Prediction of infarction volume and infarction growth rate in acute ischemic stroke.
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ABSTRACT:
SUBMITTER: Kamran S
PROVIDER: S-EPMC5548812 | biostudies-other | 2017 Aug
REPOSITORIES: biostudies-other
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Project description:BackgroundPatients with acute ischemic stroke (AIS) are susceptible to acute myocardial infarction (AMI), which would lead to a dramatic increase of in-hospital mortality.ObjectivesThe authors established and validated an easy-used model to stratify the risk of in-hospital AMI among patients with AIS.MethodsWe consecutively included patients with AIS who were admitted within 7 days from symptom onset in our prospectively maintained database (NCT04487340) from January 2016 to December 2020. In the derivation cohort from 70 centers, we developed a score to predict in-hospital AMI by integrating the bedside-accessible predictors identified via multivariable logistic regression. Then in the validation cohort from 22 centers, we externally evaluated the performance of this score.ResultsOverall, 96,367 patients were included. In-hospital AMI occurred in 392 (0.41%) patients. The final model, named CTRAN, incorporated 5 predictors including the history of coronary heart disease, malignant tumor, renal insufficiency, age, and baseline National Institutes of Health Stroke Scale score. The CTRAN score was confirmed in the validation cohort using receiver operating characteristic curve, which yielded an area under the curve of 0.758 (95% CI: 0.718-0.798).ConclusionsThe CTRAN score could be a good tool for clinicians to identify patients with AIS at high in-hospital AMI risk.
| S-EPMC9876956 | biostudies-literature
Project description:Stroke remains an important health challenge. Here, we study whether circulating chemokine (C-C motif) ligand 5 (CCL5) levels may predict clinical outcomes for stroke patients. A total of 100 consecutive stroke patients (36 acute ischemic and 64 hemorrhagic) were admitted to the stroke unit. Clinical history data and monitoring parameters were recorded. Blood serum was collected at days 0, 1, and hospital discharge to measure CCL5 levels by ELISA. Infarct or hemorrhagic volume, neurological severity (NIHSS), and functional prognosis (mRankin scale) were measured as clinical outcomes. CCL5 levels were lower in patients with hemorrhagic stroke than in patients with acute ischemic stroke. No differences were found between females and males in both types of stroke. Ischemic stroke patients whose infarct volume grew had lower CCL5 levels at day 0. Levels of CCL5 in ischemic and hemorrhagic patients were not associated with more severe symptoms/worse prognosis (NIHSS > 3; mRankin > 2) at admission or at 3 months. CCL5 could be used as a diagnostic marker to distinguish between ischemic and hemorrhagic strokes. Furthermore, CCL5 levels could predict the infarct volume outcomes in ischemic patients.
| S-EPMC9456070 | biostudies-literature
Project description:BackgroundHeart rate turbulence (HRT), an ECG-based marker of autonomic cardiac regulation, has shown high prognostic value in patients with established cardiovascular diseases, while data in patients with acute ischemic stroke are scarce.Patients and methodsThe HRT parameters turbulence onset and turbulence slope were analyzed using Holter-ECG recordings from patients with acute ischemic stroke, consecutively enrolled in the prospective observational HEBRAS study. HRT was categorized as normal (category 0; both parameters normal), abnormal (category 1; one parameter abnormal), or severely abnormal (category 2; both parameters abnormal). Outcomes of interest were functional outcome according to modified Rankin Scale (mRS) score at 3 months, mortality at 1 year, newly detected atrial fibrillation (AF), and evidence of focal myocardial fibrosis on cardiovascular MRI.ResultsHRT was assessed in 335 patients in sinus rhythm (median age 69 years, 37% female, median NIHSS score 2 on admission), including 262 (78%) with normal HRT, 47 (14%) with abnormal and 26 (8%) with severely abnormal HRT. Compared with normal HRT, severely abnormal HRT was associated with increased disability [higher mRS] at 3 months (adjusted odds ratio [aOR]: 2.9, 95% confidence interval [CI]: 1.3-6.6), new AF (aOR: 3.5, 95% CI: 1.1-10.6), MRI-detected myocardial fibrosis (aOR: 5.8, 95% CI: 1.3-25.9), but not with mortality at 1 year after stroke (aOR: 3.0, 95% CI: 0.7-13.9). Abnormal HRT was not associated with the analyzed outcomes.ConclusionsSeverely abnormal HRT was associated with increased disability and previously unknown cardiac comorbidities. The potential role of HRT in selecting patients for extended AF monitoring and cardiac imaging should be further investigated.
| S-EPMC10916809 | biostudies-literature
Project description:BackgroundIn-hospital ischemic stroke following acute ST-elevation myocardial infarction (STEMI) has not been evaluated on a national scale in the United States.MethodsWe used 2003 to 2014 Nationwide Inpatient Sample data to identify adults with a principal diagnosis of STEMI. Patients were divided into two groups defined by presence or absence of ischemic stroke. Clinical characteristics and in-hospital outcomes were studied using relevant statistics. Multiple linear and logistic regression models identified factors associated with ischemic stroke, national trend of in-hospital stroke incidence and in-hospital mortality.ResultsOf 1,842,529 STEMI patients hospitalized from 2003 to 2014, 22,268 (1.2%) developed acute in-hospital ischemic stroke. Those with acute strokes were older (age ? 65 years: 70% vs 46%), more likely female (51% vs 33%), and had higher rates of atrial fibrillation (28.9% vs 12.2%) and heart failure (40.5% vs 21.1%). Age and gender adjusted incidence of in-hospital ischemic stroke following STEMI remained stable; 1.4% in 2003 and 1.5% in 2014 (P trend = 0.50). However, age and gender adjusted in-hospital mortality declined in STEMI patients with and without in-hospital ischemic stroke [AOR 0.97 (0.95-0.99) P trend = 0.03, and AOR 0.98 (0.98-0.99) P trend < 0.001, respectively]. Patients with ischemic strokes had higher in-hospital mortality (25.7% Vs 7.2%, p < 0.001), [AOR 2.11, 95% CI (1.92-2.32)].ConclusionIn the United States, the incidence of acute in-hospital stroke remained stable from 2003 to 2014 following STEMI with significant decrease of in-hospital mortality trends. Despite slight improvement in mortality trends, in-hospital mortality rates remained elevated calling for interventions to optimize health care delivery.
| S-EPMC7736913 | biostudies-literature
Project description:PURPOSE:Contributions of cerebrospinal fluid (CSF) have not been previously taken into account in the quantification of APT CEST effects, and correction for the dilution of CEST effects by CSF may allow for more robust measurement of CEST signals. The objective of this study was to compare the robustness of a partial volume (PV) correction model against a standard (4-pool) multi-pool model as far as their ability to quantify CEST effects in healthy, normal, and pathological tissue. METHODS:MRI data from 12 patients presenting with ischemic stroke, and 6 healthy subjects, were retrospectively analyzed. CEST signals derived from a 4-pool model and a PV correction model were compared for repeatability and pathological tissue contrast. The effect of PV correction (PVC) was assessed within 3 ranges of tissue PV estimate (PVE): high PVE voxels, low PVE voxels, and the whole slice. RESULTS:In voxels with a high tissue PVE, PV correction did not make a significant difference to absolute APTR* . In low PVE voxels, the PVC model exhibited a significantly decreased ischemic core signal. The PVC measures exhibited higher repeatability between healthy subjects (4 pools: 3.4%, PVC: 2.4%) while maintaining a similar ischemic core CNR (0.7) to the 4-pool model. In whole slice analysis it was found that both models exhibited similar results. CONCLUSIONS:PV correction yielded a measure of APT effects that was more repeatable than standard 4-pool analysis while achieving a similar CNR in pathological tissue, suggesting that PV-corrected analysis was more robust at low values of tissue PVE.
| S-EPMC6771886 | biostudies-literature
Project description:Early neurological improvement as assessed with the NIH stroke scale (NIHSS) at 24 h has been associated with improved long-term functional outcomes following acute ischemic stroke (AIS). Cardiac dysfunction is often present in AIS, but its association with outcomes is incompletely defined. We performed a pilot study to evaluate the association between non-invasively measured cardiac parameters and 24-h neurological improvement in prospectively enrolled patients with suspected AIS who presented within 12 h of symptom-onset and had an initial systolic blood pressure>140 mm Hg. Patients receiving thrombolytic therapy or mechanical thrombectomy were excluded. Non-invasive pulse contour analysis was used to measure mean arterial blood pressure (MAP), cardiac stroke volume index (cSVI), cardiac output (CO) and cardiac index (CI). Transcranial Doppler recorded mean middle cerebral artery flow velocity (MFV). We defined a decrease of 4 NIHSS points or NIHSS ≤ 1 at 24-h as neurological improvement. Of 75 suspected, 38 had confirmed AIS and did not receive reperfusion therapy. Of these, 7/38 (18.4%) had neurological improvement over 24 h. MAP was greater in those without improvement (108, IQR 96-123 mm Hg) vs. those with (89, IQR 73-104 mm Hg). cSVI, CO, and MFV were similar between those without and with improvement: 37.4 (IQR 30.9-47.7) vs. 44.7 (IQR 42.3-55.3) ml/m2; 5.2 (IQR 4.2-6.6) vs. 5.3 (IQR 4.7-6.7) mL/min; and 39.9 (IQR 32.1-45.7) vs. 34.4 (IQR 27.1-49.2) cm/s, respectively. Multivariate analysis found MAP and cSVI as predictors for improvement (OR 0.93, 95%CI 0.85-0.98 and 1.14, 95%CI 1.03-1.31). In this pilot study, cSVI and MAP were associated with 24-h neurological improvement in AIS.
| S-EPMC8637535 | biostudies-literature
Project description:Background and purposeWe investigated whether the annual volume of patients with acute ischemic stroke referred from a primary stroke center (PSC) for endovascular treatment (EVT) is associated with treatment times and functional outcome.MethodsWe used data from the Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands (MR CLEAN) registry (2014-2017). We included patients with acute ischemic stroke of the anterior circulation who were transferred from a PSC to a comprehensive stroke center (CSC) for EVT. We examined the association between EVT referral volume of PSCs and treatment times and functional outcome using multivariable regression modeling. The main outcomes were time from arrival at the PSC to groin puncture (PSC-door-to-groin time), adjusted for estimated ambulance travel times, time from arrival at the CSC to groin puncture (CSC-door-to-groin time), and modified Rankin Scale (mRS) score at 90 days after stroke.ResultsOf the 3637 patients in the registry, 1541 patients (42%) from 65 PSCs were included. Mean age was 71 years (SD ± 13.3), median National Institutes of Health Stroke Scale score was 16 (interquartile range [IQR]: 12-19), and median time from stroke onset to arrival at the PSC was 53 min (IQR: 38-90). Eighty-three percent had received intravenous thrombolysis. EVT referral volume was not associated with PSC-door-to-groin time (adjusted coefficient: -0.49 min/annual referral, 95% confidence interval [CI]: -1.27 to 0.29), CSC-door-to-groin time (adjusted coefficient: -0.34 min/annual referral, 95% CI: -0.69 to 0.01) or 90-day mRS score (adjusted common odds ratio: 0.99, 95% CI: 0.96-1.01).ConclusionsIn patients transferred from a PSC for EVT, higher PSC volumes do not seem to translate into better workflow metrics or patient outcome.
| S-EPMC9292965 | biostudies-literature
Project description:About one-third of acute stroke patients may experience stroke-in-evolution, which is often associated with a worse outcome. Recently, we showed that multiscale entropy (MSE), a non-linear method for analysis of heart rate variability (HRV), is an early outcome predictor in non-atrial fibrillation (non-AF) stroke patients. We aimed to further investigate MSE as a predictor of SIE. We included 90 non-AF ischemic stroke patients admitted to the intensive care unit (ICU). Nineteen (21.1%) patients met the criteria of SIE, which was defined as an increase in the National Institutes of Health Stroke Scale score of ≥2 points within 3 days of admission. The MSE of HRV was analyzed from 1-hour continuous ECG signals during the first 24 hours of admission. The complexity index was defined as the area under the MSE curve. Compared with patients without SIE, those with SIE had a significantly lower complexity index value (21.3 ± 8.5 vs 26.5 ± 7.7, P = 0.012). After adjustment for clinical variables, patients with higher complexity index values were significantly less likely to have SIE (odds ratio = 0.897, 95% confidence interval 0.818-0.983, P = 0.020). In summary, early assessment of HRV by MSE can be a potential predictor of SIE in ICU-admitted non-AF ischemic stroke patients.
| S-EPMC4665162 | biostudies-other
Project description:Background and objectivesPost-stroke cognitive impairment (PSCI) occurs in up to 50% of patients with acute ischemic stroke (AIS). Thus, the prediction of cognitive outcomes in AIS may be useful for treatment decisions. This PSCI cohort study aimed to determine the applicability of a machine learning approach for predicting PSCI after stroke.MethodsThis retrospective study used a prospective PSCI cohort of patients with AIS. Demographic features, clinical characteristics, and brain imaging variables previously known to be associated with PSCI were included in the analysis. The primary outcome was PSCI at 3-6 months, defined as an adjusted z-score of less than - 2.0 standard deviation in at least one of the four cognitive domains (memory, executive/frontal, visuospatial, and language), using the Korean version of the Vascular Cognitive Impairment Harmonization Standards-Neuropsychological Protocol (VCIHS-NP). We developed four machine learning models (logistic regression, support vector machine, extreme gradient boost, and artificial neural network) and compared their accuracies for outcome variables.ResultsA total of 951 patients (mean age 65.7 ± 11.9; male 61.5%) with AIS were included in this study. The area under the curve for the extreme gradient boost and the artificial neural network was the highest (0.7919 and 0.7365, respectively) among the four models for predicting PSCI according to the VCIHS-NP definition. The most important features for predicting PSCI include the presence of cortical infarcts, mesial temporal lobe atrophy, initial stroke severity, stroke history, and strategic lesion infarcts.ConclusionOur findings indicate that machine-learning algorithms, particularly the extreme gradient boost and the artificial neural network models, can best predict cognitive outcomes after ischemic stroke.
| S-EPMC10468853 | biostudies-literature
Project description:Background Prehospital delay is an important contributor to poor outcomes in both acute ischemic stroke (AIS) and acute myocardial infarction (AMI). We aimed to compare the prehospital delay and related factors between AIS and AMI. Methods and Results We identified patients with AIS and AMI who were admitted to the 11 Korean Regional Cardiocerebrovascular Centers via the emergency room between July 2016 and December 2018. Delayed arrival was defined as a prehospital delay of >3 hours, and the generalized linear mixed-effects model was applied to explore the effects of potential predictors on delayed arrival. This study included 17 895 and 8322 patients with AIS and AMI, respectively. The median value of prehospital delay was 6.05 hours in AIS and 3.00 hours in AMI. The use of emergency medical services was the key determinant of delayed arrival in both groups. Previous history, 1-person household, weekday presentation, and interhospital transfer had higher odds of delayed arrival in both groups. Age and sex had no or minimal effects on delayed arrival in AIS; however, age and female sex were associated with higher odds of delayed arrival in AMI. More severe symptoms had lower odds of delayed arrival in AIS, whereas no significant effect was observed in AMI. Off-hour presentation had higher and prehospital awareness had lower odds of delayed arrival; however, the magnitude of their effects differed quantitatively between AIS and AMI. Conclusions The effects of some nonmodifiable and modifiable factors on prehospital delay differed between AIS and AMI. A differentiated strategy might be required to reduce prehospital delay.
| S-EPMC9238627 | biostudies-literature