The CT-DRAGON score was developed to predict long-term functional outcome after acute stroke in the anterior circulation treated by thrombolysis. Its implementation in clinical practice may be hampered by its plethora of variables. The current study was designed to develop and evaluate an alternative score, as a reduced set of features, derived from the original CT-DRAGON score. This single-center retrospective study included 564 patients treated for stroke, in the anterior and the posterior circulation. At 90 days, favorable [modified Rankin Scale score (mRS) of 0-2] and miserable outcome (mRS of 5-6) were predicted by the CT-DRAGON in 427 patients. Bootstrap forests selected the most relevant parameters of the CT-DRAGON, in order to develop a reduced set of features. Discrimination, calibration and misclassification of both models were tested. The area under the receiver operating characteristic curve (AUROC) for the CT-DRAGON was 0.78 (95% CI 0.74-0.81) for favorable and 0.78 (95% CI 0.72-0.83) for miserable outcome. Misclassification was 29% for favorable and 13.5% for miserable outcome, with a 100% specificity for the latter. National Institutes of Health Stroke Scale (NIHSS), pre-stroke mRS and age were identified as the strongest contributors to favorable and miserable outcome and named the reduced features set. While CT-DRAGON was only available in 323 patients (57%), the reduced features set could be calculated in 515 patients (91%) ( < 0.001). Misclassification was 25.8% for favorable and 14.4% for miserable outcome, with a 97% specificity for miserable outcome. The reduced features set had better discriminative power than CT-DRAGON for both outcomes (both < 0.005), with an AUROC of 0.82 (95% CI 0.79-0.86) and 0.83 (95% CI 0.77-0.87) for favorable and miserable outcome, respectively. The CT-DRAGON score revealed acceptable discrimination in our cohort of both anterior and posterior circulation strokes, receiving all treatment modalities. The reduced features set could be measured in a larger cohort and with better discrimination. However, the reduced features set needs further validation in a prospective, multicentre study. : http://www.clinicaltrials.gov. Identifiers: NCT03355690, NCT04092543.
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http://dx.doi.org/10.3389/fneur.2020.00718 | DOI Listing |
HSS J
November 2024
Limb Lengthening and Complex Reconstruction Service, Department of Orthopedic Surgery, Hospital for Special Surgery, New York, NY, USA.
J Stroke Cerebrovasc Dis
December 2024
Department of Neurosurgery, Kyoto Tanabe Central Hospital, Kyoto, Japan.
Drug Deliv
December 2024
Department of Gastroenterology, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.
The application of multidisciplinary techniques in the management of endocrine-related cancers is crucial for harnessing the advantages of multiple disciplines and their coordinated efforts in eliminating tumors. Due to the malignant characteristics of cancer cells, they possess the capacity to develop resistance to traditional treatments such as chemotherapy and radiotherapy. Nevertheless, despite diligent endeavors to enhance the prediction of outcomes, the overall survival rate for individuals afflicted with endocrine-related malignancy remains quite miserable.
View Article and Find Full Text PDFSci Rep
August 2024
Department of Neurological Surgery, Chiba University Hospital, 1-8-1 Inohana, Chiba, 260-8677, Japan.
Diagnostics (Basel)
July 2024
Department of Neurology, University Hospital Salzburg, Christian Doppler Klinik, Paracelsus Medical University Salzburg, 5020 Salzburg, Austria.
Background: Despite the increased use of mechanical thrombectomy (MT) in recent years, there remains a lack of research on in-hospital mortality rates following the procedure, the primary factors influencing these rates, and the potential for predicting them. This study aimed to utilize interpretable machine learning (ML) to help clarify these uncertainties.
Methods: This retrospective study involved patients with anterior circulation large vessel occlusion (LVO)-related ischemic stroke who underwent MT.
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