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.

Background and Purpose: We evaluated whether stroke severity, functional outcome, and mortality are different in patients with ischemic stroke with or without coronavirus disease 2019 (COVID-19) infection. Methods: A prospective, observational, multicentre cohort study in Catalonia, Spain. Recruitment was consecutive from mid-March to mid-May 2020. Patients had an acute ischemic stroke within 48 hours and a previous modified Rankin Scale (mRS) score of 0 to 3. We collected demographic data, vascular risk factors, prior mRS score, National Institutes of Health Stroke Scale score, rate of reperfusion therapies, logistics, and metrics. Primary end point was functional outcome at 3 months. Favourable outcome was defined depending on the previous mRS score. Secondary outcome was mortality at 3 months. We performed mRS shift and multivariable analyses. Results: We evaluated 701 patients (mean age 72.3±13.3 years, 60.5% men) and 91 (13%) had COVID-19 infection. Median baseline National Institutes of Health Stroke Scale score was higher in patients with COVID-19 compared with patients without COVID-19 (8 [3–18] versus 6 [2–14], P =0.049). Proportion of patients with a favourable functional outcome was 33.7% in the COVID-19 and 47% in the non-COVID-19 group. However, after a multivariable logistic regression analysis, COVID-19 infection did not increase the probability of unfavourable functional outcome. Mortality rate was 39.3% among patients with COVID-19 and 16.1% in the non-COVID-19 group. In the multivariable logistic regression analysis, COVID-19 infection was a risk factor for mortality (hazard ratio, 3.14 [95% CI, 2.10–4.71]; P <0.001). Conclusions: Patients with ischemic stroke and COVID-19 infection have more severe strokes and a higher mortality than patients with stroke without COVID-19 infection. However, functional outcome is comparable in both groups.

Background and Purpose: Improving prehospital triage of large vessel occlusion (LVO) would reduce time to reperfusion therapies. We aimed to study early predictors of LVO in acute ischemic stroke to identify candidates for endovascular treatment. Methods: The Stroke-Chip was a prospective observational study conducted at 6 Stroke Centers in Catalonia. Blood samples were obtained in the first 6 hours from symptom onset of consecutive patients. Stroke severity was evaluated with National Institutes of Health Stroke Scale (NIHSS) and LVO was assessed. Independent association of multiple blood biomarkers with LVO was evaluated using logistic regression models adjusted by covariates. Sensitivity, specificity, and predictive values were assessed for NIHSS and the combination of NIHSS and selected serum biomarkers levels. Results: One thousand three hundred eight suspected strokes were enrolled for a 17-month period. LVO was not assessed in 131 patients. One thousand one hundred seventy-seven patients were selected for analysis (mean age 69.3 years, 56% men, median baseline NIHSS of 6, and median time to blood collection 2.5 hours). LVO was detected in 262 patients. LVO patients were older, had higher baseline NIHSS, history of atrial fibrillation, and lower time from stroke onset to admission. After logistic regression analysis, D-dimer remained an independent predictor of LVO (odds ratio, 1.59 [1.31–1.92]). Specificity and positive predictive value to exclude or detect LVO were higher when using combined D-dimer levels and NIHSS score assessment rather than NIHSS alone. Conclusions: Early D-dimer levels are an independent predictor of LVO and may be useful to better optimize prehospital patient transport to the appropriate stroke center.

We conducted a systematic review and individual participant data meta‐analysis to explore the role of C‐reactive protein (CRP) in early detection or prediction of post‐stroke infections. CRP, an acute‐phase reactant binds to the phosphocholine expressed on the surface of dead or dying cells and some bacteria, thereby activating complement and promoting phagocytosis by macrophages. We searched PubMed up to May‐2015 for studies measuring CRP in stroke and evaluating post‐stroke infections. Individual participants’ data were merged into a single database. CRP levels were standardized and divided into quartiles. Factors independently associated with post‐stroke infections were determined by logistic regression analysis and the additional predictive value of CRP was assessed by comparing areas under receiver operating characteristic curves and integrated discrimination improvement index. Data from seven studies including 699 patients were obtained. Standardized CRP levels were higher in patients with post‐stroke infections beyond 24 h. Standardized CRP levels in the fourth quartile were independently associated with infection in two different logistic regression models, model 1 [stroke severity and dysphagia, odds ratio = 9.70 (3.10–30.41)] and model 2 [age, sex, and stroke severity, odds ratio = 3.21 (1.93–5.32)]. Addition of CRP improved discrimination in both models [integrated discrimination improvement = 9.83% (0.89–18.77) and 5.31% (2.83–7.79), respectively], but accuracy was only improved for model 1 (area under the curve 0.806–0.874, p = 0.036). In this study, CRP was independently associated with development of post‐stroke infections, with the optimal time‐window for measurement at 24–48 h. However, its additional predictive value is moderate over clinical information. Combination with other biomarkers in a panel seems a promising strategy for future studies. image

Background and Purpose: The aim of this study was to evaluate and independently validate SAA (serum amyloid A)—a recently discovered blood biomarker—to predict poststroke infections. Methods: The derivation cohort (A) was composed of 283 acute ischemic stroke patients and the independent validation cohort (B), of 367 patients. The primary outcome measure was any stroke-associated infection, defined by the criteria of the US Centers for Disease Control and Prevention, occurring during hospitalization. To determine the association of SAA levels on admission with the development of infections, logistic regression models were calculated. The discriminatory ability of SAA was assessed, by calculating the area under the receiver operating characteristic curve. Results: After adjusting for all predictors that were significantly associated with any infection in the univariate analysis, SAA remained an independent predictor in study A (adjusted odds ratio, 1.44 [95% CI, 1.16–1.79]; P =0.001) and in study B (adjusted odds ratio, 1.52 [1.05–2.22]; P =0.028). Adding SAA to the best regression model without the biomarker, the discriminatory accuracy improved from 0.76 (0.69–0.83) to 0.79 (0.72–0.86; P <0.001; likelihood ratio test) in study A. These results were externally validated in study B with an improvement in the area under the receiver operating characteristic curve, from 0.75 (0.70–0.81) to 0.76 (0.71–0.82; P <0.038). Conclusions: Among patients with ischemic stroke, blood SAA measured on admission is a novel independent predictor of infection after stroke. SAA improved the discrimination between patients who developed an infection compared with those who did not in both derivation and validation cohorts. Registration: URL: https://www.clinicaltrials.gov . Unique identifier: NCT00390962.

Clinical trials are the hallmark of evidence-based medicine, but recruitment is often challenging, especially in stroke trials investigating patients not being able to give informed consent. In some nations, ethics committees will not approve of inclusion in a clinical study via consent of a legal representative. The ethical dilemma of including or excluding those patients has not been properly addressed, as there is little data on the effect of stroke characteristics on the ability to give informed consent. To examine differences between patients able and unable to consent at inclusion to an acute stroke trial, we conducted a post-hoc analysis of monitoring records from a multicentric interventional trial. These records listed patients who gave informed consent by themselves and those who needed a legal representative to do so. This exemplary STRAWINSKI trial aimed at improving stroke outcome by biomarker-guided antibiotic treatment of stroke associated pneumonia and included patients within 40 h after stroke onset, suffering from MCA infarctions with an NIHSS score > 9 at admission. Standard descriptive and associative statistics were calculated to compare baseline characteristics and outcome measures between patients who were able to consent and those who were not. We identified the person giving consent in 228 out of 229 subjects. Patients with inability to consent were older (p < 0.01), suffered from more left-hemispheric (p < 0.01) and more severe strokes (NIHSS, p < 0.01), were more likely to die during hospitalisation (p < 0.01) or have unfavourable outcome at discharge (mRS, p < 0.01), to develop fever (p < 0.01) and tended to be more susceptible to infections (p = 0.06) during the acute course of the disorder. Demographics, stroke characteristics and outcomes significantly affect stroke patients in their ability to consent. Where selection criteria and primary outcome measures of a trial are significantly affected by ability to consent, excluding patients unable to consent might be unethical. URL http://www.clinicaltrials.gov . Unique identifier: NCT01264549 .