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12. Artificial intelligence as an initial reader for double reading in breast cancer screening: a prospective initial study of 32,822 mammograms of the Egyptian population.

Author

Mansour, Sahar, Sweed, Enas, Gomaa, Mohammed Mohammed Mohammed, Hussein, Samar Ahmed, Abdallah, Engy, Nada, Yassmin Mohamed, Kamal, Rasha, Mohamed, Ghada, Taha, Sherif Nasser, and Moustafa, Amr Farouk Ibrahim

Subjects
PREDICTIVE tests, READING, BIOPSY, RISK assessment, REFERENCE values, RECEIVER operating characteristic curves, DIAGNOSTIC imaging, DATA analysis, BREAST tumors, EARLY detection of cancer, ARTIFICIAL intelligence, RESEARCH evaluation, PROBABILITY theory, KRUSKAL-Wallis Test, DECISION making in clinical medicine, DESCRIPTIVE statistics, CHI-squared test, LONGITUDINAL method, WORKFLOW, MAMMOGRAMS, COMPUTERS in medicine, STATISTICS, DIGITAL image processing, DATA analysis software, SENSITIVITY & specificity (Statistics), PATIENT aftercare
Abstract

Background: Although artificial intelligence (AI) has potential in the field of screening of breast cancer, there are still issues. It is vital to make sure AI does not overlook cancer or cause needless recalls. The aim of this work was to investigate the effectiveness of indulging AI in combination with one radiologist in the routine double reading of mammography for breast cancer screening. The study prospectively analyzed 32,822 screening mammograms. Reading was performed in a blind-paired style by (i) two radiologists and (ii) one radiologist paired with AI. A heatmap and abnormality scoring percentage were provided by AI for abnormalities detected on mammograms. Negative mammograms and benign-looking lesions that were not biopsied were confirmed by a 2-year follow-up. Results: Double reading by the radiologist and AI detected 1324 cancers (6.4%); on the other side, reading by two radiologists revealed 1293 cancers (6.2%) and presented a relative proportion of 1·02 (p < 0·0001). At the recall stage, suspicion and biopsy recommendation were more presented by the AI plus one radiologist combination than by the two radiologists. The interpretation of the mammogram by AI plus only one radiologist showed a sensitivity of 94.03%, a specificity of 99.75%, a positive predictive value of 96.571%, a negative predictive value of 99.567%, and an accuracy of 99.369% (from 99.252 to 99.472%). The positive likelihood ratio was 387.260, negative likelihood ratio was 0.060, and AUC "area under the curve" was 0.969 (0.967–0.971). Conclusions: AI could be used as an initial reader for the evaluation of screening mammography in routine workflow. Implementation of AI enhanced the opportunity to reduce false negative cases and supported the decision to recall or biopsy. [ABSTRACT FROM AUTHOR]

Published
2024
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13. Impact of PEG400–Zeolite Performance as a Material for Enhancing Strength of the Mechanical Properties of LECA/Foamed Lightweight Concrete.

Author

Al-Jabali, Hebah Mohammad, Edris, Walid Fouad, Khairy, Shady, Mohamed, Ghada N., Elsayed, Hebatallah A., and El-Latief, Ahmed A.

Subjects
AIR-entrained concrete, POLYETHYLENE glycol, STRENGTH of materials, COMPRESSIVE strength, TENSILE strength
Abstract

A versatile building material, foamed concrete is made of cement, fine aggregate, and foam combined with coarse aggregate. This study provides a description of how constant coarse aggregate replacement (50%) of LECA and foamed concrete, which are lightweight concrete types, by zeolite as a filler and PEG-400 as a plasticizer, water retention agent, and strength enhancer affect the mechanical properties of the cement. A study that examined the characteristics of cellular lightweight concrete in both its fresh and hardened forms was carried out for both foamed concrete and LECA concrete. In order to do this, a composite of zeolite and polyethylene glycol 400 was made using the direct absorption method, and no leakage was seen. Zeolite was loaded to a level of 10% and 20% of the total weight in cement, while 400 g/mol PEG was used at levels of 1%, 1.5%, and 2% of the cement's weight. Various mixtures having a dry density of 1250 kg/m3 were produced. Properties like dry density, splitting tensile strength, and compressive strength were measured. An increase in the amount of PEG400–zeolite was seen to lower the workability, or slump, of both foamed and LECA concrete, while the replacement of aggregate by zeolite resulted in an exponential drop in both compressive and flexural strengths. [ABSTRACT FROM AUTHOR]

Published
2024
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16. Stem cell therapy: a new hope for stroke and traumatic brain injury recovery and the challenge for rural minorities in South Carolina.

Author

Mohamed, Ghada A., Lench, Daniel H., Grewal, Parneet, Rosenberg, Mark, and Voeks, Jenifer

Subjects
FUNCTIONAL magnetic resonance imaging, BRAIN injuries, STEM cell treatment, RURAL health, MESENCHYMAL stem cells
Abstract

Stroke and traumatic brain injury (TBI) are a significant cause of death and disability nationwide. Both are considered public health concerns in rural communities in the state of South Carolina (SC), particularly affecting the African American population resulting in considerable morbidity, mortality, and economic burden. Stem cell therapy (SCT) has emerged as a potential intervention for both diseases with increasing research trials showing promising results. In this perspective article, the authors aim to discuss the current research in the field of SCT, the results of early phase trials, and the utilization of outcome measures and biomarkers of recovery. We searched PubMed from inception to December 2023 for articles on stem cell therapy in stroke and traumatic brain injury and its impact on rural communities, particularly in SC. Early phase trials of SCT in Stroke and Traumatic Brain injury yield promising safety profile and efficacy results, but the findings have not yet been consistently replicated. Early trials using mesenchymal stem cells for stroke survivors showed safety, feasibility, and improved functional outcomes using broad and domain-specific outcome measures. Neuroimaging markers of recovery such as Functional Magnetic Resonance Imaging (fMRI) and electroencephalography (EEG) combined with neuromodulation, although not widely used in SCT research, could represent a breakthrough when evaluating brain injury and its functional consequences. This article highlights the role of SCT as a promising intervention while addressing the underlying social determinants of health that affect therapeutic outcomes in relation to rural communities such as SC. It also addresses the challenges ethical concerns of stem cell sourcing, the high cost of autologous cell therapies, and the technical difficulties in ensuring transplanted cell survival and strategies to overcome barriers to clinical trial enrollment such as the ethical concerns of stem cell sourcing, the high cost of autologous cell therapies, and the technical difficulties in ensuring transplanted cell survival and equitable healthcare. [ABSTRACT FROM AUTHOR]

Published
2024
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26. Evaluation of the structural performance of T-section beams with construction defects utilizing numerical analysis.

Author

Sayed, Abd Al-Kader A. Al, Al-jabali, Hebah Mohammad, Fahmy, Mohamed, Mohamed, Ghada N., Bayoumi, El-Said Abd-Allah, Selouma, Tarek Ibrahim, Stolz, Carina M., and Perlingeiro, Mayra Soares Pereira Lima

Subjects
WOODEN beams, NUMERICAL analysis, CONCRETE slabs, REINFORCED concrete construction, FINITE element method, REINFORCING bars, FUNCTIONAL analysis
Abstract

This study investigates recent incidents of slabs collapse in reinforced concrete T-beam constructions attributed to deficiencies in design detailing and execution. It employs numerical analyses using the finite element method in ANSYS software to model T-section beams, with validation against experimental tests. Subsequently, a parametric study is conducted to explore the behavior of T-section beams under various design and construction variables, including the spacing of secondary reinforcements in the slab, the diameter of secondary main reinforcements, and slab thickness. The numerical analysis results are found to align well with experimental findings. The parametric study highlights that the eccentricity of reinforcing bars in the secondary direction of the slab is more detrimental than in the main direction. Furthermore, using 10 mm diameter reinforcement in the slab, either in the main or secondary direction, enhances the slab's resistance to applied loads. Additionally, the study reveals that increasing the stiffness of the slab contributes to an improved resistance of the beam. [ABSTRACT FROM AUTHOR]

Published
2024
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29. Text classification in the BNC using corpus and statistical methods

Author

Mohamed, Ghada

Subjects
410.1
Abstract

The main part of this thesis sets out to develop a system of categories within a text typology. Although there exist many different approaches to the classification of text into categories, this research fills a gap in the literature, as most work on text classification is based on features external to the text such as the text's purpose, the aim of discourse, and the medium of communication. Text categories that have been set up based on some external features are not linguistically defined. In consequence, texts that belong to the same type are not necessarily similar in their linguistic forms. Even Biber's (1988) linguistically-oriented work was based on externally defined ~registers. Further, establishing text categories based on text-external features favours theoretical and qualitative approaches of text classification. These approaches can be seen as top-down approaches where external features are defined functionally in advance, and subsequently patterns of linguistic features are described in relation to each function. In such a case, the process of linking texts with a particular type is not done in a systematic way. In this thesis, I show how a text typology based on similarities in linguistic form can be developed systematically using a multivariate statistical technique; namely, cluster analysis. Following a review of various possible approaches to multivariate statistical analysis, I argue that cluster analysis is the most appropriate for systematising the study of text classification, because it has the distinctive feature of placing objects into distinct groupings based on their overall similarities across multiple variables. Cluster analysis identifies these grouping algorithmically. The objects to be clustered in my thesis are the written texts in the British National Corpus (BNC). I will make use of the written part only, since results of previous research which attempts to classify texts of this dataset were not very beneficial. Takahashi (2006), for instance, identified merely a broad distinction between formal and informal styles in the written part; whereas in the spoken part, he could come up with insightful results. Thus, it seems justifiable to look at the part of the BNC which Taka..1.ashi found intractable, using a different multivariate technique, to see if this methodology allows patterns to emerge in the dataset. Further, there are two other reasons to use the written BNC. First, some studies (e.g. Akinnaso 1982; Chafe and Danielewicz 1987) suggest that distinctions between text varieties based on frequencies of linguistic features can be identified even within one mode of communication, i.e. writing. Second, analysing written text varieties has direct implications for pedagogy (Biber and Conrad 2009). The variables measured in the written texts of the BNC are linguistic features that have functional associations. However, any linguistic feature can be interpreted functionally; hence, we cannot say that there is an easy way to decide on a list of linguistic features to investigate text varieties. In this thesis, the list of linguistic features is informed by some aspects of Systemic Functional Theory (STF) and characteristics identified in previous research on writing, as opposed to speech. SFT lends itself to the interpretation of how language is used through functional associations of linguistic features, treating meaning and form as two inseparable notions. This characteristic of SFT can be one source to inform my research to some extent, which assumes that a model of text-types can be established by investigating not only the linguistic features shared in each type, but also the functions served by these linguistic features in each type. However, there is no commitment in this study to aspects of SFT other than those I have discussed here. Similarly, the linguistic features that reflect characteristics of speech and writing identified in previous research also have a crucial role in distinguishing between different texts. For instance, writing is elaborate, and this is associated with linguistic features such as subordinate clauses, prepositional phrases, adjectives, and so on. However, these characteristics do not only reflect the distinction between speech and writing; they can also distinguish between different spoken texts or different written texts (see Akinnaso 1982). Thus, the linguistic features seen as important from these two perspectives are included in my list of linguistic features. To make the list more principled and exhaustive, I also consult a comprehensive corpus-based work on English language, along with some microscopic studies examining individual features in different registers. The linguistic features include personal pronouns, passive constructions, prepositional phrases, nominalisation, modal auxiliaries, adverbs, and adjectives. Computing a cluster analysis based on this data is a complex process with many steps. At each step, several alternative techniques are available. Choosing among the available teclmiques is a non-trivial decision, as multiple alternatives are in common use by statisticians. I demonstrate how a process of testing several combinations of clustering methods, in order to determine the most useful/stable clustering combination(s) for use in the classification of texts by their linguistic features . To test the robustness of the clustering algorithms techniques and to validate the cluster analysis, I use three validation techniques for cluster analysis, namely the cophenetic coefficient, the adjusted Rand index, and the AV p-value. The findings of the cluster analysis represent a plausible attempt to systematise the study of the diversity of texts by means of automatic classification. Initially, the cluster analysis resulted in 16 clusters/text types. However, a thorough investigation of those 16 clusters reveals that some clusters represent quite similar text types. Thus, it is possible to establish overall headings for similar types, reflecting their shared linguistic features. The resulting typology contains six major text types: persuasion, narration, informational narration, exposition, scientific exposition, and literary exposition. Cluster analysis thus proves to be a powerful tool for structuring the data, if used with caution. The way it is implemented in this study constitutes an advance in the field of text typology. Finally, a small-scale case study of the validity of the text typology is carried out. A questionnaire is used to find out whether and to what extent my taxonomy corresponds to native speakers' understanding of textual variability, that is, whether the taxonomy has some mental reality for native speakers of English. The results showed that native speakers of English, on the one hand, are good at explicitly identifying the grammatical features associated with scientific exposition and narration; but on the other hand, they are not so good at identifying the grammatical features associated with literary exposition and persuasion. The results also showed that participants seem to have difficulties in identifying grammatical features of informational narration. The results of this small-scale case study indicate that the text typology in my thesis is, to some extent, a phenomenon that native speakers are aware of, and thus we can justify placing our trust in the results - at least in their general pattern, if not in every detail.

Published
2011

33. The way to design web-based (EMP) course in EFL context: A bridge from evaluation to course design

Author

Abubaker-Faraj Basim M. and Mohamed Ghada

Subjects
ESP, English for medical purposes, web-based learning, History of scholarship and learning. The humanities, AZ20-999
Abstract

As the worldwide use of English increases it has become indispensable in educational, vocational and professional environments. As a result, English for specific purposes (ESP) has a central role in teaching English at the tertiary level. With rapid advances in technological development, technology has emerged as one of the key aspects of teaching and learning English in classrooms. Based on the students' needs to use technology in learning English for medical purposes (EMP), the internet has turned into a valuable EMP resource. However, the selection of appropriate websites that match the learners' and teachers' needs can turn into a time-consuming process.

Published
2018

44. Tissue Clock Beyond Time Clock: Endovascular Thrombectomy for Patients With Large Vessel Occlusion Stroke Beyond 24 Hours

Author

Mohamed, Ghada A., primary, Nogueira, Raul G., additional, Essibayi, Muhammed Amir, additional, Aboul-Nour, Hassan, additional, Mohammaden, Mahmoud, additional, Haussen, Diogo C., additional, Ruiz, Aldo Mendez, additional, Gross, Bradley A., additional, Kuybu, Okkes, additional, Salem, Mohamed M., additional, Burkhardt, Jan-Karl, additional, Jankowitz, Brian, additional, Siegler, James E., additional, Patel, Pratit, additional, Hester, Taryn, additional, Ortega-Gutierrez, Santiago, additional, Farooqui, Mudassir, additional, Galecio-Castillo, Milagros, additional, Nguyen, Thanh N., additional, Abdalkader, Mohamad, additional, Klein, Piers, additional, Charles, Jude H., additional, Saini, Vasu, additional, Yavagal, Dileep R., additional, Jumah, Ammar, additional, Alaraj, Ali, additional, Peng, Sophia, additional, Hafeez, Muhammad, additional, Tanweer, Omar, additional, Kan, Peter, additional, Scaggiante, Jacopo, additional, Matsoukas, Stavros, additional, Fifi, Johanna T., additional, Mayer, Stephan A., additional, and Chebl, Alex B., additional

Published
2023
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48. Global Impact of the COVID-19 Pandemic on Stroke Volumes and Cerebrovascular Events: A 1-Year Follow-up

Author

Society of Vascular and Interventional Neurology (US), Nguyen, Thanh N., Qureshi, Muhammad M., Klein, Piers, Yamagami, Hiroshi, Mikulik, Robert, Czlonkowska, Anna, Abdalkader, Mohamad, Sedova, Petra, Sathya, Anvitha, Lo, Hannah C., Mansour, Ossama Yassin, Vanguru, Husitha Reddy, Lesaine, Emilie, Tsivgoulis, Georgios, Loochtan, Aaron I., Demeestere, Jelle, Uchino, Ken, Inoa, Violiza, Goyal, Nitin, Charidimou, Andreas, Siegler, James E., Yaghi, Shadi, Aguiar de Sousa, Diana, Mohammaden, Mahmoud H., Haussen, Diogo C., Kristoffersen, Espen Saxhaug, Lereis, Virginia Pujol, Scollo, Sergio Daniel, Campbell, Bruce C. V., Ma, Alice, Thomas, James Orton, Parsons, Mark W., Singhal, Shaloo, Slater, Lee-Anne, Tomazini Martins, Rodrigo, Enzinger, Chris, Gattringer, Thomas, Rahman, Aminur, Bonnet, Thomas, Ligot, Noemie, De Raedt, Sylvie, Lemmens, Robin, Vanacker, Peter, Vandervorst, Fenne, Conforto, Adriana Bastos, Hidalgo, Raquel C. T., Neves, Luciana de Oliveira, Martins, Rodrigo Targa, Mora Cuervo, Daissy Liliana, Rebello, Leticia C., Santiago, Igor Bessa, Silva, Isabelle Lameirinhas da, Sakelarova, Teodora, Kalpachki, Rosen, Alexiev, Filip, Catanese, Luciana, Cora, Elena Adela, Goyal, Mayank, Hill, Michael D., Kelly, Michael E., Khosravani, Houman, Lavoie, Pascale, Peeling, Lissa, Pikula, Aleksandra, Rivera, Rodrigo, Chen, Hui-Sheng, Chen, Yimin, Huo, Xiaochuan, Miao, Zhongrong, Yang, Shuiquan, Bedekovic, Marina Roje, Bralic, Marina, Budincevic, Hrvoje, Corredor-Quintero, Ángel Basilio, Lara-Sarabia, Osvaldo E., Cabal, Martin, Tenora, Dusan, Fibrich, Petr, Herzig, Roman, Hlaváčová, Helena, Hrabanovska, Emanuela, Hlinovsky, David, Jurak, Lubomir, Kadlcikova, Jana, Karpowicz, Igor, Klecka, Lukas, Kovar, Martin, Lauer, David, Neumann, Jiri, Palouskova, Hana, Reiser, Martin, Rekova, Petra, Rohan, Vladimir, Skoda, Ondrej, Škorňa, Miroslav, Sobotková, Lenka, Sramek, Martin, Zakova, Lenka, Christensen, Hanne, Drenck, Nicolas, Iversen, Helle Klingenberg, Truelsen, Thomas Clement, Wienecke, Troels, Sobh, Khalid, Ylikotila, Pauli, Alpay, Kemal, Strbian, Daniel, Bernady, Patricia, Casenave, Philippe, Dan, Maria, Faucheux, Jean-Marc, Gentric, Jean-Christophe, Magro, Elsa, Sabben, Candice, Reiner, Peggy, Rouanet, Francois, Bohmann, Ferdinand O., Boskamp, Stefan, Mbroh, Joshua, Nagel, Simon, Nolte, Christian H, Ringleb, Peter A., Rosenkranz, Michael, Poli, Sven, Thomalla, Götz, Karapanayiotides, Theodoros, Koutroulou, Ioanna, Kargiotis, Odysseas, Palaiodimou, Lina, Barrientos Guerra, José Domingo, Huded, Vikram, Menon, Bindu, Nagendra, Shashank, Prajapati, Chintan, Sylaja, P. N., Krishna Pramana, Nyoman Angga, Sani, Achmad Firdaus, Ghoreishi, Abdoreza, Farhoudi, Mehdi, Hokmabadi, Elyar Sadeghi, Raya, Tariq Abu, Kalmanovich, Shani Avnery, Ronen, Levite, Sabetay, Sergiu Ionut, Acampa, Maurizio, Adami, Alessandro, Castellan, Lucio, Longoni, Marco, Ornello, Raffaele, Renieri, Leonardo, Bigliani, Claudia Rolla, Romoli, Michele, Sacco, Simona, Salmaggi, Andrea, Sangalli, Davide, Zini, Andrea, Doijiri, Ryosuke, Fukuda, Hiroki, Fujinaka, Toshiyuki, Fujita, Kyohei, Imamura, Hirotoshi, Sakai, Nobuyuki, Kanamaru, Takuya, Kimura, Naoto, Kono, Ryuhei, Miyake, Kosuke, Sakaguchi, Manabu, Sakai, Kenichiro, Sonoda, Kazutaka, Todo, Kenichi, Miyashita, Fumio, Tokuda, Naoki, Matsumaru, Yuji, Matsumoto, Shoji, Ohara, Nobuyuki, Shindo, Seigo, Takenobu, Yohei, Yoshimoto, Takeshi, Toyoda, Kazunori, Uwatoko, Takeshi, Yagita, Yoshiki, Yamada, Takehiro, Yamamoto, Nobuaki, Yamamoto, Ryoo, Yazawa, Yukako, Sugiura, Yuri, Waweru, Peter Kuria, Baek, Jang-Hyun, Lee, Si Baek, Seo, Kwon-Duk, Sohn, Sung-Il, Arsovska, Anita Ante, Chan, Yong Chieh, Wan Zaidi, Wan Asyraf, Jaafar, Ainul Syahrilfazli, Gongora-Rivera, Fernando, Martinez-Marino, Manuel, Infante-Valenzuela, Adrian, Groppa, Stanislav, Leahu, Pavel, Coutinho, Jonathan M, Rinkel, Leon A., Dippel, Diederik W. J., Dam-Nolen, Dianne H. K. van, Ranta, Annemarei, Wu, Teddy Y., Adebayo, Tajudeen Temitayo, Bello, Abiodun H., Nwazor, Ernest Okwundu, Sunmonu, Taofiki Ajao, Wahab, Kolawole Wasiu, Ronning, Ole Morten, Sandset, Else Charlotte, Al Hashmi, Amal M., Ahmad, Saima, Rashid, Umair, Rodriguez-Kadota, Liliana, Vences, Miguel Ángel, Yalung, Patrick Matic, Hao Dy, Jon Stewart, Pineda-Franks, Maria Carissa, Co, Christian Oliver, Brola, Waldemar, Debiec, Aleksander, Dorobek, Malgorzata, Karlinski, Michal Adam, Labuz-Roszak, Beata M., Lasek-Bal, Anetta, Sienkiewicz-Jarosz, Halina, Staszewski, Jacek, Sobolewski, Piotr, Wiacek, Marcin, Zielinska-Turek, Justyna, Araujo, Andre Pinho, Rocha, Mariana, Castro, Pedro, Cruz, Vitor Tedim, Ferreira, Paulo Venancio, Ferreira, Patricia, Nunes, Ana Paiva, Fonseca, Luisa, Marto, João Pedro, Pinho E Melo, Teresa, Rodrigues, Miguel, Silva, M. Luis, Dimitriade, Adela, Falup-Pecurariu, Cristian, Hamid, May Adel, Venketasubramanian, Narayanaswamy, Krastev, Georgi, Mako, Miroslav, Ayo-Martin, Oscar, Hernández-Fernández, Francisco, Blasco, Jordi, Rodríguez-Vázquez, Alejandro, Cruz-Culebras, Antonio, Moniche, Francisco, Montaner, Joan, Pérez-Sánchez, Soledad, García Sánchez, María Jesús, Guillán Rodríguez, Marta, Jood, Katarina, Nordanstig, Annika, Mazya, Michael V., Moreira, Tiago T. P., Bernava, Gianmarco, Beyeler, Morin, Bolognese, Manuel, Carrera, Emmanuel, Dobrocky, Tomas, Karwacki, Grzegorz Marek, Keller, Emanuela, Hsieh, Chang Yang, Boonyakarnkul, Surawan, Churojana, Anchalee, Aykac, Ozlem, Ozdemir, Atilla Ã-Zcan, Bajrami, Arsida, Senadim, Songul, Hussain, Syed Irteza, John, Seby, Banerjee, Soma, Kwan, Joseph, Krishnan, Kailash, Lenthall, Robert, Matthews, Ashok, Wong, Ken, Zhang, Liqun, Altschul, Dorothea, Asif, Kaiz S., Bahiru, Zeelalem, Below, Kristine, Biller, José, Ruland, Sean, Chaudry, Saqib A., Chen, Michael, Chebl, Alex, Cibulka, Jackie, Cistrunk, Leon, Clark, Judith, Colasurdo, Marco, Czap, Alexandra, de Havenon, Adam, D'Amato, Salvatore, Dharmadhikari, Sushrut, Grimmett, Kasey B., Dmytriw, Adam A., Etherton, Mark R., Ezepue, Chizoba, Farooqui, Mudassir, Feske, Steven K., Fink, Lauren, Gasimova, Ulviyya, Guzik, Amy K., Hakemi, Maryam, Hovingh, Majesta, Khan, Muhib, Jillela, Dinesh, Kan, Peter T., Khatri, Rakesh, Khawaja, Ayaz M., Khoury, Naim N., Kiley, Nicole L., Kim, Benny S., Kolikonda, Murali K., Kuhn, Anna Luisa, Lara, Stephanie, Linares, Guillermo, Linfante, Italo, Lukovits, Timothy G., Lycan, Sarah, Male, Shailesh S., Maali, Laith, Mancin, John, Masoud, Hesham, Mohamed, Ghada A., Monteiro, Andre, Nahab, Fadi, Nalleballe, Krishna, Ortega-Gutiérrez, Santiago, Puri, Ajit S, Radaideh, Yazan, Rahangdale, Rahul H., Rai, Ansaar, Ramakrishnan, Pankajavalli, Reddy, Aravind B., Rojas-Soto, Diana M., Romero, José Rafael, Rost, Natalia S., Rothstein, Aaron, Omran, Setareh Salehi, Sheth, Sunil A., Siddiqui, Adnan H., Starosciak, Amy K., Tarlov, Nicholas E., Taylor, Robert A., Wang, Michael J., Wolfe, Jared, Wong, Ka-Ho, Le, Huynh Vu, Nguyen, Quy Viet, Pham, Thong Nhu, Nguyen, Trung Thanh, Phan, Hoang Thi, Ton, Mai Duy, Fischer, Urs, Michel, Patrik, Strambo, Davide, Martins, Sheila O., Zaidat, Osama O., Nogueira, Raul G., Society of Vascular and Interventional Neurology (US), Nguyen, Thanh N., Qureshi, Muhammad M., Klein, Piers, Yamagami, Hiroshi, Mikulik, Robert, Czlonkowska, Anna, Abdalkader, Mohamad, Sedova, Petra, Sathya, Anvitha, Lo, Hannah C., Mansour, Ossama Yassin, Vanguru, Husitha Reddy, Lesaine, Emilie, Tsivgoulis, Georgios, Loochtan, Aaron I., Demeestere, Jelle, Uchino, Ken, Inoa, Violiza, Goyal, Nitin, Charidimou, Andreas, Siegler, James E., Yaghi, Shadi, Aguiar de Sousa, Diana, Mohammaden, Mahmoud H., Haussen, Diogo C., Kristoffersen, Espen Saxhaug, Lereis, Virginia Pujol, Scollo, Sergio Daniel, Campbell, Bruce C. V., Ma, Alice, Thomas, James Orton, Parsons, Mark W., Singhal, Shaloo, Slater, Lee-Anne, Tomazini Martins, Rodrigo, Enzinger, Chris, Gattringer, Thomas, Rahman, Aminur, Bonnet, Thomas, Ligot, Noemie, De Raedt, Sylvie, Lemmens, Robin, Vanacker, Peter, Vandervorst, Fenne, Conforto, Adriana Bastos, Hidalgo, Raquel C. T., Neves, Luciana de Oliveira, Martins, Rodrigo Targa, Mora Cuervo, Daissy Liliana, Rebello, Leticia C., Santiago, Igor Bessa, Silva, Isabelle Lameirinhas da, Sakelarova, Teodora, Kalpachki, Rosen, Alexiev, Filip, Catanese, Luciana, Cora, Elena Adela, Goyal, Mayank, Hill, Michael D., Kelly, Michael E., Khosravani, Houman, Lavoie, Pascale, Peeling, Lissa, Pikula, Aleksandra, Rivera, Rodrigo, Chen, Hui-Sheng, Chen, Yimin, Huo, Xiaochuan, Miao, Zhongrong, Yang, Shuiquan, Bedekovic, Marina Roje, Bralic, Marina, Budincevic, Hrvoje, Corredor-Quintero, Ángel Basilio, Lara-Sarabia, Osvaldo E., Cabal, Martin, Tenora, Dusan, Fibrich, Petr, Herzig, Roman, Hlaváčová, Helena, Hrabanovska, Emanuela, Hlinovsky, David, Jurak, Lubomir, Kadlcikova, Jana, Karpowicz, Igor, Klecka, Lukas, Kovar, Martin, Lauer, David, Neumann, Jiri, Palouskova, Hana, Reiser, Martin, Rekova, Petra, Rohan, Vladimir, Skoda, Ondrej, Škorňa, Miroslav, Sobotková, Lenka, Sramek, Martin, Zakova, Lenka, Christensen, Hanne, Drenck, Nicolas, Iversen, Helle Klingenberg, Truelsen, Thomas Clement, Wienecke, Troels, Sobh, Khalid, Ylikotila, Pauli, Alpay, Kemal, Strbian, Daniel, Bernady, Patricia, Casenave, Philippe, Dan, Maria, Faucheux, Jean-Marc, Gentric, Jean-Christophe, Magro, Elsa, Sabben, Candice, Reiner, Peggy, Rouanet, Francois, Bohmann, Ferdinand O., Boskamp, Stefan, Mbroh, Joshua, Nagel, Simon, Nolte, Christian H, Ringleb, Peter A., Rosenkranz, Michael, Poli, Sven, Thomalla, Götz, Karapanayiotides, Theodoros, Koutroulou, Ioanna, Kargiotis, Odysseas, Palaiodimou, Lina, Barrientos Guerra, José Domingo, Huded, Vikram, Menon, Bindu, Nagendra, Shashank, Prajapati, Chintan, Sylaja, P. 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Abstract

Background and Objectives: Declines in stroke admission, IV thrombolysis (IVT), and mechanical thrombectomy volumes were reported during the first wave of the COVID-19 pandemic. There is a paucity of data on the longer-term effect of the pandemic on stroke volumes over the course of a year and through the second wave of the pandemic. We sought to measure the effect of the COVID-19 pandemic on the volumes of stroke admissions, intracranial hemorrhage (ICH), IVT, and mechanical thrombectomy over a 1-year period at the onset of the pandemic (March 1, 2020, to February 28, 2021) compared with the immediately preceding year (March 1, 2019, to February 29, 2020)., Methods: We conducted a longitudinal retrospective study across 6 continents, 56 countries, and 275 stroke centers. We collected volume data for COVID-19 admissions and 4 stroke metrics: ischemic stroke admissions, ICH admissions, IVT treatments, and mechanical thrombectomy procedures. Diagnoses were identified by their ICD-10 codes or classifications in stroke databases., Results: There were 148,895 stroke admissions in the 1 year immediately before compared with 138,453 admissions during the 1-year pandemic, representing a 7% decline (95% CI [95% CI 7.1–6.9]; p < 0.0001). ICH volumes declined from 29,585 to 28,156 (4.8% [5.1–4.6]; p < 0.0001) and IVT volume from 24,584 to 23,077 (6.1% [6.4–5.8]; p < 0.0001). Larger declines were observed at high-volume compared with low-volume centers (all p < 0.0001). There was no significant change in mechanical thrombectomy volumes (0.7% [0.6–0.9]; p = 0.49). Stroke was diagnosed in 1.3% [1.31–1.38] of 406,792 COVID-19 hospitalizations. SARS-CoV-2 infection was present in 2.9% ([2.82–2.97], 5,656/195,539) of all stroke hospitalizations., Discussion: There was a global decline and shift to lower-volume centers of stroke admission volumes, ICH volumes, and IVT volumes during the 1st year of the COVID-19 pandemic compared with the prior year. Mechanical thrombectomy volumes were preserved. These results suggest preservation in the stroke care of higher severity of disease through the first pandemic year., Trial Registration Information: This study is registered under NCT04934020.

Published
2023

50. Inactive Matrix Gla Protein in Relation to Renal and Cardiac Functions and Cardiac Valvular Calcification Among Type 2 Diabetes Patients.

Author

Reda, Sara, Fawzy, Olfat, Sayed, Doaa, Mohamed, Ghada, and Khidr, Emad Gamil

Abstract

Background: Matrix Gla protein (MGP) is a robust innate suppressor of the detrimental process of vascular calcification in the human body. Objectives: The interrelationship between circulating MGP levels and renal and cardiac dysfunction, besides echocardiographic calcification score (ECS) was investigated in a sample of type 2 diabetes (T2D) patients. Methods: The study included 130 subjects. They were 95 patients with T2D and 35 age- and sex-matched healthy controls. Patients were further subdivided into 52 T2D patients without DKD (eGFR ⩾ 60 ml/minute/1.73 m²) and 43 T2D persons with DKD (eGFR > 60 ml/minute/1.73 m²). Serum MGP levels, determined by ELISA, renal function tests, lipid profile, and echocardiography were studied in all participants. Results: Significantly elevated circulating inactive MGP level was noted in individuals having T2D compared to controls. It correlated negatively with eGFR and left ventricular (LV) diastolic and systolic functions and positively with indices of LV hypertrophy. ECS was significantly increased in both T2D groups compared to controls and in DKD group compared to the diabetic group without DKD. A significant positive correlation was observed between inactive MGP and ECS. Conclusion: Serum inactive MGP may contribute to the development of DKD and to the associated process of cardiac valvular calcification. It may be a beneficial diagnostic marker for early prediction of cardiac calcification and preclinical LV systolic and diastolic dysfunction in T2D patients, especially in those complicated with DKD. [ABSTRACT FROM AUTHOR]

Published
2023
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