BACKGROUND: Endovascular treatment (EVT) has revolutionized the standard treatment of vertebrobasilar artery occlusion (VBAO) with moderate infarct core, but its effectiveness in patients with a low posterior circulation Acute Stroke Prognosis Early CT Score (pc-ASPECTS) is unclear. This study aimed to assess EVT effects in VBAO patients with pc-ASPECTS <6.
METHODS: This retrospective study enrolled patients with VBAO within 24 hours of the estimated occlusion time at 65 stroke centers in a nationwide registration in China. The primary outcome was a favorable shift in the modified Rankin Scale (mRS) at 90 days. The secondary outcomes included a favorable outcome (mRS 0-3) and functional independence (mRS 0-2). Propensity score matching and inverse probability of treatment weighting were used to compare the outcomes of patients treated with EVT and those with best medical management.
RESULTS: A total of 431 patients with VBAO and pc-ASPECTS <6 were included. EVT was associated with a favorable shift in the mRS score at 90 days (OR 1.72, 95% CI 1.19 to 2.5), a higher probability of a favorable outcome (OR 1.66, 95% CI 1.02 to 2.74), and improved functional independence (OR 1.76, 95% CI 1.06 to 2.96). EVT also significantly reduced the risk of 90-day mortality (OR 0.62, 95% CI 0.40 to 0.96), but increased the risk of symptomatic intracranial hemorrhage (OR 2.76, 95% CI 1.06 to 8.58).
CONCLUSIONS: The results of this study suggest that EVT may be a safe and effective treatment option for patients with VBAO and pc-ASPECTS <6. Further studies are needed to investigate the effect of EVT in patients with pc-ASPECTS <6 and to identify patients who may benefit from EVT.

Heart failure (HF) is one of the most common diagnoses on admission to hospital in Germany, and one which incurs high costs. Integrated care in case management programs (CMPs) aims to improve treatment quality in the sense of guideline-driven treatment, while reducing hospital admissions, hospital costs, and mortality. A total of 1,844 patient data records from 11 German statutory health insurance companies enrolled in the CMP (intervention group [IG]) were compared with 1,844 standard-care patients (control group) using propensity score matching. The two groups were assessed over three follow-up observation periods regarding the endpoints\' treatment costs, hospitalization rate, indicators for treatment quality (diagnostics, physician contact), and mortality. The evaluation revealed no significant differences regarding overall costs. The IG incurred significantly higher outpatient costs, but the medication costs and inpatient costs were not significantly different. There were also no significant differences in the number of hospital admissions. Patients within the CMP had significantly more frequent contact with a cardiologist, and underwent echocardiographic examination significantly more frequently. Mortality during the first follow-up observation year was considerably more favorable for the IG. There are indications that treatment quality is improved in HF patients.

UNASSIGNED: The application of machine learning in health care often necessitates the use of hierarchical codes such as the International Classification of Diseases (ICD) and Anatomical Therapeutic Chemical (ATC) systems. These codes classify diseases and medications, respectively, thereby forming extensive data dimensions. Unsupervised feature selection tackles the \"curse of dimensionality\" and helps to improve the accuracy and performance of supervised learning models by reducing the number of irrelevant or redundant features and avoiding overfitting. Techniques for unsupervised feature selection, such as filter, wrapper, and embedded methods, are implemented to select the most important features with the most intrinsic information. However, they face challenges due to the sheer volume of ICD and ATC codes and the hierarchical structures of these systems.
UNASSIGNED: The objective of this study was to compare several unsupervised feature selection methods for ICD and ATC code databases of patients with coronary artery disease in different aspects of performance and complexity and select the best set of features representing these patients.
UNASSIGNED: We compared several unsupervised feature selection methods for 2 ICD and 1 ATC code databases of 51,506 patients with coronary artery disease in Alberta, Canada. Specifically, we used the Laplacian score, unsupervised feature selection for multicluster data, autoencoder-inspired unsupervised feature selection, principal feature analysis, and concrete autoencoders with and without ICD or ATC tree weight adjustment to select the 100 best features from over 9000 ICD and 2000 ATC codes. We assessed the selected features based on their ability to reconstruct the initial feature space and predict 90-day mortality following discharge. We also compared the complexity of the selected features by mean code level in the ICD or ATC tree and the interpretability of the features in the mortality prediction task using Shapley analysis.
UNASSIGNED: In feature space reconstruction and mortality prediction, the concrete autoencoder-based methods outperformed other techniques. Particularly, a weight-adjusted concrete autoencoder variant demonstrated improved reconstruction accuracy and significant predictive performance enhancement, confirmed by DeLong and McNemar tests (P<.05). Concrete autoencoders preferred more general codes, and they consistently reconstructed all features accurately. Additionally, features selected by weight-adjusted concrete autoencoders yielded higher Shapley values in mortality prediction than most alternatives.
UNASSIGNED: This study scrutinized 5 feature selection methods in ICD and ATC code data sets in an unsupervised context. Our findings underscore the superiority of the concrete autoencoder method in selecting salient features that represent the entire data set, offering a potential asset for subsequent machine learning research. We also present a novel weight adjustment approach for the concrete autoencoders specifically tailored for ICD and ATC code data sets to enhance the generalizability and interpretability of the selected features.

暂无摘要。

BACKGROUND: Treatment of anterior cerebral artery (ACA) aneurysms is still not well established. The Leo stent with blood flow direction is a retrievable stent for intracranial aneurysms, whereas it needs to be studied clearly in patients with ACA aneurysms.
METHODS: Consecutive patients with ACA aneurysms were retrospectively enrolled in three neurosurgical centers between January 2016 and October 2021. The data on demographics, aneurysm characteristics, symptom resolution, and postoperative course were collected and analyzed. The aneurysm occlusion status was appraised by Raymond-Ray Occlusion Class (RROC).
RESULTS: A total of 57 patients with ACA aneurysms were included in our study. Immediate postprocedural angiograms showed that 20 aneurysms (35.1%) were in complete occlusion (RROC 1), 26 aneurysms (45.6%) were in near-complete occlusion (RROC 2), 11 aneurysms (19.3%) were in incomplete occlusion (RROC 3). The angiographic follow-up found that the rate of complete occlusion increased to 57.9%, and near-completion and incomplete occlusion dropped to 29.8% and 12.3%, respectively. The angiographic result of the last follow-up improved significantly (Z=- 2.805, P=0.005). Univariate analysis indicated that distal location of aneurysms (Z=4.538, P=0.033) and ruptured aneurysms (χ2=.6120, P=0.032) were potential risk factors for intra-parent artery narrowing. Furthermore, multivariate logistic regression analysis found that A3 aneurysms (95% CI 1.427~32.744, P=0.016) are the key risk factor for intra-parent artery narrowing.
CONCLUSIONS: The Leo stent is safe and effective for aneurysms located in ACA circulations. The overall occlusion degree improved during follow-up. A distal, small artery was the risk factor for intra-parent artery narrowing.

BACKGROUND: Robust collateral circulation has been linked with better reperfusion and clinical outcomes. It remains unclear how individual assessments of collateral circulation may be translated into clinical practice.
METHODS: The pooled Highly Effective Reperfusion Evaluated in Multiple Endovascular Stroke Trials (HERMES) angiography dataset was analyzed by a centralized, independent imaging core blinded to other clinical data. Conventional angiography was acquired immediately prior to endovascular therapy. Collaterals were graded with the American Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology (ASITN) system and associated with baseline patient characteristics, reperfusion, and day 90 modified Rankin Score (mRS). Both 90-day all-cause mortality and day 90 mRS were modeled via multivariable logistic regression.
RESULTS: Angiography was available in 376/605 (62%) patients. Baseline ASPECTS (Alberta Stroke Program Early CT Score) (p=0.043), history of diabetes mellitus (p=0.048), site of occlusion (p<0.001), and degree of subsequent Thrombolysis in Cerebral Infarction (TICI) reperfusion (p<0.001) were associated with collateral grades. ASITN collateral grade was strongly associated with ordinal mRS from baseline to 90 days in an unadjusted analysis (p<0.001). Multivariable regression demonstrated that collateral status is a strong determinant of mRS outcome in the presence of other predictors (OR=1.37 per grade, 95% CI [1.05 to 1.74], p=0.018). By comparing ORs, 1 unit of ASITN was determined to be approximately equivalent to 4.5 points of NIHSS, 11 years of age, 1.5 points of ASPECTS, or 100 min less delay from onset to puncture, in terms of impact on mRS.
CONCLUSIONS: Individual collateral physiology may contribute significantly to reperfusion success and clinical outcomes after acute ischemic stroke. Building a consensus for the role of angiographic collateral assessment in the allocation of adjuvant reperfusion therapies may help galvanize a precision medicine approach in stroke.

暂无摘要。

UNASSIGNED: Arterial injury is extremely rare after total knee arthroplasty.
METHODS: We describe a 68-year-old woman with dislocation of total knee arthroplasty after falling from a height. She had a popliteal artery injury and a vascular bypass was performed in delay. The patient died of a second myocardial infarction 3.5 months after her first introduction to our center.
UNASSIGNED: Due to the prominent risk of vascular injuries after dislocation in TKA patients, we recommend performing vascular evaluations using CT angiography for all patients.
CONCLUSIONS: Any untreated vascular compromise in the setting of TKA dislocation may lead to devastating outcomes such as amputation and death.

BACKGROUND: Carotid web (CaW) is a risk factor for ischemic stroke, mainly in young patients with stroke of undetermined etiology. Its detection is challenging, especially among non-experienced physicians.
METHODS: We included patients with CaW from six international trials and registries of patients with acute ischemic stroke. Identification and manual segmentations of CaW were performed by three trained radiologists. We designed a two-stage segmentation strategy based on a convolutional neural network (CNN). At the first stage, the two carotid arteries were segmented using a U-shaped CNN. At the second stage, the segmentation of the CaW was first confined to the vicinity of the carotid arteries. Then, the carotid bifurcation region was localized by the proposed carotid bifurcation localization algorithm followed by another U-shaped CNN. A volume threshold based on the derived CaW manual segmentation statistics was then used to determine whether or not CaW was present.
RESULTS: We included 58 patients (median (IQR) age 59 (50-75) years, 60% women). The Dice similarity coefficient and 95th percentile Hausdorff distance between manually segmented CaW and the algorithm segmented CaW were 63.20±19.03% and 1.19±0.9 mm, respectively. Using a volume threshold of 5 mm3, binary classification detection metrics for CaW on a single artery were as follows: accuracy: 92.2% (95% CI 87.93% to 96.55%), precision: 94.83% (95% CI 88.68% to 100.00%), sensitivity: 90.16% (95% CI 82.16% to 96.97%), specificity: 94.55% (95% CI 88.0% to 100.0%), F1 measure: 0.9244 (95% CI 0.8679 to 0.9692), area under the curve: 0.9235 (95%CI 0.8726 to 0.9688).
CONCLUSIONS: The proposed two-stage method enables reliable segmentation and detection of CaW from head and neck CT angiography.

暂无摘要。