Araştırma Çıktıları
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Item The classification of scoliosis braces developed by SOSORT with SRS, ISPO, and POSNA and approved by ESPRM(SPRINGER, 2022-01-01) Negrini, Stefano; Aulisa, Angelo Gabriele; Cerny, Pavel; de Mauroy, Jean Claude; McAviney, Jeb; Mills, Andrew; Donzelli, Sabrina; Grivas, Theodoros B.; Hresko, M. Timothy; Kotwicki, Tomasz; Labelle, Hubert; Marcotte, Louise; Matthews, Martin; O'Brien, Joe; Parent, Eric C.; Price, Nigel; Manuel, Rigo; Stikeleather, Luke; Vitale, Michael G.; Wong, Man Sang; Wood, Grant; Wynne, James; Zaina, Fabio; Bruno, Marco Brayda; Wursching, Suncica Bulat; Caglar, Yilgor; Cahill, Patrick; Dema, Eugenio; Knott, Patrick; Lebel, Andrea; Lein, Grigorii; Newton, Peter O.; Smith, Brian G.Purpose Studies have shown that bracing is an effective treatment for patients with idiopathic scoliosis. According to the current classification, almost all braces fall in the thoracolumbosacral orthosis (TLSO) category. Consequently, the generalization of scientific results is either impossible or misleading. This study aims to produce a classification of the brace types. Methods Four scientific societies (SOSORT, SRS, ISPO, and POSNA) invited all their members to be part of the study. Six level 1 experts developed the initial classifications. At a consensus meeting with 26 other experts and societies' officials, thematic analysis and general discussion allowed to define the classification (minimum 80\% agreement). The classification was applied to the braces published in the literature and officially approved by the 4 scientific societies and by ESPRM. Results The classification is based on the following classificatory items: anatomy (CTLSO, TLSO, LSO), rigidity (very rigid, rigid, elastic), primary corrective plane (frontal, sagittal, transverse, frontal \& sagittal, frontal \& transverse, sagittal \& transverse, three-dimensional), construction-valves (monocot, bivalve, multisegmented), construction-closure (dorsal, lateral, ventral), and primary action (bending, detorsion, elongation, movement, push-up, three points). The experts developed a definition for each item and were able to classify the 15 published braces into nine groups. Conclusion The classification is based on the best current expertise (the lowest level of evidence). Experts recognize that this is the first edition and will change with future understanding and research. The broad application of this classification could have value for brace research, education, clinical practice, and growth in this field.Item Towards Development of a Standard Terminology of the World Health Organization Classification of Tumors of the Central Nervous System in the Turkish Language, and a Perspective on the Practical Implications of the WHO Classification for Low and Middle Income Countries(FEDERATION TURKISH PATHOLOGY SOC, 2022-01-01) Soylemezoglu, Figen; Oz, Buge; Egilmez, Reyhan; Pekmezci, Melike; Bozkurt, Suheyla; Danyeli, Ayca Ersen; Onguru, Onder; Kulac, Ibrahim; Tihan, TarikIn our manuscript, we propose a common terminology in the Turkish language for the newly adopted WHO classification of the CNS tumors, also known as the WHO CNS 5th edition. We also comment on the applicability of this new scheme in low and middle income countries, and warn about further deepening disparities between the global north and the global south. This division, augmented by the recent COVID-19 pandemic, threatens our ability to coordinate efforts worldwide and may create significant disparities in the diagnosis and treatment of cancers between the ``haves{''} and the ``have nots{''}.Item Toward the Development of a Comprehensive Clinically Oriented Patient Profile: A Systematic Review of the Purpose, Characteristic, and Methodological Quality of Classification Systems of Adult Spinal Deformity(OXFORD UNIV PRESS INC, 2021-01-01) Kwan, Kenny Yat Hong; Naresh-Babu, J.; Jacobs, Wilco; de Kleuver, Marinus; Polly, David W.; Yilgor, Caglar; Wu, Yabin; Park, Jong-Beom; Ito, Manabu; van Hooff, Miranda L.; Deformity, A.O. Spine Knowledge ForumBACKGROUND: Existing adult spinal deformity (ASD) classification systems are based on radiological parameters but management of ASD patients requires a holistic approach. A comprehensive clinically oriented patient profile and classification of ASD that can guide decision-making and correlate with patient outcomes is lacking. OBJECTIVE: To perform a systematic review to determine the purpose, characteristic, and methodological quality of classification systems currently used in ASD. METHODS: A systematic literature search was conducted in MEDLINE, EMBASE, CINAHL, and Web of Science for literature published between January 2000 and October 2018. From the included studies, list of classification systems, their methodological measurement properties, and correlation with treatment outcomes were analyzed. RESULTS: Out of 4470 screened references, 163 were included, and 54 different classification systems for ASD were identified. The most commonly used was the Scoliosis Research Society-Schwab classification system. A total of 35 classifications were based on radiological parameters, and no correlation was found between any classification system levels with patient-related outcomes. Limited evidence of limited quality was available on methodological quality of the classification systems. For studies that reported the data, intraobserver and interobserver reliability were good (kappa = 0.8). CONCLUSION:This systematic literature search revealed that current classification systems in clinical use neither include a comprehensive set of dimensions relevant to decision-making nor did they correlate with outcomes. A classification system comprising a core set of patient-related, radiological, and etiological characteristics relevant to the management of ASD is needed.Item CogNet: classification of gene expression data based on ranked active-subnetwork- oriented KEGG pathway enrichment analysis(PEERJ INC, 2021-01-01) Yousef, Malik; Ulgen, Ege; Sezerman, Osman UgurMost of the traditional gene selection approaches are borrowed from other fields such as statistics and computer science, However, they do not prioritize biologically relevant genes since the ultimate goal is to determine features that optimize model performance metrics not to build a biologically meaningful model. Therefore, there is an imminent need for new computational tools that integrate the biological knowledge about the data in the process of gene selection and machine learning. Integrative gene selection enables incorporation of biological domain knowledge from external biological resources. In this study, we propose a new computational approach named CogNet that is an integrative gene selection tool that exploits biological knowledge for grouping the genes for the computational modeling tasks of ranking and classification. In CogNet, the pathfindR serves as the biological grouping tool to allow the main algorithm to rank active-subnetwork-oriented KEGG pathway enrichment analysis results to build a biologically relevant model. CogNet provides a list of significant KEGG pathways that can classify the data with a very high accuracy. The list also provides the genes belonging to these pathways that are differentially expressed that are used as features in the classification problem. The list facilitates deep analysis and better interpretability of the role of KEGG pathways in classification of the data thus better establishing the biological relevance of these differentially expressed genes. Even though the main aim of our study is not to improve the accuracy of any existing tool, the performance of the CogNet outperforms a similar approach called maTE while obtaining similar performance compared to other similar tools including SVM-RCE. CogNet was tested on 13 gene expression datasets concerning a variety of diseases.