Sex Differences in Outcomes of Acute Myocardial Injury After Stroke.

BACKGROUND: Sex differences in presentation, treatment, and prognosis of cardiovascular disorders are well recognized. Although an association between acute myocardial injury and mortality after ischemic stroke has been demonstrated, it is unclear whether prevalence and outcome of poststroke acute myocardial injury differ between women and men. METHODS AND RESULTS: We prospectively screened consecutive patients with acute ischemic stroke and serial high-sensitivity cardiac troponin T measurements admitted to our center. Acute myocardial injury was defined as at least 1 high-sensitivity cardiac troponin T value above the upper reference limit (14 ng/L) with a rise/fall of >20%. Rates of acute myocardial injury were also calculated using sex-specific high-sensitivity cardiac troponin T cutoffs (women upper reference limit, 9 ng/L; men upper reference limit, 16 ng/L). Logistic regression analyses were performed to evaluate the association between acute myocardial injury and outcomes. Of 1067 patients included, 494 were women (46%). Women were older, had a higher rate of known atrial fibrillation, were more likely to be functionally dependent before admission, had higher stroke severity, and more often had cardioembolic strokes (all P values <0.05). The crude prevalence of acute myocardial injury differed by sex (29% women versus 23% men, P=0.024). Statistically significant associations between acute myocardial injury and outcomes were observed in women (7-day in-hospital mortality: adjusted odds ratio [aOR], 3.2 [95% CI, 1.07-9.3]; in-hospital mortality: aOR, 3.3 [95% CI, 1.4-7.6]; modified Rankin Scale score at discharge: aOR, 1.6 [95% CI, 1.1-2.4]) but not in men. The implementation of sex-specific cutoffs did not increase the prognostic value of acute myocardial injury for unfavorable outcomes. CONCLUSIONS: The prevalence of acute myocardial injury after ischemic stroke and its association with mortality and greater disability might be sex-dependent. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03892226.

Machine learning using multimodal and autonomic nervous system parameters predicts clinically apparent stroke-associated pneumonia in a development and testing study.

BACKGROUND: Stroke-associated pneumonia (SAP) is a preventable determinant for poor outcome after stroke. Machine learning (ML) using large-scale clinical data warehouses may be able to predict SAP and identify patients for targeted interventions. The aim of this study was to develop a prediction model for identifying clinically apparent SAP using automated ML. METHODS: The ML model used clinical and laboratory parameters along with heart rate (HR), heart rate variability (HRV), and blood pressure (BP) values obtained during the first 48 h after stroke unit admission. A logistic regression classifier was developed and internally validated with a nested-cross-validation (nCV) approach. For every shuffle, the model was first trained and validated with a fixed threshold for 0.9 sensitivity, then finally tested on the out-of-sample data and benchmarked against a widely validated clinical score (A2DS2). RESULTS: We identified 2390 eligible patients admitted to two-stroke units at Charité between October 2020 and June 2023, of whom 1755 had all parameters available. SAP was diagnosed in 96/1755 (5.5%). Circadian profiles in HR, HRV, and BP metrics during the first 48 h after admission exhibited distinct differences between patients with SAP diagnosis vs. those without. CRP, mRS at admission, leukocyte count, high-frequency power in HRV, stroke severity at admission, sex, and diastolic BP were identified as the most informative ML features. We obtained an AUC of 0.91 (CI 0.88-0.95) for the ML model on the out-of-sample data in comparison to an AUC of 0.84 (CI 0.76-0.91) for the previously established A2DS2 score (p < 0.001). The ML model provided a sensitivity of 0.87 (CI 0.75-0.97) with a corresponding specificity of 0.82 (CI 0.78-0.85) which outperformed the A2DS2 score for multiple cutoffs. CONCLUSIONS: Automated, data warehouse-based prediction of clinically apparent SAP in the stroke unit setting is feasible, benefits from the inclusion of vital signs, and could be useful for identifying high-risk patients or prophylactic pneumonia management in clinical routine.

Data lake-driven analytics identify nocturnal non-dipping of heart rate as predictor of unfavorable stroke outcome at discharge.

BACKGROUND: Post-stroke heart rate (HR) and heart rate variability (HRV) changes have been proposed as outcome predictors after stroke. We used data lake-enabled continuous electrocardiograms to assess post-stroke HR and HRV, and to determine the utility of HR and HRV to improve machine learning-based predictions of stroke outcome. METHODS: In this observational cohort study, we included stroke patients admitted to two stroke units in Berlin, Germany, between October 2020 and December 2021 with final diagnosis of acute ischemic stroke or acute intracranial hemorrhage and collected continuous ECG data through data warehousing. We created circadian profiles of several continuously recorded ECG parameters including HR and HRV parameters. The pre-defined primary outcome was short-term unfavorable functional outcome after stroke indicated through modified Rankin Scale (mRS) score of > 2. RESULTS: We included 625 stroke patients, 287 stroke patients remained after matching for age and National Institute of Health Stroke Scale (NIHSS; mean age 74.5 years, 45.6% female, 88.9% ischemic, median NIHSS 5). Both higher HR and nocturnal non-dipping of HR were associated with unfavorable functional outcome (p < 0.01). The examined HRV parameters were not associated with the outcome of interest. Nocturnal non-dipping of HR ranked highly in feature importance of various machine learning models. CONCLUSIONS: Our data suggest that a lack of circadian HR modulation, specifically nocturnal non-dipping, is associated with short-term unfavorable functional outcome after stroke, and that including HR into machine learning-based prediction models may lead to improved stroke outcome prediction.

Frequency, associated variables, and outcomes of acute myocardial injury according to the fourth Universal Definition of Myocardial Infarction in patients with acute ischemic stroke.

Background: Myocardial injury as indicated by elevation of cardiac troponin levels is common after acute ischemic stroke (AIS) and linked to poor outcomes. Previous studies rarely reported on serial hs-cTn measurements to distinguish whether myocardial injury is acute or chronic. Thus, little is known about frequency, associated variables, and outcome of acute myocardial injury in AIS. Methods and patients: In this single-centered observational cohort study, from 01/2019 to 12/2020, consecutive patients with neuroimaging-confirmed AIS <48 h after symptom onset, and serial troponin measurements within the first 2 days after admission (Roche Elecsys®, hs-cardiac troponin T) were prospectively registered. Acute myocardial injury was defined according to the fourth Universal Definition of Myocardial Infarction (troponin above the upper reference limit and rise/fall>20%). Outcomes of interest were in-hospital mortality and unfavorable functional status at discharge (modified Rankin Scale >1). Results: Out of 1067 analyzed patients, 25.3% had acute myocardial injury, 40.4% had chronic myocardial injury and 34.3% had no myocardial injury. Older age, higher stroke severity, thrombolytic treatment, and impaired kidney function were independently associated with acute myocardial injury. In-hospital mortality was higher in patients with acute myocardial injury than in those without (13% vs 3%, adjusted OR, 2.9% [95% CI, 1.6-5.5]). Compared with no myocardial injury, both acute and chronic myocardial injury were associated with unfavorable functional status at discharge (adjusted OR, 1.6 [95% CI, 1.1-2.5] and OR, 1.7 [95% CI, 1.2-2.4], respectively). Conclusions: A quarter of patients with AIS have evidence of acute myocardial injury according to the fourth Universal Definition of Myocardial Infarction. The strong association with in-hospital mortality highlights the need for clinical awareness and future studies on underlying mechanisms.

Aetiology, secondary prevention strategies and outcomes of ischaemic stroke despite oral anticoagulant therapy in patients with atrial fibrillation.

OBJECTIVE: To investigate the aetiology, subsequent preventive strategies and outcomes of stroke despite anticoagulation in patients with atrial fibrillation (AF). METHODS: We analysed consecutive patients with AF with an index imaging-proven ischaemic stroke despite vitamin K-antagonist (VKA) or direct oral anticoagulant (DOAC) treatment across 11 stroke centres. We classified stroke aetiology as: (i) competing stroke mechanism other than AF-related cardioembolism; (ii) insufficient anticoagulation (non-adherence or low anticoagulant activity measured with drug-specific assays); or, (iii) AF-related cardioembolism despite sufficient anticoagulation. We investigated subsequent preventive strategies with regard to the primary (composite of recurrent ischaemic stroke, intracranial haemorrhage, death) and secondary endpoint (recurrent ischaemic stroke) within 3 months after index stroke. RESULTS: Among 2946 patients (median age 81 years; 48% women; 43% VKA, 57% DOAC), stroke aetiology was competing mechanism in 713 patients (24%), insufficient anticoagulation in 934 (32%) and cardioembolism despite sufficient anticoagulation in 1299 (44%). We found high rates of the primary (27% of patients; completeness 91.6%) and secondary endpoint (4.6%; completeness 88.5%). Only DOAC (vs VKA) treatment after index stroke showed lower odds for both endpoints (primary: adjusted OR (aOR) (95% CI) 0.49 (0.32 to 0.73); secondary: 0.44 (0.24 to 0.80)), but not switching between different DOAC types. Adding antiplatelets showed higher odds for both endpoints (primary: aOR (95% CI) 1.99 (1.25 to 3.15); secondary: 2.66 (1.40 to 5.04)). Only few patients (1%) received left atrial appendage occlusion as additional preventive strategy. CONCLUSIONS: Stroke despite anticoagulation comprises heterogeneous aetiologies and cardioembolism despite sufficient anticoagulation is most common. While DOAC were associated with better outcomes than VKA, adding antiplatelets was linked to worse outcomes in these high-risk patients. Our findings indicate that individualised and novel preventive strategies beyond the currently available anticoagulants are needed. TRIAL REGISTRATION NUMBER: ISRCTN48292829.

UNC93B1 Is Widely Expressed in the Murine CNS and Is Required for Neuroinflammation and Neuronal Injury Induced by MicroRNA let-7b.

The chaperone protein Unc-93 homolog B1 (UNC93B1) regulates internalization, trafficking, and stabilization of nucleic acid-sensing Toll-like receptors (TLR) in peripheral immune cells. We sought to determine UNC93B1 expression and its functional relevance in inflammatory and injurious processes in the central nervous system (CNS). We found that UNC93B1 is expressed in various CNS cells including microglia, astrocytes, oligodendrocytes, and neurons, as assessed by PCR, immunocyto-/histochemistry, and flow cytometry. UNC93B1 expression in the murine brain increased during development. Exposure to the microRNA let-7b, a recently discovered endogenous TLR7 activator, but also to TLR3 and TLR4 agonists, led to increased UNC93B1 expression in microglia and neurons. Microglial activation by extracellular let-7b required functional UNC93B1, as assessed by TNF ELISA. Neuronal injury induced by extracellular let-7b was dependent on UNC93B1, as UNC93B1-deficient neurons were unaffected by the microRNA's neurotoxicity in vitro. Intrathecal application of let-7b triggered neurodegeneration in wild-type mice, whereas mice deficient for UNC93B1 were protected against injurious effects on neurons and axons. In summary, our data demonstrate broad UNC93B1 expression in the murine brain and establish this chaperone as a modulator of neuroinflammation and neuronal injury triggered by extracellular microRNA and subsequent induction of TLR signaling.