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We present information on acute stroke care for the first wave of the COVID-19 pandemic in Australia using data from the Australian Stroke Clinical Registry (AuSCR). The first case of COVID-19 in Australia was recorded in late January 2020 and national restrictions to control the virus commenced in March. To account for seasonal effects of stroke admissions, patient-level data from the registry from January to June 2020 were compared to the same period in 2019 (historical-control) from 61 public hospitals. We compared periods using descriptive statistics and performed interrupted time series analyses. Perceptions of stroke clinicians were obtained from 53/72 (74%) hospitals participating in the AuSCR (80% nurses) via a voluntary, electronic feedback survey. Survey data were summarized to provide contextual information for the registry-based analysis. Data from the registry covered locations that had 91% of Australian COVID-19 cases to the end of June 2020. For the historical-control period, 9,308 episodes of care were compared with the pandemic period (8,992 episodes). Patient characteristics were similar for each cohort (median age: 75 years; 56% male; ischemic stroke 69%). Treatment in stroke units decreased progressively during the pandemic period (control: 76% pandemic: 70%, p < 0.001). Clinical staff reported fewer resources available for stroke including 10% reporting reduced stroke unit beds. Several time-based metrics were unchanged whereas door-to-needle times were longer during the peak pandemic period (March-April, 2020; 82 min, control: 74 min, p = 0.012). Our data emphasize the need to maintain appropriate acute stroke care during times of national emergency such as pandemic management.
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BACKGROUND: Prognostication following hypoxic ischemic encephalopathy (brain injury) is important for clinical management. The aim of this exploratory study is to use a decision tree model to find clinical and MRI associates of severe disability and death in this condition. We evaluate clinical model and then the added value of MRI data. METHOD: The inclusion criteria were as follows: age ≥17 years, cardio-respiratory arrest, and coma on admission (2003-2011). Decision tree analysis was used to find clinical [Glasgow Coma Score (GCS), features about cardiac arrest, therapeutic hypothermia, age, and sex] and MRI (infarct volume) associates of severe disability and death. We used the area under the ROC (auROC) to determine accuracy of model. There were 41 (63.7% males) patients having MRI imaging with the average age 51.5 ± 18.9 years old. The decision trees showed that infarct volume and age were important factors for discrimination between mild to moderate disability and severe disability and death at day 0 and day 2. The auROC for this model was 0.94 (95% CI 0.82-1.00). At day 7, GCS value was the only predictor; the auROC was 0.96 (95% CI 0.86-1.00). CONCLUSION: Our findings provide proof of concept for further exploration of the role of MR imaging and decision tree analysis in the early prognostication of hypoxic ischemic brain injury.
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BACKGROUND AND AIM: The availability and access of hospital administrative data [coding for Charlson comorbidity index (CCI)] in large data form has resulted in a surge of interest in using this information to predict mortality from stroke. The aims of this study were to determine the minimum clinical data set to be included in models for predicting disability after ischemic stroke adjusting for CCI and clinical variables and to evaluate the impact of CCI on prediction of outcome. METHOD: We leverage anonymized clinical trial data in the Virtual International Stroke Trials Archive. This repository contains prospective data on stroke severity and outcome. The inclusion criteria were patients with available stroke severity score such as National Institutes of Health Stroke Scale (NIHSS), imaging data, and outcome disability score such as 90-day Rankin Scale. We calculate CCI based on comorbidity data in this data set. For logistic regression, we used these calibration statistics: Nagelkerke generalised R2 and Brier score; and for discrimination we used: area under the receiver operating characteristics curve (AUC) and integrated discrimination improvement (IDI). The IDI was used to evaluate improvement in disability prediction above baseline model containing age, sex, and CCI. RESULTS: The clinical data among 5,206 patients (55% males) were as follows: mean age 69 ± 13 years, CCI 4.2 ± 0.8, and median NIHSS of 12 (IQR 8, 17) on admission and 9 (IQR 5, 15) at 24 h. In Model 2, adding admission NIHSS to the baseline model improved AUC from 0.67 (95% CI 0.65-0.68) to 0.79 (95% CI 0.78-0.81). In Model 3, adding 24-h NIHSS to the baseline model resulted in substantial improvement in AUC to 0.90 (95% CI 0.89-0.91) and increased IDI by 0.23 (95% CI 0.22-0.24). Adding the variable recombinant tissue plasminogen activator did not result in a further change in AUC or IDI to this regression model. In Model 3, the variable NIHSS at 24 h explains 87.3% of the variance of Model 3, follow by age (8.5%), comorbidity (3.7%), and male sex (0.5%). CONCLUSION: Our results suggest that prediction of disability after ischemic stroke should at least include 24-h NIHSS and age. The variable CCI is less important for prediction of disability in this data set.
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BACKGROUND: Evidence of a decline in the incidence of stroke has emerged from population-based studies. These have included retrospective and prospective cohorts. However, in Australia and other countries, government bodies and stroke foundations predict a rise in the prevalence of stroke that is anticipated to increase the burden of stroke across the entire domain of care. This increase in prevalence must be viewed as different from the decline in incidence being observed, a measure of new stroke cases. In Victoria, all public emergency department visits and public and private hospital admissions are reported to the Department of Health and Human Services and include demographic, diagnostic, and procedural/treatment information. METHODS: We obtained data from financial years 1997/1998 to 2007/2008 inclusive, for all cases with a primary stroke diagnosis (ICD-10-AM categories) with associated data fields. Incident cases were established by using a 5-year clearance period. RESULTS: From 2003/2004 to 2007/2008 inclusive, there were 53,425 patients with a primary stroke or TIA diagnosis. The crude incident stroke rate for first ever stroke was 211 per 100,000 per year (95% CI 205-217) [females-205 per 100,000 per year (95% CI 196-214) and males-217 per 100,000 per year (95% CI 210-224)]. The overall stroke rates were seen to significantly decline over the period [males (per 100,000 per year) 227 in 2003/2004 to 202 in 2007/2008 (p = 0.0157) and females (per 100,000 per year) 214 in 2003/2004 to 188 in 2007/2008 (p = 0.0482)]. Ischemic stroke rates also appeared to decline; however, this change was not significant. CONCLUSION: These results demonstrate a significant decline in stroke incidence during the study period and may suggest evidence for effectiveness of primary and secondary prevention strategies in cerebrovascular risk factor management.
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BACKGROUND: Lacunar infarct has been characterized as small subcortical infarct. It is postulated to occur from "in situ microatheroma or lipohyalinosis" in small vessel or lacunar mechanism. Based on this idea, such infarcts by lacunar mechanism should not be associated with large area of perfusion deficits that extend beyond the subcortical region to the cortical region. By contrast, selected small subcortical infarcts, as defined by MR imaging in the subacute and chronic stage, may initially have large perfusion deficit or related large vessel occlusions. These infarcts with "lacunar" phenotype may also be caused by disease in the parent vessel and may have very different stroke mechanism from small vessel disease. Our aim is to describe differences in imaging characteristics between patients with small subcortical infarction with "lacunar phenotype" from those with lacunar mechanism. MATERIALS AND METHODS: Patients undergoing acute CT perfusion/angiography (CTP/CTA) within 6 h of symptom onset and follow-up magnetic resonance imaging (MRI) for ischemic stroke were included (2009-2013). Lacunar infarct was defined as a single subcortical infarct ≤20 mm on follow-up MRI. Presence of perfusion deficits, vessel occlusion, and infarct dimensions was compared between lacunar infarcts and other topographical infarct types. RESULTS: Overall, 182 patients (mean age 66.4 ± 15.3 years, 66% males) were included. Lacunar infarct occurred in 31 (17%) patients. Of these, 12 (39%) patients had a perfusion deficit compared with those with any cortical infarction (120/142, 67%), and the smallest lacunar infarct with a perfusion deficit had a diameter of <5 mm. The majority of patients with lacunar infarction (8/12, 66.7%) had a relevant vessel occlusion. A quarter of lacunar infarcts had a large artery stroke mechanism evident on acute CTP/CTA. Lacunar mechanism was present in 3/8 patients with corona radiata, 5/10 lentiform nucleus, 5/6 posterior limb of internal capsule (PLIC), 3/5 thalamic infarcts, 1/2 miscellaneous locations. There was a trend to significant with regards to finding lacunar mechanism among patients with thalamic and PLIC infarcts versus lentiform nucleus and corona radiata infarcts (p = 0.13). CONCLUSION: Diverse stroke mechanisms were present among subcortical infarcts in different locations. When available acute CTP/CTA should be combined with subacute imaging of subcortical infarct to separate "lacunar phenotype" from those with lacunar mechanism.