The Role of Electrocardiographic Markers for Predicting Atrial Fibrillation in Patients with Acute Ischemic Stroke: Data from the BIOSIGNAL Cohort Study.

BACKGROUND AND AIMS: P-wave abnormalities in the 12-lead electrocardiogram (ECG) have been associated with a higher risk of acute ischemic stroke (AIS) as well as atrial fibrillation (AF). This study aimed to assess pre-determined ECG criteria during sinus rhythm in unselected AIS patients and their value for predicting newly diagnosed atrial fibrillation (NDAF) after hospital admission. METHODS: P-wave alterations were measured on 12-lead ECG on admission in all consecutively enrolled patients without known AF between October 2014 and 2017. The outcome of interest was NDAF, identified by prolonged electrocardiographic monitoring within one year after the index AIS. Univariable and multivariable logistic regression was applied to assess the magnitude and independence of the association between pre-selected ECG markers and NDAF. The discriminatory accuracy was evaluated with the area under the receiver operating characteristic curve (AUC), and the incremental prognostic value was estimated with the net reclassification index. RESULTS: NDAF was detected in 87 (10%) of 856 patients during a follow-up of 365 days. Out of the pre-selected ECG parameters, advanced interatrial block (aIAB) and PR interval in lead II were independently associated with NDAF in univariable regression analysis. Only aIAB remained a significant predictor in multivariable analysis. Adding aIAB to the best-performing multivariable regression model improved the discriminatory accuracy to predict NDAF from an AUC of 0.78 (95%-CI 0.77-0.80) to 0.81 (95%-CI 0.80-0.83, p < 0.001). CONCLUSION: aIAB is independently and highly associated with NDAF in patients with AIS, has high inter-rater reliability, and therefore may be helpful to refine diagnostic work-up to search for AF in AIS.

Serum S-100B adds incremental value for the prediction of symptomatic intracranial hemorrhage and brain edema after acute ischemic stroke.

Background: Early identification of patients developing symptomatic intracranial hemorrhage and symptomatic brain edema after acute ischemic stroke is essential for clinical decision-making. Astroglial protein S-100B is a marker of blood-brain barrier disruption, which plays an important role in the formation of intracranial hemorrhage and brain edema. In this study, we assessed the prognostic value of serum S-100B for the development of these complications. Methods: Serum S-100B levels were measured within 24 h from symptom onset in 1749 consecutive acute ischemic stroke patients from the prospective, observational, multicenter BIOSIGNAL cohort study (mean age 72.0 years, 58.3% male). To determine symptomatic intracranial hemorrhage or symptomatic brain edema, follow-up neuroimaging was performed in all patients receiving reperfusion therapy or experiencing clinical worsening with an NIHSS increase of ⩾4. Results: Forty six patients (2.6%) developed symptomatic intracranial hemorrhage and 90 patients (5.2%) developed symptomatic brain edema. After adjustment for established risk factors, log10S-100B levels remained independently associated with both symptomatic intracranial hemorrhage (OR 3.41, 95% CI 1.7-6.9, p = 0.001) and symptomatic brain edema (OR 4.08, 95% CI 2.3-7.1, p < 0.001) in multivariable logistic regression models. Adding S-100B to the clinical prediction model increased the AUC from 0.72 to 0.75 (p = 0.001) for symptomatic intracranial hemorrhage and from 0.78 to 0.81 (p < 0.0001) for symptomatic brain edema. Conclusions: Serum S-100B levels measured within 24 h after symptom onset are independently associated with the development of symptomatic intracranial hemorrhage and symptomatic brain edema in acute ischemic stroke patients. Thus, S-100B may be useful for early risk-stratification regarding stroke complications.

Impact of Seizures and Status Epilepticus on Outcome in Patients with Aneurysmal Subarachnoid Hemorrhage.

BACKGROUND: We aimed to evaluate the association between seizures as divided by timing and type (seizures or status epilepticus) and outcome in patients with aneurysmal subarachnoid hemorrhage (aSAH). METHODS: All consecutive patients with aSAH admitted to the neurocritical care unit of the University Hospital Zurich between 2016 and 2020 were included. Seizure type and frequency were extracted from electronic patient files. RESULTS: Out of 245 patients, 76 experienced acute symptomatic seizures, with 39 experiencing seizures at onset, 18 experiencing acute seizures, and 19 experiencing acute nonconvulsive status epilepticus (NCSE). Multivariate analysis revealed that acute symptomatic NCSE was an independent predictor of unfavorable outcome (odds ratio 14.20, 95% confidence interval 1.74-116.17, p = 0.013) after correction for age, Hunt-Hess grade, Fisher grade, and delayed cerebral ischemia. Subgroup analysis showed a significant association of all seizures/NCSE with higher Fisher grade (p < 0.001 for acute symptomatic seizures/NCSE, p = 0.031 for remote symptomatic seizures). However, although acute seizures/NCSE (p = 0.750 and 0.060 for acute seizures/NCSE respectively) were not associated with unfavorable outcome in patients with a high Hunt-Hess grade, they were significantly associated with unfavorable outcome in patients with a low Hunt-Hess grade (p = 0.019 and p < 0.001 for acute seizures/NCSE, respectively). CONCLUSIONS: Acute symptomatic NCSE independently predicts unfavorable outcome after aSAH. Seizures and NCSE are associated with unfavorable outcome, particularly in patients with a low Hunt-Hess grade. We propose that NCSE and the ictal or postictal reduction of Glasgow Coma Scale may hamper close clinical evaluation for signs of delayed cerebral ischemia, and thus possibly leading to delayed diagnosis and therapy thereof in patients with a low Hunt-Hess grade.

Measurement of Midregional Pro-Atrial Natriuretic Peptide to Discover Atrial Fibrillation in Patients With Ischemic Stroke.

BACKGROUND: Midregional pro-atrial natriuretic peptide (MR-proANP) is a promising biomarker to differentiate the underlying etiology of acute ischemic stroke (AIS). OBJECTIVES: This study aimed to determine the role of MR-proANP for classification as cardioembolic (CE) stroke, identification of newly diagnosed atrial fibrillation (NDAF), and risk assessment for major adverse cardiovascular events (MACE). METHODS: This study measured MR-proANP prospectively collected within 24 hours after symptom-onset in patients with AIS from the multicenter BIOSIGNAL (Biomarker Signature of Stroke Aetiology) cohort study. Primary outcomes were CE stroke etiology and NDAF after prolonged cardiac monitoring, as well as a composite outcome of MACE (recurrent cerebrovascular events, myocardial infarction, or cardiovascular death) within 1 year. Logistic/Poisson and subproportional hazard regression were applied to evaluate the association between MR-proANP levels and outcomes. Additionally, a model for prediction of NDAF was derived and validated as a decision tool for immediate clinical application. RESULTS: Between October 1, 2014, and October 31, 2017, this study recruited 1,759 patients. Log10MR-proANP levels were associated with CE stroke (OR: 7.96; 95% CI: 4.82-13.14; risk ratio: 3.12; 95% CI: 2.23-4.37), as well as NDAF (OR: 35.3; 95% CI: 17.58-71.03; risk ratio: 11.47; 95% CI: 6.74-19.53), and MACE (subdistributional HR: 2.02; 95% CI: 1.32-3.08) during follow-up. The model to predict NDAF including only age and MR-proANP levels had a good discriminatory capacity with an area under the curve of 0.81 (95% CI: 0.76-0.86), was well calibrated (calibration in the large: -0.086; calibration slope 1.053), and yielded higher net-benefit compared with validated scores to predict NDAF (AS5F score, CHA2DS2-VASc [Congestive Heart Failure, Hypertension, Age ≥65 or ≥75, Diabetes, Prior Cardioembolic Event, (female) Sex, or Vascular Disease] score). CONCLUSIONS: MR-proANP is a valid biomarker to determine risk of NDAF and MACE in patients with AIS and can be used as a decision tool to identify patients for prolonged cardiac monitoring. (Biomarker Signature of Stroke Aetiology Study: The BIOSIGNAL study [BIOSIGNAL]; NCT02274727).

Lipoprotein(a) is associated with large artery atherosclerosis stroke aetiology and stroke recurrence among patients below the age of 60 years: results from the BIOSIGNAL study.

AIMS: Lipoprotein(a) [Lp(a)] is a recognized causal risk factor for atherosclerotic cardiovascular disease but its role for acute ischaemic stroke (AIS) is controversial. In this study, we evaluated the association of Lp(a) with large artery atherosclerosis (LAA) stroke and risk of recurrent cerebrovascular events in AIS patients. METHODS AND RESULTS: For this analysis of the prospective, observational, multicentre BIOSIGNAL cohort study we measured Lp(a) levels in plasma samples of 1733 primarily Caucasian (98.6%) AIS patients, collected within 24 h after symptom onset. Primary outcomes were LAA stroke aetiology and recurrent cerebrovascular events (ischaemic stroke or transient ischaemic attack) within 1 year. We showed that Lp(a) levels are independently associated with LAA stroke aetiology [adjusted odds ratio 1.48, 95% confidence interval (CI) 1.14-1.90, per unit log10Lp(a) increase] and identified age as a potent effect modifier (Pinteraction =0.031) of this association. The adjusted odds ratio for LAA stroke in patients aged <60 years was 3.64 (95% CI 1.76-7.52) per unit log10Lp(a) increase and 4.04 (95% CI 1.73-9.43) using the established cut-off ≥100 nmol/l. For 152 recurrent cerebrovascular events, we did not find a significant association in the whole cohort. However, Lp(a) levels ≥100 nmol/l were associated with an increased risk for recurrent events among patients who were either <60 years [adjusted hazard ratio (HR) 2.40, 95% CI 1.05-5.47], had evident LAA stroke aetiology (adjusted HR 2.18, 95% CI 1.08-4.40), or had no known atrial fibrillation (adjusted HR 1.60, 95% CI 1.03-2.48). CONCLUSION: Elevated Lp(a) was independently associated with LAA stroke aetiology and risk of recurrent cerebrovascular events among primarily Caucasian individuals aged <60 years or with evident arteriosclerotic disease.

Natural History, Phenotypic Spectrum, and Discriminative Features of Multisystemic RFC1 Disease.

OBJECTIVE: To delineate the full phenotypic spectrum, discriminative features, piloting longitudinal progression data, and sample size calculations of replication factor complex subunit 1 (RFC1) repeat expansions, recently identified as causing cerebellar ataxia, neuropathy, vestibular areflexia syndrome (CANVAS). METHODS: Multimodal RFC1 repeat screening (PCR, Southern blot, whole-exome/genome sequencing-based approaches) combined with cross-sectional and longitudinal deep phenotyping in (1) cross-European cohort A (70 families) with ≥2 features of CANVAS or ataxia with chronic cough (ACC) and (2) Turkish cohort B (105 families) with unselected late-onset ataxia. RESULTS: Prevalence of RFC1 disease was 67% in cohort A, 14% in unselected cohort B, 68% in clinical CANVAS, and 100% in ACC. RFC1 disease was also identified in Western and Eastern Asian individuals and even by whole-exome sequencing. Visual compensation, sensory symptoms, and cough were strong positive discriminative predictors (>90%) against RFC1-negative patients. The phenotype across 70 RFC1-positive patients was mostly multisystemic (69%), including dysautonomia (62%) and bradykinesia (28%) (overlap with cerebellar-type multiple system atrophy [MSA-C]), postural instability (49%), slow vertical saccades (17%), and chorea or dystonia (11%). Ataxia progression was ≈1.3 Scale for the Assessment and Rating of Ataxia points per year (32 cross-sectional, 17 longitudinal assessments, follow-up ≤9 years [mean 3.1 years]) but also included early falls, variable nonlinear phases of MSA-C-like progression (SARA points 2.5-5.5 per year), and premature death. Treatment trials require 330 (1-year trial) and 132 (2-year trial) patients in total to detect 50% reduced progression. CONCLUSIONS: RFC1 disease is frequent and occurs across continents, with CANVAS and ACC as highly diagnostic phenotypes yet as variable, overlapping clusters along a continuous multisystemic disease spectrum, including MSA-C-overlap. Our natural history data help to inform future RFC1 treatment trials. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that RFC1 repeat expansions are associated with CANVAS and ACC.

SAA (Serum Amyloid A): A Novel Predictor of Stroke-Associated Infections.

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.