Determinants of door-in-door-out time in patients with ischaemic stroke transferred for endovascular thrombectomy.

BACKGROUND: Long door-in-door-out (DIDO) times are an important cause of treatment delay in patients transferred for endovascular thrombectomy (EVT) from primary stroke centres (PSC) to an intervention centre. Insight in causes of prolonged DIDO times may facilitate process improvement interventions. We aimed to quantify different components of DIDO time and to identify determinants of DIDO time. METHODS: We performed a retrospective cohort study in a Dutch ambulance region consisting of six PSCs and one intervention centre. We included consecutive adult patients with anterior circulation large vessel occlusion, transferred from a PSC for EVT between October 1, 2019 and November 31, 2020. We subdivided DIDO into several time components and quantified contribution of these components to DIDO time. We used univariable and multivariable linear regression models to explore associations between potential determinants and DIDO time. RESULTS: We included 133 patients. Median (IQR) DIDO time was 66 (52-83) min. The longest component was CTA-to-ambulance notification time with a median (IQR) of 24 (16-37) min. DIDO time increased with age (6 min per 10 years, 95% CI: 2-9), onset-to-door time outside 6 h (20 min, 95% CI: 5-35), M2-segment occlusion (15 min, 95% CI: 4-26) and right-sided ischaemia (12 min, 95% CI: 2-21). CONCLUSIONS: The CTA-to-ambulance notification time is the largest contributor to DIDO time. Higher age, onset-to-door time longer than 6 h, M2-segment occlusion and right-sided occlusions are independently associated with a longer DIDO time. Future interventions that aim to decrease DIDO time should take these findings into account.

Comparison of eight prehospital stroke scales to detect intracranial large-vessel occlusion in suspected stroke (PRESTO): a prospective observational study.

BACKGROUND: Due to the time-sensitive effect of endovascular treatment, rapid prehospital identification of large-vessel occlusion in individuals with suspected stroke is essential to optimise outcome. Interhospital transfers are an important cause of delay of endovascular treatment. Prehospital stroke scales have been proposed to select patients with large-vessel occlusion for direct transport to an endovascular-capable intervention centre. We aimed to prospectively validate eight prehospital stroke scales in the field. METHODS: We did a multicentre, prospective, observational cohort study of adults with suspected stroke (aged ≥18 years) who were transported by ambulance to one of eight hospitals in southwest Netherlands. Suspected stroke was defined by a positive Face-Arm-Speech-Time (FAST) test. We included individuals with blood glucose of at least 2·5 mmol/L. People who presented more than 6 h after symptom onset were excluded from the analysis. After structured training, paramedics used a mobile app to assess items from eight prehospital stroke scales: Rapid Arterial oCclusion Evaluation (RACE), Los Angeles Motor Scale (LAMS), Cincinnati Stroke Triage Assessment Tool (C-STAT), Gaze-Face-Arm-Speech-Time (G-FAST), Prehospital Acute Stroke Severity (PASS), Cincinnati Prehospital Stroke Scale (CPSS), Conveniently-Grasped Field Assessment Stroke Triage (CG-FAST), and the FAST-PLUS (Face-Arm-Speech-Time plus severe arm or leg motor deficit) test. The primary outcome was the clinical diagnosis of ischaemic stroke with a proximal intracranial large-vessel occlusion in the anterior circulation (aLVO) on CT angiography. Baseline neuroimaging was centrally assessed by neuroradiologists to validate the true occlusion status. Prehospital stroke scale performance was expressed as the area under the receiver operating characteristic curve (AUC) and was compared with National Institutes of Health Stroke Scale (NIHSS) scores assessed by clinicians at the emergency department. This study was registered at the Netherlands Trial Register, NL7387. FINDINGS: Between Aug 13, 2018, and Sept 2, 2019, 1039 people (median age 72 years [IQR 61-81]) with suspected stroke were identified by paramedics, of whom 120 (12%) were diagnosed with aLVO. Of all prehospital stroke scales, the AUC for RACE was highest (0·83, 95% CI 0·79-0·86), followed by the AUC for G-FAST (0·80, 0·76-0·84), CG-FAST (0·80, 0·76-0·84), LAMS (0·79, 0·75-0·83), CPSS (0·79, 0·75-0·83), PASS (0·76, 0·72-0·80), C-STAT (0·75, 0·71-0·80), and FAST-PLUS (0·72, 0·67-0·76). The NIHSS as assessed by a clinician in the emergency department did somewhat better than the prehospital stroke scales with an AUC of 0·86 (95% CI 0·83-0·89). INTERPRETATION: Prehospital stroke scales detect aLVO with acceptable-to-good accuracy. RACE, G-FAST, and CG-FAST are the best performing prehospital stroke scales out of the eight scales tested and approach the performance of the clinician-assessed NIHSS. Further studies are needed to investigate whether use of these scales in regional transportation strategies can optimise outcomes of patients with ischaemic stroke. FUNDING: BeterKeten Collaboration and Theia Foundation (Zilveren Kruis).

Prediction of major vascular events in patients with transient ischemic attack or ischemic stroke: a comparison of 7 models.

BACKGROUND AND PURPOSE: In patients with a recent TIA or minor stroke, prediction of long-term risk of major vascular events is important, but difficult. We aimed to study the external validity of currently available prediction models. METHODS: We validated predictions from 3 population-based models (Framingham, SCORE, and INDIANA project) and 4 stroke cohort-based models (Stroke Prognosis Instrument II, Oxford TIA, Dutch TIA study, and the ABCD(2) study) in an independent cohort of patients with a recent TIA or minor stroke. The validation cohort consisted of 592 patients with TIA or minor stroke, with a mean follow-up of 2 years. The primary outcome was the 2-year risk of the composite outcome event of nonfatal stroke, myocardial infarction, or vascular death. We used calibration graphs and c-statistics to evaluate the 7 models. RESULTS: The 2-year risk of the primary outcome event was 12%. Calibration was adequate for stroke population-based studies. After adjustment for baseline risk and for prevalence of risk factors, calibration was adequate for the Dutch TIA, the ABCD(2), and Stroke Prognosis Instrument II models. Discrimination ranged from 0.61 to 0.68. CONCLUSIONS: Discrimination was poor for all currently available risk prediction models for patients with a recent TIA or minor stroke, indicating the need for stronger predictors. Clinical usefulness may be best for the ABCD(2) model, which had a limited number of easily obtainable variables, a reasonable c-statistic (0.64), and good calibration.

Inadequate acoustical temporal bone window in patients with a transient ischemic attack or minor stroke: role of skull thickness and bone density.

Transcranial Doppler (TCD) ultrasonography may provide important diagnostic and prognostic information in patients with ischemic stroke or transient ischemic attack. TCD also enhances the effect of thrombolytic treatment in patients with acute stroke. In some patients, especially elderly women, TCD cannot be performed because of temporal bone window failure (WF). We investigated whether skull thickness or bone density on computed tomography scans predicts WF. In 182 patients with a transient ischemic attack or minor ischemic stroke, skull thickness and bone density measurements were made at the level of the temporal bone window. Multiple logistic regression analysis was used to relate independent variables to WF and to adjust the estimates for possible confounding factors. TCD signals were absent on the symptomatic side in 22 female and 11 male patients (18%). Both skull thickness and radiodensity at the level of the temporal bone window were strongly related to WF as well as age and female gender. After adjustment according to age and gender, skull thickness at the temporal bone window was an independent prognostic factor of WF (odds ratio [OR]: 2.3 per mm increase in skull thickness, 95% confidence interval [CI]: 1.4 to 3.8). Radiodensity of the temporal bone decreased with age in women (-52 HU per 10 y over 50 y of age, 95% CI: -73 to -30) but in men (-10 HU per 10 y over 50 y of age, 95% CI: -33 to 13), no statistically significant association was observed. We computed probabilities of WF for each patient individually. With a probability cut point of 50%, 33% of the patients with WF and 97% of the patient without WF were correctly identified. The area under the receiver operating characteristic (ROC) curve of this simple prediction model including age, gender and skull thickness was 0.88; the area under the ROC curve of a gender-stratified model including age, skull thickness and radiodensity was 0.90. This difference was not statistically or clinically significant p = 0.13). WF is more common in women because density of the temporal bone in elderly women is low. Absence of WF can be predicted by a combination of three simple parameters: skull thickness, age and gender. This may help to select patients with ischemic stroke for diagnostic TCD screening and to facilitate targeted delivery of ultrasound-enhanced thrombolysis.

Relationships of transcranial blood flow Doppler parameters with major vascular risk factors: TCD study in patients with a recent TIA or nondisabling ischemic stroke.

PURPOSE: The relationship between intracranial vascular disease and cardiovascular risk factors such as smoking, hypertension, diabetes mellitus, and total serum cholesterol in patients with recent cerebral ischemia is not well established. We used transcranial Doppler (TCD) sonography tests as parameters of intracranial vascular disease and investigated the relationship between these parameters and conventional cardiovascular risk factors. METHODS: We prospectively studied 598 patients with a minor ischemic stroke or transient ischemic attack (TIA). In all patients, flow velocities in the left and right middle cerebral artery (MCA), and cerebrovascular reactivity to CO2 were measured by means of TCD sonography. Student's t-test and linear regression analysis were used to determine the relationship between the baseline characteristics, vascular risk factors, and TCD parameters. RESULTS: After adjustment for other vascular risk factors, a statistically significant relationship with mean flow velocity in the MCA was found for age (3.5 cm/s/10 years of age; 95% CI, 2.5-4.5 cm/s/10 years of age; p < 0.0001), sex (-2.9 cm/s for male sex; 95% CI, -5.5 to -0.3 cm/s; p = 0.03), diabetes (5.6 cm/s for diabetics; 95% CI, 2.1-9.1 cm/s; p = 0.002), and total serum cholesterol (2.4 cm/s per mmol increase in total serum cholesterol; 95% CI, 1.4-3.5 cm/s; p < 0.0001). Total serum cholesterol and hypertension were related to cerebrovascular reactivity to CO2. CONCLUSIONS: Cerebral flow velocity is influenced by multiple interacting factors. Results of TCD investigations should be adjusted for age, sex, diabetes, and cholesterol when used for diagnostic or prognostic purposes.