Background: For patients with aneurysmal subarachnoid hemorrhage (aSAH), the Universal Coverage Scheme in Thailand covers the full costs of surgical and endovascular procedures except for those of embolization coils and assisting devices. Costs and effectiveness were compared between endovascular coiling and neurosurgical clipping to inform reimbursement policy decisions.
Methods: Costs and quality-adjusted life years (QALYs) were compared between coiling and clipping using the decision tree and Markov models. Mortality and functional outcomes of clipping were derived from national and hospital databases, and relative efficacies of coiling were obtained from meta-analyses of randomized controlled trials. Risks of rebleeding were abstracted from the International Subarachnoid Aneurysm Trial. Costs of the primary treatments, retreatments and follow-up care as well as utilities were obtained from hospital-based data. Non-health and indirect costs were abstracted from standard cost lists.
Results: Coiling and clipping contributed 10.59 and 9.28 QALYs to patients aged in their 50s. Under the societal and healthcare perspectives, the incremental costs incurred by coiling compared with clipping were US$1923 and $4343, respectively, which were equal to the incremental cost-effectiveness ratio of US$1470 and $3321 per QALY gained, respectively. Coiling became a cost-saving option when the costs of coil devices were reduced by 65.7%. At the country's cost-effectiveness threshold of US$5156, the probability of coiling being cost-effective was 71.3% and 65.6%, under the societal and healthcare perspectives, respectively.
Conclusion: Endovascular treatment for aSAH is cost-effective and this evidence supports coverage by national insurance.
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http://dx.doi.org/10.1136/neurintsurg-2021-017970 | DOI Listing |
The biodiversity of freshwater fishes is extensive in Mexico; however, knowledge of their associated myxozoan parasites is limited. This study aimed to recognize myxozoan parasites in the endemic fish Mayaheros urophthalmus. Two new species, Myxobolusmayarum n.
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Health and Medical Research Institute, Department of Life Science and Biotechnology, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba Central-6, 1-1-1 Higashi, Tsukuba, Ibaraki 305-8566, Japan. Electronic address:
Determining the handedness of helical nanocoils using transmission electron microscopy (TEM) has traditionally been challenging due to the deep depth of field and transmission nature of TEM, complementary techniques are considered necessary and have been practiced such as low angle rotary shadowing, scanning electron microscopy (SEM), or atomic force microscopy (AFM). These methods require customized sample preparation, making direct comparison difficult. Inspired by the need to identify the helical winding direction from TEM images alone, we developed a specialized tomography grid to capture stereo-pair images, enabling stereopsis.
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Medical Image and Data Analysis (MIDAS.lab), Department of Diagnostic and Interventional Radiology, University of Tuebingen, Tuebingen, Germany.
Cardiac Cine Magnetic Resonance Imaging (MRI) provides an accurate assessment of heart morphology and function in clinical practice. However, MRI requires long acquisition times, with recent deep learning-based methods showing great promise to accelerate imaging and enhance reconstruction quality. Existing networks exhibit some common limitations that constrain further acceleration possibilities, including single-domain learning, reliance on a single regularization term, and equal feature contribution.
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Department of Neurological Surgery, University of Miami, Miami, Florida, USA.
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Kobayashi Hospital, 510 Imaichi, Izumo City, Shimane, 693-0001, Japan.
Adverse effects of advanced age and poor initial neurological status on outcomes of patients with aneurysmal subarachnoid hemorrhage (SAH) have been documented. While a predictive model of the non-linear correlation between advanced age and clinical outcome has been reported, no previous model has been validated. Therefore, we created a prediction model of the non-linear correlation between advanced age and clinical outcome by machine learning and validated it using a separate cohort.
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