Immunological biomarkers improve the accuracy of clinical risk models of infection in the acute phase of ischemic stroke

Evaluation of a novel scoring system based on thrombosis and inflammation for predicting stroke-associated pneumonia: A retrospective cohort study

Background

Inflammation and thrombosis are involved in the development of stroke-associated pneumonia (SAP). Our aim was to evaluate the predictive value of a novel, simplified, thrombo-inflammatory prognostic score (TIPS) that combines both inflammatory and thrombus biomarkers in the early phase of ischemic stroke (IS).

Methods

The study population consisted of 897 patients with a first diagnosis of IS admitted to the emergency department of five tertiary hospitals in China. Of these, the data from 70% of patients was randomly selected to derive the model and the other 30% for model validation. A TIPS of “2” was indicative of high inflammation and thrombosis biomarkers and “1” of one biomarker, with “0” indicative of absence of biomarkers. Multivariate logistic regression analyses were used to identify the association between TIPS and SAP.

Results

The TIPS was an independent predictor of SAP and 90-day mortality, with the incidence of SAP being significantly higher for patients with a high TIPS. The TIPS provided superior predictive value for SAP than clinical scores (A2DS2) and biomarkers currently used in practice, for both the derivation and validation sets. Mediation analysis revealed that TIPS provided a predictive value than either thrombotic (NLR) and inflammatory (D-dimer) biomarkers alone.

Conclusion

The TIPS score may be a useful tool for early identification of patients at high-risk for SAP after IS.

Circulating Inflammatory Biomarkers in Early Prediction of Stroke-Associated Infections

(1) Background: Patients with acute ischaemic stroke (AIS) are at high risk for stroke-associated infections (SAIs). We hypothesised that increased concentrations of systemic inflammation markers predict SAIs and unfavourable outcomes; (2) Methods: In 223 patients with AIS, blood samples were taken at ≤24 h, 3 d and 7d after a stroke, to determine IL-6, IL-10, CRP and LBP. The outcome was assessed using the modified Rankin Scale at 90 d. Patients were thoroughly examined regarding the development of SAIs; (3) Results: 47 patients developed SAIs, including 15 lower respiratory tract infections (LRTIs). IL-6 and LBP at 24 h differed, between patients with and without SAIs (IL-6: p < 0.001; LBP: p = 0.042). However, these associations could not be confirmed after adjustment for age, white blood cell count, reduced consciousness and NIHSS. When considering the subgroup of LRTIs, in patients who presented early (≤12 h after stroke, n = 139), IL-6 was independently associated with LRTIs (OR: 1.073, 95% CI: 1.002−1.148). The ROC-analysis for prediction of LRTIs showed an AUC of 0.918 for the combination of IL-6 and clinical factors; (4) Conclusions: Blood biomarkers were not predictive for total SAIs. At early stages, IL-6 was independently associated with outcome-relevant LRTIs. Further studies need to clarify the use of biochemical markers to identify patients prone to SAIs.

Stroke-induced immunosuppression: implications for the prevention and prediction of post-stroke infections

Stroke produces a powerful inflammatory cascade in the brain, but also a suppression of the peripheral immune system, which is also called stroke-induced immunosuppression (SIIS). The main processes that lead to SIIS are a shift from a lymphocyte phenotype T-helper (Th) 1 to a Th2 phenotype, a decrease of the lymphocyte counts and NK cells in the blood and spleen, and an impairment of the defense mechanisms of neutrophils and monocytes. The direct clinical consequence of SIIS in stroke patients is an increased susceptibility to stroke-associated infections, which is enhanced by clinical factors like dysphagia. Among these infections, stroke-associated pneumonia (SAP) is the one that accounts for the highest impact on stroke outcome, so research is focused on its early diagnosis and prevention. Biomarkers indicating modifications in SIIS pathways could have an important role in the early prediction of SAP, but currently, there are no individual biomarkers or panels of biomarkers that are accurate enough to be translated to clinical practice. Similarly, there is still no efficient therapy to prevent the onset of SAP, and clinical trials testing prophylactic antibiotic treatment and β-blockers have failed. However, local immunomodulation could open up a new research opportunity to find a preventive therapy for SAP. Recent studies have focused on the pulmonary immune changes that could be caused by stroke similarly to other acquired brain injuries. Some of the traits observed in animal models of stroke include lung edema and inflammation, as well as inflammation of the bronchoalveolar lavage fluid.

Usefulness of the Neutrophil-to-Lymphocyte Ratio as a Predictor of Pneumonia and Urinary Tract Infection Within the First Week After Acute Ischemic Stroke

Background: A high Neutrophil-to-Lymphocyte ratio (NLR) in patients with acute ischemic stroke (AIS) has been associated with post-stroke infections, but it's role as an early predictive biomarker for post-stroke pneumonia (PSP) and urinary tract infection (UTI) is not clear.

Aim: To investigate the usefulness of NLR obtained within 24 h after AIS for predicting PSP and UTI in the first week.

Methods: Clinical and laboratory data were retrieved from the University Hospital Brussels stroke database/electronic record system. Patients were divided into those who developed PSP or UTI within the first week after stroke onset and those who didn't. Receiver operating characteristics (ROC) curves and logistic regression analysis were used to identify independent predictors.

Results: Five hundred and fourteen patients were included, of which 15.4% (n = 79) developed PSP and 22% (n = 115) UTI. In univariate analysis, NLR was significantly higher in patients who developed PSP (4.1 vs. 2.8, p < 0.001) but not in those who developed UTI (3.3 vs. 2.9, p = 0.074). Multiple logistic regression analysis for PSP showed that NLR, male gender, dysphagia, and stroke severity measured by the National Institutes of Health Stroke Scale (NIHSS), were independent predictors of PSP. For NLR alone, the area under the curve (AUC) in the ROC curve was 0.66 (95% CI = 0.59–0.73). When combining NLR ≥ 4.7 with age >75 years, male gender, NIHSS > 7, and dysphagia, the AUC increased to 0.84 (95% CI = 0.79–0.89).

Conclusion: The NLR within 24 h after AIS appears to have no predictive value for post-stroke UTI, and is only a weak predictor for identifying patients at high risk for PSP. Its predictive value for PSP appears to be much stronger when incorporated in a prediction model including age, gender, NIHSS score, and dysphagia.

Cross-Reactivity as a Mechanism Linking Infections to Stroke

The relevance of infections as risk factor for cerebrovascular disease is being increasingly recognized. Nonetheless, the pathogenic link between the two entities remains poorly understood. Consistent with recent advances in medicine, the present work addresses the hypothesis that infection-induced immune responses may affect human proteins associated with stroke. Applying established procedures in bioinformatics, the pathogen antigens and the human proteins were searched for common sequences using pentapeptides as probes. The resulting data demonstrate massive peptide sharing between infectious pathogens-such as Chlamydia pneumoniae, Streptococcus pneumoniae, Tannerella forsythia, Haemophilus influenzae, Influenza A virus, and Cytomegalovirus-and human proteins related to risk of ischemic and hemorrhagic stroke. Moreover, the shared peptides are also evident in a number of epitopes experimentally proven immunopositive in the human host. The present findings suggest cross-reactivity as a potential mechanistic link between infections and stroke.

Sepsis biomarkers reprofiling to predict stroke-associated infections

We aimed to evaluate the usefulness of sepsis biomarkers to predict stroke-associated infections. Soluble triggering receptor expressed on myeloid cells-1 (sTREM-1), mid-regional pro-adrenomedullin (MR-proADM), presepsin (sCD14), and soluble urokinase-type plasminogen activator receptor (suPAR), were explored in 125 blood samples collected at different time-points. At baseline, MR-proADM was an independent predictor of infection [>0.94pg/mL, OR=3.63 (1.16-11.33), p=0.026], as well as suPAR at 24h [>2185.8pg/mL, OR=5.81 (1.05-32.26), p=0.044]. Both MR-proADM and suPAR were raised in patients with infections throughout the first week after stroke. These results are especially relevant for MR-proADM given its early elevation, which would allow early preventive interventions.

Blood/Brain Biomarkers of Inflammation After Stroke and Their Association With Outcome: From C-Reactive Protein to Damage-Associated Molecular Patterns

Stroke represents one of the most important causes of disability and death in developed countries. However, there is a lack of prognostic tools in clinical practice to monitor the neurological condition and predict the final outcome. Blood biomarkers have been proposed and studied in this indication; however, no biomarker is currently used in clinical practice. The stroke-related neuroinflammatory processes have been associated with a poor outcome in stroke, as well as with poststroke complications. In this review, we focus on the most studied blood biomarkers of this inflammatory processes, cytokines, and C-reactive protein, evaluating its association with outcome and complications in stroke through the literature, and performing a systematic review on the association of C-reactive protein and functional outcome after stroke. Globally, we identified uncertainty with regard to the association of the evaluated biomarkers with stroke outcome, with little added value on top of clinical predictors such as age or stroke severity, which makes its implementation unlikely in clinical practice for global outcome prediction. Regarding poststroke complications, despite being more practical scenarios in which to make medical decisions following a biomarker prediction, not many studies have been performed, although there are now some candidates for prediction of poststroke infections. Finally, as potential new candidates, we reviewed the pathophysiological actions of damage-associated molecular patterns as triggers of the neuroinflammatory cascade of stroke, and their possible use as biomarkers.

Ischemic stroke outcome: A review of the influence of post-stroke complications within the different scenarios of stroke care

Stroke remains one of the main causes of death and disability worldwide. The challenge of predicting stroke outcome has been traditionally assessed from a general point of view, where baseline non-modifiable factors such as age or stroke severity are considered the most relevant factors. However, after stroke occurrence, some specific complications such as hemorrhagic transformations or post stroke infections, which lead to a poor outcome, could be developed. An early prediction or identification of these circumstances, based on predictive models including clinical information, could be useful for physicians to individualize and improve stroke care. Furthermore, the addition of biological information such as blood biomarkers or genetic polymorphisms over these predictive models could improve their prognostic value. In this review, we focus on describing the different post-stroke complications that have an impact in short and long-term outcome across different time points in its natural history and on the clinical-biological information that might be useful in their prediction.

Neuroinflammatory biomarkers: From stroke diagnosis and prognosis to therapy

Stroke is the third leading cause of death in industrialized countries and one of the largest causes of permanent disability worldwide. Therapeutic options to fight stroke are still limited and the only approved drug is tissue-plasminogen activator (tPA) and/or mechanical thrombectomy. Post-stroke inflammation is well known to contribute to the expansion of the ischemic lesion, whereas its resolution stimulates tissue repair and neuroregeneration processes. As inflammation highly influences susceptibility of stroke patients to overcome the disease, there is an increasing need to develop new diagnostic, prognostic and therapeutic strategies for post-stroke inflammation. This review provides a brief overview of the contribution of the inflammatory mechanisms to the pathophysiology of stroke. It specially focuses on the role of inflammatory biomarkers to help predicting stroke patients' outcome since some of those biomarkers might turn out to be targets to be therapeutically altered overcoming the urgent need for the identification of potent drugs to modulate stroke-associated inflammation. This article is part of a Special Issue entitled: Neuro Inflammation edited by Helga E. de Vries and Markus Schwaninger.

Neuroendocrine hormones as prognostic biomarkers in the setting of acute stroke: overcoming the major hurdles

Stroke represents one of the major causes of disability and mortality worldwide and prediction of outcome represents a challenge for both clinicians and researchers. In the past years, many blood markers have been associated with stroke outcome but despite this evidence, no biomarker is routinely used in stroke management. In this review, we focus on markers of the neuroendocrine system, which represent potential candidates to be implemented in clinical practice. Moreover, we present a systematic review and literature-based meta-analysis for copeptin, a new biomarker of the hypothalamo-pituitary-adrenal axis that has shown additional predictive value over clinical information in a large prospective study. The meta-analysis of the included 7 studies, with more than 2000 patients, reinforced its association with poor outcome (pooled odds ratio: 2.474 [1.678-3.268]) and mortality (pooled OR: 2.569 [1.642-3.495]). We further review the current situation of the topic and next steps to implement these tools by clinicians.

The association of CHA2DS2-VASc score and blood biomarkers with ischemic stroke outcomes: the Belgrade stroke study

BACKGROUND

Many blood biomarkers have a positive association with stroke outcome, but adding blood biomarkers to the National Institutes of Health Stroke Scale (NIHSS) did not significantly improve its discriminatory ability. We investigated the association of the CHA2DS2-VASc score with unfavourable functional outcome (defined as a 30-day modified Rankin Scale [mRS] ≥ 3) in patients presenting with acute ischemic stroke (AIS), and examined whether the addition of blood biomarkers (troponin I [TnI], fibrinogen, C-reactive protein [CRP]) affects the model discriminatory ability.

METHODS

We conducted an observational single-centre study of consecutive patients with AIS. All patients were admitted to hospital within 24 hours from the neurological symptoms onset.

RESULTS

Of 240 patients (mean age 70.0 ± 8.9 years), unfavourable 30-day outcome occurred in 92 (38.3%). Patients with mRS ≥ 3 were older and more likely to have atrial fibrillation or other comorbidities (all p<0.001). They had higher levels of CRP, fibrinogen, TnI and higher CHA2DS2-VASc and CHADS2 scores (all p<0.05). The adjusted CHA2DS2-VASc score had excellent predictive ability for poor stroke outcome (c-statistic 0.982;95%CI,0.964-1.000, p<0.001). Whilst CRP had the highest sensitivity (83.7%), cardiac TnI was the most specific (97.3%) for prediction of poor stroke outcome (cut-off: >0.09 µg/L). Compared with each of these biomarkers, CHA2DS2-VASc score had significantly better predictive ability for poor stroke outcome (c-statistic for CRP, Fibrinogen and TnI was 0.853;95%CI,0.802-0.895, 0.848;95%CI,0.796-0.891, and 0.792;95%CI,0.736-0.842, all p<0.001, respectively, versus 0.932;95%CI,0.892-0.960, p<0.001 for the CHA2DS2-VASc, all p for the comparisons<0.01). There was no significant difference in the predictive ability of the CHA2DS2-VASc score vs. combinations of the CHA2DS2-VASc and TnI or TnI, fibrinogen and CRP (z statistic 0.369, p = 0.7119; integrated discrimination index 0.00801 and 0.00172, respectively, both p>0.05).

CONCLUSIONS

The CHA2DS2-VASc score alone reliably predicts 30-day unfavourable outcome of stroke. Adding blood biomarkers to the CHA2DS2-VASc score did not significantly increase the predictive ability of the model.

Is early clinical evidence of autonomic shift predictive of infection after aneurysmal subarachnoid hemorrhage

BACKGROUND

Autonomic shift (AS), characterized by increased sympathetic nervous system activation, has been implicated in neurologically mediated cardiopulmonary dysfunction and immunodepression after stroke. We investigated the prevalence of AS defined by readily available clinical parameters and determined the association of AS with subsequent infection in a cohort of patients with aneurysmal subarachnoid hemorrhage (aSAH).

METHODS

Data were obtained from a single-center cohort study of aSAH patients admitted from January 1, 2007, through April 1, 2012. AS was defined as at least 1 early (<72 hours) routine clinical marker of neurologically mediated cardiopulmonary dysfunction based on electrocardiogram, echocardiogram, cardiac enzymes, or neurogenic pulmonary edema. Multivariable logistic regression models were developed to evaluate the association between AS and subsequent infection after adjusting for other covariates.

RESULTS

A total of 167 patients were included in the analysis (mean age 56, 27% men). AS was seen in 66 of 167 patients (40%; 95% confidence interval [CI], 32%-47%), and infection was seen in 80 of 167 patients (48%; 95% CI, 40%-55%). AS was associated with subsequent infection on unadjusted analysis (odds ratio [OR] 2.11; 95% CI, 1.12-3.97); however, this association was no longer significant when adjusting for other predictors of infection (OR 1.36; 95% CI, .67-2.76). Age, clinical grade, and aneurysm location were all independent predictors of infection after aSAH.

CONCLUSIONS

We identified AS based on readily available clinical markers in 40% of patients with aSAH, though AS defined by these clinical criteria was not an independent predictor of infection. Additional studies may be warranted to determine the optimal definition of AS and the clinical significance of this finding.