the patients who participated in this study, and thereby made this work possible. Conflict of interest The authors have no relevant potential conflicts of interest to declare. Funding
The author(s) received no specific funding for this work.
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