Inflammatory and stress markers predicting pneumonia, outcome, and etiology in patients with stroke: Biomarkers for predicting pneumonia, functional outcome, and death after stroke

Biomarkers to improve functional outcome prediction after ischemic stroke: Results from the SICFAIL, STRAWINSKI, and PREDICT studies

BACKGROUND AND AIMS

Acute ischemic stroke (AIS) outcome prognostication remains challenging despite available prognostic models. We investigated whether a biomarker panel improves the predictive performance of established prognostic scores.

METHODS

We investigated the improvement in discrimination, calibration, and overall performance by adding five biomarkers (procalcitonin, copeptin, cortisol, mid-regional pro-atrial natriuretic peptide (MR-proANP), and N-terminal pro-B-type natriuretic peptide (NT-proBNP)) to the Acute Stroke Registry and Analysis of Lausanne (ASTRAL) and age/NIHSS scores using data from two prospective cohort studies (SICFAIL, PREDICT) and one clinical trial (STRAWINSKI). Poor outcome was defined as mRS > 2 at 12 (SICFAIL, derivation dataset) or 3 months (PREDICT/STRAWINSKI, pooled external validation dataset).

RESULTS

Among 412 SICFAIL participants (median age 70 years, quartiles 59-78; 63% male; median NIHSS score 3, quartiles 1-5), 29% had a poor outcome. Area under the curve of the ASTRAL and age/NIHSS were 0.76 (95% CI 0.71-0.81) and 0.77 (95% CI 0.73-0.82), respectively. Copeptin (0.79, 95% CI 0.74-0.84), NT-proBNP (0.80, 95% CI 0.76-0.84), and MR-proANP (0.79, 95% CI 0.75-0.84) significantly improved ASTRAL score's discrimination, calibration, and overall performance. Copeptin improved age/NIHSS model's discrimination, copeptin, MR-proANP, and NT-proBNP improved its calibration and overall performance. In the validation dataset (450 patients, median age 73 years, quartiles 66-81; 54% men; median NIHSS score 8, quartiles 3-14), copeptin was independently associated with various definitions of poor outcome and also mortality. Copeptin did not increase model's discrimination but it did improve calibration and overall model performance.

DISCUSSION

Copeptin, NT-proBNP, and MR-proANP improved modest but consistently the predictive performance of established prognostic scores in patients with mild AIS. Copeptin was most consistently associated with poor outcome in patients with moderate to severe AIS, although its added prognostic value was less obvious.

Development and validation of a machine learning-based prognostic risk stratification model for acute ischemic stroke

Acute ischemic stroke (AIS) is a most prevalent cause of serious long-term disability worldwide. Accurate prediction of stroke prognosis is highly valuable for effective intervention and treatment. As such, the present retrospective study aims to provide a reliable machine learning-based model for prognosis prediction in AIS patients. Data from AIS patients were collected retrospectively from the Second Affiliated Hospital of Xuzhou Medical University between August 2017 and July 2019. Independent prognostic factors were identified by univariate and multivariate logistic analysis and used to develop machine learning (ML) models. The ML model performance was assessed by area under the receiver operating characteristic curve (AUC) and radar plot. Shapley Additive explanations (SHAP) values were used to interpret the importance of all features included in the predictive model. A total of 677 AIS patients were included in the present study. Poor prognosis was observed in 209 patients (30.9%). Six variables, including neuron specific enolase (NSE), homocysteine (HCY), S-100β, dysphagia, C-reactive protein (CRP), and anticoagulation were included to establish ML models. Six different ML algorithms were tested, and Random Forest model was selected as the final predictive model with the greatest AUC of 0.908. Moreover, according to SHAP results, NSE impacted the predictive model the most, followed by HCY, S-100β, dysphagia, CRP and anticoagulation. Based on the RF model, an online tool was constructed to predict the prognosis of AIS patients and assist clinicians in optimizing patient treatment. The present study revealed that NSE, HCY, CRP, S-100β, anticoagulation, and dysphagia were important factors for poor prognosis in AIS patients. ML algorithms were used to develop predictive models for predicting the prognosis of AIS patients, with the RF model presenting the optimal performance.

Limited Link of Common Blood Parameters with Tinnitus

Background: Tinnitus severity is generally assessed by psychometric and audiological instruments. However, no objective measure exists to evaluate the subjective discomfort and suffering caused by this hearing phenomenon. The objective of this work was to determine the possible blood parameters for diagnostics and therapy. Methods: We measured tinnitus distress by using the Tinnitus Questionnaire (TQ) and collected tinnitus-related audiological measures, namely the hearing threshold (HT), tinnitus loudness (TL), and sensation level (SL, i.e., the tinnitus loudness/hearing threshold at a tinnitus frequency). Blood samples were taken from 200 outpatients of the Tinnitus Centre of the Charité, and 46 routine blood count parameters were examined. The possible interactions were determined by (robust) linear models. Results: Tinnitus distress and audiological measurements were largely uncorrelated but could partly be predicted by selected blood parameters. First, the erythrocyte counts predicted tinnitus distress to a small extent. Second, the levels of vitamin D3 explained about 6% of tinnitus loudness and, age-dependently, the hearing threshold variability. Last, the levels of uric acid explained about 5% of the sensation level variability. Conclusions: Tinnitus is a multidimensional phenomenon. The marginal influences of blood markers suggest the possible roles of inflammation and oxidative stress produced by psychological or somatic burdens. Clinically, a vitamin D substitution (in older patients) might have a hearing-protective effect.

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.

Galectin-3 is associated with the functional outcome and mortality in stroke patients: A systematic review and meta-analysis

Introduction

There is still a lack of sensitive predictive tools for stroke outcomes. High galectin-3 concentration is associated with an increased risk of stroke. This study investigated the relationship between blood galectin-3 levels and stroke prognosis.

Methods

The PubMed, EMBASE, and Cochrane Library databases were searched as of May 2021. Data from eligible studies on the relationship between galectin-3 and stroke prognosis were extracted for the meta-analysis.

Results

The outcomes included the modified Rankin Scale (mRS), mortality rate, and prognostic accuracy of galectin-3 on mRS after stroke. Odds ratio (OR) and 95% CI were used to assess the association between galectin-3 and the prognostic outcomes. Subgroup analysis based on the study design was performed to evaluate the correlation of galectin-3 with mRS and mortality. A random-effects model was adopted for this meta-analysis. A total of 5 studies involving 3607 stroke patients were included. Higher serum galectin-3 level was associated with mRS (OR [95% CI]: 2.02 [1.08, 3.77]) and mortality (OR [95% CI]: 2.17 [1.17, 4.02]) after stroke. Subgroup analysis revealed a similar relationship between galectin-3 and mRS for both prospective and retrospective studies. There were no associations between galectin-3 level and mortality rate in prospective studies. Galectin-3 had a good predictive ability on mRS after stroke (AUC: 0.88, 95% CI:0.85, 0.91).

Conclusion

Elevated blood galectin-3 levels were associated with prognostic outcomes after stroke, including functional outcome mRS and mortality rate. Moreover, galectin-3 had a good predictive ability for the prognosis of stroke.

The Role of Arginine-Vasopressin in Stroke and the Potential Use of Arginine-Vasopressin Type 1 Receptor Antagonists in Stroke Therapy: A Narrative Review

Stroke is a life-threatening condition in which accurate diagnoses and timely treatment are critical for successful neurological recovery. The current acute treatment strategies, particularly non-invasive interventions, are limited, thus urging the need for novel therapeutical targets. Arginine vasopressin (AVP) receptor antagonists are emerging as potential targets to treat edema formation and subsequent elevation in intracranial pressure, both significant causes of mortality in acute stroke. Here, we summarize the current knowledge on the mechanisms leading to AVP hyperexcretion in acute stroke and the subsequent secondary neuropathological responses. Furthermore, we discuss the work supporting the predictive value of measuring copeptin, a surrogate marker of AVP in stroke patients, followed by a review of the experimental evidence suggesting AVP receptor antagonists in stroke therapy. As we highlight throughout the narrative, critical gaps in the literature exist and indicate the need for further research to understand better AVP mechanisms in stroke. Likewise, there are advantages and limitations in using copeptin as a prognostic tool, and the translation of findings from experimental animal models to clinical settings has its challenges. Still, monitoring AVP levels and using AVP receptor antagonists as an add-on therapeutic intervention are potential promises in clinical applications to alleviate stroke neurological consequences.

Copeptin Implementation on Stroke Prognosis

Predicting functional outcome following stroke is considered to be of key importance in an attempt to optimize overall stroke care. Although clinical prognostic tools have been widely implemented, optimal blood biomarkers might be able to yield additional information regarding each stroke survivor's propensity for recovery. Copeptin seems to have interesting prognostic potential poststroke. The present review aims to explore the prognostic significance of copeptin in stroke patients. Literature research of two databases (MEDLINE and Scopus) was conducted to trace all relevant studies published between 16 February 2012 and 16 February 2022 that focused on the utility of copeptin as a prognostic marker in acute stroke setting. 25 studies have been identified and included in the present review. The predictive ability of copeptin regarding both functional outcome and mortality appears to be in the range of established clinical variables, thus highlighting the added value of copeptin evaluation in stroke management. Apart from acute ischemic stroke, the discriminatory accuracy of the biomarker was also demonstrated among patients with transient ischemic attack, intracerebral hemorrhage, and subarachnoid hemorrhage. Overall, copeptin represents a powerful prognostic tool, the clinical implementation of which is expected to significantly facilitate the individualized management of stroke patients.

Study protocol of Branch Atheromatous Disease-related stroke (BAD-study): a multicenter prospective cohort study

BACKGROUND

As a meaningful subtype of ischemic stroke in Asians, Branch atheromatous disease (BAD)-related stroke is associated with high early neurological deterioration (END) and disability, but is understudied and without recommended therapy. The mechanism of END still remains unclear. Branch atheromatous disease-related stroke study (BAD-study) therefore aims to investigate demographic, clinical and radiological features, and prognosis of BAD-related stroke in Chinese patients.

METHODS/DESIGN

BAD-study is a nationwide, multicenter, consecutive, prospective, observational cohort study enrolling patients aged 18-80 years with BAD-related stroke within 72 h after symptom onset. Initial clinical data, laboratory tests, and imaging data are collected via structured case report form, and follow-ups will be performed at 7 days, 30 days, 90 days, 6 months and 12 months after enrollment. The primary outcome is the score on modified Rankin Scale at 90-day follow-up with single-blinded assessment. Secondary outcomes include END within 7 days, and National institute of health stroke scale score, Barthel index, cerebrovascular events, major bleeding complications, and all-cause mortality during 90-day follow-up. Characteristics of penetrating and parent artery will be assessed by high-resolution magnetic resonance imaging combined with other imaging techniques.

DISCUSSION

BAD-study can provide demographic, clinical, radiological, and prognostic characteristics of BAD-related stroke, and thereby potentially figure out the vascular mechanism of early neurological deterioration and optimize therapy strategy with the aid of advanced imaging technique. Baseline data and evidence will also be generated for randomized controlled trials on BAD-related stroke in the future.

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.

Hypersensitive C-reactive protein-albumin ratio is associated with stroke-associated pneumonia and early clinical outcomes in patients with acute ischemic stroke

OBJECTIVES

We aimed to explore the association between the baseline hypersensitive C-reactive protein-albumin ratio (CAR) and stroke-associated pneumonia (SAP) during hospitalization and the short-term prognosis in patients with acute ischemic stroke (AIS).

METHODS

We enrolled 766 patients with AIS and collected their admission baseline characteristics, including their National Institutes of Health Stroke Scale score, CAR, age, atrial fibrillation, dysphagia, sex, stroke severity (A² DS² ) score, and other information. The occurrence of SAP within 7 days after stroke, length of hospital stay, and physical condition at discharge were also recorded. The patients' Modified Rankin Scale (mRS) scores and mortality 3 months after AIS were further evaluated at follow-up. All patients were divided into four groups based on the quartiles of the admission CAR (Q1 <1.3, Q2 1.3-3.7, Q3 3.7-9.3, Q4 ≥9.3).

RESULTS

During hospitalization, 92 (11.9%) patients were diagnosed with SAP. The patients with SAP had a higher CAR than the non-SAP patients (p < .001). In the multivariate-adjusted model, the patients in the Q3 and Q4 groups had a higher SAP risk (aOR was 5.21 and 17.72, p-trend < .001) than those in the lowest quartile. The area under the curve for the CAR's ability to predict SAP was 0.810 in the receiver operating characteristic curve analysis and had a similar predictive efficacy as the A² DS²  score (p <.05). The length of stay in the SAP group was almost the same as that in the non-SAP group, but the clinical outcomes were worse at discharge and at the 3-month follow-up in the SAP group. In addition, the patients in the higher CAR quartiles at admission were more likely to have poorer clinical outcomes.

CONCLUSIONS

Patients with AIS with a high CAR at admission are more likely to develop SAP during hospitalization and have poor short-term clinical outcomes. These findings might help to timely identify patients at high risk of SAP and provide a basis for further research on prophylactic antibiotic therapy.

Peripheral Organ Injury After Stroke

Stroke is a disease with high incidence, mortality and disability rates. It is also the main cause of adult disability in developed countries. Stroke is often caused by small emboli on the inner wall of the blood vessels supplying the brain, which can lead to arterial embolism, and can also be caused by cerebrovascular or thrombotic bleeding. With the exception of recombinant tissue plasminogen activator (rt-PA), which is a thrombolytic drug used to recanalize the occluded artery, most treatments have been demonstrated to be ineffective. Stroke can also induce peripheral organ damage. Most stroke patients have different degrees of injury to one or more organs, including the lung, heart, kidney, spleen, gastrointestinal tract and so on. In the acute phase of stroke, severe inflammation occurs in the brain, but there is strong immunosuppression in the peripheral organs, which greatly increases the risk of peripheral organ infection and aggravates organ damage. Nonneurological complications of stroke can affect treatment and prognosis, may cause serious short-term and long-term consequences and are associated with prolonged hospitalization and increased mortality. Many of these complications are preventable, and their adverse effects can be effectively mitigated by early detection and appropriate treatment with various medical measures. This article reviews the pathophysiological mechanism, clinical manifestations and treatment of peripheral organ injury after stroke.

Serum Calcium Levels and in-Hospital Infection Risk in Patients with Acute Ischemic Stroke

Purpose

Stroke-associated infection (SAI) is one of the most common post-stroke complications, which may lead to a relatively poor prognosis. This study aims to explore the potential relationship between serum calcium levels and SAI.

Patients and Methods

This is a cross-sectional study involving 395 participants. SAI is a term that covers stroke-associated pneumonia (SAP), urinary tract infection (UTI), as well as other infections diagnosed during the first week after a stroke. Serum calcium levels were measured within 24 hrs of admission. To determine the association of serum calcium levels with the SAI, logistic regression models were calculated. An adjusted spline regression model was used to further confirm the relationship between the two.

Results

Among the total patients, SAI occurred in 107 (27.1%) patients. Serum calcium was associated with SAI and was independent of the SAI risk factors for age, admission NIHSS score, and intravascular therapy [adjusted OR 0.040 (95% CI = 0.005-0.291), p = 0.002]. Remarkably, this trend applies predominantly to serum calcium levels less than 2.25mmol/L (p= 0.005 for linearity).

Conclusion

Serum calcium levels are associated with the risk of SAI, when serum calcium is below normal (2.25mmol/L), the risk of SAI increases as serum calcium levels decrease.

Immune Pathways in Etiology, Acute Phase, and Chronic Sequelae of Ischemic Stroke

Inflammation and immune mechanisms are crucially involved in the pathophysiology of the development, acute damage cascades, and chronic course after ischemic stroke. Atherosclerosis is an inflammatory disease, and, in addition to classical risk factors, maladaptive immune mechanisms lead to an increased risk of stroke. Accordingly, individuals with signs of inflammation or corresponding biomarkers have an increased risk of stroke. Anti-inflammatory drugs, such as IL (interleukin)-1β blockers, methotrexate, or colchicine, represent attractive treatment strategies to prevent vascular events and stroke. Lately, the COVID-19 pandemic shows a clear association between SARS-CoV2 infections and increased risk of cerebrovascular events. Furthermore, mechanisms of both innate and adaptive immune systems influence cerebral damage cascades after ischemic stroke. Neutrophils, monocytes, and microglia, as well as T and B lymphocytes each play complex interdependent roles that synergize to remove dead tissue but also can cause bystander injury to intact brain cells and generate maladaptive chronic inflammation. Chronic systemic inflammation and comorbid infections may unfavorably influence both outcome after stroke and recurrence risk for further stroke. In addition, stroke triggers specific immune depression, which in turn can promote infections. Recent research is now increasingly addressing the question of the extent to which immune mechanisms may influence long-term outcome after stroke and, in particular, cause specific complications such as poststroke dementia or even poststroke depression.

Stroke Core Volume Weighs More Than Recanalization Time for Predicting Outcome in Large Vessel Occlusion Recanalized Within 6 h of Symptoms Onset

Introduction

Current guidelines suggest that perfusion imaging should only be performed > 6 h after symptom onset. Pathophysiologically, brain perfusion should matter whatever the elapsed time. We aimed to compare relative contribution of recanalization time and stroke core volume in predicting functional outcome in patients treated by endovascular thrombectomy within 6-h of stroke-onset.

Methods

Consecutive patients presenting between January 2015 and June 2021 with (i) an acute ischaemic stroke due to an anterior proximal occlusion, (ii) a successful thrombectomy (TICI >2a) within 6-h of symptom-onset and (iii) CT perfusion imaging were included. Core stroke volume was automatically computed using RAPID software. Two linear regression models were built that included in the null hypothesis the pre-treatment NIHSS score and the hypoperfusion volume (Tmax > 6 s) as confounding variables and 24 h post-recanalization NIHSS and 90 days mRS as outcome variables. Time to recanalization was used as covariate in one model and stroke core volume as covariate in the other.

Results

From a total of 377 thrombectomies, 94 matched selection criteria. The Model null hypothesis explained 37% of the variability for 24 h post-recanalization NIHSS and 42% of the variability for 90 days MRS. The core volume as covariate increased outcome variability prediction to 57 and 56%, respectively. Time to recanalization as covariate marginally increased outcome variability prediction from 37 and 34% to 40 and 42.6%, respectively.

Conclusion

Core stroke volume better explains outcome variability in comparison to the time to recanalization in anterior large vessel occlusion stroke with successful thrombectomy done within 6 h of symptoms onset. Still, a large part of outcome variability prediction fails to be explained by the usual predictors.

Predictors of stroke favorable functional outcome in Guinea, results from the Conakry stroke registry

Low- to middle-income countries (LMICs) now bear most of the stroke burden. In LMICs, stroke epidemiology and health care systems are different from HICs. Therefore, a high-income country (HIC)-based predictive model may not correspond to the LMIC stroke context. Identify the impact of modifiable variables in acute stroke management in Conakry, Guinea as potential predictors of favorable stroke outcome. Data were extracted from the Conakry stroke registry that includes 1018 patients. A logistic regression model was built to predict favorable stroke outcomes, defined as mRS 0–2. Age, admission NIHSS score, mean arterial blood pressure and capillary glycemia were chosen as covariates. Delay to brain CT imaging under 24 h from symptom onset, fever, presence of sores and abnormal lung auscultation were included as factors. NIHSS score on admission, age and ischemic stroke were included in the null model as nuisance parameters to determine the contribution of modifiable variables to predict stroke favorable outcome. Lower admission NIHSS, brain CT imaging within 24 h of symptoms onset and lower mean arterial blood pressure emerged as a significant positive predictors of favorable stroke outcome with respective odd ratios (OR) of 1.35 [1.28–1.43], 2.1 [1.16–3.8] and 1.01 [1.01–1.04]. The presence of fever or sores impacted negatively stroke favorable outcomes with OR of 0.3 [0.1–0.85] and 0.25 [0.14–0.45]. The area under receiver operating characteristic curves (AUC) of the model was 0.86. This model explained 44.5% of the variability of the favorable stroke outcome with 10.2% of the variability explained by the modifiable variables when admission NIHSS, and ischemic stroke were included in the null model as nuisance parameter. In the Conakry stroke registry, using a logistic regression to predict stroke favorable outcome, five variables that led to an AUC of 0.86: admission NIHSS, early brain CT imaging, fever, sores and mean blood pressure. This paves the way for future public health interventions to test whether modulating amendable variables leads to increased favorable stroke outcomes in LMICs.

A Combined Clinical and Serum Biomarker-Based Approach May Allow Early Differentiation Between Patients With Minor Stroke and Transient Ischemic Attack as Well as Mid-term Prognostication

Background: Early differentiation between transient ischemic attack (TIA) and minor ischemic stroke (MIS) impacts on the patient's individual diagnostic work-up and treatment. Furthermore, estimations regarding persisting impairments after MIS are essential to guide rehabilitation programs. This study evaluated a combined clinical- and serum biomarker-based approach for the differentiation between TIA and MIS as well as the mid-term prognostication of the functional outcome, which is applicable within the first 24 h after symptom onset. Methods: Prospectively collected data were used for a retrospective analysis including the neurological deficit at admission (National Institutes of Health Stroke Scale, NIHSS) and the following serum biomarkers covering different pathophysiological aspects of stroke: Coagulation (fibrinogen, antithrombin), inflammation (C reactive protein), neuronal damage in the cellular [neuron specific enolase], and the extracellular compartment [matrix metalloproteinase-9, hyaluronic acid]. Further, cerebral magnetic resonance imaging was performed at baseline and day 7, while functional outcome was evaluated with the modified Rankin Scale (mRS) after 3, 6, and 12 months. Results: Based on data from 96 patients (age 64 ± 14 years), 23 TIA patients (NIHSS 0.6 ± 1.1) were compared with 73 MIS patients (NIHSS 2.4 ± 2.0). In a binary logistic regression analysis, the combination of NIHSS and serum biomarkers differentiated MIS from TIA with a sensitivity of 91.8% and a specificity of 60.9% [area under the curve (AUC) 0.84]. In patients with NIHSS 0 at admission, this panel resulted in a still acceptable sensitivity of 81.3% (specificity 71.4%, AUC 0.69) for the differentiation between MIS (n = 16) and TIA (n = 14). By adding age, remarkable sensitivities of 98.4, 100, and 98.2% for the prediction of an excellent outcome (mRS 0 or 1) were achieved with respect to time points investigated within the 1-year follow-up. However, the specificity was moderate and decreased over time (83.3, 70, 58.3%; AUC 0.96, 0.92, 0.91). Conclusion: This pilot study provides evidence that the NIHSS combined with selected serum biomarkers covering pathophysiological aspects of stroke may represent a useful tool to differentiate between MIS and TIA within 24 h after symptom onset. Further, this approach may accurately predict the mid-term outcome in minor stroke patients, which might help to allocate rehabilitative resources.

Copeptin and Stress

Vasopressin (AVP) and copeptin are released in equimolar amounts from the same precursor. Due to its molecular stability and countless advantages as compared with AVP, copeptin perfectly mirrors AVP presence and has progressively emerged as a reliable marker of vasopressinergic activation in response to osmotic and hemodynamic stimuli in clinical practice. Moreover, evidence highlighting the prognostic potential of copeptin in several acute diseases, where the activation of the AVP system is primarily linked to stress, as well as in psychologically stressful conditions, has progressively emerged. Furthermore, organic stressors induce a rise in copeptin levels which, although non-specific, is unrelated to plasma osmolality but proportional to their magnitude: suggesting disease severity, copeptin proved to be a reliable prognostic biomarker in acute conditions, such as sepsis, early post-surgical period, cardiovascular, cerebrovascular or pulmonary diseases, and even in critical settings. Evidence on this topic will be briefly discussed in this article.

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.

Lipopolysaccharide binding protein and sCD14 as risk markers of stroke-associated pneumonia

To determine the utility of lipopolysaccharide binding protein (LBP) and soluble CD14 (sCD14) as risk markers of stroke-associated pneumonia (SAP). We included 331 stroke patients. The plasma levels of LBP (median: 19.4 vs 15.3 μg/mL, P < 0.01) and sCD14 (median: 1.5 vs 1.4 μg/mL, P = 0.04) were elevated in SAP. In multivariate analysis, a higher level of LBP (OR: 1.09, 95%CI: 1.05-1.13), but not sCD14 (OR: 2.16, 0.94-4.97), was associated with SAP. The addition of LBP or sCD14 to the clinical model did not improve its discriminatory ability. Our results suggest the modest value of studied biomarkers for SAP prediction.

Procalcitonin related to stroke-associated pneumonia and clinical outcomes of acute ischemic stroke after IV rt-PA treatment

To investigate the possible relationship between procalcitonin (PCT) and stroke-associated pneumonia (SAP) as well as clinical outcomes after recombinant tissue plasminogen activator (rt-PA) treatment of AIS. From June 2015 to December 2019, 173 consecutive patients with AIS after IV rt-PA treatment were prospectively enrolled. Serum PCT concentrations were measured after admission. Multivariate logistic regression analysis was used to examine the potential risk factors of SAP, poor outcome and mortality. Of the 173 patients, 49 (28.3%) participants were identified with SAP, 87 (50.3%) with poor outcome, and 28 (16.2%) with mortality. Multivariate logistic regression analysis demonstrated that patients with PCT in the second [odds ratio (OR) 4.413; 95% confidence interval (CI) 1.331-14.634; P = 0.015] and third tertile (OR 10.958; 95% CI 3.524-34.071; P < 0.001) were more likely to have SAP compared with the first tertile. Besides, PCT was an independent predictor of 3-month poor outcome (OR 3.219, 95% CI 1.291-8.028, P = 0.007) and mortality (OR 7.538, 95% CI 2.061-27.564, P = 0.002). In receiver operating characteristic (ROC) curve analysis, the diagnostic and prognostic accuracy of PCT was higher than hs-CRP. This study demonstrated that PCT was a reliable diagnostic and prognostic biomarker of SAP and poor clinical outcomes in Chinese AIS patients after IV rt-PA treatment.

Infection as a Stroke Risk Factor and Determinant of Outcome After Stroke

Understanding the relationship between infection and stroke has taken on new urgency in the era of the coronavirus disease 2019 (COVID-19) pandemic. This association is not a new concept, as several infections have long been recognized to contribute to stroke risk. The association of infection and stroke is also bidirectional. Although infection can lead to stroke, stroke also induces immune suppression which increases risk of infection. Apart from their short-term effects, emerging evidence suggests that poststroke immune changes may also adversely affect long-term cognitive outcomes in patients with stroke, increasing the risk of poststroke neurodegeneration and dementia. Infections at the time of stroke may also increase immune dysregulation after the stroke, further exacerbating the risk of cognitive decline. This review will cover the role of acute infections, including respiratory infections such as COVID-19, as a trigger for stroke; the role of infectious burden, or the cumulative number of infections throughout life, as a contributor to long-term risk of atherosclerotic disease and stroke; immune dysregulation after stroke and its effect on the risk of stroke-associated infection; and the impact of infection at the time of a stroke on the immune reaction to brain injury and subsequent long-term cognitive and functional outcomes. Finally, we will present a model to conceptualize the many relationships among chronic and acute infections and their short- and long-term neurological consequences. This model will suggest several directions for future research.

Long-Term Outcomes in Patients with Stroke after in-Hospital Treatment-Study Protocol of the Prospective Stroke Cohort Augsburg (SCHANA Study)

INTRODUCTION

In Germany, stroke is the third leading cause of death, with more than 60,000 fatalities out of approximately 260,000 cases (first-ever and recurrent strokes) each year. So far, there are only a few long-term studies investigating determinants of the natural course of the disease, especially in the era of mechanical thrombectomy.

MATERIALS AND METHODS

The prospective single-center stroke cohort Augsburg (SCHANA) study will include about 1000 patients treated for stroke in the University Hospital of Augsburg. Patients aged 18 years or older with a confirmed diagnosis of ischemic or hemorrhagic stroke are included in the study. Information on demographic characteristics, onset of symptoms, etiologic factors, comorbidities, quality of life, invasive and non-invasive treatment, complications, and laboratory parameters are collected during a personal interview conducted during the patients' hospital stay and via a medical chart review. About 30 mL of blood is collected from each patient, and after processing and aliquoting, all blood specimens are frozen at -80° C. The study participants will be followed-up via postal questionnaires at three and 12 months after discharge from the hospital. Furthermore, mortality follow-ups will be conducted. Cox-regression analysis will be used to estimate relative risks.

CONCLUSION

The SCHANA study will generate comprehensive data on the long-term course of the disease. In addition to the main outcomes, recurrent events and survival, patient-oriented outcomes such as health-related quality of life and depression are the focus of the study.