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Somatic multicomorbidity and disability in patients with psychiatric disorders in comparison to the general population: a quasi-epidemiological investigation in 54,826 subjects from 40 countries (COMET-G study)
- Konstantinos N. Fountoulakis, Grigorios N. Karakatsoulis, Seri Abraham, Kristina Adorjan, Helal Uddin Ahmed, Renato D. Alarcón, Kiyomi Arai, Sani Salihu Auwal, Michael Berk, Sarah Bjedov, Julio Bobes, Teresa Bobes-Bascaran, Julie Bourgin-Duchesnay, Cristina Ana Bredicean, Laurynas Bukelskis, Akaki Burkadze, Indira Indiana Cabrera Abud, Ruby Castilla-Puentes, Marcelo Cetkovich, Hector Colon-Rivera, Ricardo Corral, Carla Cortez-Vergara, Piirika Crepin, Domenico De Berardis, Sergio Zamora Delgado, David De Lucena, Avinash De Sousa, Ramona Di Stefano, Seetal Dodd, Livia Priyanka Elek, Anna Elissa, Berta Erdelyi-Hamza, Gamze Erzin, Martin J. Etchevers, Peter Falkai, Adriana Farcas, Ilya Fedotov, Viktoriia Filatova, Nikolaos K. Fountoulakis, Iryna Frankova, Francesco Franza, Pedro Frias, Tatiana Galako, Cristian J. Garay, Leticia Garcia-Álvarez, Maria Paz García-Portilla, Xenia Gonda, Tomasz M. Gondek, Daniela Morera González, Hilary Gould, Paolo Grandinetti, Arturo Grau, Violeta Groudeva, Michal Hagin, Takayuki Harada, Tasdik M. Hasan, Nurul Azreen Hashim, Jan Hilbig, Sahadat Hossain, Rossitza Iakimova, Mona Ibrahim, Felicia Iftene, Yulia Ignatenko, Matias Irarrazaval, Zaliha Ismail, Jamila Ismayilova, Asaf Jakobs, Miro Jakovljević, Nenad Jakšić, Afzal Javed, Helin Yilmaz Kafali, Sagar Karia, Olga Kazakova, Doaa Khalifa, Olena Khaustova, Steve Koh, Svetlana Kopishinskaia, Korneliia Kosenko, Sotirios A. Koupidis, Illes Kovacs, Barbara Kulig, Alisha Lalljee, Justine Liewig, Abdul Majid, Evgeniia Malashonkova, Khamelia Malik, Najma Iqbal Malik, Gulay Mammadzada, Bilvesh Mandalia, Donatella Marazziti, Darko Marčinko, Stephanie Martinez, Eimantas Matiekus, Gabriela Mejia, Roha Saeed Memon, Xarah Elenne Meza Martínez, Dalia Mickevičiūtė, Roumen Milev, Muftau Mohammed, Alejandro Molina-López, Petr Morozov, Nuru Suleiman Muhammad, Filip Mustač, Mika S. Naor, Amira Nassieb, Alvydas Navickas, Tarek Okasha, Milena Pandova, Anca-Livia Panfil, Liliya Panteleeva, Ion Papava, Mikaella E. Patsali, Alexey Pavlichenko, Bojana Pejuskovic, Mariana Pinto Da Costa, Mikhail Popkov, Dina Popovic, Nor Jannah Nasution Raduan, Francisca Vargas Ramírez, Elmars Rancans, Salmi Razali, Federico Rebok, Anna Rewekant, Elena Ninoska Reyes Flores, María Teresa Rivera-Encinas, Pilar Saiz, Manuel Sánchez de Carmona, David Saucedo Martínez, Jo Anne Saw, Görkem Saygili, Patricia Schneidereit, Bhumika Shah, Tomohiro Shirasaka, Ketevan Silagadze, Satti Sitanggang, Oleg Skugarevsky, Anna Spikina, Sridevi Sira Mahalingappa, Maria Stoyanova, Anna Szczegielniak, Simona Claudia Tamasan, Giuseppe Tavormina, Maurilio Giuseppe Maria Tavormina, Pavlos N. Theodorakis, Mauricio Tohen, Eva Maria Tsapakis, Dina Tukhvatullina, Irfan Ullah, Ratnaraj Vaidya, Johann M. Vega-Dienstmaier, Jelena Vrublevska, Olivera Vukovic, Olga Vysotska, Natalia Widiasih, Anna Yashikhina, Panagiotis E. Prezerakos, Daria Smirnova
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- Journal:
- CNS Spectrums / Volume 29 / Issue 2 / April 2024
- Published online by Cambridge University Press:
- 25 January 2024, pp. 126-149
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Background
The prevalence of medical illnesses is high among patients with psychiatric disorders. The current study aimed to investigate multi-comorbidity in patients with psychiatric disorders in comparison to the general population. Secondary aims were to investigate factors associated with metabolic syndrome and treatment appropriateness of mental disorders.
MethodsThe sample included 54,826 subjects (64.73% females; 34.15% males; 1.11% nonbinary gender) from 40 countries (COMET-G study). The analysis was based on the registration of previous history that could serve as a fair approximation for the lifetime prevalence of various medical conditions.
ResultsAbout 24.5% reported a history of somatic and 26.14% of mental disorders. Mental disorders were by far the most prevalent group of medical conditions. Comorbidity of any somatic with any mental disorder was reported by 8.21%. One-third to almost two-thirds of somatic patients were also suffering from a mental disorder depending on the severity and multicomorbidity. Bipolar and psychotic patients and to a lesser extent depressives, manifested an earlier (15–20 years) manifestation of somatic multicomorbidity, severe disability, and probably earlier death. The overwhelming majority of patients with mental disorders were not receiving treatment or were being treated in a way that was not recommended. Antipsychotics and antidepressants were not related to the development of metabolic syndrome.
ConclusionsThe finding that one-third to almost two-thirds of somatic patients also suffered from a mental disorder strongly suggests that psychiatry is the field with the most trans-specialty and interdisciplinary value and application points to the importance of teaching psychiatry and mental health in medical schools and also to the need for more technocratically oriented training of psychiatric residents.
Cognitive null steering in frequency diverse array radars
- Sarah Saeed, Ijaz Mansoor Qureshi, Abdul Basit, Ayesha Salman, Waseem Khan
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- Journal:
- International Journal of Microwave and Wireless Technologies / Volume 9 / Issue 1 / February 2017
- Published online by Cambridge University Press:
- 29 July 2015, pp. 25-33
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Null steering has been a challenge in radar communications for the past few decades. In this paper, a novel cognitive null steering technique in frequency diverse array radars using frequency offset selection is presented. The proposed system is a complete implementable framework that provides precise and deep null placement in the range and angle locations of the interference source. The proposed system is cognitive such that the transmitter and receiver are connected via a feedback loop. System extracts interference source location parameters from the radar scene using Multiple Signal Classification, a super resolution direction of arrival estimation technique. Neural networks known for minimum computation time, and good non-linear and non-parametric approximation have been utilized for prediction of next location of the interference source. Simulation results validate the proposed frequency offset selection by demonstrating precise and deep nulls at the desired locations.