Background And Purpose: The purpose of this study was to analyze the 30-day outcome after introduction of a rapid carotid endarterectomy (CEA) program. Reasons for delay in CEA and the incidence of early recurrence neurological symptoms were recorded.
Methods: This is a prospective population-based study of delays to CEA and 30-day outcome in patients with symptomatic carotid stenosis. Neurological recurrence (NR) rate was determined after initiation of urgent best medical treatment (loading dose aspirin/clopidogrel and duel therapy with aspirin plus clopidogrel with a statin) until CEA and compared with NR ≤90 days prior index event.
Results: Of a total of 4905 (transient ischemic attack/ischemic stroke, and ocular events) patients, 115 symptomatic patients underwent CEA, 42% within 14 days of the index event and 99% within 14 days of surgical referral. The overall NR from index event to CEA in symptomatic carotid stenosis patients was significantly lower (2.5% [95% confidence interval, 1%-6%]) after best medical treatment when compared with NR ≤90 days in those before referral to a stroke clinic (29% [95% confidence interval, 22%-37%]; P<0.00001). There were no significant differences in outcomes among 48 early (<14 days), 46 intermediate (14-30 days), and 21 delayed (>30 days) CEAs.
Conclusions: CEA can be performed in the subacute period without significantly increasing the operative risk. The urgent best medical treatment was associated with significant reduction in the risk of early NR in CEA patients. It seems that urgent aggressive best medical treatment may obviate the need for urgent CEA.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1161/STROKEAHA.111.000798 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
PHIStruct: Improving phage-host interaction prediction at low sequence similarity settings using structure-aware protein embeddings.
Bioinformatics
January 2025
Bioinformatics Lab, Advanced Research Institute for Informatics, Computing and Networking, De La Salle University, Manila, 1004, Philippines.
Motivation: Recent computational approaches for predicting phage-host interaction have explored the use of sequence-only protein language models to produce embeddings of phage proteins without manual feature engineering. However, these embeddings do not directly capture protein structure information and structure-informed signals related to host specificity.
Results: We present PHIStruct, a multilayer perceptron that takes in structure-aware embeddings of receptor-binding proteins, generated via the structure-aware protein language model SaProt, and then predicts the host from among the ESKAPEE genera.
Smoking Cessation Interventions in the Lung Cancer Screening Setting: A Randomized Clinical Trial.
JAMA Intern Med
January 2025
Department of Behavioral Science, The University of Texas MD Anderson Cancer Center, Houston.
Importance: The optimal configuration of a smoking cessation intervention in a lung cancer screening (LCS) setting has not yet been established.
Objective: To evaluate the efficacy of 3 tobacco treatment strategies of increasing integration and intensity in the LCS setting.
Design, Setting, And Participants: In this randomized clinical trial, LCS-eligible current smokers were randomized into 3 treatments: quitline (QL), QL plus (QL+), or integrated care (IC).
Automatic segmentation model and machine learning model grounded in ultrasound radiomics for distinguishing between low malignant risk and intermediate-high malignant risk of adnexal masses.
Insights Imaging
January 2025
Medical Research Department, Qingdao Hospital, University of Health and Rehabilitation Sciences (Qingdao Municipal Hospital), Qingdao, P. R. China.
Objective: To develop an automatic segmentation model to delineate the adnexal masses and construct a machine learning model to differentiate between low malignant risk and intermediate-high malignant risk of adnexal masses based on ovarian-adnexal reporting and data system (O-RADS).
Methods: A total of 663 ultrasound images of adnexal mass were collected and divided into two sets according to experienced radiologists: a low malignant risk set (n = 446) and an intermediate-high malignant risk set (n = 217). Deep learning segmentation models were trained and selected to automatically segment adnexal masses.
A combination of low-temperature radiofrequency thermocoagulation and pulsed radiofrequency of the bilateral Gasserian ganglion for bilateral trigeminal neuralgia due to multiple sclerosis: a case report.
JA Clin Rep
January 2025
Department of Pain Clinic, NTT Medical Center Tokyo, 5-9-22 Higashi-Gotanda, Shinagawa-Ku, Tokyo, 141-8625, Japan.
Background: Bilateral trigeminal neuralgia secondary to multiple sclerosis is an extremely rare condition. When Gasserian ganglion block is performed, it is necessary to achieve reliable long-term analgesic effects while avoiding treatment-related complications.
Case Presentation: A 49-year-old male with multiple sclerosis exhibited persistent dull pain and paroxysmal electric shock-like pain in his bilateral maxillary molars and mandible.
Integrating machine learning with mendelian randomization for unveiling causal gene networks in glioblastoma multiforme.
Discov Oncol
January 2025
Department of Medical Imaging, Shenzhen Longhua District Key Laboratory of Neuroimaging, Shenzhen Longhua District Central Hospital, Shenzhen, 518110, China.
Background: Glioblastoma multiforme (GBM) is a highly aggressive brain cancer with poor prognosis and limited treatment options. Despite advances in understanding its molecular mechanisms, effective therapeutic strategies remain elusive due to the tumor's genetic complexity and heterogeneity.
Methods: This study employed a comprehensive analysis approach integrating 113 machine learning algorithms with Mendelian Randomization (MR) analysis to investigate the molecular underpinnings of GBM.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!