Acute Stroke Registry And Analysis Of Lausanne Research Articles

The Usefulness of Factor XIII Concentration Assessment in Patients in the Acute Phase of Ischaemic Stroke Treated with Thrombolysis.

In recent years, there has been a growing interest in factor XIII in ischaemic stroke. The study's main aim was to assess the usefulness of factor XIII concentration determination in patients with acute ischaemic stroke (AIS) treated with thrombolysis with recombinant tissue plasminogen activator (t-PA). The study was conducted in two groups of 84 patients with AIS: group I-with thrombolytic therapy and group II-without thrombolysis. A physical examination, neurological status (using the National Institutes of Health Stroke Scale, NIHSS), daily patients' activities measured with the Barthel Index and Modified Rankin Scale (mRS), and blood parameters were conducted on day 1 and day 7. The following parameters were assessed: highly sensitive C-reaction protein (CRP), fibrinogen, D-dimers (DD), neutrophil-lymphocyte ratio (NLR index), and the concentration of factor XIII-A. In group I, the concentration of XIII-A decreased significantly between day 1 and 7 (p < 0.001). In group I, the concentration of XIII-A on day 7 in Total Anterior Circulation Infarct (TACI) was significantly lower than in non-TACI stroke. XIII-A concentration in group I was significantly lower in patients < 31 points with Acute Stroke Registry and Analysis of Lausanne (ASTRAL). A greater decrease in XIII-A between the first sampling on day 1 and the second sampling on day 7 was associated with a worse patient neurological state in group I. In patients with AIS treated with t-PA, factor XIII concentrations decrease in the acute phase of stroke, and the largest decrease occurs in the TACI stroke. Determination of factor XIII concentration in patients with AIS can be used in clinical practice as an additional parameter supporting the assessment of stroke severity and may play a role in the prognosis; lower factor XIII-A activity may be a predictor of a worse prognosis.

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

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. 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). 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. 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.

Service delivery in acute ischemic stroke patients: Does sex matter?

Women with acute ischemic stroke (AIS) are older and have greater preexisting handicap than men. Given that these factors do not fully explain their poorer long-term outcomes, we sought to investigate potential sex differences in the delivery of acute stroke care in a large cohort of consecutive AIS patients. We analyzed all patients from ASTRAL (Acute Stroke Registry and Analysis of Lausanne) from March 2003 to December 2019. Multivariable analyses were performed on acute time metrics, revascularization therapies, ancillary examinations for stroke workup, subacute symptomatic carotid artery revascularization, frequency of change in goals of care (palliative care), and length of hospital stay. Of the 5347 analyzed patients, 45% were biologically female and the median age was 74.6 years. After multiple adjustments, female sex was significantly associated with higher onset-to-door (adjusted hazard ratio [aHR] = 1.09, 95% confidence interval [CI] = 1.04-1.14) and door-to-endovascular-puncture intervals (aHR = 1.15, 95% CI = 1.05-1.25). Women underwent numerically fewer diagnostic examinations (adjusted odds ratio [aOR] = 0.94, 95% CI = 0.85-1.04) and fewer subacute carotid revascularizations (aOR = 0.69, 95% CI = 0.33-1.18), and had longer hospital stays (aHR = 1.03, 95% CI = 0.99-1.07), but these differences were not statistically significant. We found no differences in the rates of acute revascularization treatments, or in the frequency of change of goals of treatments. This retrospective analysis of a large, consecutive AIS cohort suggests that female sex is associated with unfavorable pre- and in-hospital time metrics, such as a longer onset-to-door and door-to-endovascular-puncture intervals. Such indicators of less effective stroke care delivery may contribute to the poorer long-term functional outcomes in female patients and require further attention.

Predictive Performance of Machine Learning–Based Models for Poststroke Clinical Outcomes in Comparison With Conventional Prognostic Scores: Multicenter, Hospital-Based Observational Study

Background Although machine learning is a promising tool for making prognoses, the performance of machine learning in predicting outcomes after stroke remains to be examined. Objective This study aims to examine how much data-driven models with machine learning improve predictive performance for poststroke outcomes compared with conventional stroke prognostic scores and to elucidate how explanatory variables in machine learning–based models differ from the items of the stroke prognostic scores. Methods We used data from 10,513 patients who were registered in a multicenter prospective stroke registry in Japan between 2007 and 2017. The outcomes were poor functional outcome (modified Rankin Scale score &gt;2) and death at 3 months after stroke. Machine learning–based models were developed using all variables with regularization methods, random forests, or boosted trees. We selected 3 stroke prognostic scores, namely, ASTRAL (Acute Stroke Registry and Analysis of Lausanne), PLAN (preadmission comorbidities, level of consciousness, age, neurologic deficit), and iScore (Ischemic Stroke Predictive Risk Score) for comparison. Item-based regression models were developed using the items of these 3 scores. The model performance was assessed in terms of discrimination and calibration. To compare the predictive performance of the data-driven model with that of the item-based model, we performed internal validation after random splits of identical populations into 80% of patients as a training set and 20% of patients as a test set; the models were developed in the training set and were validated in the test set. We evaluated the contribution of each variable to the models and compared the predictors used in the machine learning–based models with the items of the stroke prognostic scores. Results The mean age of the study patients was 73.0 (SD 12.5) years, and 59.1% (6209/10,513) of them were men. The area under the receiver operating characteristic curves and the area under the precision-recall curves for predicting poststroke outcomes were higher for machine learning–based models than for item-based models in identical populations after random splits. Machine learning–based models also performed better than item-based models in terms of the Brier score. Machine learning–based models used different explanatory variables, such as laboratory data, from the items of the conventional stroke prognostic scores. Including these data in the machine learning–based models as explanatory variables improved performance in predicting outcomes after stroke, especially poststroke death. Conclusions Machine learning–based models performed better in predicting poststroke outcomes than regression models using the items of conventional stroke prognostic scores, although they required additional variables, such as laboratory data, to attain improved performance. Further studies are warranted to validate the usefulness of machine learning in clinical settings.

Rare stroke mechanisms in 4154 consecutive patients: causes, predictors, treatment, and outcomes

BackgroundRare mechanisms of stroke (RMS) in acute ischemic stroke (AIS) have rarely been studied applying a systematic approach. Our aim was to define the frequency, etiologies, predictors, and outcomes of RMS in a consecutive series of AIS.MethodsData from consecutive patients from 2003 to 2016 were derived from the Acute STroke Registry and Analysis of Lausanne (ASTRAL). Frequency of subcategories of RMS was calculated. In a case–control design, RMS were compared to strokes of all other mechanisms. Outcome was assessed with 3-month Rankin-shift and 12-month mortality and recurrence rates.ResultsOut of 4154 AISs, 222 (5.3%) were found to have a RMS (42.0% female, median age 66 years). The most frequent RMS etiologies were medical interventions (25.6%), active oncological disease (22.5%), and vasculitis (11.7%). In multivariate analysis, RMS patients were younger, had more preceding and bilateral strokes, and a higher admission temperature. They were associated with less traditional risk factors and more systemic disease (such as AIDS, coagulopathy, and cancer). RMS also had more early ischemic changes on plain CT, less revascularization treatments, and more symptomatic hemorrhagic transformations. They presented significantly higher 3-month disability (Rankin-shift-ORadj 1.74), 12-month recurrence (ORadj 1.99), and mortality rates (ORadj 2.41).ConclusionsRMS occurred in 5.3% of a large population of consecutive AISs and are most frequently related to medical interventions, cancer, and vasculitis. RMS patients have less traditional risk factors but more systemic comorbidities, hemorrhagic transformations, recurrences, and a worse long-term outcome. Identification of RMS has direct implications for early treatment and long-term outcome.

Stroke in the stroke unit: Recognition, treatment and outcomes in a single-centre cohort.

In-hospital strokes (IHS) are associated with longer diagnosis times, treatment delays and poorer outcomes. Strokes occurring in the stroke unit have seldom been studied. Our aim was to assess the management of in-stroke-unit ischaemic stroke (ISUS) by analysing ISUS characteristics, delays in diagnosis, treatments and outcomes. Consecutive patients from the Acute Stroke Registry and Analysis of Lausanne (ASTRAL), from January 2003 to June 2019, were classified as ISUS, other-IHS or community-onset stroke (COS). Baseline and stroke characteristics, time to imaging and time to treatment, missed treatment opportunities, treatment rates and outcomes were compared using multivariate analysis with adjustment for relevant clinical, imaging and laboratory data available in ASTRAL. Amongst the 3456 patients analysed, 138 (4.0%) were ISUS, 214 (6.2%) other-IHS and 3104 (89.8%) COS. In multivariate analysis, patients with ISUS more frequently had known stroke onset time than other-IHS (adjusted odds ratio [aOR] 2.44; 95% confidence interval [CI] 1.39-4.35) or COS (aOR 2.56; 95% CI 1.59-4.17), had fewer missed treatment opportunities than other-IHS (aOR 0.22; 95% CI 0.06-0.86) and higher endovascular treatment (EVT) rates than COS (aOR 3.03; 95% CI 1.54-5.88). ISUS was associated with a favourable shift in the modified Rankin Scale at 3 months in comparison with other-IHS (aOR 1.73; 95% CI 1.11-2.69) or COS (aOR 1.46; 95% CI 1.00-2.12). In-stroke-unit ischaemic stroke more frequently had known stroke onset time than other-IHS or COS, fewer missed treatment opportunities than other-IHS and a higher EVT rate than COS. This readiness to identify and treat patients in the stroke unit may explain the better long-term outcome of ISUS.

Does ASTRAL score at hospital admission predict symptomatic haemorrhagic transformation in acute ischaemic stroke after revascularisation? A pilot single-centre study.

Accurately predicting outcomes after acute ischaemic stroke (AIS) is a major clinical goal. The aim of this pilot study was to evaluate the prognostic validity and accuracy of the Acute Stroke Registry and Analysis of Lausanne (ASTRAL) score in predicting symptomatic haemorrhagic transformation (sHT) in patients with AIS who have undergone revascularisation. Consecutive patients hospitalised for AIS who underwent treatment with intravenous thrombolysis (IVT) and/or mechanical thrombectomy (MT) were identified, and their ASTRAL scores at hospital admission were estimated. The study endpoint was sHT within 24 hours of stroke onset. The predictive performance of the ASTRAL score was investigated through logistic regression analysis and discrimination and calibration tests. Sixty-eight AIS patients, with a median age of 69 (58-79) years, were included. sHT occurred in 20 (29.4%) of the 68 patients. The ASTRAL score was significantly higher in patients who developed sHT compared to non-sHT patients [36 (34-38) versus 24 (17-32); p<0.001]. The ASTRAL score was an independent predictor of sHT, and showed good discriminative power (area under the curve 0.88; 95% confidence interval, 0.789-0.965). ASTRAL score is an independent predictor of sHT and shows high predictive accuracy in patients with AIS. Future studies are warranted to confirm these results.

Early Prediction of Functional Outcomes After Acute Ischemic Stroke Using Unstructured Clinical Text: Retrospective Cohort Study.

BackgroundSeveral prognostic scores have been proposed to predict functional outcomes after an acute ischemic stroke (AIS). Most of these scores are based on structured information and have been used to develop prediction models via the logistic regression method. With the increased use of electronic health records and the progress in computational power, data-driven predictive modeling by using machine learning techniques is gaining popularity in clinical decision-making.ObjectiveWe aimed to investigate whether machine learning models created by using unstructured text could improve the prediction of functional outcomes at an early stage after AIS.MethodsWe identified all consecutive patients who were hospitalized for the first time for AIS from October 2007 to December 2019 by using a hospital stroke registry. The study population was randomly split into a training (n=2885) and test set (n=962). Free text in histories of present illness and computed tomography reports was transformed into input variables via natural language processing. Models were trained by using the extreme gradient boosting technique to predict a poor functional outcome at 90 days poststroke. Model performance on the test set was evaluated by using the area under the receiver operating characteristic curve (AUC).ResultsThe AUCs of text-only models ranged from 0.768 to 0.807 and were comparable to that of the model using National Institutes of Health Stroke Scale (NIHSS) scores (0.811). Models using both patient age and text achieved AUCs of 0.823 and 0.825, which were similar to those of the model containing age and NIHSS scores (0.841); the model containing preadmission comorbidities, level of consciousness, age, and neurological deficit (PLAN) scores (0.837); and the model containing Acute Stroke Registry and Analysis of Lausanne (ASTRAL) scores (0.840). Adding variables from clinical text improved the predictive performance of the model containing age and NIHSS scores, the model containing PLAN scores, and the model containing ASTRAL scores (the AUC increased from 0.841 to 0.861, from 0.837 to 0.856, and from 0.840 to 0.860, respectively).ConclusionsUnstructured clinical text can be used to improve the performance of existing models for predicting poststroke functional outcomes. However, considering the different terminologies that are used across health systems, each individual health system may consider using the proposed methods to develop and validate its own models.

Editors' Note: Association of Time of Day When Endovascular Therapy for Stroke Starts and Functional Outcome

In their analysis of the Acute Stroke Registry and Analysis of Lausanne (ASTRAL) and University Hospital of Bern stroke registries, Dr. Hajdu et al. observed a temporal effect of endovascular treatment on outcomes of patients with acute large vessel occlusion. Specifically, patients treated with endovascular thrombectomy between 8 and 11 am were at greater odds of achieving clinical improvement (as determined by a shift in the modified Rankin Scale) when compared with patients treated during other time intervals, whereas patients treated in the late afternoon and early evening were at lower odds of a better functional outcome. These observations were found despite multivariable modeling, including adjustment for delay from symptom onset to endovascular start time, which could have mediated this effect. Dr. Aristizabal-Carmona and colleagues argue that certain physiologic elements, which vary throughout the day, may contribute to this effect on outcomes associated with severe stroke. Whether the effect of treatment time of day is modifiable remains an open question. In their analysis of the Acute Stroke Registry and Analysis of Lausanne (ASTRAL) and University Hospital of Bern stroke registries, Dr. Hajdu et al. observed a temporal effect of endovascular treatment on outcomes of patients with acute large vessel occlusion. Specifically, patients treated with endovascular thrombectomy between 8 and 11 am were at greater odds of achieving clinical improvement (as determined by a shift in the modified Rankin Scale) when compared with patients treated during other time intervals, whereas patients treated in the late afternoon and early evening were at lower odds of a better functional outcome. These observations were found despite multivariable modeling, including adjustment for delay from symptom onset to endovascular start time, which could have mediated this effect. Dr. Aristizabal-Carmona and colleagues argue that certain physiologic elements, which vary throughout the day, may contribute to this effect on outcomes associated with severe stroke. Whether the effect of treatment time of day is modifiable remains an open question.

Preconditioning by Preceding Ischemic Cerebrovascular Events

BackgroundEmerging yet contrasting evidence from animal and human studies associates ischemic preconditioning with improvement of subsequent stroke severity, although long‐term outcome remains unclear. The purpose of this study was to analyze how preceding cerebral ischemic events influence subsequent stroke severity and outcome.Methods and ResultsData for this retrospective cohort study were extracted from ASTRAL (Acute Stroke Registry and Analysis of Lausanne). This registry includes a sample of all consecutive patients with acute ischemic strokes admitted to the stroke unit and/or intensive care unit of the Lausanne University Hospital, Switzerland. We investigated associations between preceding ischemic events (transient ischemic attacks or ischemic strokes) and the impact on subsequent stroke severity and clinical improvement within 24 hours, measured through National Institute of Health Stroke Scale, as well as 3‐month outcome, determined through a shift in the modified Rankin Scale. Of 3530 consecutive patients with ischemic stroke (43% women, median age 73 years), 1001 (28%) had ≥1 preceding cerebral ischemic events (45% transient ischemic attack, 55% ischemic stroke; 31% multiple events). After adjusting for multiple prehospital, clinical, and laboratory confounders, admission stroke severity was significantly lower in patients preconditioned through a preceding ischemic event, but 24‐hour improvement was not significant and 3‐month outcome was unfavorable.ConclusionsPreceding ischemic events were independently associated with a significant reduction in subsequent stroke severity but worsened long‐term clinical outcome. These results, if confirmed by future randomized studies, may help design neuroprotective strategies. The unfavorable effect on stroke outcome is probably a consequence of the cumulative disability burden after multiple ischemic events.

Ischemic stroke on hormonal contraceptives: Characteristics, mechanisms and outcome.

Systemic contraceptives increase the risk of ischemic stroke but little is known about the characteristics, mechanisms and long-term outcome post stroke of patients on hormonal contraception. We sought to To assess characteristics and outcome of acute ischemic stroke (AIS) in young women using systemic hormonal contraceptives (SHC) and compare them to strokes in non-contraceptive users. Using the Acute STroke Registry and Analysis of Lausanne (ASTRAL), we analyzed demographics, risk factors, clinical, radiological and treatment data of consecutive female patients of <50 years between 2003 to 2015. We compared groups with and without SHC in a logistic regression analysis. Of the 179 female patients of <50 years during the observation period, 57 (39.6%) used SHC, 71.9% of whom, a combined oral contraceptive pill. On logistic regression contraceptive users were significantly younger but had comparable stroke severity. They had less migraine with aura and tobacco use, and more hyperlipidaemia. Also, contraceptive users had significantly less intra and extracranial stenosis and occlusion on arterial imaging, but more focal hypoperfusion on CT-perfusion. Undetermined mechanism of stroke was more frequent with SHC users, whereas rare mechanisms were more frequent in non-users. The contraceptive user group had a more favourable adjusted 12-month outcome with significantly fewer ischemic recurrences after stopping systemic contraception in all. Contraceptive users with ischemic strokes are younger and have lesser tobacco use and migraine with aura and more hyperlipidemia. Their stroke mechanism is more often undetermined using a standardised work-up, and their adjusted long-term outcome is more favourable with less stroke recurrence.

Correlation between ASPECTS and Core Volume on CT Perfusion: Impact of Time since Stroke Onset and Presence of Large-Vessel Occlusion.

Both ASPECTS and core volume on CTP are used to estimate infarct volume in acute ischemic stroke. To evaluate the potential role of ASPECTS for acute endovascular treatment decisions, we studied the correlation between ASPECTS and CTP core, depending on the timing and the presence of large-vessel occlusion. We retrospectively reviewed all MCA acute ischemic strokes with standardized reconstructions of CTP maps entered in the Acute STroke Registry and Analysis of Lausanne (ASTRAL) registry. Correlation between ASPECTS and CTP core was determined for early (<6 hours) versus late (6-24 hours) times from stroke onset and in the presence versus absence of large-vessel occlusion. We used correlation coefficients and adjusted multiple linear regression models. We included 1046 patients with a median age of 71.4 years (interquartile range, IQR = 59.8-79.4 years), an NIHSS score of 12 (IQR, 6-18), an ASPECTS of 9 (IQR, 7-10), and a CTP core of 13.6 mL (IQR, 0.6-52.8 mL). The overall correlation between ASPECTS and CTP core was moderate (ρ = -0.49, P < .01) but significantly stronger in the late-versus-early window (ρ = -0.56 and ρ = -0.48, respectively; P = .05) and in the presence versus absence of large-vessel occlusion (ρ = -0.40 and ρ = -0.20, respectively; P < .01). In the regression model, the independent association between ASPECTS and CTP core was confirmed and was twice as strong in late-arriving patients with large-vessel occlusion (β = -0.21 per 10 mL; 95% CI, -0.27 to -0.15; P < .01) than in the overall population (β = -0.10; 95% CI, -0.14 to -0.07; P < .01). In a large cohort of patients with acute ischemic stroke, we found a moderate correlation between ASPECTS and CTP core. However, this was stronger in patients with large-vessel occlusion and longer delay from stroke onset. Our results could support the use of ASPECTS as a surrogate marker of CTP core in late-arriving patients with acute ischemic stroke with large-vessel occlusion.

Stroke chameleons: acute central pain mimicking acute coronary syndrome.

'Stroke chameleons' refer to a group of syndromes that initially are not diagnosed as cerebrovascular events but are then found to represent stroke. The objective of this study was to report on acute ischaemic stroke (AIS) patients with chest or epigastric pain of central origin, clinically resembling an acute coronary syndrome (ACS). A prospective list was kept of AIS patients admitted to our institution between 2002 and 2014 with stroke symptoms appearing as an ACS on first clinical evaluation. For each identified patient, clinical and radiological features, delay to correct diagnosis, stroke etiology and 3-month functional outcome were reviewed. Data were mainly extracted from the Acute Stroke Registry and Analysis of Lausanne (ASTRAL). Five AIS patients presenting mainly with chest or epigastric pain leading to a wrong diagnosis of ACS were identified. Cardiac evaluation showed minor electrocardiogram changes in two patients and isolated troponin elevation in one, subsequently shown to be of non-coronary origin. The correct diagnosis of AIS was made only between 1h and 72h after hospital arrival. Four patients presented a vertebrobasilar stroke. None of the patients received acute stroke revascularization therapy despite two of them being in the time window for such treatment. Acute ischaemic stroke presentation can infrequently resemble an ACS. In cases of negative cardiac work-up, a central origin of chest pain should be considered, especially in the presence of subtle other neurological symptoms or signs. Appropriate diagnosis of stroke could avoid treatment delays and improve outcomes.

Prediction of Outcome in Embolic Strokes of Undetermined Source

Background and AimPredicting outcome after stroke is a major goal and research field. The Embolic Stroke of Undetermined Source (ESUS) is a recently introduced clinical construct, and the prediction of outcome in this population has to be further explored. The aim of the study was to evaluate the prognostic validity and accuracy of the Acute Stroke Registry and Analysis of Lausanne (ASTRAL) score in patients with ESUS. MethodsConsecutive patients hospitalized for acute ischemic stroke who met the ESUS diagnostic criteria were identified and the ASTRAL scores estimated. The study endpoint was the 3-month unfavorable outcome (modified Rankin Scale>2). Predictive performance was investigated through logistic regression analysis and discrimination and calibration tests. ResultsAmong 202 patients with ESUS, 67 (33.2%) had unfavourable 3-month outcome. The ASTRAL score was an independent predictor of poor outcome [adjOR = 1.44, 95% confidence interval (CI) 1.30-1.60, P < .001], showed good discriminatory power (area under the receiver operating characteristic curve .913, 95% CI .871-.956) and was well calibrated (Hosmer-Lemeshow test P = .496). ConclusionsThe ASTRAL score was an independent predictor of 3-month functional outcome and showed high predictive accuracy in patients with ESUS.

Effect of CPAP Treatment of Sleep Apnea on Clinical Prognosis After Ischemic Stroke: An Observational Study.

To evaluate continuous positive airway pressure (CPAP) treatment in patients with moderate to severe sleep-disordered breathing (SDB) after an ischemic stroke. We identified patients included in the Acute Stroke Registry and Analysis of Lausanne (ASTRAL) who underwent polysomnography after an ischemic stroke. We compared patients without significant SDB (apnea-hypopnea index [AHI] < 15 events/h: SDB-), with AHI ≥ 15 events/h who refused CPAP or with poor CPAP adherence (SDB+ CPAP-), and patients with SDB effectively treated by CPAP (SDB+ CPAP+). We analyzed data from 101 patients (age 68.5 ± 11.1 years, 84.1% men). In multivariate analysis the SDB+ CPAP+ group was associated with a significant reduction of stroke recurrence and mortality (odds ratio 0.13, 95% confidence interval 0.00-0.86, P = .031), whereas atrial fibrillation was independently associated with a higher risk (odds ratio 4.32, 95% confidence interval 1.51-12.33, P = .006). Event-free survival analysis (stroke recurrence and death) after 2-year follow-up showed that those in the SDB+ CPAP+ group had significantly higher cardiovascular survival, and Cox proportion hazard model identified CPAP treatment as significantly associated with survival time (P = .025). The AHI and the National Institutes of Health Stroke Scale subacute score were independently associated with CPAP adherence among patients with SDB. This observational study shows that CPAP treatment in stroke patients with moderate to severe SDB is associated with lower rates of stroke recurrence and death.

Machine Learning-Based Model for Prediction of Outcomes in Acute Stroke.

Background and Purpose- The prediction of long-term outcomes in ischemic stroke patients may be useful in treatment decisions. Machine learning techniques are being increasingly adapted for use in the medical field because of their high accuracy. This study investigated the applicability of machine learning techniques to predict long-term outcomes in ischemic stroke patients. Methods- This was a retrospective study using a prospective cohort that enrolled patients with acute ischemic stroke. Favorable outcome was defined as modified Rankin Scale score 0, 1, or 2 at 3 months. We developed 3 machine learning models (deep neural network, random forest, and logistic regression) and compared their predictability. To evaluate the accuracy of the machine learning models, we also compared them to the Acute Stroke Registry and Analysis of Lausanne (ASTRAL) score. Results- A total of 2604 patients were included in this study, and 2043 (78%) of them had favorable outcomes. The area under the curve for the deep neural network model was significantly higher than that of the ASTRAL score (0.888 versus 0.839; P<0.001), while the areas under the curves of the random forest (0.857; P=0.136) and logistic regression (0.849; P=0.413) models were not significantly higher than that of the ASTRAL score. Using only the 6 variables that are used for the ASTRAL score, the performance of the machine learning models did not significantly differ from that of the ASTRAL score. Conclusions- Machine learning algorithms, particularly the deep neural network, can improve the prediction of long-term outcomes in ischemic stroke patients.

Determining factors of better leptomeningeal collaterals: a study of 857 consecutive acute ischemic stroke patients.

In acute ischemic stroke (AIS) collaterals correlate with infarct size, recanalization rate and clinical outcome. We aimed to identify factors associated with better collateral status in a large series of AIS patients with middle cerebral artery (MCA) occlusion. In the Acute STroke Registry and Analysis of Lausanne (ASTRAL) from 2003 to 2016, we identified all consecutive AIS with proximal MCA occlusion on CT-angiography performed < 24h. Collaterals were scored from 0 (absent) to 3 (≥ 100%) and related to multiple demographic, clinical, metabolic and radiological variables in a multivariate regression analysis (MVA). The 857 included patients had a median age of 72.3years, 48.4% were female and median admission NIHSS was 16. Better collaterals were associated with younger age (OR 0.99; 95% CI 0.98-1.00), hemineglect (OR 1.35; 95% CI 1.03-1.76), absence of visual field defects (OR 0.64; 95% CI 0.46-0.90), eye deviation (OR 0.58; 95% CI 0.43-0.79) and decreased vigilance (OR 0.62; 95% CI 0.44-0.88). Better collaterals were also associated with dyslipidemia (OR 1.57; 95% CI 1.16-2.13), no previous statin use (OR 0.69; 95% CI 0.50-0.95), and lower creatinine levels (OR 0.99; 95% CI 0.99-1.00). On neuroimaging, better collaterals related to higher ASPECTS score (OR 1.27; 95% CI 1.20-1.35) and higher clot burden score (OR 1.09; 95% CI 1.03-1.14). Younger age, dyslipidemia and lower creatinine levels were predictors of better collaterals in AIS patients from proximal MCA occlusions. Greater degree of collaterals related to lower stroke severity on admission. On neuroimaging, better collaterals were independently associated with minor early ischemic changes and lower clot burden. These data may add knowledge on pathophysiology of collaterals development and may help to identify patients with better collaterals for late or aggressive recanalization treatments.

Skiing Associated Stroke: Causes, Treatment, and Outcome

BackgroundPrevious studies have described ischemic stroke temporally related to specific triggers, but only 1 series collected patients with acute ischemic stroke (AIS) following downhill skiing and all caused by cervical artery dissections. Here we describe our series of AIS temporally associated to ski practice, focusing on the frequency, pathogenesis, clinical presentation, and prognosis. MethodsWe maintained a prospective list of Skiing Associated Strokes (SASs) from 2003 to 2017. From all AIS patients included in our stroke registry Acute Stroke Registry and Analysis of Lausanne (ASTRAL) over the same period, we identified a comparison group of non-SAS patients, matched for age and gender. ResultsIn the 12-year observation period, we identified 17 SASs (4 females, median age 51 years) and 51 matched control patients with nonski-associated strokes. Vascular risk factors, stroke features, and outcome were similar between the 2 groups. Stroke mechanism was arterial dissection in 11 of 17 SASs (65%) and in 7 of 51 control patients (14%, chi-square test: P < .05). In the other 6 cases of ski-associated stroke, etiology was cardiac embolism from atrial fibrillation in 2 patients, large vessel atherosclerosis with stenosis >50% in 1 patient, and undetermined in 3. Among the 11 patients with SAS caused by dissection, 8 reported minor falls while skiing, 1 had a major head trauma without loss of consciousness, and 2 had no traumatism (compared to preceding trauma in 29 of 147 [20%] of all other AIS caused by arterial dissection in ASTRAL, P < .01). ConclusionsArterial dissection was a significantly more frequent stroke mechanism in SAS compared to matched controls, but other mechanisms occurred as well. Minor or moderate skiing-related trauma preceded most SAS with dissections.

Perfusion computed tomography in posterior circulation stroke: predictors and prognostic implications of focal hypoperfusion.

The aim was to determine the predictors of focal hypoperfusion on computed tomography (CT) perfusion (CTP) in patients with acute posterior circulation stroke and its association with long-term outcome. Patients with posterior circulation stroke were selected from the Acute Stroke Registry and Analysis of Lausanne (ASTRAL) who underwent CTP within 24h of stroke onset as part of the stroke imaging protocol. Hypoperfusion was defined as an area of visually well demarcated mean transit time prolongation corresponding to an arterial territory on standard reconstruction CTP imaging maps. Areas of hypoperfusion were assessed with the posterior circulation Acute Stroke Prognosis Early CT Score. Clinical and imaging associations with focal hypoperfusion were identified using multiple imputation analyses, and the adjusted functional outcome measured by the modified Rankin Scale at 3 and 12months was determined. Of the 3595 consecutive patients from the ASTRAL registry between 2003 and 2014, 1070 (29.7%) had a posterior circulation stroke and 436 of these (40.7%) patients had a good quality baseline CTP. 23.1% had early ischaemic changes and 37.4% had focal hypoperfusion. In multiple imputation analysis, visual field deficits, reduced level of consciousness, cardiac and multiple stroke mechanisms, significant vessel pathology and ischaemic changes visible on plain CT were associated with focal hypoperfusion. Focal hypoperfusion was independently associated with outcome at 12months (odds ratio 2.04, 95% confidence interval 1.22-3.42, P<0.01). In posterior circulation stroke patients undergoing acute CTP, multiple clinical, aetiological and radiological variables were associated with focal hypoperfusion. Patients with focal hypoperfusion had a worse 12-month outcome.

Abstract TP45: Predictors for Good Collaterals in 857 Patients With Acute Ischemic Stroke and Proximal Middle Cerebral Artery Occlusion

Background: Good collaterals in acute ischemic stroke (AIS) correlate with smaller infarct size, improved outcome, and better recanalization rates after revascularisation treatments. Given that the variables determining collateral circulation are poorly understood, we aimed to identify predictors of good collaterals in a large series of AIS with middle cerebral artery (MCA) occlusion. Methods: In the Acute STroke Registry and Analysis of Lausanne (ASTRAL) from 2003 to 2016, we identified all AIS with MCA occlusion (M1 or proximal M2) on CT angiography (CTA) performed within 24 hours. Collaterals were graded from 0 (absent) to 3 (100% or more) and classified as good (grades 2 and 3) or poor. We correlated collateral status with various clinical, metabolic and radiological variables in a univariate, then multivariate regression analyses (MVA). Results: Of the 2’027 patients with AIS involving the MCA and good quality CTA during the study period, 857 met the inclusion criteria. Median age was 72.3±20.5 years, 48.4% were females, and median admission NIHSS was 16±9. Younger age (OR=0.99, confidence interval (CI) 0.98-0.99) and lower NIHSS on admission (OR=0.92, CI=0.90-0.94) were significantly associated with good collaterals. Hyperglycemia (OR=0.94, CI=0.88-0.99) and higher creatininemia (OR=0.99, CI=0.99-1) correlated with poor collaterals. The distribution of vascular risk factors was similar. Radiologically, good collateral status was predicted by higher ASPECTS score (OR=1.31, CI=1.24-1.40), absence of a hyperdense MCA sign (OR=0.60, CI=0.46-0.79), lower clot burden (OR=1.18, CI=1.12-1.24) and absence of proximal intracranial arterial pathology (OR=0.44, CI=0.33-0.58). MVA results will be presented. Conclusion: Good collaterals are associated with lower age and lower NIHSS, whereas high blood glucose and creatinine values predicted poor collaterals. On neuroimaging, minor early ischemic changes, lower clot burden and distal site of vascular occlusion correlated with good collaterals. These data may predict stroke outcome in certain patients, explain futile recanalisation, and help select patients for late or aggressive recanalisation treatments independently of time windows.